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Record W2993562544 · doi:10.1590/0034-7167-2018-0535

The aging of families with members with intellectual disabilities

2019· article· en· W2993562544 on OpenAlexaboutno aff
Renata Balieiro Takebayashi, Hugo Fernandes, Maria Goreti da Silva Cruz, Marcelo Geovane Perseguino, Selma Eloy Machado Marques, Ana Lúcia de Moraes Horta

Bibliographic record

VenueRevista Brasileira de Enfermagem · 2019
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual disabilityFamily memberPsychologyIsolation (microbiology)Qualitative researchContent analysisGerontologyDevelopmental psychologySociologyMedicinePsychiatryFamily medicineSocial science

Abstract

fetched live from OpenAlex

OBJECTIVE: to understand the structure and dynamics of families in the late stage of the life cycle that have a member with intellectual disability. METHOD: qualitative research using the Calgary Family Assessment Model as methodological framework. The study had 38 participants, distributed into 10 families that had a member with intellectual disability and whose parents were elderly. The interviews were analyzed with content analysis technique. RESULTS: the following analytical categories were evidenced: "living with intellectual disability", "communication as a strategy for encounter", "family isolation and the need for support" and "concerns about care in the future". CONCLUSION: families in the late life cycle who had a member with intellectual disability are arranged in a structure that overloads a single caregiver (mother), has little support network, uses communication as an instrument for understanding themselves and the other, besides having difficulties in projecting the future.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.334
Teacher spread0.297 · 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.

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

Citations7
Published2019
Admission routes1
Has abstractyes

Explore more

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