The objective of this commentary is to develop a framework for assessing the rigour of qualitative approaches that identifies and distinguishes between the diverse objectives of qualitative health research, guided by a narrative review of the published literature on qualitative guidelines and standards from peer-reviewed journals and national funding organisations that support health services research, patient-centered outcomes research and other applied health research fields. In this framework, we identify and distinguish three objectives of qualitative studies in applied health research: exploratory, descriptive and comparative. For each objective, we propose methodological standards that may be used to assess and improve rigour across all study phases—from design to reporting. Similar to hierarchies of quality of evidence within quantitative studies, we argue that standards for qualitative rigour differ, appropriately, for studies with different objectives and should be evaluated as such. Distinguishing between different objectives of qualitative health research improves the ability to appreciate variation in qualitative studies and to develop appropriate evaluations of the rigour and success of qualitative studies in meeting their stated objectives. Researchers, funders and journal editors should consider how further developing and adopting the framework for assessing qualitative rigour outlined here may advance the rigour and potential impact of this important mode of inquiry.
Social scientists have long been concerned with how and why marginalized groups create and participate in subcultures. There has been significantly less work examining how those with access to conventional status and success participate in subcultures, often despite significant economic and social costs. The result has been lopsided theorizing that neglects much of the positive, affective, and moral appeal of subcultures at all levels of stratification. The participation of middle-class men and women in the rapidly growing world of cage-fighting speaks to this longstanding issue in the existing literature. We find these individuals participate in a sporting subculture that involves bodily, interpersonal, and professional sacrifices because they feel it gives them the ability to viscerally realize the widely shared American ideals that form the core components of their "moral world." The subculture holds particular sway over its members because they feel that its ideals, status hierarchies, and daily practices more directly embody the deeply embedded principles of middle-class morality and habitus than other elements of their lives.
This article employs an original empirical analysis to contribute to scientific understandings of the relationship between social characteristics and perceptions of discrimination in healthcare encounters within and across racial categories in the U.S. Our analysis focuses on a diverse sample of 43,020 adults aged 18 to 85 drawn from the California Health Interview Survey (CHIS). We use a series of weighted descriptive statistics and logistic regression models to parse out factors associated with perceived discrimination and chart how they vary by race and ethnicity. Members of racial minorities were more likely to report perceptions of discrimination, and while the effect was somewhat mitigated by introducing patient and health-care system factors into our models, the race effects remained both statistically significant and of substantial magnitude (particularly for African Americans and Native Americans). Poor self-reported health and communication difficulties in the clinical encounter were associated with increased perceptions of discrimination across all groups. Further, among non-whites, increased education was associated with increased perceptions of discrimination net of other factors. These findings suggest efforts to reduce disparities in medical care should continue to focus on expanding the depth and quality of patient–provider interactions for disadvantaged racial groups, while also being attentive to other factors that affect perceived racial discrimination in healthcare encounters within and across racial groups.
This article argues the advance of computational methods for analyzing, visualizing and disseminating social scientific data can provide substantial tools for ethnographers operating within the broadly realist ‘normal-scientific tradition’ (NST). While computation does not remove the fundamental challenges of method and measurement that are central to social research, new technologies provide resources for leveraging what NST researchers see as ethnography’s strengths (e.g. the production of in situ observations of people over time) while addressing what NST researchers see as ethnography’s weaknesses (e.g. questions of sample size, generalizability and analytical transparency). Specifically, we argue computational tools can help: (1) scale ethnography, (2) improve transparency, (3) allow basic replications, and (4) ultimately address fundamental concerns about internal and external validity. We explore these issues by illustrating the utility of three forms of ethnographic visualization enabled by computational advances – ethnographic heatmaps (ethnoarrays), a combination of participant observation data with techniques from social network analysis (SNA), and text mining. In doing so, we speak to the potential uses and challenges of nascent ‘computational ethnography.’
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