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Quality of life and physical functioning in HIV‐infected individuals receiving antiretroviral therapy in KwaZulu‐Natal, South Africa

2008· article· en· W2111755410 on OpenAlexaff
Patricia McInerney, Busisiwe P. Ncama, Dean Wantland, Busisiwe Bhengu, Chris A. McGibbon, Sheila Davis, Inge B. Corless, Patrice K. Nicholas

Bibliographic record

VenueNursing and Health Sciences · 2008
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsAntiretroviral therapyMedicineQuality of life (healthcare)Social supportHuman immunodeficiency virus (HIV)Explained variationClinical psychologyGerontologyPsychologyViral loadFamily medicineNursing

Abstract

fetched live from OpenAlex

KwaZulu-Natal province, South Africa, accounts for 28.7% of the HIV infection total and one-third of infections among youth and children in South Africa. The purpose of this study was to examine the variables of HIV/AIDS symptoms, social support, influence of comorbid medical problems, length of time adhering to antiretroviral therapy medications, quality of life, adherence to antiretroviral medications, and physical functioning in HIV-infected individuals. Based on our model, the combination of these variables was found to determine physical functioning outcomes and adherence to HIV medications. Significant relationships were observed between physical functioning and the dependent variables of length of time on medications, comorbid health problems, and social support. A linear regression model was built to determine the degree to which these variables predicted physical functioning. In total, these predictor variables explained 29% of the variance in physical functioning. These results indicate that those individuals who reported a greater length of time on medications, fewer comorbid health problems, and greater social support had better physical functioning.

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)0.001
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 score0.039
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.150
GPT teacher head0.435
Teacher spread0.285 · 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

Citations47
Published2008
Admission routes1
Has abstractyes

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