The validity of the SF-12 and SF-6D instruments in people living with HIV/AIDS in Kenya
Bibliographic record
Abstract
BACKGROUND: Health-related quality of life (HRQoL) and health state utility value (HSUV) measurements are vital components of healthcare clinical and economic evaluations. Accurate measurement of HSUV and HRQoL require validated instruments. The 12-item Short-Form Health Survey (SF-12) is one of few instruments that can evaluate both HRQoL and HSUV, but its validity has not been assessed in people living with HIV/AIDS (PLWHA) in east Africa, where the burden of HIV is high. METHODS: This cross-sectional study used baseline data from a randomized trial involving PLWHA in Kenya. Data included responses from a translated and adapted SF-12 survey as well as key demographic and clinical data. Construct validity of the survey was examined by testing the SF-12's ability to distinguish between groups known in advance to have differences in their health based on their disease severity. We classified disease severity based on established definitions from the US Center for Disease Control (CDC) and WHO, as well as a previously studied viral load threshold. T-tests and ANOVA were used to test for differences in HRQoL and HSUV scores. Area under the receive operator curve (AUC) was used to test the discriminative ability of the HRQoL and HSUV instruments. RESULTS: Differences in physical component scores met the minimum clinically important difference among participants with more advanced HIV when defined by CD4 count (4.3 units) and WHO criteria (compared to stage 1, stages 2, 3 and 4 were 2.0, 7.2 and 9.8 units lower respectively). Mental score differences met the minimum clinically important difference between WHO stage 1 and stage 4 patients (4.4). Differences in the HSUV were statistically lower in more advanced HIV by all three definitions of severity. The AUC showed poor to weak discriminatory ability in most analyses, but had fair discriminatory ability between WHO clinical stage 1 and clinical stage 4 individuals (AUC = 0.71). CONCLUSION: Our findings suggest that the Kiswahili translated and adapted version of the SF-12 could be used as an assessment tool for physical health, mental health and HSUV for Kiswahili-speaking PLHWA. TRIAL REGISTRATION: Clinical trials.gov identifier: NCT00830622 . Registered 26 January 2009.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".