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Who benefits from a dietary online intervention? Evidence from Italy, Spain and Greece

  • Ralf Schwarzer (a1), Lena Fleig (a1), Lisa M Warner (a1), Maryam Gholami (a1), Lluis Serra-Majem (a2) (a3) (a4), Joy Ngo (a2), Blanca Roman-Viñas (a2) (a3), Lourdes Ribas-Barba (a2) (a3), Alessandro Distante (a5), Evangelia Ntzani (a6) (a7), George Giannakis (a8) and Maria L Brandi (a9)...
Abstract
Objective

The traditional Mediterranean diet includes high consumption of fruits, vegetables, olive oil, legumes, cereals and nuts, moderate to high intake of fish and dairy products, and low consumption of meat products. Intervention effects to improve adoption of this diet may vary in terms of individuals’ motivational or volitional prerequisites. In the context of a three-country research collaboration, intervention effects on these psychological constructs for increasing adoption of the Mediterranean diet were examined.

Design

An intervention was conducted to improve Mediterranean diet consumption with a two-month follow-up. Linear multiple-level models examined which psychological constructs (outcome expectancies, planning, action control and stage of change) were associated with changes in diet scores.

Setting

Web-based intervention in Italy, Spain and Greece.

Subjects

Adults (n 454; mean age 42·2 (sd 10·4) years, range 18–65 years; n 112 at follow-up).

Results

Analyses yielded an overall increase in the Mediterranean diet scores. Moreover, there were interactions between time and all four psychological constructs on these changes. Participants with lower levels of baseline outcome expectancies, planning, action control and stage of change were found to show steeper slopes, thus greater behavioural adoption, than those who started out with higher levels.

Conclusions

The intervention produced overall improvements in Mediterranean diet consumption, with outcome expectancies, planning, action control and stage of change operating as moderators, indicating that those with lower motivational or volitional prerequisites gained more from the online intervention. Individual differences in participants’ readiness for change need to be taken into account to gauge who would benefit most from the given treatment.

