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Record W4292595626 · doi:10.2196/40046

Examining the Delivery of a Tailored Chinese Mind-Body Exercise to Low-Income Community-Dwelling Older Latino Individuals for Healthy Aging: Feasibility and Acceptability Study

2022· article· en· W4292595626 on OpenAlexvenueno aff
Yan Du, Neela K. Patel, Arthur E. Hernández, Maria Zamudio-Samano, Shiyu Li, Tianou Zhang, Roman Fernandez, Byeong Yeob Choi, William M. Land, Sarah L. Ullevig, Vanessa Estrada, Jessh Mondesir Mavoungou Moussavou, Deborah Parra‐Medina, Zenong Yin

Bibliographic record

VenueJMIR Formative Research · 2022
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsAttendanceGerontologyMedicineThematic analysisHealthy agingCognitionIndependent livingPhysical therapySuccessful agingQualitative research

Abstract

fetched live from OpenAlex

BACKGROUND: Older Latino individuals are disproportionally affected by various chronic conditions including impairments in physical and cognitive functions, which are essential for healthy aging and independent living. OBJECTIVE: This study aimed to evaluate the feasibility and acceptability of FITxOlder, a 12-week mind-body exercise program, in community-dwelling low-income, predominantly older Latino individuals, and assess its preliminary effects on health parameters relevant to healthy aging and independent living. METHODS: This 12-week, single-arm, stage 1B feasibility study had a pre- and poststudy design. A total of 13 older adults (mean age 76.4, SD 7.9 years; 11/13, 85% Latino) of a congregate meal program in a senior center were enrolled. FITxOlder was a tailored Chinese mind-body exercise program using Five Animal Frolics led by a bilingual community health worker (CHW) participating twice a week at the senior center and facilitated by mobile health technology for practice at home, with incrementally increasing goals moving from once a week to at least 3 times a week. The feasibility and acceptability of the study were examined using both quantitative and qualitative data. Healthy aging-related outcomes (eg, physical and cognitive function) were assessed using paired 2-tailed t tests. Qualitative interview data were analyzed using thematic analysis. RESULTS: The attendance rate for the 24 exercise sessions was high (22.7/24, 95%), ranging from 93% (1.8/2) to 97% (1.9/2) over the 12 weeks. Participants were compliant with the incremental weekly exercise goals, with 69.2% (9/13) and 75.0% (9/12) meeting the home and program goals in the last 4 weeks, respectively. Approximately 83% (10/12) to 92% (11/12) of the participants provided favorable feedback on survey questions regarding the study and program implementation, such as program content and support, delivery by the CHW, enjoyment and appeal of the Five Animal Frolics, study burden and incentives, and safety concerns. The qualitative interview data revealed that FITxOlder was well accepted; participants reported enjoyment and health benefits and the desire to continue to practice and share it with others. The 5-time sit-to-stand test (mean change at posttest assessment=-1.62; P<.001; Cohen d=0.97) and 12-Item Short Form Health Survey physical component scores (mean change at post intervention=5.71; P=.01; Cohen d=0.88) exhibited changes with large effect sizes from baseline to 12 weeks; the other parameters showed small or medium effect sizes. CONCLUSIONS: The research findings indicated that the CHW-led and mobile health-facilitated Chinese qigong exercise program is feasible and acceptable among low-income Latino older adults. The trending health benefits of the 12-week FITxOlder program suggest it is promising to promote physical activity engagement in underserved older populations to improve health outcomes for healthy aging and independent living. Future research with larger samples and longer interventions is warranted to assess the health benefits and suitability of FITxOlder.

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)0.009
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.178
GPT teacher head0.472
Teacher spread0.294 · 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 designNon-randomized trial
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
Published2022
Admission routes1
Has abstractyes

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