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Record W2130128075 · doi:10.1177/160940691301200101

Using Qualitative Methods to Assess the Measurement Property of a New HIV Disability Questionnaire

2013· article· en· W2130128075 on OpenAlexaff
Kelly K. O’Brien, Tarik Bereket, Marilyn Swinton, Patricia Solomon

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2013
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsInterviewRigourSensibilityQualitative researchPsychologyApplied psychologyCoding (social sciences)Data collectionTriangulationHuman immunodeficiency virus (HIV)Perspective (graphical)ReflexivityMedicineComputer scienceFamily medicineSociologyArtificial intelligence

Abstract

fetched live from OpenAlex

The purpose of this article is to describe our experience using a qualitative team approach and predetermined theoretical framework to assess sensibility of a newly developed HIV disability questionnaire. Two interviewers conducted structured qualitative interviews with 22 adults living with HIV, asking participants how well the questionnaire characterized the disability they experienced living with HIV. Data collection and analysis occurred over six stages with four analysts who met throughout. Strengths of our approach included the ability to assess the sensibility of the questionnaire from the perspective of adults living with HIV, collect and analyze data across multiple sites, establish a systematic team analytical process, and enhance rigour through multiple coding, team reflexivity, and interviewer and analyst triangulation. Challenges included increased resources required to coordinate and implement this approach, differential recruitment rates, initial divergent analytical styles, and the potential to miss emerging codes given the structured nature of the analysis. This article offers a methodological process for researchers to use a qualitative team approach with directed content analysis to assess the sensibility of a new health status questionnaire.

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)0.034
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.450
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.805
GPT teacher head0.699
Teacher spread0.107 · 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; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreMethods

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

Citations8
Published2013
Admission routes1
Has abstractyes

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