Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Validating stage of change measures for physical activity and dietary behaviors for overweight women

Abstract

Objective:

To investigate the construct, concurrent and predictive validity of stage of change measures for physical activity (PA), and intakes of fruit and vegetables (FVs), dietary fiber (FB) and dietary fat (DF) among a sample of overweight women.

Design:

Subjects were 401 women (mean age=41, s.d.=8.7 years; mean body mass index=32.35, s.d.=4.6) recruited to participate in a 12-month weight loss intervention trial. Concurrent validity tests included (1) self-report of current behavior, (2) decisional balance (for example, pros and cons of behavior change), (3) self-efficacy, (4) the MTI Actigraph accelerometer (for the PA staging measure), and (5) a food-frequency questionnaire (for all dietary staging measures). Predictive validity was assessed through tests of the relationship between the baseline stage of change measures and their corresponding behavior 1-year later.

Results:

Coefficient α-tests of internal consistency exceeded 0.70 on the majority of scales. Concurrent validity tests indicated strong validity evidence for three staging measures and little validity for the DF staging measure (η2 range, 0.02–0.18). All staging algorithms demonstrated predictive validity (η2 range, 0.04–0.126).

Conclusion:

Staging measures can determine motivational readiness for overweight women, contribute to the standardization of stage of change assessment and facilitate cross-study comparisons.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  1. Prochaska JO, Velicer WF . The Transtheoretical Model of health behavior change. Am J Health Promot 1997; 12: 38–48.

    Article  CAS  Google Scholar 

  2. Reed GR, Velicer WF, Prochaska JO, Rossi JS, Marcus BH . What makes a good staging algorithm: examples from regular exercise. Am J Health Promot 1997; 12: 57–67.

    Article  CAS  Google Scholar 

  3. Nigg C, Hellsten L, Norman G, Burbank P, Braun L, Breger R et al. Physical activity staging distribution: establishing a heuristic using multiple studies. Ann Behav Med 2005; 29 (suppl): 35–45.

    Article  Google Scholar 

  4. Pearlman MY, Wernicke R, Thorndike F, Haaga DA . Stages of change in smoking cessation: a comparison of expectancies among precontemplators and contemplators. J Ration Emotive Cogn Behav Ther 2004; 22: 131–147.

    Article  Google Scholar 

  5. Prochaska JJ, Rossi JS, Redding CA, Rosen AB, Tsoh JY, Humfleet GL et al. Depressed smokers and stage of change: implications for treatment interventions. Drug and Alcohol Depend 2004; 76: 143–151.

    Article  Google Scholar 

  6. Garrett NA, Alesci NL, Schultz MM, Foldes SS, Magnan SJ, Manley MW . The relationship of stage of change for smoking cessation to stage of change for fruit and vegetable consumption and physical activity in a health plan population. Am J Health Promot 2004; 19: 118–127.

    Article  Google Scholar 

  7. de Vet E, de Nooijer J, de Vries NK, Brug J . Determinants of forward stage transition from precontemplation and ontemplation for fruit consumption. Am J Health Promot 2005; 19: 278–285.

    Article  Google Scholar 

  8. Hughes JR, Keely JP, Fagerstrom KO, Callas PW . Intentions to quit smoking change over short periods of time. Addict Behav 2005; 30: 653–662.

    Article  Google Scholar 

  9. O'Hea EL, Boudreaux ED, Jeffries SK, Taylor CL, Scarinci IC, Brantley PJ . Stage of change movement across three health behaviors: the role of self-efficacy. Am J Health Promot 2004; 19: 94–102.

    Article  Google Scholar 

  10. Schumann A, Meyer C, Rumpf H, Hannover W, Hapke U, John U . Stage of change transitions and processes of change, decisional balance, and self-efficacy in smokers: a Transtheoretical Model validation using longitudinal data. Psychol Addict Behav 2005; 19: 3–9.

    Article  Google Scholar 

  11. Jordan PJ, Nigg CR . Applying the Transtheoretical Model: tailoring interventions to stages of change. In: Burbank PM, Riebe D (eds). Promoting Exercise and Behavior Change in Older Adults: Interventions with the Transtheoretical Model. Springer Publishing Co.: New York, NY, US, 2002, pp 181–207.

    Google Scholar 

  12. Steptoe A, Kerry S, Rink E, Hilton S . The impact of behavioral counseling on stage of change in the fat intake, physical activity, and cigarette smoking in adults at increased risk of coronary heart disease. Am J Public Health 2001; 91: 265–269.

