OBJECTIVES: To develop a broad set of claimant-reported items to assess behavioral health functioning relevant to the Social Security disability determination processes, and to evaluate the underlying structure of behavioral health functioning for use in development of a new functional assessment instrument. DESIGN: Cross-sectional. SETTING: Community. PARTICIPANTS: Item pools of behavioral health functioning were developed, refined, and field tested in a sample of persons applying for Social Security disability benefits (N=1015) who reported difficulties working because of mental or both mental and physical conditions. INTERVENTIONS: None. MAIN OUTCOME MEASURE: Social Security Administration Behavioral Health (SSA-BH) measurement instrument. RESULTS: Confirmatory factor analysis (CFA) specified that a 4-factor model (self-efficacy, mood and emotions, behavioral control, social interactions) had the optimal fit with the data and was also consistent with our hypothesized conceptual framework for characterizing behavioral health functioning. When the items within each of the 4 scales were tested in CFA, the fit statistics indicated adequate support for characterizing behavioral health as a unidimensional construct along these 4 distinct scales of function. CONCLUSIONS: This work represents a significant advance both conceptually and psychometrically in assessment methodologies for work-related behavioral health. The measurement of behavioral health functioning relevant to the context of work requires the assessment of multiple dimensions of behavioral health functioning. Specifically, we identified a 4-factor model solution that represented key domains of work-related behavioral health functioning. These results guided the development and scale formation of a new SSA-BH instrument.
OBJECTIVES: To develop a broad set of claimant-reported items to assess behavioral health functioning relevant to the Social Security disability determination processes, and to evaluate the underlying structure of behavioral health functioning for use in development of a new functional assessment instrument. DESIGN: Cross-sectional. SETTING: Community. PARTICIPANTS: Item pools of behavioral health functioning were developed, refined, and field tested in a sample of persons applying for Social Security disability benefits (N=1015) who reported difficulties working because of mental or both mental and physical conditions. INTERVENTIONS: None. MAIN OUTCOME MEASURE: Social Security Administration Behavioral Health (SSA-BH) measurement instrument. RESULTS: Confirmatory factor analysis (CFA) specified that a 4-factor model (self-efficacy, mood and emotions, behavioral control, social interactions) had the optimal fit with the data and was also consistent with our hypothesized conceptual framework for characterizing behavioral health functioning. When the items within each of the 4 scales were tested in CFA, the fit statistics indicated adequate support for characterizing behavioral health as a unidimensional construct along these 4 distinct scales of function. CONCLUSIONS: This work represents a significant advance both conceptually and psychometrically in assessment methodologies for work-related behavioral health. The measurement of behavioral health functioning relevant to the context of work requires the assessment of multiple dimensions of behavioral health functioning. Specifically, we identified a 4-factor model solution that represented key domains of work-related behavioral health functioning. These results guided the development and scale formation of a new SSA-BH instrument.
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Authors: Elizabeth E Marfeo; Pengsheng Ni; Stephen M Haley; Kara Bogusz; Mark Meterko; Christine M McDonough; Leighton Chan; Elizabeth K Rasch; Diane E Brandt; Alan M Jette Journal: Arch Phys Med Rehabil Date: 2013-03-29 Impact factor: 3.966
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Authors: Elizabeth E Marfeo; Pengsheng Ni; Stephen M Haley; Kara Bogusz; Mark Meterko; Christine M McDonough; Leighton Chan; Elizabeth K Rasch; Diane E Brandt; Alan M Jette Journal: Arch Phys Med Rehabil Date: 2013-03-29 Impact factor: 3.966
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Authors: Elizabeth E Marfeo; Stephen M Haley; Alan M Jette; Susan V Eisen; Pengsheng Ni; Kara Bogusz; Mark Meterko; Christine M McDonough; Leighton Chan; Diane E Brandt; Elizabeth K Rasch Journal: Arch Phys Med Rehabil Date: 2013-03-30 Impact factor: 3.966
Authors: Mark Meterko; Elizabeth E Marfeo; Christine M McDonough; Alan M Jette; Pengsheng Ni; Kara Bogusz; Elizabeth K Rasch; Diane E Brandt; Leighton Chan Journal: Arch Phys Med Rehabil Date: 2014-12-18 Impact factor: 3.966
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