BACKGROUND: Understanding the social determinants underlying health disparities benefits from a mixed-methods, participatory research approach. OBJECTIVES: Photovoice was used in a research project seeking to identify and validate existing data and models used to address socio-spatial determinants of health in at-risk neighborhoods. METHODS: High-risk neighborhoods were identified using geospatial models of pre-identified social determinants of health. Students living within these neighborhoods were trained in Photovoice, and asked to take pictures of elements that influence their neighborhood's health and to create narratives explaining the photographs. RESULTS: Students took 300 photographs showing elements that they perceived affected community health. Negative factors included poor pedestrian access, inadequate property maintenance, pollution, and evidence of gangs, criminal activity, and vagrancy. Positive features included public service infrastructure and outdoor recreation. Photovoice data confirmed and contextualized the geospatial models while building community awareness and capacity. CONCLUSIONS: Photovoice can be a useful research tool for building community capacity and validating quantitative data describing social determinants of health.
BACKGROUND: Understanding the social determinants underlying health disparities benefits from a mixed-methods, participatory research approach. OBJECTIVES: Photovoice was used in a research project seeking to identify and validate existing data and models used to address socio-spatial determinants of health in at-risk neighborhoods. METHODS: High-risk neighborhoods were identified using geospatial models of pre-identified social determinants of health. Students living within these neighborhoods were trained in Photovoice, and asked to take pictures of elements that influence their neighborhood's health and to create narratives explaining the photographs. RESULTS: Students took 300 photographs showing elements that they perceived affected community health. Negative factors included poor pedestrian access, inadequate property maintenance, pollution, and evidence of gangs, criminal activity, and vagrancy. Positive features included public service infrastructure and outdoor recreation. Photovoice data confirmed and contextualized the geospatial models while building community awareness and capacity. CONCLUSIONS: Photovoice can be a useful research tool for building community capacity and validating quantitative data describing social determinants of health.
Authors: Caroline C Wang; Susan Morrel-Samuels; Peter M Hutchison; Lee Bell; Robert M Pestronk Journal: Am J Public Health Date: 2004-06 Impact factor: 9.308
Authors: Michael F Dulin; Thomas M Ludden; Hazel Tapp; Heather A Smith; Brisa Urquieta de Hernandez; Joshua Blackwell; Owen J Furuseth Journal: J Am Board Fam Med Date: 2010 Jan-Feb Impact factor: 2.657
Authors: Michael F Dulin; Thomas M Ludden; Hazel Tapp; Joshua Blackwell; Brisa Urquieta de Hernandez; Heather A Smith; Owen J Furuseth Journal: J Am Board Fam Med Date: 2010 Jan-Feb Impact factor: 2.657
Authors: Jonathan W Necheles; Emily Q Chung; Jennifer Hawes-Dawson; Gery Wayne Ryan; Shield B Williams; Heidi N Holmes; Kenneth B Wells; Mary E Vaiana; Mark A Schuster Journal: Prog Community Health Partnersh Date: 2007
Authors: Maren J Coffman; Brisa Urquieta de Hernandez; Heather A Smith; Andrew McWilliams; Yhenneko J Taylor; Hazel Tapp; Johanna Claire Schuch; Owen Furuseth; Michael Dulin Journal: Hisp Health Care Int Date: 2017-09-11
Authors: Alexandra F Lightfoot; Kari Thatcher; Florence M Simán; Eugenia Eng; Yesenia Merino; Tainayah Thomas; Tamera Coyne-Beasley; Mimi V Chapman Journal: Qual Soc Work Date: 2017-04-21
Authors: Daniel A Hackman; Stephanie A Robert; Jascha Grübel; Raphael P Weibel; Eirini Anagnostou; Christoph Hölscher; Victor R Schinazi Journal: Sci Rep Date: 2019-07-01 Impact factor: 4.379