Consumer evaluation of ‘Veggycation®’, a website promoting the health benefits of vegetables
Reetica Rekhy A C , Aila Khan B , Floris van Ogtrop A and Robyn McConchie AA Department of Plant and Food Sciences, Faculty of Agriculture and Environment, University of Sydney, Level 4, Biomedical Building, 1 Central Avenue, Australian Technology Park, Eveleigh, NSW 2015, Australia.
B School of Business, University of Western Sydney, Parramatta, NSW 2150, Australia.
C Corresponding author. Email: reetica.rekhy@sydney.edu.au
Health Promotion Journal of Australia 28(1) 21-29 https://doi.org/10.1071/HE16003
Submitted: 13 January 2016 Accepted: 10 May 2016 Published: 1 July 2016
Abstract
Issue addressed: Whether the website Veggycation® appeals to particular groups of consumers significantly more than other groups.
Methods: Australian adults aged ≥18 years (n = 1000) completed an online survey. The website evaluation instrument used was tested for validity and reliability. Associations between demographic variables and website evaluation dimensions of attractiveness, content, user-friendliness and loyalty intentions were examined using a general linear model (GLM). The appraisal of the website was further investigated based on the respondents’ daily consumption level of vegetables and the importance they attach to vegetable consumption in their diet, using GLM and a Tukey’s all-pair comparison.
Results: Veggycation® has a high level of acceptance among the Australian community with certain groups evaluating the website more favourably. These include women, people aged ≤ 29 years, higher income respondents, non-metro respondents and those who viewed vegetables as extremely important in their daily diet.
Conclusions: Customisation of the website for consumer groups with low vegetable consumption is recommended. Designing tailored communication tools will assist in enhancing the knowledge base of vegetable-related health benefits and may promote vegetable consumption among the Australian population.
So what?: The promotion of higher vegetable consumption is aided by tailored, well-designed web communication. This study adds to the existing body of knowledge for the education of organisations developing e-tools for promoting health education and literacy.
Key words: demographic groups, gender differences, vegetable consumption, website evaluation dimensions.
References
[1] World Health Organization. Promoting fruit and vegetable consumption around the world: information sheet. Geneva:World Health Organization; 2013. Available from: http://www.who.int/dietphysicalactivity/fruit/en/ [Verified 30 March 2016].[2] Agudo A. Measuring intake of fruit and vegetables. Background paper for the Joint FAO/WHO Workshop on Fruit and Vegetables for Health, 1–3 September 2004, Kobe, Japan. Geneva: World Health Organization; 2005. Available: http://www.who.int/iris/handle/10665/43144 [Verified 30 March 2016].
[3] Pomerleau J, Lock K, Knai C, McKee M (2005) Interventions designed to increase adult fruit and vegetable intake can be effective: a systematic review of the literature. J Nutr 135, 2486–95.
[4] Rekhy R, McConchie R (2014) Promoting consumption of fruit and vegetables for better health. Have campaigns delivered on the goals? Appetite 79, 113–23.
| Promoting consumption of fruit and vegetables for better health. Have campaigns delivered on the goals?Crossref | GoogleScholarGoogle Scholar | 24751917PubMed |
[5] Australian Institute of Health and Welfare (AIHW). Australia’s food & nutrition. Contract No.: Cat.no.PHE 163. Canberra: AIHW: 2012.
[6] Woolcott Research Pty Ltd. Evaluation of the national Go For 2&5 campaign January 2007. Australian Government Department of Health and Ageing; 2007. Available from: http://www.healthyactive.gov.au/internet/healthyactive/publishing.nsf/Content/2&5-eval-jan07 [Verified 9 June 2016].
[7] Australian Government. Swap it, don’t stop it. The Australian National Preventive Health Agency; 2013. Available from: http://www.swapitwa.com.au [Verified 6 June 2016].
[8] Department of Health and Ageing. Get set for life – habits for healthy kids. Australian Government; 2013. Available from: http://www.healthyactive.gov.au/Internet/healthyactive/publishing.nsf/Content/getset4life-index [Verified 6 June 2016].
[9] Australian Bureau of Statistics. National Health Survey: First results, 2014–15. Canberra: Australian Bureau of Statistics; 2015.
