The effect of physician self-disclosure on patient self-disclosure and patient perceptions of the physician

Kadji, Keou; Mast, Marianne Schmid

doi:10.1016/j.pec.2021.02.030

Cited by 14 publications

(14 citation statements)

References 42 publications

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“…In the first part of the mediation process (i.e., empathy → self-disclosure), our results demonstrated that empathy is positively related to self-disclosure. This finding is congruent with prior research that suggested that empathic individuals are prone to self-disclosure behaviors [ 28 ]. Additionally, in daily life, individual empathy includes self-disclosure behavior [ 60 ].…”

Section: Discussionsupporting

confidence: 91%

“…The results indicated that self-disclosure is a crucial explanatory mechanism through which empathy relates to community workers’ PTG. Specifically, empathic community workers tended to score higher on self-disclosure, which was related to higher levels of personal growth during the pandemic, consistent with past research [ 11 , 28 ]. In this sense, high self-disclosure is not only a reflection of empathic ability but also an internal antecedent of PTG.…”

Section: Discussionsupporting

confidence: 88%

“…Empathic counselors tend to share private and related experiences with clients and to yield more self-disclosure behaviors [ 27 ], which can help establish good consulting relationships and improve the consulting effect. Doctors with high empathy can obtain more personal information from patients through self-disclosure, which has a positive impact on diagnosis and treatment [ 28 ]. Additionally, empathic individuals’ self-disclosure can promote other people’s expressions of the same emotion or cognition.…”

Section: Introductionmentioning

confidence: 99%

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Empathy and Post-Traumatic Growth among Chinese Community Workers during the COVID-19 Pandemic: Roles of Self-Disclosure and Social Support

Dou

Liu

Xiong

et al. 2022

IJERPH

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Given the prolonged nature of the COVID-19 pandemic and its long-term psychological impacts, this study aimed to explore how empathy leads to post-traumatic growth (PTG) among Chinese community workers. Guided by the revised PTG model, this study identified the relation between empathy and PTG using a multiple mediation model that included self-disclosure and social support as hypothesized mediators. This study utilized data from 414 Chinese adults aged 20 years or older who completed an online survey during the pandemic. Self-disclosure and social support were measured as mediating variables. The study variables were positively correlated with PTG. Empathy was positively correlated with self-disclosure and social support. After controlling for demographic covariates, the results indicated that self-disclosure and social support mediated the link between empathy and PTG in both parallel and sequential fashion. Empathy, self-disclosure, and social support played important roles in the growth of Chinese community workers. The present findings have been useful in increasing our understanding, policy programs, and interventions by governments or regional bodies to ameliorate community workers’ PTG.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Empathy and Post-Traumatic Growth among Chinese Community Workers during the COVID-19 Pandemic: Roles of Self-Disclosure and Social Support

Dou

Liu

Xiong

et al. 2022

IJERPH

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“…SDoH can also be found within secure messages as well as during interactions with patient navigators. Previous studies show that patients’ self-disclosure depends on the gender of physicians and their own willingness to be open and disclose information to patients [ 33 ]. Additionally, the way questions are framed can dictate patients’ willingness to respond to sensitive questions about SDoH [ 34 ].…”

Section: Discussionmentioning

confidence: 99%

Barriers and Facilitators of Obtaining Social Determinants of Health of Patients With Cancer Through the Electronic Health Record Using Natural Language Processing Technology: Qualitative Feasibility Study With Stakeholder Interviews

