IU Indianapolis ScholarWorks :: Browsing by Author "Morse, Gary"

Browsing by Author "Morse, Gary"

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BREATHE: A Pilot Study of a One-Day Retreat to Reduce Burnout Among Mental Health Professionals
(2011-02) Salyers, Michelle P.; Hudson, Candice; Morse, Gary; Rollins, Angela L.; Monroe-DeVita, Maria; Wilson, Cynthia; Freeland, Leah
OBJECTIVE: Staff burnout is a frequent problem for mental health providers and may be associated with negative outcomes for providers, consumers, and organizations. This study tested an intervention to reduce staff burnout. METHODS: Community mental health providers were invited to participate in a day-long training session to learn methods to reduce burnout. A Web-based survey was given at time of registration, before the intervention, and again six weeks later. RESULTS: Eighty-four providers participated in the training, and follow-up data were available for 74. Six weeks after the day-long training, staff reported significant decreases in emotional exhaustion and depersonalization and significant increases in positive views toward consumers. There were no significant changes in providers' sense of personal accomplishment, job satisfaction, or intention to leave their position. Ninety-one percent of the staff reported the training to be helpful. CONCLUSIONS: This brief intervention is feasible, is acceptable to staff, and may improve burnout and staff attitudes.
Burnout in Mental Health Services: A Review of the Problem and Its Remediation
(2012-09) Morse, Gary; Salyers, Michelle P.; Rollins, Angela L.; Monroe-DeVita, Maria; Pfahler, Corey
Staff burnout is increasingly viewed as a concern in the mental health field. In this article we first examine the extent to which burnout is a problem for mental health services in terms of two critical issues: its prevalence and its association with a range of undesirable outcomes for staff, organizations, and consumers. We subsequently provide a comprehensive review of the limited research attempting to remediate burnout among mental health staff. We conclude with recommendations for the development and rigorous testing of intervention approaches to address this critical area.
A Comparative Effectiveness Trial to Reduce Burnout and Improve Quality of Care
(Springer, 2019-03) Salyers, Michelle P.; Garabrant, Jennifer M.; Luther, Lauren; Henry, Nancy; Fukui, Sadaaki; Shimp, Dawn; Wu, Wei; Gearhart, Tim; Morse, Gary; York, Mary M.; Rollins, Angela L.; Psychology, School of Science
Clinician burnout is presumed to negatively impact healthcare quality; yet scant research has rigorously addressed this hypothesis. Using a mixed-methods, randomized, comparative effectiveness design, we tested two competing approaches to improve care—one addressing clinician burnout and the other addressing how clinicians interact with consumers—with 192 clinicians and 469 consumers at two community mental health centers. Although qualitative reports were promising, we found no comparative effectiveness for either intervention on burnout, patient-centered processes, or other outcomes. Discussion includes identifying ways to strengthen approaches to clinician burnout.
Factors that affect quality of care among mental health providers: Focusing on job stress and resources
(American Psychological Association, 2021) Fukui, Sadaaki; Salyers, Michelle P.; Morse, Gary; Rollins, Angela L.; School of Social Work
Objective: High-quality, person-centered care is a priority for mental health services. The current study conducted secondary data analysis to examine the impact of job stress (i.e., interaction with high-risk consumer cases, increased caseload, emotional exhaustion) and resources (i.e., increased organizational and supervisory support, autonomy, role clarity) on providers' perceived quality of care. Methods: Data consisted of 145 direct care providers from an urban community mental health center. Structural equation modeling was used for testing the hierarchical regression model, sequentially adding job stress and resource variables in the prediction models for the quality of care (i.e., person-centered care, discordant care [conflict with consumers and tardiness]). Results: Person-centered care was positively associated with increased role clarity, organizational support, and larger caseload size, while a lower level of discordant care was associated with lower emotional exhaustion, smaller caseload size, less interaction with high-risk consumer cases, and with increased role clarity. Conclusions and Implications for Practice: Resources on the job may be particularly important for improved person-centered care, and lowering job stress may help reduce discordant care. The current study suggests the need for the mental health organizations to attend to both job stress and resources for providers to improve the quality of care.
