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Record W4388014842 · doi:10.1177/10731911231201145

Adequacy of the WHOQoL-BREF to Assess the Quality of Life of Victims of Armed Conflicts

2023· article· en· W4388014842 on OpenAlexaff
Liu Mok, Alina Wong, Antonio L. Manzanero, Marta Guarch-Rubio, José Carlos Celedón Rivero, Wilson Miguel Salas Picón

Bibliographic record

VenueAssessment · 2023
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsWestern University
FundersUniversidad Complutense de Madrid
KeywordsPsychologyQuality of life (healthcare)Clinical psychologyPsychometricsPsychotherapist

Abstract

fetched live from OpenAlex

There is a deterioration in the quality of life (QoL) of survivor victims of warlike conflicts. Because there is a need to guarantee the effectiveness of assessment tools for these populations, we studied the adequacy of the World Health Organization Quality of Life Questionnaire (WHOQoL-BREF) to assess the QoL of 1,136 surviving victims of the armed conflict in Colombia. Although this questionnaire has yielded promising results, questions remain about its psychometric suitability for specific populations. We used model modification at the item level, comparisons of models with different factor structures, and dimensionality analysis to address the psychometric problems encountered. Dimensionality analysis using a bifactor model suggests that WHOQoL-BREF total scores might be a more appropriate way of reporting results when model fit adequacy is not reached. Conclusions are offered on the psychometric properties of the WHOQoL-BREF, the evaluation of special populations, and possible strategies to address future questionnaire modifications.

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)0.000
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 score0.360
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.169
GPT teacher head0.481
Teacher spread0.313 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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