[10] Australian Bureau of Statistics. Household use of information technology, Australia, 2012–13. Canberra: Australian Bureau of Statistics; 2014.
[11] Webb TL, Joseph J, Yardley L, Michie S (2010) Using the Internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res 12, e4
| Using the Internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy.Crossref | GoogleScholarGoogle Scholar | 20164043PubMed |
[12] McDermott L, Stead M, Hastings G (2005) What is and what is not social marketing: the challenge of reviewing the evidence. JMM 21, 545–53.
| What is and what is not social marketing: the challenge of reviewing the evidence.Crossref | GoogleScholarGoogle Scholar |
[13] Eason J, MacTavish-West H, Lister C, West D. Conveying health benefits of Australian vegetables. Report No.: Contract No.: VG12043. Sydney: Horticulture Australia Ltd; 2014.
[14] Cheng C, Dunn M (2015) Health literacy and the Internet: A study on the readability of Australian online health information. Aust N Z J Public Health 39, 309–14.
| Health literacy and the Internet: A study on the readability of Australian online health information.Crossref | GoogleScholarGoogle Scholar | 25716142PubMed |
[15] Uetrecht CL, Greenberg M, Dwyer JJM, Sutherland S, Tobin S (1999) Factors influencing vegetable and fruit use: implications for promotion. Am J Health Behav 23, 172–81.
| Factors influencing vegetable and fruit use: implications for promotion.Crossref | GoogleScholarGoogle Scholar |
[16] Pringle G (2013) Research, regulation and reward – food health regulations under the spotlight. Food NZ 13, 10–1.
[17] Plaza B (2009) Monitoring web traffic source effectiveness with Google Analytics: an experiment with time series. Aslib Proc 61, 474–82.
| Monitoring web traffic source effectiveness with Google Analytics: an experiment with time series.Crossref | GoogleScholarGoogle Scholar |
[18] Ritterband LM, Thorndike FP, Cox DJ, Kovatchev BP, Gonder-Frederick LA (2009) A behavior change model for Internet interventions. Ann Behav Med 38, 18–27.
| A behavior change model for Internet interventions.Crossref | GoogleScholarGoogle Scholar | 19802647PubMed |
[19] Shaikh U, Scott BJ (2005) Extent, accuracy, and credibility of breastfeeding information on the Internet. J Hum Lact 21, 175–83.
| Extent, accuracy, and credibility of breastfeeding information on the Internet.Crossref | GoogleScholarGoogle Scholar | 15886343PubMed |
[20] Hartmann J, Sutcliffe A, De Angeli A, editors. Investigating attractiveness in web user interfaces. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. San Jose, CA: ACM; 2007.
[21] McKay HG, Glasgow RE, Feil EG, Boles SM, Barrera M (2002) Internet-based diabetes self-management and support: initial outcomes from the Diabetes Network project. Rehabil Psychol 47, 31–48.
| Internet-based diabetes self-management and support: initial outcomes from the Diabetes Network project.Crossref | GoogleScholarGoogle Scholar |
[22] Chiou W-C, Lin C–C, Perng C (2010) A strategic framework for website evaluation based on a review of the literature from 1995–2006. Inform Manage 47, 282–90.
| A strategic framework for website evaluation based on a review of the literature from 1995–2006.Crossref | GoogleScholarGoogle Scholar |
[23] Kim H, Niehm LS (2009) The impact of website quality on information quality, value, and loyalty intentions in apparel retailing. J Interact Mark 23, 221–33.
| The impact of website quality on information quality, value, and loyalty intentions in apparel retailing.Crossref | GoogleScholarGoogle Scholar |
[24] Yuan J, Morrison AM, Linton S, Feng R, Jeon S (2004) Marketing small wineries: an exploratory approach to website evaluation. Tour Recreat Res 29, 15–25.
| Marketing small wineries: an exploratory approach to website evaluation.Crossref | GoogleScholarGoogle Scholar |
[25] Kim S, Stoel L (2004) Dimensional hierarchy of retail website quality. Inform Manage 41, 619–33.
| Dimensional hierarchy of retail website quality.Crossref | GoogleScholarGoogle Scholar |
[26] Morrison AM, Taylor S, Morrison AJ, Morrison AD (1999) Marketing small hotels on the World Wide Web. Info Tech Tourism 2, 97–113.
