The Impact of Primary Care Providers’ Bias on Depression Screening for Lesbian Women

Primary care providers’ (PCPs) implicit and explicit bias can adversely affect health outcomes of lesbian women including their mental health. Practice guidelines recommend universal screening for depression in primary care settings, yet the guidelines often are not followed. The intersection of PCPs’ implicit and explicit bias toward lesbian women may lead to even lower screening and diagnosis of depression in the lesbian population than in the general population. The purpose of this secondary analysis was to examine the relationship between PCPs’ implicit and explicit bias toward lesbian women and their recommendations for depression screening in this population. PCPs ( n = 195) in Kentucky completed a survey that included bias measures and screening recommendations for a simulated lesbian patient. Bivariate inferential statistical tests were conducted to compare the implicit and explicit bias scores of PCPs who recommended depression screening and those who did not. PCPs who recommended depression screening demonstrated more positive explicit attitudes toward lesbian women ( p < .05) and their implicit bias scores were marginally lower than the providers who did not recommend depression screening (p = .068). Implications for practice: Depression screening rates may be even lower for lesbian women due to implicit and explicit bias toward this population. Training to increase providers’ awareness of bias and its harm is the first step to improve primary care for lesbian women. Policies must protect against discrimination based on sexual orientation or gender identity.

Psychometric Properties of Screening Questionnaires To Detect Depression In Primary Healthcare Setting In Rural Ethiopia

Background: Much of the research about the validity of depression screening questionnaires is on criterion validity. Evidence is scarce on the concurrent, convergent and construct validity of these measures, particularly from low-income countries. This study aimed to evaluate the psychometric properties of depression screening questionnaires in primary healthcare (PHC) in rural Ethiopia. Methods: A facility-based cross-sectional study was conducted with 587 participants recruited from patients attending three PHC facilities and two Holy water sites. The psychometric properties of five mental health screening questionnaires were evaluated: the nine item Patient Health Questionnaire (PHQ-9), the two item version of PHQ-9 (PHQ-2), a version of PHQ-9 with two added items of irritability and noise intolerance (PHQ-11), the Patient Health Questionnaire-15 (PHQ-15), and the World Health Organization-Five Well-being Index (WHO-5). Clinical diagnosis of depression was ascertained by psychiatrists using a semi-structured interview. We analyzed data using exploratory factor analysis, Spearman’s rank order correlation coefficient (Rho), the Mann Whitney test of the equality of medians, univariate logistic regression and Cronbach’s alpha. Results: PHQ-9, PHQ-11 and WHO-5 were found to be unidimensional, with items in each scale highly loading onto one factor (factor loadings ranging from 0.64 to 0.87). The items of each instrument were internally consistent, with Cronbach’s alpha ranging from 0.72 (PHQ-2) to 0.89 (PHQ-11). Scores for all screening scales were moderately or highly correlated with each other (Rho= 0.58 to 0.98) and moderately correlated with anxiety and disability scores. Median scores of all screening scales were significantly higher in those diagnosed with depression. The association of items measuring emotional and cognitive symptoms with the diagnosis of depression was stronger than the association with items measuring somatic symptoms. Irritability and noise intolerance had higher association with depression diagnosis than PHQ-9 items. Conclusion: Emotional and cognitive symptoms are more useful than somatic symptoms to predict the diagnosis of depression. Irritability and noise intolerance are more useful to detect depression. Future research should focus on testing the unidimensionality of PHQ-9, PHQ-11 and WHO-5 using confirmatory factor analysis; establishing the criterion validity of PHQ-11 and WHO-5; and on assessing test-retest reliability of all the measures.

Designing Depression Screening Chatbots

Advances in voice recognition, natural language processing, and artificial intelligence have led to the increasing availability and use of conversational agents (chatbots) in different settings. Chatbots are systems that mimic human dialogue interaction through text or voice. This paper describes a series of design considerations for integrating chatbots interfaces with health services. The present paper is part of ongoing work that explores the overall implementation of chatbots in the healthcare context. The findings have been created using a research through design process, combining (1) literature survey of existing body of knowledge on designing chatbots, (2) analysis on state-of-the-practice in using chatbots as service interfaces, and (3) generative process of designing a chatbot interface for depression screening. In this paper we describe considerations that would be useful for the design of a chatbot for a healthcare context.