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Association between attitudes of stigma toward mental illness and attitudes toward adoption of evidence-based practice within health care providers in Bahrain.

ABSTRACT: The health care system is one of the key areas where people with mental illnesses could experience stigma. Clinicians can hold stigma attitudes during their interactions with patients with mental illness. To improve the quality of mental health services and primary care, evidence-based practices should be disseminated and implemented. In this study, we evaluated the attitudes of health care providers in Bahrain toward people with mental illness and adoption of evidence-based practice using the Opening Minds Stigma Scale for Healthcare Providers (OMS-HC) and Evidence-Based Practice Attitude Scale (EBPAS). We conducted a cross-sectional study across 12 primary health care centers and a psychiatric hospital (the country's main mental health care facility). A self-report questionnaire was distributed among all health care providers. A total of 547 health care providers participated, with 274 from mental health services and 273 from primary care services. Results of the OMS-HC indicated differences between both main groups and subgroups. Regression model analysis reported significant outcomes. There was no statistical difference found between both groups in EBPAS scores. A weak but statistically significant negative association was reported between both scales. Participants showed varying stigma attitudes across different working environments, with less stigma shown in mental health services than in primary care services. Providers who were more open to adopting evidence-based practices showed less stigma toward people with mental illness. Comparing our findings with previous research showed that health care providers in Bahrain hold more stigma attitudes than other groups studied. We hope that this study serves as an initial step toward future campaigns against the stigma of mental illness in Bahrain and across the region.

SUBMITTER: Al Saif F

PROVIDER: S-EPMC6886841 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Project description:BackgroundAlthough risk prediction has become an integral part of clinical practice guidelines for cardiovascular disease (CVD) prevention, multiple studies have shown that patients' risk still plays almost no role in clinical decision-making. Because little is known about why this is so, we sought to understand providers' views on the opportunities, barriers, and facilitators of incorporating risk prediction to guide their use of cardiovascular preventive medicines.MethodsWe conducted semi-structured interviews with primary care providers (n = 33) at VA facilities in the Midwest. Facilities were chosen using a maximum variation approach according to their geography, size, proportion of MD to non-MD providers, and percentage of full-time providers. Providers included MD/DO physicians, physician assistants, nurse practitioners, and clinical pharmacists. Providers were asked about their reaction to a hypothetical situation in which the VA would introduce a risk prediction-based approach to CVD treatment. We conducted matrix and content analysis to identify providers' reactions to risk prediction, reasons for their reaction, and exemplar quotes.ResultsMost providers were classified as Enthusiastic (n = 14) or Cautious Adopters (n = 15), with only a few Non-Adopters (n = 4). Providers described four key concerns toward adopting risk prediction. Their primary concern was that risk prediction is not always compatible with a "whole patient" approach to patient care. Other concerns included questions about the validity of the proposed risk prediction model, potential workflow burdens, and whether risk prediction adds value to existing clinical practice. Enthusiastic, Cautious, and Non-Adopters all expressed both doubts about and support for risk prediction categorizable in the above four key areas of concern.ConclusionsProviders were generally supportive of adopting risk prediction into CVD prevention, but many had misgivings, which included concerns about impact on workflow, validity of predictive models, the value of making this change, and possible negative effects on providers' ability to address the whole patient. These concerns have likely contributed to the slow introduction of risk prediction into clinical practice. These concerns will need to be addressed for risk prediction, and other approaches relying on "big data" including machine learning and artificial intelligence, to have a meaningful role in clinical practice.

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Association between attitudes of stigma toward mental illness and attitudes toward adoption of evidence-based practice within health care providers in Bahrain.

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