Objective: To compare health benefits achieved in a transtheoretical model‐chronic disease (TM‐CD) minimal intervention for obesity vs. augmented usual care (AUC). Research Method and Procedures: This was a 2‐year, randomized clinical trial with overweight or obese men and women from 15 primary care sites. AUC (n = 336) included dietary and exercise advice, prescriptions, and three 24‐hour dietary recalls every 6 months. TM‐CD care (n = 329) included AUC elements plus “stage of change” (SOC) assessments for five target behaviors every other month, mailed SOC and target behavior—matched workbooks, and monthly telephone calls from a weight‐loss advisor. Weight change was the primary outcome. Results: Repeated measures models under the missing at random assumption yielded nonsignificant adjusted differences between the AUC and TM‐CD groups for weight change, waist circumference, energy intake or expenditure, blood pressure, and blood lipids. The pattern of change over time suggested that TM‐CD participants were trying harder to impact target behaviors during the first 6 to 12 months of the trial but relapsed afterward. Sixty percent of trial participants maintained their baseline weights for 18 to 24 months. Discussion: A combination of mailed patient materials and monthly telephone calls based on the transtheoretical model and some elements of chronic disease care is not powerful enough, relative to AUC, to alter target behaviors among overweight primary care patients in an obesogenic environment. AUC may be sufficient to maintain weights among at‐risk primary care patients.

Res. 2003;11:641-652. Objective: According to the Transtheoretical Model (TM), tailoring interventions to patients' readiness to change can enhance patient progress and help patients use therapeutic resources more effectively. However, tailoring an intervention depends on accurate assessment of patients' stage of change (SOC). This study describes a multi-item algorithm of SOC (M-SOC) for weight loss-related behaviors that attempts to overcome some of the conceptual and methodological difficulties encountered in previously SOC assessments. Research Methods: Data were collected from participants randomly assigned to the treatment arm of a clinical trial comparing a TM-based, cognitive-behavioral intervention with enhanced usual care for weight loss. Results: The stair-step relationships hypothesized by the TM between assessed SOC and key behavioral measures were found for all algorithms (p Ͻ 0.05), indicating that the M-SOC algorithm performs as well as single item algorithms. However, 50% fewer patients were classified in action or maintenance for dietary fat intake and portion control (p Ͻ 0.05) by the multiple-item algorithms, providing staging more consistent with the clinical presentation of obese individuals. In addition, logistic regression analyses indicated that the single-item algorithms were not sufficient predictors of these behavioral domains. Discussion: To the extent that treatment is guided by assessed SOC, there is potential for a considerable variability in interventions with different approaches to staging. For weight-loss interventions that target portion control and decreased fat intake, the multi-item SOC algorithms seem to be better guides for matching treatments to SOC.

These preliminary results merit replication in a larger primary care-based trial with a longer continuous intervention and follow-up period.

No abstract

Purpose: The purpose of this study was to identify data available at the time of hospital admission that predict readmission risk.Methods: We performed a retrospective multiple regression analysis of 958 adult, nonpregnant patients admitted to the Family Medicine Service between June 2012 and October 2013. Data were abstracted from hospital administrative sources and electronic medical records. The outcome was 30-day hospital readmission. Candidate readmission predictors included polypharmacy (>6 medicines), Charlson comorbidity index, age, sex, insurance status, emergency department use, smoking, nursing report of cognitive issues, patient report of social support or financial issues, and a history of heart failure, pneumonia, or chronic obstructive pulmonary disease.Results: Patients at the Family Medicine Service had a 14% readmission risk. Bivariate analysis showed that high Charlson scores (>5), polypharmacy, heart failure, pneumonia, or chronic obstructive pulmonary disease each increased readmission risk (P < .05). A logistic model showed an estimated odds ratio for readmission for high Charlson scores of 1.7 (95% confidence interval, 1.1-2.6) and of 2.1 for polypharmacy (95% confidence interval,