Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
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.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11423372 | PMC |
http://dx.doi.org/10.1177/20552076241280037 | DOI Listing |
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