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Record W2987926763 · doi:10.2196/13858

Parental Perspectives of a Wearable Activity Tracker for Children Younger Than 13 Years: Acceptability and Usability Study

2019· article· en· W2987926763 on OpenAlexvenueno aff
Kelly A. Mackintosh, Stephanie E. Chappel, Jo Salmon, Anna Timperio, Kylie Ball, Helen Brown, Susie Macfarlane, Nicola D. Ridgers

Bibliographic record

VenueJMIR mhealth and uhealth · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersMedical Research CouncilDeakin UniversityNational Health and Medical Research CouncilNational Heart Foundation of Australia
KeywordsUsabilityWearable computerActivity trackerPsychologymHealthHuman–computer interactionDevelopmental psychologyApplied psychologyComputer sciencePsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: There is increasing availability of, and interest in, wearable activity trackers for children younger than 13 years. However, little is known about how children and parents use these activity trackers or perceive their acceptability. OBJECTIVE: This study primarily aimed to ascertain parental perspectives on the acceptability and usability of wearables designed to monitor children's physical activity levels. Secondary aims were to (1) identify practical considerations for future use in physical activity interventions and promotion initiatives; (2) determine use of different features and functions incorporated into the accompanying app; and (3) identify parents' awareness of their child's current physical activity levels. METHODS: In total, 36 children (18 boys and 18 girls) aged 7-12 years were asked to wear a wrist-worn activity tracker (KidFit) for 4 consecutive weeks and to use the accompanying app with parental assistance and guidance. Each week, one parent from each family (n=25; 21 mothers and 4 fathers) completed a Web-based survey to record their child's activity tracker use, app interaction, and overall experiences. At the end of the 4-week period, a subsample of 10 parents (all mothers) participated in face-to-face interviews exploring perceptions of the acceptability and usability of wearable activity trackers and accompanying apps. Quantitative and qualitative data were analyzed descriptively and thematically, respectively. Thematic data are presented using pen profiles, which were constructed from verbatim transcripts. RESULTS: Parents reported that they and their children typically found the associated app easy to use for activity tracking, though only step or distance information was generally accessed and some difficulties interpreting the data were reported. Children were frustrated with not being able to access real-time feedback, as the features and functions were only available through the app, which was typically accessed by, or in the presence of, parents. Parents identified that children wanted additional functions including a visual display to track and self-monitor activity, access to the app for goal setting, and the option of undertaking challenges against schools or significant others. Other barriers to the use of wearable activity trackers included discomfort of wearing the monitor because of the design and the inability to wear for water- or contact-based sports. CONCLUSIONS: Most parents reported that the wearable activity tracker was easy for their child or children to use and a useful tool for tracking their children's daily activity. However, several barriers were identified, which may impact sustained use over time; both the functionality and wearability of the activity tracker should therefore be considered. Overall, wearable activity trackers for children have the potential to be integrated into targeted physical activity promotion initiatives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.446
Teacher spread0.396 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations78
Published2019
Admission routes1
Has abstractyes

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