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Relations between mental health team characteristics and work role performance.

ABSTRACT: Effective mental health care requires a high performing, interprofessional team. Among 79 mental health teams in Quebec (Canada), this exploratory study aims to 1) determine the association between work role performance and a wide range of variables related to team effectiveness according to the literature, and to 2) using structural equation modelling, assess the covariance between each of these variables as well as the correlation with other exogenous variables. Work role performance was measured with an adapted version of a work role questionnaire. Various independent variables including team manager characteristics, user characteristics, team profiles, clinical activities, organizational culture, network integration strategies and frequency/satisfaction of interactions with other teams or services were analyzed under the structural equation model. The later provided a good fit with the data. Frequent use of standardized procedures and evaluation tools (e.g. screening and assessment tools for mental health disorders) and team manager seniority exerted the most direct effect on work role performance. While network integration strategies had little effect on work role performance, there was a high covariance between this variable and those directly affecting work role performance among mental health teams. The results suggest that the mental healthcare system should apply standardized procedures and evaluation tools and, to a lesser extent, clinical approaches to improve work role performance in mental health teams. Overall, a more systematic implementation of network integration strategies may contribute to improved work role performance in mental health care.

SUBMITTER: Fleury MJ

PROVIDER: S-EPMC5633152 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Relations between mental health team characteristics and work role performance.

Fleury Marie-Josée MJ Grenier Guy G Bamvita Jean-Marie JM Farand Lambert L

PloS one 20171009 10

Effective mental health care requires a high performing, interprofessional team. Among 79 mental health teams in Quebec (Canada), this exploratory study aims to 1) determine the association between work role performance and a wide range of variables related to team effectiveness according to the literature, and to 2) using structural equation modelling, assess the covariance between each of these variables as well as the correlation with other exogenous variables. Work role performance was measu ...[more]

PMID: 28991923

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Project description:ObjectiveTo identify work-environment characteristics associated with Veterans Health Administration (VHA) behavioral health provider (BHP) burnout among psychiatrists, psychologists, and social workers.Data sourcesThe 2015-2018 data from Annual All Employee Survey (AES); Mental Health Provider Survey (MHPS); N = 57,397 respondents; facility-level Mental Health Onboard Clinical (MHOC) staffing and productivity data, N = 140 facilities.Study designFor AES and MHPS separately, we used mixed-effects logistic regression to predict BHP burnout using surveys from year pairs (2015-2016, 2016-2017, 2017-2018; six models). Within each year-pair, we used the earlier year of data to train models and tested the model in the later year, with burnout (emotional exhaustion and/or depersonalization) as the outcome for each survey. We used potentially modifiable work-environment characteristics as predictors, controlling for employee demographic characteristics as covariates, and employment facility as random intercepts.Data collection/extraction methodsWe included work-environment predictors that appeared in all 4 years (11 in AES; 17 in MHPS).Principal findingsIn 2015-2018, 31.0%-38.0% of BHPs reported burnout in AES or MHPS. Work characteristics consistently associated with significantly lower burnout were included for AES: reasonable workload; having appropriate resources to perform a job well; supervisors address concerns; given an opportunity to improve skills. For MHPS, characteristics included: reasonable workload; work improves veterans' lives; mental health care provided is well-coordinated; and three reverse-coded items: staffing vacancies; daily work that clerical/support staff could complete; and collateral duties reduce availability for patient care. Facility-level staffing ratios and productivity did not significantly predict individual-level burnout. Workload represented the strongest predictor of burnout in both surveys.ConclusionsThis study demonstrated substantial, ongoing impacts that having appropriate resources including staff, workload, and supervisor support had on VHA BHP burnout. VHA may consider investing in approaches to mitigate the impact of BHP burnout on employees and their patients through providing staff supports, managing workload, and goal setting.

Project description:Questionnaires are among the most basic and widespread tools to assess the mental health of a population in epidemiological and public health studies. Their most obvious advantage (firsthand self-report) is also the source of their main problems: the raw data requires interpretation, and are a snapshot of the specific sample's status at a given time. Efforts to deal with both issues created a bi-dimensional space defined by two orthogonal axes, in which most of the quantitative mental health research can be located. Methods aimed to assure that mental health diagnoses are solidly grounded on existing raw data are part of the individual validity axis. Tools allowing the generalization of the results across the entire population compose the collective validity axis. This paper raises a different question. Since one goal of mental health assessments is to obtain results that can be generalized to some extent, an important question is how robust is a questionnaire result when applied to a different population or to the same population at a different time. In this case, there is deep uncertainty, without any a priori probabilistic information. The main claim of this paper is that this task requires the development of a new robustness to deep uncertainty axis, defining a three-dimensional research space. We demonstrate the analysis of deep uncertainty using the concept of robustness in info-gap decision theory. Based on data from questionnaires collected before and during the Covid-19 pandemic, we first locate a mental health assessment in the space defined by the individual validity axis and the collective validity axis. Then we develop a model of info-gap robustness to uncertainty in mental health assessment, showing how the robustness to deep uncertainty axis interacts with the other two axes, highlighting the contributions and the limitations of this approach. The ability to measure robustness to deep uncertainty in the mental health realm is important particularly in troubled and changing times. In this paper, we provide the basic methodological building blocks of the suggested approach using the outbreak of Covid-19 as a recent example.

Dataset Information

Relations between mental health team characteristics and work role performance.

Publications

Relations between mental health team characteristics and work role performance.

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