OBJECTIVE: Health care access may be a significant contributor to health outcome. However, few data exist on perception of barriers by patients in treatment, and attending a clinic visit does not mean that no barriers exist. Understanding barriers for treated populations is particularly important in optimizing care for high vulnerability populations, such as those with mental illness and the elderly. METHOD: A structured interview, demographic questionnaire, and SF-12 were administered to 324 veterans presenting for primary care or mental health appointments at a Veterans Affairs medical center. Principle components analysis was performed and relationships to vulnerability characteristics were identified. RESULTS: Most interview items showed modest mean levels but high variance. Responses were stable over three to six weeks. As hypothesized, perceived total barriers were greater in participants from several vulnerable populations: those receiving treatment for mental health problems, those with disabilities, and those with worse physical and mental function. Minority participants did not perceive greater barriers. An "inverted-U" relationship with age was found. Principal components analysis assigned 18 items across six clinically meaningful subscales. Participants with mental health treatment perceived greater barriers in three subscales including provider communication. Curvilinear relationships were again seen between subscales and age. CONCLUSIONS: Even individuals "in care" perceive barriers. Members of vulnerable populations, particularly those receiving mental health treatment, perceive greater barriers. Data support a multi-dimensional conceptualization of perceived barriers, and different subgroups experience different patterns of barriers.
OBJECTIVE: Health care access may be a significant contributor to health outcome. However, few data exist on perception of barriers by patients in treatment, and attending a clinic visit does not mean that no barriers exist. Understanding barriers for treated populations is particularly important in optimizing care for high vulnerability populations, such as those with mental illness and the elderly. METHOD: A structured interview, demographic questionnaire, and SF-12 were administered to 324 veterans presenting for primary care or mental health appointments at a Veterans Affairs medical center. Principle components analysis was performed and relationships to vulnerability characteristics were identified. RESULTS: Most interview items showed modest mean levels but high variance. Responses were stable over three to six weeks. As hypothesized, perceived total barriers were greater in participants from several vulnerable populations: those receiving treatment for mental health problems, those with disabilities, and those with worse physical and mental function. Minority participants did not perceive greater barriers. An "inverted-U" relationship with age was found. Principal components analysis assigned 18 items across six clinically meaningful subscales. Participants with mental health treatment perceived greater barriers in three subscales including provider communication. Curvilinear relationships were again seen between subscales and age. CONCLUSIONS: Even individuals "in care" perceive barriers. Members of vulnerable populations, particularly those receiving mental health treatment, perceive greater barriers. Data support a multi-dimensional conceptualization of perceived barriers, and different subgroups experience different patterns of barriers.
Authors: Lauren K Richards; Eric Bui; Meredith Charney; Katherine Clair Hayes; Allison L Baier; Paula K Rauch; Michael Allard; Naomi M Simon Journal: Community Ment Health J Date: 2016-05-07
Authors: Jennifer M Hensel; Valerie H Taylor; Kinwah Fung; Rebecca Yang; Simone N Vigod Journal: Can J Psychiatry Date: 2018-01-18 Impact factor: 4.356
Authors: Rachel Kimerling; Joanne Pavao; Liberty Greene; Julie Karpenko; Allison Rodriguez; Meghan Saweikis; Donna L Washington Journal: Med Care Date: 2015-04 Impact factor: 2.983
Authors: Allison L Baier; Luana Marques; Christina P C Borba; Hope Kelly; Katherine Clair-Hayes; Louise Dixon De Silva; Louis K Chow; Naomi M Simon Journal: Mil Psychol Date: 2018-12-20
Authors: Ann M Cheney; Christopher J Koenig; Christopher J Miller; Kara Zamora; Patricia Wright; Regina Stanley; John Fortney; James F Burgess; Jeffrey M Pyne Journal: BMC Health Serv Res Date: 2018-07-31 Impact factor: 2.655
Authors: Michelle M Hilgeman; Dr Robert J Cramer; Matthew C Hoch; Amber N Collins; Sasha Zabelski; Nicholas R Heebner Journal: Mil Med Date: 2022-03-21 Impact factor: 1.563