[27] Ricciardi L, Mostashari F, Murphy J, Daniel JG, Siminerio EP (2013) A national action plan to support consumer engagement via e-health. Health Aff (Millwood) 32, 376–84.
| A national action plan to support consumer engagement via e-health.Crossref | GoogleScholarGoogle Scholar | 23381531PubMed |
[28] Keselman A, Logan R, Smith CA, Leroy G, Zeng-Treitler Q (2008) Developing informatics tools and strategies for consumer-centered health communication. J Am Med Inform Assoc 15, 473–83.
| Developing informatics tools and strategies for consumer-centered health communication.Crossref | GoogleScholarGoogle Scholar | 18436895PubMed |
[29] Snow J, Mann M. Qualtrics survey software: handbook for research professionals. Qualtrics Labs, Inc; 2013.
[30] Braveman P, Egerter S, Williams DR (2011) The social determinants of health: coming of age. Annu Rev Public Health 32, 381–98.
| The social determinants of health: coming of age.Crossref | GoogleScholarGoogle Scholar | 21091195PubMed |
[31] Woolf SH, Braveman P (2011) Where health disparities begin: the role of social and economic determinants – and why current policies may make matters worse. Health Aff (Millwood) 30, 1852–9.
| Where health disparities begin: the role of social and economic determinants – and why current policies may make matters worse.Crossref | GoogleScholarGoogle Scholar | 21976326PubMed |
[32] Australian Department of Immigration and Citizenship. Multicultural Australia. Canberra: Commonwealth of Australia; 2013.
[33] Morrison AM, Taylor JS, Douglas A (2004) Website evaluation in tourism and hospitality. J Travel Tourism Mark 17, 233–51.
| Website evaluation in tourism and hospitality.Crossref | GoogleScholarGoogle Scholar |
[34] Hong S, Kim J (2004) Architectural criteria for website evaluation – conceptual framework and empirical validation. Behav Inf Technol 23, 337–57.
| Architectural criteria for website evaluation – conceptual framework and empirical validation.Crossref | GoogleScholarGoogle Scholar |
[35] O’Brien HL, Toms EG (2010) The development and evaluation of a survey to measure user engagement. JASIST 61, 50–69.
| The development and evaluation of a survey to measure user engagement.Crossref | GoogleScholarGoogle Scholar |
[36] Likert R. A method of constructing an attitude scale. Scaling: a sourcebook for behavioral scientists. Chicago: Aldine. 1974.
[37] Sutcliffe A. Heuristic evaluation of website attractiveness and usability. 2001. Available from: http://link.springer.com/chapter/10.1007%2F3-540-45522-1_11 [Verified 24 May 2016].
[38] Sutcliffe A, editor. Assessing the reliability of heuristic evaluation for web site attractiveness and usability. Proceedings of the 35th Annual Hawaii International Conference on System Sciences HICSS-35; 2002 7–10 Jan. 2002.
[39] Morahan-Martin JM (2004) How Internet users find, evaluate, and use online health information: a cross-cultural review. Cyberpsychol Behav 7, 497–510.
| How Internet users find, evaluate, and use online health information: a cross-cultural review.Crossref | GoogleScholarGoogle Scholar | 15667044PubMed |
[40] Kivits J (2009) Everyday health and the Internet: a mediated health perspective on health information seeking. Sociol Health Illn 31, 673–87.
| Everyday health and the Internet: a mediated health perspective on health information seeking.Crossref | GoogleScholarGoogle Scholar | 19220804PubMed |
[41] Rosen DE, Purinton E (2004) Website design: viewing the web as a cognitive landscape. J Bus Res 57, 787–94.
| Website design: viewing the web as a cognitive landscape.Crossref | GoogleScholarGoogle Scholar |
[42] Ajzen I. Attitudes, personality, and behavior. Maidenhead, UK: McGraw-Hill Education; 2005.
[43] RCore T. R. A language and environment for statistical computing. Vienna; R Foundation for Statistical Computing; 2012 Available from: http://www. R-project. org [Verified 6 June 2016].
