This longitudinal study investigated the pattern of change in pain intensity, disability, and depression in 232 chronic pain patients who were followed up for 2 years since pain onset. Most studies that have investigated changes in these variables over time have used participants who had already been in pain for more than 3 months. Few studies have followed up individuals from the acute phase onward and such studies used traditional statistical methods that cannot identify transition points over time or measure inter-individual variability.
We followed up individuals with chronic pain from pain onset up to 18 months and we examined their pain intensity, disability and depression trajectories using a modelling approach that allows to account for between and within-individual variability. We compared three patterns of change based on theoretical criterions: a simple linear growth model; a spline model with a 3-month transition point; and a spline model with a 6-month transition point. Time with pain was selected as time metric to characterise the change in these variables in the transition from acute to chronic pain. Sex and age differences were also examined.
The results showed that the pain intensity trajectory was best represented by the spline model with a 3-month transition point, whereas disability and depression were best explained by linear growth models. There were sex differences at intercept level in all the models. There were age differences at baseline for pain intensity. No sex or age differences were found for the slope.
Pain intensity decreased in the first 3 months but underwent no further change. Disability and depression slightly but constantly decreased over time. Although women and older individuals are more likely to report higher pain intensity or pain-related disability in the first three months with pain, no differences by sex or age appear to be associated with the changes in pain intensity, depression and disability through the process of chronification.
Our findings suggest that pain chronification could be considered a continuous process and contribute to the ongoing discussion on the utility of standard classifications of pain as acute or chronic from a clinical point of view. Clinical and intervention decisions based in these standard classifications should consider the differences in the trajectories of pain related variables over time. In addition, this article illustrates a statistical procedure that can be of utility to pain researchers.
DOI of refers to article: http://dx.doi.org/10.1016/j.sjpain.2017.05.008.
Ethical issues: This research project was approved and registered by the Carlos Haya Hospital Ethics Committee. Informed consent was obtained prior to data collection.
Conflict of interest: None declared.
This study was supported by grants from the Spanish Ministry of Science and Innovation (PSI2008-01803/PSIC and PSI2012-32662); and the Regional Government of Andalusia (HUM-566; P07-SEJ- 3067).
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Let Y be a variable measured on an individual (i =1 to N) over time (t = 1 to T), where Y is pain intensity, depression, and disability in each model, respectively; time is time with pain.
The first model is a linear growth model, which can be written as
where Yit is the observed score on individual i at measurement t, yi0 is the latent initial level score of an individual i, yis is a latent score of individual i, representing the slope or change in the individual over time, timeit is the observed time with pain of individual i at measurement t, and eit is the latent error score of individual i at measurement t. This model includes sources of individual differences in the level and slope, as
where the level and slope scores have fixed group means (μ0 and μs and residuals (ei0 and eis), and these residuals have variance components ( and σ0s; u ~ N(0, G)). Similarly, the error term associated with the within-person residual eit also has a zero mean and a variance term , (ei ~ N(0, R)).
The next model allows a change of direction in the trajectory at a specific point in time (i.e., a linear spline model). Two linear spline models with two pre-determined transition points were investigated; one with a transition point at 3 months with pain (according to the standard definition of chronic pain), and the second at 6 months with pain (as suggested by Philips and Grant ). These models can be written as
where time1 and time2 represent the time with pain before and after the transition point, yis1 and yis2 are the regression coefficients associated with the linear changes before and after that transition point, and yi0 represents the score at that point. This model has been found to be useful to evaluate hypotheses on differential rates of change across various periods of time. For further information on these models see Kail and Ferrer  and McArdle et al. .
Appendix B. Supplementary data
Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.sjpain.2017.02.009.
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