Accepted for/Published in: JMIR Formative Research
Date Submitted: Aug 5, 2022
Date Accepted: Apr 14, 2023
Feasibility and preliminary efficacy of digital interventions for depressive symptoms in working adults: a multi-arm randomized pilot trial
ABSTRACT
Background:
Depressive symptoms are highly prevalent and have broad ranging negative implications. Digital interventions are increasingly available in a workplace context, but supporting evidence is limited.
Objective:
This study evaluated the feasibility, acceptability and preliminary efficacy of three digital interventions for depressive symptoms in a sample of UK based working adults experiencing subthreshold or mild to moderate symptoms.
Methods:
This was a parallel, multi-arm, pilot randomised controlled trial. Participants were allocated to one of three digital interventions or a wait list control group and had three weeks to complete 6-8 short self-guided sessions. Online assessments were conducted at weeks 0, 3 and 7. The interventions are available on the Unmind platform and draw on evidence based psychological therapies. Feasibility and acceptability were assessed using engagement and feedback data, efficacy outcomes were assessed using validated measures of mental health, wellbeing, and functioning, and linear mixed models.
Results:
405 participants were randomised and 92% were retained. 97% initiated their allocated intervention and 67% completed all sessions. 81% rated the quality as excellent or good, and 80% were satisfied or very satisfied. All groups showed significant, maintained improvements in wellbeing, functioning, and depressive and anxiety symptoms vs control (p<0.05). Hedges g effect sizes were predominantly in the small to medium range.
Conclusions:
All interventions were feasible and acceptable, and findings indicate that their use can improve depressive symptoms, wellbeing and functioning. Pre-defined criteria for a definitive trial were met. Clinical Trial: The study protocol was pre-registered on ISRCTN (registration number ISRCTN13067492) and the Open Science Framework (https://osf.io/).
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