Implementation of Direct-to-Patient Mobile Teledermatology in VA.

BACKGROUND: Innovative technology can enhance patient access to healthcare but must be successfully implemented to be effective. OBJECTIVE: We evaluated Department of Veterans Affairs' (VA's) implementation of My VA Images, a direct-to-patient asynchronous teledermatology mobile application enabling established dermatology patients to receive follow-up care remotely instead of in-person. DESIGN /PARTICIPANTS/APPROACH: Following pilot testing at 3 facilities, the app was introduced to 28 facilities (4 groups of 7) every 3 months using a stepped-wedge cluster-randomized design. Using the Organizational Theory of Implementation Effectiveness, we examined the app's implementation using qualitative and quantitative data consisting of encounter data from VA's corporate data warehouse; app usage from VA's Mobile Health database; bi-monthly reports from facility representatives; phone interviews with clinicians; and documented communications between the operational partner and facility staff. KEY RESULTS: Implementation policies and practices included VA's vision to expand home telehealth and marketing/communication strategies. The COVID-19 pandemic dominated the implementation climate by stressing staffing, introducing competing demands, and influencing stakeholder attitudes to the app, including its fit to their values. These factors were associated with mixed implementation effectiveness, defined as high quality consistent use. Nineteen of 31 exposed facilities prepared to use the app; 10 facilities used it for actual patient care, 7 as originally intended. Residents, nurse practitioners, and physician assistants were more likely than attendings to use the app. Facilities exposed to the app pre-pandemic were more likely to use and sustain the new process. CONCLUSIONS: Considerable heterogeneity existed in implementing mobile teledermatology, despite VA's common mission, integrated healthcare system, and stakeholders' broad interest. Identifying opportunities to target favorable facilities and user groups (such as teaching facilities and physician extenders, respectively) while addressing internal implementation barriers including incomplete integration with the electronic health record as well as inadequate staffing may help optimize the initial impact of direct-to-patient telehealth. The COVID pandemic was a notable extrinsic barrier. CLINICAL TRIALS REGISTRATION: NCT03241589.

Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis.

BACKGROUND: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings. OBJECTIVE: This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts. METHODS: Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score. RESULTS: Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (ß=-93.61, P<.001), increased sleep variability (ß=0.96, P<.001), and delayed circadian rhythms (ie, sleep onset: ß=0.55, P=.001; sleep offset: ß=1.12, P<.001; M10 onset: ß=0.73, P=.003; HR acrophase: ß=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (ß of PHQ-8 × spring = -31.51, P=.002) and summer (ß of PHQ-8 × summer = -42.61, P<.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (ß of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer. CONCLUSIONS: Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

Management of Depression in Adults: A Review.

Importance: Approximately 9% of US adults experience major depression each year, with a lifetime prevalence of approximately 17% for men and 30% for women. Observations: Major depression is defined by depressed mood, loss of interest in activities, and associated psychological and somatic symptoms lasting at least 2 weeks. Evaluation should include structured assessment of severity as well as risk of self-harm, suspected bipolar disorder, psychotic symptoms, substance use, and co-occurring anxiety disorder. First-line treatments include specific psychotherapies and antidepressant medications. A network meta-analysis of randomized clinical trials reported cognitive therapy, behavioral activation, problem-solving therapy, interpersonal therapy, brief psychodynamic therapy, and mindfulness-based psychotherapy all had at least medium-sized effects in symptom improvement over usual care without psychotherapy (standardized mean difference [SMD] ranging from 0.50 [95% CI, 0.20-0.81] to 0.73 [95% CI, 0.52-0.95]). A network meta-analysis of randomized clinical trials reported 21 antidepressant medications all had small- to medium-sized effects in symptom improvement over placebo (SMD ranging from 0.23 [95% CI, 0.19-0.28] for fluoxetine to 0.48 [95% CI, 0.41-0.55] for amitriptyline). Psychotherapy combined with antidepressant medication may be preferred, especially for more severe or chronic depression. A network meta-analysis of randomized clinical trials reported greater symptom improvement with combined treatment than with psychotherapy alone (SMD, 0.30 [95% CI, 0.14-0.45]) or medication alone (SMD, 0.33 [95% CI, 0.20-0.47]). When initial antidepressant medication is not effective, second-line medication treatment includes changing antidepressant medication, adding a second antidepressant, or augmenting with a nonantidepressant medication, which have approximately equal likelihood of success based on a network meta-analysis. Collaborative care programs, including systematic follow-up and outcome assessment, improve treatment effectiveness, with 1 meta-analysis reporting significantly greater symptom improvement compared with usual care (SMD, 0.42 [95% CI, 0.23-0.61]). Conclusions and Relevance: Effective first-line depression treatments include specific forms of psychotherapy and more than 20 antidepressant medications. Close monitoring significantly improves the likelihood of treatment success.

