94 research outputs found

    Behavior Change without Behavior Change Communication: Nudging Handwashing among Primary School Students in Bangladesh.

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    Behavior change communication for improving handwashing with soap can be labor and resource intensive, yet quality results are difficult to achieve. Nudges are environmental cues engaging unconscious decision-making processes to prompt behavior change. In this proof-of-concept study, we developed an inexpensive set of nudges to encourage handwashing with soap after toilet use in two primary schools in rural Bangladesh. We completed direct observation of behaviors at baseline, after providing traditional handwashing infrastructure, and at multiple time periods following targeted handwashing nudges (1 day, 2 weeks, and 6 weeks). No additional handwashing education or motivational messages were completed. Handwashing with soap among school children was low at baseline (4%), increasing to 68% the day after nudges were completed and 74% at both 2 weeks and 6 weeks post intervention. Results indicate that nudge-based interventions have the potential to improve handwashing with soap among school-aged children in Bangladesh and specific areas of further inquiry are discussed

    The Integrated Behavioural Model for Water, Sanitation, and Hygiene: a systematic review of behavioural models and a framework for designing and evaluating behaviour change interventions in infrastructure-restricted settings.

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    BACKGROUND: Promotion and provision of low-cost technologies that enable improved water, sanitation, and hygiene (WASH) practices are seen as viable solutions for reducing high rates of morbidity and mortality due to enteric illnesses in low-income countries. A number of theoretical models, explanatory frameworks, and decision-making models have emerged which attempt to guide behaviour change interventions related to WASH. The design and evaluation of such interventions would benefit from a synthesis of this body of theory informing WASH behaviour change and maintenance. METHODS: We completed a systematic review of existing models and frameworks through a search of related articles available in PubMed and in the grey literature. Information on the organization of behavioural determinants was extracted from the references that fulfilled the selection criteria and synthesized. Results from this synthesis were combined with other relevant literature, and from feedback through concurrent formative and pilot research conducted in the context of two cluster-randomized trials on the efficacy of WASH behaviour change interventions to inform the development of a framework to guide the development and evaluation of WASH interventions: the Integrated Behavioural Model for Water, Sanitation, and Hygiene (IBM-WASH). RESULTS: We identified 15 WASH-specific theoretical models, behaviour change frameworks, or programmatic models, of which 9 addressed our review questions. Existing models under-represented the potential role of technology in influencing behavioural outcomes, focused on individual-level behavioural determinants, and had largely ignored the role of the physical and natural environment. IBM-WASH attempts to correct this by acknowledging three dimensions (Contextual Factors, Psychosocial Factors, and Technology Factors) that operate on five-levels (structural, community, household, individual, and habitual). CONCLUSIONS: A number of WASH-specific models and frameworks exist, yet with some limitations. The IBM-WASH model aims to provide both a conceptual and practical tool for improving our understanding and evaluation of the multi-level multi-dimensional factors that influence water, sanitation, and hygiene practices in infrastructure-constrained settings. We outline future applications of our proposed model as well as future research priorities needed to advance our understanding of the sustained adoption of water, sanitation, and hygiene technologies and practices

    Household-level risk factors for secondary influenza-like illness in a rural area of Bangladesh

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    This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Objective To describe household‐level risk factors for secondary influenza‐like illness (ILI), an important public health concern in the low‐income population of Bangladesh. Methods Secondary analysis of control participants in a randomised controlled trial evaluating the effect of handwashing to prevent household ILI transmission. We recruited index‐case patients with ILI – fever (<5 years); fever, cough or sore throat (≥5 years) – from health facilities, collected information on household factors and conducted syndromic surveillance among household contacts for 10 days after resolution of index‐case patients’ symptoms. We evaluated the associations between household factors at baseline and secondary ILI among household contacts using negative binomial regression, accounting for clustering by household. Results Our sample was 1491 household contacts of 184 index‐case patients. Seventy‐one percentage reported that smoking occurred in their home, 27% shared a latrine with one other household and 36% shared a latrine with >1 other household. A total of 114 household contacts (7.6%) had symptoms of ILI during follow‐up. Smoking in the home (RRadj 1.9, 95% CI: 1.2, 3.0) and sharing a latrine with one household (RRadj 2.1, 95% CI: 1.2, 3.6) or >1 household (RRadj 3.1, 95% CI: 1.8–5.2) were independently associated with increased risk of secondary ILI. Conclusion Tobacco use in homes could increase respiratory illness in Bangladesh. The mechanism between use of shared latrines and household ILI transmission is not clear. It is possible that respiratory pathogens could be transmitted through faecal contact or contaminated fomites in shared latrines

    Air pollution dispersion from biomass stoves to neighboring homes in Mirpur, Dhaka, Bangladesh.

