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      How participants report their health status: cognitive interviews of self-rated health across race/ethnicity, gender, age, and educational attainment

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          Abstract

          Background

          Self-rated health (SRH) is widely used to measure subjective health. Yet it is unclear what underlies health ratings, with implications for understanding the validity of SRH overall and across sociodemographic characteristics. We analyze participants’ explanations of how they formulated their SRH answer in addition to which health factors they considered and examine group differences in these processes.

          Methods

          Cognitive interviews were conducted with 64 participants in a convenience quota sample crossing dimensions of race/ethnicity (white, Latino, black, American Indian), gender, age, and education. Participants rated their health then described their thoughts when answering SRH. We coded participants’ answers in an inductive, iterative, and systematic process from interview transcripts, developing analytic categories (i.e., themes) and subdimensions within. We examined whether the presence of each dimension of an analytic category varied across sociodemographic groups.

          Results

          Our qualitative analysis led to the identification and classification of various subdimensions of the following analytic categories: types of health factors mentioned, valence of health factors, temporality of health factors, conditional health statements, and descriptions and definitions of health. We found differences across groups in some types of health factors mentioned—corresponding, conflicting, or novel with respect to prior research. Furthermore, we also documented various processes through which respondents integrate seemingly disparate health factors to formulate an answer through valence and conditional health statements. Finally, we found some evidence of sociodemographic group differences with respect to types of health factors mentioned, valence of health factors, and conditional health statements, highlighting avenues for future research.

          Conclusion

          This study provides a description of how participants rate their general health status and highlights potential differences in these processes across sociodemographic groups, helping to provide a more comprehensive understanding of how SRH functions as a measure of health.

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          Most cited references11

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          What do global self-rated health items measure?

          One of the most frequently used health status measures consists of a single item that asks respondents to rate their overall health as excellent, good, fair, or poor. This study identified the conceptual domain that is assessed by this self-rated health measure. Findings from 158 in-depth interviews revealed that the same frame of reference is not used by all respondents in answering this question. Some study participants think about specific health problems when asked to rate their health, whereas others think in terms of either general physical functioning or health behaviors. The data further revealed that the specific referents that are used vary by age. In addition, more tentative findings suggest that the use of specific referents may also vary by education and race. Finally, the results suggest that certain referents may not be related to closed-ended health ratings in predictable ways.
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            How is your health in general? A qualitative study on self-assessed health.

            The single-item measure on self-assessed health has been widely used, as it presents researchers with a summary of an individual's general state of health. A qualitative study was initiated to find out which particular aspects are included in health self-assessments; which aspects do people consider when answering the question 'How is your health in general?'. Subgroup differences were studied with respect to gender, age, health status and health assessment. Qualitative study with stratification by background characteristic, health status and health assessment (n=40). Almost 80% of the participants referred to one or more physical aspects (chronic illness, physical problems, medical treatment, age-related complaints, prognosis, bodily mechanics, and resilience). However, when assessing their health, participants also include aspects that go beyond the physical dimension of health. In total, 80 percent of the participants-whether or not in addition to physical aspects-referred to other health dimensions. Besides physical aspects, participants considered the extent to which they are able to perform (functional dimension -28%), the extent to which they adapted to, or their attitude towards an existing illness (coping dimension -28%), and simply the way they feel (wellbeing dimension -20%). In this study, health behaviour or lifestyle factors (behavioural dimension -3%) proved to be relatively unimportant in health self-assessments. Self-assessed health proved to be a multidimensional concept. For most part, subgroup differences in self-assessed health could be attributed to experience with ill health: being relatively inexperienced with health problems versus having a history of health problems.
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              Association of self-rated health with multimorbidity, chronic disease and psychosocial factors in a large middle-aged and older cohort from general practice: a cross-sectional study

              Background The prevalence of coexisting chronic conditions (multimorbidity) is rising. Disease labels, however, give little information about impact on subjective health and personal illness experience. We aim to examine the strength of association of single and multimorbid physical chronic diseases with self-rated health in a middle-aged and older population in England, and to determine whether any association is mediated by depression and other psychosocial factors. Methods 25 268 individuals aged 39 to 79 years recruited from general practice registers in the European Prospective Investigation of Cancer (EPIC-Norfolk) study, completed a survey including self-rated health, psychosocial function and presence of common physical chronic conditions (cancer, stroke, heart attack, diabetes, asthma/bronchitis and arthritis). Logistic regression models determined odds of “moderate/poor” compared to “good/excellent” health by condition and number of conditions adjusting for psychosocial measures. Results One-third (8252) reported one, around 7.5% (1899) two, and around 1% (194) three or more conditions. Odds of “moderate/poor” self-rated health worsened with increasing number of conditions (one (OR = 1.3(1.2–1.4)) versus three or more (OR = 3.4(2.3–5.1)), and were highest where there was comorbidity with stroke (OR = 8.7(4.6–16.7)) or heart attack (OR = 8.5(5.3–13.6)). Psychosocial measures did not explain the association between chronic diseases and multimorbidity with self-rated health.The relationship of multimorbidity with self-rated health was particularly strong in men compared to women (three or more conditions: men (OR = 5.2(3.0–8.9)), women OR = 2.1(1.1–3.9)). Conclusions Self-rated health provides a simple, integrative patient-centred assessment for evaluation of illness in the context of multiple chronic disease diagnoses. Those registering in general practice in particular men with three or more diseases or those with cardiovascular comorbidities and with poorer self-rated health may warrant further assessment and intervention to improve their physical and subjective health.
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                Author and article information

                Contributors
                1(773) 508-3445 , dgarbarski@luc.edu
                dykema@ssc.wisc.edu
                kcroes@ssc.wisc.edu
                dfedwards@education.wisc.edu
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                4 October 2017
                4 October 2017
                2017
                : 17
                : 771
                Affiliations
                [1 ]ISNI 0000 0001 1089 6558, GRID grid.164971.c, Department of Sociology, , Loyola University Chicago, ; Coffey Hall 440, 1032 W. Sheridan Rd, Chicago, IL 60660 USA
                [2 ]ISNI 0000 0001 2167 3675, GRID grid.14003.36, University of Wisconsin Survey Center, , University of Wisconsin-Madison, ; 475 N. Charter Street, Room 4308, Madison, WI 53706 USA
                [3 ]ISNI 0000 0001 2167 3675, GRID grid.14003.36, University of Wisconsin Survey Center, , University of Wisconsin-Madison, ; 475 N. Charter Street, Room 4416, Madison, WI 53706 USA
                [4 ]ISNI 0000 0001 2167 3675, GRID grid.14003.36, Departments of Kinesiology-Occupational Therapy Program, Neurology and Medicine, , University of Wisconsin-Madison, ; 2170 Medical Science Center, 1300 University Avenue, Madison, WI 53706-1532 USA
                Author information
                http://orcid.org/0000-0002-7764-9751
                Article
                4761
                10.1186/s12889-017-4761-2
                5628425
                28978325
                b9577432-6a73-45ea-902b-d926f88d2c66
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 12 April 2017
                : 14 September 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100006545, National Institute on Minority Health and Health Disparities;
                Award ID: P60MD003428
                Funded by: FundRef http://dx.doi.org/10.13039/100009633, Eunice Kennedy Shriver National Institute of Child Health and Human Development;
                Award ID: T32 HD049302
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: R24 HD047873
                Award ID: P30 AG017266
                Funded by: FundRef http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;
                Award ID: UL1TR000427
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Public health
                us,self-rated health,cognitive interviewing,grounded theory coding,evaluative frameworks,response process,health disparities,sociodemographic differences

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