IMPORTANCE Depression is a frequent comorbid condition in patients with persistent back pain and is associated with substantial adverse consequences, including the risk of developing opioid use disorders. Shifting the focus from depression treatment to preventing depression might be a viable way to reduce the disease burden.OBJECTIVE To evaluate the effectiveness of a web-based self-help intervention to reduce the incidence of major depressive episode (MDE) in patients with persistent back pain. DESIGN, SETTING, AND PARTICIPANTS Prevention of Depression in Back Pain Patients (PROD-BP) was a pragmatic, observer-blinded randomized clinical trial with a parallel design conducted in Germany. Eligible adults with a diagnosis of persistent back pain and subclinical depressive symptoms, but who were depression free, were recruited either on-site or after discharge from 82 orthopedic clinics between October 1, 2015, and July 31, 2017. All analyses were conducted according to the intention-to-treat principle from October 31, 2018, to April 30, 2019. INTERVENTIONSThe intervention group received an e-coach-guided, web-based self-help intervention that was based on cognitive behavioral therapy and tailored to the needs of patients with persistent back pain. The intervention included 6 obligatory modules and 3 optional modules to be completed by participants as well as feedback from e-coaches. Both the intervention and control groups had unrestricted access to treatment as usual.MAIN OUTCOMES AND MEASURES Primary outcome was time to onset of an MDE over a 12-month period as assessed by blinded diagnostic raters using the Structured Clinical Interview for DSM-5. Secondary outcomes included depression severity, quality of life, pain intensity, pain-related disability, pain self-efficacy, work capacity, and user satisfaction assessed with a variety of instruments.RESULTS A total of 295 participants (mean [SD] age, 52.8 [7.7] years; 184 women [62.4%]) were recruited and randomized to either the intervention group (n = 149) or control group (n = 146). The intervention reduced the risk of MDE onset by 52% (hazard ratio, 0.48; 95% CI, 0.28-0.81; P < .001). Twenty-one participants (14.1%) in the intervention group and 41 participants (28.1%) in the control group experienced an MDE over the 12-month period. The number needed to treat to prevent 1 new case of MDE was 2.84 (95% CI, 1.79-9.44). CONCLUSIONS AND RELEVANCEResults of this trial showed that among patients with persistent back pain, depression can be prevented by a guided web-based self-help intervention in addition to treatment as usual. This finding suggests that using a scalable digital approach to integrate psychological treatment into routine pain management is feasible.TRIAL REGISTRATION German Clinical Trials Register Identifier: DRKS00007960

<b><i>Introduction:</i></b> There is neither strong evidence on effective treatments for patients with chronic back pain (CBP) and depressive disorder nor sufficiently available mental health care offers. <b><i>Objective:</i></b> The aim is to assess the effectiveness of internet- and mobile-based interventions (IMI) as a scalable approach for treating depression in a routine care setting. <b><i>Methods:</i></b> This is an observer-masked, multicenter, pragmatic randomized controlled trial with a randomization ratio of 1:1.<b><i></i></b>Patients with CBP and diagnosed depressive disorder (mild to moderate severity) were recruited from 82 orthopedic rehabilitation clinics across Germany. The intervention group (IG) received a guided depression IMI tailored to CBP next to treatment-as-usual (TAU; including medication), while the control group (CG) received TAU. The primary outcome was observer-masked clinician-rated Hamilton depression severity (9-week follow-up). The secondary outcomes were: further depression outcomes, pain-related outcomes, health-related quality of life, and work capacity. Biostatistician blinded analyses using regression models were conducted by intention-to-treat and per protocol analysis. <b><i>Results:</i></b> Between October 2015 and July 2017, we randomly assigned 210 participants (IG, <i>n</i> = 105; CG, <i>n</i> = 105), mostly with only a mild pain intensity but substantial pain disability. No statistically significant difference in depression severity between IG and CG was observed at the 9-week follow-up (β = –0.19, 95% CI –0.43 to 0.05). Explorative secondary depression (4/9) and pain-related (4/6) outcomes were in part significant (<i>p</i> &#x3c; 0.05). Health-related quality of life was significantly higher in the IG. No differences were found in work capacity. <b><i>Conclusion:</i></b> The results indicate that an IMI for patients with CBP and depression in a routine care setting has limited impact on depression. Benefits in pain and health-related outcomes suggest that an IMI might still be a useful measure to improve routine care.

