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Record W4286848867 · doi:10.13096/rfre.v7n2.171

Identification of the elders’ needs and ressources in Fleurimont, Québec, Canada : towards occupational therapists’ interventions supporting aging in place

2021· article· en· W4286848867 on OpenAlexaffabout
Fabienne Labonté, Marina Sirois, Amélie Roberge, Marie-Ève Ravenelle, Reem Hussein, Mélanie Levasseur

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsUniversité de SherbrookeCentre Intégré de Santé et de Services Sociaux des LaurentidesCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-Québec
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Le vieillissement de la population engendre plusieurs défis, notamment pour favoriser le maintien à domicile (MAD) des aînés. Puisqu’une augmentation est anticipée, il importe de mieux connaître les besoins de MAD des aînés, notamment pour les résidents de Fleurimont (arrondissement de Sherbrooke, Québec, Canada). Une meilleure connaissance des ressources est aussi requise. Cette étude visait à identifier : 1) les besoins de MAD des aînés de Fleurimont et 2) les ressources disponibles. Une recherche-action a été utilisée auprès de 45 aînés et proches provenant des 9 communautés de Fleurimont. Cinq forums d’informateurs-clés ont été réalisés à l’aide d’un guide d’entretien semi-structuré. Une analyse de contenu thématique intra et intercas a été menée à l’aide d’une grille de codage mixte. Âgés de 64 à 94 ans (76,2±7,6), la majorité des aînés et des proches étaient des femmes, qualifiaient leur santé de bonne ou d’excellente et souhaitaient rester à domicile le plus longtemps possible. Associés à une diminution de leurs capacités physiques, les principaux besoins concernaient entre autres l’habitation, les déplacements, les soins personnels et les loisirs. Malgré qu’elles soient nombreuses, les ressources tant publiques, privées que communautaires étaient peu connues. Une liste de besoins et de ressources a été élaborée et permettra, ultimement, de mieux identifier ce dont les aînés ont besoin et, ainsi, de mettre en place davantage de solutions adaptées au MAD. Il importe de poursuivre les études auprès de clientèles en situation de vulnérabilités, tel que les aînés confinés à leur domicile ou ayant une santé précaire. ________________________________________________________________________________________________________________ The aging of the population creates several challenges, particularly for helping older adults to age in place. Since an increase is anticipated, it is important to better understand the needs of aging in place older adults, especially for residents in Fleurimont, a borough of Sherbrooke, Quebec, Canada. A better knowledge of the resources is also required. This study aimed to identify 1) the needs of aging in place older adults in Fleurimont and 2) the adequacy between the needs and the resources available in order to better adapt the community offer. An action research was used with 45 older adults and relatives from the 9 districts of Fleurimont. Five key informant forums were realized using a semi-structured interview guide. A thematic content analysis was conducted using a mixed coding grid. Aged between 64 and 94 (76.2 ± 7.6), most older adults and relatives were women, rated their health as good or excellent, and wanted to stay at home as long as possible. Associated with a decrease in their physical abilities, the main needs concerned housing, mobility, personal care and leisure. Although they were numerous, the resources were little known. A list of various needs and resources has been developed and will, ultimately, contribute to better identify what older adults need and implement further solutions adapted to aging in place. Studies on aging in place must continue for clients in situations of vulnerability, such as older adults living alone or with precarious health.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.335

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.244
GPT teacher head0.581
Teacher spread0.337 · 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 designQualitative
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

Citations0
Published2021
Admission routes2
Has abstractyes

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