Effects of an Acceptance-Facilitating Intervention on Acceptance and Usage of Digital Interventions for Binge Eating

Linardon, Jake; Anderson, Cleo; Chapneviss, Tara; Hants, Emma; Shatte, Adrian; Fuller‐Tyszkiewicz, Matthew

doi:10.1176/appi.ps.202100616

Cited by 4 publications

(6 citation statements)

References 11 publications

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“…Each item was again modified to make it applicable to a DBT-based app and was rated on a scale ranging from 1 ( does not apply at all ) to five ( applies completely ). Internal consistency has shown to be acceptable across all subscales in previous research [ 23 ]. Cronbach’s alpha was alpha (a) in the present study 0.81, 0.59, 0.85, and 0.70, respectively.…”

Section: Methodsmentioning

confidence: 84%

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Target-user preferences, motivations, and acceptance for a dialectical behaviour therapy smartphone application for eating disorders

Anderson,

Fuller-Tyszkiewicz,

Messer

et al. 2024

Eat Weight Disord

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Purpose Evidence shows that dialectical behavioural therapy (DBT) is efficacious for eating disorders (ED), yet few people have access to specialized treatments like DBT. Translating key DBT skills for delivery via a smartphone application may broaden the dissemination of evidence-based interventions. However, prior to developing a DBT-based app, it is crucial to gather information on target-user needs and preferences. Assessing overall acceptance and identifying predictors of acceptance, informed by the UTAUT framework, is also important. This process ensures not only a demand for such an app, but also that users receive content and features tailored to their needs. Method This study aimed to understand target-user preferences of DBT-based apps for EDs by assessing willingness to engage, overall acceptance levels, and preferred functionality/content delivery modes (n = 326 symptomatic participants). Results Eighty-eight percent indicated they would be willing to use a DBT-based ED app if it were available. Acceptance levels of a DBT app were high (64%), which was uniquely predicted by performance expectancy (perceptions of how beneficial an intervention is) and facilitating conditions (expectations of technological infrastructure and support in interventions) in path analysis. Content perceived as important to contain were emotion regulation techniques, tailored intervention strategies, and psychoeducation. Conclusion Findings generate important information about target-user preferences of a DBT-based app for EDs, highlighting necessary design principles for apps of this kind. Level of evidence Level V, cross-sectional descriptive study.

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Section: Methodsmentioning

confidence: 84%

“…Total scores were derived by summing each item, where higher scores indicate greater acceptance. Internal consistency has been shown to be acceptable across all subscales in previous research [ 23 ]. Internal consistency in this study was acceptable ( α = 0.74).…”

Section: Methodsmentioning

confidence: 88%

Target-user preferences, motivations, and acceptance for a dialectical behaviour therapy smartphone application for eating disorders

Anderson,

Fuller-Tyszkiewicz,

Messer

et al. 2024

Eat Weight Disord

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“…Subscales include Skepticism and Perception of Risks ("it is difficult to implement the suggestions of a psychological online intervention effectively in everyday life"), Confidence in Effectiveness ("a psychological online intervention can inspire me to better approach my problems"), Technological Threat ("I learn skills to better manage my everyday life from a therapist rather than from a psychological online intervention"), and Anonymity Benefits ("by using a psychological online intervention, I do not have to fear that someone will find out that I have psychological problems"). For a full list of the items used to assess these constructs, readers are referred Linardon, Anderson, et al (2022).…”

Section: Perspectives Of Digital Interventionsmentioning

confidence: 99%

“…Practically speaking, the numbers-neededto-treat for EDE-Q global scores when comparing the two groups against the waitlist were 3.13 and 3.85, indicating that around three participants would need to be treated for one individual to see symptom improvements relative to control group. Improvements were sustained at 8-week follow-up and both interventions were well-tolerated among participants (seeLinardon, Anderson, et al, 2022 for further detail). The mean age of the sample was 34.1…”

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confidence: 95%

Exploration of the individual and combined effects of predictors of engagement, dropout, and change from digital interventions for recurrent binge eating

