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Abstract

Purpose.

Test the applicability of the transtheoretical model (TTM) to adult fruit/vegetable consumption.

Design.

Cross-sectional random-digit dial survey.

Setting.

Hawaii.

Subjects.

700 (62.6% female; age [mean ± SD], 47 ± 17.1 years; education [mean ± SD], 14.6 ± 2.8 years; 35.0% white, 31.1% Asian, 22.1% native Hawaiian/Pacific Islander, 11.8% other).

Measures.

Stages, processes, self-efficacy, decisional balance, and self-reported fruit/vegetable consumption.

Analysis.

Confirmatory factor analysis tested the factor structure. Analyses of variance were used to explore stage differences in constructs.

Results.

Stage distribution was precontemplation (33%), contemplation (4%), preparation (37%), action (3%), and maintenance (23%). A 10-factor process model with two higher-order correlated factors (experiential and behavioral) provided the best data fit (X² = 1446.12; df = 366; p < .0001; comparative fit index [CFI] = .89; standardized root mean square residual [SRMR] = .05). The self-efficacy structure fit the data well (X² = 81.86; df = 9; p < .0001; CFI = .94; SRMR = .04), as did the decisional balance structure (X² = 37.42; df = 19;p = .007; CFI = .99; SRMR = .02). Processes, self-efficacy, decisional balance, and fruit/vegetable consumption behavior differed significantly by stage, with medium effect sizes for most variables.

Conclusion.

The variables revealed adequate fit to the theorized measurement models. TTM predictions regarding stage differences in self-efficacy, pros and cons, and fruit/vegetable consumption were confirmed; however, most experiential and behavioral processes increased in the early stages and then leveled off.

Keywords

Transtheoretical Model Processes of Change Stages of Change Self-efficacy Decisional Balance Fruit and Vegetables Prevention Research Manuscript format: research Research purpose: modeling/relationship testing Study design: nonexperimental Outcome measure: cognitive,behavioral Setting: state Health focus: nutrition Strategy: behavior change Target population: adults Target population circumstances: education/income level,geographic location,ethnicity

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References

Ness

Powles

. Fruit and vegetables and cardiovascular disease: a review. Int J Epidemiol. 1997;26:1–13.

Joshipura

Ascherio

Manson

. Vegetable and fruit intake in relation to ischemic stroke. JAMA. 1999;282:1233–1239.

Peto

. Cancer epidemiology in the last century and the next decade. Nature. 2001;411:390–395.

Marwich

. Learning how phytochemicals fight disease. JAMA. 1995;274:1328–1330.

US Dept of Agriculture, Human Nutrition Information Service. The Food Guide Pyramid. Washington, DC: US Dept of Agriculture; 1992. Home and Garden Bulletin 232.

Serdula

Bland

. Trends in fruit and vegetable consumption among adults in 16 US states: Behavioral Risk Factor Surveillance System, 1990–1996. Am J Public Health. 2000;90:777–781.

State of Hawaii BRFSS 2005: How often do you eat fruits and vegetables? Available at: http://www.hawaii.gov/health/statistics/brfss/brfss2005/2005/demo05/-frtindx.html. Accessed November 21, 2007.

Krebs-Smith

Heimendinger

Patterson

. Psychosocial factors associated with fruit and vegetable consumption. Am J Health Promot. 1995;10:98–104.

Havas

Treiman

Langenberg

. Factors associated with fruit and vegetable consumption among women participating in WIC. J Am Diet Assoc. 1998;98:1141–1148.

10.

Steptoe

Perkins-Porras

McKay

. Psychological factors associated with fruit and vegetable intake and with biomarkers in adults from a low-income neighborhood. Health Psychol. 2003;22:148–155.

11.

Van Duyn

MAS

Kristal

Dodd

. Association of awareness, intrapersonal and interpersonal factors, and stage of change with fruit and vegetable consumption: a national survey. Am J Health Promot. 2001;16:69–78.

12.

Patterson

Kristal

White

. Do beliefs, knowledge and perceived norms about diet and cancer predict dietary change? Am J Public Health. 1996;86:1394–1400.

13.

Harnack

Block

Subar

Lane

Brand

. Association of cancer prevention-related nutrition knowledge, beliefs and attitudes to cancer prevention dietary behavior. J Am Diet Assoc. 1997;97:957–965.

14.

Brug

Lechner

de Vries

. Psychosocial determinants of fruit and vegetable consumption. Appetite. 1995;25:285–296.

15.

Brug

Glanz

Kok

. The relationship between self-efficacy, attitudes, intake compared to others, consumption and stages of change related to fruit and vegetables. Am J Health Promot. 1997;12:25–30.

16.

