Randomized Controlled Trial

Background: Depression is highly prevalent in the working population and is associated with significant loss of workdays; however, access to evidence- based treatment is limited. Objective: This study evaluated the effectiveness of a Web-based intervention in reducing mild to moderate depression and sickness absence. Methods: In an open-label randomized controlled trial, participants were recruited from a large-scale statutory health insurance and were assigned to two groups. The intervention group had access to a 12 week Web-based program consisting of structured interactive sessions and therapist support upon request. The wait-list control group had access to unguided Web- based psycho-education. Depressive symptoms were self-assessed at baseline, post-treatment, and follow-up (12 weeks after treatment) using the Patient Health Questionnaire (PHQ-9) and Beck Depression Inventory (BDI-II) as primary outcome measures. Data on sickness absence was retrieved from health insurance records. Intention-to-treat (ITT) analysis and per-protocol (PP) analysis were performed. Results: Of the 180 participants who were randomized, 88 completed the post-assessment (retention rate: 48.8%, 88/180). ITT analysis showed a significant between-group difference in depressive symptoms during post- treatment in favor of the intervention group, corresponding to a moderate effect size (PHQ-9: d=0.55, 95% CI 0.25-0.85, P<.001, and BDI-II: d=0.41, CI 0.11-0.70, P=.004). PP analysis partially supported this result, but showed a non-significant effect on one primary outcome (PHQ-9: d=0.61, 95% CI 0.15-1.07, P=.04, and BDI-II: d=0.25 95% CI −0.18 to 0.65, P=.37). Analysis of clinical significance using reliable change index revealed that significantly more participants who used the Web-based intervention (63%, 63/100) responded to the treatment versus the control group (33%, 27/80; P<.001). The number needed to treat (NNT) was 4.08. Within both groups, there was a reduction in work absence frequency (IG: −67.23%, P<.001, CG: −82.61%, P<.001), but no statistical difference in sickness absence between groups was found (P=.07). Conclusions: The Web-based intervention was effective in reducing depressive symptoms among adults with sickness absence. As this trial achieved a lower power than calculated, its results should be replicated in a larger sample. Further validation of health insurance records as an outcome measure for eHealth trials is needed. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN): 02446836; http://www.isrctn.com/ISRCTN02446836 (Archived by WebCite at http://www.webcitation.org/6jx4SObnw

Effectiveness of Telephone-Based Health Coaching for Patients with Chronic Conditions: A Randomised Controlled Trial

<div><p>Background</p><p>Chronic diseases, like diabetes mellitus, heart disease and cancer are leading causes of death and disability. These conditions are at least partially preventable or modifiable, e.g. by enhancing patients’ self-management. We aimed to examine the effectiveness of telephone-based health coaching (TBHC) in chronically ill patients.</p><p>Methods and Findings</p><p>This prospective, pragmatic randomized controlled trial compares an intervention group (IG) of participants in TBHC to a control group (CG) without TBHC. Endpoints were assessed two years after enrolment. Three different groups of insurees with 1) multiple conditions (chronic campaign), 2) heart failure (heart failure campaign), or 3) chronic mental illness conditions (mental health campaign) were targeted. The telephone coaching included evidence-based information and was based on the concepts of motivational interviewing, shared decision-making, and collaborative goal setting. Patients received an average of 12.9 calls. Primary outcome was time from enrolment until hospital readmission within a two-year follow-up period. Secondary outcomes comprised the probability of hospital readmission, number of daily defined medication doses (DDD), frequency and duration of inability to work, and mortality within two years. All outcomes were collected from routine data provided by the statutory health insurance. As informed consent was obtained after randomization, propensity score matching (PSM) was used to minimize selection bias introduced by decliners. For the analysis of hospital readmission and mortality, we calculated Kaplan-Meier curves and estimated hazard ratios (HR). Probability of hospital readmission and probability of death were analysed by calculating odds ratios (OR). Quantity of health service use and inability to work were analysed by linear random effects regression models. PSM resulted in patient samples of 5,309 (IG: 2,713; CG: 2,596) in the chronic campaign, of 660 (IG: 338; CG: 322) in the heart failure campaign, and of 239 (IG: 101; KG: 138) in the mental health campaign. In none of the three campaigns, there were significant differences between IG and CG in time until hospital readmission. In the chronic campaign, the probability of hospital readmission was higher in the IG than in the CG (OR = 1.13; p = 0.045); no significant differences could be found for the other two campaigns. In the heart failure campaign, the IG showed a significantly reduced number of hospital admissions (-0.41; p = 0.012), although the corresponding reduction in the number of hospital days was not significant. In the chronic campaign, the IG showed significantly increased number of DDDs. Most striking, there were significant differences in mortality between IG and CG in the chronic campaign (OR = 0.64; p = 0.005) as well as in the heart failure campaign (OR = 0.44; p = 0.001).</p><p>Conclusions</p><p>While TBHC seems to reduce hospitalization only in specific patient groups, it may reduce mortality in patients with chronic somatic conditions. Further research should examine intervention effects in various subgroups of patients, for example for different diagnostic groups within the chronic campaign, or duration of coaching.</p><p>Trial Registration</p><p>German Clinical Trials Register <a href="https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00000584" target="_blank">DRKS00000584</a></p></div

Effects of telephone-based health coaching on healthcare utilization: Results of linear fixed effects difference-in-difference regression models (per protocol).

<p>Effects of telephone-based health coaching on healthcare utilization: Results of linear fixed effects difference-in-difference regression models (per protocol).</p

Sample Characteristics at Baseline, Pre- and Post-Matching.

<p>Sample Characteristics at Baseline, Pre- and Post-Matching.</p

Descriptive statistics of health care utilization (Post-Matching).

<p>Descriptive statistics of health care utilization (Post-Matching).</p

Effects of telephone-based health coaching on healthcare utilization: Results of linear fixed effects difference-in-difference regression models (ITT-II).

<p>Effects of telephone-based health coaching on healthcare utilization: Results of linear fixed effects difference-in-difference regression models (ITT-II).</p

Effects of telephone-based health coaching on mortality.

<p>Kaplan-Meier survival curves (red curve = intervention group; blue curve = control group).</p