Evaluation and optimization of digital psychological self-help interventions

Background: Mental health problems are widespread, and while evidence-based psychological treatments exist, many individuals still lack access. Digital psychological self-help interventions have been proposed as part of the solution. Their key advantage is accessibility - by allowing individuals to independently work with digital treatment materials, they enable access to care regardless of location and extend treatment reach without increasing the demand for clinicians. However, these interventions often suffer from low treatment engagement and effects, underscoring the need to expand knowledge on how to optimize them.

Aim: The overall aim of this thesis was to examine the feasibility of delivering digital psychological self-help interventions to populations with diverse mental health problems, and to evaluate strategies to optimize these interventions in terms of treatment engagement, efficacy, and user experience.

Study I was a feasibility study evaluating a digital self-help problem-solving intervention provided to patients (N = 12) with clinically significant symptoms of depression and/or anxiety on the waiting list for routine psychiatric care. Usability and credibility were deemed sufficient. Nine out of twelve engaged with the intervention at least once, and five completed the final step. Most participants reported a positive overall user experience. Symptom improvement varied, with some participants meeting criteria for clinical improvement and recovery. No severe negative effects were reported. The findings indicate that a digital self-help problem-solving intervention may be feasible to provide to patients on the waiting list for routine psychiatric care.

Study II was a randomized controlled trial assessing the effect of an optimized versus basic graphical user interface (GUI) in a digital self-help problem-solving intervention provided to a general population sample (N = 397) reporting emotional or practical problems. No significant differences between groups were found in usability or credibility. Participants who used the optimized GUI were significantly more likely to engage with the intervention at least once (71.7% vs. 50%), generated significantly more solutions both overall and per problem, and rated the intervention as significantly easier to understand and less overwhelming. The findings show that incorporating an optimized GUI into a digital self-help problem-solving intervention for the general population can improve engagement, without impacting usability or credibility.

Study III was a factorial randomized controlled trial (2x2x2) evaluating the effect of an optimized GUI, automated reminders, and an adaptive treatment strategy, in a digital self-help intervention for individuals with insomnia (N = 447). The optimized GUI significantly improved engagement ratings during treatment (d = 0.34) and up to three months later (d = 0.24), recorded sleep log days, login frequency, and usability. Automated reminders significantly increased sleep log days and logins, while the adaptive treatment strategy significantly improved treatment satisfaction, and required an average of 13.74 minutes of clinician time per individual. Being in all three factors led to a greater symptom improvement during the treatment period (d = 0.50). Negative effects were evenly distributed across factors. No severe negative effects were reported. The findings show that an optimized GUI and automated reminders can independently increase engagement with a digital self-help insomnia intervention, and when combined with an adaptive treatment strategy, symptom improvement can be enhanced.

Conclusions: Digital psychological self-help interventions seem to be feasible for both clinical and general populations. In these interventions, improved intervention design can significantly enhance treatment engagement, symptom improvement, and user experience. In summary, they show promise as a complement to clinician-guided treatment methods and as a means of scaling up psychological treatment, provided they are carefully designed for self-help use.

List of scientific papers

I. Hentati, A., Forsell, E., Ljótsson, B., Lindefors, N., & Kraepelien, M. (2022). A self-guided and monitored digital problem-solving intervention for patients with symptoms of depression or anxiety on the waiting list for treatment in routine psychiatric care: Feasibility study. BJPsych Open, 8(2), e43. https://doi.org/10.1192/bjo.2022.14

II. Hentati, A., Forsell, E., Ljótsson, B., Kaldo, V., Lindefors, N., & Kraepelien, M. (2021). The effect of user interface on treatment engagement in a self-guided digital problem-solving intervention: A randomized controlled trial. Internet Interventions, 26, 100448. https://doi.org/10.1016/j.invent.2021.100448

III. Hentati, A., Hentati Isacsson, N., Rosén, A., Jernelöv, S., Kaldo, V., Ljotsson, B., Forsell, E., Lindefors, N., & Kraepelien, M. Effects of an optimized graphical user interface, automated reminders, and an adaptive treatment strategy on treatment engagement and outcome in digital self-help for insomnia: A single-blind factorial randomized controlled trial. [Submitted]