Elsevier

Addictive Behaviors

Volume 21, Issue 5, September–October 1996, Pages 555-584
Addictive Behaviors

A criterion measurement model for health behavior change

https://doi.org/10.1016/0306-4603(95)00083-6Get rights and content

Abstract

Researchers in the field of health behavior change have traditionally relied on a univariate criterion measure to evaluate the efficacy of an intervention. Such measures have superficial face validity but suffer from a number of problems: (a) lack of precise definitions: (b) poor statistical power; and (c) a lack of meaningfulness for some aspects of the problem. As an alternative, a theoretical model is developed that attempts to define more appropriate multivariate sets of dependent variables for the study of health behavior change. The model involves three separate constructs: Positive Evaluation Strength, Negative Evaluation Strength, and Habit Strength. The pattern of change for each construct is described across four stages of change: Precontemplation, Contemplation, Action, and Maintenance. For each construct, two thresholds are proposed representing the ability of the environment to modify the construct. Four tests of the model are provided from existing data sets. First, a structural model analysis was used to test if the proposed measurement model adequately fits the data. Second, a dynamic typology approach produced profiles of change that are consistent with the model. Third, a time series analysis provided support for the assumed model. Fourth, longitudinal, five-wave panel design was employed to test if the relation between the two cognitive variables (Pros and Cons) and the behavioral measure (Habit Strength) was consistent with the model. Implications for alternative intervention strategies are discussed.

References (108)

  • A. Bandura

    Self-efficacy: Toward a unifying theory of behavior change

    Psychological Review

    (1977)
  • A. Bandura

    Self-efficacy mechanism in human agency

    American Psychologist

    (1982)
  • P.M. Bentler

    Multivariate analysis with latent variables: Causal modeling

    Annual Review of Psychology

    (1980)
  • P.M. Bentler

    Comparatiave fit indices in structural models

    Psychological Bulletin

    (1990)
  • H.T. Blane et al.

    Pschological theories of drinking and alcoholism

    (1987)
  • H.P. Blossfield et al.

    Event history analysis: Statistical theory and application in the social sciences

    (1989)
  • G.E.P. Box et al.

    Time-series analysis: Forecasting and control.

    (1976)
  • K.D. Brownell et al.

    Understanding and preventing relapse

    American Psychologist

    (1986)
  • R.W. Coan

    Personality variables associated with cigarette smoking

    Journal of Personality and Social Psychology

    (1973)
  • R.J. Coelho

    Self-efficacy and cessation of smoking

    Psychological Reports

    (1984)
  • J. Cohen

    Statistical power analysis for the behavioral sciences

    (1977)
  • L.M. Collins et al.

    Latent class models for stage-sequential dynamic latent variable

    Multivariate Behavioral Research

    (1992)
  • L.M. Collines et al.
  • M.M. Condiotte et al.

    Self-efficacy and relapse in smoking cessation programs

    Journal of Consulting and Clinical Psychology

    (1981)
  • P.T. Costa et al.

    Smoking motive factors: A review and replication

    International Journal of the Addictions

    (1980)
  • L.J. Cronbach et al.

    Construct validity in psychological tests

    Psychological Bulletin

    (1955)
  • C.C. DiClemente

    Self-efficacy and smoking cessation maintenance: A preliminary report

    Cognitive Therapy and Research

    (1981)
  • C.C. DiClemente

    Self-efficacy and the addictive behaviors

    Journal of Social and Clinical Psychology

    (1986)
  • C.C. DiClemente et al.

    The processes of smoking cessation: An analysis of precontemplation, contemplation and preparation stages of change

    Journal of Consulting and Clinical Psychology

    (1991)
  • C.C. DiClemente et al.

    Self-efficacy and the stages of self-change of smoking

    Cognitive Therapy and Research

    (1985)
  • J.L. Fava et al.

    Applying the Transtheoretical Model to a large representative smoking sample

    Addictive Behaviors

    (1994)
  • R.E. Glasgow et al.

    Biochemical validation of smoking status in public health settings: pros, cons, and data from four low-intensity intervention trials

    Addictive Behaviors

    (1993)
  • G.V. Glass et al.

    Design and analysis of time-series experiments

    (1975)
  • J.W. Graham et al.

    Modeling transitions in latent stage-sequential processes: A substance use prevention example

    Journal of Consulting and Clinical Psychology

    (1991)
  • A.R. Hakstian et al.

    The behavior of number of factor rules with simulated data

    Multivariate Behavioral Research

    (1982)
  • J. Harrop et al.

    A comparison of alternative approaches to the analysis of interrupted time-series

    Multivariate Behavioral Research

    (1985)
  • J.W. Harrop et al.

    Computer programs for interrupted time series analysis: II. A quantitative evaluation

    Multivariate Behavioral Research

    (1990)
  • D. Horn

    Why do you smoke

  • D. Horn

    A model for the study of personal choice health behavior

    International Journal of the Addictions

    (1976)
  • D. Horn et al.

    Some dimensions of a model for smoking behavior change

    American Journal of Public Health

    (1966)
  • M.F. Hoyt et al.

    Increasing adherence to a stressful decision via a motivational balance-sheet procedure: A field experiment

    Journal of Personality and Social Psychology

    (1975)
  • F.F. Ikard et al.

    A scale to differentiate between types of smoking as related to the management of affect

    International Journal of the Addictions

    (1969)
  • F.F. Ikard et al.

    The experience of affect as a determinant of smoking behavior: A series of validity studies

    Journal of Abnormal Psychology

    (1973)
  • D.N. Jackson

    The dynamics of structured personality tests: 1971

    Psychological Review

    (1971)
  • I.L. Janis et al.

    Decision making: A psychological analysis of conflict, choice and commitment

    (1977)
  • R.R. Jones et al.

    Effects of serial dependency on the agreement between visual and statistical inference

    Journal of Applied Behavior Analysis

    (1978)
  • K.G. Joreskog

    A general method for analysis of covariance structures

    Biometrika

    (1970)
  • K.G. Joreskog

    Statistical models and methods for analysis of longitudinal data

  • K.G. Joreskog

    Structural analysis of covariance and correlation matrices

    Psychometrika

    (1978)
  • K.G. Joreskog et al.
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      The inclusion criteria were as follows: (1) studies reporting both the prevalence of stages of change for smoking cessation and factors associated with specific stages, in adolescents; (2) studies reporting only the prevalence of stages of change for smoking cessation in adolescents; (3) sample consisting of adolescents, i.e., individuals aged between 12 and 19 years; (4) observational studies or intervention studies that reported prevalence data at baseline. The exclusion criteria were as follows: (1) gray literature—material published by governments, organizations, and industrial or commercial entities for non–academic purposes; theses, dissertations, conference proceedings, and abstracts; (2) review articles, editorials, and letters; (3) studies of specific sub-populations of adolescents (e.g., adolescents with acute or chronic disease); (4) studies with combined adolescent and adult or elderly samples; (5) studies using definitions of the stages of change which do not match the original TTM as defined by Prochaska et al. [10–12]: PC = not planning to change the behavior over the next six months; C = thinking of changing in the next six months, but not next month; P = planning to change next month and has already attempted to change in the past year; A = has been attempting to change for less than six months; M = has maintained change for at least six months); (6) studies that did not report prevalence data for all five stages of change. Calibration process: the whole team of four reviewers participated in a calibration process before selecting publications for review.

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    This work was supported by Grant CA27821 and CA50087 from the National Cancer Institute.

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