The Use of Online Survey Software for Psychology Research Data Collection: Overview of Issues and an Example

Grant Heller, M.A., M.S., and Ph.D. Barry Dauphin

Introduction

The following presentation explores issues with conducting survey research online, and uses an online study as an example. As a field, psychology has often benefited from survey research. This has traditionally been conducted by paper and pencil measures. However, online research is able to address many limitations of traditional surveys including: 1.) Coding and data entry errors, 2.) Incomplete surveys or missed items, 3.) Interpretation of illegible items, 4.) Expense of photocopying, 5.) Waste of unused surveys, 6.) Physical storage of completed surveys. Further, posting surveys online allows for a much broader geographic sample, as well as allowing for an increased sample size. Some of these survey tools are available online free for students or offer significant academic discounts, and thus are a powerful and economical tool for assisting in conducting survey research.

Method

Participants. 254 (n = 116 males) participants completed the questionnaire. The sample was primarily Caucasian (n = 189). Ages ranged from 18 to 63 years. Participants were recruited from online repositories hosting psychology research studies, through online ads for volunteers, social networking sites, and through the UDM psychology participant pool.

Measure. The Videogaming Experiences Questionnaire – Revised (VEQ-R) consisted of 22 items aimed at assessing level of involvement in VG, level of realism in games played, preferred level of aggressive content in games played, as well as sources of benefit and interference from VG. The questionnaire was administered through Surveygizmo, an online software program for creating and hosting surveys.

Results

Survey results were factor analyzed (PAF extraction) with Varimax rotation. Results suggest a five factor solution accounting for 52% of the variance. Internal consistency was high (Cronbach’s α = .895). The five factors include: 1.) VG Perceived interference (related to work/school, emotional well-being, relationships, etc.), 2.) VG Perceived Benefits (related to work/school, emotional well-being, relationships, etc.), 3.) VG Intensity (preferring 1st person games, violent content, realistic games), 4.) VG Engagement (excitement, feeling engaged or immersed), and 5.) VG Frequency (frequency of play, increased recent involvement).

Participants represented a much wider geographical dispersion than a typical university participant pool survey. Nonstudent participants completed the survey on a volunteer basis. Online survey collection increased N more quickly, thus contributing to improved psychometrics of the instrument.

 

Conclusion

Scale revision of the VEQ resulted in 5 factors associated with VG. Issues of sampling were improved from the previous measure, and internal consistency was increased. Future studies seek to further improve psychometric properties of the scale and cross-validate it with other measures. Overall, conducting the study online allowed for significant improvements in sampling, decreased cost, and increased research efficiency.

This research was supported by a 2009-10 UDM Mellon Grant to Barry Dauphin, Ph.D.