What are the barriers and facilitators to community handwashing with water and soap? A systematic review
Bibliographic record
Abstract
Handwashing with water and soap (HWWS) is an effective method of cleaning and disinfecting the surface of the hands. HWWS is effective in infection control and prevention transmission, such as in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). However, rates of handwashing compliance vary globally. This systematic review aimed to identify the barriers and facilitators to community HWWS globally. We conducted a comprehensive search strategy in OVID Medline, OVID Embase, Web of Science Core Collection, and Scopus using keywords and subject headings related to handwashing. Studies were excluded if they reported hand hygiene among healthcare or food service workers, considered the use of alcohol rubs, or involved an intervention in a healthcare or food preparation setting. The quality of eligible studies was assessed using the Mixed Methods Appraisal Tool, and data were extracted from the articles and analyzed using the Theoretical Domains Framework and inductive thematic analysis. The search strategy yielded a total of 11,696 studies, and 46 studies met the eligibility criteria. Study dates ranged from 2003 to 2020 and included 26 countries; the most frequently represented were Bangladesh, India, and Kenya. A total of 21 barriers and 23 facilitators to HWWS were identified and organized into the Theoretical Domains Framework. The most frequently cited domains were environmental context and resources, goals, and knowledge. Nine themes emerged from these barriers and facilitators: resource availability, cost and affordability, handwash station design and infrastructure, accessibility, gender roles, champions, health promotion, time management, and knowledge, beliefs, and behaviors. This review uncovered multiple barriers and facilitators around a determinant framework to observe and create an in-depth, multidimensional image of a community-based hand hygiene situation. New comprehensive interventions and implementation strategies can be developed using the findings to target the contextual barriers and facilitators to improve and increase HWWS rates. Stakeholders (i.e., practitioners, researchers, policymakers) can use the findings to revise, design, or evaluate new or existing projects, interventions, and policies to improve HWWS. Registration: A protocol for this systematic review was developed and uploaded onto the PROSPERO-International prospective register of systematic reviews database (Registration number: CRD42020221210).
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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 | 0.017 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".