Comparing online and telephone survey results in the context of a skin cancer prevention campaign evaluation

Journal of Public Health (United Kingdom)

Volumn 39, Issue 1, 2017, Pages 193-201

  Hollier, L P ^a   Pettigrew, S ^a   Slevin, T ^a,b   Strickland, M ^b   Minto, C ^b  

^a CURTIN UNIVERSITY   (Australia)

^b Cancer Council WA   (Australia)

Author keywords

Campaign evaluation; Online survey; Telephone survey; Web panel

Indexed keywords

ADOLESCENT; ADULT; COMPARATIVE STUDY; FEMALE; HEALTH PROMOTION; HEALTH SURVEY; HUMAN; INTERNET; INTERVIEW; MALE; MIDDLE AGED; PROCEDURES; SKIN TUMOR; TELECOMMUNICATION; TELEPHONE; YOUNG ADULT;

ADOLESCENT; ADULT; FEMALE; HEALTH PROMOTION; HEALTH SURVEYS; HUMANS; INTERNET; INTERVIEWS AS TOPIC; MALE; MIDDLE AGED; SKIN NEOPLASMS; TELECOMMUNICATIONS; TELEPHONE; YOUNG ADULT;

EID: 85018986038     PISSN: 17413842     EISSN: 17413850     Source Type: Journal    
DOI: 10.1093/pubmed/fdw018     Document Type: Article

References (52)