[44] Bretz F, Hothorn T, Westfall P. Multiple comparisons using R. Boca Raton, FL: CRC Press; 2010.
[45] Nardo M, Saisana M, Saltelli A, Tarantola S, Hoffman A, Giovannini E. Handbook on constructing composite indicators: methodology and user guide. 2005. Organisation for Economic Co-operation and Development.
[46] Wagner WE, III. Using IBM® SPSS® statistics for research methods and social science statistics, 5th edn. Thousand Oaks, CA: Sage; 2014.
[47] Ostry A, Young ML, Hughes M (2008) The quality of nutritional information available on popular websites: a content analysis. Health Educ Res 23, 648–55.
| The quality of nutritional information available on popular websites: a content analysis.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD1cvjvF2luw%3D%3D&md5=7e825f59706aa2e4ee053dfb50a8b4e8CAS | 17897928PubMed |
[48] Law R, Qi S, Buhalis D (2010) Progress in tourism management: a review of website evaluation in tourism research. Tour Manage 31, 297–313.
| Progress in tourism management: a review of website evaluation in tourism research.Crossref | GoogleScholarGoogle Scholar |
[49] Naik K, Tripathy P. Software testing and quality assurance: theory and practice. Hoboken, NJ: John Wiley & Sons; 2008.
[50] Baker AH, Wardle J (2003) Sex differences in fruit and vegetable intake in older adults. Appetite 40, 269–75.
| Sex differences in fruit and vegetable intake in older adults.Crossref | GoogleScholarGoogle Scholar | 12798784PubMed |
[51] Chung S-J, Hoerr SL (2005) Predictors of fruit and vegetable intakes in young adults by gender. Nutr Res 25, 453–63.
| Predictors of fruit and vegetable intakes in young adults by gender.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXlt1Kjtb0%3D&md5=c3f530b063ef18eff356c0b852044ecbCAS |
[52] Cyr D, Bonanni C (2005) Gender and website design in e-business IJEB 3, 565–82.
| Gender and website design in e-businessCrossref | GoogleScholarGoogle Scholar |
[53] Rowlands I, Nicholas D, Williams P, Huntington P, Fieldhouse M, Gunter B, et al (2008) The Google generation: the information behaviour of the researcher of the future. Aslib Proc 60, 290–310. Available from: http://dx.doi.org/10.1108/00012530810887953 [Verified 9 June 2016].
[54] Oblinger D, Oblinger J. Is it age or IT: first steps toward understanding the Net generation. Washington, DC: EDUCAUSE; 2005.
[55] Holt BJ, Morrell RW. Guidelines for web site design for older adults: the ultimate influence of cognitive factors. In Morrell RW, editor. Older adults, health information, and the World Wide Web. Mawah Psychology Press; 2001. p. 109–29.
[56] Jansen BJ. Use of the Internet in higher-income households. Washington, D.C.: Pew Research Center; 2010.
[57] Nie NH (2001) Sociability, interpersonal relations, and the Internet reconciling conflicting findings. Am Behav Sci 45, 420–35.
| Sociability, interpersonal relations, and the Internet reconciling conflicting findings.Crossref | GoogleScholarGoogle Scholar |
[58] Mollen A, Wilson H (2010) Engagement, telepresence and interactivity in online consumer experience: reconciling scholastic and managerial perspectives. J Bus Res 63, 919–25.
| Engagement, telepresence and interactivity in online consumer experience: reconciling scholastic and managerial perspectives.Crossref | GoogleScholarGoogle Scholar |
[59] Sashi C (2012) Customer engagement, buyer-seller relationships, and social media. MD 50, 253–72.
| Customer engagement, buyer-seller relationships, and social media.Crossref | GoogleScholarGoogle Scholar |
[60] Pokela J, Denny E, Steblea I, Melanson F (2008) Don’t hang up yet: a comparison of online and telephone survey methodologies. Strat Health Care Market 25, 4–7.
[61] Bias R, Mayhew D. Cost-justifying usability: an update for the Internet age, 2nd edn. San Francisco: Morgan Kaufmann Publishers; 2005.