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Record W4327796956 · doi:10.1123/japa.2022-0118

Navigating a New Normal: Perceptions and Experiences of an Online Exercise Program for Older Adults During COVID-19

2023· article· en· W4327796956 on OpenAlexaff
Sarah Galway, Meghan H.D. Laird, Matthieu Dagenais, Kimberley L. Gammage

Bibliographic record

VenueJournal of Aging and Physical Activity · 2023
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsBrock University
Fundersnot available
KeywordsThematic analysisPopularityPerceptionPsychologyCoronavirus disease 2019 (COVID-19)Medical educationApplied psychologyGerontologyPandemicReflexivityQualitative researchMedicineSocial psychologyDisease

Abstract

fetched live from OpenAlex

Online exercise programming has surged in popularity; however, little is known about older adults' perceptions and experiences of online exercise. The purpose of this study was to qualitatively examine older adults' (aged 59-82 years) experiences and perceptions of an online exercise program during the COVID-19 pandemic. Nineteen individuals (individuals who used the online exercise program and those who did not) completed a semistructured interview. Three main themes were generated from the data using reflexive thematic analysis: (a) can online exercise really work for older adults? (b) technology attitudes and experiences influence online participation, and (c) barriers and advantages of the online exercise program and the home environment. Most participants who took part were able to overcome initial barriers through technical support and experience. Our findings highlight ways to promote advantages and address barriers of online exercise for older adults and emphasize the importance of fostering social experiences and training online exercise instructors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.411
Teacher spread0.360 · 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.

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

Citations11
Published2023
Admission routes1
Has abstractyes

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