Evaluating a Measure of Social Health Derived from Two Mental Health Recovery Measures: The California Quality of Life (CA-QOL) and Mental Health Statistics Improvement Program Consumer Survey (MHSIP)

Social health is important to measure when assessing outcomes in community mental health. Our objective was to validate social health scales using items from two broader commonly used measures that assess mental health outcomes. Participants were 609 adults receiving psychological treatment services. Items were identified from the California Quality of Life (CA-QOL) and Mental Health Statistics Improvement Program (MHSIP) outcome measures by their conceptual correspondence with social health and compared to the Social Functioning Questionnaire (SFQ) using correlational analyses. Pearson correlations for the identified CA-QOL and MSHIP items with the SFQ ranged from .42 to .62, and the identified scale scores produced Pearson correlation coefficients of .56, .70, and, .70 with the SFQ. Concurrent validity with social health was supported for the identified scales. The current inclusion of these assessment tools allows community mental health programs to include social health in their assessments

Some recommendations for developing multidimensional computerized adaptive tests for patient-reported outcomes

PURPOSE: Multidimensional item response theory and computerized adaptive testing (CAT) are increasingly used in mental health, quality of life (QoL), and patient-reported outcome measurement. Although multidimensional assessment techniques hold promises, they are more challenging in their application than unidimensional ones. The authors comment on minimal standards when developing multidimensional CATs. METHODS: Prompted by pioneering papers published in QLR, the authors reflect on existing guidance and discussions from different psychometric communities, including guidelines developed for unidimensional CATs in the PROMIS project. RESULTS: The commentary focuses on two key topics: (1) the design, evaluation, and calibration of multidimensional item banks and (2) how to study the efficiency and precision of a multidimensional item bank. The authors suggest that the development of a carefully designed and calibrated item bank encompasses a construction phase and a psychometric phase. With respect to efficiency and precision, item banks should be large enough to provide adequate precision over the full range of the latent constructs. Therefore CAT performance should be studied as a function of the latent constructs and with reference to relevant benchmarks. Solutions are also suggested for simulation studies using real data, which often result in too optimistic evaluations of an item bank's efficiency and precision. DISCUSSION: Multidimensional CAT applications are promising but complex statistical assessment tools which necessitate detailed theoretical frameworks and methodological scrutiny when testing their appropriateness for practical applications. The authors advise researchers to evaluate item banks with a broad set of methods, describe their choices in detail, and substantiate their approach for validation