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Record W6889138125 · doi:10.25384/sage.c.6941866.v1

Short-Form HIV Disability Questionnaire Sensibility, Utility, and Implementation Considerations in Community-Based Settings: A Mixed Methods Study

2023· other· en· W6889138125 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSensibilityHuman immunodeficiency virus (HIV)Focus groupQualitative researchPerspective (graphical)Quality of life (healthcare)

Abstract

fetched live from OpenAlex

<b>Purpose:</b> We assessed the sensibility, utility, and implementation considerations of the Short-Form HIV Disability Questionnaire (SF-HDQ) in community-based settings. <b>Methods:</b> We conducted a mixed-methods study with adults living with HIV and community providers in seven community sites in Canada. We administered the SF-HDQ, a sensibility questionnaire and conducted semi-structured interviews. The SF-HDQ was sensible if median scores were ≥5/7(adults living with HIV) and ≥4/7(community providers) for ≥80% of the sensibility questionnaire items. Qualitative interview data were analyzed using content analysis. <b>Results:</b> Median sensibility scores were ≥5 for adults living with HIV (n = 44) and ≥4 for community providers (n = 10) for 95% and 100% of items, respectively. The SF-HDQ is comprehensive, represented disability, captured its episodic nature, and was easy to complete. Community utility included: facilitating communication and engagement with community; taking a snapshot of disability and tracking changes over time; guiding referrals; fostering self-reflection; and informing community programs. Considerations for implementation included flexible, person-centered approaches to mode and processes of administration, and communicating scores based on personal preferences among persons living with HIV. <b>Conclusion:</b> The SF-HDQ possesses sensibility and utility for use in community-based 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)0.038
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient 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: none
Teacher disagreement score0.631
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0380.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.152
GPT teacher head0.486
Teacher spread0.334 · 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
Published2023
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207