Linardon,

Fuller‐Tyszkiewicz

2024

Intl J Eating Disorders

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ObjectiveOur ability to predict responsiveness to digital interventions for eating disorders has thus far been poor, potentially for three reasons: (1) there has been a narrow set of predictors explored; (2) prediction has mostly focused on symptom change, ignoring other aspects of the user journey (uptake, early engagement); and (3) there is an excessive focus on the unique effects of predictors rather than the combined contributions of a predictor set. We evaluated the univariate and multivariate effects of outcome predictors in the context of a randomized trial (n = 398) of digitally delivered interventions for recurrent binge eating.MethodThirty baseline variables were selected as predictors, ranging from specific symptoms, to key protective factors, to technological acceptance, and to online treatment attitudes. Outcomes included uptake, early engagement, and remission. Univariate (d) and multivariate (D) standardized mean differences were calculated to estimate the individual and combined effects of predictors, respectively.ResultsAt the univariate level, few predictors produced an effect size larger than what is considered small (d > .20) across outcomes. However, our multivariate approach enhanced prediction (Ds = .65 to 1.12), producing accuracy rates greater than chance (63%–71% accuracy). Less than half of the chosen variables proved to be useful in contributing to predictions in multivariate models.ConclusionFindings suggest that accuracy in outcome prediction from digitally delivered interventions may be better driven by the aggregation of many small effects rather than one or several largely influential predictors. Replication with different data streams (sensor, neuroimaging) would be useful.Public SignificanceOur ability to predict who will and will not benefit from digital interventions for eating disorders has been poor. We highlight the viability of a multivariate approach to outcome prediction, whereby prediction may be better driven by the aggregation of many small effects rather than one or a few influential predictors.

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“…To tackle these concerns and close knowledge gaps, tailored acceptance-facilitating interventions (AFIs) such as multi-component information strategies have been found to be a promising tool in educating individuals about innovative approaches, such as dMHSs. 51 – 60 For instance, Hein et al 61 could show that physicians’ acceptance of health apps focusing on chronic pain was strengthened by a short educational video providing information about the content of health apps, for example, how they can be used and evidence of recent studies. Credibility and performance expectancy were the strongest predictors of acceptance, followed by skepticism.…”

Section: Introductionmentioning

confidence: 99%

Investigating information needs and preferences regarding digital mental health services among medical and psychology students in Germany: A qualitative study

et al. 2023

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Background Since 2020, physicians and psychotherapists in Germany can prescribe digital mental health services (dMHSs). However, even future healthcare professionals (HCPs), such as medical and psychology students, remain reluctant to use dMHSs, although they are a risk group for mental health issues themselves. Reasons include scepticism and lacking awareness of dMHSs, which can be addressed by acceptance-facilitating interventions (AFIs) such as information strategies. To date, though, little is known about their information needs. Methods Semi-structured interviews with n = 21 students were conducted between August and September 2021. Students of legal age studying psychology or medicine at a German university could participate. Interview recordings were transcribed verbatim and content-analyzed according to Mayring, using deductive and inductive coding. Results Most students reported having little experience with dMHSs. Digital health has barely been raised in their study, even though it was perceived as crucial for personal needs as well as in preparation for their work as HCPs. Students favoured receiving information on and recommendations for dMHSs from their university via, e.g. social media or seminars. Among others, information about data safety, scientific evidence base and application scope were preferred. Additionally, information on costs as well as user reviews seemed to be essential components of information strategies because students were concerned that high costs or low usability would hinder uptake. Conclusions The results give first insights on how future HCPs would like to be informed on dMHSs. Future research should focus on systematic variations of AFIs' components mimicking real-world decision scenarios to increase the adoption of dMHSs.

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Effects of an Acceptance-Facilitating Intervention on Acceptance and Usage of Digital Interventions for Binge Eating

Cited by 4 publications

References 11 publications

Target-user preferences, motivations, and acceptance for a dialectical behaviour therapy smartphone application for eating disorders

Target-user preferences, motivations, and acceptance for a dialectical behaviour therapy smartphone application for eating disorders

Exploration of the individual and combined effects of predictors of engagement, dropout, and change from digital interventions for recurrent binge eating

Investigating information needs and preferences regarding digital mental health services among medical and psychology students in Germany: A qualitative study

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