Using Telephone Survey Data to Predict Participation in an. Internet Panel Survey

Transcription

1 Using Telephone Survey Data to Predict Participation in an Internet Panel Survey David J. Roe, Jason Stockdale, Matthew Farrelly, Todd Heinrich RTI International May 18, 2007 RTI International is a trade name of Research Triangle Institute 3040 Cornwallis Road P.O. Box Research Triangle Park, North Carolina, USA Phone Fax droe@rti.org 1

2 Overview Introduction Research Questions Study Background Bivariate Results Regression Results Conclusions Directions for Future Research 2

3 Introduction As declines in telephone response rates continue, the need for flexible data collection strategies adaptable to a rapidly changing environment is clear Despite reservations regarding general population surveys on the web, internet surveys have become a useful data collection strategy for collecting data from longitudinal panels and list samples: absence of interviewer bias, convenience, lower costs, use of multimedia 3

4 Study Background Healthy Youth Panel Survey (HYPS) National survey of youth aged Measures issues related to tobacco advertising, tobacco use and physical health Web follow-up with youth who have continued to participate over the past few years with a telephone version of the interview Seven week pilot project was conducted to gain insight into collecting data from youth on-line 4

5 Why Move HYPS to the web? Youth today live in a very media rich environment Surveying youth is increasingly difficult School surveys are burdensome and facing increased resistance Finally, telephone surveys are becoming increasingly difficult to conduct with youth and are expensive Challenging to reach the target sample because of their relatively low incidence in the population Also known to underreport smoking rates compared to school based surveys 5

6 Making the Move After completing two longitudinal telephone surveys, 84% (N=807) of respondents agreed to participate in an Internet Panel Despite this apparent interest, we were only able to complete on-line interviews with approximately 54% (N=433) of respondents who expressed interest 6

7 Research Questions Are responses to items in the telephone survey significant predictors of participation in the web survey? Did demographic variables such as age, race, education and parental influence and oversight play a role in limiting participation? Are there relationships between a respondent s perceived ability to use the internet and their participation in the web survey? 7

8 Bivariate Results % Willing to Participate in Web Panel % Who Completed Web Survey Age

9 Bivariate Results, Ctd. % Willing to Participate in Web Panel % Who Completed Web Survey Gender Male Female 87.4** 81.2** 59.3*** 47.9*** ** Difference between categories is significant at p <.01 based on Chi-Square tests *** Difference between categories is significant at p <.001 based on Chi-Square tests 9

10 Bivariate Results, Ctd. Race White African American Hispanic Other % Willing to Participate in Web Panel % Who Completed Web Survey

11 Bivariate Results, Ctd. Education No High School Some High School HS Grad or GED Some College College Grad % Willing to Participate in Web Panel 76.7** 83.0** 83.3** 93.8** 100** % Who Completed Web Survey ** Difference between categories is significant at p <.01 based on Chi-Square tests 11

12 Bivariate Results, Ctd. School Performance Much Better or Better than Average Average Worse or Much Worse than Average % Willing to Participate in Web Panel 88.5*** 76.7*** 68.3*** % Who Completed Web Survey 59.2*** 40.1*** 42.9*** *** Difference between categories is significant at p <.001 based on Chi-Square tests 12

13 Bivariate Results, Ctd. Other Variables Enrolled in School Lives with Both Parents Regularly Attend Religious Service Have a Bedroom to Oneself Smoked in the Past 30 days Employed Full or Part Time % Willing to Participate in Web Panel 85.7*** 87.8** * 77.1* 85.1 % Who Completed Web Survey * Born in U.S *** Significant at p <.001, ** Significant at p<.01, * Significant at p<.05 13

14 Bivariate Results, Ctd. Computer/Internet Access Variables Have Own Personal Computer & Internet Use a PC Anywhere Go Online for or Internet Online at Least Once a Day Use a High Speed Connection % Willing to Participate in Web Panel 87.7*** 85.6*** 88.4*** 91.1*** 88.7 % Who Completed Web Survey ** 53.7 ** Difference between categories is significant at p <.01 based on Chi-Square tests *** Difference between categories is significant at p <.001 based on Chi-Square tests 14

15 Bivariate Results, Ctd. Where Online Most Often? Home School Work Someplace Else % Willing to Participate in Web Panel % Who Completed Web Survey

16 Regression Results Willing to Participate Completed Age (compare to 15 to 17) 13 to 14 Year Olds 18 to 20 Year Olds Male 1.64* 1.64** Race (compare to White, Non Hispanic) African American, Non Hispanic Hispanic Other Race Non-Hispanic Born in US ** Significant at p<.01, * Significant at p<.05 16

17 Regression Results, Ctd. Willing to Participate Completed Enrolled in School School Performance (compare to Average) Much Better or Better Much Worse or Worse 1.85** ** 1.03 No High School (0-8) Education (compare to HS Grad or GED) Some High School (9-11) Some College or Technical School College Graduate or Higher Missing Education 0.14 ** Significant at p<.01, * Significant at p<.05 17

18 Regression Results, Ctd. Employed for Wages Willing to Participate 0.97 Completed 1.25 Weekly Wages Earned * Smoked in Past 30 Days Lives with Both Parents ** Attends Church Regularly Has a Bedroom to Oneself ** Significant at p<.01, * Significant at p<.05 18

19 Regression Results, Ctd. Personal Computer (not used by others) Use a PC at Home, School, Anywhere Else Go Online to Access the Internet or to Willing to Participate ** Completed Go Online at Least Once Daily 1.99** 1.35 Use a High-Speed Connection ** Significant at p<.01, * Significant at p<.05 19

20 Regression Results, Ctd. Willing to Participate Completed Where Online (compared to Home) Where Online: School Where Online: Work Where Online: Other ** Significant at p<.01, * Significant at p<.05 20

21 Conclusions Many more apparently significant factors when it comes to willingness to complete Demographics Parental influence and lifestyle Computers/internet access Many significant relationships fall away when control for other factors is applied Completion, for the most part, seems to be random 21

22 Directions for Future research Explore other operational factors Time of year Panel burnout Contact methods Focus on the significant differences that do remain Explore providing equipment or access to increase willingness Explore increasing incentives for completion 22

23 Contact Information Thank You! David Roe