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Record W4409655735 · doi:10.46413/boneyusbad.1517554

Mcgill Empowerment Assessment-Diabetes Questionnaire: Turkish Validity and Reliability Study

2025· article· en· W4409655735 on OpenAlexaboutno aff
Seda Karaman, Gülcan Bahçecioğlu Turan, Zülfünaz Özer

Bibliographic record

VenueBandırma Onyedi Eylül Üniversitesi Sağlık Bilimleri ve Araştırmaları Dergisi · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHealth Education and Validation
Canadian institutionsnot available
Fundersnot available
KeywordsTurkishReliability (semiconductor)ValidityEmpowermentPsychologyDiabetes mellitusClinical psychologyApplied psychologyGerontologyMedicinePsychometricsPolitical sciencePower (physics)PhysicsEndocrinology

Abstract

fetched live from OpenAlex

Aim: The present study aimed to examine the Turkish validity and reliability of the McGill Empowerment Assessment-Diabetes (MEA-D) Questionnaire in individuals with diabetes. Material and Method: The present study was conducted in methodological design. This methodological study was conducted on 300 individuals diagnosed with diabetes. Personal information form and MEA-D were used to collect the data. Exploratory and confirmatory factor analysis, Cronbach’s alpha, item-total score correlation, and test-retest analysis were used to evaluate the data collected. Results: Factor loads of items were between 0.64-0.92. Fit index values were x²/SD 1.90, CFI = 0.97, NFI = 0.92, IFI = 0.96, TLI = 0.95 RMSEA = 0.078, RMR = 0.07, and SRMR = 0.08. Sub-dimensions had Cronbach’s Alpha values between 0.92 and 0.98, while total Cronbach’s alpha value was 0.96. It was concluded that the Turkish version of the 28-item and 4 sub-dimension questionnaire was confirmed with no changes to the original form. Conclusion: Turkish version of the MEA-D is a valid and reliable tool for evaluating the empowerment status of individuals diagnosed with diabetes and for being used in clinical settings.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.374
Teacher spread0.343 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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