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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.

BackgroundReducing the disease burden of major depressive disorder (MDD) is of major public health relevance. The prevention of depression is regarded as one possible approach to reach this goal. People with multiple risk factors for MDD such as chronic back pain and subthreshold depressive symptoms may benefit most from preventive measures. The Internet as intervention setting allows for scaling up preventive interventions on a public mental health level.MethodsThis study is a multicenter pragmatic randomized controlled trial (RCT) of parallel design aiming to investigate the (cost-) effectiveness of an Internet- and mobile-based intervention (IMI) for the prevention of depression in chronic back pain patients (PROD-BP) with subthreshold depressive symptoms. eSano BackCare-DP is a guided, chronic back pain-specific depression prevention intervention based on cognitive behavioral therapy (CBT) principles comprising six weekly plus three optional modules and two booster sessions after completion of the intervention. Trained psychologists provide guidance by sending feedback messages after each module. A total of 406 patients with chronic back pain and without a depressive disorder at baseline will be recruited following orthopedic rehabilitation care and allocated to either intervention or treatment-as-usual (TAU). Primary patient-relevant endpoint of the trial is the time to onset of MDD measured by the telephone-administered Structured Clinical Interview for DSM (SCID) at baseline and 1-year post-randomization. Key secondary outcomes are health-related quality of life, depression severity, pain intensity, pain-related disability, ability to work, intervention satisfaction and adherence as well as side effects of the intervention. Online assessments take place at baseline and 9 weeks as well as 6 and 12 months post-randomization. Cox regression survival analysis will be conducted to estimate hazard ratio at 12-month follow-up. Moreover, an economic analysis will be conducted from a societal and public health perspective.DiscussionThis is the first study examining an IMI for depression prevention in a sample of chronic pain patients. If this implementation of a depression prevention IMI into orthopedic aftercare proves effective, the intervention could be integrated into routine care with minimal costs and extended for use with other chronic diseases. Results will have implications for researchers, health care providers and public health policy makers.Trial registrationThe trial is registered at the WHO International Clinical Trials Registry Platform via the German Clinical Studies Trial Register (DRKS): DRKS00007960. Registered 12 August 2015.

IntroductionDepression often co-occurs with chronic back pain (CBP). Internet and mobile-based interventions (IMIs) might be a promising approach for effectively treating depression in this patient group. In the present study, we will evaluate the effectiveness and cost-effectiveness of a guided depression IMI for individuals with CBP (eSano BackCare-D) integrated into orthopaedic healthcare.Methods and analysisIn this multicentre randomised controlled trial of parallel design, the groups eSano BackCare-D versus treatment as usual will be compared. 210 participants with CBP and diagnosed depression will be recruited subsequent to orthopaedic rehabilitation care. Assessments will be conducted prior to randomisation and 9 weeks (post-treatment) and 6 months after randomisation. The primary outcome is depression severity (Hamilton Rating Scale for Depression-17). Secondary outcomes are depression remission and response, health-related quality of life, pain intensity, pain-related disability, self-efficacy and work capacity. Demographic and medical variables as well as internet affinity, intervention adherence, intervention satisfaction and negative effects will also be assessed. Data will be analysed on an intention-to-treat basis with additional per-protocol analyses. Moreover, a cost-effectiveness and cost-utility analysis will be conducted from a societal perspective after 6 months.Ethics and disseminationAll procedures are approved by the ethics committee of the Albert-Ludwigs-University of Freiburg and the data security committee of the German Pension Insurance (Deutsche Rentenversicherung). The results will be published in peer-reviewed journals and presented on international conferences.Trial registration number DRKS00009272; Pre-results.

