References
- Lee LM, Thacker SB. Public health surveillance and knowing about health in the context of growing sources of health data. Am J Prev Med. 2011;41(6):636–640. doi:10.1016/j.amepre.2011.08.015.
- American College Health Association. Standards of practice for health promotion in higher education. https://www.acha.org/documents/resources/guidelines/ACHA_Standards_of_Practice_for_Health_Promotion_in_Higher_Education_May2012.pdf. Published May 2012. Accessed September 10, 2018.
- Council for the Advancement of Standards in Higher Education. CAS Professional Standards for Higher Education. Washington, DC: Council for the Advancement of Standards in Higher Education; 2015.
- Ottawa Charter for Health Promotion. Health Promot Int. 1986;1(4):405. doi:10.1093/heapro/1.4.405.
- Buhi ER, DeBate RD, McDermott RJ. Planning health promotion and disease prevention programs. In: Coreil J ed. Social and Behavioral Foundations of Public Health. Los Angeles, CA:Sage; 2010:247–272.
- American College Health Association. Healthy Campus 2020. https://www.acha.org/healthycampus. Published 2017. Accessed August 31, 2018.
- National Institute on Alcohol Abuse and Alcoholism. College alcohol intervention matrix (CollegeAIM). https://www.collegedrinkingprevention.gov/CollegeAIM/Introduction/Default.aspx. Published 2017. Accessed August 31, 2018.
- Archer E, Hand GA, Blair SN. Validity of U.S. nutritional surveillance: national health and nutrition examination survey caloric energy intake data, 1971-2010. PLoS One. 2013;8(10):e76632. doi:10.1371/journal/pone.0076632.
- Samson JE, Tanner-Smith EE. Single-session alcohol interventions for heavy drinking college students: a systematic review and meta-analysis. J Stud Alcohol Drugs. 2015;76(4):530–543. doi:10.15288/jsad.2015.76.530.
- Kaner EF, Beyer FR, Muirhead C, et al. Effectiveness of brief alcohol interventions in primary care populations. Cochrane Database Syst Rev. 2018;2:CD004148. doi:10.1002/14651858.CD004148.pub4.
- Tobler NS, Stratton HH. Effectiveness of school-based drug prevention programs: a meta-analysis of the research. J Prim Prev. 1997;18(1):71–128. doi:10.1023/A:1024630205999.
- Bernert DJ, Ding K, Hoban MT. Sexual and substance use behaviors of college students with disabilities. Am J Health Behav. 2012;36(4):459–471. doi:10.5993/AJHB.36.4.3.
- Goodwin RD, Grinberg A, Shapiro J, et al. Hookah use among college students: prevalence, drug use, and mental health. Drug Alcohol Depend. 2014;141:16–20. doi:10.1016/j.drugalcdep.2014.04.024.
- Kerr D, Ding K, Burke A, Ott-Walter K. An alcohol, tobacco, and other drug use comparison of lesbian, bisexual, and heterosexual undergraduate women. Subst Use Misuse. 2015;50(3):340–349. doi:10.3109/10826084.2014.980954.
- Shih T-H FX. Comparing response rates in e-mail and paper surveys: a meta-analysis. Educ Res Rev. 2009;4:26–40. doi:10.1016/j.edurev.2008.01.003.
- Slater M, Kiran T. Measuring the patient experience in primary care: comparing e-mail and waiting room survey delivery in a family health team. Can Fam Physician. 2016;62(12):e740–e748. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5154665/pdf/062e740.pdf.
- McMahon SR, Iwamoto M, Massoudi MS, et al. Comparison of e-mail, fax, and postal surveys of pediatricians. Pediatrics. 2003;111(4 Pt 1):e299–303. http://pediatrics.aappublications.org/content/pediatrics/111/4/e299.full.pdf.
- Seguin R, Godwin M, MacDonald S, McCall M. E-mail or snail mail? Randomized controlled trial on which works better for surveys. Can Fam Physician. 2004;50:414–419.
- Akl EA, Maroun N, Klocke RA, Montori V, Schünemann HJ. Electronic mail was not better than postal mail for surveying residents and faculty. J Clin Epidemiol. 2005;58(4):425–429. doi:10.1016/j.jclinepi.2004.10.006.
- American College Health Association. Fall 2016 reference group data report. http://www.acha-ncha.org/docs/NCHA-II_FALL_2016_REFERENCE_GROUP_DATA_REPORT.pdf. Published 2017. Accessed June 4, 2018.