Quality Improvement Efforts in VA Community Living Centers Following Public Reporting of Performance.

For two decades, the U.S. government has publicly reported performance measures for most nursing homes, spurring some improvements in quality. Public reporting is new, however, to Department of Veterans Affairs nursing homes (Community Living Centers [CLCs]). As part of a large, public integrated healthcare system, CLCs operate with unique financial and market incentives. Thus, their responses to public reporting may differ from private sector nursing homes. In three CLCs with varied public ratings, we used an exploratory, qualitative case study approach involving semi-structured interviews to compare how CLC leaders (n = 12) perceived public reporting and its influence on quality improvement. Across CLCs, respondents said public reporting was helpful for transparency and to provide an "outside perspective" on CLC performance. Respondents described employing similar strategies to improve their public ratings: using data, engaging staff, and clearly defining staff roles vis-à-vis quality improvement, although more effort was required to implement change in lower performing CLCs. Our findings augment those from prior studies and offer new insights into the potential for public reporting to spur quality improvement in public nursing homes and those that are part of integrated healthcare systems.

Practices Supporting Electronic Health Record Transitions: Lessons from Four US Healthcare Systems.

BACKGROUND: Electronic health record (EHR) transitions are common and complex organizational changes, yet limited published literature is available to guide health systems that are changing from one EHR to another. Clinicians and staff end users at sites that have undergone EHR transitions may have critical insights that could inform future transitions. OBJECTIVE: To assess end user perspectives on organizational practices that support successful EHR transitions. DESIGN: Multi-site qualitative study of end users at healthcare systems that transitioned to a new EHR (either Epic or Cerner) within the prior 3 years. PARTICIPANTS: Forty-two participants, including providers, clinical leaders, and informaticists at four geographically and organizationally diverse US healthcare systems. APPROACH: We conducted semi-structured telephone interviews, which were audio-recorded and transcribed. We used content analysis to identify key practices that influenced EHR transition success. KEY RESULTS: Participants described specific organizational practices that they found most helpful in supporting EHR transitions, and these practices transcended individual sites and EHR systems. We categorized practices based on how they were described relative to the stage of implementation. During pre-go-live, recommended practices included communicate rationale and anticipated outcomes of the EHR change; understand baseline workflows; and plan for appropriate customization. During go-live, recommended practices included personalize training and support; invest in robust internal support; reduce workload expectations; and proactively address challenges. The recommended post-go-live practice was to continue to invest in the change. CONCLUSIONS: Our findings may act as a roadmap for future EHR transitions by identifying specific and actionable organizational practices across stages of implementation. These recommendations highlight the role of health system leaders in preparing for the organizational change, working with and supporting end users, and addressing challenges that arise.

From "Local Control" to "Dependency": Transitions to Single-Vendor Integrated Electronic Health Record Systems and Their Implications for the EHR Workforce.

