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Record W4401052813 · doi:10.1080/20473869.2024.2380945

Initial psychometric properties of the medical outcomes study social support survey in caregivers of individuals with intellectual disabilities in Brazil

2024· article· en· W4401052813 on OpenAlexaff
Crystian Moraes Silva Gomes, Arthur C. Macedo, Lilian Gazzoli Zanotelli

Bibliographic record

VenueInternational Journal of Developmental Disabilities · 2024
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyIntellectual disabilityClinical psychologyPsychometricsDevelopmental psychologySocial supportGerontologyPsychiatrySocial psychologyMedicine

Abstract

fetched live from OpenAlex

This study investigated the initial evidence of internal structure and convergent validity of the Brazilian version of the Medical Outcomes Study Social Support Survey (MOS-SSS) in caregivers of individuals with intellectual disabilities. This study included 185 caregivers of individuals with disabilities who were users of a non-governmental organization in southeastern Brazil. We performed exploratory and confirmatory factor analyses, internal consistency reliability, and predictive validity analyses. Our results demonstrated a one-dimensional internal structure for the adapted scale, consisting of nineteen items and presenting good precision coefficients (α = 0.96 and ω = 0.96) and composite reliability (0.96). Also, the MOS-SSS showed convergent validity with the Family APGAR Scale and the family support and self-control factors of the Informal Caregiver Burden Assessment Questionnaire-Short Version. These findings suggest that the Brazilian version of the MOS-SSS has adequate psychometric properties and can be used in this context and population.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.158
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.101
GPT teacher head0.400
Teacher spread0.299 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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