Part of the population considers themselves as sensitive to the man-made electromagnetic radiation (EMF) emitted by powerlines, electric wiring, electric home appliance and the wireless communication devices and networks. Sensitivity is characterized by a broad variety of non-specific symptoms that the sensitive people claim to experience when exposed to EMF. While the experienced symptoms are currently considered as a real life impairment, the factor causing these symptoms remains unclear. So far, scientists were unable to find causality link between symptoms experienced by sensitive persons and the exposures to EMF. However, as presented in this review, the executed to-date scientific studies, examining sensitivity to EMF, are of poor quality to find the link between EMF exposures and sensitivity symptoms of some people. It is logical to consider that the sensitivity to EMF exists but the scientific methodology used to find it is of insufficient quality. It is time to drop out psychology driven provocation studies that ask about feelings-based non-specific symptoms experienced by volunteers under EMF exposure. Such research approach produces only subjective and therefore highly unreliable data that is insufficient to prove, or to disprove, causality link between EHS and EMF. There is a need for a new direction in studying sensitivity to EMF. The basis for it is the notion of a commonly known phenomenon of individual sensitivity, where individuals’ responses to EMF depend on the genetic and epigenetic properties of the individual. It is proposed here that new studies, combining provocation approach, where volunteers are exposed to EMF, and high-throughput technologies of transcriptomics and proteomics are used to generate objective data, detecting molecular level biochemical responses of human body to EMF.
Phenomenon of sensitivity to electromagnetic radiation, like radiation emitted by e.g. electric wiring, electric appliances, power lines, wireless communication devices and networks, is commonly, and historically, known as electromagnetic (hyper)-sensitivity (EHS) or, with its newer scientific term, idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF) . Persons claiming to be EHS are commonly more concerned with the exposures to radiation emitted by base stations and Wi-Fi devices because the radiation exposure is involuntary, not possible to regulate by the unwillingly exposed person and it is continuous in the environment, lasting 24/7. Exposures of the EHS persons to cell phone handsets are often, mistakenly, of lesser concern to EHS persons because the user can decide how and when the radiation-emitting phone handset is used. The scientifically correct argument that the majority of radiation exposure received by the people comes from the phone handset  is often mistakenly overlooked. Scientific research of EHS consists of three types of studies:
Survey studies, where examined persons are not exposed experimentally to EMF. Surveys examine the prevalence of the self-diagnosed EHS persons in the whole population and attempts to determine whether there is any link between EHS symptoms and the environmental or personal exposures to various sources of EMF.
Provocation studies, where the self-diagnosed EHS or control volunteers are experimentally exposed to a single particular type of EMF, at well-known and monitored quantity. During or soon after the end of exposure the study subjects are being asked whether they feel any of the EHS symptoms to be induced during experimental exposure or sham exposure and whether they are able to recognize when the radiation source is emitting EMF and when it is not.
Biochemical and physiological studies, are looking for biochemical markers of EHS that are expressed in self-diagnosed EHS persons. The markers, selected for examination, are known to be likely associated with the symptoms in self-diagnosed EHS persons. Currently, in the biochemical studies, the examined self-diagnosed EHS persons are not exposed experimentally to EMF but they provide scientists with detailed information on what kind of EMF sources they believe cause their symptoms and what kind of physiological symptoms. Researchers in such studies attempt to determine whether any particular biochemical marker is expressed more or less prominently in the self-diagnosed EHS persons.
The above listed three types of studies have one overarching problem that is not addressed at all in EHS research. It is that the researchers analyze solely effects of exposures to EMF and do not address simultaneously occurring in real life exposures to other environmental pollutants, e.g. chemicals, particulate matter, radiations other than EMF. These environmental pollutants might act in concert with the EMF exposures what might lead in some cases to additive or even synergistic effects.
This review summarizes results of the to-date performed research on EHS, critically analyzes the obtained data and suggests the future directions for research.
The following terms used in searches: electromagnetic (hyper)-sensitivity (EHS), idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF), provocation studies, ELF-EMF, RF-EMF.
Only peer-reviewed original experimental studies published in the English language until March, 2021 were considered.
The first approach, to find the prevalence of EHS, was to perform questionnaire surveys of the population. This approach has some major problems. The first one is that not all persons approached by scientists with questionnaire about health and EMF exposures, respond and return the questionnaire. Thus, even if scientists selected the most representative subset of population the results will be skewed because only the persons most interested in the research topic will respond to scientists’ inquiries. Those with less interest or those not affected personally by EMF exposures might not respond, simply because of the lack of interest or lack of time. This, in turn skews results as the final population sample may significantly differ from the originally selected representative group, and EHS persons might be overrepresented in the examined population. Any estimates of EHS prevalence or potential impact of EMF on the prevalence of EHS become less representative of the population.
Another problem of surveys is that this approach was doable in the past. Currently it is more difficult to perform because of the omnipresence of devices emitting man-made ELF-EMF and RF-EMF in the living environment. The omnipresence of the EMF-emitting devices causes the difficulty to find a suitable control populations that could be compared with the exposed populations and with the self-diagnosed EHS sub-populations.
When reviewing survey studies, it is necessary to keep in mind that all survey studies claiming to examine prevalence of EHS in response to a certain type of EMF exposure are misleading because of the ubiquity of ELF and RF exposures in living environment. All persons examined in surveys are exposed to the particular EMF examined in survey but, also, exposed to a multitude of other EMF sources that might, or might not, have synergistic or additive effect on EHS symptoms.
ELF-EMF survey studies on general population and on EHS persons
Table 1 (see supplementary materials) presents ELF-EMF survey studies , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,  published from 1985 till the present. Studies published in 1980s examined the effects of exposures to visual display terminals (VDT) and complaints of the VDT operators of e.g. headache, vision problems muscular discomfort or skin rashes. Several of the VDT studies found no excess of symptoms in VDT operators group vs. controls [26, 30, 32, 33], but other VDT studies found some correlation between the occupational-time spent in front of VDT and number of health complaints [29, 34]. There were also studies that have found differences in the occurrence of skin symptoms in VDT operators but, according to the study authors, these differences were related not to VDT-emitted radiation but rather to psychological differences between persons [24, 25, 27]. Overall, it remained unclear whether any of the health complaints of the VDT operators were due to the VDT-emitted radiation or whether the health problems were caused by the long work hours in ergonomically inconvenient positions.
One of the VDT studies has examined a hypothesis that antioxidants (vitamins C and E and selenium) could alleviate symptoms of EHS in persons occupationally exposed to VDT . Study has examined not only subjective self-reported symptoms but also objective, serum levels of uric acid and diphenylpycrylhydrazyl. Serum levels of these two biochemical markers did not show correlation with the self-reported EHS symptoms. The study concluded that the antioxidant therapy had no alleviating impact on the EHS symptoms.
Several studies examined, cancer-unrelated, effects of exposures to residential powerlines [28, 31] as well as occupational exposures of persons working at electrical power plants and transmission stations [3, 7, 8, 23, 28].
The study of 120 households in close proximity to powerlines and 120 control households were examined with questionnaire on symptoms like headache, migraine, depression and number of sick leave days and the distance from the powerline. The authors found that the health problems were more frequent in those living close to powerlines. However, the authors did not have any other objective measure except for the number of sick leave days .
Study of 152 women living in close proximity to electric transmission lines examined impact of the proximity to electric transmission line on the general health problems and on the worry associated with the proximity. It appears that the split between worried and not worried persons was 45–55%, respectively. Among the persons living farther from the electric transmission lines the prevalence of health problems was lower than in persons living in close proximity. However, as authors stated, there were several limiting factors that lessen the value of this study, such as recall bias, social desirability or the not examined at all hypochondriasis .
Studies of the occupational exposures of persons working in power plants or power transmission facilities used questionnaires asking for the number of the subjective self-reported symptoms like sleep problems, stress, depression, anxiety and general health. Study of 287 workers of electrical power transmission and distribution stations demonstrated no significant correlation between ELF exposures and health . A small study of 40 workers of power substation in Iran has shown that, compared with control workers not exposed to ELF, the exposed workers had more problems with sleep and with general health . The study of 854 workers of power plant in China has shown that occupational exposure to EMF was correlated with poor sleep quality and duration. However, there was no association with the overall duration of the occupational exposure or with the use of mobile phone . Another study of 275 power plant workers has suggested that long-term occupational exposure to ELF MF may lead to depression, anxiety and poor sleep quality .
A French study has examined effects of occupational exposure to EMF generated by transformers  on the blood and blood cells’ properties. The study found that occupational exposure for 8 h daily for 1–5 years to 50 Hz radiation has led to a decline in blood lymphocytes in general and to a specific decline of subsets of lymphocytes CD4, CD3 and CD2 with the concomitant increase in the number of NK cells. It also appeared that physiological changes were reversed when the exposure was terminated and re-appeared after the re-exposure. Unfortunately, the size of this study (13 exposed + 13 controls) is too small to draw any more generalized conclusions.
A number of studies used questionnaires to examine residential and personal exposures to multitude types of EMF (ELF and RF) that are present in nowadays human environment [4, 5, 9], , [11, 13], , , , . Overall, as expected, the self-diagnosed EHS persons had significantly more health and quality of life complaints than the non-EHS persons. There was a tendency that women had more frequently the self-diagnosed EHS and more of the EHS associated non-specific health symptoms. The lack of objective metrics for EHS and relying solely on the subjective self-diagnosis of EHS made it problematic to correlate EHS symptoms with EMF exposures.
Two potentially meaningful, EHS survey studies were performed in Taiwan. Data collection for both of the studies was separated by the 5 years’ time period. The first Taiwanese study, published in 2011 , has determined the prevalence of EHS in Taiwan to be 13.3%. The study performed 5 years later and published in 2018  has shown a decline in EHS prevalence to 4.6% of the examined population. The study subjects of the research published in 2011 were only men whereas the study subjects of the research published in 2018 were both, men and women. Therefore, because the populations examined in both Taiwanese studies were this much different, the final result of the decline of EHS in Taiwan population from 13.3 to 4.6% is uncertain as it might have been caused by the differences between examined populations.
Overall, EHS surveys had relatively small sample size what diminished their scientific value. The exceptionally large group of examined subjects consisted of 10,605 persons . Only few surveys had several thousands of participants [4, 5, 9, 14, 16, 19, 30], and the majority of studies had only few tens to few hundreds of participants.
The majority of the studied endpoints were non-specific and subjective symptoms, in some studies the list of symptoms was long, listing 43  or even 68  symptoms examined by a questionnaire. However, no matter how long was the list of non-specific symptoms, the problem was that these symptoms were subject to personal feelings and thinking of the study subjects. Thus, results of such EHS survey studies are difficult to judge and compare because the data in every study comes from different population and is subjective, not objective. The data might be subject to the particular set of participants, especially in the small studies, what might affect the conclusions of the study. Reliability of such studies is difficult to assess when the data, provided either directly by the study subjects or collected by the trained interviewing personnel, however, remains subjective and depending on the personal feelings and attitudes of the examined person at the time of examination.
Only two of the studies, listed in Table 1, have collected, besides the list of subjective non-specific symptoms, also physiological samples for biochemical evaluation [21, 23]. This is real problem because the vast majority of research on ELF effects on human physiology is not using objective measures of effects but is based nearly exclusively on subjective self-reported of health problems.
Unfortunately, there are also published studies that had a very small number of subjects what prevented reliable statistical analysis, even when there appeared to be some likelihood of correlation between ELF MF exposures and the non-specific symptoms [6, 8].
RF-EMF survey studies on general population
Table 2 (see supplementary materials) presents survey-type studies [4, 5, 9, 14, 16, 17, 36], , , , , , , , , , , , , , [50, 51], , , , , , , , , , , , , , , , , , , [70, 71], , , , , , , , , , , , , , , , , , , , , , , , , , [97, 102], , , , , , , , , , , , , , , , published from 1996 till the present, examining the possibility of causality link between RF-EMF exposures and the non-specific health symptoms experienced by the members of the general public. These survey studies have examined persons of different age, from 0 to over 80 years, but designations of children, adolescents and adults varied. In this review is used United Nations definition of age: children 0–10 years, adolescents 10–19 years and adults over 19 years.
One of the problems in evaluation of the data obtained in RF-EMF surveys is the long list of examined non-specific symptoms. These symptoms might be caused by a variety of stimuli and not solely the RF-EMF. The list of some over 70 symptoms, examined to a varying extent in the majority of the RF-EMF survey studies (alphabetical order):
allergy, arrhythmia, back pain, bloated feeling in abdomen, blurred vision, bodily pain, chest pain, compulsive/obsessive behaviour, concentration capacity, concentration difficulties, conduct problems, dementia, depressive symptoms, discomfort during calls, dizziness, dryness of the throat, ear symptoms, emotional disorders, emotional problems, emotional role functioning, fainting, fatigue, flushing, forgetfulness, general health perceptions, headaches, hearing difficulties, heart palpitations, hostility, hyperactivity, hypertension, inattention, interpersonal sensitivity, irritability, lack of energy, loss of appetite, memory problems, mental health, migraine, muscular pain, nausea, neck or shoulder symptoms, neck pain, nervousness, numbness in the heed or face, pain abdomen, palpitations, paranoid ideation, peer relationship problems, phobic anxiety, physical functioning, physical ill-being, prickling in the ear, pro-social behavior, psychosocial well-being, psychoticism, salivary problems, sensitivity towards sounds, shortness of breath, skin symptoms, sleep – insomnia, sleep adequacy, sleep disturbance, sleep latency, social role functioning, sweating, tight feeling in chest, tingling fingers, tinnitus, tiredness, tremor, visual disturbances, vitality, warming of the ear.
All the symptoms lack precise definitions and are prone to individual interpretation by the study subjects. This long list of symptoms, examined in different combinations in different studies, shows how unspecific the survey inquiries were and how very subjective is the data collected in the to-date executed research on the RF-EMF effects on healthy or self-diagnosed EHS persons.
Several cohort studies examined effects of RF-EMF exposures on health. Possibly the largest cohort study that examined risk of nervous disease among Danish mobile phone subscribers, was based on the data from the Danish Cohort . The study found small but significant increase in hospitalizations for migraine and vertigo and concluded that this finding should be further studied. The problem with the Danish Cohort studies on mobile phones is not only the lack of radiation exposure data but the use as a substitute the mobile phone subscription records. The RF-EMF exposure substitute data of Danish Cohort is of lesser quality than in the studies that used minutes of calling as a surrogate of radiation exposure [98, 99]. The COSMOS Cohort, has published to-date two studies based on the parts of the total cohort from Sweden and Finland. The Swedish/Finnish part of the COSMOS Cohort consisted of total 24,169 participants where 21,049 were from Sweden and 3,120 from Finland. The first study has examined headache, hearing problems and tinnitus  and the second study has examined sleep and sleep problems . Both studies reported lack of correlation between operator-recorded mobile phone use and end-points examined in the study. However, there might be some concerns about the reliability of the results of these published already COSMOS Cohort studies [36, 37] as well as the future publications from the COSMOS Cohort. The reason is the fact that of paramount importance for the correct evaluation of data is the correct data on exposure to RF-EMF. Unfortunately, while there is some progress in the quality of the exposure data in COSMOS cohort study, as compared with e.g. Danish cohort study  or INRERPHONE case-control study , this progress is still insufficient to assure the reliability of the final conclusions because none of the used surrogates of radiation exposure is of satisfactory quality. INTERPHONE study used as surrogate of RF-EMF exposure minutes of calling, provided by the cases and controls from their own memory. This of course caused possible recall bias and especially the persons who developed brain cancer might have been recalling higher phone use than it was in reality. To avoid the recall bias, COSMOS cohort relies on the calling information from the network operators who provide the minutes of phone use by cohort participants. This removes some of the recall bias present in the INTREPHONE study . However, it does not improve much the reliability of data analysis. In both, INTERPHONE and COSMOS, the surrogate of radiation exposure are minutes of calling by the participants. This information is insufficient to estimate the real radiation exposure of person. Mobile phones are designed to emit radiation depending on how far or how close the phone is to the nearest base station. Mobile phone being in close proximity to base station emits less radiation than the mobile phone being far away from base station (Figure 1). This means that two persons using mobile phone for the same length of time will be exposed to different doses of radiation, depending on their proximity to the base station. This means that in both, INTERPHONE and COSMOS studies, persons exposed to different levels of radiation are placed in the same exposure group for the statistical analysis because they used mobile phone for the same number of minutes. This likely leads to an underestimation of the effects (dilution of the effects) of radiation exposure in INTERPHONE and COSMOS studies. A relatively in small size, prospective cohort study on 3,396 adult students from China has examined the effects of using mobile phone, for over 4 h per day, on sleep parameters . Conclusion of the study was that use of mobile phone for over 4 h per day caused sleep disturbance and that lessening the use of the mobile phone ameliorated the sleep problem. Another cohort study, the Dutch AMIGO cohort, was used to analyze whether perceived exposures to mobile phone RF-EMF, noise and air pollution have impact on appearance of non-specific symptoms. The cohort was sizable, 14,829 persons, and has shown that the perceived exposures were associated with higher scores on non-specific symptoms . A South Korean study examined the correlation between the length of mobile phone calls (in minutes, self-reported) and occurrence of non-specific symptoms . Increase/decline in the average length of phone call correlated directly with an increase/decline in headaches in women. The length of the call had no impact on e.g. stress, sleep, cognition or depression. A very similar results were obtained in earlier study from the same research team in South Korea . Headache and related back pain was examined in small group (1,270) of persons that were part of the Dutch AMIGO cohort. It appeared that persons with perceived exposure to mobile phone base station, the perceived risk and health problems scored higher on the analysis of the non-specific symptoms caused by the base stations. It also appeared that female sex, young age and high education led to more concerns over the safety of base stations . The Dutch AMIGO cohort was also used to examine effects of mobile phone base station on variety of non-specific health symptoms. Interestingly, analysis of 222 follow-up participants has determined that an increase in exposure did not correlate with ill health. However, perceived higher exposure was associated with higher symptoms reporting, what suggests that the radiation emitted by the base station was not the cause of the symptoms .
Several studies examined distance-dependency, from the nearest mobile phone base station, on the non-specific health symptoms [55, 58, 63]. These studies have examined only a very small number of persons living in close proximity to mobile phone base stations. The obtained results suggested that the distance from the base station might correlate with the frequency of the non-specific health symptoms. However, there were significant differences in the distance from base station to the dwelling that appeared to correlate with lesser impact on health symptoms: over 50 m , over 300 m , over 1 km .
An interesting, but small, study of the impact of mobile phone use and exposure to mobile phone base stations was published from Poland . The obtained data suggested that exposures to base stations contributed to the occurrence of depression and that the conversations, using mobile phone, decreased the feeling of depression. This curious finding may suggest that the problem of depression and amelioration of it by talking on mobile phone is likely not caused by the radiation exposure.
