Abstract
It is often difficult to interpret the clinical or policy significance of findings from mental health research when results are presented only in terms of statistical significance. Results expressed in terms of p values or as a metric corresponding to a mental health status scale are seldom intuitively meaningful. To help interpret the significance of research results, we demonstrate a social validity approach that relates scores on mental health status scales to four subsequent major life events. A logistic regression model is used to estimate the relation between mental health status scores and the probability of subsequent major life events, using data obtained on Medicaid beneficiaries with schizophrenia from an evaluation of the Utah Prepaid Mental Health Plan. Using this relatively simple approach will demonstrate to policy makers, clinicians, and researchers the social impact of an outcome, thereby aiding in the interpretation of the significance of results.
Original language | English |
---|---|
Pages (from-to) | 91-97 |
Number of pages | 7 |
Journal | Mental Health Services Research |
Volume | 3 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2001 |
Externally published | Yes |
Keywords
- Clinical significance
- Effect size
- Life events
- Mental health status
- Schizophrenia