Comparison of RCT eligible and ineligible patients on demographics and medical comorbidity.

<p><i>NYHA, New York Heart Association; RCT, randomized controlled trial.</i></p>*<p><i>p<.05.</i></p

Psychiatric RCT ineligibility in heart failure patients referred for psychiatric care according to depression status.

<p><i>RCT, randomized controlled trial.</i></p>*<p><i>p<.05.</i></p

Proportion of standard RCT exclusion criteria met by HF patients according to depression status (yes vs. no).

<p>Proportion of standard RCT exclusion criteria met by HF patients according to depression status (yes vs. no).</p

Flow chart of patients through the study.

<p>Flow chart of patients through the study.</p

Comparison of RCT eligible and ineligible patients on clinical psychiatric characteristics.

<p><i>GAD, Generalized Anxiety Disorder; PHQ, Patient Health Questionnaire; RCT, randomized controlled trial.</i></p>*<p><i>p<.05.</i></p>a<p><i>Medical records depression and medical records anxiety inclusive of diagnoses that conflicts with psychologist SCID assessment. Medical records missing depression or anxiety diagnosis evaluates medical record comorbidity lists and hospital discharge summaries in preceding 6 months prior to assessment with the SCID diagnosis.</i></p

Prevalence of depression and anxiety disorders in heart failure patients referred for psychiatric care.

<p><i>RCT, randomized controlled trial; SCID, Structured Clinical Interview.</i></p>*<p><i>p<.05.</i></p

Additional file 1: of Effectiveness and acceptance of a web-based depression intervention during waiting time for outpatient psychotherapy: study protocol for a randomized controlled trial

SPIRIT-checklist. (DOC 162 kb

Table_1_Unveiling mechanisms of change in digital interventions for depression: Study protocol for a systematic review and individual participant data meta-analysis.DOCX

IntroductionThe efficacy and effectiveness of digital interventions for depression are both well-established. However, precise effect size estimates for mediators transmitting the effects of digital interventions are not available; and integrative insights on the specific mechanisms of change in internet- and mobile-based interventions (IMIs)—as related to key features like delivery type, accompanying support and theoretical foundation—are largely pending.ObjectiveWe will conduct a systematic review and individual participant data meta-analysis (IPD-MA) evaluating the mediators associated with therapeutic change in various IMIs for depression in adults.MethodsWe will use three electronic databases (i.e., Embase, Medline/PubMed, PsycINFO) as well as an already established database of IPD to identify relevant published and unpublished studies. We will include (1) randomized controlled trials that examine (2) mediators of (3) guided and unguided (4) IMIs with (5) various theoretical orientations for (6) adults with (7) clinically relevant symptoms of depression (8) compared to an active or passive control condition (9) with depression symptom severity as primary outcome. Study selection, data extraction, as well as quality and risk of bias (RoB) assessment will be done independently by two reviewers. Corresponding authors of eligible primary studies will be invited to share their IPD for this meta-analytic study. In a 1-stage IPD-MA, mediation analyses (e.g., on potential mediators like self-efficacy, emotion regulation or problem solving) will be performed using a multilevel structural equation modeling approach within a random-effects framework. Indirect effects will be estimated, with multiple imputation for missing data; the overall model fit will be evaluated and statistical heterogeneity will be assessed. Furthermore, we will investigate if indirect effects are moderated by different variables on participant- (e.g., age, sex/gender, symptom severity), study- (e.g., quality, studies evaluating the temporal ordering of changes in mediators and outcomes), and intervention-level (e.g., theoretical foundation, delivery type, guidance).DiscussionThis systematic review and IPD-MA will generate comprehensive information on the differential strength of mediators and associated therapeutic processes in digital interventions for depression. The findings might contribute to the empirically-informed advancement of psychotherapeutic interventions, leading to more effective interventions and improved treatment outcomes in digital mental health. Besides, with our novel approach to mediation analyses with IPD-MA, we might also add to a methodological progression of evidence-synthesis in psychotherapy process research.Study registration with Open Science Framework (OSF)https://osf.io/md7pq/.</p

Validation of the Mobile Application Rating Scale (MARS)

Background: Mobile health apps (MHA) have the potential to improve health care. The commercial MHA market is rapidly growing, but the content and quality of available MHA are unknown. Instruments for the assessment of the quality and content of MHA are highly needed. The Mobile Application Rating Scale (MARS) is one of the most widely used tools to evaluate the quality of MHA. Only few validation studies investigated its metric quality. No study has evaluated the construct validity and concurrent validity. Objective: This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS. Methods: Data was pooled from 15 international app quality reviews to evaluate the metric properties of the MARS. The MARS measures app quality across four dimensions: Engagement, functionality, aesthetics and information quality. Construct validity was evaluated by assessing related competing confirmatory models by confirmatory factor analysis (CFA). Noncentrality (RMSEA), incremental (CFI, TLI) and residual (SRMR) fit indices were used to evaluate the goodness of fit. As a measure of concurrent validity, the correlations to another quality assessment tool (ENLIGHT) were investigated. Reliability was determined using Omega. Objectivity was assessed by intra-class correlation. Results In total, MARS ratings from 1,299 MHA covering 15 different health domains were included. Confirmatory factor analysis confirmed a bifactor model with a general factor and a factor for each dimension (RMSEA = 0.074, TLI = 0.922, CFI = 0.940, SRMR = 0.059). Reliability was good to excellent (Omega 0.79 to 0.93). Objectivity was high (ICC = 0.82). MARS correlated with ENLIGHT (ps<.05). Conclusion: The metric evaluation of the MARS demonstrated its suitability for the quality assessment. As such, the MARS could be used to make the quality of MHA transparent to health care stakeholders and patients. Future studies could extend the present findings by investigating the re-test reliability and predictive validity of the MARS