Efficacy of a Mobile App–Based Behavioral Intervention (DRIVEN) to Help Individuals With Unemployment-Related Emotional Distress Return to Work: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Employment plays an important role in the maintenance of mental and physical health. Losing a job creates emotional distress, which can, in turn, interfere with effective job seeking. Thus, a program for job seekers that provides support for both the logistics of job seeking as well as emotional distress may help people find employment and improve emotional well-being. OBJECTIVE: This study aims to test the efficacy of the 6-week intervention for job seekers in a randomized controlled trial. METHODS: This is a parallel-assignment randomized control trial comparing a 6-week return-to-work intervention versus job seeking as usual for a stratified sample of job seekers (n=150). The intervention will be delivered through a mobile phone app and scheduled video counseling sessions with a job coach. Assessments will be taken weekly during the intervention as well as 8 and 16 weeks later. The intervention and control group procedures will be administered remotely, allowing the study to take place in several regions of the United States. Eligible participants will be adults aged 18 to 65 years, currently unemployed, and actively searching for work. Participants will be recruited from 7 major metropolitan areas in the United States using online advertisements on Craigslist. The primary outcome measure is the Job Search Behavior Scale, which has 2 subscales, preparatory job search behavior and active job search behavior. Employment status will also be assessed throughout the trial. A mixed-model regression analysis will be used to compare job searching behavior in the intervention group versus the control group. A time-to-event analysis (ie, survival analysis) will be used to compare employment status in the 2 experimental groups. Secondary outcomes will also be evaluated, including job search self-efficacy and mental health-related outcomes such as anxiety and depression. RESULTS: This study started on August 7, 2023, and as of June 2024, we have enrolled 140 participants. Enrollment began in August 2023 and will conclude by October 2024. Half of the participants (75/150, 50%) will be assigned to the intervention arm while the other half (75/150, 50%) will be assigned to the control arm, job seeking as usual. CONCLUSIONS: The findings from this study will determine the efficacy of a mobile app-based intervention that uses both job training and psychological techniques on job seeking and employment outcomes. This first trial of Distress Return-to-Work Intervention (DRIVEN) will provide important information about blended support techniques for unemployed individuals, determine the usefulness of mobile apps to address large-scale mental health outcomes, and improve our understanding of the relationship between depression and unemployment status. TRIAL REGISTRATION: ClinicalTrials.gov NCT06026280; https://clinicaltrials.gov/study/NCT06026280. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/62715.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.024 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.062 | 0.009 |
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 source (direct Gemma or distilled Codex), 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".