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Record W2886705233 · doi:10.1177/1557988318792158

Engaging Older Men in Physical Activity: Implications for Health Promotion Practice

2018· article· en· W2886705233 on OpenAlexafffundabout
Manpreet Thandi, Alison Phinney, John L. Oliffe, Sabrina T. Wong, Heather McKay, Joanie Sims‐Gould, Simran Sahota

Bibliographic record

VenueAmerican Journal of Men s Health · 2018
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMovember Canada
KeywordsGerontologyPhotovoiceEthnic groupHealth promotionPsychologyPhysical activityQualitative researchPopulationMedicinePublic healthSociologyNursingEnvironmental healthPhysical therapy

Abstract

fetched live from OpenAlex

According to Health Canada (2016), only about 11% of older men meet recommended guidelines for physical activity, and participation decreases as men age. This places men at considerable risk of poor health, including an array of chronic diseases. A demographic shift toward a greater population of less healthy older men would substantially challenge an already beleaguered health-care system. One strategy to alter this trajectory might be gender-sensitized community-based physical activity. Therefore, a qualitative study was conducted to enhance understanding of community-dwelling older men's day-to-day experiences with physical activity. Four men over age 65 participated in a semistructured interview, three walk-along interviews, and a photovoice project. An interpretive descriptive approach to data analysis was used to identify three key themes related to men's experiences with physical activity: (a) "The things I've always done," (b) "Out and About," and (c) "You do need the group atmosphere at times." This research extends the knowledge base around intersections among older men, physical activity, and masculinities. The findings provide a glimpse of the diversity of older men and the need for physical activity programs that are unique to individual preferences and capacities. The findings are not generalized to all men but the learnings from this research may be of value to those who design programs for older men in similar contexts. Future studies might address implementation with a larger sample of older men who reside in a broad range of geographic locations and of different ethnicities.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.069
GPT teacher head0.465
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.

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

Citations29
Published2018
Admission routes3
Has abstractyes

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