Numbers of adult participants, in many survey studies examining effects of mobile phones and mobile phone base stations on induction of non-specific symptoms in healthy persons, were relatively small (below 1,000 persons) or very small (below 500 persons). These small group sizes, in combination with the broad array of non-specific symptoms, and the complete lack of real radiation exposure data makes it very difficult to draw reliable conclusions for the broader population [17, 40, 42, 44, 48, 52, 56, 58, 62], , [64, 66], , [68, 73, 75, 78, 79, 84, 85, 89, 95, 96, 102], , , , , , , , , , , [113, 116].
The insufficient number of the participants in the survey studies becomes apparent in the meta-analysis study where results of 17 research studies were pooled together . Combining survey participants from the 17 various studies led to analysis of total 1,174 cases, what means an average of only 69 cases per study , , , , , , , , , , , , , , , , . Such a small size of the studies practically precludes drawing reliable population-related conclusions of effects or lack of these. It is also uncertain whether combining statistically non-significant data from 17 studies into one meta-analysis, will achieve statistically more reliable outcome.
An interesting study was performed in India but, unfortunately because of the very small sample size (178 adult persons) it is difficult to assess the significance of the results . What is different from other studies is that usually persons that are selected for the studies are of good health. However, the study in India has selected persons with epilepsy and examined whether use of mobile phone will have effect on the frequency of seizures. Results indicated that over the one year of follow-up there was no significant impact of mobile phone use on the frequency of seizures. However, the usage of mobile phone by the persons with epilepsy was very low and this, not radiation exposures per se, might have contributed to the final result of no effect on seizure frequency. However, it is advisable that studies would use not only healthy volunteers but also persons with significant health problems. Such studies would provide evidence on whether the current safety limits protect users with health problems.
Children and adolescents were examined in several survey studies examining the effects of mobile phone and base stations emitted radiation [38, 46, 49, 53], , [55, 59], , [61, 65, 70], , [72, 77, 81, 83, 88, 94]. In general, these studies concluded that the various problems with sleep, behavior and learning correlate well with the years of use of mobile phone and with the daily length of mobile phone use but not necessarily with the exposure to RF-EMF radiation emitted by these devices.
There are also studies with unfulfilled expectations, possibly due to design or execution problems. Large study of 18,935 children, examined potential loss of hearing in small children, age up to 7 years, had inconclusive outcome due to, as stated by the authors, a variety of biases that were not accounted for . A South Korean study that examined correlation between the attention deficit-hyperactivity disorder (ADHD), mobile phone use and lead exposure was also inconclusive as it was not possible to determine whether the ADHD occurred due to mobile phone use or due to the concurrently happening lead exposure . Another inconclusive study in children came from Denmark, examined was correlation between mobile phone use and headache/migraine. Unfortunately, list of unexamined confounders, like watching TV, playing video games and use of computers, prevented scientists from making any reliable conclusions . A series of studies from Germany, has specifically pointed out that the RF-EMF exposures in their studies were below the ICNIRP guidelines and that the observed symptoms, like fatigue, rather occurred by chance and were not caused by the radiation exposures [81, 83, 88]. Study from Sweden  has found out that girls use much more DECT phones than boys and that the most frequent symptoms correlated with mobile phone use are asthmatic symptoms, difficulties in concentration and headaches. However, the results are of little use as this study was solely explorative in nature and, as stated by the authors, unaccounted for many bias and confounding. An important opinion was expressed in an Iranian study in children. The results indicated a correlation between mobile phone use and several non-specific symptoms like: headache, myalgia, palpitation, fatigue, tinnitus, concentration problems, attention problems and nervousness. However the authors wrote: “Imprecise definitions of the symptoms might have affected responses” . This lack of precise definitions for a number of non-specific symptoms is a larger problem because not only study subjects but also scientists might have collected data that is very subjective and prone to varying misinterpretations when there is lack of precise and commonly accepted definitions of what given symptom means and how it should be recognized. Of course, on top of the lack of precise definitions come problems with the measurments of the strength of the symptom. E.g. pain, that is a common part of the non-specific symptoms, has no method to measure it strength objectively. Every person is likely to have subjective and differing threshold for what they consider a strong or a weak pain.
RF-EMF survey studies of EHS persons
Table 3 (see supplementary materials) briefly presents survey studies [10, 11, 13, 15, 74, 135], , , , , , , , , , ,  examining causality link between RF-EMF exposures and non-specific symptoms in EHS persons. These studies attempted to find out what sources of RF-EMF (mobile phone, mobile phone base station, Wi-Fi), in what order of causality-importance and what type of symptoms, induce in persons claiming to be EHS. One of the problems with relating the symptoms with particular exposures is the fact that all study-participants lived in environments full of exposures to variety of man-made EMF sources. Singling out a particular radiation source, without detailed measurement of radiation from this and other sources, prevents making reliable conclusions on how the particular source of RF-EMF affects given EHS person. Another problem of exposures is that even when the radiation from a particular source is measured, still it is unknown how other concurrent EMF exposures affect, or not, the symptoms experienced by the study subjects, especially in subjects that are very EMF sensitive by own admission.
It has been known, and recently it has been confirmed by a research study  that the majority of RF-EMF exposure comes from the own mobile phone. Exposures from the mobile phone base stations and Wi-Fi are, in comparison, very small. Therefore, any studies on the effects of mobile phone base stations performed on study-subjects are likely to be biased or misinterpreted because of the concurrent exposures to mobile phones. While the scientists try to estimate levels of mobile phone base station’s radiation output, they collect data where mobile phone radiation has, to various degree in different persons, affected the occurrence of non-specific symptoms.
One of the problems experienced by EHS persons is not only lack of tools to diagnose EHS but also lack of understanding, from health professionals, of what EHS is. A Dutch study attempted to examine how many EHS persons end up looking for advice from health professionals . Study has shown that the majority of health professionals complain of being inadequately informed about EHS and, in general, on health effects of EMF. This might be one of the reasons why only a third of the occupational health professionals has ever been contacted by EHS sufferers.
Recently, has been published a new methodological approach to study responses of self-diagnosed EHS persons to RF-EMF exposures in regular daily life [137, 138]. EHS volunteers were equipped with exposimeter and electronic diaries. Exposimeters recorded, continuously, exposures to a broad spectrum of EMF in city environment and the occurrence of symptoms was recorded by EHS persons in electronic diary at the time of occurrence. This permitted to look for any time-correlation between exposure and symptoms. In the first very small study with 7 participants were found some correlations between perceived and occurred exposure and some correlations in respect of strength of the symptoms . In the second study with 57 participants there was no correlation, on the group level, between exposures and symptoms. Only in one particular participant the correlation between exposure and symptoms was found . This pilot approach might be the best way to proceed with evaluating correlation between symptoms and exposures. However, currently, the use of this method is limited by the size of the exposimeter (backpack-size) and by the cost of it. It would be very helpful if the rapid progress in miniaturization of the equipment could lead to speeding up of future studies where symptoms and exposures would be recorded concurrently and each EHS persons would be evaluated individually for his/her responses to specific exposures.
An interesting observation was made on differences between the self-diagnosed EHS persons recruited to experiments from the general population via Internet and recruited via Non-Governmental Organization . It appeared that the persons recruited by the NGO had much stronger EHS symptoms than persons recruited as sensitive through the Internet call. This difference might cause bias affecting results in studies where researchers used different ways to recruit EHS volunteers.
Study executed in Finland, with a long list of 68 examined symptoms, and population sample of 194 EHS volunteers, has found that before the onset of EHS the most common health complaint were allergies . However, after the onset of EHS the dominant health problems were nervous system related. The most of complaints were recorded for mobile phones and VDT. Avoidance of these devices provided the best help in alleviation of EHS symptoms. The other ways to alleviate symptoms were dietary change, nutritional supplements and exercise. Psychotherapy and medications were not helpful in alleviation of health symptoms. The possible bias towards the stronger health complaints was potentially caused by the sex composition of the participants, 37 men and 157 women, since women are known to more readily admit health problems than men.
Another study of self-diagnosed EHS persons came to the conclusion that in order to perform good quality study it is necessary to have a versatile interdisciplinary team of researchers . Scientists measured the exposures of volunteers in their homes and found that while the radiation levels were within the current safety standards, in some participants (8 of 25) some of the reported health symptoms correlated with EMF exposure. In order to perform EHS studies correctly, team of psychology and psychiatry experts supplemented with experts in dosimetry was required. Such composition of research teams is, unfortunately, not the case in the majority of the published EHS research.
Another problem, besides the often lack of interdisciplinary approach, is the small number of EHS persons examined in surveys. Studies listed in Table 3 had at most less than 100 self-diagnosed EHS volunteers what caused problems in achieving statistical significance admitted by many authors. The proposed recently approach of examining individual cases seems to be the best way to resolve the problem of the low number of volunteers willing to participate in research studies.
Provocation studies of EHS persons
Research using provocation studies is dominated by the psychology-related approach and psychology methods. In such studies volunteers, either healthy controls or persons with self-diagnosed EHS, are exposed in a controlled setting to a particular type of EMF and asked what kind of symptoms of EHS they felt during and shortly after the exposure and whether they can recognize when the EMF exposure is on and when it is off.
The majority of to-date research on EHS that forms the basis for the WHO and ICNIRP opinions on sensitivity to EMF, are the provocation studies. Reliability of these studies, similarly to survey studies, is hampered by the subjectivity of the data. Both, the surveys and the provocations, rely on what the study subjects/volunteers said to feel when exposed to EMF or to sham exposures. Pre-formed personal opinions on EHS and subjective feelings of study subjects about the EHS and about the research team performing the study might have a direct influence on the subjective responses given to the scientists. This is a serious subjective-data-reliability problem that is not sufficiently addressed when determining the existence and the prevalence of EHS.
For tens of years people were complaining about health symptoms they experience in response to EMF. First there were powerlines and electric wiring at home and at work, then came computer screens (VDU) and most recently came mobile phones, mobile phone base stations and Wi-Fi. As shown elegantly by Dieudonne , the symptoms of EHS appear before the subjects start questioning effects of EMF on their health. Dieudonne has listed 7 stages how persons, experiencing non-specific symptoms which source clinicians are unable to determine and are unable to treat, are arriving at self-diagnosis of EHS: (1) onset of symptoms; (2) failure to find a solution; (3) discovery of EHS; (4) gathering of information about EHS; (5) implicit appearance of conviction; (6) self-experimentation; (7) conscious acceptance of conviction that the experienced symptoms are EHS caused by EMF exposures .
ELF-EMF provocation studies
Table 4 (see supplementary materials) presents ELF-EMF provocation studies , , , , , , , , , , , , , , , , , , , , , , , , . The problem of this evidence are too small, for reliable statistics, groups of self-diagnosed EHS persons or healthy volunteers used as stand-alone experimental group or as controls for the EHS volunteers. The size of studies ranges from a single case study to studies of groups of slightly over 100 persons. Data obtained in studies with such small numbers of cases are insufficient for reliable statistical analysis. In some cases scientists themselves admitted that the low numbers affected sensitivity of the experiments .
As seen in Table 4, exposure conditions in all studies are very different in respect of devices providing exposure, the quality and quantity of exposure and the time-frame of exposure (length, continuous or on/off) as well as time-frame of post-exposure inquiries about symptoms and perceiving of the exposure. This large variability of experimental conditions makes direct comparisons between the studies as well as meta-analyses very difficult if not impossible statistically.
Examined endpoints were mostly subjective feelings and health symptoms self-described by the volunteers. Only very few studies included in their evaluations also objective measures of the effects as, e.g. EKG or EEG, histopathology or biochemical markers. Both, objective and subjective endpoints appeared to have mostly no correlation with ELF exposures. Also, one result appears to be common for all studies. The subjects, no matter whether self-diagnosed EHS or healthy controls, were not able to recognize when the exposure was on and when it was off.
However, even though the ELF provocation studies showed largely no correlation between the examined battery of symptoms and ELF exposures, it might be that the studies were in some ways insufficiently sensitive and accurate to detect effects of ELF exposure. It is possible that when examining group of cases the statistical analysis shows overall no effect but some of the individual cases might in fact respond to ELF. Some of the case-studies have shown a possibility that some persons might respond to ELF exposure.
A single case study executed in USA by the team of Andrew A. Marino  observed effect of 60 Hz electric field on self-diagnosed female physician. In a double-blind study, subject experienced temporal pain, headache, muscles’ twitching and skipped heartbeats. The symptoms were caused not by continuous exposure but by the field transitions (off–on, on–off). However, like in other provocation studies, the subject was not able to feel the ELF field consciously but only through the experienced symptoms.
However, not always the single cases, claiming to be affected by ELF exposures, are indeed affected in blinded experiment. In a single-case study in Sweden, a plumber complaining of severe EHS was examined in blinded provocation studies . The whole-body exposures to electromagnetic coil using random mix of sham, 34 µT or 100 µT did not cause any EHS symptoms or were not recognized when field was on or off. Interestingly and importantly, after the plumber was informed about the outcome of the experiment, he was able to return to his work. The author suggested that this kind of examinations might help some EHS persons to understand that sometimes EMF exposures might not be the cause of their particular health problem.
In a case study, performed on two persons complaining of skin-related effects from occupational exposures to video terminal unit (VDU), scientists examined the presence of the mast cells in skin biopsies . It was possible to correlate the disappearance of the somatostatin positive mast cells with the end of exposure to VDU. The authors concluded that it is likely that the decline in the number of mast cells in skin biopsies is due to the disappearance of the somatostatin positive mast cells. This might explain the lessening of the clinical skin symptoms such as itch, pain, edema and erythema upon termination of exposure to VDU. It appears that in these particular two EHS cases it was possible to correlate the VDU exposure with the objective data from the histological and physiological examination of the skin.
However, a double blind provocation VDU study on 12 EHS persons and 12 matching controls has shown lack of effect on mast cells and inflammatory mediators . Blood samples were analyzed for number of stress bio-markers like melatonin, prolactin, adrenocorticotrophic hormone, neuropeptide Y, and growth hormone, and the expression of different peptides, cellular markers, and cytokines (somatostatin, CD1, factor XIIIa, and tumor necrosis factor-alpha). Skin biopsies were also analyzed for the occurrence of mast cells. The outcome of the study was negative. Study subjects were not able to recognize when the exposure was on and when it was off. Also, there was no significant differences in examined bio-markers of stress. Similar lack of effect of ELF exposure on blood stress markers was observed in double blind provocation study on 17 EHS persons . Blood analysis for the presence of prolactin, cortisol, dehydro-epi-androsterone, and cholesterol levels has shown lack of any effect from the ELF exposure.
The opposing results obtained by the studies that examined the same marker of the stress – presence of mast cells in skin biopsies following exposure to VDU – suggest that the single case evaluations might be a better way to find sensitive persons. Analyses of larger groups of EHS persons might mask the presence of a single sensitive person within the group [163, 168, 170].
Some of the old and some of the newer studies that examined biochemical markers of stress have come to no-effect conclusions. A study of effects of VDT on stress markers in group of 36 women and one man (students) has observed lack of the effect of exposure on the levels of biochemical markers, 8-hydroxy-2-deoxyguanosine and chromogranin A. The study concluded that while the work with VDT leads to mental fatigue, it is not a health effect per se . The study on men working on powerlines lines has examined series of blood hormones, thyroid stimulating hormone, luteinizing hormone, follicle stimulating hormone, prolactin, cortisol, neopterin, testosterone, and found no effect of exposure .
One of the ELF provocation studies has examined impact of nocebo on the appearance and experiencing of EHS. Experiments performed on 40 university students have indicated that the psycho-social factors may play a dominant role in becoming an EHS person, through an enhanced risk perception and expectations, self-monitoring, somatization and somatosensory amplification .
Taken together, the majority of the ELF-EMF provocation studies have not found correlation between effects of exposures and the examined subjective endpoints. Examination of the objective endpoints, like various biomarkers of stress in blood samples, provided mixed evidence of the effects. It might be reasonable to continue research looking for single cases that clearly respond with subjective and objective endpoints. Analyses of groups of EHS, no matter how well set up, might miss the single cases in the “crowd” of non-responders.
RF-EMF provocation studies
Table 5 (see supplementary materials) presents a number of provocation studies where volunteers were exposed to RF-EMF at the levels of mobile phone or mobile phone base station, Wi-Fi or TETRA radio [122, 124], , , , , [129, 131, 132, 134, 150, 170, 172], , , , , , , , , , , , , , , , , , [190, 191], , , , , , , , , , , , , , , , , , , [210, 211], , , , , , , , , , , , , , , , , , , , . Additionally, in recent years, a number of studies have examined whether nocebo effect might be responsible for the onset of EHS symptoms.
Provocation studies examined causality link between RF-EMF exposure and symptoms of EHS by exposing volunteers to RF-EMF in controlled conditions. Radiation exposures lasted from few seconds or minutes to few hours and were, with a few exceptions, of the power level that was in compliance with the international safety guidelines. Study subjects were asked of their feelings and symptoms and whether they are able to determine when the radiation is on and when it is off. The majority of such provocation studies have not found causality link between symptoms of EHS and exposures to RF-EMF. Also, commonly, the study subjects were unable to correctly recognize when the radiation exposure is on and when it is off.
The majority of the provocation studies were performed in research laboratory. However, some of the studies attempted to improve radiation exposure conditions by performing experiments in subjects’ home setting. Only a few studies have measured biochemical endpoints to provide objective experimental data.
Studies performed at home of the volunteers attempted to mimic as closely as possible real everyday exposures of the volunteers. Leitgeb and co-workers  performed study on 43 subjects, who were deeply convinced that RF-EMF exposures cause their sleep problems. Experiments were performed at homes of the study subjects under a real environmental conditions. The study did not found any EMF-dependent sleep disturbances and volunteer-specific analysis of data did not show any significant effects of exposure. Similar approach of exposing volunteers at home was used in recent Australian study, co-authored by an international team of EHS experts . The study was performed using only three subjects because of the recruitment problems. Severity of symptoms experienced by the study subjects was assessed with a visual analog scale. Additionally, study subjects were asked about the RF-EMF field perception. Obtained data did not show significant difference between exposure and sham conditions. Volunteers were also unable to correctly recognize when the exposure was on and when it was off. Furthermore, the belief that exposure was on has correlated with the severity of symptom scoring on analog scale.
The same Australian team attempted to elucidate the mechanism regulating alpha EEG activity in persons exposed to RF-EMF . Besides the measurement of EEG, researchers measured skin temperature in 8 different sites. Exposures were performed at SAR of 1 and 2 W/kg. In both exposure conditions there was a small increase in temperature of the finger’s skin. This made the researchers to propose that the RF-EMF exposure-induced change in EEG is a thermal effect. It also was suggested that this small thermal effect is ameliorated by the radiation safety guidelines that should protect against thermal effects of exposures. Unfortunately, this explanation might be premature. First of all, SAR levels that were used in experiments might cause small temperature increases of 0.1–0.3 °C. Thus, the small increase in temperature of the finger’s skin is not surprising. Safety guidelines protect from the thermal effects but it relates to much stronger increases of temperature by more than 1 °C. Australian team observed the increase of the temperature in the range of 0.1 °C, what means that this kind of small increase is not being alleviated by the current international safety guidelines.
