1. Factors associated with frequency of responding to electronic surveys among students attending a large minority-serving university: The Student Behavioral Health Survey (SBHS-Web)
Meredith L. Wilcox, MPH
Department of Epidemiology
William W. Darrow, PhD
Department of Health Promotion
Florida International University,
Miami, Florida, US

2. Presenter Disclosures Meredith L
Presenter Disclosures Meredith L. Wilcox (1) The following personal financial relationships with commercial interests relevant to this presentation existed during the past 12 months: No relationships to disclose

3. BACKGROUND
Electronic surveys have numerous advantages over traditional survey modes:
Fewer physical and financial resources
Reach a larger number of potential participants
Favorable for collecting data on sensitive topics
Overall, response to electronic surveys are estimated to be 11-20% lower than traditional survey modes.
Response higher among student-, employee-, military-populations
Response higher among non-Hispanic White and Asian students compared with their Hispanic and African American counterparts.
Participation in electronic surveys are influenced by society-, respondent-, and design-related factors.
AIM
Identify factors associated with history of responding to electronic surveys among student respondents of the Student Behavioral Health Survey (SBHS- Web) conducted in Spring 2013
- Primarily favorable for collecting data on sensitive topics owing to the confidentiality and anonymity offered to participants.
Favorable for surveying college students, a population that is readily available for sampling and that tends to have greater knowledge and access to technology than the general public
Society-related: population-type, with greater response among employee, student, and military populations
Respondent-related: age, gender, income, health status, computer resources, computer literacy
Design-related: Survey content, Length of survey and invitations, personalization of the s, use of pre-notification, number and frequency of s
This finding unfortunately is not consistent for college students of all demographics; African American and Hispanic students are notably less likely to complete electronic surveys than their White or Asian American counterparts.(Sutherland 2013; Fan 2010; Krebs 2010; Cranford, 2008; Krebs 2007) This disparity may be attributed to decreased availability of reliable technology at the universities serving minority students, or to historically low participation by minorities in health research.(Fan 2010; UyBico 2007)

4. Method of data collection
SBHS-Web
AIMS
Measure sensitive behaviors (sexual activity, use of drugs and alcohol) of the student population
Increase student response using 2-factor experimental design
MOTIVATION
The National College Health Assessment II (NCHA-II), a similar survey on sensitive topics, has been administered at the same university for the past few years as an online survey.
Year
Method of data collection
Response Rate
2004
Paper-based questionnaire
(NCHA)
40% of selected classes participated,
80% of students participated
2010
Online survey
5.7%
2011
7.0%
2012
5.0%
2013
3.5%

5. SBHS-Web METHODOLOGY Large, minority-serving, 4-year public university
- Student population ≈54,000
- 57% female; 61% Hispanic
10-day period in March-April 2013
8,000 student addresses randomly selected
Randomized into 4 groups of equal size
Invited to participate through
Pre-notification (select students), invitation , 3 reminder s at 48-hour intervals
No incentives were used

6. Pre-notification email
SBHS-Web
TREATMENT GROUPS
Pre-notification No
Yes
Improved design
Standard
(S)
pre-notification
(SP)
Innovative
(I)
(IP)
Pre-notification Sent 48 hours prior to the survey invitation
Innovative group: Increased personalization of notifications
Sender name
Subject lines of the
Logo of the sender
header
Closing of the

7. SBHS-Web IMPROVEMENTS IN EMAIL DESIGN Design element Standard
Innovative
Sender name
Survey Research Nine (SR-9)
Individual names of the SR-9 team members
subject line
“Introducing the SBHS-Web”
“Complete the SBHS-Web”
“Why don’t students respond?”
“What do you think?”
“Spam it’s not”
“Time is running out”
“Your last chance”
headers
“Adult online consent to participate in a research study”
“This is your opportunity!”
“We really want to know!”
“We still really want to know!”
Logo
University/college logo
Logo of SR-9 research team
Closing of s
“Thank you for taking time to complete this survey”
Name, signature, website of principle investigator;
Individual names of SR-9

8. SBHS-Web
Invitation

9. SBHS-Web Response rate of the SBHS-Web by treatment group–
2013 SBHS-Web, March-April 2013, Miami, Florida
*Response rate significantly lower than that of the IP group at p<0.001
Treatment group
Response
n (%)
Standard (S)
129 (6.5)*
Standard pre-notification (SP)
125 (6.3)*
Innovative (I)
98 (4.9)*
Innovative pre-notification (IP)
280 (14.0)
TOTAL
632 (7.9)

10. Frequency of responding to previous electronic surveys
SBHS-Web
Frequency of responding to previous electronic surveys sent by the university system, by treatment group– 2013 SBHS-Web, March-April 2013, Miami, Florida
Chi-squared, p<0.001
Treatment group
Frequency of responding to previous electronic surveys
Never/ rarely
(row %)
Sometimes
Usually/always
Standard (S)
25%
31%
44%
Standard pre-notification (SP)
30%
46%
23%
Innovative (I)
40%
Innovative pre-notification (IP)
38%
39%
TOTAL
33%
28%