BACKGROUND: Healthcare systems that previously used either a single legacy electronic health record (EHR) system or a "best-of-breed" combination of products from multiple vendors are increasingly adopting integrated, single-vendor EHR systems. Though healthcare leaders are beginning to recognize the dramatic collateral consequences of these transitions, their impact on the EHR workforce - internal actors most closely involved in governing and supporting the EHR - is poorly understood. OBJECTIVE: Identify perceived impacts of adopting single-vendor, integrated EHR systems on the institutional EHR workforce. DESIGN: In this qualitative study, we conducted semi-structured phone interviews in four healthcare systems in the USA that had adopted an integrated EHR within the previous five years. PARTICIPANTS: Forty-two staff members of four geographically and organizationally diverse healthcare systems, including 22 individuals with formal informatics roles. APPROACH: Transcribed interviews were coded and analyzed using qualitative content analysis methods. KEY RESULTS: Across organizations, participants described a loss of autonomy by the EHR workforce at the individual and institutional level following the adoption of an integrated EHR. We also identified references to transformations in four key professional functions of the EHR workforce: communication, governance, optimization, and education. CONCLUSIONS: Transitions to integrated EHR systems can have important implications for the autonomy and professional functions of the EHR workforce. These findings may help institutions embarking on similar transitions better anticipate and prepare for these changes through such practices as revising job descriptions, strengthening EHR governance structures, and reinforcing pathways to engage frontline clinicians in supporting the EHR. Findings may also help institutions structure vendor contracts in a way that anticipates and mitigates loss of autonomy.

Rural Veterans' Experiences with Social Risk Factors: Impacts, Challenges, and Care System Recommendations.

BACKGROUND: Social risk factors, such as food insecurity and financial needs, are associated with increased risk of cardiovascular diseases, health conditions that are highly prevalent in rural populations. A better understanding of rural Veterans' experiences with social risk factors can inform expansion of Veterans Health Administration (VHA) efforts to address social needs. OBJECTIVE: To examine social risk and need from rural Veterans' lived experiences and develop recommendations for VHA to address social needs. DESIGN: We conducted semi-structured interviews with participants purposively sampled for racial diversity. The interview guide was informed by Andersen's Behavioral Model of Health Services Use and the Outcomes from Addressing Social Determinants of Health in Systems framework. PARTICIPANTS: Rural Veterans with or at risk of cardiovascular disease who participated in a parent survey and agreed to be recontacted. APPROACH: Interviews were recorded and transcribed. We analyzed transcripts using directed qualitative content analysis to identify themes. KEY RESULTS: Interviews (n = 29) took place from March to June 2022. We identified four themes: (1) Social needs can impact access to healthcare, (2) Structural factors can make it difficult to get help for social needs, (3) Some Veterans are reluctant to seek help, and (4) Veterans recommended enhancing resource dissemination and navigation support. CONCLUSIONS: VHA interventions should include active dissemination of information on social needs resources and navigation support to help Veterans access resources. Community-based organizations (e.g., Veteran Service Organizations) could be key partners in the design and implementation of future social need interventions.

Validation of the Lee-Jones theoretical model of fear of cancer recurrence among breast cancer survivors using a structural equation modeling approach.

OBJECTIVE: The Lee-Jones model posits that antecedent individual and interpersonal factors predicate the development of fear of cancer recurrence (FCR) through cognitive and emotional processing, which further to behavioral, emotional, and/or physiological responses. We analyzed data from FoRtitude, a FCR intervention grounded in the Lee-Jones FCR model, to evaluate associations between FCR antecedents, resources (e.g., breast cancer self-efficacy, BCSE) and psychological and behavioral consequences. METHODS: Women with breast cancer who completed treatment and reported clinically elevated levels of FCR were randomized into a 4-week online psychosocial intervention or contact control group. We assessed BCSE, FCR, and physical activity, anxiety and depression, or symptoms at baseline, 4 and 8 weeks. Separate structural equation models were constructed with both baseline data and change scores (baseline-8 weeks) to examine the pathways linking BCSE, FCR and: (1) physical activity; (2) anxiety and depression; and (3) symptoms (fatigue, sleep disturbance, cognitive concerns). RESULTS: At baseline, higher levels of BCSE were associated with lower levels of FCR. Higher FCR was associated with worse psychological effects and symptoms but not behavioral response. Change models revealed that an increase in BCSE was associated with a decrease in FCR at 8-week assessment, which was associated with reductions in psychological effects. A change in BCSE was also directly associated with reductions in psychological effects. CONCLUSIONS: Results support the Lee-Jones model as a foundation for FCR interventions among breast cancer survivors. Replicability among varied populations is needed to examine effects on behavioral outcomes of FCR such as health care utilization. CLINICAL TRIALS REGISTRATION: NCT03384992.

