Social Cognitive Theory

1. Social Cognitive Theory Caroline McNaughton Tittel Nutrition Education May 22, 2000

2. Social Cognitive Theory Mischel & Bandura • SCT addresses • Psychosocial dynamics influencing health behavior • Methods of promoting behavior change • Self-efficacy, self-confidence, and outcome expectations • Reciprocal determinism • Behavior, personal factors & environment all interact

3. Reciprocal DeterminismBandura Person EnvironmentBehavior

4. Relevance of SCT to Health Education • Comprehensive • Cognitive, emotional & behavioral explanations of behavior  • Constructs provide avenues for behavioral research & health education practice • Application of theoretical ideas developed in other areas of psychology to health behaviors & behavior 

5. Environment Situation Behavioral capability Expectations Expectancies Self-control Observational learning Reinforcements Self-efficacy Emotional coping responses Reciprocal determinism Constructs of SCTMischel & Bandura

6. Use of SCT in Nutrition • Predicting Influences • “Social cognitive model of fruit and vegetable consumption in elementary school children” -Resnicow K et al • “Social-cognitive predictors of fruit and vegetable intake in children” -Reynolds KD et al • “Examination of specific nutrition/health behaviors using a social cognitive model” -Lewis CJ et al • Interventions • “Gimme 5 fruit, juice, and vegetables for fun and health: Outcome evaluation” -Baranowski T et al • “Development and evaluation of an intervention program: “Control on campus” -Wdowik MJ et al • “Changing fruit and vegetable consumption among children: The 5-a-Day Power Plus program in St. Paul, Minnesota” -Perry CL et al

7. Beverage Consumption • Extent to which milk & soda consumption behaviors are influenced by SC variables has not been examined • Justification • Current health concerns • consumption behaviors can be measured accurately • comparisons b/t whole/low-fat/skim & regular/diet soda Lewis et al (1989) J Am Diet Assoc; 89:194-202

8. Study DesignLewis et al • Written questionnaire mailed in 2 phases • Phase 1: 39 items frequency of consumption, knowledge, attitudes & behavior as well as demog • Phase 2: 59 items differential association, social and non-social reinforcement, behavior modeling • 457 adults mean age of 47 y, 58% female • 709 college students mean age 21 y, 50% female

9. Model for Food Frequency Consumption Behavior modeling Frequency of food consumption behavior Differential Association Evaluative Definitions Non-social reinforcement Social Reinforcement Lewis et al

10. SCT VariablesLewis et al • Differential association • perceptions of family, friends, health experts, media • Attitude • “milk is important” & “soda is acceptable” • Social reinforcement • positive feelings, belonging, pleasing others • Nutrition knowledge • “true” & “false” & “don’t know”

11. SCT VariablesLewis et al • Behavior modeling • frequency by mother, father, other adult, significant other, friend, & favorite media star • Behavioral commitment • selection of beverages low in fat & sugar • Taste enjoyment • “not at all” (1) to “very much” (5)

12. ResultsLewis et al • For both groups and for all 4 beverages, neither social reinforcement nor behavior modeling directly influence FOBC • Milk • taste enjoyment, commitment, attitudes toward importance directly related to FOBC for both groups & both whole & low-fat/skim • taste enjoyment related to commitment & attitude • media, student, whole versus family, adult, whole

13. ResultsLewis et al • Soda • more variable than milk for consumption b/t groups & type of beverage • taste enjoyment & commitment were directly related to FOBC for both groups & both regular & diet

14. ConclusionsLewis et al “Best predictor of behavior is the person’s intention to perform the behavior” “Nutrition knowledge . . . may help to create an intervening variable, ‘behavioral intention,’ which in turn leads to the actual behavior” “ . . . social beverages . . . more variable & easily changed . . . healthful beverages. . . steady & deeply rooted”

15. Gimme 5! • Multi-component randomized school intervention in 4th and 5th graders to  FJV consumption • Levels of FJV consumption in children range from 1.9 to 2.5 servings •  thru the elementary school years • Focus groups conducted to determine environmental, personal & behavioral factors Baranowski et al (2000) Health Education & Behavior; 27(1):96-111

16. Gimme 5!Baranowski et al • 8 matched elementary school pairs • 6-week intervention (12 sessions) • conducted by trained teacher • transparencies, handouts, worksheets, posters & weekly newsletters • Taste testing of snacks prepared by FSP • MTV-like video • Role-playing skits • Point-of-Purchase education

17. SCT VariablesBaranowski et al • Environment •  availability & accessibility • Behavioral capability • asking skills, FaSST recipes • Outcome expectancies •  performance w/o  acceptance by peers • Self-control • Goals for FJV at meals & snacks

18. SCT VariablesBaranowski et al • Observational Learning • teacher, parents (?) • Reinforcement • prizing for completing assignments, congratulations • Self-efficacy • Role-play to bolster asking & shopping skills • Reciprocal determinism

19. ResultsBaranowski et al • 1,172 students provided 7-d food records for 3 y • 15% African American, 85% Euro-American • Curriculum implementation was 47% for all activities, w/ only 22% of crucial activities performed •  participation in video & POP education activities • Effect size of 0.2 servings comparable to other interventions • ’s in weekday FJV consumption • impacting home consumption is elusive

20. ResultsBaranowski et al

21. Future DirectionsBaranowski et al • Better understanding of food choice • More effectively impact mediating variables & processes • Explorations of alternatives channels • Teacher training which results in higher curriculum fidelity • Higher dose of several intervention components

22. Control on Campus Abstract from Wdowik et al (2000) Diabetes Educ; 26(1): 95-104 • Based on SCT and EHBM • Type I Diabetes knowledge, attitudes & behaviors assessed pre-, post- & at follow-up • 3 intervention cohorts, 1 control • Reporting of HbA1C & knowledge  significantly for intervention groups • More support on campus, overcame fears associated with BG testing,  frequency of BG testing,  testing when BG felt to be low

23. Limitations of SCT • Too many constructs • Limited in its ability to predict behavior • No significant behavior  seen in large intervention studies • Applied to a single behavior or not • Additional influences • Fails to address nonlinearities

24. References • Baranowski T et al. (2000) Health Education and Behavior; 27(1):96-111. • Elder JP. Motivating Health Behavior. New York: Delmar, 1994. • Glanz K. Health Behavior and Health Education: Theory, Research and Practice. San Francisco: Jossey-Bass, 1997. • Lewis CJ et al. (1989) J Am Diet Assoc; 89:194-202. • Perry CL et al. (1998) Am J Pub Health; 88(4):603-609. • Resnicow K et al. (1997) Health Psychology; 16(3):272-276. • Reynolds KD et al. J of Nutr Edu; 31(1):23-30. • Wdowik MJ et al. (2000) Diabetes Educ; 26(1):95-104.