1. Leavy JE, Bull FC, Rosenberg M et al. Physical activity mass media campaigns and their evaluation: A systematic review of the literature 2003-2010. Health Educ Res 2011;26:1060-85.
2. O'Hara BJ, Phongsavan P, Gebel K et al. Longer term impact of the mass media campaign to promote the get healthy information and coaching servicew: increasing the saliency of a new public health program. Health Promot Pract 2014;15:828-38.
3. Evans JR, Mathur A. The value of online surveys. Internet Res 2005;15:195-219.
4. Beck KH, Yan AF, Wang MQ. A comparison of web-based and telephone surveys for assessing traffic safety concerns, beliefs, and behaviors. J Safety Res 2009;40:377-81.
5. Braunsberger K, Wybenga H, Gates R. A comparison of reliability between telephone and web-based surveys. J Bus Res 2007; 60:758-64.
6. Blumberg SJ, Luke JV. Coverage bias in traditional telephone surveys of low-income and young adults. Public Opin Q 2007;71:734-49.
7. Hoebel J, von der Lippe E, Lange C et al. Mode differences in a mixed-mode health interview survey among adults. Arch Public Health 2014;72:46.
8. Kempf AM, Remington PL. New challenges for telephone survey research in the twenty-first century. Annu Rev Public Health 2007;28:113-26.
9. Carey RN, Reid A, Driscoll TR et al. An advance letter did not increase the response rates in a telephone survey: A randomized trial. J Clin Epidemiol 2013;66:1417-21.
10. Von der Lippe E, Schmich P, Lange C. Advance letters as a way of reducing non-response in a National Health Telephone Survey: differences between listed and unlisted numbers. Surv Res Methods 2011;5:103-16.
11. Callegaro M, McCutcheon AL, Ludwig J. Who's calling? The impact of caller ID on telephone survey response. Field Methods 2010;22:175-91.
12. Tuckel P, O'Neill H. The vanishing respondent in telephone surveys. J Advert Res 2002;42:26-48.
13. Bowling A. Mode of questionnaire administration can have serious effects on data quality. J Public Health 2005;27:281-91.
14. Cooley PC, Miller HG, Gribble JN et al. Automating telephone surveys: using T-ACASI to obtain data on sensitive topics. Comput Human Behav 2000;16:1-11.
15. Johnson TP, Fendrich M, Shaligram C et al. An evaluation of the effects of interviewer characteristics in an RDD telephone survey of drug use. J Drug Issues 2000;30:77-101.
16. Hope S, Campanelli P, Nicolaas G et al. The Role of the Interviewer in Producing Mode Effects: Results from a Mixed Modes Experiment Comparing Face-to-face, Telephone and Web Administration. Institute for Social and Economic Research (ISER)Working Paper Series, No. 2014-20, 2014.
17. Yeager DS, Krosnick JA, Chang L et al. Comparing the accuracy of RDD telephone surveys and internet surveys conducted with probability and non-probability samples. Public Opin Q 2011;75:1-39.
18. Taylor PA, Nelson NM, Grandjean BD et al. Mode Effects and Other Potential Biases in Panel-based Internet Surveys: Final Report. Laramie, WY: Wyoming Survey & Analysis Center, University of Wyoming, 2009.
19. Bowling A, Bond M, Jenkinson C et al. Short Form 36 (SF-36) Health Survey questionnaire: which normative data should be used? Comparisons between the norms provided by the Omnibus Survey in Britain, the Health Survey for England and the Oxford Healthy Life Survey. J Public Health 1999;21:255-70.
20. Kreuter F, Presser S, Tourangeau R. Social desirability bias in CATI, IVR, and web surveys the effects of mode and question sensitivity. Public Opin Q 2008;72:847-65.
21. McPeake J, Bateson M, O'Neill A. Electronic surveys: how to maximise success. Nurse Res 2014;21:24-6.
22. Hansen MR, Bentzen J. High-risk sun-tanning behaviour: A quantitative study in Denmark, 2008-2011. Public Health 2014;128:777-83.
23. Roster CA, Rogers RD, Albaum G et al. A comparison of response characteristics from web and telephone surveys. Int J Market Res 2004;46:359-74.
24. Yang M-C, Tan EC-H. Web-based and telephone surveys to assess public perception toward the National Health Insurance in Taiwan: A comparison of cost and results. Interact J Med Res 2015;4:e9.
25. Fricker S, Galesic M, Tourangeau R et al. An experimental comparison of web and telephone surveys. Public Opin Q 2005;69:370-92.
26. Berrens RP, Bohara AK, Jenkins-Smith H et al. The advent of Internet surveys for political research: A comparison of telephone and internet samples. Polit Anal 2003;11:1-22.
27. Fan W, Yan Z. Factors affecting response rates of the web survey: A systematic review. Comput Human Behav 2010;26:132-9.
28. Akl EA, Maroun N, Klocke RA et al. Electronic mail was not better than postal mail for surveying residents and faculty. J Clin Epidemiol 2005;58:425-9.
29. Truell AD, Bartlett JE, Alexander MW. Response rate, speed, and completeness: A comparison of Internet-based and mail surveys. Behav Res Methods Instrum Comput 2002;34:46-9.
30. Tingling P, Parent M, Wade M. Extending the capabilities of Internet-based research: lessons from the field. Internet Res 2003;13:223-35.
31. Australian Bureau of Statistics. Household use of Information Technology, Australia, 2012-13. 2014. http://www.abs.gov.au/AUSSTATS/abs@nsf/Lookup/8146.0Main+Features12012-13?OpenDocument (June 2015, date last accessed).
32. File T, Ryan C. Computer and Internet Use in the United States: 2013. Washington, DC: American Community Survey Reports, ACS-28, United States Census Bureau, 2014.
33. Office for National Statistics. Internet Access-Households and Individuals 2014. 2014. http://www.ons.gov.uk/ons/rel/rdit2/internet-access-households-and-individuals/2014/stb-ia-2014.html (June 2015, date last accessed).
34. Temple EC, Brown RF. A comparison of Internet-based participant recruitment methods: engaging the hidden population of cannabis users in research. J Res Pract 2012;7:1-20.
35. Craig BM, Hays RD, Pickard AS et al. Comparison of US panel vendors for online surveys. J Med Internet Res 2013;15:e260.
36. Link MW, Mokdad AH. Alternative modes for health surveillance surveys: an experiment with web, mail, and telephone. Epidemiology 2005;16:701-4.
37. Szolnoki G, Hoffmann D. Online, face-to-face and telephone surveys-comparing different sampling methods in wine consumer research. Wine Economics Policy 2013;2:57-66.
38. Hines DA, Douglas EM, Mahmood S. The effects of survey administration on disclosure rates to sensitive items among men: A comparison of an internet panel sample with a RDD telephone sample. Comput Human Behav 2010;26:1327-35.
39. Schillewaert N, Meulemeester P. Comparing response distributions of offline and online data collection methods. Int J Market Res 2005;47:163-78.
40. Montague M, Borland R, Sinclair C. Slip! Slop! Slap! and SunSmart, 1980-2000: skin cancer control and 20 years of population-based campaigning. Health Educ Behav 2001;28:290-305.
41. Dixon HG, Pratt IS, Scully ML et al. Using a mass media campaign to raise women's awareness of the link between alcohol and cancer: cross-sectional pre-intervention and post-intervention evaluation surveys. BMJ Open 2015;5:e006511.
42. Clayforth C, Pettigrew S, Mooney K et al. A cost-effectiveness analysis of online, radio and print tobacco control advertisements targeting 25-39 year-old males. Aust N Z J Public Health 2014;38:270-4.
43. Diepgen T, Mahler V. The epidemiology of skin cancer. Br J Dermatol 2002;146:1-6.
44. Dobbinson SJ, Wakefield M, Hill D et al. Prevalence and determinants of Australian adolescents' and adults' weekend sun protection and sunburn, summer 2003-2004. J Am Acad Dermatol 2008;59: 602-14.
45. Cokkinides VE, Weinstock M, Glanz K et al. Trends in sunburns, sun protection practices, and attitudes toward sun exposure protection and tanning among US adolescents, 1998-2004. Pediatrics 2006;118: 853-64.
46. Dobbinson SJ, Slevin T. What We Are Doing About Sun Protection: Are We Making Progress? Sun, Skin and Health. Australia: CSIRO Publishing, 2014,237-47.
47. Australian Bureau of Statistics. Socio-economic Indexes for Areas (SEIFA). 2011. http://www.abs.gov.au/websitedbs/censushome. nsf/home/seifa (June 2015, date last accessed).
48. Niederdeppe J. Assessing the validity of confirmed ad recall measures for public health communication campaign evaluation. J Health Commun 2005;10:635-50.
49. Tsao W-C. Big five personality traits as predictors of Internet usage categories. Int J Manage 2013;30:374-86.
50. Han JY, Kim J-H, Yoon HJ et al. Social and psychological determinants of levels of engagement with an online breast cancer support group: posters, lurkers, and non-users. J Health Commun 2012;17:356-71.
51. Terlutter R, Bidmon S, Röttl J. Who uses physician-rating websites? Differences in sociodemographic variables, and health status of users and non-users of physician-rating websites. J Med Internet Res 2014;16:e97.
52. Vocino A, Polonsky M, Dolnicar S. Segmenting Australian online panellists based on volunteering motivations. Asia Pac J Market Logist 2015;27:4-22.