Post-stroke Depressive Symptoms and Cognitive Performances: A Network Analysis.

OBJECTIVE: To examine the relationships between post-stroke depression and cognition using network analysis. In particular, we identified central depressive symptoms, central cognitive performances, and bridge components that connect these 2 constructs. DESIGN: An observational study. We applied network analysis to analyze baseline data to visualize and quantify the relationships between depression and cognition. SETTING: Home and Community. PARTICIPANTS: 202 participants with mild-to-moderate stroke (N=202; mean age: 59.7 years; 55% men; 55% Whites; 90% ischemic stroke). INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: Patient Health Questionnaire (PHQ-8) for depressive symptoms and the NIH Toolbox Cognitive Battery for cognitive performances. RESULTS: Depressive symptoms were positively intercorrelated with the network, with symptoms from similar domains clustered together. Mood (expected influence=1.58), concentration (expected influence=0.67), and guilt (expected influence=0.63) were the top 3 central depressive symptoms. Cognitive performances also showed similar network patterns, with executive function (expected influence=0.89), expressive language (expected influence=0.68), and processing speed (expected influence=0.48) identified as the top 3 central cognitive performances. Psychomotor functioning (bridge expected influence=2.49) and attention (bridge expected influence=1.10) were the components connecting depression and cognition. CONCLUSIONS: The central and bridge components identified in this study might serve as targets for interventions against these deficits. Future trials are needed to compare the effectiveness of interventions targeting the central and bridge components vs general interventions treating depression and cognitive impairment as a homogenous clinical syndrome.

Factors affecting the implementation of employee whole health in the veterans health administration: a qualitative evaluation.

BACKGROUND: There is increasing recognition of the need to focus on the health and well-being of healthcare employees given high rates of burnout and turnover. Employee wellness programs are effective at addressing these issues; however, participation in these programs is often a challenge and requires large scale organizational transformation. The Veterans Health Administration (VA) has begun to roll out their own employee wellness program-Employee Whole Health (EWH)-focused on the holistic needs of all employees. This evaluation's goal was to use the Lean Enterprise Transformation (LET) model for organizational transformation to identify key factors-facilitators and barriers-affecting the implementation of VA EWH. METHODS: This cross-sectional qualitative evaluation based on the action research model reflects on the organizational implementation of EWH. Semi-structured 60-minute phone interviews were conducted in February-April 2021 with 27 key informants (e.g., EWH coordinator, wellness/occupational health staff) knowledgeable about EWH implementation across 10 VA medical centers. Operational partner provided a list of potential participants, eligible because of their involvement in EWH implementation at their site. The interview guide was informed by the LET model. Interviews were recorded and professionally transcribed. Constant comparative review with a combination of a priori coding based on the model and emergent thematic analysis was used to identify themes from transcripts. Matrix analysis and rapid turnaround qualitative methods were used to identify cross-site factors to EWH implementation. RESULTS: Eight common factors in the conceptual model were found to facilitate and/or hinder EWH implementation efforts: [1] EWH initiatives, [2] multilevel leadership support, [3] alignment, [4] integration, [5] employee engagement, [6] communication, [7] staffing, and [8] culture. An emergent factor was [9] the impact of the COVID-19 pandemic on EWH implementation. CONCLUSIONS: As VA expands its EWH cultural transformation nationwide, evaluation findings can (a) enable existing programs to address known implementation barriers, and (b) inform new sites to capitalize on known facilitators, anticipate and address barriers, and leverage evaluation recommendations through concerted implementation at the organization, process, and employee levels to jump-start their EWH program implementation.

