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Record W2263606761 · doi:10.3109/01942638.2015.1101044

Establishing the Cultural Equivalence of the Young Children's Participation and Environment Measure (YC-PEM) for Use in Singapore

2015· article· en· W2263606761 on OpenAlexaff
Chun Yi Lim, Mary Law, Mary A. Khetani, Nancy Pollock, Peter Rosenbaum

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsMcMaster University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsComprehensionEquivalence (formal languages)Cultural issuesPsychologyPerceptionRelevance (law)Cultural diversityApplied psychologyCognitionConceptual frameworkCultural group selectionEthnic groupComputer scienceSociologyPolitical science

Abstract

fetched live from OpenAlex

AIMS: Establishing the cultural equivalence of clinical assessments is critical to ensuring culturally competent care. Developed in North America, the Young Children's Participation and Environment Measure (YC-PEM) is a caregiver questionnaire of participation in home, preschool, and community activities and perceptions of environmental impact on participation. The purpose of this study is to establish the cultural equivalence of YC-PEM content for use in Singapore. METHODS: We conducted semi-structured interviews with ten early childhood and healthcare providers and cognitive interviews with ten parents in Singapore to examine the relevance of original YC-PEM content (activities, environmental factors, item wording). Interviews were transcribed, summarized, and categorized according to item, semantic, conceptual, and operational dimensions of the Applied Cultural Framework that served as a decision-making guide to keep, modify, or delete the items. RESULTS: Providers and parents agreed on conceptual, item and semantic changes but less on operational changes. Significant changes were made to improve comprehension of the YC-PEM. CONCLUSIONS: Despite using the same language, the majority of the YC-PEM items needed modification to be relevant to the Singapore culture. Cultural adaptation of the YC-PEM is important because there are cultural differences in children's participation and their environments, as well as the way people understand words.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.264
GPT teacher head0.475
Teacher spread0.211 · 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.

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".

Quick stats

Citations28
Published2015
Admission routes1
Has abstractyes

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