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Copyright
Corresponding author
* Corresponding author: Email ralf.schwarzer@fu-berlin.de
References
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1. Joshipura, KJ, Hu, FB, Manson, JE et al. (2001) The effect of fruit and vegetable intake on risk for coronary heart disease. Ann Intern Med 134, 11061114.
2. Sofi, F, Cesari, F, Abbate, R et al. (2008) Adherence to Mediterranean diet and health status: meta-analysis. BMJ 337, a1344.
3. Sofi, F, Abbate, R, Gensini, GF et al. (2010) Accruing evidence on benefits of adherence to the Mediterranean diet on health: an updated systematic review and meta-analysis. Am J Clin Nutr 92, 11891196.
4. Estruch, R, Ros, E, Salas-Salvadó, J et al. (2013) Primary prevention of cardiovascular disease with a Mediterranean diet. N Engl J Med 368, 12791290.
5. Riboli, E & Norat, T (2003) Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk. Am J Clin Nutr 78, 3 Suppl., 559S569S.
6. Vainio, H & Weiderpass, E (2006) Fruit and vegetables in cancer prevention. Nutr Cancer 54, 111142.
7. Serra-Majem, L, Roman, B & Estruch, R (2006) Scientific evidence of interventions using the Mediterranean diet: a systematic review. Nutr Rev 64, 2 Pt 2, S27S47.
8. Guilbert, JJ (2003) The World Health Report 2002 – Reducing Risks, Promoting Healthy Life. Educ Health (Abingdon) 16, 230.
9. Hall, JN, Moore, S, Harper, SB et al. (2009) Global variability in fruit and vegetable consumption. Am J Prev Med 36, 402409.
10. Shaikh, AR, Yaroch, AL, Nebeling, L et al. (2008) Psychosocial predictors of fruit and vegetable consumption in adults: a review of the literature. Am J Prev Med 34, 535543.
11. Schwarzer, R & Luszczynska, A (2015) Health action process approach. In Predicting Health Behaviours, 3rd ed., pp. 252278 [M Conner and P Norman, editors]. Maidenhead: McGraw-Hill Open University Press.
12. Godinho, CA, Alvarez, M-J, Lima, ML et al. (2015) Health messages to promote fruit and vegetable consumption at different stages: a match–mismatch design. Psychol Health 30, 14101432.
13. Bandura, A (1997) Self-Efficacy: The Exercise of Control. New York: Freeman.
14. Prochaska, JO & DiClemente, CC (1983) Stages and processes of self-change of smoking: toward an integrative model of change. J Consult Clin Psychol 51, 390395.
15. Fishbein, M & Ajzen, I (2010) Prediction and Change of Behavior: The Reasoned Action Approach. New York: Psychology Press.
16. Radtke, T, Kaklamanou, D, Scholz, U et al. (2014) Are diet-specific compensatory health beliefs predictive of dieting intentions and behaviour? Appetite 76, 3643.
17. Hagger, MS, Luszczynska, A, de Wit, J et al. (2016) Implementation intention and planning interventions in health psychology: recommendations from the Synergy expert group for research and practice. Psychol Health 31, 814839.
18. Hagger, MS & Luszczynska, A (2014) Implementation intention and action planning interventions in health contexts: state of the research and proposals for the way forward. Appl Psychol Health Well Being 6, 147.
19. Adriaanse, MA, Vinkers, CD, De Ridder, DT et al. (2011) Do implementation intentions help to eat a healthy diet? A systematic review and meta-analysis of the empirical evidence. Appetite 56, 183193.
20. Sniehotta, FF, Scholz, U & Schwarzer, R (2005) Bridging the intention–behaviour gap: planning, self-efficacy, and action control in the adoption and maintenance of physical exercise. Psychol Health 20, 143160.
21. Zhou, G, Gan, Y, Miao, M et al. (2015) The role of action control and action planning on fruit and vegetable consumption. Appetite 91, 6468.
22. Schröder, H, Fitó, M, Estruch, R et al. (2011) A short screener is valid for assessing Mediterranean diet adherence among older Spanish men and women. J Nutr 141, 11401145.
23. Fleig, L, Ngo, J, Roman, B et al. (2015) Beyond single behaviour theory: adding cross-behaviour cognitions to the health action process approach. Br J Health Psychol 20, 824841.
24. Kreausukon, P, Gellert, P, Lippke, S et al. (2012) Planning and self-efficacy can increase fruit and vegetable consumption: a randomized controlled trial. J Behav Med 35, 443451.
25. Lippke, S, Ziegelmann, JP, Schwarzer, R et al. (2009) Validity of stage assessment in the adoption and maintenance of physical activity and fruit and vegetable consumption. Health Psychol 28, 183193.
26. Heck, RH, Thomas, SL & Tabata, LN (2014) Multilevel and Longitudinal Modeling with IBM SPSS. New York: Routledge.
27. Hoffman, L (2015) Longitudinal Analysis: Modeling Within-Person Fluctuation and Change. Oxford: Routledge.
28. De Vet, E, De Nooijer, J, De Vries, NK et al. (2006) The transtheoretical model for fruit, vegetable and fish consumption: associations between intakes, stages of change and stage transition determinants. Int J Behav Nutr Phys Act 3, 13.
29. Wiedemann, AU, Lippke, S, Reuter, T et al. (2011) The more the better? The number of plans predicts health behaviour change. Appl Psychol 3, 87106.
30. Steptoe, A, Perkins-Porras, L, McKay, C et al. (2003) Psychological factors associated with fruit and vegetable intake and with biomarkers in adults from a low-income neighborhood. Health Psychol 22, 148155.
31. Di Noia, J, Contento, IR & Prochaska, JO (2008) Computer-mediated intervention tailored on transtheoretical model stages and processes of change increases fruit and vegetable consumption among urban African-American adolescents. Am J Health Promot 22, 336341.
32. Thomson, CA & Ravia, J (2011) A systematic review of behavioral interventions to promote intake of fruit and vegetables. J Am Diet Assoc 111, 15231535.
33. Bartholomew, LK, Parcel, GS & Kok, G (1998) Intervention mapping: a process for developing theory and evidence-based health education programs. Health Educ Behav 25, 545563.
34. Michie, S, Ashford, S, Sniehotta, FF et al. (2011) A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: the CALO-RE taxonomy. Psychol Health 26, 14791498.
35. Michie, S, Richardson, M, Johnston, M et al. (2013) The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med 46, 8195.
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Public Health Nutrition
  • ISSN: 1368-9800
  • EISSN: 1475-2727
  • URL: /core/journals/public-health-nutrition
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