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1000
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Abstract/Summary
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<jats:p><jats:bold>Background:</jats:bold> Limited evidence suggests that mobile mood-monitoring can improve mental health outcomes and therapeutic engagement in young people. The aim of this mixed methods study was to explore the clinical impacts of mobile mood-monitoring in youth with mental health problems, using a publicly accessible app.</jats:p><jats:p><jats:bold>Methods:</jats:bold> Twenty-three patients with mental health problems and 24 young people without mental health problems participated in the quantitative study. Participants monitored their mood using a mood-monitoring app twice a day for 3 weeks, which was preceded by a 3-week baseline period. Outcome measures included momentary and retrospective assessments of affect regulation (all participants) and therapeutic engagement (patients only). Following the quantitative study, patients (<jats:italic>n</jats:italic> = 7) and their clinicians (<jats:italic>n</jats:italic> = 6) participated in individual interviews. Interview data was analysed using thematic analysis.</jats:p><jats:p><jats:bold>Results:</jats:bold> Use of the mood-monitoring app significantly reduced momentary negative mood (<jats:italic>p</jats:italic> &lt; 0.001) and retrospectively assessed impulsivity across all 47 participants (<jats:italic>p</jats:italic> = 0.001). All other outcomes showed no significant difference. Qualitative feedback similarly indicated the potential of apps to improve problems with impulsivity in patients. Furthermore, apps may aid communication, promote empowerment, and ameliorate memory difficulties in clinical appointments.</jats:p><jats:p><jats:bold>Conclusions:</jats:bold> This mixed methods study demonstrated the potential utility of apps for clinical practice. Apps may potentially be an interventional tool, or at a minimum, an adjunct to existing treatments. Data was collected from a small sample size over a short study duration, limiting the generalisability of findings and inferences regarding long-term effects. Potential sources of bias in the qualitative study (e.g., researcher bias) should also be considered.</jats:p>
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1000
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Hinweis
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DeepGreen-ID: de910719775649db850e87e2ec8387e4 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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