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    BACKGROUND: Indoor air pollution, including fine particulate matter (PM2.5) and carbon monoxide (CO), is a major risk factor for pneumonia and other respiratory diseases. Biomass-burning cookstoves are major contributors to PM2.5 and CO concentrations. However, high concentrations of PM2.5 (> 1000 μg/m3) have been observed in homes in Dhaka, Bangladesh that do not burn biomass. We described dispersion of PM2.5 and CO from biomass burning into nearby homes in a low-income urban area of Dhaka, Bangladesh. METHODS: We recruited 10 clusters of homes, each with one biomass-burning (index) home, and 3-4 neighboring homes that used cleaner fuels with no other major sources of PM2.5 or CO. We administered a questionnaire and recorded physical features of all homes. Over 24 h, we recorded PM2.5 and CO concentrations inside each home, near each stove, and outside one neighbor home per cluster. During 8 of these 24 h, we conducted observations for pollutant-generating activities such as cooking. For each monitor, we calculated geometric mean PM2.5 concentrations at 5-6 am (baseline), during biomass burning times, during non-cooking times, and over 24 h. We used linear regressions to describe associations between monitor location and PM2.5 and CO concentrations. RESULTS: We recruited a total of 44 homes across the 10 clusters. Geometric mean PM2.5 and CO concentrations for all monitors were lowest at baseline and highest during biomass burning. During biomass burning, linear regression showed a decreasing trend of geometric mean PM2.5 and CO concentrations from the biomass stove (326.3 μg/m3, 12.3 ppm), to index home (322.7 μg/m3, 11.2 ppm), neighbor homes sharing a wall with the index home (278.4 μg/m3, 3.6 ppm), outdoors (154.2 μg/m3, 0.7 ppm), then neighbor homes that do not share a wall with the index home (83.1 μg/m3,0.2 ppm) (p = 0.03 for PM2.5, p = 0.006 for CO). CONCLUSION: Biomass burning in one home can be a source of indoor air pollution for several homes. The impact of biomass burning on PM2.5 or CO is greatest in homes that share a wall with the biomass-burning home. Eliminating biomass burning in one home may improve air quality for several households in a community

    Social Influence on Handwashing with Soap: Results from a Cluster Randomized Controlled Trial in Bangladesh.

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    We analyzed data from a cluster-randomized controlled trial conducted among 20 schools in Rajshahi, Bangladesh, to explore the role of social influence on handwashing with soap (HWWS) in a primary school setting. Using data collected through covert video cameras outside of school latrines, we used robust Poisson regression analysis to assess the impact of social influence-defined as the presence of another person near the handwashing location-on HWWS after a toileting event. In adjusted analyses, we found a 30% increase in HWWS when someone was present, as compared with when a child was alone (Prevalence ratio 1.30; 95% confidence interval: 1.14-1.47, P < 0.001). The highest prevalence of HWWS was found when both child(ren) and adult(s) were present or when just children were present (64%). Our study supports the conclusion that the presence of another individual after a toileting event can positively impact HWWS in a primary school setting

    Designing a handwashing station for infrastructure-restricted communities in Bangladesh using the integrated behavioural model for water, sanitation and hygiene interventions (IBM-WASH).

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    BACKGROUND: In Bangladesh diarrhoeal disease and respiratory infections contribute significantly to morbidity and mortality. Handwashing with soap reduces the risk of infection; however, handwashing rates in infrastructure-restricted settings remain low. Handwashing stations--a dedicated, convenient location where both soap and water are available for handwashing--are associated with improved handwashing practices. Our aim was to identify a locally feasible and acceptable handwashing station that enabled frequent handwashing for two subsequent randomized trials testing the health effects of this behaviour. METHODS: We conducted formative research in the form of household trials of improved practices in urban and rural Bangladesh. Seven candidate handwashing technologies were tested by nine to ten households each during two iterative phases. We conducted interviews with participants during an introductory visit and two to five follow up visits over two to six weeks, depending on the phase. We used the Integrated Behavioural Model for Water, Sanitation and Hygiene (IBM-WASH) to guide selection of candidate handwashing stations and data analysis. Factors presented in the IBM-WASH informed thematic coding of interview transcripts and contextualized feasibility and acceptability of specific handwashing station designs. RESULTS: Factors that influenced selection of candidate designs were market availability of low cost, durable materials that were easy to replace or replenish in an infrastructure-restricted and shared environment. Water storage capacity, ease of use and maintenance, and quality of materials determined the acceptability and feasibility of specific handwashing station designs. After examining technology, psychosocial and contextual factors, we selected a handwashing system with two different water storage capacities, each with a tap, stand, basin, soapy water bottle and detergent powder for pilot testing in preparation for the subsequent randomized trials. CONCLUSIONS: A number of contextual, psychosocial and technological factors influence use of handwashing stations at five aggregate levels, from habitual to societal. In interventions that require a handwashing station to facilitate frequent handwashing with soap, elements of the technology, such as capacity, durability and location(s) within the household are key to high feasibility and acceptability. More than one handwashing station per household may be required. IBM-WASH helped guide the research and research in-turn helped validate the framework

    Categorising interventions to levels of inpatient care for small and sick newborns: Findings from a global survey.

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    BACKGROUND: In 2017, 2.5 million newborns died, mainly from prematurity, infections, and intrapartum events. Preventing these deaths requires health systems to provide routine and emergency care at birth, and quality inpatient care for small and sick newborns. Defined levels of emergency obstetric care (EmOC) and standardised measurement of "signal functions" has improved tracking of maternal care in low- and middle-income countries (LMICs). Levels of newborn care, particularly for small and sick newborns, and associated signal functions are still not consistently defined or tracked. METHODS: Between November 2016-November 2017, we conducted an online survey of professionals working in maternal and newborn health. We asked respondents to categorise 18 clinical care interventions that could act as potential signal functions for small and sick newborns to 3 levels of care they thought were appropriate for health systems in LMICs to provide: "routine care at birth", "special care" and "intensive care". We calculated the percentage of respondents that classified each intervention at each level of care and stratified responses to look at variation by respondent characteristics. RESULTS: Six interventions were classified to specific levels by more than 50% of respondents as "routine care at birth," three interventions as "special care" and one as "intensive care". Eight interventions were borderline between these care levels. Responses were more consistent for interventions with relevant WHO clinical care guidelines while more variation in respondents' classification was observed in complex interventions that lack standards or guidelines. Respondents with experience in lower-income settings were more likely to assign a higher level of care for more complex interventions. CONCLUSIONS: Results were consistent with known challenges of scaling up inpatient care in lower-income settings and underline the importance of comprehensive guidelines and standards for inpatient care. Further work is needed to develop a shortlist of newborn signal functions aligned with emergency obstetric care levels to track universal health coverage for mothers and their newborns
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