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Researchers analyzed 436 on-line surveys collected between September and October 2019.  Chi Square analysis was conducted with p >.1 chance of statistical error to determine differences in group responses.

The Georgia’s Coast: Interest, Knowledge and Attitudes survey had a completion rate of 76% and an average response time of 16 minutes. The survey included incentives (raffle prizes and $5 donation made to an environmental organization) for completion. Invitations to participate were primarily sent through organizations that had an environmental focus but appeals to participants were also made to the larger public through media releases.

For the purposes of this report, the following categories were used to evaluate differences.

• Age: Younger = 34 and under; Middle= Between 35 and 49; Older = 50+
• Education: Lower= college degree, certificate or less; Higher = graduate degree
• Household Composition: No Children; With Children
• Gender: Female; Male
• Residence: Georgia Coastal (10 Counties); Georgia Mainland (146 Counties); Outside Georgia
• Political Leaning: Conservative; Moderate; Progressive/Liberal
• Socio-Economic Status: Lower = $39,999 or less; Middle = $40,000 – $99,999; Upper = $100,000+

Limits to Generalizability

Online surveys have distinctive features related to design, distribution and evaluation of data. Relevance of the survey topic has been shown to influence response rates (Groves et al, 2000), as has survey fatigue (Liu & Wronski, 2017; Porter, 2004b; Saxon et al, 2003), and even such factors as the focus of the study, the methods of contact, the methods of data collection, and the wording of the questionnaire title (Crawford, McCabe, & Pope, 2005; Dillman, 2000; Dillman & Frey, 1974; Dillman, & Smyth, 2007; Goyder, 1987; Hox & Deleeuw, 1994; Lund & Gram, 1998; Miller, 1991). Fan and Yan (2010) established five survey delivery elements affecting survey response rate. These elements are sample, delivery mode, invitation design, the use of pre-notification and reminders, and the use of incentives.

In general, more educated and more affluent people are more likely to participate in surveys than less educated and less affluent people (Curtin, Presser, and Singer, 2000; Goyder, Warriner, & Miller, 2002; Singer, van Hoewyk, & Maher, 2000). Women are more likely to participate than men (Curtin et al 2000; Moore & Tarnai, 2002; Singer et al 2000), white people are more likely to participate than non-white people (Curtin et al 2000; Groves, Singer, & Corning, 2000; Voight, Koepsell & Daling, 2003) and urban residents are more likely than rural (Reips, 2002).

Another influencer is that participants may not respond to questions accurately if they believe that their answer is not socially desirable (Crowne and Marlowe 1960; Silver, Anderson, and Abramson 1986). Also, progressive leaning respondents are much more likely to participate than conservatives and individuals from smaller households are more likely to participate than those from larger ones (Hargittai & Karaoglu, 2018).

Respondent Profile

The typical respondent to this online survey was a white, older female, living in one of Georgia’s largest urban coastal communities with advanced education and moderate to progressive political leanings. Respondents were more likely to be from a household without children and with an annual household income above $60,000.  While these attributes are not reflective of the entire population of the state of Georgia, they do closely mirror the population that participates in online surveys. This is especially true considering the focus being on interests, attitudes and knowledge regarding Georgia’s coast.