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Record W2953594395 · doi:10.1111/jar.12640

What is and isn’t working: Factors involved in sustaining community‐based health and participation initiatives for people ageing with intellectual and developmental disabilities

2019· article· en· W2953594395 on OpenAlexaff
Natasha A. Spassiani, Brad A. Meisner, Megan S. Abou Chacra, Tamar Heller, Joy Hammel

Bibliographic record

VenueJournal of Applied Research in Intellectual Disabilities · 2019
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsSurrey Place CentreCentre for Addiction and Mental HealthYork University
FundersNational Institute on AgingNational Institute on Disability and Rehabilitation Research
KeywordsPhotovoiceAgency (philosophy)Intellectual disabilityActive ageingPsychologyGerontologyPeer supportNursingPublic relationsMedicineSociologyOlder peoplePolitical scienceEconomic growth

Abstract

fetched live from OpenAlex

As people with intellectual and developmental disabilities (I/DD) age, it is important that I/DD agencies are prepared to support healthy ageing in homes and in communities. This study explored supports and barriers to sustaining community-based health and participation initiatives (CBHPI) for people ageing with I/DD living in group homes managed by agencies. The study utilized interviews and photovoice with 70 participants-35 individuals with I/DD and 35 management/direct support agency staff. Data were analysed through content analysis and triangulation of data where five themes emerged: Agency values and policies related to healthy ageing; resources and staff competencies; communication between management and staff; community/university partnerships; and peer relations. Findings show that I/DD agencies and people with I/DD value CBHPI, but they find them difficult to sustain due to limited resources and lack of training specific to ageing with I/DD. Conducting system-level research within I/DD agencies to include first-person accounts of people with I/DD, staff and management provides insight on how to effectively support the needs of people with I/DD to improve their health and community participation as they age.

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)0.016
metaresearch head score (Gemma)0.039
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.011
Scholarly communication0.0090.007
Open science0.0020.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.191
GPT teacher head0.408
Teacher spread0.217 · 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

Citations37
Published2019
Admission routes1
Has abstractyes

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