<sec> <title>BACKGROUND</title> <p>The social media site Twitter has 145 ... more <sec> <title>BACKGROUND</title> <p>The social media site Twitter has 145 million daily active users worldwide, and has become a popular forum for users to communicate their healthcare concerns and experiences as patients. In the fall of 2018, a hashtag titled #DoctorsAreDickheads emerged, with almost 40,000 posts calling attention to healthcare experiences.</p> </sec> <sec> <title>OBJECTIVE</title> <p>We sought to identify common healthcare conditions and conceptual themes represented within the phenomenon of this viral Twitter hashtag.</p> </sec> <sec> <title>METHODS</title> <p>We analyzed a random 5% sample (N=500) of available tweets for qualitative analysis between the dates October 15 2018 – December 31st 2018, when the hashtag was most active. We dual coded 20% of the sample, and the remainder individually. We abstracted the user's healthcare role and clinical conditions from the tweet and user profile, and utilized a phenomenological content analysis to identify prevalent conceptual themes through sequential open coding, memoing, and discussion of concepts until agreement was reached.</p> </sec> <sec> <title>RESULTS</title> <p>Our final sample comprised 491 tweets and 282 unique Twitter users. In our sample, 49.8% were from patients or patient advocates, 4.3% caregivers, 9.4% healthcare professionals, 3.5% journalists/media; 1.4% academic/researchers, and 31.6% non-healthcare individuals/other. The most commonly mentioned clinical conditions were chronic pain, mental health, and musculoskeletal conditions (mainly Ehlers-Danlos Syndrome). We identified three major themes: disbelief in patients' experience and knowledge which contributes to medical errors and harm; the power differential between patients and providers; and metacommentary on the meaning and impact of the #DoctorsAreDickheads hashtag.</p> </sec> <sec> <title>CONCLUSIONS</title> <p>People publicly disclose personal and often troubling healthcare experiences on social media. This adds new accountability for the patient-provider interaction, and shapes the public's viewpoint of how clinicians behave. Hashtags such as this offer valuable opportunities to learn from patient experiences. Recommendations include developing best practices for providers to improve communication, supporting patients through challenging diagnoses, and promoting patient engagement.</p> </sec>
Background The social media site Twitter has 145 million daily active users worldwide and has bec... more Background The social media site Twitter has 145 million daily active users worldwide and has become a popular forum for users to communicate their health care concerns and experiences as patients. In the fall of 2018, a hashtag titled #DoctorsAreDickheads emerged, with almost 40,000 posts calling attention to health care experiences. Objective This study aims to identify common health care conditions and conceptual themes represented within the phenomenon of this viral Twitter hashtag. Methods We analyzed a random sample of 5.67% (500/8818) available tweets for qualitative analysis between October 15 and December 31, 2018, when the hashtag was the most active. Team coders reviewed the same 20.0% (100/500) tweets and the remainder individually. We abstracted the user’s health care role and clinical conditions from the tweet and user profile, and used phenomenological content analysis to identify prevalent conceptual themes through sequential open coding, memoing, and discussion of c...
Supplemental material, SUPPLEMENTAL_TABLES._2020.01.25 for Understanding the Role of Past Health ... more Supplemental material, SUPPLEMENTAL_TABLES._2020.01.25 for Understanding the Role of Past Health Care Discrimination in Help-Seeking and Shared Decision-Making for Depression Treatment Preferences by Ana M. Progovac, Dharma E. Cortés, Valeria Chambers, Jonathan Delman, Deborah Delman, Danny McCormick, Esther Lee, Selma De Castro, María José Sánchez Román, Natasha A. Kaushal, Timothy B. Creedon, Rajan A. Sonik, Catherine Rodriguez Quinerly, Caryn R. R. Rodgers, Leslie B. Adams, Ora Nakash, Afsaneh Moradi, Heba Abolaban, Tali Flomenhoft, Ruth Nabisere, Ziva Mann, Sherry Shu-Yeu Hou, Farah N. Shaikh, Michael Flores, Dierdre Jordan, Nicholas J. Carson, Adam C. Carle, Frederick Lu, Nathaniel M. Tran, Margo Moyer and Benjamin L. Cook in Qualitative Health Research
As a part of a larger, mixed-methods research study, we conducted semi-structured interviews with... more As a part of a larger, mixed-methods research study, we conducted semi-structured interviews with 21 adults with depressive symptoms to understand the role that past health care discrimination plays in shaping help-seeking for depression treatment and receiving preferred treatment modalities. We recruited to achieve heterogeneity of racial/ethnic backgrounds and history of health care discrimination in our participant sample. Participants were Hispanic/Latino ( n = 4), non-Hispanic/Latino Black ( n = 8), or non-Hispanic/Latino White ( n = 9). Twelve reported health care discrimination due to race/ethnicity, language, perceived social class, and/or mental health diagnosis. Health care discrimination exacerbated barriers to initiating and continuing depression treatment among patients from diverse backgrounds or with stigmatized mental health conditions. Treatment preferences emerged as fluid and shaped by shared decisions made within a trustworthy patient–provider relationship. Howev...