Burnout, employee engagement, and changing organizational contexts in VA primary care during the early COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic involved a rapid change to the working conditions of all healthcare workers (HCW), including those in primary care. Organizational responses to the pandemic, including a shift to virtual care, changes in staffing, and reassignments to testing-related work, may have shifted more burden to these HCWs, increasing their burnout and turnover intent, despite their engagement to their organization. Our objectives were (1) to examine changes in burnout and intent to leave rates in VA primary care from 2017-2020 (before and during the pandemic), and (2) to analyze how individual protective factors and organizational context affected burnout and turnover intent among VA primary care HCWs during the early months of the pandemic. METHODS: We analyzed individual- and healthcare system-level data from 19,894 primary care HCWs in 139 healthcare systems in 2020. We modeled potential relationships between individual-level burnout and turnover intent as outcomes, and individual-level employee engagement, perceptions of workload, leadership, and workgroups. At healthcare system-level, we assessed prior-year levels of burnout and turnover intent, COVID-19 burden (number of tests and deaths), and the extent of virtual care use as potential determinants. We conducted multivariable analyses using logistic regression with standard errors clustered by healthcare system controlled for individual-level demographics and healthcare system complexity. RESULTS: In 2020, 37% of primary care HCWs reported burnout, and 31% reported turnover intent. Highly engaged employees were less burned out (OR = 0.57; 95% CI 0.52-0.63) and had lower turnover intent (OR = 0.62; 95% CI 0.57-0.68). Pre-pandemic healthcare system-level burnout was a major predictor of individual-level pandemic burnout (p = 0.014). Perceptions of reasonable workload, trustworthy leadership, and strong workgroups were also related to lower burnout and turnover intent (p < 0.05 for all). COVID-19 burden, virtual care use, and prior year turnover were not associated with either outcome. CONCLUSIONS: Employee engagement was associated with a lower likelihood of primary care HCW burnout and turnover intent during the pandemic, suggesting it may have a protective effect during stressful times. COVID-19 burden and virtual care use were not related to either outcome. Future research should focus on understanding the relationship between engagement and burnout and improving well-being in primary care.

Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis.

BACKGROUND: Major depressive disorder (MDD) affects millions of people worldwide, but timely treatment is not often received owing in part to inaccurate subjective recall and variability in the symptom course. Objective and frequent MDD monitoring can improve subjective recall and help to guide treatment selection. Attempts have been made, with varying degrees of success, to explore the relationship between the measures of depression and passive digital phenotypes (features) extracted from smartphones and wearables devices to remotely and continuously monitor changes in symptomatology. However, a number of challenges exist for the analysis of these data. These include maintaining participant engagement over extended time periods and therefore understanding what constitutes an acceptable threshold of missing data; distinguishing between the cross-sectional and longitudinal relationships for different features to determine their utility in tracking within-individual longitudinal variation or screening individuals at high risk; and understanding the heterogeneity with which depression manifests itself in behavioral patterns quantified by the passive features. OBJECTIVE: We aimed to address these 3 challenges to inform future work in stratified analyses. METHODS: Using smartphone and wearable data collected from 479 participants with MDD, we extracted 21 features capturing mobility, sleep, and smartphone use. We investigated the impact of the number of days of available data on feature quality using the intraclass correlation coefficient and Bland-Altman analysis. We then examined the nature of the correlation between the 8-item Patient Health Questionnaire (PHQ-8) depression scale (measured every 14 days) and the features using the individual-mean correlation, repeated measures correlation, and linear mixed effects model. Furthermore, we stratified the participants based on their behavioral difference, quantified by the features, between periods of high (depression) and low (no depression) PHQ-8 scores using the Gaussian mixture model. RESULTS: We demonstrated that at least 8 (range 2-12) days were needed for reliable calculation of most of the features in the 14-day time window. We observed that features such as sleep onset time correlated better with PHQ-8 scores cross-sectionally than longitudinally, whereas features such as wakefulness after sleep onset correlated well with PHQ-8 longitudinally but worse cross-sectionally. Finally, we found that participants could be separated into 3 distinct clusters according to their behavioral difference between periods of depression and periods of no depression. CONCLUSIONS: This work contributes to our understanding of how these mobile health-derived features are associated with depression symptom severity to inform future work in stratified analyses.

Organizational Readiness for Patient-Facing Mobile Teledermatology to Care for Established Veteran Patients in the United States.