On the other hand, the lack of effect of RF-EMF exposure on EEG was observed in study of healthy volunteers treated by a variety of exposure protocols at 1,800 MHz . The authors did not observe any effects on EEG and subjects did not report any remarkable sensations during the exposure. It was also concluded that there was no evidence for athermic (non-thermal) effects of the exposure.
Another study has examined changes in the skin temperature in response to EMF exposure to TETRA field . In this blinded study, using healthy volunteers, exposures at SAR of 1.5 W/kg had no effect on skin temperature. Exposures at high SAR of 6 W/kg have increased skin temperature by 0.8 °C, but this increase of the skin temperature was not recognized, felt, by the study subjects.
Only few studies had examined objective endpoints, of the response to RF-EMF, by measuring biochemical markers. Hillert and co-workers  have performed biochemical blood analysis and determined the values of erythrocyte sedimentation rate, white blood cell count, electrolytes, glucose, liver function enzymes, thyroid stimulating hormone, creatinine, cortisol, prolactin, and hemoglobin. There was no significant difference between exposed and non-exposed groups in examined biochemical markers. It was also observed that the belief that RF-EMF exposure was active led study subjects to experience skin symptoms. In another study , has been found difference, between the unexposed cases and controls, in the presence of such biochemical markers as substance P, TNF R1 and brain derived neurotrophic factor BDNF. However, exposure to RF-EMF had no effect on the examined biomarkers.
A case-study from Australia  has demonstrated that, if determined correctly, analysis of a single person-case might provide reliable evidence to support the existence of EHS. In this single case study, has been examined a 34 years old female journalist complaining of dysaesthesiae, an abnormal unpleasant sensation felt when touched skin, caused by damage to peripheral nerves. During experiment, the subject spoke on the phone wrapped in a thin layer of polystyrene, to avoid heating effects. The symptoms of dysaesthesiae appeared after ca. 7 min of the mobile phone use. The authors concluded that there might be neurological basis for some cases of the dysaesthesiae, and that dysaesthesiae in some of the cases might be associated with the use of mobile phone. The cause of the dysaesthesiae appeared to be non-thermal. The study by Hocking and Westerman  suggests that evaluation of groups of healthy or EHS volunteers might hide effects experienced by single cases within the group. Finding and examining such single cases, consistently responding to EMF exposures, might help in search for the proof of EHS existence and for the causality link between EHS and EMF exposures.
As the provocation studies were unable to find causality link between symptoms of EHS and exposures to EMF, scientists begun to look for other, radiation unrelated, explanations for the symptoms experienced by self-diagnosed EHS persons. A number of studies have examined possibility of a link between a nocebo and EHS symptoms [172, 174, 175, 178, 181, 192]. In such studies, healthy volunteers were shown either movies presenting dangers of EMF exposures or neutral films. Afterwards, when exposed to sham EMF, persons that saw film on dangers of EMF exposures have experienced more frequently non-specific symptoms, like these experienced by the self-diagnosed EHS persons. This outcome has been used as an argument that there is no link between EMF exposures and EHS symptoms but that the alarmist presentations in the news media may cause some people to develop non-specific symptoms of EHS.
Biochemical and physiological approach studies of EHS persons
With very few exceptions, the majority of research on EHS has examined a diverse variety of subjective endpoints, based on the feelings experienced by study subjects during or after exposure. Experimental data collected in such studies is likely biased because of the strong individual-dependent subjectivity of responses provided by each study subject. Relying solely on such subjective database of effects might lead to bias in evaluation of the results of the studies and cause dismissal of the EHS because the feelings-based data is too diverse and has too much of internal variability to provide statistically significant results.
In order to acquire objective data from the examination of the EHS subjects it is necessary to complement the feelings-based non-specific and subjective data with the objective data from examining biochemical changes in response to EMF exposures.
As shown in Tables 1–5, only a very few studies of EHS have examined biochemical markers [21, 23, 125, 163, 168, 170, 204, 213]. This data lacks systematic approach and, because of its scarcity, is still insufficient to provide scientifically reliable data on the biochemistry and physiology of EHS.
A study from Sweden has examined whether RF-EMF affects human blood-brain barrier and blood-cerebrospinal fluid barrier. As markers of leakage were measured blood levels of transthyretin and S100B protein . The obtained results were not statistically significant with the exception of the transthyretin sample analyzed 1 h after end of exposure. Overall, scientists were unable to explain whether the observation had any clinical or diagnostic significance.
Levels of salivary and urinary markers in 30 EHS and 25 controls were analyzed by Andrianome and co-workers . Quantified were cortisol in saliva and urine, alpha-amylase (sAA), immunoglobulin A and C Reactive Protein levels in saliva and neopterin in urine (uNeopterin). Only saliva alpha-amylase was found to be significantly higher (p<0.005) in the EHS group, what suggests that the sympathetic adrenal medullar system might be activated. Balakrishnan and co-workers  examined blood samples of heavy users of mobile phones and determined that the serum levels of C-reactive protein and Hsp70 as well as the gene expression of hsp70 were significantly increased as compared with controls. Dahmen and co-workers analyzed blood samples of EHS patients and found significantly lower TSH and higher alanine transaminase – and aspartate aminotransferase. Some EHS had also elevated levels of C-reactive protein. Authors concluded that EHS might not be a single disorder but rather a complex mixture of different etiology . Markova and co-workers have examined effects of mobile phone radiation, in vitro, on lymphocytes from EHS persons. RF-EMF appeared to affect chromatin conformation and 53BP1/gamma-H2AX foci in way similar to thermal shock. However, there was no difference in responses of leukocytes from control and EHS patients . The clinical and/or diagnostic significance of these biochemical observations remains still unknown.
The largest effort to determine biochemical changes in EHS persons was performed by the team of Belpomme and co-workers , , . However, the French team did not examine effects of EMF exposures per se because the study subjects were not exposed experimentally to EMF. Assumption that EMF, was the cause of the non-specific EHS symptoms, was based entirely on the self-diagnosis stories of the EHS persons, provided to the research team. The French team, using biochemistry/physiology approach, has claimed that not only EHS is proven to be caused by EMF exposures but they claimed to identify biochemical markers of EHS, that could be used in clinical diagnosis of the EHS.
The first experimental study by the French team was published in 2015 . The authors indicated that the collection of physiological samples and interviews with the self-diagnosed EHS persons begun in 2009. The cohort consisted of 1,216 persons of whom, for not explained reasons, only 727 were analyzed in this study. Remaining, the unanalyzed persons, were excluded by some not precisely described criteria, including unspecified pathologies discovered after their enrollment in the study. According to the authors, the cohort consisted of persons from different European countries (not specified in detail) as well as from the USA, Canada, Australia, Russia, China, Middle East and Africa. Selection of EHS persons for the study was claimed to be done in face-to-face interview, using a validated pre-established questionnaire. However, the questionnaire as well as its validation method were not presented in the article. French team has used several criteria to exclude/include cases for the research shown in Table 6, with some critical comments. Considering large geographical dispersion of the cohort, the authors did not explain how the biological samples were collected, stored and analyzed while preventing the potential degradation of the sensitive biological material. There is also lack of explanation whether the cohort members themselves approached scientists or whether they were, in a balanced way, pre-selected by the research team using some, unspecified in the article, criteria. The way of collecting the cohort is of importance. The authors claim that the females are more susceptible to develop EHS. As proof of this claim they stated that for this reason the cohort has more females than males (495 women vs. 232 men). The claim of the higher susceptibility of women, in this particular study, might be questionable because the higher number of participating women might be just a selection bias. It might be caused by the higher number of self-enrolling women to the cohort.
|French team’s criteria||Comment|
|Absence of known pathology accounting for the observed clinical symptoms||Potential cause of selection bias. Some diseases and ailments might predispose patients to be more, or less, sensitive to EMF exposures|
|Reproducibility of symptom occurrence under the influence of EMFs and/or multiple chemicals whatever their incriminated source||Claim of reproducibility of the symptoms, whenever the exposure happens, is based solely on the opinion of the volunteer. Subjective claim, not confirmed by the scientists|
|Regression or disappearance of symptoms in the case of EMF and/or multiple chemical avoidance||Claim of regression and of disappearance of symptoms is based solely on the opinion of the volunteer. Subjective claim, not confirmed by the scientists|
|Chronic evolution||Claim of the chronic evolution of symptoms in the presence of exposure is based solely on the opinion of volunteer. Subjective claim, not confirmed by the scientists|
|Symptoms such as headache, superficial and/or deep sensibility abnormalities, skin lesions, sympathetic nerve dysfunction, reduced cognitive ability including loss of immediate memory and attention and/or concentration deficiencies, insomnia, chronic fatigue and depressive tendency, all main clinical symptoms reported as non-specific symptoms in the scientific literature, but which when grouped together may evoke clinically the diagnosis of EHS (data not shown)||Variety of symptoms listed but without any data support. The scientists specifically mentioned that “data not shown”|
|No serious pre-existing pathology such as atherosclerosis, diabetes, cancer; and/or neurodegenerative or psychiatric diseases which have been associated with EHS and/or MCS in the past or at the inclusion time but would render difficult the interpretation of clinical symptoms and biomarker data (see Section “EHS/MCS as a possible sentinel pathological disorder”)||Potential selection bias. Some pathologies might predispose person for EHS. Such volunteers should be used in studies but analyzed separately from other EHS volunteers|
|For each patient written informed consent. Study of this large cohort of patients was not a case-control study neither a randomized study so there was no specific control group||Lack of controls leads to lack of baseline of the effects observed in EHS persons and makes the size of the observed effects unverifiable|
The working hypothesis of the French team was that environmental factors, such as EMFs and/or chemicals, induce neuro-inflammation and oxidative stress in the brain, leading to disruption of the blood-brain barrier (BBB). While there are experimental studies in animals , ,  and in vitro  suggesting that BBB might be affected by the EMF exposures, none of the studies has shown it to occur in humans. In agreement with the working hypothesis the health status of the participants was analyzed with battery of physiological tests for which there is lack of information to assure reliable quality of sample collection and analysis, especially in the context of the geographical spread of the cohort. Biochemical tests analyzed the following endpoints, thought to fit well the working hypothesis presented above: high-sensitivity C reactive protein (hs-CRP), Vitamin D2-D3, histamine, IgE, protein S100B, nitrotyrosine (NTT), heat shock protein 70 (HSP70), heat shock protein 27 (HSP27), Aati-O-myelin autoantibodies, hydroxy-melatonin sulfate (6-Ω), and 6-Ω/creatinine. In addition to the biochemical tests, the authors analyzed blood flow in the temporal lobes and determined the pulsometric index (PI) using a non-invasive method of ultrasonic tomosphygmography.
The changes in expression of the examined biochemical markers did not occur in the majority of the patients but only in a relatively small proportion of persons with self-diagnosed EHS, multiple chemical sensitivity (MCS), or persons with both ailments (EHS + MCS). The proportion of examined persons with the increased expression of the biochemical marker has been used by the authors to claim that the statistical significance of the change in examined markers is a possible clinical detection of EHS. For example, the authors presented claim that histamine is the key molecular marker of EHS. However, only 40% of self-diagnosed EHS persons had an increase of histamine level. None of the remaining stress factors was highly prevalent in EHS persons: hs-CRP increased in 15% of EHS, vitamin D2–D3 declined in 23.2% of EHS, histamine increased in 40% of EHS, IgE increased in 22% of EHS, protein S100B increased in 15.5% of EHS, nitrotyrosin (NTT) increased in 29% of EHS, Hsp27, Hsp70 detected in 7–19% of EHS, antibody to O-myelin detected in 17–29% of EHS, melatonin to creatinine ratio declined in EHS but the variation was too large to provide a specific number for the ratio, pulsatility declined in 50.5% of EHS, but data for the pulsatility were not shown by the authors in the published study. Furthermore, the authors did not specify whether there was any overlap in the changes of the expression of different markers and whether there was any EHS person that expressed majority or even all of the examined biochemical markers. Most importantly, there was not presented evidence that any of the markers was induced by EMF exposure or affected by EMF exposure
The French team concluded that EHS and MCS were both associated with the same abnormalities, based on the analyses of biochemical factors. Furthermore, the French team suggested that both pathologies, EHS and MCS, share a common pathophysiological mechanism. It might be so, but it remains unproven based on the provided evidence. It also might be that the groups of self-diagnosed EHS patients and self-diagnosed MCS patients are cross-contaminated because of the possible incorrect self-diagnoses. Thus the claim of common pathophysiological mechanism is uncertain, at the best, and it requires a better supportive evidence.
The French team has proposed pathophysiological model for the development of EHS (Table 7; with critical comments). However, without the evidence linking EMF exposures with the occurrence of non-specific symptoms and biochemical markers, claimed to be manifestations of EHS, this proposed model of mechanism remains unproven.
|Steps of the proposed mechanism of EHS||Comment|
|Under the influence of EMF, a cerebral hypoperfusion/hypoxia-related neuro-inflammation may occur||The authors did not demonstrate that EMF exposures lead to cerebral hypoperfusion or neuro-inflammation. This link is claimed only because of the self-diagnosis of EHS persons. If self-diagnosis is incorrect the whole mechanism collapses|
|Due to the release of histamine and other mediators the blood-brain barrier stability is disrupted and an increase in permeability may result from the oxidative and/or nitrosative stress||The authors did not examine impact on BBB. Only 40% of the self-diagnosed EHS had an increased blood level of histamine. The other 60% did not have increased histamine levels. Possibility that they might have local release of histamine is only speculation, not supported by the data|
|Circulating inflammatory cells could pass through BBB and enter the brain to initiate a vicious circle which may considerably amplify the neuro-inflammation process||No evidence presented|
|Because of oxidative and nitrosative stress and subsequent decreased melatonin bioavailability and autoimmune response, physiological defense mechanisms are weakened making EHS and/or MCS patients to be potentially at risk of developing chronic neurodegenerative diseases and cancer||No evidence presented|
The second experimental study from the French team was published in 2018 . In this study has been presented evidence to support the establishment of the diagnostic criteria for distinguishing the EHS persons from the non-EHS persons. The French team has examined the list of 23 symptoms that might distinguish an EHS from a non-EHS person. The data was presented solely as a percentage of persons having the examined EHS symptoms. For the majority of symptoms in non-EHS persons (14 out of 23) the percentage equaled 0%. For each symptom, the authors claimed the p-value was calculated. Unfortunately, from the presented data it was not possible to determine the reliability of the presented p-values, because the occurrence of symptoms was presented only as a single percentage number. For example, for the symptom of headache, the value for EHS persons was 88% but for non-EHS controls it was 0%, as if non-EHS persons would not suffer of headache at all. But, puzzlingly, the p-value presented for the headache is shown as highly statistically significant of p<0.0001, which claim is not verifiable due to the lack of data. The same goes for the claim that the pulsatility index of brain’s front lobes declines in EHS persons. French team did not present any evidence linking changes of pulsatility with past EMF exposures. The claim that anyone having a decline in pulsatility index suffers of EHS has not been proven.
In the diagnosis of EHS, French team has relied solely on the self-statements of the self-diagnosed EHS persons . Interestingly, the patients claimed to get symptoms of EHS during exposures to EMF and the symptoms subsided when avoiding exposures. Acceptance of this claim as such, without any objective evidence, would mean that the French team has found several hundreds of persons that are able to feel EMF exposures. However, French team did not present any experimental evidence that would validate this claim. Furthermore, this claim is in clear contradiction with the results of the majority of the psychologic provocation studies where EHS persons were unable to recognize active EMF exposure.
The third experimental study from the French team was published in 2018 . In this study, as the inclusion criteria for study subjects were the self-diagnosed EHS combined with the pulsatility index and with the four markers of the oxidative stress: plasma histamine, serum protein S100B, serum Hsp70 and serum Hsp27. The study subjects were not exposed to EMF but the causality link of EHS with EMF was based solely on the self-diagnosis of EHS. The study presented a very long speculation of how the oxidative stress may influence normal physiology. However, there was not presented any evidence that would demonstrate that the oxidative stress is caused in the self-diagnosed EHS persons by the past EMF exposures, or that the oxidative stress induced by exposures affects overall physiology of EHS persons. The same applies to the pulsatility index – it has not been shown that pulsatility index is in any way affected/connected to EMF exposures. It remains unknown what has caused the decline in the pulsatility index observed in the self-diagnosed EHS persons.
Recently published review article on use of the ultrasonic tomosphygmography in detection of EHS does not produce any evidence to back up claim that EHS is detectable by ultrasonic tomosphygmography detected changes in pulsatility of the brain’s front lobes . The author, of this review, solely refers to the opinions presented in articles of the French team , , , claiming that pulsatility and oxidative stress were proven to be markers of EHS. They were not.
In summary, research studies examining different biomarkers in EHS persons have the problem of the lack of evidence showing correlation between the EMF exposures and the biomarkers considered as the biomarkers of EHS. The selection of the study subjects has relied solely on the opinion presented by the self-diagnosed EHS person. The scientists do not have knowledge whether the self-diagnoses of EHS are correct or not. The scientists do not know whether the EHS group is contaminated by the incorrectly self-diagnosed EHS persons, and, if so, to what degree. As proposed by Dahmen and co-workers, EHS might not be a single disorder but rather a complex mixture of different etiology . Because of that, it is important to determine whether any of the examined biomarkers is in any way correlating with past or present EMF exposures. Without this knowledge, it might be very difficult to study EHS biomarkers when scientists examine simultaneously several different etiologies.
Does EHS exist?
Collectively, the to-date executed studies were unable to prove causal link between EHS and EMF exposures. However, there are several indicators suggesting that individual sensitivity to EMF might exist. There is a well-known, and scientifically well-established, phenomenon of the individual sensitivity . Individual sensitivity means that, because of the genetic and the epigenetic differences between people, different persons may have different sensitivity to the same agent, whether it is natural or man-made, radiation or chemical. The phenomenon of the individual sensitivity to radiation is well known for ionizing radiation [246, 247], for non-ionizing ultraviolet radiation [248, 249] and for ultrasound .
In respect of the EMF exposures, several studies have shown that individual differences might led to individual sensitivity to EMF. Epidemiological case-control study, Interphone, has shown that only some of the persons in the highest exposed to mobile phone radiation group have developed brain cancer. The recent study from the National Toxicology Program (NTP) in USA has shown that in the highest exposure group, where radiation dose received by animals (rats) was very high only few rats from this highly exposed group have developed cancer. There are also laboratory studies on in vitro exposed cells showing that different cell types may have different sensitivity to EMF exposures , , . Therefore, it is scientifically justified to suspect (assume) that the individual sensitivity maight also exist for the EMF exposures. However, the essential, but still unanswered questions are:
what are the levels of EMF that are tolerated without adverse health effects by the majority of the population and,
what are the physiological pre-conditions (e.g. health status) for the occurrence of the higher sensitivity to EMF and,
what counter-measures need to be considered to protect those more sensitive and vulnerable to EMF exposures.