Background: Depression treatment disparities are well documented. Differing treatment preferences... more Background: Depression treatment disparities are well documented. Differing treatment preferences across social groups have been suggested as a cause of these disparities. However, existing studies of treatment preferences have been limited to individuals currently receiving clinical care, and existing measures of depression treatment preferences have not accounted for factors that may be disproportionately relevant to the preferences of disparities populations. This study therefore aimed to assess depression treatment preferences by race/ethnicity and gender in a representative community sample, while accounting for access to healthcare, provider characteristics, and past experiences of discrimination in healthcare settings. Methods: We conducted a nationally representative study of individuals with depression in and out of clinical care. Treatment preferences (medication versus talk therapy) were elicited through a discrete choice experiment that accounted for tradeoffs with factors related to access and provider characteristics deemed relevant by community stakeholders. Past discrimination was assessed through questions about unfair treatment from medical providers and front desk staff due to personal characteristics (e.g., race, gender). We used conditional logit models to assess treatment preferences by race/ethnicity and gender and examined whether preferences were associated with past experiences of healthcare discrimination. Results: Non-Hispanic white respondents (OR-here, the odds of a talk therapy preference over the odds of a medication preference: 0.80, 95% CI: 0.64, 0.99) and men (OR 0.76, 95% CI: 0.60, 0.96) preferred medication over talk therapy, while non-Hispanic black respondents, Hispanic respondents, and women did not prefer one over the other. Past discrimination in healthcare settings was associated with lower preferences for talk therapy and greater preferences for medication, particularly among non-Hispanic black respondents and women respondents. Conclusions: Addressing previous methodological limitations yielded estimates for depression treatment preferences by race/ethnicity and gender that differed from past studies. Also, past discrimination in healthcare settings was associated with current treatment preferences.
<sec> <title>BACKGROUND</title> <p>The social media site Twitter has 145 ... more <sec> <title>BACKGROUND</title> <p>The social media site Twitter has 145 million daily active users worldwide, and has become a popular forum for users to communicate their healthcare concerns and experiences as patients. In the fall of 2018, a hashtag titled #DoctorsAreDickheads emerged, with almost 40,000 posts calling attention to healthcare experiences.</p> </sec> <sec> <title>OBJECTIVE</title> <p>We sought to identify common healthcare conditions and conceptual themes represented within the phenomenon of this viral Twitter hashtag.</p> </sec> <sec> <title>METHODS</title> <p>We analyzed a random 5% sample (N=500) of available tweets for qualitative analysis between the dates October 15 2018 – December 31st 2018, when the hashtag was most active. We dual coded 20% of the sample, and the remainder individually. We abstracted the user's healthcare role and clinical conditions from the tweet and user profile, and utilized a phenomenological content analysis to identify prevalent conceptual themes through sequential open coding, memoing, and discussion of concepts until agreement was reached.</p> </sec> <sec> <title>RESULTS</title> <p>Our final sample comprised 491 tweets and 282 unique Twitter users. In our sample, 49.8% were from patients or patient advocates, 4.3% caregivers, 9.4% healthcare professionals, 3.5% journalists/media; 1.4% academic/researchers, and 31.6% non-healthcare individuals/other. The most commonly mentioned clinical conditions were chronic pain, mental health, and musculoskeletal conditions (mainly Ehlers-Danlos Syndrome). We identified three major themes: disbelief in patients' experience and knowledge which contributes to medical errors and harm; the power differential between patients and providers; and metacommentary on the meaning and impact of the #DoctorsAreDickheads hashtag.</p> </sec> <sec> <title>CONCLUSIONS</title> <p>People publicly disclose personal and often troubling healthcare experiences on social media. This adds new accountability for the patient-provider interaction, and shapes the public's viewpoint of how clinicians behave. Hashtags such as this offer valuable opportunities to learn from patient experiences. Recommendations include developing best practices for providers to improve communication, supporting patients through challenging diagnoses, and promoting patient engagement.</p> </sec>
Background The social media site Twitter has 145 million daily active users worldwide and has bec... more Background The social media site Twitter has 145 million daily active users worldwide and has become a popular forum for users to communicate their health care concerns and experiences as patients. In the fall of 2018, a hashtag titled #DoctorsAreDickheads emerged, with almost 40,000 posts calling attention to health care experiences. Objective This study aims to identify common health care conditions and conceptual themes represented within the phenomenon of this viral Twitter hashtag. Methods We analyzed a random sample of 5.67% (500/8818) available tweets for qualitative analysis between October 15 and December 31, 2018, when the hashtag was the most active. Team coders reviewed the same 20.0% (100/500) tweets and the remainder individually. We abstracted the user’s health care role and clinical conditions from the tweet and user profile, and used phenomenological content analysis to identify prevalent conceptual themes through sequential open coding, memoing, and discussion of c...