Machine Learning with Human Resources Data: Predicting Turnover among Community Mental Health Center Employees
(International Center of Mental Health Policy and Economics, 2023) Fukui, Sadaaki; Wu, Wei; Greenfield, Jaime; Salyers, Michelle P.; Morse, Gary; Garabrant, Jennifer; Bass, Emily; Kyere, Eric; Dell, Nathaniel; School of Social Work
Background: Human resources (HR) departments collect extensive employee data that can be useful for predicting turnover. Yet, these data are not often used to address turnover due to the complex nature of recorded data forms. Aims of the study: The goal of the current study was to predict community mental health center employees' turnover by applying machine learning (ML) methods to HR data and to evaluate the feasibility of the ML approaches. Methods: Historical HR data were obtained from two community mental health centers, and ML approaches with random forest and lasso regression as training models were applied. Results: The results suggested a good level of predictive accuracy for turnover, particularly with the random forest model (e.g., Area Under the Curve was above .8) compared to the lasso regression model overall. The study also found that the ML methods could identify several important predictors (e.g., past work years, wage, work hours, age, job position, training hours, and marital status) for turnover using historical HR data. The HR data extraction processes for ML applications were also evaluated as feasible. Discussion: The current study confirmed the feasibility of ML approaches for predicting individual employees' turnover probabilities by using HR data the organizations had already collected in their routine organizational management practice. The developed approaches can be used to identify employees who are at high risk for turnover. Because our primary purpose was to apply ML methods to estimate an individual employee's turnover probability given their available HR data (rather than determining generalizable predictors at the wider population level), our findings are limited or restricted to the specific organizations under the study. As ML applications are accumulated across organizations, it may be expected that some findings might be more generalizable across different organizations while others may be more organization-specific (idiographic). Implications for health care provision and use: The organization-specific findings can be useful for the organization's HR and leadership to evaluate and address turnover in their specific organizational contexts. Preventing extensive turnover has been a significant priority for many mental health organizations to maintain the quality of services for clients. Implications for health policies: The generalizable findings may contribute to broader policy and workforce development efforts. Implications for further research: As our continuing research effort, it is important to study how the ML methods and outputs can be meaningfully utilized in routine management and leadership practice settings in mental health (including how to develop organization-tailored intervention strategies to support and retain employees) beyond identifying high turnover risk individuals. Such organization-based intervention strategies with ML applications can be accumulated and shared by organizations, which will facilitate the evidence-based learning communities to address turnover. This, in turn, may enhance the quality of care we can offer to clients. The continuing efforts will provide new insights and avenues to address data-driven, evidence-based turnover prediction and prevention strategies using HR data that are often under-utilized.
Measuring Quality of Care in Community Mental Health: Validation of Concordant Clinician and Client Quality-of-Care Scales
(Springer, 2019-04-12) Luther, Lauren; Fukui, Sadaaki; Garabrant, Jennifer M.; Rollins, Angela L.; Morse, Gary; Henry, Nancy; Shimp, Dawn; Gearhart, Timothy; Salyers, Michelle P.; Psychology, School of Science
Measuring quality of care can transform care, but few tools exist to measure quality from the client’s perspective. The aim of this study was to create concordant clinician and client self-report quality of care scales in a sample of community mental health clinicians (n = 189) and clients (n = 469). The client scale had three distinct factors (Person-Centered Care, Negative Staff Interactions, and Inattentive Care), while the clinician scale had two: Person-Centered Care and Discordant Care. Both versions demonstrated adequate internal consistency and validity with measures related to satisfaction and the therapeutic relationship. These measures are promising, brief quality assessment tools.