Purpose: To improve patient access to skin care, the Department of Veterans Affairs (VA) developed a patient-facing asynchronous mobile teledermatology application (app), which allows patients to follow up remotely with dermatologists. To understand how the app would be received in VA, we examined Organizational Readiness for Change (ORC), an important prelude to effective implementation, which includes the shared resolve and collective ability of organizational members to implement a change. Methods: We used a mixed-methods multiple case study approach to assess ORC at three VA facilities. Data derived from a site process call, surveys, and semistructured telephone interviews of VA staff, field notes, and administrative data. Results: Participants at all three facilities supported the intervention and recognized the value of using the app to increase patients' access to dermatologists, but expressed concerns largely related to disruption of the pre-existing clinical workflow. Participants at the facility most actively using the app had the highest overall ORC score and reported the most facilitators. Facility leadership support when guided by a clinical champion minimized barriers by recognizing the complexities of health care provision at specialty clinics. Discussion: While provider buy-in remained a barrier, leadership, guided by the clinical champion, played a critical role instituting implementation strategies. The strong association between the ORC survey score and the presence of facilitators and barriers suggests that the ORC survey may be a rapid, convenient, and effective tool for health care systems to identify favorable sites for wider implementation of mobile telehealth care. Clinical Trials Identifier: NCT03241589.

A Multi-site Case Study of Care Coordination Between Primary Care and Specialty Care.

BACKGROUND: Care coordination is critical for patients with multiple chronic conditions, but fragmentation of care persists. Providers' perspectives of facilitators and barriers to coordination are needed to improve care. OBJECTIVES: We sought to understand providers' perspectives on care coordination for patients having multiple chronic diseases served by multiple providers. RESEARCH DESIGN: Based upon our earlier survey of patients with multiple chronic conditions, we selected 8 medical centers having high and low coordination. We interviewed providers to identify facilitators and barriers to coordination and compare them between patient-rated high sites and low sites and between primary care (PC)-mental health (MH) and PC-medical/surgical specialty care. SUBJECTS: Physicians, nurses and other clinicians in PC, cardiology, and MH (N=102) in 8 Veterans Affairs medical centers. RESULTS: We identified warm handoffs, professional relationships, and physical proximity as facilitators, and service agreements, reporting relationships and staffing as barriers. PC-MH coordination was reported as better than PC-medical/surgical specialty coordination. Facilitators were more prevalent and barriers less prevalent in sites rated high by patients than sites rated low, and between PC-MH than between PC-specialty care. DISCUSSION: We noted that professional relationships were highly related to coordination and both affected other facilitators and barriers and were affected by them. We suggested actions to improve relationships directly, and to address other facilitators and barriers that affect relationships and coordination. Among these is the use of the Primary Care Mental Health Integration model.

Differences in Burnout and Intent to Leave Between Women's Health and General Primary Care Providers in the Veterans Health Administration.

BACKGROUND: Although they are a minority of patients served by the Veterans Health Administration (VHA), women Veterans comprise a fast-growing segment of these patients and have unique clinical needs. Women's health primary care providers (WH-PCPs) are specially trained and designated to provide care for women Veterans. Prior work has demonstrated that WH-PCPs deliver better preventative care and have more satisfied patients than PCPs without the WH designation. However, due to unique clinical demands or other factors, WH-PCPs may experience more burnout and intent to leave practice than general PCPs in the VHA. OBJECTIVE: To examine differences in burnout and intent to leave practice among WH and general PCPs in the VHA. DESIGN: Multi-level logistic regression analysis of three cross-sectional waves of PCPs within the VHA using the national All Employee Survey and practice data (2017-2019). We modeled outcomes of burnout and intent to leave practice as a function of WH provider designation, gender, and other demographics and practice characteristics, such as support staff ratio, panel size, and setting. PARTICIPANTS: A total of 7903 primary care providers (5152 general PCPs and 2751 WH-PCPs; response rates: 63.9%, 65.7%, and 67.5% in 2017, 2018, and 2019, respectively). MAIN MEASURES: Burnout and intent to leave practice. KEY RESULTS: WH-PCPs were more burned out than general PCPs (unadjusted: 55.0% vs. 46.9%, p<0.001; adjusted: OR=1.29, 95% confidence interval [CI] 1.10-1.55) but did not have a higher intention to leave (unadjusted: 33.4% vs. 32.1%, p=0.27; adjusted: OR=1.07, CI 0.81-1.41). WH-PCPs with intentions to leave were more likely to select the response option of "job-related (e.g., type of work, workload, burnout, boredom)" as their primary reason to leave. CONCLUSIONS: Burnout is higher among WH-PCPs compared to general PCPs, even after accounting for provider and practice characteristics. More research on causes of and solutions for these differences in burnout is needed.

