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Factors Influencing Sedentary Behaviour in Older Adults: An Ecological Approach

2016· article· en· W2508473268 on OpenAlexaffabout
Linna Tam‐Seto, Patricia L. Weir, Shilpa Dogra

Bibliographic record

VenueAIMS Public Health · 2016
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Ontario Institute of TechnologyUniversity of WindsorQueen's University
Fundersnot available
KeywordsHealth promotionGerontologyFocus groupPopulationKnowledge translationSedentary lifestylePsychologyPublic healthPerceptionPhysical activityMedicineEnvironmental healthPhysical therapy

Abstract

fetched live from OpenAlex

Sedentary behaviour is negatively associated with several health outcomes and is particularly problematic among older adults. Knowledge translation tools and public health promotion strategies are needed; however, little evidence is available to inform framing of such tools or development of intervention programs. The aim of the present study was to use data on the perceptions of sedentary time and the programs or supports older adults identify as important for reducing their sedentary time, to inform knowledge translation strategies targeting this population. Focus groups were conducted with four groups of older adults (n = 26) at local seniors' centres (Ontario, Canada). Participants were 74 ± 8.5 years old and were engaging in both sedentary and physical activities in a social environment. Using the Ecological Model for sedentary time in adults, we categorized data into leisure time, household, transport and occupation domains. Intrinsic and extrinsic factors that worked to either discourage or promote sedentary behaviour were identified. Drawing on both groupings of data, results were synthesized to inform public health strategies on appropriate messaging and better uptake of programming and guidelines. For example, successful programs developed on the topic will need to include a social component and a mentally stimulating component, as these were identified as critical for enjoyment and motivation. It was clear from this analysis that sedentary time reduction strategies will need to consider the different domains in which older adults accumulate sedentary time.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.090
GPT teacher head0.347
Teacher spread0.256 · 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

Citations41
Published2016
Admission routes2
Has abstractyes

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