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
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,025 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,003 |
| Méta-épidémiologie (sens large) | 0,012 | 0,006 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,062 | 0,009 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».