Therefore, there is discrepancy between the probability of EHS existence and the outcomes of the EHS research studies. If the logical argument supporting existence of EHS is correct then there might be problems with the quality of the design of the EHS research studies.
Quality of the EHS research
As presented above, there are several common problems with the to-date executed EHS studies. These problems are:
the majority of research data is subjective and describes non-specific symptoms
lack of objective markers of EMF effects
low numbers of EHS volunteers participating in the studies what might cause selection bias
very large diversity of EMF exposure protocols
acquiring data, either during the exposure or soon afterwards, precludes look at the late or chronic effects.
In 2019 a review study analyzed methodological limitations of the to-date performed psychological provocation studies . It has presented an extensive list of 13 possible biases and errors in psychological provocation studies. However, some important potential biases were not considered by the authors of the review.
The list of bias presented in Schmiedchen and co-workers  was as follows:
Was the level of EMF exposure and method of blinding appropriate?
Were individuals excluded whose symptoms may be explained by somatic diseases or mental disorders?
Was the contrast in the severity of symptoms between situations with/without exposure verified?
Were EMF exposures (type of exposure source, frequency range and exposure level) applied that individuals associate with their symptoms?
Were exposure durations and assessment times applied that matched the time scales for the symptoms to appear?
Were the symptoms registered in the trials matched with those experienced in everyday exposure situations?
Was the background exposure level controlled and minimized?
Was the exposure level controlled?
Were the intervals between exposure sessions sufficiently long to allow for recovery and to avoid carry-over effects?
Were biases related to sequence and period of the exposure conditions minimized (for studies with cross-over design)?
Were biases related to confounders and cofactors minimized (for studies comparing parallel groups of IEI-EMF participants with different exposure conditions)?
Were biases minimized that are related to attrition and to incomplete data included in the analysis?
Was bias related to selective outcome reporting minimized?
Only 28 of the to-date published EHS psychological provocation studies was considered by the review authors to be of sufficient quality for the inclusion in the review. These 28 studies were considered to be methodically sound. As stated by the authors, these methodically sound studies indicated that an effect of exposure is unlikely. The authors speculated that, even if the physical effect exists, it must be either very weak or affects only small number of individuals.
This review  shows how very imperfect is the research on EHS because of the identified 845 studies only 28 were selected as of eligible quality, after fulfilling the 13 criteria. However, after all, these 28 studies that passed the 13 quality criteria were not of good quality as judged by the authors of the review:
Seven (25%) studies included in this review reported elevated or reduced symptom levels upon exposure to EMF, while the majority of the studies (n=21, 75%) did not find evidence for exposure-related effects in IEI-EMF individuals. Study outcomes, i.e., positive or negative results, were not restricted to specific types or frequency ranges of exposure.
It means that only 7 studies have shown either positive or negative effect. Such extremely limited evidence is insufficient to claim that EHS exists or that EHS does not exist. It is also far too little of the data to speculate about lack of restrictions towards any specific frequency ranges of exposure. The final recommendation of this review was that further experimental studies should be performed preferably at the individual level and not like it was mostly done till now, on group level where small effects might have remind hidden when examining larger group of EHS individuals together. This recommendations strengthens the notion that it is very likely that the groups of self-diagnosed EHS volunteers are contaminated, to the unknown degree, by the falsely self-diagnosed EHS persons that suffer of the non-specific symptoms that are caused by other than EMF exposures.
The major quality and reliability problems of the to-date performed EHS studies (surveys, provocations and biochemical studies) that were not included in the review by Schmiedchen and co-workers  is that the obtained experimental data is mostly subjective and not objective information.
Recent review of the hypotheses explaining occurrence of EHS has examined three types of hypotheses examined in studies of EHS :
The electromagnetic hypothesis – EMF exposures cause EHS, in particular, the non-thermal effects induced by EMF
The cognitive hypothesis – false assumption that EMF causes symptoms of EHS that assumption is potentiated by the nocebo effect
The attributive hypothesis – symptoms are being explained by EHS to cope with the symptoms of unknown and unexplainable origin
It was suggested that all three hypotheses might be correct and that several sub-groups of EHS sufferers might exist:
those that respond to EMF exposures from some of the EMF-emitting devices and have EMF-induced health problems
those that believe in harm caused by EMF devices and this belief causes their health symptoms
those that have health problem that medical doctors fail to identify its source and persons attribute it to EMF exposures to cope with the problem (avoidance of EMF).
However, no hypothesis could be considered satisfactory. All of the hypotheses and research studies performed to examine these hypotheses, rely solely on the self-diagnosis of EHS by the study subjects. Many, or even majority, of self-diagnoses might be false. This leads to contamination of the experimental group and to the dilution of the observed, if any, EHS effects.
Ledent and co-workers  have stated that the best suited for isolating effects of EMF are provocation studies but number of innovations should be included in protocols, such as: the involvement of people with EHS in the development of the protocol, the attenuation of the anxiogenic nature of the tests, the individualization of the protocol, the validation of the neutral or normal reactivity state before the test, and the use of a cocktail of real, rather than artificially generated, sources.
Unfortunately, the unlimited trust in provocation studies, as the best suited to find out an explanation for the cause(s) of EHS, is worrisome as it might lead to further delays in finding answers about the causes of EHS. The involvement of EHS persons in the process of developing improved exposure protocol, the co-development, is laudable but similar approach was tried in the past and with no advance in research outcomes.
However, no matter how the experiments were prepared, several major problems remain:
Did co-designing experiments, where researchers and EHS volunteers collaborated closely, in any meaningful way alleviated distrust of the volunteers?
Are the self-diagnoses of EHS correct when done in collaboration with research team?
Are the exposures sufficient enough to cause symptoms?
Are the lag-times after exposure long enough to allow development of delayed symptoms?
Responses provided by the volunteers remain subjective.
No objective way to assure that exposure protocol and symptoms have causality link.
There is a number of drawbacks in the design of all of the to-date executed EHS studies that were not mentioned but that will prevent making any far reaching conclusions on the existence and on the causes of the EHS. The drawbacks [as proposed by D. Leszczynski] are as follows:
Drawback #1: It is not known whether the volunteers are indeed suffering of EHS. This means that the experimental groups of self-diagnosed EHS persons might be contaminated by the misdiagnosed EHS persons. In extreme cases it might happen that none of the self-diagnosed EHS volunteers is indeed and EHS sufferer. They might experience non-specific symptoms caused by non-EMF environmental exposures.
Drawback #2: There are two types of selection bias in the to-date executed EHS studies. The first one is introduced by the scientists who exclude persons with any pre-existing health problems. Scientists do not know whether pre-existing health problems might pre-dispose a person to develop EHS. Exclusion of persons with pre-existing health problems is incorrect at this discovery stage. Persons with pre-existing health problems should be included, though they could/should be analyzed separately. The second selection bias is introduced by the volunteers who either fail to volunteer or who initially agree to participate in a study but later withdraw their consent because of either becoming afraid of potential health risk from exposures or because of the distrust in the scientific team.
Drawback #3: Psychological methods of inquiry, used in psychological provocation studies, were not examined and not proven for their suitability to detect EHS. Assuming that the EHS exists, none of the experimental methods of psychology, used in the to-date executed psychological provocation studies, has been demonstrated to be able to detect physiological outcomes of the EHS stemming from the exposures to EMF. Furthermore, all psychological provocation studies were designed to examine acute occurrences of EHS symptoms and might be unsuitable to detect delayed or chronic EHS symptoms.
Drawback #4: Conclusions of the provocation studies performed using psychology methods might be affected and/or even invalidated because of the existence of the placebo and nocebo phenomena. Placebo and nocebo indicate the ability of the human mind to affect physiology of human body [256, 257]. There is a well-known phenomenon among medical students of the “medical students’ disease”. It is a condition frequently reported in medical students, who perceive themselves to be experiencing the symptoms of a disease that they are currently studying. The condition is associated with the fear of contracting the disease in question. The same is likely happening when researchers show to study subjects’ films presenting dangers of EMF exposures. It is obvious and expected that some persons will afterwards “experience” some of the symptoms presented in the film. Furthermore, volunteers participating in such studies have pre-conceived opinions on EMF and health. Thus, claims that news media reports cause rise in the occurrence of EHS is incorrect. Also, the responses of the self-diagnosed EHS persons given during the provocation experiments are likely influenced by their pre-existing opinions about EHS. Thus, the data collected in the psychological provocation studies is not only un-objective but it is affected by the pre-existing opinions.
The way how EHS persons arrive at own self-diagnosis of EHS was elegantly presented by Dieudonné  and it is in agreement with the drawback #4 by D. Leszczynski. Claiming that the subjective data of the to-date executed provocation studies is scientifically reliable to diagnose EHS is incorrect. Subjective data from the psychological provocation studies does not prove, as some claim, that EHS is caused solely by a worry and not by EMF exposures. The above-listed drawbacks suggest/indicate that the scientific data obtained in the to-date executed survey studies, the psychological provocation studies and the biochemical EHS studies is unreliable and insufficient to prove, or to disprove, the existence of EHS.
The future of the research on EHS
The psychological approach of surveys and provocation studies has to be supplemented with physiological and biochemical measurements, examining the individual’s molecular level responses to EMF exposures . The future studies should have part of provocation study where individuals, not groups of individuals, would be examined with questions about what and when they feel in response to exposure. The other part of the same research should be the collection of samples for biochemical analysis of whether the exposure causes changes in expression of biochemical markers and whether it will be possible to find biochemical markers that will be universally altered by the exposures. The studies should have double-blind set up and both healthy and EHS persons should be analyzed together and only after the analysis is completed, the health status of volunteers should be revealed. Furthermore, the problem of the lag between the exposure and the appearance of symptoms is an important one but not easy to resolve. The supplementation of the subjective psychology data with the objective biochemistry data will help to establish whether the acute EHS responses take place. Once the acute EHS is established, a remedy to the lag problem might be considered. It will be likely very costly as it might require sequestering volunteers, for some period of time (days–weeks) in environmental isolation from environmental EMF exposures, to perform psychological inquiries and biochemical samplings at different times after exposure to examined EMF exposure.
The current diminished interest in studying EHS is fueled by the misconception that the provocation studies alone, using psychology approach and asking about feelings, were enough to prove that EHS is not caused by EMF exposures. This is absolutely incorrect. Only combination of provocation study with biochemical examination will resolve the EHS enigma. However, the idea of examining biochemistry of EMF exposed persons is being opposed by many researchers of bioelectromagnetics. Thus, for comparison, it is good to look elsewhere, where transcriptomics and proteomics approaches are being used to resolve and explain health problems.
Pain is one of the non-specific symptoms experienced, among others, by the EHS sufferers. Feeling of pain is very individual and there is no objective scale to measure pain. Pain is considered to be multidimensional and adaptive. Individual expectations, moods or attention affect how the pain is handled by the brain and how it is, in the end, felt by the individual. In some cases to relieve pain is necessary surgical or chemical intervention. However, many cases of pain is possible to relieve without surgery or drugs, just by psychological intervention [259, 260]. In understanding the pain, and in research towards controlling it, is important to know where from the pain comes. Chronic pain is classified into three categories, nociceptive pain caused by tissue damage, neuropathic pain caused by nerve damage and pain of unknown source, the idiopathic pain. For example stress and sleep problems disturb mechanisms that regulate feeling of pain. The positive expectation that a drug will help in relieving pain were shown to increase efficacy of the drug . Furthermore, MRI images have shown that different areas of the brain differently respond to the same drug when it is associated with positive or with negative expectations. If the source of the pain is unknown then the methods to alleviate this pain might fail. Chronic pain develops in some 20% of people experiencing pain. Women are more susceptible to develop chronic pain. Other factors that help to develop chronic pain are age, stressful experiences and prone to catastrophic-thinking nature of the patient.
Scientists are now looking for objective measurements of pain because all current methods of relieving pain are based on subjective information received from the patient. This is insufficient. The problem is that currently there are no methods to detect pain and strength of it from e.g. blood test. However, methods using biomarkers, genetics and epigenetics are considered to be of paramount importance in the future of developing objective tests for pain .
Patients’ subjective description of symptoms combined with the biomarker objective information is considered the future for developing pain control. The same approach should be taken to resolve the problem of sensitivity to exposures from EMF. Physiological studies of responses to EMF exposures will generate data useful for developing diagnostic tools for the detection of EMF sensitive persons and to, potentially, develop methods to mitigate the physiological effects of EMF exposures without the necessity of avoidance of EMF exposures. This biochemical approach has been shown to be able to experimentally generate data on EMF-exposure affected proteins or genes . In the coming era of 5G technology and the already being developed 6G technology, avoidance of EMF exposures will become virtually impossible for any person wishing to remain function and prosper in the society.
Problems and solutions for EHS research are summarized in Figure 2.
Over the last 30 years, a sizable number of research studies has examined causality link between EMF exposures and EHS symptoms.
The majority of the studies did not find any link between EMF and EHS.
The EHS studies have examined acute effects but did not have capability to examine delayed EMF responses.
The major problem is that scientists do not know whether EHS volunteers have indeed correct self-diagnosis of EHS or whether the diagnosis is incorrect and experimental groups are contaminated, to unknown degree, by non-EHS persons. In extreme situation, the small group of volunteers used in research study might have no EHS persons at all.
Recently, research on EHS has drifted into direction of nocebo as the cause of EHS, what is incorrect.
Instead of studying obvious impact of nocebo, or likes of medical students’ disease, research should focus on finding suitable biochemical and biophysical markers that could be used, in combination with single-individual-focused provocation studies, to determine the sources of the EHS symptoms.
The opinion that there is no causality link between EHS and EMF is unproven. This opinion, expressed by the World Health Organization EMF Project, the International Commission on Non-Ionizing Radiation Protection, International Committee on Electromagnetic Safety and numerous governmental organizations, should be revised because the scientific research data is of insufficient quality to be used as a proof of the lack of causality.
Research funding: The Finnish Electrosensitivity Foundation (Sähköherkkyyssäätiö), Helsinki, Finland.
Author contributions: Not applicable (single author).
Competing interests: Author declares no conflict of interest.
Ethical approval: Not applicable.
Informed consent: Not applicable.