Lechner

Brug

de Vries

. Misconceptions of fruit and vegetable consumption: differences between objective and subjective estimation of intake. J Nutr Educ. 1997;29:313–320.

17.

Dittus

Hillers

Beerman

. Benefits and barriers to fruit and vegetable intake: relationship between attitudes and consumption. J Nutr Educ. 1995;27:120–126.

18.

Prochaska

Di Clemente

. Stages and processes of self-change in smoking: towards an integrative model of change. J Consult Clin Psychol. 1983;51:390–395.

19.

Prochaska

Redding

Evers

. The transtheoretical model of behavior change. In: Glanz

Lewis

Rimer

eds. Health Behavior and Health Education: Theory, Research and Practice. 2nd ed. San Francisco, Calif: Jossey-Bass; 1997:60–84.

20.

Bandura

. Self-efficacy mechanisms in human agency. Am Psychol. 1982;87:122–147.

21.

Janis

Mann

. Decision-Making: A Psychological Analysis of Conflict, Choice and Commitment. New York, NY: Free Press; 1977.

22.

Padula

Rossi

Nigg

. Using focus groups for instrument development: application of the transtheoretical model to fruit and vegetable behaviors of older adults. J Nutr Elderly. 2003;22:13–34.

23.

Laforge

Greene

Prochaska

. Psychosocial factors influencing low fruit and vegetable consumption. J Behav Med. 1994;17:361–374.

24.

Campbell

Symons

Demark-Wahnfried

. Stages of change and psychosocial correlates of fruit and vegetable consumption among rural African-American church members. Am J Health Promot. 1998;12:185–191.

25.

Ling

Horwath

. Self-efficacy and consumption of fruit and vegetables—validation of a summated scale. Am J Health Promot. 1999;13:290–298.

26.

Ling

Horwath

. Defining and measuring stages of change for dietary behaviors: readiness to meet fruit, vegetable and grain guidelines among Chinese Singaporeans. J Am Diet Assoc. 2000;100:898–904.

27.

Ling

Horwath

. Perceived benefits and barriers of increased fruit and vegetable consumption: validation of summated scales. J Nutr Educ. 2001;33:603–610.

28.

Betts

Horacek

. The importance of decisional balance and self-efficacy in relation to stages of change for fruit and vegetable intakes by young adults. Am J Health Promot. 2002;16:157–166.

29.

Tucker

Reicks

. Exercise as a gateway behavior for healthful eating among older adults: an exploratory study. J Nutr Educ Behav. 2002;34:S14–S19.

30.

Greene

Fey-Yensan

Padula

. Differences in psychosocial variables by stage of change for fruits and vegetables in older adults. J Am Diet Assoc. 2004;104:1236–1243.

31.

Kloek

van Lenthe

van Nierop

PWM

Mackenbach

. Stages of change for fruit and vegetable consumption in deprived neighborhoods. Health Educ Behav. 2004;31:223–241.

32.

De Oliveira MDCF, Anderson

Auld

Kendall

. 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.

33.

Burke

Richards

Milligan

RAK

. Stages of change for health-related behaviors in 18-year old Australians. Psychol Health. 2000;14:1061–1075.

34.

Campbell

Tessaro

DeVellis

. Tailoring and targeting a worksite health promotion program to address multiple health behaviors among blue collar women. Am J Health Promot. 2000;14:306–313.

35.

Frame

Green

Herr

. The stages of change for dietary fat and fruit and vegetable intake of patients at the outset of a cardiac rehabilitation program. Am J Health Promot. 2001;15:405–413.

36.

Chung

Hoerr

Levine

Coleman

. Processes underlying young women's decisions to eat fruits and vegetables. J Hum Nutr Diet. 2006;19:287–298.

37.

de Vet

de Nooijer

de Vries

Brug

. Determinants of forward stage transition from precontemplation and contemplation for fruit consumption. Am J Health Promot. 2005;19:278–285.

38.

de Vet

de Nooijer

de Vries

Brug

. Do the transtheoretical processes of change predict transitions in stages of change for fruit intake? Health Educ Behav. 2006;2:1–16.

39.

Kloek

van Lenthe

van Nierop

PWM

. Impact evaluation of a Dutch community intervention to improve health-related behaviour in deprived neighbourhoods. Health Place. 2006;12:665–677.

40.

Resnicow

McCarty

Baranowski

. Are precontemplators less likely to change their dietary behavior? A prospective analysis. Health Educ Res. 2003;18:693–705.

41.

Sorenson

Stoddard

Macario

. Social support and readiness to make dietary changes. Health Educ Behav. 1998;25:586–598.

42.

Campbell

DeVellis

Strecher

. Improving dietary behavior: the effectiveness of tailored messages in primary care settings. Am J Public Health. 1994;84:783–787.