Introduction. Diabetes mellitus type 1 and type 2 are linked to higher prevalence and occurrences of depression. Internet-based depression- and diabetes-specific cognitive behavioral therapies (CBT) can be effective in reducing depressive symptom severity and diabetes-related emotional distress. The aim of the study was to test whether disease-specific severity indicators moderate the treatment outcome in a 6-week minimally guided web-based self-help intervention on depression and diabetes (GET.ON Mood Enhancer Diabetes (GET.ON M.E.D.)) and to determine its effectiveness in a nonsuicidal severely depressed subgroup. Methods. Randomized controlled trial- (RCT-) based data (N=253) comparing GET.ON M.E.D. to an online psychoeducation control group was used to test disease-specific severity indicators as predictors/moderators of a treatment outcome. Changes in depressive symptom severity and treatment response were examined in a nonsuicidal severely depressed subgroup (CES−D>40; N=40). Results. Major depressive disorder diagnosis at the baseline (pprf6=0.01), higher levels of depression (Beck Depression Inventory II; pprpo=0.00; pprf6=0.00), and lower HbA1c (pprpo=0.04) predicted changes in depressive symptoms. No severity indicator moderated the treatment outcome. Severely depressed participants in the intervention group showed a significantly greater reduction in depressive symptom severity (dprpo=2.17, 95% Confidence Interval (CI): 1.39-2.96) than the control condition (dprpo=0.92; 95% CI: 0.001-1.83), with a between-group effect size of dprpo=1.05 (95% CI: 0.11-1.98). Treatment response was seen in significantly more participants in the intervention (4/20; 20%) compared to the control group (0/20, 0%; χ2 2N=40=4.44; p<0.02). At the 6-month follow-up, effects were maintained for depressive symptom reduction (dpr6f=0.71; 95% CI: 0.19-1.61) but not treatment response. Conclusion. Disease-specific severity indicators were not related to a differential effectiveness of guided self-help for depression and diabetes. Clinical meaningful effects were observed in nonsuicidal severely depressed individuals, who do not need to be excluded from web-based guided self-help. However, participants should be closely monitored and referred to other treatment modalities in case of nonresponse.

Background Depression is a common comorbid condition in individuals with chronic back pain (CBP), leading to poorer treatment outcomes and increased medical complications. Digital interventions have demonstrated efficacy in the prevention and treatment of depression; however, high dropout rates are a major challenge, particularly in clinical settings. Objective This study aims to identify the predictors of dropout in a digital intervention for the treatment and prevention of depression in patients with comorbid CBP. We assessed which participant characteristics may be associated with dropout and whether intervention usage data could help improve the identification of individuals at risk of dropout early on in treatment. Methods Data were collected from 2 large-scale randomized controlled trials in which 253 patients with a diagnosis of CBP and major depressive disorder or subclinical depressive symptoms received a digital intervention for depression. In the first analysis, participants’ baseline characteristics were examined as potential predictors of dropout. In the second analysis, we assessed the extent to which dropout could be predicted from a combination of participants’ baseline characteristics and intervention usage variables following the completion of the first module. Dropout was defined as completing <6 modules. Analyses were conducted using logistic regression. Results From participants’ baseline characteristics, lower level of education (odds ratio [OR] 3.33, 95% CI 1.51-7.32) and both lower and higher age (a quadratic effect; age: OR 0.62, 95% CI 0.47-0.82, and age2: OR 1.55, 95% CI 1.18-2.04) were significantly associated with a higher risk of dropout. In the analysis that aimed to predict dropout following completion of the first module, lower and higher age (age: OR 0.60, 95% CI 0.42-0.85; age2: OR 1.59, 95% CI 1.13-2.23), medium versus high social support (OR 3.03, 95% CI 1.25-7.33), and a higher number of days to module completion (OR 1.05, 95% CI 1.02-1.08) predicted a higher risk of dropout, whereas a self-reported negative event in the previous week was associated with a lower risk of dropout (OR 0.24, 95% CI 0.08-0.69). A model that combined baseline characteristics and intervention usage data generated the most accurate predictions (area under the receiver operating curve [AUC]=0.72) and was significantly more accurate than models based on baseline characteristics only (AUC=0.70) or intervention usage data only (AUC=0.61). We found no significant influence of pain, disability, or depression severity on dropout. Conclusions Dropout can be predicted by participant baseline variables, and the inclusion of intervention usage variables may improve the prediction of dropout early on in treatment. Being able to identify individuals at high risk of dropout from digital health interventions could provide intervention developers and supporting clinicians with the ability to intervene early and prevent dropout from occurring.