JMIR Publications

ABSTRACT

Background:

Integrating stress-reduction interventions into the workplace may improve the health and well-being of employees, and there is an opportunity to leverage ubiquitous everyday work technologies to understand dynamic work contexts and facilitate stress-reduction wherever work happens. Sensing-powered just-in-time adaptive intervention (JITAI) systems have the potential to adapt and deliver tailored interventions, but such adaptation requires a comprehensive analysis of contextual and individual-level variables that may influence intervention outcomes and be leveraged to drive the system’s decision-making.

Objective:

This study aims to identify key tailoring variables that influence momentary engagement in digital stress- reduction micro-interventions to inform the design of similar JITAI systems.

Methods:

To inform the design of such dynamic adaptation, we analyzed data from 43 participants during a four-week deployment of a system that incorporates passively sensed data across everyday work devices to send just-in-time stress- reduction micro-interventions in the workplace. We evaluated 27 trait-based factors (i.e., individual characteristics), state-based factors (i.e., workplace contextual and behavioral signals, momentary stress), and intervention-related factors (i.e., location, function) across 1,585 system-initiated interventions. We built logistical regression models to identify which factors contribute to the momentary engagement, the choice of interventions, the engagement given an intervention choice, the user rating of interventions engaged, and the stress reduction from the engagement.

Results:

We found that women (OR=0.41, 95% CI [0.21, 0.77]), those with higher Neuroticism (OR=0.57, 95% CI [0.39, 0.81]), those with higher Cognitive Reappraisal skills (OR=0.69, 95% CI [0.52, 0.91]), and those that chose Calm (OR=0.43, 95% CI [0.23, 0.78]) and Address (OR=0.40, 95% CI [0.16, 0.97]) interventions were significantly less likely to experience stress reduction, while those with higher Agreeableness (OR=1.73, 95% CI [1.10, 2.76]) and those that chose prompt-based(OR=6.65, 95% CI [1.53, 36.45]) or video-based(OR=5.62, 95% CI [1.12, 34.10]) interventions were significantly more likely to experience stress reduction. We also found that work-related contextual signals such as lower Meeting Counts (OR=0.62, 95% CI [0.49, 0.78]) and lower Engagement Skewness (OR=0.64, 95% CI [0.51, 0.79]) were associated with a higher likelihood of engagement, indicating that state-based contextual factors such as being in a meeting or time of the day may matter more for engagement than efficacy. In addition, a JIT intervention that was explicitly rescheduled to a later time was more likely to be engaged (OR=1.77, 95% CI [1.32, 2.38]).

Conclusions:

JITAI systems have the potential to integrate timely support into the workplace. Based on our findings, we recommend that individual, contextual, and content-based factors be incorporated into the system for tailoring as well as for monitoring unhelpful usage behaviors across subgroups and contexts.