1. Baliatsas, C, Van Kamp, I, Lebret, E, Rubin, GJ. Idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF): a systematic review of identifying criteria. BMC Publ Health 2012;12:643. https://doi.org/10.1186/1471-2458-12-643.Search in Google Scholar PubMed PubMed Central
2. van Wel, L, Liorni, I, Huss, A, Thielens, A, Wiart, J, Joseph, W, et al.. Radio-frequency electromagnetic field exposure and contribution of sources in the general population: an organ-specific integrative exposure assessment. J Expo Sci Environ Epidemiol 2021;31:999–1007. https://doi.org/10.1038/s41370-021-00287-8.Search in Google Scholar PubMed
3. Hosseinabadi, MB, Khanjani, N, Ebrahimi, MH, Haji, B, Abdolahfard, M. The effect of chronic exposure to extremely low-frequency electromagnetic fields on sleep quality, stress, depression and anxiety. Electromagn Biol Med 2019;38:96–101. https://doi.org/10.1080/15368378.2018.1545665.Search in Google Scholar PubMed
4. Huang, PC, Cheng, MT, Guo, HR. Representative survey on idiopathic environmental intolerance attributed to electromagnetic fields in Taiwan and comparison with the international literature. Environ Health 2018;17:5. https://doi.org/10.1186/s12940-018-0351-8.Search in Google Scholar PubMed PubMed Central
5. Baliatsas, C, Bolte, J, Yzermans, J, Kelfkens, G, Hooiveld, M, Lebret, E, et al.. Actual and perceived exposure to electromagnetic fields and non-specific physical symptoms: an epidemiological study based on self-reported data and electronic medical records. Int J Hyg Environ Health 2015;218:331–44. https://doi.org/10.1016/j.ijheh.2015.02.001.Search in Google Scholar PubMed
6. Bolte, JF, Baliatsas, C, Eikelboom, T, van Kamp, I. Everyday exposure to power frequency magnetic fields and associations with non-specific physical symptoms. Environ Pollut 2014;196:224–9.10.1016/j.envpol.2014.10.011Search in Google Scholar
7. Liu, H, Chen, G, Pan, Y, Chen, Z, Jin, W, Sun, C, et al.. Occupational electromagnetic field exposures associated with sleep quality: a cross-sectional study. PLoS One 2014;9:e110825. https://doi.org/10.1371/journal.pone.0110825.Search in Google Scholar PubMed PubMed Central
8. Monazzam, MR, Hosseini, M, Matin, LF, Aghaei, HA, Khosroabadi, H, Hesami, A. Sleep quality and general health status of employees exposed to extremely low frequency magnetic fields in a petrochemical complex. J Environ Health Sci Eng 2014;12:78. https://doi.org/10.1186/2052-336x-12-78.Search in Google Scholar PubMed PubMed Central
9. Baliatsas, C, van Kamp, I, Hooiveld, M, Yzermans, J, Lebret, E. Comparing non-specific physical symptoms in environmentally sensitive patients: prevalence, duration, functional status and illness behavior. J Psychosom Res 2014;76:405–13. https://doi.org/10.1016/j.jpsychores.2014.02.008.Search in Google Scholar PubMed
10. van Dongen, D, Smid, T, Timmermans, DR. Symptom attribution and risk perception in individuals with idiopathic environmental intolerance to electromagnetic fields and in the general population. Perspect Publ Health 2014;134:160–8. https://doi.org/10.1177/1757913913492931.Search in Google Scholar PubMed
11. Hagström, M, Auranen, J, Ekman, R. Electromagnetic hypersensitive Finns: symptoms, perceived sources and treatments, a questionnaire study. Pathophysiology 2013;20:117–22. https://doi.org/10.1016/j.pathophys.2013.02.001.Search in Google Scholar PubMed
12. Barsam, T, Monazzam, MR, Haghdoost, AA, Ghotbi, MR, Dehghan, SF. Effect of extremely low frequency electromagnetic field exposure on sleep quality in high voltage substations. Iran J Environ Health Sci Eng 2012;9:15. https://doi.org/10.1186/1735-2746-9-15.Search in Google Scholar PubMed PubMed Central
13. Kato, Y, Johansson, O. Reported functional impairments of electrohypersensitive Japanese: a questionnaire survey. Pathophysiology 2012;19:95–100. https://doi.org/10.1016/j.pathophys.2012.02.002.Search in Google Scholar PubMed
14. Tseng, MMC, Lin, YP, Cheng, TJ. Prevalence and psychiatric comorbidity of self-reported electromagnetic field sensitivity in Taiwan: a population-based study. J Formos Med Assoc 2011;110:634–41. https://doi.org/10.1016/j.jfma.2011.08.005.Search in Google Scholar PubMed
15. Johansson, A, Nordin, S, Heiden, M, Sandstrom, M. Symptoms, personality traits, and stress in people with mobile phone-related symptoms and electromagnetic hypersensitivity. J Psychosom Res 2010;68:37–45. https://doi.org/10.1016/j.jpsychores.2009.06.009.Search in Google Scholar PubMed
16. Schreier, N, Huss, A, Röösli, M. The prevalence of symptoms attributed to electromagnetic field exposure: a cross-sectional representative survey in Switzerland. Soz Praventivmed 2006;51:202–9. https://doi.org/10.1007/s00038-006-5061-2.Search in Google Scholar PubMed
17. Schüz, J, Petters, C, Egle, UT, Jansen, B, Kimbel, R, Letzel, S, et al.. The “Mainzer EMF-Wachhund”: results from a watchdog project on self-reported health complaints attributed to exposure to electromagnetic fields. Bioelectromagnetics 2006;27:280–7. https://doi.org/10.1002/bem.20212.Search in Google Scholar PubMed
18. Maisch, D, Podd, J, Rapley, B. Changes in health status in a group of CFS and CF patients following removal of excessive 50 Hz magnetic field exposure. ACNEM J 2002;21:15–9.Search in Google Scholar
19. Li, CY, Chen, PC, Sung, FC, Lin, RS. Residential exposure to power frequency magnetic field and sleep disorders among women in an urban community of northern Taiwan. Sleep 2002;25:428–32.Search in Google Scholar
20. Hillert, L, Berglind, N, Arnetz, BB, Bellander, T. Prevalence of self-reported hypersensitivity to electric or magnetic fields in a population-based questionnaire survey. Scand J Work Environ Health 2002;28:33–41. https://doi.org/10.5271/sjweh.644.Search in Google Scholar PubMed
21. Hillert, L, Kolmodin-Hedman, B, Eneroth, P, Arnetz, BB. The effect of supplementary antioxidant therapy in patients who report hypersensitivity to electricity: a randomized controlled trial. Med Gen Med 2001;3:11.Search in Google Scholar
22. Prasad, SK, Vyas, S. Health problems among workers of iron welding machines: an effect of electromagnetic fields. J Environ Biol 2001;22:129–32.Search in Google Scholar
23. Bonhomme-Faivre, L, Marion, S, Bezie, Y, Auclair, H, Fredj, G, Hommeau, C. Study of human neurovegetative and hematologic effects of environmental low-frequency (50-Hz) electromagnetic fields produced by transformers. Arch Environ Health 1998;53:87–92. https://doi.org/10.1080/00039896.1998.10545968.Search in Google Scholar PubMed
24. Eriksson, N, Hoog, J, Sandström, M, Stenberg, B. Facial skin symptoms in office workers. A five-year follow-up study. J Occup Environ Med 1997;39:108–18. https://doi.org/10.1097/00043764-199702000-00007.Search in Google Scholar PubMed
25. Bergdahl, J. Psychologic aspects of patients with symptoms presumed to be caused by electricity or visual display units. Acta Odontol Scand 1995;53:304–10. https://doi.org/10.3109/00016359509005992.Search in Google Scholar PubMed
26. Sandström, M, Hansson Mild, K, Stenberg, B, Wall, S. Skin symptoms among VDT workers and electromagnetic fields – a case report. Indoor Air 1995;5:29–37. https://doi.org/10.1111/j.1600-0668.1995.t01-3-00005.x.Search in Google Scholar
27. Stenberg, B, Eriksson, N, Hansson Mild, K, Hoog, J, Sandström, M, Sundell, J, et al.. Facial skin symptoms in visual display terminal (VDT) workers. A case-referent study of personal, psychosocial, building – and VDT-related risk indicators. Int J Epidemiol 1995;24:796–803. https://doi.org/10.1093/ije/24.4.796.Search in Google Scholar PubMed
29. Goldoni, J, Bobic, J, Saric, M. Psychological and ergonomic aspects of work with video display terminals. Arh Hig Rada Toksikol 1992;43:219–26.Search in Google Scholar
30. Liden, S, Berg, M. Skin problems in users of video display terminals. Discrepancy between subjective symptoms and objective signs. Acta Derm Venereol Suppl (Stockh) 1991;156:18–22.Search in Google Scholar
31. Dowson, DI, Lewith, GT, Campbell, M, Mullee, MA, Brewster, LA. Overhead high-voltage cables and recurrent headache and depressions. Practitioner 1988;232:435–6.Search in Google Scholar
32. Knave, BG, Wibom, RI, Voss, M, Hedstrom, LD, Bergqvist, UO. Work with video display terminals among office employees. I. Subjective symptoms and discomfort. Scand J Work Environ Health 1985;11:457–66. https://doi.org/10.5271/sjweh.2200.Search in Google Scholar PubMed
33. Boos, SR, Calissendorff, BM, Knave, BG, Nyman, KG, Voss, M. Work with video display terminals among office employees. III. Ophthalmologic factors. Scand J Work Environ Health 1985;11:475–81. https://doi.org/10.5271/sjweh.2207.Search in Google Scholar PubMed
34. Knave, BG, Wibom, RI, Bergqvist, UO, Carlsson, LL, Levin, MI, Nylen, PR. Work with video display terminals among office employees. II. Physical exposure factors. Scand J Work Environ Health 1985;11:467–74. https://doi.org/10.5271/sjweh.2199.Search in Google Scholar PubMed
35. Broadbent, DE, Broadbent, MH, Male, JC, Jones, MR. Health of workers exposed to electric fields. Br J Ind Med 1985;42:75–84. https://doi.org/10.1136/oem.42.2.75.Search in Google Scholar PubMed PubMed Central
36. Tettamanti, G, Auvinen, A, Åkerstedt, T, Kojo, K, Ahlbom, A, Heinävaara, S, et al.. Long-term effect of mobile phone use on sleep quality: results from the cohort study of mobile phone use and health (COSMOS). Environ Int 2020;140:105687. https://doi.org/10.1016/j.envint.2020.105687.Search in Google Scholar PubMed PubMed Central
37. Auvinen, A, Feychting, M, Ahlbom, A, Hillert, L, Elliott, P, Schüz, J, et al.. Headache, tinnitus and hearing loss in the international Cohort study of mobile phone use and health (COSMOS) in Sweden and Finland. Int J Epidemiol 2019;48:1567–79. https://doi.org/10.1093/ije/dyz127.Search in Google Scholar PubMed PubMed Central
38. Cabré-Riera, A, Torrent, M, Donaire-Gonzalez, D, Vrijheid, M, Cardis, E, Guxens, M. Telecommunication devices use, screen time and sleep in adolescents. Environ Res 2019;171:341–47. https://doi.org/10.1016/j.envres.2018.10.036.Search in Google Scholar PubMed
39. Liu, S, Wing, YK, Hao, Y, Li, W, Zhang, J, Zhang, B. The associations of long-time mobile phone use with sleep disturbances and mental distress in technical college students: a prospective cohort study. Sleep 2019;42:1–10. https://doi.org/10.1093/sleep/zsy213.Search in Google Scholar PubMed
40. Wdowiak, A, Błachnio, A, Raczkiewicz, D, Misztal-Okońska, P, Iwanowicz-Palus, G, Bień, A, et al.. The influence of electromagnetic fields generated by wireless connectivity systems on the occurrence of emotional disorders in women: a preliminary report. Neuroendocrinol Lett 2018;39:550–60.Search in Google Scholar
41. Martens, AL, Slottje, P, Smid, T, Kromhout, H, Vermeulen, RCH, Timmermans, DRM. Longitudinal associations between risk appraisal of base stations for mobile phones, radio or television and non-specific symptoms. J Psychosom Res 2018;112:81–9. https://doi.org/10.1016/j.jpsychores.2018.07.008.Search in Google Scholar PubMed
42. Višnjić, A, Veličković, V, Sokolović, D, Stanković, M, Mijatović, K, Stojanović, M, et al.. Relationship between the manner of mobile phone use and depression, anxiety, and stress in university students. Int J Environ Res Publ Health 2018;15:697.10.3390/ijerph15040697Search in Google Scholar
43. Martens, AL, Reedijk, M, Smid, T, Huss, A, Timmermans, D, Strak, M, et al.. Modeled and perceived RF-EMF, noise and air pollution and symptoms in a population cohort. Is perception key in predicting symptoms? Sci Total Environ 2018;639:75–83. https://doi.org/10.1016/j.scitotenv.2018.05.007.Search in Google Scholar PubMed
44. Sagiv, D, Migirov, L, Madgar, O, Nakache, G, Wolf, M, Shapira, Y. Mobile phone usage does not affect sudden sensorineural hearing loss. J Laryngol Otol 2018;132:29–32. https://doi.org/10.1017/s0022215117002365.Search in Google Scholar
45. Claeson, AS, Palmquist, E, Nordin, S. Physical and chemical trigger factors in environmental intolerance. Int J Hyg Environ Health 2018;221:586–92. https://doi.org/10.1016/j.ijheh.2018.02.009.Search in Google Scholar PubMed
46. Durusoy, R, Hassoy, H, Özkurt, A, Karababa, AO. Mobile phone use, school electromagnetic field levels and related symptoms: a cross-sectional survey among 2150 high school students in Izmir. Environ Health 2017;16:51. https://doi.org/10.1186/s12940-017-0257-x.Search in Google Scholar PubMed PubMed Central
47. Martens, AL, Slottje, P, Timmermans, DR, Kromhout, H, Reedijk, M, Vermeulen, RC, et al.. Modeled and perceived exposure to radiofrequency electromagnetic fields from mobile-phone base stations and the development of symptoms over time in a general population cohort. Am J Epidemiol 2017;186:210–9. https://doi.org/10.1093/aje/kwx041.Search in Google Scholar PubMed
48. Cho, YM, Lim, HJ, Jang, H, Kim, K, Choi, JW, Shin, C, et al.. A follow-up study of the association between mobile phone use and symptoms of ill health. Environ Health Toxicol 2017;32:e2017001.10.5620/eht.e2017001Search in Google Scholar
49. Schoeni, A, Roser, K, Röösli, M. Symptoms and the use of wireless communication devices: a prospective cohort study in Swiss adolescents. Environ Res 2017;154:275–83. https://doi.org/10.1016/j.envres.2017.01.004.Search in Google Scholar PubMed
50. Nagarjunakonda, S, Amalakanti, S, Uppala, V, Gajula, RK, Tata, RS, Bolla, HB, et al.. Mobile phones and seizures: drug-resistant epilepsy is less common in mobile-phone-using patients. Postgrad Med J 2017;93:25–8. https://doi.org/10.1136/postgradmedj-2016-134140.Search in Google Scholar PubMed
51. Slottje, P, van Moorselaar, I, van Strien, R, Vermeulen, R, Kromhout, H, Huss, A. Electromagnetic hypersensitivity (EHS) in occupational and primary health care: a nation-wide survey among general practitioners, occupational physicians and hygienists in The Netherlands. Int J Hyg Environ Health 2017;220:395–400. https://doi.org/10.1016/j.ijheh.2016.11.013.Search in Google Scholar PubMed
52. Cho, YM, Lim, HJ, Jang, H, Kim, K, Choi, JW, Shin, C, et al.. A cross-sectional study of the association between mobile phone use and symptoms of ill health. Environ Health Toxicol 2016;31:e2016022. https://doi.org/10.5620/eht.e2016022.Search in Google Scholar PubMed PubMed Central
53. Roser, K, Schoeni, A, Röösli, M. Mobile phone use, behavioural problems and concentration capacity in adolescents: a prospective study. Int J Hyg Environ Health 2016;219:759–69. https://doi.org/10.1016/j.ijheh.2016.08.007.Search in Google Scholar PubMed
54. Schoeni, A, Roser, K, Bürgi, A, Röösli, M. Symptoms in Swiss adolescents in relation to exposure from fixed site transmitters: a prospective cohort study. Environ Health 2016;15:77. https://doi.org/10.1186/s12940-016-0158-4.Search in Google Scholar PubMed PubMed Central
55. Singh, K, Nagaraj, A, Yousuf, A, Ganta, S, Pareek, S, Vishnani, P. Effect of electromagnetic radiations from mobile phone base stations on general health and salivary function. J Int Soc Prev Community Dent 2016;6:54–9.10.4103/2231-0762.175413Search in Google Scholar
56. Eyvazlou, M, Zarei, E, Rahimi, A, Abazari, M. Association between overuse of mobile phones on quality of sleep and general health among occupational health and safety students. Chronobiol Int 2016;33:293–300. https://doi.org/10.3109/07420528.2015.1135933.Search in Google Scholar PubMed
57. Stalin, P, Abraham, SB, Kanimozhy, K, Prasad, RV, Singh, Z, Purty, AJ. Mobile phone usage and its health effects among adults in a semi-urban area of southern India. J Clin Diagn Res 2016;10:LC14–6. https://doi.org/10.7860/JCDR/2016/16576.7074.Search in Google Scholar PubMed PubMed Central
58. Silva, DF, Barros, WR, Almeida, MD, Rego, MA. Exposure to non-ionizing electromagnetic radiation from mobile telephony and the association with psychiatric symptoms. Cad Saúde Pública 2015;31:2110–26. https://doi.org/10.1590/0102-311x00104114.Search in Google Scholar
59. Huss, A, van Eijsden, M, Guxens, M, Beekhuizen, J, van Strien, R, Kromhout, H, et al.. Environmental radiofrequency electromagnetic fields exposure at home, mobile and Cordless phone use, and sleep problems in 7-year-old Children. PLoS One 2015;10:e0139869. https://doi.org/10.1371/journal.pone.0139869.Search in Google Scholar PubMed PubMed Central
60. Zheng, F, Gao, P, He, M, Li, M, Tan, J, Chen, D, et al.. Association between mobile phone use and self-reported well-being in children: a questionnaire-based cross-sectional study in Chongqing, China. BMJ Open 2015;5:e007302. https://doi.org/10.1136/bmjopen-2014-007302.Search in Google Scholar PubMed PubMed Central
61. Chiu, CT, Chang, YH, Chen, CC, Ko, MC, Li, CY. Mobile phone use and health symptoms in children. J Formos Med Assoc 2015;114:598–604. https://doi.org/10.1016/j.jfma.2014.07.002.Search in Google Scholar PubMed
62. Islam, SM. Awareness and self-reported health hazards of electromagnetic waves from mobile phone towers in Dhaka, Bangladesh: a pilot study. Adv Public Health 2014:952832.10.1155/2014/952832Search in Google Scholar
63. Pachuau, L, Sailo, L, Pachuau, Z, Lalngneia, PC. RF radiation from mobile phone towers and their effects on human body. Indian J Radio Space Phys 2014;43:186–9.Search in Google Scholar
64. Saxena, Y, Shrivastava, A, Priyanka, S. Mobile usage and sleep patterns among medical students. Indian J Physiol Pharmacol 2014;58:100–3.Search in Google Scholar
65. Zheng, F, Gao, P, He, M, Li, M, Wang, C, Zeng, Q, et al.. Association between mobile phone use and inattention in 7102 Chinese adolescents: a population-based cross-sectional study. BMC Publ Health 2014;14:1–7. https://doi.org/10.1186/1471-2458-14-1022.Search in Google Scholar PubMed PubMed Central