- CORE Institute. CORE alcohol and drug survey long form - form 194: executive summary 2011-2013 national data. https://core.siu.edu/_common/documents/2011-2013.pdf. Published 2014. Accessed December 5, 2018.
- National Center for Education Statistics. Digest of Education Statistics, 2015. https://nces.ed.gov/pubs2016/2016014.pdf. Published 2016. Accessed December 5, 2018.
- Delker E, Brown Q, Hasin DS. Alcohol consumption in demographic subpopulations: an epidemiologic overview. Alcohol Res. 2016;38:7–15.
- Keeter S, Miller C, Kohut A, Groves RM, Presser S. Consequences of reducing nonresponse in a national telephone survey. Public Opin Q. 2000;64(2):125–148. doi:10.1086/317759.
- Maitland A, Lin A, Cantor D, et al. A nonresponse bias analysis of the health information national trends survey (HINTS). J Health Commun. 2017;22(7):545–553. doi:10.1080/10810730.2017.1324539.
- Kypri K, Stephenson S, Langley J. Assessment of nonresponse bias in an internet survey of alcohol use. Alcohol Clin Exp Res. 2004;28:630–634.
- Link MW, Mokdad AH. Effects of survey mode on self-reports of adult alcohol consumption: a comparison of mail, web and telephone approaches. J Stud Alcohol. 2005;66:239–245.
- Sarndal C-E, Swensson B, Wretman J. Model Assisted Survey Sampling. New York, NY: Springer; 1992.
- West BT, McCabe SE. Alternative approaches to assessing nonresponse bias in longitudinal survey estimates: an application to substance-use outcomes among young adults in the United States. Am J Epidemiol. 2017;185(7):591–600. doi:10.1093/aje/kww115.
- Lin I-F, Schaeffer NC. Using survey participants to estimate the impact of nonparticipation. Public Opin Q. 1995;59(2):236–258. doi:10.1086/269471.
- Meiklejohn J, Connor J, Kypri K. The effect of low survey response rates on estimates of alcohol consumption in a general population survey. PLoS One. 2012;7(4):e35527. doi:10.1371/jounral.pone.0035527.
- Lahaut VM, Jansen HA, van de Mheen D, Garretsen HF, Verdurmen JE, van Dijk A. Estimating non-response bias in a survey on alcohol consumption: comparison of response waves. Alcohol Alcohol. 2003;38(2):128–134. doi:10.1093/alcalc/agg044.
- Boniface S, Scholes S, Shelton N, Connor J. Assessment of non-response bias in estimates of alcohol consumption: applying the continuum of resistance model in a general population survey in england. PLoS One. 2017;12(1):e0170892. doi:10.1371/journal.pone.0170892.
- Arentz S, Smith CA, Abbott JA, Bensoussan A. A survey of the use of complementary medicine by a self-selected community group of Australian women with polycystic ovary syndrome. BMC Complement Altern Med. 2014;14:472. doi:10.1186/1472-6882-14-472.
- CORE Institute. Benefits of utilizing CORE institute survey. http://core.siu.edu/benefits/index.php. Published 2017. Accessed August 31, 2017.
- Fisher CB, Fried AL, Anushko A. Development and validation of the college drinking influences survey. J Am Coll Health. 2007;56(3):217–230. doi:10.3200/JACH.56.3.217-230.
- Centers for Disease Control and Prevention. Alcohol and public health: frequently asked questions. https://www.cdc.gov/alcohol/faqs.htm. Published 2017. Accessed August 31, 2017.
- Thompson KM, Leinfelt FH, Smyth JM. Self-reported official trouble and official arrest: validating a piece of the core alcohol and drug survey. J Subst Use. 2006;11(1):23–26. doi:10.1080/14659890500114342.
- Schwartz S, Carpenter KM. The right answer for the wrong question: consequences of type III error for public health research. Am J Public Health. 1999;89(8):1175–1180. doi:10.2105/ajph.89.8.1175.
- United States Census Bureau. The digital divide: percentage of households by broadband internet subscription, computer type, race and Hispanic origin. https://www.census.gov/library/visualizations/2017/comm/internet.html. Published 2017. Accessed December 10, 2018.
- Anderson M. Digital divide persists even as lower-income americans make gains in tech adoption. http://www.pewresearch.org/fact-tank/2017/03/22/digital-divide-persists-even-as-lower-income-americans-make-gains-in-tech-adoption/. Published 2017. Accessed December 10, 2018.
- Tsetsi E, Rains SA. Smartphone Internet access and use: extending the digital divide and usage gap. Mob Media Com. 2017;5(3):239–255. doi:10.1177/2050157917708329.