Process evaluation of complex interventions in chronic and neglected tropical diseases in low- and middle-income countries—a scoping review protocol
Bibliographic record
Abstract
BACKGROUND: The use of process evaluations is a growing area of interest in research groups working on complex interventions. This methodology tries to understand how the intervention was implemented to inform policy and practice. A recent systematic review by Liu et al. on process evaluations of complex interventions addressing non-communicable diseases found few studies in low- and middle- income countries (LMIC) because it was restricted to randomized controlled trials, primary healthcare level and non-communicable diseases. Yet, LMICs face different barriers to implement interventions in comparison to high-income countries such as limited human resources, access to health care and skills of health workers to treat chronic conditions especially at primary health care level. Therefore, understanding the challenges of interventions for non-communicable diseases and neglected tropical diseases (diseases that affect poor populations and have chronic sequelae) will be important to improve how process evaluation is designed, conducted and used in research projects in LMICs. For these reasons, in comparison to the study of Liu et al., the current study will expand the search strategy to include different study designs, languages and settings. OBJECTIVE: Map research using process evaluation in the areas of non-communicable diseases and neglected tropical diseases to inform the gaps in the design and conduct of this type of research in LMICs. METHODS: Scoping review of process evaluation studies of randomized controlled trials (RCTs) and non-RCTs of complex interventions implemented in LMICs including participants with non-communicable diseases or neglected tropical diseases and their health care providers (physicians, nurses, technicians and others) related to achieve better health for all through reforms in universal coverage, public policy, service delivery and leadership. The aspects that will be evaluated are as follows: (i) available evidence of process evaluation in the areas of non-communicable diseases and neglected tropical diseases such as frameworks and theories, (ii) methods applied to conduct process evaluations and (iii) gaps between the design of the intervention and its implementation that were identified through the process evaluation. Studies published from January 2008. Exclusion criteria are as follows: not peer reviewed articles, not a report based on empirical research, not reported in English or Spanish or Portuguese or French, reviews and non-human research. DISCUSSION: This scoping review will map the evidence of process evaluations conducted in LMICs. It will also identify the methods they used to collect and interpret data, how different theories and frameworks were used and lessons from the implementation of complex interventions. This information will allow researchers to conduct better process evaluations considering special characteristics from countries with limited human resources, scarce data available and limited access to health care.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".