ABSTRACT
BACKGROUND: Personalizing medical care is becoming increasingly popular, particularly mental health care. There is growing interest in formalizing medical decision making based on evolving patient symptoms in an evidence-based manner. To determine optimal sequencing of treatments, the sequences themselves must be studied; this may be accomplished by using a sequential multiple assignment randomized trial (SMART). It has been hypothesized that SMART studies may improve participant retention and generalizability. METHODS: We examine the hypotheses that SMART studies are more generalizable and have better retention than traditional randomized clinical trials via a case study of a SMART study of antipsychotic medications. We considered the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia study, comparing the trial participant characteristics and overall retention to those of comparable trials found via a review of all related trials conducted from 2000 onwards. RESULTS: A MEDLINE search returned 6435 results for primary screening; ultimately, 48 distinct trials were retained for analysis. The study population in CATIE was similar to, although perhaps less symptomatic than, the study populations of traditional randomized clinical trials (RCTs), suggesting no large gains in generalizability despite the pragmatic nature of the trial. However, CATIE did see good month-by-month retention. CONCLUSIONS: SMARTs offer the possibility of studying treatment sequences in a way that a series of traditional RCTs cannot. SMARTs may offer improved retention; however, this case study did not find evidence to suggest greater generalizability using this trial design. TRIAL REGISTRATION: ClinicalTrials.gov NCT00014001 . Registered on 6 April 2001.
Subject(s)
Antipsychotic Agents/therapeutic use , Patient Dropouts , Process Assessment, Health Care/methods , Randomized Controlled Trials as Topic/methods , Research Design , Schizophrenia/drug therapy , Humans , Process Assessment, Health Care/standards , Randomized Controlled Trials as Topic/standards , Research Design/standards , Schizophrenia/diagnosis , Treatment OutcomeABSTRACT
AIMS: The content of public health research is often statistically complex. This review seeks to assess the breadth of statistical literacy required to understand this material, with a view to informing practitioners' statistical training. METHODS: We review the statistical content of original research articles published in 2011 in four major public health journals. Categories of statistical methodologies are identified and their frequency of use recorded. Methods' "usefulness" in terms of the extent to which their understanding increases accessibility to the literature is assessed. RESULTS: A total of 482 articles were reviewed and 30 categories of methods identified. Along with descriptive statistics (467 articles), regression analyses were also common, with logistic regression (206 articles) more than twice as prevalent as linear regression (95 articles). More complex regression models for use with clustered data were also commonly encountered, appearing in 96 articles. CONCLUSIONS: The public health literature features a wide variety of statistical methods, some of which are advanced. To ensure the literature remains accessible, training for public health practitioners should include statistical training that maximizes breadth as well as depth of understanding.