43.

Perkins-Porras

Cappuccio

Rink

. Does the effect of behavioral counseling on fruit and vegetable intake vary with stage of readiness to change? Prev Med. 2005;40:314–320.

44.

Pullen

Walker

. Midlife and older rural women's adherence to US dietary guidelines across stages of change in healthy eating. Public Health Nurs. 2002;19:170–178.

45.

Di Noia

Schinke

Prochaska

Contento

. Application of the transtheoretical model to fruit and vegetable consumption among economically disadvantaged African-American adolescents: preliminary findings. Am J Health Promot. 2006;20:342–348.

46.

Henry

Reimer

Smith

Reicks

. Associations of decisional balance, processes of change, and self-efficacy with stages of change for increased fruit and vegetable consumption among low-income African-American mothers. J Am Diet Assoc. 2006;106:841–849.

47.

Horwath

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

48.

Lamb

Joshi

. The stage model and processes of change in dietary fat reduction. J Hum Nutr Diet. 1996;9:43–53.

49.

Bowen

Meischke

Tomoyasu

. Preliminary evaluation of the processes of changing to a low fat diet. Health Educ Res. 1994;9:85–94.

50.

Clark

Rossi

Greaney

. Intervening on exercise and nutrition in older adults: the Rhode Island SENIOR Project. J Aging Health. 2005;17:753–778.

51.

Rossi

Greene

. Development of a brief measure of self-efficacy for fruit and vegetable consumption in older adults [abstract]. Ann Behav Med. 2003;25(suppl):S159.

52.

Rossi

Greene

. Development of a brief measure of decision-making for fruit and vegetable consumption in older adults [abstract]. Ann Behav Med. 2001;23(suppl):S096.

53.

Thompson

Subar

Smith

. Fruit and vegetable assessment: performance of 2 new short instruments and a food frequency questionnaire. J Am Diet Assoc. 2002;102:1764–1772.

54.

Muthen

. Mplus: Statistical Analysis With Latent Variables. 3rd ed. Los Angeles, Calif: Muthen & Muthen; 2004.

55.

Arbuckle

Wothke

. AMOS 4 User's Reference Guide. Chicago, Ill: Smallwaters Corp; 1999.

56.

Enders

Bandalos

. The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Struct Equation Modeling. 2001;8:430–457.

57.

Arbuckle

. Full information estimation in the presence of incomplete data. In: Marcoulides

Schumacker

eds. Advanced Structural Equation Modeling: Issues and Techniques. Mahwah, NJ: Erlbaum; 1996:243–277.

58.

Bollen

. Structural Equations With Latent Variables. New York, NY: Wiley; 1989.

59.

Joreskog

. Testing structural equation models. In: Bollen

ed. Testing Structural Equation Models. Newbury Park, Calif: Sage Publications; 1993:294–316.

60.

Bentler

. Comparative fit indexes in structural models. Psychol Bull. 1990;107:238–246.

61.

Bentler

. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equation Modeling. 1999;6:1–55.

62.

Marsh

Balla

McDonald

. Goodness-of-fit indexes in confirmatory factor analysis: the effect of sample size. Psychol Bull. 1988;103:391–410.

63.

Tabachnik

Fidell

. Using Multivariate Statistics. 3rd ed. New York, NY: HarperCollins College Publishers; 1996.

64.

Cohen

. Statistical Power Analysis for the Behavioral Sciences. New York, NY: Academic; 1977.

65.

Centers for Disease Control and Prevention: Behavioral Risk Factor Surveillance System: Prevalence and Trends Data. Available at: http://apps.nccd.cdc.gov/brfss/. Accessed March 3, 2008.

66.

Bowen

Meischke

Tomoyasu

. Preliminary evaluation of the processes of changing to a low-fat diet. Health Educ Res. 1994;9:85–94.

67.

Ounpuu

. Application of the Transtheoretical Model to Dietary Fat Reduction [dissertation]. Guelph, Ontario, Canada: University of Guelph; 1997.

68.

Gulliver

. The Transtheoretical Model and Milk Product Intake [dissertation]. Dunedin, New Zealand: University of Otago; 1998.

69.

Segan

Borland

Greenwood

. What is the right thing at the right time? Interactions between stages and processes of change among smokers who make a quit attempt. Health Psychol. 2004;23:86–93.

70.

Rosen

. Is the sequencing of change processes by stage consistent across health problems? A meta analysis. Health Psychol. 2000;19:593–604.

Investigating Fruit and Vegetable Consumption Using the Transtheoretical Model

Abstract

Purpose.

Design.

Setting.

Subjects.

Measures.

Analysis.

Results.

Conclusion.

Keywords

Get full access to this article

References