11. AIM
Identify factors associated with history of responding to electronic surveys among student respondents of the Student Behavioral Health Survey (SBHS-Web) conducted in Spring 2013

12. Methodology STUDY OUTCOME
Frequency of responding to previous electronic surveys sent through university system
Never/rarely
Sometimes
Usually/always
STATISTICAL ANALYSIS
Association between outcome and factors: Chi-squared tests, logistic regression models
Two-tailed significance level of α≤0.05
SPSS version 19 (SPSS Inc., Chicago, IL)

13. RESULTS Demographics of student respondents (n=632)–
2013 SBHS-Web, March-April 2013, Miami, Florida
Characteristic %
Age (years), Median (range)
23 (18-60)
Gender, % female
60.1
Hispanic ethnicity
58.9
Marital status, Single
76.9
Employment, Employed full-time
22.3
Foreign-borne
42.6

14. RESULTS School-related characteristics of student respondents (n=632)–
2013 SBHS-Web, March-April 2013, Miami, Florida
Characteristic %
Class level
Undergraduate, 1st-2nd year
25.5
Undergraduate, 3rd year or higher
51.1
Graduate/Professional/other
23.4
Place of residence
On campus
7.8
Off campus alone or w/parents/family
61.6
Off campus w/partner or roommate, or other
30.7
Majority of classes taken at main campus
82.0
How often do you respond to electronic surveys sent through the university system?
Never/rarely
32.6
Sometimes
39.1
Usually/always
28.3

15. RESULTS Independent variables selected a prior
NOT associated with outcome (chi-squared, p>0.20)
Eliminated due to collinearity
Age in years X
Hispanic ethnicity
Gender
Marital status
Relationship status
Employment
Place of residence
Foreign-borne
Class level
Time of day of classes
Campus where majority of classes are taken
Member of fraternity/sorority/social club
Member of pre-professional/service/honor society
Frequency of opening survey invitations
sent by university system
Treatment group in SBHS-Web S

16. *Compared with usually/always responding
RESULTS
Odds of students never/rarely* responding to electronic surveys sent through the university system– 2013 SBHS-Web, March-April 2013, Miami, Florida
*Response rate significantly lower than that of the IP group at p<0.001
Unadjusted
Adjusted
OR (95% CI) p
Hispanic ethnicity
1.58 ( )
0.029
1.29 ( )
0.265
Male gender
1.81 ( )
0.006
2.03 ( )
0.002
Class level
Undergraduate, 1st-2nd year
1.49 ( )
0.172
1.51 ( )
0.215
Undergraduate, 3rd year+
2.40 ( )
0.001
2.42 ( )
Graduate/Professional/other
Ref.
---
Treatment group S SP
2.33 ( )
0.100
2.28 ( )
0.015 I
1.84 ( )
0.073
1.87 ( )
0.072 IP
2.95 ( )
<0.001
3.26 ( )
*Compared with usually/always responding
Adjusted for “place of residence” and “campus where majority of classes are taken”
OR=odds ratio; CI=confidence interval; S=standard; SP=standard pre-notification; I=innovative; IP=innovative pre-notification

17. *Compared with usually/always responding
RESULTS
Odds of students sometimes* responding to electronic surveys sent through the university system– 2013 SBHS-Web, March-April 2013, Miami, Florida
*Response rate significantly lower than that of the IP group at p<0.001
Unadjusted
Adjusted
OR (95% CI) p
Hispanic ethnicity
1.26 ( )
0.248
1.00 ( )
0.999
Male gender
1.57 ( )
0.029
1.61 ( )
0.027
Class level
Undergraduate, 1st-2nd year
1.14 ( )
0.636
1.31 ( )
0.379
Undergraduate, 3rd year+
1.78 ( )
0.016
1.78 ( )
Graduate/Professional/other
Ref.
---
Treatment group S SP
2.85 ( )
0.001
2.96 ( ) I
1.92 ( )
0.042
1.95 ( )
0.040 IP
2.45 ( )
2.61 ( )
<0.001
*Compared with usually/always responding
Adjusted for “place of residence” and “campus where majority of classes are taken”
OR=odds ratio; CI=confidence interval; S=standard; SP=standard pre-notification; I=innovative; IP=innovative pre-notification

18. Strengths & Limitations
SBHS-Web was anonymous and confidential
Students were randomized into treatment groups
Large sample overall and within each treatment group
Many demographic and school-related variables available
LIMITATIONS
All data self-reported
Data not available for non-responders
Difficulties in implementing survey may have affected response within certain treatment groups
Timing of the survey may have affected response
Some factors associated with frequency of responding were not available

19. Summary
Low response to previous electronic surveys sent by the university was more prevalent within the treatment groups that received the pre- notifications and/or improved design.
After adjusting for other covariates, the odds of infrequently responding to previous electronic surveys sent by the university were significantly higher among students in the SP, I, and IP groups compared with those in the S group.
This suggests that improved design of notifications and use of pre-notification may be promising methods of increasing response among students who infrequently respond to electronic surveys.
Public health implications: Reduce bias in student response to electronic surveys collected using electronic surveys.

20. Thank You