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Record W4205487413 · doi:10.2196/32274

Changes in Use of a Leisure Activity Mobile App for Children With Disabilities During the COVID-19 Pandemic: Retrospective Study

2021· article· en· W4205487413 on OpenAlexaffvenueabout
Paul Yejong Yoo, Mehrnoosh Movahed, Ishana Rue, Carlos Denner dos Santos, Annette Majnemer, Keiko Shikako‐Thomas

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2021
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcGill UniversityÉcole de Technologie SupérieureMcGill University Health Centre
Fundersnot available
KeywordsListing (finance)PandemicPromotion (chess)PsychologyPublic engagementCoronavirus disease 2019 (COVID-19)Internet privacyPolitical scienceGerontologyPublic relationsMedicineBusinessComputer scienceDiseasePolitics

Abstract

fetched live from OpenAlex

BACKGROUND: Participation in leisure activities is essential for child development and a human right as per the United Nations Convention on the Rights of the Child. Children with disabilities face several restrictions when participating in leisure activities as compared to same age peers without disabilities. Access to information about accessible, inclusive leisure activities is one of the barriers limiting participation, and one potential health promotion strategy is to provide access to information to increase participation. The Jooay App is a mobile app listing such activities in Canada and Australia. With the COVID-19 global pandemic and subsequent public health measures, most community-based facilities providing the activities listed on Jooay were closed. The app therefore started listing online activities offered with the expectation of continuing to provide information for families and understanding the extent to which users relied on the mobile app as a tool to identify new safe leisure opportunities. OBJECTIVE: This study aims to describe the engagement of the Jooay app before and during COVID-19, and to estimate the extent to which the listing of online activities was related to the engagement of the Jooay app. METHODS: We conducted a retrospective study comparing Jooay app use between March 2020 and February 2021 to the engagement between March 2019 and February 2020 by Jooay users. Spearman rank correlations were carried out to identify associations between the activities listed and the users' engagement from May 2020 to February 2021. RESULTS: =0.900). CONCLUSIONS: The engagement with the Jooay App presented an expected decrease during the first wave of the COVID-19 pandemic. The addition of online adapted leisure activities to the app's listings during the pandemic increased app use. Access to information about inclusive activities is a barrier for children with disabilities to engage in leisure. Mobile health solutions can be responsive to contextual factors and consider the social determinants of health such as socioeconomic and public health emergency issues that can impact the participation of vulnerable populations such as children with disabilities and help eliminate barriers to participation. The provision of online leisure opportunities during the pandemic could facilitate participation in these activities during the pandemic and beyond, which is essential and beneficial for the physical and mental well-being of children with disabilities and their families.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.044
GPT teacher head0.316
Teacher spread0.273 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2021
Admission routes3
Has abstractyes

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