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A novel self-rating instrument designed for long-term, app-based monitoring of ADHD symptoms: A mixed-methods development and validation study. | LitMetric

A novel self-rating instrument designed for long-term, app-based monitoring of ADHD symptoms: A mixed-methods development and validation study.

Digit Health

Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.

Published: September 2024

AI Article Synopsis

  • Regular monitoring of ADHD treatment is crucial, but traditional care often limits patient interaction to yearly visits; apps can help facilitate ongoing monitoring.
  • A study involving 13 clinicians led to the creation of the mCASS, a tool designed for self-monitoring ADHD symptoms via a smartphone app, which was then tested with a larger group of 397 individuals.
  • The mCASS showed good reliability and validity, covering key areas of ADHD impact, and highlights the importance of incorporating feedback from both clinicians and patients in developing effective mobile health solutions.

Article Abstract

Background: Regular outcome monitoring is essential for effective attention deficit hyperactivity disorder (ADHD) treatment, yet routine care often limits long-term contacts to annual visits. Smartphone apps can complement current practice by offering low-threshold, long-term sustainable monitoring capabilities. However, special considerations apply for such measurement which should be anchored in stakeholder preferences.

Methods: This mixed-methods study engaged 13 experienced clinicians from Region Stockholm in iterative qualitative interviews to inform development of an instrument for app-based ADHD monitoring: the mHealth scale for Continuous ADHD Symptom Self-monitoring (mCASS). A subsequent survey, including the mCASS and addressing app-based monitoring preferences, was administered to 397 individuals with self-reported ADHD. Psychometric properties of the mCASS were explored through exploratory factor analysis and examinations of internal consistency. Concurrent validity was calculated between the mCASS and the Adult ADHD Self-Report Scale-V1.1 (ASRS-V1.1). Additional quantitative analyses included summary statistics and repeated-measures ANOVAs.

Results: Clinicians identified properties influencing willingness to use and adherence including content validity, clinical relevance, respondent burden, tone, wording and preferences for in-app results presentation. The final 12-item mCASS version demonstrated four factors covering everyday tasks, productivity, rest and recovery and interactions with others, explaining 47.4% of variance. Preliminary psychometric assessment indicated satisfactory concurrent validity ( = .595) and internal consistency ( = .826).

Conclusions: The mCASS, informed by clinician and patient experiences, appears to be valid for app-based assessment of ADHD symptoms. Furthermore, insights are presented regarding important considerations when developing mobile health (mHealth) instruments for ADHD individuals. These can be of value for future, similar endeavours.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11423372PMC
http://dx.doi.org/10.1177/20552076241280037DOI Listing

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