Using Exit Surveys to Elicit Turnover Reasons among Behavioral Health Employees for Organizational Interventions
(APA, 2025) Fukui, Sadaaki; Garabrant, Jennifer; Greenfield, Jaime; Salyers, Michelle P.; Morse, Gary; Bass, Emily; School of Social Work
Objective: The current study explored turnover reasons via exit surveys for organizational interventions. Methods: The exit surveys were conducted at a community behavioral health organization for over a year, and the open-ended question responses on turnover reasons were analyzed. Results: Thirty-five exit surveys were returned (58% response rate). Five major turnover themes were identified: struggles in current job roles, negative experiences with upper management and senior colleagues, quality of care concerns, no foreseeable future, and personal/family reasons. Conclusions and Implications for Practice: Exit surveys are a useful approach to identify turnover reasons for organizational interventions. The findings provide insights into contextualized strategies for retaining the behavioral health workforce.
Why do Stayers Stay? Perceptions of White and Black Long-Term Employees in a Community Mental Health Center
(Springer, 2024-06) Bass, Emily; Salyers, Michelle P.; Hall, Ashton; Garabrant, Jennifer; Morse, Gary; Kyere, Eric; Dell, Nathaniel; Greenfield, Jaime; Fukui, Sadaaki; School of Social Work
Previous research has focused on factors influencing turnover of employees in the mental health workforce, yet little research has explored reasons why employees stay. To facilitate retaining a diverse mental health workforce, the current study aimed to elucidate factors that contributed to employees’ tenure at a community mental health center (CHMC) as well as compare these perceptions between Black and White employees. Long-term employees (7 years or more) from one urban CMHC (n = 22) completed semi-structured stayer interviews. Using emergent thematic analysis, stayer interviews revealed four major themes for why they have stayed at the organization for 7 years or more: (1) work as a calling, (2) supportive relationships, (3) opportunities for growth or meaningful contribution, and (4) organization mission’s alignment with personal attributes or values. Comparison between Black and White stayer narratives revealed differences in their perceptions with work as a calling and opportunities for growth and meaningful contribution. Guided by themes derived from stayer interviews, the current study discusses theoretical (e.g., job embeddedness theory, theory of racialized organizations, self-determination theory) and practical implications (e.g., supporting job autonomy, Black voices in leadership) in an effort to improve employee retention and address structural racism within a mental health organization.
Working overtime in community mental health: Associations with clinician burnout and perceived quality of care
(American Psychological Association, 2017-06) Luther, Lauren; Gearhart, Timothy; Fukui, Sadaaki; Morse, Gary; Rollins, Angela L.; Salyers, Michelle P.; Psychology, School of Science
OBJECTIVE: Funding cuts have increased job demands and threatened clinicians' ability to provide high-quality, person-centered care. One response to increased job demands is for clinicians to work more than their official scheduled work hours (i.e., overtime). We sought to examine the frequency of working overtime and its relationships with job characteristics, work-related outcomes, and quality of care in community health clinicians. METHOD: One hundred eighty-two clinicians completed demographic and job characteristics questions and measures of burnout, job satisfaction, turnover intention, work-life conflict, and perceived quality of care. Clinicians also reported the importance of reducing stress and their confidence in reducing their stress. Clinicians who reported working overtime were compared to clinicians that did not on demographic and job characteristics and work-related outcomes. RESULTS: Ninety-four clinicians (52%) reported working overtime in a typical week. Controlling for exempt status and group differences in time spent supervising others, those working overtime reported significantly increased burnout and work-life conflict and significantly lower job satisfaction and quality of care than those not working overtime. Clinicians working overtime also reported significantly greater importance in reducing stress but less confidence in their ability to reduce stress than those not working overtime. There were no significant group differences for turnover intention. CONCLUSION AND IMPLICATIONS FOR PRACTICE: Working overtime is associated with negative consequences for clinician-related work outcomes and perceived quality of care. Policies and interventions aimed at reducing overtime and work-related stress and burnout may be warranted in order to improve quality of care.

Browsing by Author "Morse, Gary"

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