Supplemental material, SUPPLEMENTAL_TABLES._2020.01.25 for Understanding the Role of Past Health ... more Supplemental material, SUPPLEMENTAL_TABLES._2020.01.25 for Understanding the Role of Past Health Care Discrimination in Help-Seeking and Shared Decision-Making for Depression Treatment Preferences by Ana M. Progovac, Dharma E. Cortés, Valeria Chambers, Jonathan Delman, Deborah Delman, Danny McCormick, Esther Lee, Selma De Castro, María José Sánchez Román, Natasha A. Kaushal, Timothy B. Creedon, Rajan A. Sonik, Catherine Rodriguez Quinerly, Caryn R. R. Rodgers, Leslie B. Adams, Ora Nakash, Afsaneh Moradi, Heba Abolaban, Tali Flomenhoft, Ruth Nabisere, Ziva Mann, Sherry Shu-Yeu Hou, Farah N. Shaikh, Michael Flores, Dierdre Jordan, Nicholas J. Carson, Adam C. Carle, Frederick Lu, Nathaniel M. Tran, Margo Moyer and Benjamin L. Cook in Qualitative Health Research
As a part of a larger, mixed-methods research study, we conducted semi-structured interviews with... more As a part of a larger, mixed-methods research study, we conducted semi-structured interviews with 21 adults with depressive symptoms to understand the role that past health care discrimination plays in shaping help-seeking for depression treatment and receiving preferred treatment modalities. We recruited to achieve heterogeneity of racial/ethnic backgrounds and history of health care discrimination in our participant sample. Participants were Hispanic/Latino ( n = 4), non-Hispanic/Latino Black ( n = 8), or non-Hispanic/Latino White ( n = 9). Twelve reported health care discrimination due to race/ethnicity, language, perceived social class, and/or mental health diagnosis. Health care discrimination exacerbated barriers to initiating and continuing depression treatment among patients from diverse backgrounds or with stigmatized mental health conditions. Treatment preferences emerged as fluid and shaped by shared decisions made within a trustworthy patient–provider relationship. Howev...
Background: Depression treatment disparities are well documented. Differing treatment preferences... more Background: Depression treatment disparities are well documented. Differing treatment preferences across social groups have been suggested as a cause of these disparities. However, existing studies of treatment preferences have been limited to individuals currently receiving clinical care, and existing measures of depression treatment preferences have not accounted for factors that may be disproportionately relevant to the preferences of disparities populations. This study therefore aimed to assess depression treatment preferences by race/ethnicity and gender in a representative community sample, while accounting for access to healthcare, provider characteristics, and past experiences of discrimination in healthcare settings. Methods: We conducted a nationally representative study of individuals with depression in and out of clinical care. Treatment preferences (medication versus talk therapy) were elicited through a discrete choice experiment that accounted for tradeoffs with factors related to access and provider characteristics deemed relevant by community stakeholders. Past discrimination was assessed through questions about unfair treatment from medical providers and front desk staff due to personal characteristics (e.g., race, gender). We used conditional logit models to assess treatment preferences by race/ethnicity and gender and examined whether preferences were associated with past experiences of healthcare discrimination. Results: Non-Hispanic white respondents (OR-here, the odds of a talk therapy preference over the odds of a medication preference: 0.80, 95% CI: 0.64, 0.99) and men (OR 0.76, 95% CI: 0.60, 0.96) preferred medication over talk therapy, while non-Hispanic black respondents, Hispanic respondents, and women did not prefer one over the other. Past discrimination in healthcare settings was associated with lower preferences for talk therapy and greater preferences for medication, particularly among non-Hispanic black respondents and women respondents. Conclusions: Addressing previous methodological limitations yielded estimates for depression treatment preferences by race/ethnicity and gender that differed from past studies. Also, past discrimination in healthcare settings was associated with current treatment preferences.
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