Process evaluation of complex interventions in non-communicable and neglected tropical diseases in low- and middle-income countries: a scoping review
Bibliographic record
Abstract
OBJECTIVES: The aim of this review is to map out the use of process evaluation (PE) in complex interventions that address non-communicable diseases (NCDs) and neglected tropical diseases (NTDs) to identify gaps in the design and conduct, as well as strengths, limitations and implications, of this type of research in low- and middle-income countries (LMICs). DESIGN: Scoping review of PE studies of complex interventions implemented in LMICs. Six databases were searched focused on studies published since 2008. DATA SOURCES: Embase, PubMed, EbscoHost, Web of Science (WOS), Virtual Health Library (VHL) Regional Portal and Global Index Medicus: Regional Indexes AIM (AFRO), LILACS (AMRO/PAHO), IMEMR (EMRO), IMSEAR (SEARO), WPRIM (WPRO) Global Index Regional Indexes, MEDLINE, SciELO. ELIGIBILITY CRITERIA: Studies conducted in LMICs on PEs of randomised controlled trials (RCTs) and non-RCTs published between January 2008 and January 2020. Other criteria were studies of interventions for people at risk or having physical and mental NCDs, and/or NTDs, and/or their healthcare providers and/or others related to achieve better health for these two disease groups. Studies were excluded if they were not reported in English or Spanish or Portuguese or French, not peer-reviewed articles, not empirical research and not human research. DATA EXTRACTION AND SYNTHESIS: Data extracted to be evaluated were: available evidence in the utilisation of PE in the areas of NCDs and NTDs, including frameworks and theories used; methods applied to conduct PEs; and in a subsample, the barriers and facilitators to implement complex interventions identified through the PE. Variables were extracted and categorised. The information was synthesised through quantitative analysis by reporting frequencies and percentages. Qualitative analysis was also performed to understand facilitators and barriers presented in these studies. The implications for PEs, and how the information from the PE was used by researchers or other stakeholders were also assessed in this approach. RESULTS: 303 studies were identified, 79% were for NCDs, 12% used the label 'PE', 27% described a theory or framework for the PE, and 42% used mixed methods to analyse their findings. Acceptability, barriers and facilitators to implement the interventions, experiences and perceptions, and feasibility were the outcomes most frequently evaluated as part of the PEs. Barriers and facilitators themes identified were contextual factors, health system factors, human resources, attitudes and policy factors. CONCLUSIONS: PEs in NCDs and NTDs are used in LMICs with a wide variety of methods. This review identified many PEs that were not labelled by the authors as such, as well as a limited application of PE-related theories and frameworks, and heterogeneous reporting of this type of study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".