Evaluating the Preliminary Effectiveness of the Person-Centered Care Assessment Tool (PCC-AT) in Zambian Health Facilities: Protocol for a Mixed Methods Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Person-centered care (PCC) within HIV treatment services has demonstrated potential to overcome inequities in HIV service access while improving treatment outcomes. Despite PCC being widely considered a best practice, no consensus exists on its assessment and measurement. This study in Zambia builds upon previous research that informed development of a framework for PCC and a PCC assessment tool (PCC-AT). OBJECTIVE: This mixed methods study aims to examine the preliminary effectiveness of the PCC-AT through assessing the association between client HIV service delivery indicators and facility PCC-AT scores. We hypothesize that facilities with higher PCC-AT scores will demonstrate more favorable HIV treatment continuity, viral load (VL) coverage, and viral suppression in comparison to those of facilities with lower PCC-AT scores. METHODS: We will implement the PCC-AT at 30 randomly selected health facilities in the Copperbelt and Central provinces of Zambia. For each study facility, data will be gathered from 3 sources: (1) PCC-AT scores, (2) PCC-AT action plans, and (3) facility characteristics, along with service delivery data. Quantitative analysis, using STATA, will include descriptive statistics on the PCC-AT results stratified by facility characteristics. Cross-tabulations and/or regression analysis will be used to determine associations between scores and treatment continuity, VL coverage, and/or viral suppression. Qualitative data will be collected via action planning, with detailed notes collected and recorded into an action plan template. Descriptive coding and emerging themes will be analyzed with NVivo software. RESULTS: As of May 2024, we enrolled 29 facilities in the study and data analysis from the key informant interviews is currently underway. Results are expected to be published by September 2024. CONCLUSIONS: Assessment and measurement of PCC within HIV treatment settings is a novel approach that offers HIV treatment practitioners the opportunity to examine their services and identify actions to improve PCC performance. Study results and the PCC-AT will be broadly disseminated for use among all project sites in Zambia as well as other HIV treatment programs, in addition to making the PCC-AT publicly available to global HIV practitioners. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54129.
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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 | 0.115 | 0.081 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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".