The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
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
Open accessAbstract
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.
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Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
In search of how people change: Applications to addictive behaviors.
Prochaska, J. O., DiClemente, C. C., & Norcross, J. C. (1992) · American Psychologist · doi:10.1037/0003-066x.47.9.1102 · Cited by 8,596
An ecological perspective on health promotion programs
McLeroy, K. R., Bibeau, D., Steckler, A., & Glanz, K. (1988) · Health Education Quarterly · doi:10.1177/109019818801500401 · Cited by 8,502
The Health Belief Model: a decade later.
Janz, N. K., & Becker, M. H. (1984) · Health Education Quarterly · doi:10.1177/109019818401100101 · Cited by 8,437
Glanz, K., & Bishop, D. B. (2010) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.012809.103604 · Cited by 2,336
A Meta-Analysis of the Effectiveness of Health Belief Model Variables in Predicting Behavior
Carpenter, C. J. (2010) · Health Communication · doi:10.1080/10410236.2010.521906 · Cited by 1,604 · cited 7×
“Hanson JA, Benedict JA: Use of the Health Belief Model to examine older adults' food-handling behaviors.”
MethodInfluentialBeyond frequency: Habit as mental construct
Verplanken, B. (2006) · British Journal of Social Psychology · doi:10.1348/014466605x49122 · Cited by 648
Achieving the ‘good life’: Why some people want latrines in rural Benin
Jenkins, M. W., & Curtis, V. (2005) · Social Science & Medicine · doi:10.1016/j.socscimed.2005.04.036 · Cited by 273
Hygiene: new hopes, new horizons
Curtis, V., Schmidt, W., Luby, S., Florez, R., Touré, O., & Biran, A. (2011) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(10)70224-3 · Cited by 228 · cited 3×
“2011) [34,35] Handwashing with soap Planning: teaching children manners”
BackgroundSelf-citationComparing the performance of indicators of hand-washing practices in rural Indian households
Biran, A., Rabie, T., Schmidt, W., Juvekar, S., Hirve, S., & Curtis, V. (2008) · Tropical Medicine & International Health · doi:10.1111/j.1365-3156.2007.02001.x · Cited by 145
Cited by
Luby, S. P., Rahman, M., Arnold, B. F., Unicomb, L., Ashraf, S., Winch, P. J., Stewart, C. P., Begum, F., Hussain, F., Benjamin-Chung, J., et al. (2018) · The Lancet Global Health · doi:10.1016/s2214-109x(17)30490-4 · Cited by 759
Self-citationPhysical interventions to interrupt or reduce the spread of respiratory viruses
Jefferson, T., Dooley, L., Ferroni, E., Al-Ansary, L. A., van Driel, M. L., Bawazeer, G. A., Jones, M. A., Hoffmann, T. C., Clark, J., Beller, E. M., et al. (2023) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd006207.pub6 · Cited by 291
De Buck, E., Van Remoortel, H., Hannes, K., Govender, T., Naidoo, S., Avau, B., Veegaete, A. V., Musekiwa, A., Lutje, V., Cargo, M., et al. (2017) · Campbell Systematic Reviews: Better Evidence for a Better World · doi:10.4073/csr.2017.7 · Cited by 99
Descending the sanitation ladder in urban Uganda: evidence from Kampala Slums
Kwiringira, J., Atekyereza, P., Niwagaba, C., & Günther, I. (2014) · BMC Public Health · doi:10.1186/1471-2458-14-624 · Cited by 96
French, M. A., Fiona Barker, S., Taruc, R. R., Ansariadi, A., Duffy, G. A., Saifuddaolah, M., Zulkifli Agussalim, A., Awaluddin, F., Zainal, Z., Wardani, J., et al. (2021) · Environment International · doi:10.1016/j.envint.2021.106679 · Cited by 63
“Our starting point is the core WASH theory of change: reducing child exposure to faecal-oral contamination will improve gastro-intestinal health and thus physical development outcomes.”
BackgroundMethodInfluentialSelf-citationHaque, S. S., & Freeman, M. C. (2021) · Environmental Health Perspectives · doi:10.1289/ehp7762 · Cited by 48
Benjamin-Chung, J., Crider, Y. S., Mertens, A., Ercumen, A., Pickering, A. J., Lin, A., Steinbaum, L., Swarthout, J., Rahman, M., Parvez, S. M., et al. (2021) · The Lancet Global Health · doi:10.1016/s2214-109x(20)30523-4 · Cited by 39
Self-citationYeasmin, F., Luby, S. P., Saxton, R. E., Nizame, F. A., Alam, M.-U., Dutta, N. C., Masud, A.-A., Yeasmin, D., Layden, A., Rahman, H., et al. (2017) · BMC Public Health · doi:10.1186/s12889-017-4693-x · Cited by 34
Self-citationAiemjoy, K., Stoller, N. E., Gebresillasie, S., Shiferaw, A., Tadesse, Z., Sewent, T., Ayele, B., Chanyalew, M., Aragie, S., Callahan, K., et al. (2017) · The American Society of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.16-0541 · Cited by 30
Hirai, M., Roess, A., Huang, C., & Graham, J. (2016) · Global Health Action · doi:10.3402/gha.v9.32833 · Cited by 29
Chaudhuri, I. N. (2017) · Frontiers in Public Health · doi:10.3389/fpubh.2017.00213 · Cited by 26
Winter, S., Dreibelbis, R., & Barchi, F. (2019) · Global Public Health · doi:10.1080/17441692.2018.1534256 · Cited by 24
Self-citationSaha, A., Moray, K. V., Devadason, D., Samuel, B., Daniel, S. E., Lalthazuali, Peter, J. V., Jamshed, J., Harigovind, M. R., Manne, M. R., et al. (2020) · Journal of Family Medicine and Primary Care · doi:10.4103/jfmpc.jfmpc_1519_20 · Cited by 13
Kanda, A., Ncube, E. J., & Voyi, K. (2022) · PLOS ONE · doi:10.1371/journal.pone.0265077 · Cited by 10
Neighborhood disorganization and women’s sanitation utilization practices in Mathare Valley, Kenya.
Winter, S., Barchi, F., & Dzombo, M. N. (2019) · Environment and Behavior · doi:10.1177/0013916518782577 · Cited by 7
Metadata
- Authors
- Dreibelbis, R., Winch, P. J., Leontsini, E., Hulland, K. R., Ram, P. K., Unicomb, L., & Luby, S. P.
- Venue
- BMC Public Health
- Published
- 2013-10-26
- Volume
- 13
- Issue
- 1
- Pages
- 1015-1015
- ISSN
- 1471-2458 (ISSN-L)
- OpenAlex
- W2035142200
- Cited by
- 413
- References
- 13
- FWCI
- 2.43
- Type
- journal article
- Language
- en
- Open access
- gold
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