Evaluating the Impacts of Patient Engagement on Health Services Research Teams: Lessons from the Veteran Consulting Network.

BACKGROUND: Despite increasing commitment to patient engagement in research, evaluation of the impact of these efforts on research processes, products, and teams is limited. OBJECTIVE: To explore the impacts of engaging patients as consultants to research studies by examining the experiences, impacts, and lessons learned from a program facilitating patient engagement at a Veterans Health Administration research center. DESIGN: We developed a logic model to articulate the activities being implemented to support patient engagement and their anticipated outcomes. Then, we conducted qualitative, semi-structured interviews with participants in the local Veteran Consulting Network to qualitatively explore these outcomes. PARTICIPANTS: Twelve researchers and eleven Veteran patients with experience working on at least one grant or funded study. APPROACH: Interview transcripts were inductively coded using a consensus-based approach. Findings were synthesized using framework analysis and mapped back onto our logic model of expected patient engagement impacts. KEY RESULTS: Patient engagement improved the perceived quality and relevance of research studies as patient consultants challenged researchers' assumptions about patient populations and clinical contexts and gave feedback that helped improve the feasibility of proposed grants, readability of study materials, comprehensiveness of study assessments, and cultural sensitivity and relevance of interventions. Patient engagement also had personal benefits to researchers and patients. Researchers reported improved communication skills and higher job satisfaction. Patients reported a sense of purpose and satisfaction from their work with greater awareness of and appreciation for research. CONCLUSIONS: Engaging patients in research can have multiple benefits to the people and work involved. Our evaluation process can serve as a template for other organizations to plan for and assess the impact of their own patient engagement programs. Creating logic models and updating them based on feedback from program users make engagement goals explicit, help verify expected mechanisms to achieve impact, and facilitate organizational learning.

Gender Differences in the Relationship Between Workplace Civility and Burnout Among VA Primary Care Providers.

BACKGROUND: Civility, or politeness, is an important part of the healthcare workplace, and its absence can lead to healthcare provider and staff burnout. Lack of civility is well-documented among mostly female nurses, but is not well-described among the gender-mixed primary care provider (PCP) workforce. Understanding civility and its relationship to burnout among male and female PCPs could help lead to tailored interventions to improve civility and reduce burnout in primary care. OBJECTIVE: To analyze gender differences in civility, burnout, and the relationship between civility and burnout among male and female PCPs. DESIGN: Multi-level logistic regression analysis of a cross-sectional national survey. PARTICIPANTS: A total of 3216 PCP respondents (1946 women and 1270 men) in 135 medical centers from a 2019 national Veterans Health Administration (VA) survey. MAIN MEASURES: Outcomes: burnout; predictors: workplace civility and gender; controls: race, ethnicity, VA tenure, and supervisory status. KEY RESULTS: Workplace civility was rated higher (p<0.001) among male (mean = 4.07, standard deviation [SD] = 0.36, range 1-5) compared to female (mean = 3.88, SD = 0.33) PCPs. Almost half of the sample reported burnout (47.6%), but this difference was not significant (p = 0.73) between the genders. Higher workplace civility was significantly related to lower burnout among female PCPs (odds ratio [OR] = 0.46, 95% confidence interval [CI] = 0.31 to 0.69), but not among male PCPs (OR = 0.71, 95% CI = 0.42 to 1.22). Interactions between civility and other demographic variables (race, ethnicity, VA tenure, or supervisory status) were not significantly related to burnout. CONCLUSION: Female PCPs report lower workplace civility than male PCPs. An inverse relationship between civility and burnout is present for women but not men. More research is needed on this phenomenon. Interventions tailored to gender- and primary care-specific needs should be employed to increase civility and reduce burnout among PCPs.

