Patient‐reported outcome measures in adult <scp>HIV</scp> care: A rapid scoping review of targeted outcomes and instruments used
Bibliographic record
Abstract
OBJECTIVE: There is international interest in the integration of patient-reported outcome measures (PROMs) into routine HIV care, but little work has synthesized the content of published initiatives. We conducted a rapid scoping review primarily to identify their selected patient-reported outcomes and respective instruments. METHODS: Four databases were searched on 4 May 2022 (Medline, Embase, CINAHL and PsychINFO) for relevant English language documents published from 2005 onwards. Dual review of at least 20% of records, full texts and data extraction was performed. Outcomes and instruments were classified with an adapted 14-domain taxonomy. Instruments with evidence of validation were described. RESULTS: Of 13 062 records generated for review, we retained a final sample of 94 documents, referring to 60 distinct initiatives led mostly in the USA (n = 29; 48% of initiatives), Europe (n = 16; 27%) and Africa (n = 9; 15%). The measured patient-reported outcome domains were: mental health (n = 42; 70%), substance use (n = 23; 38%), self-management (n = 16; 27%), symptoms (n = 12; 20%), sexual/reproductive health (n = 12; 20%), physical health (n = 9; 15%), treatment (n= 8; 13%), cognition (n = 7; 12%), quality of life (n = 7; 12%), violence/abuse (n = 6; 10%), stigma (n = 6; 10%), socioeconomic issues (n = 5; 8%), social support (n = 3; 5%) and body/facial appearance (n = 1; 2%). Initiatives measured 2.6 outcome domains, on average (range = 1-11). In total, 62 distinct validated PROMs were identified, with 53 initiatives (88%) employing at least one (M = 2.2). Overwhelmingly, the most used instrument was any version of the Patient Health Questionnaire to measure symptoms of depression, employed by over a third (26; 43%) of initiatives. CONCLUSION: Published PROM initiatives in HIV care have spanned 19 countries and disproportionately target mental health and substance use.
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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 | 0.098 | 0.223 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.032 | 0.037 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".