Alpert¹,

Kim²,

McDonnell³

et al. 2022

JMIR Form Res

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Background Social determinants of health (SDoH), such as geographic neighborhoods, access to health care, education, and social structure, are important factors affecting people’s health and health outcomes. The SDoH of patients are scarcely documented in a discrete format in electronic health records (EHRs) but are often available in free-text clinical narratives such as physician notes. Innovative methods like natural language processing (NLP) are being developed to identify and extract SDoH from EHRs, but it is imperative that the input of key stakeholders is included as NLP systems are designed. Objective This study aims to understand the feasibility, challenges, and benefits of developing an NLP system to uncover SDoH from clinical narratives by conducting interviews with key stakeholders: (1) oncologists, (2) data analysts, (3) citizen scientists, and (4) patient navigators. Methods Individuals who frequently work with SDoH data were invited to participate in semistructured interviews. All interviews were recorded and subsequently transcribed. After coding transcripts and developing a codebook, the constant comparative method was used to generate themes. Results A total of 16 participants were interviewed (5 data analysts, 4 patient navigators, 4 physicians, and 3 citizen scientists). Three main themes emerged, accompanied by subthemes. The first theme, importance and approaches to obtaining SDoH, describes how every participant (n=16, 100%) regarded SDoH as important. In particular, proximity to the hospital and income levels were frequently relied upon. Communication about SDoH typically occurs during the initial conversation with the oncologist, but more personal information is often acquired by patient navigators. The second theme, SDoH exists in numerous forms, exemplified how SDoH arises during informal communication and can be difficult to enter into the EHR. The final theme, incorporating SDoH into health services research, addresses how more informed SDoH can be collected. One strategy is to empower patients so they are aware about the importance of SDoH, as well as employing NLP techniques to make narrative data available in a discrete format, which can provide oncologists with actionable data summaries. Conclusions Extracting SDoH from EHRs was considered valuable and necessary, but obstacles such as narrative data format can make the process difficult. NLP can be a potential solution, but as the technology is developed, it is important to consider how key stakeholders document SDoH, apply the NLP systems, and use the extracted SDoH in health outcome studies.

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“…Contrarily, if they don't want to disclose information, they will employ less words or speak nothing to express their opinions and attitudes ( 57 , 58 ). Therefore, the amount of disclosure is significantly correlated with the disclosure degree ( 58 , 59 ). To effectively represent the amount and degree of patient disclosure, for each patient we used the average length (in characters) of their textual messages (PTL) to indicate the patient's level of self-disclosure.…”

Section: Methodsmentioning

confidence: 99%

Patients' Self-Disclosure Positively Influences the Establishment of Patients' Trust in Physicians: An Empirical Study of Computer-Mediated Communication in an Online Health Community

Liu

et al. 2022

Front. Public Health

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With the development of telemedicine and e-health, usage of online health communities has grown, with such communities now representing convenient sources of information for patients who have geographical and temporal constraints regarding visiting physical health-care institutions. Many previous studies have examined patient–provider communication and health-care service delivery in online health communities; however, there is a dearth of research exploring the relationship between patients' level of self-disclosure and the establishment of patients' trust in physicians. Consequently, this study aims to explore how patients' self-disclosure affects the establishment of patients' trust in physicians. “Good Doctor,” which is a China-based online health community, was used as a data source, and a computer program was developed to download data for patient–physician communication on this community. Then, data for communications between 1,537 physicians and 63,141 patients were obtained. Ultimately, an empirical model was built to test our hypotheses. The results showed that patients' self-disclosure positively influences their establishment of trust in physicians. Further, physicians' provision of social support to patients showed a complete mediating effect on the relationship between patients' self-disclosure and patients' establishment of trust in physicians. Finally, evidence of “hope-for-help” motivation in patients' messages weakened the effect of patients' self-disclosure when physicians' social support was text-based, but strengthened it when physicians' social support was voice-based.

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The effect of physician self-disclosure on patient self-disclosure and patient perceptions of the physician

Cited by 14 publications

References 42 publications

Empathy and Post-Traumatic Growth among Chinese Community Workers during the COVID-19 Pandemic: Roles of Self-Disclosure and Social Support

Empathy and Post-Traumatic Growth among Chinese Community Workers during the COVID-19 Pandemic: Roles of Self-Disclosure and Social Support

Barriers and Facilitators of Obtaining Social Determinants of Health of Patients With Cancer Through the Electronic Health Record Using Natural Language Processing Technology: Qualitative Feasibility Study With Stakeholder Interviews

Patients' Self-Disclosure Positively Influences the Establishment of Patients' Trust in Physicians: An Empirical Study of Computer-Mediated Communication in an Online Health Community

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