Ghent University. Faculty of Psychology and Educational Sciences
Abstract
More than half of the Flemish adolescents report mild to serious mental problems. Healthy lifestyle behaviors are protective factors for mental health, and a focus on modifiable health behaviors for the promotion of mental health can be both destigmatizing and empowering. Increasingly, mobile technology is being used to deliver health behavior change interventions, and mobile health (mHealth) interventions have been shown feasible in an adolescent population. The goal of the project within this doctoral thesis was to develop and evaluate a mobile healthy lifestyle intervention for the promotion of mental health in adolescents. Specifically, we aimed to develop a multicomponent mHealth intervention, to evaluate its effectiveness in promoting healthy lifestyles and mental health, to gain insight in the components or mechanisms that led to behavior change, and to investigate determinants and outcomes of different types of engagement with the intervention.
In a first phase, the mHealth intervention #LIFEGOALS was created. The requirements for the technology were based on theory and evidence, and on an investigation of the context and the needs and expectations of stakeholders and end-users. The design took place in an interdisciplinary team and in close collaboration with adolescents and stakeholders. An iterative development process resulted in a self-regulation-based app, coupled with an activity tracker, which was complemented with gamification elements, a support chatbot, and narrative videos. The participatory development and final intervention are described.
In a second phase, the #LIFEGOALS intervention was evaluated. First, to evaluate the effect of the narrative on automatic attitude change, we aimed to develop an implicit measure to assess automatic sleep-related attitudes. However, the findings from our validation study indicated that the developed implicit measures were not suited to assess automatic sleep-related attitudes. For that reason we did not pursue the use of implicit measures for evaluating the narrative component. The effectiveness of the #LIFEGOALS intervention as a whole, was evaluated in a cluster-controlled trial. Self-reports and accelerometers were used to assess the effect of the intervention on health behavior and mental health. Results were mixed. The mHealth intervention showed beneficial effects on physical activity, sedentary behavior, sleep quality, mood, and self-perception. Most of the effects, however, were moderated by pandemic-related measures and only present in a close-to-normal context. For participants who had to follow partially remote education due to the pandemic, negative intervention effects were found on health-related quality of life, mood, and perceived social 1
support. This quantitative trial was complemented with qualitative interviews with participants who had actively used the #LIFEGOALS app. Interviewed users experienced that the reward system and the self-regulation techniques had contributed to their behavior change, and that increased health-related awareness had motivated to change behavior. The findings furthermore pointed to social factors, quality of technology, and autonomy as important elements within mHealth for adolescent health promotion.
As a final part of the evaluation, engagement with the intervention was investigated. Analyses of continuously logged usage data and self-reported experience of engagement with the intervention revealed overall low usage of the app. There was a clear drop in usage after the first week. After six weeks, only one third of the participants who had installed the intervention still used the app. Ratings of experience were neutral to positive and dropped only slightly over time. Non-usage attrition was lowest with the activity-tracker, and its usage showed the weakest correlation with other component use. The self-regulation techniques and gamification were the most used app-components, and their use was strongly interrelated. Experiential engagement and usage of the activity-tracker differed as a function of education type. Using cluster analysis, we identified four groups of engagement with the #LIFEGOALS intervention: no usage, initial usage, mainly use of the activity tracker, and mainly use of the narrative. Age, social support, and depressive symptoms predicted engagement group, but the engagement group did not differentially affect the change in health behavior outcomes from pre- to post-intervention.
To conclude, despite the extensive participatory development of the #LIFEGOALS intervention, engagement with the app was low. This limited our ability to investigate intervention effects and engagement types. The mixed effects of the intervention on healthy lifestyles and mental health were moreover moderated by the COVID-19 pandemic-related context. The self-regulation and gamification components are likely to have contributed to behavior change. More research is needed to optimize and evaluate a support chatbot and narrative videos within mHealth. Tailoring the intervention to the context, leveraging positive social influence, and integrating implementation science in the development process, are discussed as possible ways to improve effective engagement with mHealth in a general adolescent population
