Assessment of clinically meaningful change is useful for treatment planning, monitoring progress, and evaluating treatment response. Outcome studies often assess statistically significant change, which may not be clinically meaningful. Study objectives are to: (1) evaluate responsiveness of the BASIS-24 using three methods for determining clinically meaningful change: reliable change index (RCI), effect size (ES), and standard error of measurement (SEM); and (2) determine which method provides an estimate of clinically meaningful change most concordant with other change measures. BASIS-24 assessments were obtained at two time points for 1,397 inpatients and 850 outpatients. The proportion showing clinically meaningful change using each method was compared to the proportion showing change in global mental health, retrospectively reported change, and clinician-assessed change. BASIS-24 demonstrated responsiveness at both aggregate and individual levels. Regarding clinically meaningful improvement and decline, SEM was most concordant with all three outcome measures; regarding no change, RCI was most concordant with all three measures.
Link to this article: http://journals.cambridge.org/abstract_S0143385704000380 How to cite this article: PAUL BLANCHARD, ROBERT L. DEVANEY, DANIEL M. LOOK, PRADIPTA SEAL and YAKOV SHAPIRO (2005). Sierpinski-curve Julia sets and singular perturbations of complex polynomials.Abstract. In this paper we consider the family of rational maps of the complex plane given by z 2 + λ z 2 where λ is a complex parameter. We regard this family as a singular perturbation of the simple function z 2 . We show that, in any neighborhood of the origin in the parameter plane, there are infinitely many open sets of parameters for which the Julia sets of the corresponding maps are Sierpinski curves. Hence all of these Julia sets are homeomorphic. However, we also show that parameters corresponding to different open sets have dynamics that are not conjugate.
Risk adjustment for mental health care is important for making meaningful comparisons of provider, program, and system performance. The purpose of this study was to compare the predictive value of three diagnosis-based risk-adjustment models for predicting self-reported mental health outcomes. Baseline and 3-month follow-up mental health assessments were obtained on 1,023 veterans in Veterans Health Administration mental health programs between 2004 and 2006. Least-squares regression models predicting mental health outcomes used the Behavior and Symptom Identification Scale-24, Veterans RAND-36, and Brief Symptom Inventory. Sequential models began with sociodemographics, added baseline self-reported mental health, and compared three psychiatric case mix schemes: two using six diagnostic categories and the other (psychiatric case mix system [PsyCMS]) using 46 categories. R (2) were lowest for sociodemographic models (0.010-0.074) and highest for models with the PsyCMS (0.187-0.425). The best predictive ability was obtained when baseline mental health and 1 year of psychiatric diagnoses were added to sociodemographic models; however, the "best" risk-adjustment model differed between inpatients and outpatients.
To assess mental health status among Latinos, culturally and linguistically appropriate instruments are needed. The purpose of this study was to assess psychometric properties and sensitivity of the Spanish revised Behavior and Symptom Identification Scale (BASIS-24), a self-report mental health assessment instrument first developed and validated in English. The Spanish translation was field tested among Spanish-speaking recipients of inpatient (N = 283) or outpatient (N = 311) mental health services in Massachusetts, Puerto Rico, and California. BASIS-24 was completed within 72 h of admission and up to 48 h before discharge (for inpatients) or at intake and 30-60 days later for outpatients. Confirmatory factor analysis indicated adequate fit for the model obtained from the English instrument. Internal consistency reliability exceeded 0.70 for five of the six factors. Concurrent and discriminant validity were partially supported. Improvement following treatment was statistically significant, with small to moderate effect sizes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.