Stefan Elbers

33 Evaluating IMPT programmes over time All remaining modalities were coded as 'other'. The description of each of the modalities and the classification were registered. A similar process was performed for healthcare providers. The following professions were coded as 'physician': occupational physician, rehabilitation physician, general practitioner and not otherwise specified physician. Other physician specialists (e.g. psychiatrist, orthopedic surgeon, anesthesiologist) who were mainly involved in a consulting instead of a coordinating role were coded as 'other'. Disciplines such as clinical psychologists, general psychologists and behavioural therapists were classified as 'psychologist'. Physical therapists and physiotherapists were classified as 'physical therapist'. Social workers and social counselors were classified as 'social worker'. Occupational therapists and nurses were classified accordingly. To assess to what extent treatment programmes aligned their programme with individual patient characteristics and preferences (i.e. tailoring), we classified each programme into low, medium or high tailoring. We defined low tailoring as any form of personalized goal- setting, because this would allow patients to relate treatment content and progress to their personal situation. All studies received at minimum a 'low' tailoring classification because we assumed that all interdisciplinary programmes include some form of collaborative goal- setting at the start of treatment. We classified programmes as medium tailoring, when they selected or optionally provided specific treatment components based on patient-specific needs or preferences. High tailoring involved a fully personalized treatment programme, with varying duration and treatment activities and modules, based on each patient's clinical assessment. Main data analysis. In addition to pain intensity, we included seven key outcome measures as outcomes in this analysis, divided over three domains: physical health,mental health and social health. For physical health, we included physical functioning and pain interference. We extracted of the outcomes depression, anxiety, anger, and self-efficacy beliefs within the mental health domain. For social health we only included social functioning. All outcomes were defined in the study protocol. For each of these outcomes that were present within a cohort, we used the available data to calculate effect sizes for pre-post, post-follow-up and pre-follow-up contrasts. To calculate effect sizes, we used the method of Becker et al's standardized mean change (SMC) (1988), with the modifications that were suggested by Morris (2000). The model assumes that the outcomes are normally distributed at both time points, with separate means but equal variances. Furthermore, the model corrects for a pre-post within-group correlation. Because we did not have access to the original data of the included cohorts, we imputed this value (Lipsey & Wilson, 2001). For all studies, we imputed the median correlation (r = .59) of a meta-analysis that investigated the range of within-group correlation values in active treatment groups (Balk et al., 2012). This value is comparable to other studies that have imputed within-group meta-analyses (Clond, 2016;