    Article  CAS  Google Scholar 

  13. Hellsten L, Nigg C, Norman G, Burbank P, Braun L, Breger R et al. Accumulation of behavioral validation evidence for physical activity stage of change. Health Psychol (in press).

  14. Dallow CB, Anderson J . Using self-efficacy and a Transtheoretical Model to develop a physical activity intervention for obese women. Am J Health Promot 2003; 17: 373–381.

    Article  Google Scholar 

  15. Burkholder GJ, Evers KA . Application of the Transtheoretical Model to several problem behaviors. In: Burbank PM, Riebe D (eds). Promoting Exercise and Behavior Change in Older Adults: Interventions with the Transtheoretical Model. Springer Publishing Co.: New York, NY, US, 2002, pp 85–145.

    Google Scholar 

  16. Glanz K, Rimer BK, Lewis FM . Theory, research, and practice in health behavior and health education. In: Glanz K, Rimer BK, Lewis FM (eds). Health Behavior and Health Education. Jossey-Bass: San Francisco, CA, 2002, pp 22–40.

    Google Scholar 

  17. Reibe D, Greene GW, Ruggiero L, Stillwell KM, Blissmer B, Nigg CR et al. Evaluation of a healthy-lifestyle approach to weight management. Prev Med 2003; 36: 45–54.

    Article  Google Scholar 

  18. Clark PG, Rossi JS, Greaney ML, Riebe DA, Greene GW, Saunders SD et al. Intervening on exercise and nutrition in older adults: the Rhode Island SENIOR Project. J Aging Health 2005; 17: 753–778.

    Article  Google Scholar 

  19. Cullen KW, Bartholomew LK, Parcel GS, Koehly L . Measuring stage of change for fruit and vegetable consumption in 9–12-year old girls. J Behav Med 1998; 21: 241–254.

    Article  CAS  Google Scholar 

  20. de Oliveria M, Anderson J, Auld G, Kendall P . Validation of a tool to measure processes of change for fruit and vegetable consumption among male college students. J Nutr Educ Behav 2005; 37: 2–11.

  21. Gulliver P, Horwath C . Women's readiness to follow milk product consumption recommendations: design and evaluation of a ‘stage of change’ algorithm. J Hum Nutr Diet 2001; 14: 277–286.

    Article  CAS  Google Scholar 

  22. Sarkin JA, Johnson SS, Prochaska JO, Prochaska JM . Applying the transtheoretical model to regular moderate exercise in an overweight population: validation of stages of change measure. Prev Med 2001; 33: 462–469.

    Article  CAS  Google Scholar 

  23. Richards-Reed G, Velicer WF, Prochaska JO, Rossi JS, Marcus BH . What makes a good staging algorithm: examples from regular exercise. Am J Health Promot 1997; 12: 57–66.

    Article  Google Scholar 

  24. DiClemente C, Prochaska J, Fairhurst S, Velicer W, Velasquez M, Rossi J . The process of smoking cessation: an analysis of precontemplation, contemplation, and preparation stages of change. J Consult Clin Psychol 1991; 59: 295–304.

    Article  CAS  Google Scholar 

  25. US Department of Health and Human Services. Healthy People 2010: Understanding and Improving Health, 2nd edn. Government Printing Office: Washington DC, 2000.

  26. Nichols J, Morgan C, Chabot L, Sallis J, Calfas K . Assessment of physical activity with the Computer Science and Applications, Inc. accelerometer: laboratory versus field validation. Res Q Exerc Sport 2000; 71: 436–443.

    Article  Google Scholar 

  27. Welk GJ . Use of accelerometry-based activity monitors to assess physical activity. In: Welk GJ (ed). Physical Activity Assessments for Health-related Research. Human Kinetics: Champaign, IL, 2002, pp 125–142.

    Google Scholar 

  28. Freedon PS, Melanson E, Sirard J . Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc 1998; 30: 777–781.

    Article  Google Scholar 

  29. Kristal AR, Vizenor NC, Patterson RE, Neuhouser ML, Shattuck AL, McLerran D . Precision and bias of food frequency-based measure of fruit and vegetable intake. Cancer Epidemiol Biomarkers Prev 2000; 9: 939–944.

    CAS  PubMed  Google Scholar 

  30. Patterson RE, Kristal AR, Carter RA, Fels-Tinker L, Bolton MP, Agurs-Collins T . Measurement characteristics of the Women's Health Initiative Food Frequency Questionnaire. Ann Epidemiol 1999; 9: 178–187.

