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Improving quality of life assessments for high-need adult Medicaid service users with mental health conditions.

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Title: Improving quality of life assessments for high-need adult Medicaid service users with mental health conditions.
Authors: Nevola, Adrienne (AUTHOR), Morris, Michael E. (AUTHOR), Felix, Holly C. (AUTHOR), Hudson, Teresa (AUTHOR), Payakachat, Nalin (AUTHOR), Tilford, J. Mick (AUTHOR)
Source: Quality of Life Research. Apr2021, Vol. 30 Issue 4, p1155-1164. 10p. 2 Diagrams, 3 Charts.
Subjects: Mental health services, Quality of life, Medicaid, Social services, Adults
Abstract: Purpose: There is a lack of consensus on how to evaluate health and social service programs for people with mental health (MH) conditions. Having service users be the primary decision makers in selecting outcome measures can inform a meaningful evaluation strategy. We sought to identify the quality of life (QoL) survey preferences of high-need adult service users with MH conditions. Methods: A systematic review identified generic, self-reported QoL surveys with evidence of validity in MH populations of interest. An advisory panel selected the most promising surveys to assess the success of programs like Medicaid for MH service users. Three groups of high-need, adult service users with MH conditions and one group of direct care staff ranked the surveys from the advisory panel, and generated and ranked characteristics that were desirable or undesirable in a QoL survey. Results: Twenty-two surveys met the inclusion criteria. Of the six surveys selected by the advisory panel, groups of service users and direct care staff most preferred the Warwick-Edinburg Mental Well-being Scale (WEMWBS). The WEMWBS best embodied the features prioritized by the groups: to have a user-friendly format and positive focus, to be clearly worded and brief, and to avoid presumptive or unrealistic items. Service user groups appreciated survey topics most amenable to self-report, such as satisfaction with relationships. Conclusion: Using QoL surveys that service users prefer can reduce the chance that deteriorating QoL is going unchecked, and increase the chance that decisions based on survey findings are meaningful to service users. [ABSTRACT FROM AUTHOR]
Copyright of Quality of Life Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Improving quality of life assessments for high-need adult Medicaid service users with mental health conditions.
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  Data: <searchLink fieldCode="AR" term="%22Nevola%2C+Adrienne%22">Nevola, Adrienne</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Morris%2C+Michael+E%2E%22">Morris, Michael E.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Felix%2C+Holly+C%2E%22">Felix, Holly C.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hudson%2C+Teresa%22">Hudson, Teresa</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Payakachat%2C+Nalin%22">Payakachat, Nalin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tilford%2C+J%2E+Mick%22">Tilford, J. Mick</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Quality+of+Life+Research%22">Quality of Life Research</searchLink>. Apr2021, Vol. 30 Issue 4, p1155-1164. 10p. 2 Diagrams, 3 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Mental+health+services%22">Mental health services</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+of+life%22">Quality of life</searchLink><br /><searchLink fieldCode="DE" term="%22Medicaid%22">Medicaid</searchLink><br /><searchLink fieldCode="DE" term="%22Social+services%22">Social services</searchLink><br /><searchLink fieldCode="DE" term="%22Adults%22">Adults</searchLink>
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  Data: Purpose: There is a lack of consensus on how to evaluate health and social service programs for people with mental health (MH) conditions. Having service users be the primary decision makers in selecting outcome measures can inform a meaningful evaluation strategy. We sought to identify the quality of life (QoL) survey preferences of high-need adult service users with MH conditions. Methods: A systematic review identified generic, self-reported QoL surveys with evidence of validity in MH populations of interest. An advisory panel selected the most promising surveys to assess the success of programs like Medicaid for MH service users. Three groups of high-need, adult service users with MH conditions and one group of direct care staff ranked the surveys from the advisory panel, and generated and ranked characteristics that were desirable or undesirable in a QoL survey. Results: Twenty-two surveys met the inclusion criteria. Of the six surveys selected by the advisory panel, groups of service users and direct care staff most preferred the Warwick-Edinburg Mental Well-being Scale (WEMWBS). The WEMWBS best embodied the features prioritized by the groups: to have a user-friendly format and positive focus, to be clearly worded and brief, and to avoid presumptive or unrealistic items. Service user groups appreciated survey topics most amenable to self-report, such as satisfaction with relationships. Conclusion: Using QoL surveys that service users prefer can reduce the chance that deteriorating QoL is going unchecked, and increase the chance that decisions based on survey findings are meaningful to service users. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Quality of Life Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Apr2021
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