66. Suleiman, A, Gee, TT, Krishnapillai, AD, Khalil, AM, Hamid, MWA, Mustapa, M. Electromagnetic radiation health effects in exposed and non-exposed residents in Penang. J Geosci Environ Protect 2014;2:77–83. https://doi.org/10.4236/gep.2014.22012.Search in Google Scholar
67. Szyjkowska, A, Gadzicka, E, Szymczak, W, Bortkiewicz, A. The risk of subjective symptoms in mobile phone users in Poland – an epidemiological study. Int J Occup Med Environ Health 2014;27:293–303. https://doi.org/10.2478/s13382-014-0260-1.Search in Google Scholar PubMed
68. Kücer, N, Pamukcu, T. Self-reported symptoms associated with exposure to electromagnetic fields: a questionnaire study. Electromagn Biol Med 2014;33:15–7. https://doi.org/10.3109/15368378.2013.783847.Search in Google Scholar PubMed
69. Gomez-Perretta, C, Navarro, EA, Segura, J, Portoles, M. Subjective symptoms related to GSM radiation from mobile phone base stations: a cross-sectional study. BMJ Open 2013;3:e003836. https://doi.org/10.1136/bmjopen-2013-003836.Search in Google Scholar PubMed PubMed Central
70. Sudan, M, Kheifets, L, Arah, OA, Olsen, J. Cell phone exposures and hearing loss in children in the Danish National Birth Cohort. Paediatr Perinat Epidemiol 2013;27:247–57. https://doi.org/10.1111/ppe.12036.Search in Google Scholar PubMed PubMed Central
71. Byun, YH, Ha, M, Kwon, HJ, Hong, YC, Leem, JH, Sakong, J, et al.. Mobile phone use, blood lead levels, and attention deficit hyperactivity symptoms in children: a longitudinal study. PLoS One 2013;8:e59742. https://doi.org/10.1371/journal.pone.0059742.Search in Google Scholar PubMed PubMed Central
72. Sudan, M, Kheifets, L, Arah, O, Olsen, J, Zeltzer, L. Prenatal and postnatal cell phone exposures and headaches in children. Open Pediatr Med J 2012;6:46–52. https://doi.org/10.2174/1874309901206010046.Search in Google Scholar PubMed PubMed Central
73. Mohler, E, Frei, P, Fröhlich, J, Braun-Fahrländer, C, Röösli, M, QUALIFEX-team. Exposure to radiofrequency electromagnetic fields and sleep quality: a prospective Cohort study. PLoS One 2012;7:e37455. https://doi.org/10.1371/journal.pone.0037455.Search in Google Scholar PubMed PubMed Central
74. Augner, C, Gnambs, T, Winker, R, Barth, A. Acute effects of electromagnetic fields emitted by GSM mobile phones on subjective well-being and physiological reactions: a meta-analysis. Sci Total Environ 2012;424:11–5. https://doi.org/10.1016/j.scitotenv.2012.02.034.Search in Google Scholar PubMed
75. Bortkiewicz, A, Gadzicka, E, Szyjkowska, A, Politanski, P, Mamrot, P, Szymczak, W, et al.. Subjective complaints of people living near mobile phone base stations in Poland. Int J Occup Med Environ Health 2012;25:31–40. https://doi.org/10.2478/s13382-012-0007-9.Search in Google Scholar PubMed
76. Frei, P, Mohler, E, Braun-Fahrländer, C, Fröhlich, J, Neubauer, G, Röösli, M, QUALIFEX-team. Cohort study on the effects of everyday life radio frequency electromagnetic field exposure on non-specific symptoms and tinnitus. Environ Int 2012;38:29–36. https://doi.org/10.1016/j.envint.2011.08.002.Search in Google Scholar PubMed
77. Mortazavi, SM, Atefi, M, KholghiF. The pattern of mobile phone use and prevalence of self-reported symptoms in elementary and junior high school students in Shiraz, Iran. Iran J Med Sci 2011;36:96–103.Search in Google Scholar
78. Alazawi, SA. Mobile phone base stations health effects. Diyala J Med 2011;1:44–52.Search in Google Scholar
79. Chu, MK, Song, HG, Kim, C, Lee, BC. Clinical features of headache associated with mobile phone use: a cross-sectional study in university students. BMC Neurol 2011;11:115. https://doi.org/10.1186/1471-2377-11-115.Search in Google Scholar PubMed PubMed Central
80. Baliatsas, C, van Kamp, I, Kelfkens, G, Schipper, M, Bolte, J, Yzermans, J, et al.. Non-specific physical symptoms in relation to actual and perceived proximity to mobile phone base stations and powerlines. BMC Publ Health 2011;11:421. https://doi.org/10.1186/1471-2458-11-421.Search in Google Scholar PubMed PubMed Central
81. Heinrich, S, Thomas, S, Heumann, C, von Kries, R, Radon, K. The impact of exposure to radio frequency electromagnetic fields on chronic well-being in young people – a cross-sectional study based on personal dosimetry. Environ Int 2011;37:26–30. https://doi.org/10.1016/j.envint.2010.06.008.Search in Google Scholar PubMed
82. Röösli, M, Mohler, E, Frei, P. Sense and sensibility in the context of radiofrequency electromagnetic field exposure. CR physique 2010;11:576–84. https://doi.org/10.1016/j.crhy.2010.10.007.Search in Google Scholar
83. Heinrich, S, Thomas, S, Heumann, C, von Kries, R, Radon, K. Association between exposure to radiofrequency electromagnetic fields assessed by dosimetry and acute symptoms in children and adolescents: a population based cross-sectional study. Environ Health 2010;9:1–9. https://doi.org/10.1186/1476-069X-9-75.Search in Google Scholar PubMed PubMed Central
84. Eger, H, Jahn, M. Specific symptoms and radiation from mobile basis stations in Selbitz, Bavaria, Germany: evidence for a dose-effect relationship. Umwelt-Medizin-Gesellschaft 2010;23:130–9.Search in Google Scholar
85. Hutter, HP, Moshammer, H, Wallner, P, Cartellieri, M, Denk-Linnert, DM, Katzinger, M, et al.. Tinnitus and mobile phone use. Occup Environ Med 2010;67:804–8. https://doi.org/10.1136/oem.2009.048116.Search in Google Scholar PubMed
86. Breckenkamp, J, Blettner, M, Kowall, B, Schüz, J, Schlehofer, B, Schmiedel, S, et al.. Results of a cross-sectional study on the association of electromagnetic fields emitted from mobile phone base stations and health complaints. Umweltmed Forsch Prax 2010;15:159–66.Search in Google Scholar
87. Mohler, E, Frei, P, Braun-Fahrländer, C, Fröhlich, J, Neubauer, G, Röösli, M. Effects of everyday radiofrequency electromagnetic-field exposure on sleep quality: a cross-sectional study. Radiat Res 2010;174:347–56. https://doi.org/10.1667/rr2153.1.Search in Google Scholar
88. Milde-Busch, A, von Kries, R, Thomas, S, Heinrich, S, Straube, A, Radon, K. The association between use of electronic media and prevalence of headache in adolescents: results from a population-based cross-sectional study. BMC Neurol 2010;10:12. https://doi.org/10.1186/1471-2377-10-12.Search in Google Scholar PubMed PubMed Central
89. Augner, C, Hacker, GW. Are people living next to mobile phone base stations more strained? Relationship of health concerns, self-estimated distance to base station, and psychological parameters. Indian J Occup Environ Med 2009;13:141–5. https://doi.org/10.4103/0019-5278.58918.Search in Google Scholar PubMed PubMed Central
90. Korpinen, LH, Pääkkönen, R. Self-report of physical symptoms associated with using mobile phones and other electrical devices. Bioelectromagnetics 2009;30:431–7. https://doi.org/10.1002/bem.20500.Search in Google Scholar PubMed
91. Berg-Beckhoff, G, Blettner, M, Kowall, B, Breckenkamp, J, Schlehofer, B, Schmiedel, S, et al.. Mobile phone base stations and adverse health effects: phase 2 of a cross-sectional study with measured radio frequency electromagnetic fields. Occup Environ Med 2009;66:124–30. https://doi.org/10.1136/oem.2008.039834.Search in Google Scholar PubMed
92. Blettner, M, Schlehofer, B, Breckenkamp, J, Kowall, B, Schmiedel, S, Reis, U. Mobile phone base stations and adverse health effects: phase 1 of a population-based, cross-sectional study in Germany. Occup Environ Med 2009;66:118–23. https://doi.org/10.1136/oem.2007.037721.Search in Google Scholar PubMed
94. Söderqvist, F, Carlberg, M, Hardell, L. Use of wireless telephones and self-reported health symptoms: a population-based study among Swedish adolescents aged 15–19 years. Environ Health 2008;7:1–10. https://doi.org/10.1186/1476-069x-7-18.Search in Google Scholar
95. Thomas, S, Kühnlein, A, Heinrich, S, Praml, G, Nowak, D, von Kries, R, et al.. Personal exposure to mobile phone frequencies and well-being in adults: a cross-sectional study based on dosimetry. Bioelectromagnetics 2008;29:463–70. https://doi.org/10.1002/bem.20414.Search in Google Scholar PubMed
96. Davidson, HC, Lutman, ME. Survey of mobile phone use and their chronic effects on the hearing of a student population. Int J Audiol 2007;46:113–8. https://doi.org/10.1080/14992020600690472.Search in Google Scholar PubMed
97. Schüz, J, Waldemar, G, Olsen, J, Johansen, C. Risks for central nervous system diseases among mobile phone subscribers: a Danish retrospective cohort study. PLoS One 2007;2:e4389.10.1371/journal.pone.0004389Search in Google Scholar
98. Leszczynski, D. Rapid response to: use of mobile phones and risk of brain tumours: update of Danish cohort study. The BMJ 2011. https://www.bmj.com/rapid-response/2011/12/03/re-use-mobile-phones-and-risk-brain-tumours-update-danish-cohort-study.Search in Google Scholar
99. Leszczynski, D. Opinion: scientific peer review in crisis. The case of the Danish Cohort. The Scientist, Feb. 25, 2013, https://www.the-scientist.com/news-opinion/opinion-scientific-peer-review-in-crisis-39728.Search in Google Scholar
100. Frei, P, Poulsen, AH, Johansen, C, Olsen, JH, Steding-Jessen, M, Schüz, J. Use of mobile phones and risk of brain tumours: update of Danish cohort study. BMJ 2011;343:d6387. https://doi.org/10.1136/bmj.d6387.Search in Google Scholar PubMed PubMed Central
101. Cardis, E, Richardson, L, Deltour, I, Armstrong, B, Feychting, M, Johansen, C, et al.. The INTERPHONE study: design, epidemiological methods, and description of the study population. Eur J Epidemiol 2007;22:647–64. https://doi.org/10.1007/s10654-007-9152-z.Search in Google Scholar PubMed
102. Vrijheid, M, Armstrong, BK, Bédard, D, Brown, J, Deltour, I, Iavarone, I, et al.. Recall bias in the assessment of exposure to mobile phones. J Expo Sci Environ Epidemiol 2009;19:369–81. https://doi.org/10.1038/jes.2008.27.Search in Google Scholar PubMed
103. Mortazavi, SM, Ahmadi, J, Shariati, M. Prevalence of subjective poor health symptoms associated with exposure to electromagnetic fields among university students. Bioelectromagnetics 2007;28:326–30. https://doi.org/10.1002/bem.20305.Search in Google Scholar PubMed
104. Hutter, HP, Moshammer, H, Wallner, P, Kundi, M. Subjective symptoms, sleeping problems, and cognitive performance in subjects living near mobile phone base stations. Occup Environ Med 2006;63:307–13. https://doi.org/10.1136/oem.2005.020784.Search in Google Scholar PubMed PubMed Central
105. Herr, C, Nieden, A, Lindenstruth, M, Stilianakis, N, Seitz, H, Eikmann, T. Relating use of mobile phones to reported sleep quality. Somnologie (Somnology) 2005;9:199–202. https://doi.org/10.1111/j.1439-054x.2005.00071.x.Search in Google Scholar
106. Meo, SA, Al-Drees, AM. Mobile phone related-hazards and subjective hearing and vision symptoms in the Saudi population. Int J Occup Med Environ Health 2005;18:53–7.Search in Google Scholar
107. Meo, SA, Al-Drees, AM. Do mobile phones cause hearing and vision complaints? A preliminary report. Saudi Med J 2005;26:882–3.Search in Google Scholar
108. Balik, HH, Turgut-Balik, D, Balikci, K, Ozcan, IC. Some ocular symptoms and sensations experienced by long term users of mobile phones. Pathol Biol (Paris) 2005;53:88–91. https://doi.org/10.1016/j.patbio.2004.03.012.Search in Google Scholar PubMed
109. Balikci, K, Cem Ozcan, I, Turgut-Balik, D, Balik, HH. A survey study on some neurological symptoms and sensations experienced by long term users of mobile phones. Pathol Biol (Paris) 2005;53:30–4. https://doi.org/10.1016/j.patbio.2003.12.002.Search in Google Scholar PubMed
110. Salama, OE, Abou El Naga, RM. Cellular phones: are they detrimental? J Egypt Public Health Assoc 2004;79:197–223.Search in Google Scholar
111. Al-Khlaiwi, T, Meo, SA. Association of mobile phone radiation with fatigue, headache, dizziness, tension and sleep disturbance in Saudi population. Saudi Med J 2004;25:732–36.Search in Google Scholar
112. Navarro, EA, Segura, J, Portoles, M, Gomez-Perretta, C. The Microwave Syndrome: a preliminary study in Spain. Electromagn Biol Med 2003;22:161–9. https://doi.org/10.1081/jbc-120024625.Search in Google Scholar
113. Santini, R, Santini, P, Le Ruz, P, Danze, JM, Seigne, M. Survey study of people living in the vicinity of cellular phone base stations. Electromagn Biol Med 2003;22:41–9. https://doi.org/10.1081/jbc-120020353.Search in Google Scholar
114. Santini, R, Seigne, M, Bonhomme-Faivre, L, Bouffet, S, Defrasne, E, Sage, M. Symptoms experienced by users of digital cellular phones: a study of a French engineering school. Electromagn Biol Med 2002;21:81–8. https://doi.org/10.1081/jbc-120003113.Search in Google Scholar
115. Sandström, M, Wilen, J, Oftedal, G, Hansson Mild, K. Mobile phone use and subjective symptoms. Comparison of symptoms experienced by users of analogue and digital mobile phones. Occup Med (Lond) 2001;51:25–35. https://doi.org/10.1093/occmed/51.1.25.Search in Google Scholar PubMed
116. Oftedal, G, Wilen, J, Sandström, M, Hansson Mild, K. Symptoms experienced in connection with mobile phone use. Occup Med (Lond) 2000;50:237–45. https://doi.org/10.1093/occmed/50.4.237.Search in Google Scholar PubMed
118. Ahamed, VI, Karthick, NG, Joseph, PK. Effect of mobile phone radiation on heart rate variability. Comput Biol Med 2008;38:709–12. https://doi.org/10.1016/j.compbiomed.2008.03.004.Search in Google Scholar PubMed
119. Andrzejak, R, Poreba, R, Poreba, M, Derkacz, A, Skalik, R, Gac, P, et al.. The influence of the call with a mobile phone on heart rate variability parameters in healthy volunteers. Ind Health 2008;46:409–17. https://doi.org/10.2486/indhealth.46.409.Search in Google Scholar PubMed
120. Atlasz, T, Kellenyi, L, Kovacs, P, Babai, N, Thuroczy, G, Hejjel, L, et al.. The application of surface plethysmography for heart rate variability analysis after GSM radiofrequency exposure. Biochem Biophys Methods 2006;69:233–6. https://doi.org/10.1016/j.jbbm.2006.03.017.Search in Google Scholar PubMed
121. Bamiou, DE, Ceranic, B, Cox, R, Watt, H, Chadwick, P, Luxon, LM. Mobile telephone use effects on peripheral audiovestibular function: a case-control study. Bioelectromagnetics 2008;29:108–17. https://doi.org/10.1002/bem.20369.Search in Google Scholar PubMed
122. Cinel, C, Russo, R, Boldini, A, Fox, E. Exposure to mobile phone electromagnetic fields and subjective symptoms: a double-blind study. Psychosom Med 2008;70:345–8. https://doi.org/10.1097/psy.0b013e31816521f1.Search in Google Scholar PubMed
123. Esen, F, Esen, H. Effect of electromagnetic fields emitted by cellular phones on the latency of evoked electrodermal activity. Int J Neurosci 2006;116:321–9. https://doi.org/10.1080/00207450500403371.Search in Google Scholar PubMed
124. Hietanen, M, Hämäläinen, AM, Husman, T. Hypersensitivity symptoms associated with exposure to cellular telephones: no causal link. Bioelectromagnetics 2002;23:264–70. https://doi.org/10.1002/bem.10016.Search in Google Scholar PubMed
125. Hillert, L, Akerstedt, T, Lowden, A, Wiholm, C, Kuster, N, Ebert, S, et al.. The effects of 884 MHz GSM wireless communication signals on headache and other symptoms: an experimental provocation study. Bioelectromagnetics 2008;29:185–96. https://doi.org/10.1002/bem.20379.Search in Google Scholar PubMed
126. Koivisto, M, Haarala, C, Krause, CM, Revonsuo, A, Laine, M, Hämäläinen, H. GSM phone signal does not produce subjective symptoms. Bioelectromagnetics 2001;22:212–5. https://doi.org/10.1002/bem.41.Search in Google Scholar PubMed
127. Kwon, MS, Koivisto, M, Laine, M, Hämäläinen, H. Perception of the electromagnetic field emitted by a mobile phone. Bioelectromagnetics 2008;29:154–9. https://doi.org/10.1002/bem.20375.Search in Google Scholar PubMed
128. Nam, KC, Lee, JH, Noh, HW, Cha, EJ, Kim, NH, Kim, DW. Hypersensitivity to RF fields emitted from CDMA cellular phones: a provocation study. Bioelectromagnetics 2009;30:641–50. https://doi.org/10.1002/bem.20518.Search in Google Scholar PubMed
129. Oftedal, G, Straume, A, Johnsson, A, Stovner, LJ. Mobile phone headache: a double blind, sham-controlled provocation study. Cephalalgia 2007;27:447–55. https://doi.org/10.1111/j.1468-2982.2007.01336.x.Search in Google Scholar PubMed
130. Parazzini, M, Ravazzani, P, Tognola, G, Thuroczy, G, Molnar, FB, Sacchettini, A, et al.. Electromagnetic fields produced by GSM cellular phones and heart rate variability. Bioelectromagnetics 2007;28:122–9. https://doi.org/10.1002/bem.20275.Search in Google Scholar PubMed
131. Rubin, GJ, Hahn, G, Everitt, BS, Cleare, AJ, Wessely, S. Are some people sensitive to mobile phone signals? Within participants double blind randomised provocation study. BMJ 2006;332:886–91. https://doi.org/10.1136/bmj.38765.519850.55.Search in Google Scholar PubMed PubMed Central
132. Tahvanainen, K, Nino, J, Halonen, P, Kuusela, T, Laitinen, T, Lansimies, E, et al.. Cellular phone use does not acutely affect blood pressure or heart rate of humans. Bioelectromagnetics 2004;25:73–83. https://doi.org/10.1002/bem.10165.Search in Google Scholar PubMed
133. Tamer, A, Gunduz, H, Ozyildirim, S. The cardiac effects of a mobile phone positioned closest to the heart. Anadolu Kardiyol Derg 2009;9:380–4.Search in Google Scholar
134. Wilen, J, Johansson, A, Kalezic, N, Lyskov, E, Sandström, M. Psychophysiological tests and provocation of subjects with mobile phone related symptoms. Bioelectromagnetics 2006;27:204–14. https://doi.org/10.1002/bem.20195.Search in Google Scholar PubMed
135. Kacprzyk, A, Kanclerz, G, Rokita, E, Tatoń, G. Which sources of electromagnetic field are of the highest concern for electrosensitive individuals? – Questionnaire study with a literature review. Electromagn Biol Med 2020;24:1–8.10.1080/15368378.2020.1839489Search in Google Scholar
