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Record W2084195019 · doi:10.1016/s1055-3290(06)60198-2

How People With HIV/AIDS Manage and Assess Their Use of Complementary Therapies: A Qualitative Analysis

2002· article· en· W2084195019 on OpenAlexaff
James Gillett, Dorothy Pawluch, Roy Cain

Bibliographic record

VenueJournal of the Association of Nurses in AIDS Care · 2002
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsMcMaster UniversityUniversity of Windsor
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Qualitative researchMedicineAlternative medicineGrounded theoryPsychologyFamily medicineSociology

Abstract

fetched live from OpenAlex

The objective of this article is to provide a qualitative analysis of the practical concerns that people with HIV/AIDS have with regard to their use of complementary therapies. In-depth semistructured interviews were conducted with a diverse range of people with HIV/AIDS (N = 46). An inductive grounded approach was used to collect and analyze the data. There were five central concerns: (a) selecting which therapies to use, (b) judging which therapies work, (c) combining Western medicine with complementary therapies, (d) assessing the safety of complementary therapies, and (e) dealing with the barriers to the use of complementary therapies. A better understanding of the practical dimensions of complementary therapy use highlights the treatment and care issues that people with HIV/AIDS face and offers insights into the role that nurses might play in addressing some of these issues.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.019
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0070.006
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.053
GPT teacher head0.350
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations13
Published2002
Admission routes1
Has abstractyes

Explore more

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