1. ^*Psychology Department, Oberlin College, Oberlin, Ohio
2. ^†Family Practice Clinical Research Center, Summa Health System, Akron, Ohio
3. ^‡Office of Biostatistics, Northeast Ohio Universities College of Medicine, Rootstown, Ohio
4. ^§College of Nursing, University of Akron, Akron, Ohio

Correspondence: Karen Sutton, Address correspondence to Karen Sutton, Department of Psychology, Oberlin College, Severance Hall, Oberlin, OH 44074. E-mail: karen.sutton@oberlin.edu

^*See Appendix for list of study centers.

Received 2 December 2001; Revised  0000; Accepted 3 March 2003.

Abstract

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 < 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 < 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.