Suggestions for Data Collection at Outdoor Recreation Sites

Introduction

Response rate is a major issue in survey research. Low response rates can result in data that fail to represent the population of interest because the nonresponse is usually not random (Porter, 2004). In other words, " Low response rates raise concerns that members of the target population that return completed questionnaires differ systematically from those who do not return completed questionnaires" (Russell, Verhoef, Injeyan, & McMorland, 2004, p. 43). In our culture of increased security and privacy protection, the problem of low response rates appears to be increasing rather than improving (Porter, 2004; Russell et al., 2004).

Therefore, it is important that data collectors make appropriate and suitable attempts to gain the cooperation of potential respondents. Data collectors should understand that they are a vital part of the research process and that the decisions that they make regarding how to collect data through the administration of face-to-face questionnaires can have considerable impact on the conclusions that analysts will draw from the data. This mini-guide to collecting survey data will provide a brief theoretical explanation for why individuals choose to participate in a study or not and will provide practical advice for gaining the cooperation of respondents.

Why Would Someone Agree to Complete a Questionnaire?

There are many possible reasons that someone might consent to complete a questionnaire, but two broad theoretical frameworks can be used to explain many of these decisions. We can think of those two frameworks as reasoned action and a dependence on heuristics (Porter, 2004). I will provide a brief explanation for each of these.

According to Dillman (2000), social exchange theory offers a suitable explanation for the reasoned action framework. Social exchange theory assumes that individuals make rational decisions to maximize benefits (Emerson, 1976; Searle, 1991) and that individuals can evaluate the payoffs of social interactions and make rational decisions regarding the consequences of participation in a relationship (Griffin, 2000).

When applied to survey data collection, this theory suggests that potential respondents might engage in a hasty cost-benefit analysis while the data collector asks for participation. If the potential respondent is not convinced of the benefit to him or her, then no reason is established to continue with the relationship, and the data collector might not achieve the cooperation of the respondent. Therefore, in an attempt to address the rational decision-making process of social exchange, a data collector might offer some explanation or rationale for the survey. Along with this, the data collector should be prepared to discuss the study's role in the allocation of resources and formation of policies that will affect the recreation site that is important to the respondent.

Heuristics represent a second framework. Heuristics are simple rules of thumb that guide our behavior. This phenomenon often occurs beneath our conscious thought, but can yield considerable influence over our decision making (McCammon, 2004; Clement, 1997). As an explanation for survey response, this psychological approach amounts to normative behaviors such as helping others and/or complying with authority.

Researchers have studied the problem of response rates through the lens of heuristics and have learned valuable information about what works and what does not. Because individuals may respond to heuristics associated with normative behaviors, simple, well-articulated requests for help can increase response rates (Mowen & Cialdini, 1980). Likewise, explaining sponsorship of an academic or government agency can establish credibility and informs the potential respondent that the survey is being conducted by an authority (Fox, Crask, & Kim, 1988).

On the other hand, data collectors should be aware that they could hinder response rates by overstating that respondents' confidentially will be maintained. Most on-site recreation surveys do not ask for sensitive, personal information. It can be counterproductive when the survey does not ask for sensitive information to overstate the fact that the respondent will not be identifiable and that her or his confidentiality will be maintained (Porter, 2004). Instead, a simple phrase stating that the survey does not ask for any sensitive, personal information may be sufficient.

The distinction between the reasoned action and heuristics approach does not suggest that they are mutually exclusive. These two explanations for participation may work in concert with one another. The following suggestions for on-site data collection offer an integrated application of these two theoretical frameworks.

Groves, Singer, and Corning (2000) recognized the influence of heuristics and, in response, suggested that data-collectors "tailor" their approach to each respondent. For example, are you approaching a local landowner? If so, this person might respond to the norm of civic duty over other heuristics. A clear, succinct explanation of the study and how it relates to the landowner could be effective in this case. Groves and colleagues referred to this as " leverage-salience theory" because the data collector is leveraging the feature of the survey that is most salient to the potential respondent. This same example could also engage the reasoned action explanation if the landowner is convinced that she or he has something to gain by participating.

Therefore, it is important that data collectors are familiar with all aspects of the study. Improper training of data collectors can result in biased data (Henderson & Bialeschki, 2002). Know why the study is being conducted, understand the issues related to the study and the local area from ALL perspectives, know who the stakeholders are, and be familiar with the sponsors of the study. This groundwork will provide the knowledge and mastery of the project that is necessary to respond to unforeseeable situations that are likely to occur in the field. Likewise, intimate familiarity with the study and associated rationale may support efforts to enact the conceptual ideas explained above.

Logistical Concerns

Carefully review and understand the sampling plan of the study. The goal of the sampling plan is to establish a framework that will guide the collection of data from a random sample of the population of visitors. The sampling plan will outline a systematic strategy that includes sampling design, timing, and the location in which data collectors will approach respondents (Watson, Cole, Turner, & Reynolds, 2000). Attend to these details because they are important features of every study and will effect the conclusions drawn from the data.

Be organized. Make careful field notes of where and when you collected the survey information. Include the date, time, location, and name of the data collector on each survey. There should be no questions about where, how, or when the data was collected. Take responsibility for a high level of organization and excellent record keeping in this regard. Record additional observations through the use of field notes. Document the response rate. Keep field notes about your data collection experience and indicate if one technique of gaining consent was more productive than another.

Summary

This mini-training guide has offered a brief theoretical explanation for why respondents might choose to participate in a study. It has also offered specific suggestions that data collectors might consider when entering the field. The quality of a study depends upon accurate response rates, and professional, well-prepared data collectors are a critical aspect of study design and implementation.

References

Clement, K. (1997). The psychology of judgment for outdoor leaders. Proceedings of the International Conference on Outdoor Recreation and Education.

Dillman, D. A. (2000). Mail and Internet surveys (2nd Ed.). NY: John Wiley & Sons.

Emerson, R. M. (1976). Social exchange theory. Annual Review of Sociology, 2, 335-362.

Fox, R. J., Crask, M. R., & Kim, J. (1988). Mail survey response rate: A meta-analysis of selected techniques for inducing response. Public Opinion Quarterly, 66(3), 608-617.

Griffin, E. (2000). A first look at communication theory (4th ed.). Boston, MA: McGraw-Hill.

Groves, R. M., Singer, E., & Corning, A. (2000). Leverage-salience theory of survey participation: Description and illustration. Public Opinion Quarterly, 64, 299-308.

Henderson K. A., & Bialeschki, D. M. (2002). Evaluating leisure services: Making enlightened decisions (2nd Ed.). State College, PA: Venture.

McCammon, I. (2004). Heuristic traps in recreational avalanche accidents: evidence and implications. Avalanche News, 68, 1-10.

Mowen J. C., & Cialdini, R. B. (1980). On implememting the door-in-the-face compliance technique in a business context. Journal of Marketing Research, 17, 253-258.

Porter, S. R. (2004). Raising response rates: What works? New Directions for Institutional Research, 121, 5-21.

Russell, M. L., Verhoef, M. J., Injeyan, H. S., & McMorland, D. G. (2004). Response rates for surveys of chiropractors. Journal of Manipulative and physiological Therapeutics, January, 43-48.

Searle, M. S. (1991). Propositions for testing social exchange theory in the context of ceasing leisure participation. Leisure Science, 13, 279-294.

Watson, A. E., Cole, D. N., Turner, D. L., & Reynolds, P. S. (2000). Wilderness recreation use estimation: A handbook of methods and systems. United States Department of Agriculture, Rocky Mountain Research Station. General Technical Report RMRS-GTR-56.