137. Bolte, JF, Clahsen, S, Vercruijsse, W, Houtveen, JH, Schipper, CM, van Kamp, I, et al.. Ecological momentary assessment study of exposure to radiofrequency electromagnetic fields and non-specific physical symptoms with self-declared electrosensitives. Environ Int 2019;131:104948. https://doi.org/10.1016/j.envint.2019.104948.Search in Google Scholar PubMed
138. Bogers, RP, van Gils, A, Clahsen, SC, Vercruijsse, W, van Kamp, I, Baliatsas, C, et al.. Individual variation in temporal relationships between exposure to radiofrequency electromagnetic fields and non-specific physical symptoms: a new approach in studying ‘electrosensitivity’. Environ Int 2018;121:297–307. https://doi.org/10.1016/j.envint.2018.08.064.Search in Google Scholar PubMed
139. Andrianome, S, de Seze, R, Braun, A, Selmaoui, B. Descriptive self-reporting survey of people with idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF): similarities and comparisons with previous studies. J Public Health (Berl) 2018;26:461–73. https://doi.org/10.1007/s10389-017-0886-0.Search in Google Scholar
140. Dieudonné, M. Does electromagnetic hypersensitivity originate from nocebo responses? Indications from a qualitative study. Bioelectromagnetics. 2016;37:14–24. https://doi.org/10.1002/bem.21937.Search in Google Scholar PubMed
141. Baliatsas, C, van Kamp, I, Bolte, J, Kelfkens, G, van Dijk, C, Spreeuwenberg, P, et al.. Clinically defined non-specific symptoms in the vicinity of mobile phone base stations: a retrospective before-after study. Sci Total Environ 2016;565:714–20. https://doi.org/10.1016/j.scitotenv.2016.05.021.Search in Google Scholar PubMed
142. Kjellqvist, A, Palmquist, E, Nordin, S. Psychological symptoms and health-related quality of life in idiopathic environmental intolerance attributed to electromagnetic fields. J Psychosom Res 2016;84:8–12. https://doi.org/10.1016/j.jpsychores.2016.03.006.Search in Google Scholar PubMed
143. Lamech, F Self-reporting of symptom development from exposure to radiofrequency fields of wireless smart meters in Victoria, Australia: a case series. Alternative Ther Health Med 2014;20:28–39.Search in Google Scholar
144. Hagström, M, Auranen, J, Johansson, O, Ekman, R. Reducing electromagnetic irradiation and fields alleviates experienced health hazards of VDU work. Pathophysiology 2012;19:81–7. https://doi.org/10.1016/j.pathophys.2012.01.005.Search in Google Scholar PubMed
145. Ghezel-Ahmadi, D, Engel, A, Weidemann, J, Budnik, LT, Baur, X, Frick, U, et al.. Heavy metal exposure in patients suffering from electromagnetic hypersensitivity. Sci Total Environ 2010;408:774–8. https://doi.org/10.1016/j.scitotenv.2009.11.023.Search in Google Scholar PubMed
146. Huss, A, Küchenhoff, J, Bircher, A, Niederer, M, Tremp, J, Waeber, R, et al.. Electromagnetic fields and health complaints – interdisciplinary case evaluations in an environmental medicine counselling project. Umweltmed Forsch Prax 2005;10:21–8.Search in Google Scholar
147. Bouisset, N, Villard, S, Legros, A. Human postural control under high levels of extremely low frequency magnetic fields. IEEE Access 2020;8:101377–85. https://doi.org/10.1109/access.2020.2997643.Search in Google Scholar
148. Bouisset, N, Villard, S, Legros, A. Human postural responses to high vestibular specific extremely low-frequency magnetic stimulations. IEEE Access 2020;8:165387–95. https://doi.org/10.1109/access.2020.3022554.Search in Google Scholar
149. Villard, S, Allen, A, Bouisset, N, Corbacio, M, Thomas, A, Guerraz, M, et al.. Impact of extremely low-frequency magnetic fields on human postural control. Exp Brain Res 2019;237:611–23. https://doi.org/10.1007/s00221-018-5442-9.Search in Google Scholar PubMed
150. van Moorselaar, I, Slottje, P, Heller, P, van Strien, R, Kromhout, H, Murbach, M, et al.. Effects of personalised exposure on self-rated electromagnetic hypersensitivity and sensibility – a double-blind randomised controlled trial. Environ Int 2017;99:255–62. https://doi.org/10.1016/j.envint.2016.11.031.Search in Google Scholar PubMed
151. Szemerszky, R, Gubanyi, M, Arvai, D, Domotor, Z, Koteles, F. Is there a connection between electrosensitivity and electrosensibility? A replication study. Int J Behav Med 2015;22:755–63. https://doi.org/10.1007/s12529-015-9477-z.Search in Google Scholar PubMed
152. Kim, SK, Choi, JL, Kwon, MK, Choi, JY, Kim, DW. Effects of 60 Hz magnetic fields on teenagers and adults. Environ Health 2013;12:1–8. https://doi.org/10.1186/1476-069x-12-42.Search in Google Scholar
153. Koteles, F, Szemerszky, R, Gubanyi, M, Kormendi, J, Szekrenyesi, C, Lloyd, R, et al.. Idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF) and electrosensibility (ES) – are they connected? Int J Hyg Environ Health 2013;216:362–70. https://doi.org/10.1016/j.ijheh.2012.05.007.Search in Google Scholar PubMed
154. Kim, DW, Choi, JL, Nam, KC, Yang, DI, Kwon, MK. Origins of electromagnetic hypersensitivity to 60 Hz magnetic fields: a provocation study. Bioelectromagnetics 2012;33:326–33. https://doi.org/10.1002/bem.20711.Search in Google Scholar PubMed
155. McCarty, DE, Carrubba, S, Chesson, AL, Frilot, C, Gonzalez-Toledo, E, Marino, AA. Electromagnetic hypersensitivity: evidence for a novel neurological syndrome. Int J Neurosci 2011;121:670–6. https://doi.org/10.3109/00207454.2011.608139.Search in Google Scholar PubMed
156. Szemerszky, R, Koteles, F, Lihi, R, Bardos, G. Polluted places or polluted minds? An experimental sham-exposure study on background psychological factors of symptom formation in ‘Idiophatic Environmental Intolerance attributed to electromagnetic fields’. Int J Hyg Environ Health 2010;213:387–94. https://doi.org/10.1016/j.ijheh.2010.05.001.Search in Google Scholar PubMed
157. Nevelsteen, S, Legros, JJ, Crasson, M. Effects of information and 50 Hz magnetic fields on cognitive performance and reported symptoms. Bioelectromagnetics 2007;28:53–63. https://doi.org/10.1002/bem.20265.Search in Google Scholar PubMed
158. Ishihara, I, Ikushima, M, Horikawa, J, Haraga, M, Kawamoto, R, Murase, C, et al.. A very low level of magnetic field exposure does not affect a participant’s mental fatigue and stress as much as VDT work. J UOEH 2005;27:25–40. https://doi.org/10.7888/juoeh.27.25.Search in Google Scholar PubMed
159. Crasson, M, Legros, JJ. Absence of daytime 50 Hz, 100 microT(rms) magnetic field or bright light exposure effect on human performance and psychophysiological parameters. Bioelectromagnetics 2005;26:225–33. https://doi.org/10.1002/bem.20070.Search in Google Scholar PubMed
160. Mueller, CH, Krueger, H, Schierz, C. Project NEMESIS: perception of a 50 Hz electric and magnetic field at low intensities (laboratory experiment). Bioelectromagnetics 2002;23:26–36. https://doi.org/10.1002/bem.95.Search in Google Scholar PubMed
161. Stenberg, B, Bergdahl, J, Edvardsson, B, Eriksson, N, Linden, G, Widman, L. Medical and social prognosis for patients with perceived hypersensitivity to electricity and skin symptoms related to the use of visual display terminals. Scand J Work Environ Health 2002;28:349–57. https://doi.org/10.5271/sjweh.685.Search in Google Scholar PubMed
162. Lyskov, E, Sandström, M, Hansson Mild, K. Provocation study of persons with perceived electrical hypersensitivity and controls using magnetic field exposure and recording of electrophysiological characteristics. Bioelectromagnetics 2001;22:457–62. https://doi.org/10.1002/bem.73.Search in Google Scholar
163. Lonne-Rahm, S, Andersson, B, Melin, L, Schultzberg, M, Arnetz, B, Berg, M. Provocation with stress and electricity of patients with “sensitivity to electricity”. J Occup Environ Med 2000;42:512–6. https://doi.org/10.1097/00043764-200005000-00009.Search in Google Scholar PubMed
164. Flodin, U, Seneby, A, Tegenfeldt, C. Provocation of electric hypersensitivity under everyday conditions. Scand J Work Environ Health 2000;26:93–8. https://doi.org/10.5271/sjweh.517.Search in Google Scholar PubMed
165. Oftedal, G, Nyvang, A, Moen, BE. Long-term effects on symptoms by reducing electric fields from visual display units. Scand J Work Environ Health 1999;25:415–21. https://doi.org/10.5271/sjweh.454.Search in Google Scholar PubMed
166. Crasson, M, Legros, JJ, Scarpa, P, Legros, W. 50 Hz magnetic field exposure influence on human performance and psychophysiological parameters: two double-blind experimental studies. Bioelectromagnetics 1999;20:474–86. https://doi.org/10.1002/(sici)1521-186x(199912)20:8<474::aid-bem2>3.0.co;2-m.10.1002/(SICI)1521-186X(199912)20:8<474::AID-BEM2>3.0.CO;2-MSearch in Google Scholar
167. Sandström, M, Lyskov, E, Berglund, A, Medvedev, S, Hansson Mild, K. Neurophysiological effects of flickering light in patients with perceived electrical hypersensitivity. J Occup Environ Med 1997;39:15–22.10.1097/00043764-199701000-00006Search in Google Scholar
168. Andersson, B, Berg, M, Arnetz, BB, Melin, L, Langlet, I, Liden, S. A cognitive-behavioral treatment of patients suffering from “electric hypersensitivity”. Subjective effects and reactions in a double-blind provocation study. J Occup Environ Med 1996;38:752–8. https://doi.org/10.1097/00043764-199608000-00009.Search in Google Scholar PubMed
170. Johansson, O, Hilliges, M, Bjornhagen, V, Hall, K. Skin changes in patients claiming to suffer from “screen dermatitis”: a two-case open-field provocation study. Exp Dermatol 1996;3:234–8.10.1111/j.1600-0625.1994.tb00282.xSearch in Google Scholar
171. Gamberale, F, Olson, BA, Eneroth, P, Lindh, T, Wennberg, A. Acute effects of ELF electromagnetic fields: a field study of linesmen working with 400 kV power lines. Br J Ind Med 1989;46:729–37. https://doi.org/10.1136/oem.46.10.729.Search in Google Scholar PubMed PubMed Central
172. Wolters, C, Harzem, J, Witthöft, M, Gerlach, AL, Pohl, A. Somatosensory illusions elicited by sham electromagnetic field exposure: experimental evidence for a predictive processing account of somatic symptom perception. Psychosom Med. 2021;83:94–100. https://doi.org/10.1097/psy.0000000000000884.Search in Google Scholar PubMed
173. Yang, L, Zhang, C, Chen, Z, Li, C, Wu, T. Functional and network analyses of human exposure to long-term evolution signal. Environ Sci Pollut Res Int 2021;5:5755–73. https://doi.org/10.1007/s11356-020-10728-w.Search in Google Scholar PubMed
174. Gao, P, Zheng, FZ, He, MD, Li, M, Deng, P, Zhou, Z, et al.. An experimental study of effects of media implication on self-report symptoms related with MP use. Front Public Health 2020;8:175. https://doi.org/10.3389/fpubh.2020.00175.Search in Google Scholar PubMed PubMed Central
175. Bräscher, AK, Schulz, SM, Van den Bergh, O, Witthöft, M. Prospective study of nocebo effects related to symptoms of idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF). Environ Res 2020;190:110019. https://doi.org/10.1016/j.envres.2020.110019.Search in Google Scholar PubMed
176. Loughran, SP, Verrender, A, Dalecki, A, Burdon, CA, Tagami, K, Park, J, et al.. Radiofrequency electromagnetic field exposure and the resting EEG: exploring the thermal mechanism hypothesis. Int J Environ Res Publ Health 2019;16:e1505. https://doi.org/10.3390/ijerph16091505.Search in Google Scholar PubMed PubMed Central
177. Eltiti, S, Wallace, D, Russo, R, Fox, E. Symptom presentation in idiopathic environmental intolerance with attribution to electromagnetic fields: evidence for a nocebo effect based on data re-analyzed from two previous provocation studies. Front Psychol 2018;9:1563. https://doi.org/10.3389/fpsyg.2018.01563.Search in Google Scholar PubMed PubMed Central
178. Verrender, A, Loughran, SP, Dalecki, A, Freudenstein, F, Croft, RJ. Can explicit suggestions about the harmfulness of EMF exposure exacerbate a nocebo response in healthy controls? Environ Res 2018;166:409–17. https://doi.org/10.1016/j.envres.2018.06.032.Search in Google Scholar PubMed
179. Verrender, A, Loughran, SP, Anderson, V, Hillert, L, Rubin, GJ, Oftedal, G, et al.. IEI-EMF provocation case studies: a novel approach to testing sensitive individuals. Bioelectromagnetics 2018;39:132–43. https://doi.org/10.1002/bem.22095.Search in Google Scholar PubMed
180. Andrianome, S, Gobert, J, Hugueville, L, Stéphan-Blanchard, E, Telliez, F, Selmaoui, B. An assessment of the autonomic nervous system in the electrohypersensitive population: a heart rate variability and skin conductance study. J Appl Physiol (1985) 2017;123:1055–62. https://doi.org/10.1152/japplphysiol.00229.2017.Search in Google Scholar PubMed
181. Bräscher, AK, Raymaekers, K, Van den Bergh, O, Witthöft, M. Are media reports able to cause somatic symptoms attributed to Wi-Fi radiation? An experimental test of the negative expectation hypothesis. Environ Res 2017;156:265–71. https://doi.org/10.1016/j.envres.2017.03.040.Search in Google Scholar PubMed
182. Burgess, AP, Fouquet, NC, Seri, S, Hawken, MB, Heard, A, Neasham, D, et al.. Acute Exposure to Terrestrial Trunked Radio (TETRA) has effects on the electroencephalogram and electrocardiogram, consistent with vagal nerve stimulation. Environ Res 2016;150:461–9. https://doi.org/10.1016/j.envres.2016.06.031.Search in Google Scholar PubMed PubMed Central
183. Verrender, A, Loughran, SP, Dalecki, A, McKenzie, R, Croft, RJ. Pulse modulated radiofrequency exposure influences cognitive performance. Int J Radiat Biol 2016;92:603–10. https://doi.org/10.1080/09553002.2016.1213454.Search in Google Scholar PubMed
184. Bamiou, DE, Ceranic, B, Vickers, D, Zamyslowska-Szmytke, E, Cox, R, Chadwick, P, et al.. Mobile telephone use effects on perception of verticality. Bioelectromagnetics 2015;36:27–34. https://doi.org/10.1002/bem.21877.Search in Google Scholar PubMed
185. S Wallace, D, Russo, R, Fox, E. Aggregated data from two double-blind base station provocation studies comparing individuals with idiopathic environmental intolerance with attribution to electromagnetic fields and controls. Bioelectromagnetics 2015;36:96–107.10.1002/bem.21892Search in Google Scholar
186. Malek, F, Rani, KA, Rahim, HA, Omar, MH. Effect of short-term mobile phone base station exposure on cognitive performance, body temperature, heart rate and blood pressure of Malaysians. Sci Rep 2015;5:13206. https://doi.org/10.1038/srep13206.Search in Google Scholar PubMed PubMed Central
187. Sauter, C, Eggert, T, Dorn, H, Schmid, G, Bolz, T, Marasanov, A, et al.. Do signals of a hand-held TETRA transmitter affect cognitive performance, well-being, mood or somatic complaints in healthy young men? Results of a randomized double-blind cross-over provocation study. Environ Res 2015;140:85–94. https://doi.org/10.1016/j.envres.2015.03.021.Search in Google Scholar PubMed
188. Dorn, H, Schmid, G, Eggert, T, Sauter, C, Bolz, T, Danker-Hopfe, H. Experimental investigation of possible warmth perception from a head exposure system for human provocation studies with TETRA handset-like signals. Bioelectromagnetics 2014;35:452–8. https://doi.org/10.1002/bem.21866.Search in Google Scholar PubMed
189. Choi, SB, Kwon, MK, Chung, JW, Park, JS, Chung, K, Kim, DW. Effects of short-term radiation emitted by WCDMA mobile phones on teenagers and adults. BMC Publ Health 2014;14:438. https://doi.org/10.1186/1471-2458-14-438.Search in Google Scholar PubMed PubMed Central
190. Vecsei, Z, Csatho, A, Thuroczy, G, Hernadi, I. Effect of a single 30 min UMTS mobile phone-like exposure on the thermal pain threshold of young healthy volunteers. Bioelectromagnetics 2013;34:530–41. https://doi.org/10.1002/bem.21801.Search in Google Scholar PubMed
191. Loughran, SP, Benz, DC, Schmid, MR, Murbach, M, Kuster, N, Achermann, P. No increased sensitivity in brain activity of adolescents exposed to mobile phone-like emissions. Clin Neurophysiol 2013;124:1303–8. https://doi.org/10.1016/j.clinph.2013.01.010.Search in Google Scholar PubMed
192. Witthöft, M, Rubin, GJ. Are media warnings about the adverse health effects of modern life self-fulfilling? An experimental study on idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF). J Psychosom Res 2013;74:206–12. https://doi.org/10.1016/j.jpsychores.2012.12.002.Search in Google Scholar PubMed
193. Schmid, MR, Murbach, M, Lustenberger, C, Maire, M, Kuster, N, Achermann, P, et al.. Sleep EEG alterations: effects of pulsed magnetic fields versus pulse-modulated radio frequency electromagnetic fields. J Sleep Res 2012;21:620–9. https://doi.org/10.1111/j.1365-2869.2012.01025.x.Search in Google Scholar PubMed
194. Schmid, MR, Loughran, SP, Regel, SJ, Murbach, M, Bratic Grunauer, A, Rusterholz, T, et al.. Sleep EEG alterations: effects of different pulse-modulated radio frequency electromagnetic fields. J Sleep Res 2012;21:50–8. https://doi.org/10.1111/j.1365-2869.2011.00918.x.Search in Google Scholar PubMed
195. Kwon, MK, Choi, JY, Kim, SK, Yoo, TK, Kim, DW. Effects of radiation emitted by WCDMA mobile phones on electromagnetic hypersensitive subjects. Environ Health 2012;11:1–8. https://doi.org/10.1186/1476-069X-11-69.Search in Google Scholar PubMed PubMed Central
196. Wallace, D, Eltiti, S, Ridgewell, A, Garner, K, Russo, R, Sepulveda, F, et al.. Cognitive and physiological responses in humans exposed to a TETRA base station signal in relation to perceived electromagnetic hypersensitivity. Bioelectromagnetics 2012;33:23–39. https://doi.org/10.1002/bem.20681.Search in Google Scholar PubMed
197. Mortazavi, SM, Mahbudi, A, Atefi, M, Bagheri, SH, Bahaedini, N, Besharati, A. An old issue and a new look: electromagnetic hypersensitivity caused by radiations emitted by GSM mobile phones. Technol Health Care 2011;19:435–43. https://doi.org/10.3233/thc-2011-0641.Search in Google Scholar PubMed
198. Nieto-Hernandez, R, Williams, J, Cleare, AJ, Landau, S, Wessely, S, Rubin, GJ. Can exposure to a terrestrial trunked radio (TETRA)-like signal cause symptoms? A randomised double-blind provocation study. Occup Environ Med 2011;68:339–44. https://doi.org/10.1136/oem.2010.055889.Search in Google Scholar PubMed