Prospective associations of text-message-based sentiment with symptoms of depression, generalized anxiety, and social anxiety.

OBJECTIVE: Language patterns may elucidate mechanisms of mental health conditions. To inform underlying theory and risk models, we evaluated prospective associations between in vivo text messaging language and differential symptoms of depression, generalized anxiety, and social anxiety. METHODS: Over 16 weeks, we collected outgoing text messages from 335 adults. Using Linguistic Inquiry and Word Count (LIWC), NRC Emotion Lexicon, and previously established depression and stress dictionaries, we evaluated the degree to which language features predict symptoms of depression, generalized anxiety, or social anxiety the following week using hierarchical linear models. To isolate the specificity of language effects, we also controlled for the effects of the two other symptom types. RESULTS: We found significant relationships of language features, including personal pronouns, negative emotion, cognitive and biological processes, and informal language, with common mental health conditions, including depression, generalized anxiety, and social anxiety (ps < .05). There was substantial overlap between language features and the three mental health outcomes. However, after controlling for other symptoms in the models, depressive symptoms were uniquely negatively associated with language about anticipation, trust, social processes, and affiliation (ßs: -.10 to -.09, ps < .05), whereas generalized anxiety symptoms were positively linked with these same language features (ßs: .12-.13, ps < .001). Social anxiety symptoms were uniquely associated with anger, sexual language, and swearing (ßs: .12-.13, ps < .05). CONCLUSION: Language that confers both common (e.g., personal pronouns and negative emotion) and specific (e.g., affiliation, anticipation, trust, and anger) risk for affective disorders is perceptible in prior week text messages, holding promise for understanding cognitive-behavioral mechanisms and tailoring digital interventions.

Psychometric validity and reliability of the 10- and 2-item Connor-Davidson resilience scales among a national sample of Americans responding to the Covid-19 pandemic: an item response theory analysis.

PURPOSE: Psychometric validity/reliability of 10-item and 2-item abbreviations of the Connor-Davidson Resilience Scale (CD-RISC-10; CD-RISC-2) was investigated via item response theory and classic approaches. METHODS: We sampled 5023 adult American participants in a June/July 2020 survey on the COVID-19 pandemic's psychological effects. Our questionnaire incorporated the CD-RISC-10 with other validated measures. CD-RISC-10 items were ranked on item-to-scale correlations, loadings on a one-factor confirmatory factor analysis model, and item slope/threshold parameters plus information curves from a unidimensional graded response model. Concurrent validity of the highest ranked item pair was evaluated vis-à-vis the CD-RISC-10 and CD-RISC-2. Internal consistency, based on average variance extracted (AVE) and multiple reliability coefficients, was also compared. Convergent/divergent validity was tested by correlating anxiety, depression, fear of COVID-19, anxiety sensitivity, coping, and personality measures with both scales and the highest ranked item pair. Binary agreement/classification indexes assessed inter-rater reliability. RESULTS: Items 2 and 9 from CD-RISC-10 ranked the highest. Reliability coefficients were > 0.93, > 0.72, and > 0.82 for the CD-RISC-10, CD-RISC-2, vs summation of items 2 and 9. AVEs were 0.66, 0.67, and 0.77. CD-RISC abbreviations and the summation of items 2 and 9 correlated negatively with anxiety (> - 0.43), depression (> - 0.42), and fear of COVID-19 (> - 0.34); positively with emotional stability (> 0.53) and conscientiousness (> 0.40). Compared to the CD-RISC-2, summative scores of items 2 and 9 more efficiently classified/discriminated high resilience on the CD-RISC-10. CONCLUSION: We confirmed construct validity/reliability of copyrighted CD-RISC abbreviations. The CD-RISC-10's items 2 and 9 were psychometrically more salient than the CD-RISC-2.

Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): recruitment, retention, and data availability in a longitudinal remote measurement study.

BACKGROUND: Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data. METHODS: Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse - Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months. RESULTS: Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had > 50% data available across all data types. CONCLUSIONS: RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group.