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Record W2730294924 · doi:10.1093/geroni/igx004.514

SUSTAINING COMMUNITY-BASED HEALTH INITIATIVES FOR ADULTS AGING WITH INTELLECTUAL DISABILITIES

2017· article· en· W2730294924 on OpenAlexaff
Natasha A. Spassiani, Brad A. Meisner, Joy Hammel, Tamar Heller

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInstitutionalisationGrounded theoryPerspective (graphical)Public relationsPsychologyNursingBusinessMedicinePolitical scienceQualitative researchSociology

Abstract

fetched live from OpenAlex

Community-based intellectual disabilities (ID) agencies provide services and supports to people aging with ID, offering these individuals opportunities to participate in their community and engage in health promoting behaviors. However, little is known about the factors involved with sustaining community-based health initiatives (CBHI) among ID agencies. The purpose of the current study was to explore the facilitators and barriers of sustaining CBHI for people aging with ID living in group homes managed by ID agencies. Two non-profit ID agencies participated in the study. Nineteen semi-structured interviews were conducted with directors, managers, and direct support staff. Interviews conducted with directors and regional managers provided a broader systemic perspective, whereas interviews with support staff provided a front line perspective of the factors that may be effecting CBHI sustainability within group home settings. Grounded theory methods, including constant comparison, were used for analysis. Findings show that although ID agencies understand the importance of health and community participation for their clients and support such initiatives, agencies lack policies, resources, and ID and health education to sustain CBHI for their clients aging with ID over time. It is important to gain a better understanding of the influencing factors involved in sustaining CBHI that are being implemented by these agencies to enable individuals with ID to experience the many positive physical, psychological, and social health outcomes as they age and to potentially decrease their risk of institutionalization due to poor 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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.004
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 head0.125
GPT teacher head0.418
Teacher spread0.292 · 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 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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