RESUMO
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.
Assuntos
Depressão , Transtorno Depressivo Maior , Dor nas Costas/prevenção & controle , Pré-Escolar , Depressão/terapia , Humanos , Ensaios Clínicos Controlados Aleatórios como Assunto , Resultado do TratamentoRESUMO
INTRODUCTION: 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. OBJECTIVE: 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. METHODS: This is an observer-masked, multicenter, pragmatic randomized controlled trial with a randomization ratio of 1:1.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. RESULTS: Between October 2015 and July 2017, we randomly assigned 210 participants (IG, n = 105; CG, n = 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 (ß = -0.19, 95% CI -0.43 to 0.05). Explorative secondary depression (4/9) and pain-related (4/6) outcomes were in part significant (p < 0.05). Health-related quality of life was significantly higher in the IG. No differences were found in work capacity. CONCLUSION: 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.
Assuntos
Terapia Cognitivo-Comportamental , Depressão , Dor nas Costas/terapia , Análise Custo-Benefício , Depressão/terapia , Humanos , Internet , Qualidade de Vida , Resultado do TratamentoRESUMO
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. Interventions: The 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 Relevance: Results 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.
Assuntos
Dor nas Costas/reabilitação , Terapia Cognitivo-Comportamental/métodos , Transtorno Depressivo/prevenção & controle , Intervenção Baseada em Internet , Adulto , Idoso , Dor nas Costas/psicologia , Doença Crônica , Comorbidade , Transtorno Depressivo/psicologia , Transtorno Depressivo Maior/prevenção & controle , Transtorno Depressivo Maior/psicologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Ensaios Clínicos Pragmáticos como Assunto , Grupos de Autoajuda , Método Simples-Cego , Resultado do TratamentoRESUMO
INTRODUCTION: Depression 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 ANALYSIS: In 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 DISSEMINATION: All 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.