199. Lindholm, H, Alanko, T, Rintamäki, H, Kännälä, S, Toivonen, T, Sistonen, H, et al.. Thermal effects of mobile phone RF fields on children: a provocationstudy. Prog Biophys Mol Biol 2011;107:399–403. https://doi.org/10.1016/j.pbiomolbio.2011.09.004.Search in Google Scholar PubMed
200. Kwon, MK, Nam, KC, Lee da, S, Jang, KH, Kim, DW. Effects of RF fields emitted from smart phones on cardio-respiratory parameters: a preliminary provocation study. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA IEEE; 2011:1961–4 pp., ISBN 9781457715891.Search in Google Scholar
201. Havas, M, Marrongelle, J, Pollner, B, Kelley, E, Rees, CR, Tully, L. Provocation study using heart rate variability shows microwave radiation from 2.4 GHz cordless phone affects autonomic nervous system. In: Non-thermal effects and mechanisms of interaction between electromagnetic fields and living matter Mattioli 1885; 2010:273–300 pp.Search in Google Scholar
202. Wallace, D, Eltiti, S, Ridgewell, A, Garner, K, Russo, R, Sepulveda, F, et al.. Do TETRA (airwave) base station signals have a short-term impact on health and well-being? A randomized double-blind provocation study. Environ Health Perspect 2010;118:735–41. https://doi.org/10.1289/ehp.0901416.Search in Google Scholar PubMed PubMed Central
203. Riddervold, IS, Kjaergaard, SK, Pedersen, GF, Andersen, NT, Franek, O, Pedersen, AD, et al.. No effect of TETRA hand portable transmission signals on human cognitive function and symptoms. Bioelectromagnetics 2010;31:191–9. https://doi.org/10.1002/bem.20571.Search in Google Scholar PubMed
204. Augner, C, Florian, M, Pauser, G, Oberfeld, G, Hacker, GW. GSM base stations: short-term effects on well-being. Bioelectromagnetics 2009;30:73–80. https://doi.org/10.1002/bem.20447.Search in Google Scholar PubMed
205. Furubayashi, T, Ushiyama, A, Terao, Y, Mizuno, Y, Shirasawa, K, Pongpaibool, P, et al.. Effects of short-term W-CDMA mobile phone base station exposure on women with or without mobile phone related symptoms. Bioelectromagnetics 2009;30:100–13. https://doi.org/10.1002/bem.20446.Search in Google Scholar PubMed
206. Eltiti, S, Wallace, D, Ridgewell, A, Zougkou, K, Russo, R, Sepulveda, F, et al.. Short-term exposure to mobile phone base station signals does not affect cognitive functioning or physiological measures in individuals who report sensitivity to electromagnetic fields and controls. Bioelectromagnetics 2009;30:556–63. https://doi.org/10.1002/bem.20504.Search in Google Scholar PubMed
207. Curcio, G, Ferrara, M, Limongi, T, Tempesta, D, Di Sante, G, De Gennaro, L, et al.. Acute mobile phones exposure affects frontal cortex hemodynamics as evidenced by functional near-infrared spectroscopy. J Cerebr Blood Flow Metabol 2009;29:903–10. https://doi.org/10.1038/jcbfm.2009.14.Search in Google Scholar PubMed
208. Wiholm, C, Lowden, A, Kuster, N, Hillert, L, Arnetz, BB, Akerstedt, T, et al.. Mobile phone exposure and spatial memory. Bioelectromagnetics 2009;30:59–65. https://doi.org/10.1002/bem.20443.Search in Google Scholar PubMed
209. Leitgeb, N, Schröttner, J, Cech, R, Kerbl, R. EMF-protection sleep study near mobile phone base stations. Somnologie (Somnology) 2008;12:234–43. https://doi.org/10.1007/s11818-008-0353-9.Search in Google Scholar
210. Nieto-Hernandez, R, Rubin, GJ, Cleare, AJ, Weinman, JA, Wessely, S. Can evidence change belief? Reported mobile phone sensitivity following individual feedback of an inability to discriminate active from sham signals. J Psychosom Res 2008;65: 453–60. https://doi.org/10.1016/j.jpsychores.2008.04.005.Search in Google Scholar PubMed
211. Stovner, LJ, Oftedal, G, Straume, A, Johnsson, A. Nocebo as headache trigger: evidence from a sham-controlled provocation study with RF fields. Acta Neurol Scand Suppl 2008;188:67–71. https://doi.org/10.1111/j.1600-0404.2008.01035.x.Search in Google Scholar PubMed
212. Kleinlogel, H, Dierks, T, Koenig, T, Lehmann, H, Minder, A, Berz, R. Effects of weak mobile phone – electromagnetic fields (GSM, UMTS) on well-being and resting EEG. Bioelectromagnetics 2008;29:479–87. https://doi.org/10.1002/bem.20419.Search in Google Scholar PubMed
213. Johansson, A, Forsgren, S, Stenberg, B, Wilen, J, Kalezic, N, Sandström, M. No effect of mobile phone-like RF exposure on patients with atopic dermatitis. Bioelectromagnetics 2008;29:353–62. https://doi.org/10.1002/bem.20402.Search in Google Scholar PubMed
214. Riddervold, IS, Pedersen, GF, Andersen, NT, Pedersen, AD, Andersen, JB, Zachariae, R, et al.. Cognitive function and symptoms in adults and adolescents in relation to rf radiation from UMTS base stations. Bioelectromagnetics 2008;29:257–67. https://doi.org/10.1002/bem.20388.Search in Google Scholar PubMed
215. Landgrebe, M, Frick, U, Hauser, S, Langguth, B, Rosner, R, Hajak, G, et al.. Cognitive and neurobiological alterations in electromagnetic hypersensitive patients: results of a case-control study. Psychol Med 2008;38:1781–91. https://doi.org/10.1017/s0033291708003097.Search in Google Scholar
216. Landgrebe, M, Hauser, S, Langguth, B, Frick, U, Hajak, G, Eichhammer, P. Altered cortical excitability in subjectively electrosensitive patients: results of a pilot study. J Psychosom Res 2007;62:283–8. https://doi.org/10.1016/j.jpsychores.2006.11.007.Search in Google Scholar PubMed
217. Arnetz, BB, Akerstedt, T, Hillert, L, Lowden, A, Kuster, N, Wiholm, C. The Effects of 884 MHz GSM wireless communication signals on self-reported symptom and sleep (EEG) – an experimental provocation study. PIERS Online 2007;3:1148–50. https://doi.org/10.2529/piers060907172142.Search in Google Scholar
218. Wiholm, C, Lowden, A, Hillert, L, Kuster, N, Arnetz, BB, Akerstedt, T, et al.. The effects of 884 MHz GSM wireless communication signals on spatial memory performance: an experimental provocation study. In: PIERS Proceedings, Prague, Czech Republic the Electromagnetics Academy; 2007:526–9 pp., ISBN 9781934142028.Search in Google Scholar
219. Eltiti, S, Wallace, D, Ridgewell, A, Zougkou, K, Russo, R, Sepulveda, F, et al.. Does short-term exposure to mobile phone base station signals increase symptoms in individuals who report sensitivity to electromagnetic fields? A double-blind randomized provocation study. Environ Health Perspect 2007;115:1603–8. https://doi.org/10.1289/ehp.10286.Search in Google Scholar
220. Heinrich, S, Ossig, A, Schlittmeier, S, Hellbrück, J. Electromagnetic fields of a UMTS mobile phone base station and possible effects on health – results from an experimental field study [Elektromagnetische Felder einer UMTS-Mobilfunkbasisstation und mögliche Auswirkungen auf die Befindlichkeit – eine experimentelle Felduntersuchung]. Umweltmed Forsch Prax 2007;12:171–80.Search in Google Scholar
221. Hinrichs, H, Heinze, HJ. High frequency GSM-1800 fields with various modulations and field strengths: No short term effect on human awake EEG. Edition Wissenschaft 2006;23:1–12.Search in Google Scholar
222. Regel, SJ, Negovetic, S, Röösli, M, Berdinas, V, Schuderer, J, Huss, A, et al.. UMTS base station-like exposure, well-being, and cognitive performance. Environ Health Perspect 2006;114:1270–5. https://doi.org/10.1289/ehp.8934.Search in Google Scholar
223. Nam, KC, Kim, SW, Kim, SC, Kim, DW. Effects of RF exposure of teenagers and adults by CDMA cellular phones. Bioelectromagnetics 2006;27:509–14. https://doi.org/10.1002/bem.20229.Search in Google Scholar
224. Leitgeb, N, Schröttner, J, Cech, R, Kerbl, R. Investigation of sleep disorders in the vicinity of high frequency transmitters. Biomed Tech (Berl) 2004;49:186–93. https://doi.org/10.1515/bmt.2004.035.Search in Google Scholar
225. Zwamborn, AP, Vossen, SH, van Leersum, BJ, Ouwens, MA, Makel, WN. Effects of global communication system radio-frequency fields on well being and cognitive functions of human subjects with and without subjective complaints. TNO Reports; 2003:1–89 pp. Search in Google Scholar
227. David, E, Reissenweber, J, Wojtysiak, A. On the phenomenon of electromagnetic hypersensitivity. Umweltmed Forsch Prax 2002;7:7–16.Search in Google Scholar
229. Borbely, AA, Huber, R, Graf, T, Fuchs, B, Gallmann, E, Achermann, P. Pulsed high-frequency electromagnetic field affects human sleep and sleep electroencephalogram. Neurosci Lett 1999;275:207–10. https://doi.org/10.1016/s0304-3940(99)00770-3.Search in Google Scholar
230. Braune, S, Wrocklage, C, Raczek, J, Gailus, T, Lucking, CH. Resting blood pressure increase during exposure to a radio-frequency electromagnetic field. Lancet 1998;351:1857–8. https://doi.org/10.1016/s0140-6736(98)24025-6.Search in Google Scholar
231. Radon, K, Maschke, C. Hypersensitivity to electricity. Umweltmed Forsch Prax 1998;3:125–9.Search in Google Scholar
232. Söderqvist, F, Carlberg, M, Hansson Mild, K, Hardell, L. Exposure to an 890-MHz mobile phone-like signal and serum levels of S100B and transthyretin in volunteers. Toxicol Lett 2009;189:63–6. https://doi.org/10.1016/j.toxlet.2009.04.027.Search in Google Scholar PubMed
233. Andrianome, S, Hugueville, L, de Seze, R, Selmaoui, B. Increasing levels of saliva alpha amylase in electrohypersensitive (EHS) patients. Int J Radiat Biol. 2017;93:841–8. https://doi.org/10.1080/09553002.2017.1325971.Search in Google Scholar
234. Balakrishnan, K, Murali, V, Rathika, C, Manikandan, T, Malini, RP, Kumar, RA, et al.. Hsp70 is an independent stress marker among frequent users of mobile phones. J Environ Pathol Toxicol Oncol 2014;33:339–47. https://doi.org/10.1615/jenvironpatholtoxicoloncol.2014011761.Search in Google Scholar
235. Dahmen, N, Ghezel-Ahmadi, D, Engel, A. Blood laboratory findings in patients suffering from self-perceived electromagnetic hypersensitivity (EHS). Bioelectromagnetics 2009;30:299–306. https://doi.org/10.1002/bem.20486.Search in Google Scholar
236. Markova, E, Hillert, L, Malmgren, L, Persson, BR, Belyaev, IY. Microwaves from GSM mobile telephones affect 53BP1 and gamma-H2AX foci in human lymphocytes from hypersensitive and healthy persons. Environ Health Perspect 2005;113:1172–7. https://doi.org/10.1289/ehp.7561.Search in Google Scholar
237. Belpomme, D, Campagnac, C, Irgaray, P. Reliable disease biomarkers characterizing and identifying electrohypersensitivity and multiple chemical sensitivity as two etiopathogenic aspects of a unique pathological disorder. Rev Environ Health 2015;30:251–71. https://doi.org/10.1515/reveh-2015-0027.Search in Google Scholar
238. Irigaray, P, Lebar, P, Belpomme, D. How ultrasonic cerebral tomosphygmography can contribute to the diagnosis of electrohypersensitivity. J Clin Diagn Res 2018;6:1.Search in Google Scholar
239. Irigaray, P, Caccamo, D, Belpomme, D. Oxidative stress in electrohypersensitivity self-reporting patients: results of a prospective in vivo investigation with comprehensive molecular analysis. Int J Mol Med 2018;42:1885–98. https://doi.org/10.3892/ijmm.2018.3774.Search in Google Scholar
240. Salford, LG, Brun, A, Eberhardt, JL, Persson, BR. Permeability of the blood-brain barrier induced by 915 MHz electromagnetic radiation, continuous wave and modulated at 8, 16, 50 and 200 Hz. Bioelectrochem Bioenerg 1993;30:293–301. https://doi.org/10.1016/0302-4598(93)80088-c.Search in Google Scholar
241. Nittby, H, Brun, A, Eberhardt, J, Malmgren, L, Persson, BRR, Salford, LG. Increased blood–brain barrier permeability in mammalian brain 7 days after exposure to the radiation from a GSM-900 mobile phone. Pathophysiology 2009;16:103–12. https://doi.org/10.1016/j.pathophys.2009.01.001.Search in Google Scholar PubMed
242. Tang, J, Zhang, Y, Yang, L, Chen, Q, Tan, L, Zuo, S, et al.. Exposure to 900 MHz electromagnetic fields activates the mkp-1/ERK pathway and causes blood-brain barrier damage and cognitive impairment in rats. Brain Res 2015;1601:92–101. https://doi.org/10.1016/j.brainres.2015.01.019.Search in Google Scholar PubMed
243. Leszczynski, D, Joenväärä, S, Reivinen, J, Kuokka, R. Non-thermal activation of the hsp27/p38MAPK stress pathway by mobile phone radiation in human endothelial cells: molecular mechanism for cancer – and blood-brain barrier-related effects. Differentiation 2002;70:120–9. https://doi.org/10.1046/j.1432-0436.2002.700207.x.Search in Google Scholar PubMed
244. Greco, F Technical assessment of ultrasonic cerebral tomosphygmography and new scientific evaluation of its clinical interest for the diagnosis of electrohypersensitivity and multiple chemical sensitivity. Diagnostics (Basel) 2020;10:427. https://doi.org/10.3390/diagnostics10060427.Search in Google Scholar
245. Foray, N, Colin, C, Bourguignon, M. 100 Years of individual radiosensitivity: how we have forgotten the evidence. Radiology 2012;264:627–31. https://doi.org/10.1148/radiol.12112560.Search in Google Scholar
246. Bourguignon, MH, Gisone, PA, Perez, MR, Michelin, S, Dubner, D, Di Giorgio, M, et al.. Genetic and epigenetic features in radiation sensitivity. Part I: cell signalling in radiation response. Eur J Nucl Med Mol Imag 2005; 32:229–46. https://doi.org/10.1007/s00259-004-1730-7.Search in Google Scholar
247. Bourguignon, MH, Gisone, PA, Perez, MR, Michelin, S, Dubner, D, Di Giorgio, M, et al.. Genetic and epigenetic features in radiation sensitivity. Part II: implications for clinical practice and radiation protection. Eur J Nucl Med Mol Imag 2005: 32:351–68. https://doi.org/10.1007/s00259-004-1731-6.Search in Google Scholar
249. Kelly, DA, Young, AR, McGregor, JM, Seed, PT, Potten, CS, Walker, SL. Sensitivity to sunburn is associated with susceptibility to ultraviolet radiation-induced suppression of cutaneous cell-mediated immunity. J Exp Med 2000;191:561–6. https://doi.org/10.1084/jem.191.3.561.Search in Google Scholar
250. Barnett, SB, Rott, HD, ter Haar, GR, Ziskin, MC, Maeda, K. The sensitivity of biological tissue to ultrasound. Ultrasound Med Biol 1997;23:805–12. https://doi.org/10.1016/s0301-5629(97)00027-6.Search in Google Scholar
251. Nylund, R, Leszczynski, D. Mobile phone radiation causes changes in gene and protein expression in human endothelial cell lines and the response seems to be genome‐ and proteome-dependent. Proteomics 2006;6:4769–80. https://doi.org/10.1002/pmic.200600076.Search in Google Scholar PubMed
252. Remondini, D, Nylund, R, Reivinen, J, Poulletier de Gannes, F, Veyret, B, Lagroye, I, et al.. Gene expression changes in human cells after exposure to mobile phone microwaves. Proteomics 2006;6:4745–54. https://doi.org/10.1002/pmic.200500896.Search in Google Scholar PubMed
253. Martin, C, Percevault, F, Ryder, K, Sani, E, Le Cun, JC, Zhadobov, M, et al.. Effects of radiofrequency radiation on gene expression: a study of gene expressions of human keratinocytes from different origins. Bioelectromagnetics 2020;41:552–7. https://doi.org/10.1002/bem.22287.Search in Google Scholar PubMed
254. Schmiedchen, K, Driessen, S, Oftedal, G. Methodological limitations in experimental studies on symptom development in individuals with idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF) – a systematic review. Environ Health 2019;18:88. https://doi.org/10.1186/s12940-019-0519-x.Search in Google Scholar
255. Ledent, M, Vatovez, B, Pirard, W, Bordarie, J, Prignot, N, Oftedal, G, et al.. Co‐designed exposure protocol in the study of idiopathic environmental intolerance attributed to electromagnetic fields. Bioelectromagnetics 2020;41:425–37. https://doi.org/10.1002/bem.22281.Search in Google Scholar
257. Tinnermann, A, Geuter, S, Sprenger, C, Finsterbusch, J, Büchel, C. Interactions between brain and spinal cord mediate value effects in nocebo hyperalgesia. Science 2017;358:105–8. https://doi.org/10.1126/science.aan1221.Search in Google Scholar
258. Leszczynski, D. The Grand Challenge: use of a new approach in developing policies in the area of radiation and health. Front Public Health 2014;2:50. https://doi.org/10.3389/fpubh.2014.00050.Search in Google Scholar
259. Beard, DJ, Rees, JL, Cook, JA, Rombach, I, Cooper, C, Merritt, N, et al.. Arthroscopic subacromial decompression for subacromial shoulder pain (CSAW): a multicentre, pragmatic, parallel group, placebo-controlled, three-group, randomised surgical trial. Lancet 2018;391:329–38. https://doi.org/10.1016/s0140-6736(17)32457-1.Search in Google Scholar
260. Paavola, M, Malmivaara, A, Taimela, S, Kanto, K, Inkinen, J, Kalske, J, et al.. Subacromial decompression versus diagnostic arthroscopy for shoulder impingement: randomised, placebo surgery controlled clinical trial. BMJ 2018;362:k2860. https://doi.org/10.1136/bmj.k2860.Search in Google Scholar PubMed PubMed Central
261. Bingel, U, Wanigasekera, V, Wiech, K, Mhuircheartaigh, RN, Lee, MC, Ploner, M, et al.. The effect of treatment expectation on drug efficacy: imaging the analgesic benefit of the opioid Remifentanil. Sci Transl Med 2011;3:70ra14. https://doi.org/10.1126/scitranslmed.3001244.Search in Google Scholar PubMed
262. Davis, KD, Aghaeepour, N, Ahn, AH, Angst, MS, Borsook, D, Brenton, A, et al.. Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities. Nat Rev Neurol 2020;16:381–400. https://doi.org/10.1038/s41582-020-0362-2.Search in Google Scholar PubMed PubMed Central
263. Karinen, A, Heinävaara, S, Nylund, R, Leszczynski, D. Mobile phone radiation might alter protein expression in human skin. BMC Genom 2008;9:77. https://doi.org/10.1186/1471-2164-9-77.Search in Google Scholar PubMed PubMed Central
The online version of this article offers supplementary material (https://doi.org/10.1515/reveh-2021-0038).
© 2021 Dariusz Leszczynski, published by De Gruyter, Berlin/Boston
This work is licensed under the Creative Commons Attribution 4.0 International License.