    Article  CAS  Google Scholar 

  31. Velicer WF, DiClemente CC, Prochaska JO, Brandenburg N . A decisional balance measure for assessing and predicting smoking status. J Pers Soc Psychol 1985; 48: 1279–1289.

    Article  CAS  Google Scholar 

  32. Marcus BH, Rakowski W, Rossi JS . Assessing motivational readiness and decision making for exercise. Health Psychol 1992; 11: 257–261.

    Article  CAS  Google Scholar 

  33. Rossi SR, Greene GW, Rossi JS, Plummer BA, Benisovich SV, Keller S et al. Validation of decisional balance and situational temptations measures for dietary fat reduction in a large school-based population of adolescents. Eating Behav 2001; 2: 1–18.

    Article  CAS  Google Scholar 

  34. Bandura A . Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice Hall: Englewood Cliffs, NJ, 1986.

    Google Scholar 

  35. Sallis JF, Pinski RB, Grossman RM, Patterson TL, Nader PR . The development of self-efficacy scales for health-related diet and exercise behaviors. Health Educ Res 1988; 3: 283–292.

    Article  Google Scholar 

  36. Cohen J . Statistical Power Analysis for the Behavioral Sciences, 2nd edn. Erlbaum: Hillsdale, NJ, 1988.

    Google Scholar 

  37. Schumann A, Estabrooks PA, Nigg CR, Hill J . Validation of the stages of change with mild, moderate, and strenuous physical activity behavior, intentions, and self-efficacy. Int J Sports Med 2003; 24: 363–365.

    Article  CAS  Google Scholar 

  38. Johnson SS, Driskell MM, Johnson JL, Dyment SJ, Prochaska JO, Prochaska JM et al. Transtheoretical model intervention for adherence to lipid-lowering drugs. Dis Manag 2006; 9: 102–114.

    Article  CAS  Google Scholar 

  39. Snelling AM, Adams TB, Korba C, Tucker L . Stages of change algorithm for calcium intake by male college students. J Am Diet Assoc 2006; 106: 904–907.

    Article  Google Scholar 

  40. Walton J, Hoerr S, Heine L, Frost S, Roisen D, Berkimer M . Physical activity and stages of change in fifth and sixth graders. J Sch Health 1999; 69: 285–289.

    Article  CAS  Google Scholar 

  41. Laforge RG, Velicer WF, Richmond RL, Owen N . Stage distributions for five health behaviors in the United States and Australia. Prev Med 1999; 28: 61–74.

    Article  CAS  Google Scholar 

  42. Velicer WF, Fava JF, Prochaska JO, Abrams DB, Emmons KM, Pierce JP . Distribution of smokers by stage in three representative samples. Prev Med 1995; 24: 401–411.

    Article  CAS  Google Scholar 

  43. Greene GW, Rossi SR, Reed GR, Willey C, Prochaska JO . Stages of change for reducing dietary fat to 30% of energy or less. J Am Diet Assoc 1994; 94: 1105–1110.

    Article  CAS  Google Scholar 

  44. Ni Mhurchu C, Margetts BM, Speller VM . Applying the stages-of-change model to dietary change. Nutr Rev 1997; 55: 10–16.

    Article  CAS  Google Scholar 

  45. Lechner L, Brug J, De Vries H, Van Assema P, Mudde A . Stages of change for fruit, vegetable, and fat intake: consequences of misconception. Health Educ Res 1998; 13: 1–11.

    Article  Google Scholar 

  46. Horwath CC . Applying the transtheoretical model to eating behaviour change: challenges and opportunities. Nutr Res Rev 1999; 12: 281–317.

    Article  CAS  Google Scholar 

  47. Marshall SJ, Biddle SJ . The Transtheoretical Model of behavior change: a meta-analysis of applications to physical activity and exercise. Ann Behav Med 2001; 23: 229–246.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was partially supported by grants CA81495-01A2, CA113828 and CA85873 from the National Cancer Institute. Portions of this paper were presented at the Society of Behavioral Medicine's 25th Annual Sessions, Baltimore, MD, March, 2004.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A H Robinson.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Robinson, A., Norman, G., Sallis, J. et al. Validating stage of change measures for physical activity and dietary behaviors for overweight women. Int J Obes 32, 1137–1144 (2008). https://doi.org/10.1038/ijo.2008.65

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ijo.2008.65

Keywords

This article is cited by

Search

Quick links