Background: Internet interventions for mental health concerns are known to be effective, but how can developing
technology be utilised to improve engagement and augment the effectiveness of these programs? One option
might be to incorporate feedback about the user's physiological state into the program, via wearable sensors.
Objectives: This mixed-methods pilot study sought to examine whether the effectiveness of an online intervention
for stress in students could be augmented by the use of prototype wearable sensors.
Methods: Students who were stressed, but not depressed, were allocated to a stress management program alone
(n = 34), with sensors (n = 29), or to no intervention (n = 35). Interventions lasted 4 weeks. Outcome measures
included measures of stress, anxious, and depressive symptoms, and were measured immediately after the interventions
and 4 weeks later. Participants in the two program groups were interviewed to gain feedback about the
program and the sensors.
Results: Significant pre-post reductions in stress (p = .019) were observed for those in the program alone group.
Significant reductions in depressive symptoms were observed among postgraduates (p = .006), but not undergraduates,
in the program only group. The program plus sensors group had a broadly similar, but weaker set of
results, indicating that the sensors impeded, rather than augmented, the effectiveness of the program. Qualitative
data explicate this finding, highlighting participation burden as a key issue. Participants provided detailed feedback
about the program, the sensors, and biofeedback exercises, which are summarised and discussed with
reference to the quantitative findings.
Conclusions: The newly developed stress management program could be an effective way to improve student
mental health. Wearable sensor technology, particularly biofeedback exercises, may be a useful contribution
for the next generation of e-therapies, but further development of the prototypes is needed and their reliability
and usability will likely affect user responses to them