Accepted for/Published in: JMIR Formative Research
Date Submitted: Jan 9, 2025
Date Accepted: Jul 5, 2025
Preventive Stress Management mHealth Intervention for Healthcare Workers: Factorial Experiment to Optimize Intervention Components
ABSTRACT
Background:
Work stress is a prevalent risk factor for health problems such as burnout and cardiovascular disease. Mobile health interventions – digital interventions delivered via mobile devices - are a promising way to combat this issue, offering the possibility of scalable programs that are easily accessible. A wide range of evidence-based stress management techniques can be used in the digital context to mitigate the negative consequences of work stress. However, evidence is needed to support what specific intervention content is most effective at preventing symptoms of stress-related health problems.
Objective:
The primary aim of the research was to identify which digital intervention components are most effective at preventing symptoms of stress-related health problems. This may inform future intervention development and provide valuable insights for how to optimize intervention effects.
Methods:
This study tested five digital intervention components that may improve stress management among workers – Engagement, Demands, Control, Journaling, and Psychoeducation. In a factorial experimental study, Swedish healthcare workers (N = 283) tested different versions of the intervention containing all possible combinations of these components. Stress-related health outcomes such as burnout, anxiety, and depression were measured using questionnaires immediately before, immediately after, and one month after the end of the intervention.
Results:
The most promising intervention effects were observed when the Demands and Control components were present together in the intervention. Including these components led to an increase in social support (β = 0.68, p < 0.001) and job crafting (β = 0.41, p = 0.063) during the intervention, as well as a decrease in symptoms of emotional exhaustion (β = -0.50, p = 0.005), burnout (β = -0.54, p = 0.004), and anxiety (β = -0.44, p = 0.035) after the intervention.
Conclusions:
Results indicate that components aiding self-insight should be integrated with components providing actionable advice for optimal intervention effects. Results from this optimization study may inform the development of digital stress management interventions to be tested in future randomized controlled trials. Clinical Trial: NCT04719351
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