MétaCan
Menu
Back to cohort
Record W3208535935 · doi:10.2196/27645

Technology Support Challenges and Recommendations for Adapting an Evidence-Based Exercise Program for Remote Delivery to Older Adults: Exploratory Mixed Methods Study

2021· article· en· W3208535935 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Aging · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute on AgingNational Institutes of HealthInstitute of Translational Health Sciences
KeywordsAttendancePhoneTroubleshootingExploratory researchPsychologyMedical educationMedicineGerontologyEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Tele-exercise has emerged as a means for older adults to participate in group exercise during the COVID-19 pandemic. However, little is known about the technology support needs of older adults for accessing tele-exercise. OBJECTIVE: This study aims to examine the needs of older adults for transition to tele-exercise, identify barriers to and facilitators of tele-exercise uptake and continued participation, and describe technology support challenges and successes encountered by older adults starting tele-exercise. METHODS: We used an exploratory, sequential mixed methods study design. Participants were older adults with symptomatic knee osteoarthritis (N=44) who started participating in a remotely delivered program called Enhance Fitness. Before the start of the classes, a subsample of the participants (n=10) completed semistructured phone interviews about their technology support needs and the barriers to and facilitators for technology adoption. All of the participants completed the surveys including the Senior Technology Acceptance Model scale and a technology needs assessment. The study team recorded the technology challenges encountered and the attendance rates for 48 sessions delivered over 16 weeks. RESULTS: Four themes emerged from the interviews: participants desire features in a tele-exercise program that foster accountability, direct access to helpful people who can troubleshoot and provide guidance with technology is important, opportunities to participate in high-value activities motivate willingness to persevere through the technology concerns, and belief in the ability to learn new things supersedes technology-related frustration. Among the participants in the tele-exercise classes (mean age 74, SD 6.3 years; 38/44, 86% female; mean 2.5, SD 0.9 chronic conditions), 71% (31/44) had a computer with a webcam, but 41% (18/44) had little or no experience with videoconferencing. The initial technology orientation sessions lasted on average 19.3 (SD 10.3) minutes, and 24% (11/44) required a follow-up assistance call. During the first 2 weeks of tele-exercise, 47% of participants (21/44) required technical assistance, which decreased to 12% (5/44) during weeks 3 to 16. The median attendance was 100% for the first 6 sessions and 93% for the subsequent 42 sessions. CONCLUSIONS: With appropriate support, older adults can successfully participate in tele-exercise. Recommendations include individualized technology orientation sessions, experiential learning, and availability of standby technical assistance, particularly during the first 2 weeks of classes. Continued development of best practices in this area may allow previously hard-to-reach populations of older adults to participate in health-enhancing, evidence-based exercise programs.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.175
GPT teacher head0.528
Teacher spread0.352 · 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