A Web- and Mobile-Based Intervention for Comorbid, Recurrent Depression in Patients With Chronic Back Pain on Sick Leave (Get.Back): Pilot Randomized Controlled Trial on Feasibility, User Satisfaction, and Effectiveness
Bibliographic record
Abstract
Background Chronic back pain (CBP) is linked to a higher prevalence and higher occurrence of major depressive disorder (MDD) and can lead to reduced quality of life. Unfortunately, individuals with both CBP and recurrent MDD are underidentified. Utilizing health care insurance data may provide a possibility to better identify this complex population. In addition, internet- and mobile-based interventions might enhance the availability of existing treatments and provide help to those highly burdened individuals. Objective This pilot randomized controlled trial investigated the feasibility of recruitment via the health records of a German health insurance company. The study also examined user satisfaction and effectiveness of a 9-week cognitive behavioral therapy and Web- and mobile-based guided self-help intervention Get.Back in CBP patients with recurrent MDD on sick leave compared with a waitlist control condition. Methods Health records from a German health insurance company were used to identify and recruit participants (N=76) via invitation letters. Study outcomes were measured using Web-based self-report assessments at baseline, posttreatment (9 weeks), and a 6-month follow-up. The primary outcome was depressive symptom severity (Center for Epidemiological Studies–Depression); secondary outcomes included anxiety (Hamilton Anxiety and Depression Scale), quality of life (Assessment of Quality of Life), pain-related variables (Oswestry Disability Index, Pain Self-Efficacy Questionnaire, and pain intensity), and negative effects (Inventory for the Assessment of Negative Effects of Psychotherapy). Results The total enrollment rate with the recruitment strategy used was 1.26% (76/6000). Participants completed 4.8 modules (SD 2.6, range 0-7) of Get.Back. The overall user satisfaction was favorable (mean Client Satisfaction Questionnaire score=24.5, SD 5.2). Covariance analyses showed a small but statistically significant reduction in depressive symptom severity in the intervention group (n=40) at posttreatment compared with the waitlist control group (n=36; F1,76=3.62, P=.03; d=0.28, 95% CI −0.17 to 0.74). Similar findings were noted for the reduction of anxiety symptoms (F1,76=10.45; P=.001; d=0.14, 95% CI −0.31 to 0.60) at posttreatment. Other secondary outcomes were nonsignificant (.06≤P≤.44). At the 6-month follow-up, the difference between the groups with regard to reduction in depressive symptom severity was no longer statistically significant (F1,76=1.50, P=.11; d=0.10, 95% CI −0.34 to 0.46). The between-group difference in anxiety at posttreatment was maintained to follow-up (F1,76=2.94, P=.04; d=0.38, 95% CI −0.07 to 0.83). There were no statistically significant differences across groups regarding other secondary outcomes at the 6-month follow-up (.08≤P≤.42). Conclusions These results suggest that participants with comorbid depression and CBP on sick leave may benefit from internet- and mobile-based interventions, as exemplified with the positive user satisfaction ratings. The recruitment strategy via health insurance letter invitations appeared feasible, but more research is needed to understand how response rates in untreated individuals with CBP and comorbid depression can be increased. Trial Registration German Clinical Trials Register DRKS00010820; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00010820.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".