Gridlocked: The impact of adapting survey grids for smartphones. Ashley Richards 1, Rebecca Powell 1, Joe Murphy 1, Shengchao Yu 2, Mai Nguyen 1

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Gridlocked: The impact of adapting survey grids for smartphones Ashley Richards 1, Rebecca Powell 1, Joe Murphy 1, Shengchao Yu 2, Mai Nguyen 1 1 RTI International 2 New York City Department of Health & Mental Hygiene 1 RTI International is a registered trademark and a trade name of Research Triangle Institute. www.rti.org

What is a grid? 2

Grids avoid repetition. 3

Grids display poorly on small screens, esp. smartphones. 4

Presentation Outline Summarize the literature on grids Suggest a modified grid format that displays better on small screens Review findings from comparison of modified versus traditional grid format Indicators of data quality: missing data, straight-lining, etc. 5

What do we know about grids? (1/2) Inter-item correlations / straight-lining Higher in grids Significantly higher (Tourangeau, Couper, & Conrad, 2004) Modest effect (Couper, Traugott, & Lamias, 2001; Toepoel, Das, & Van Soest, 2009) No effect (Yan, 2005; Callegaro, Shand-Lubbers, & Dennis, 2009) Missing data Higher in grids (Iglesias, Bir, & Torgerson, 2001; Toepoel, Das, & van Soest, 2009) Lower in grids (Couper, Traugott, & Lamias, 2001) 6

What do we know about grids? (2/2) Survey completion time Faster in grids (Couper, Tourangeau, Conrad, & Zhang, 2013; Couper, Traugott, & Lamias, 2001; Tourangeau, Couper, & Conrad, 2004) Seems to be due to an increase in measurement error (Peytchev, 2005) Respondents evaluation of the questionnaire Less favorable when grids are used (Toepoel, Das, & van Soest, 2009) Display Poor on small screens (e.g. Link et al., 2014) 7

If you are conducting online surveys, you are conducting mobile surveys. -Link, Murphy, Schober, et al. (2014) 8

Smartphone Ownership Over Time 70% 60% 50% 40% 30% 20% 10% 0% Feb-11 Sep-11 Apr-12 Oct-12 May-13 Nov-13 Jun-14 Dec-14 9 Pew Research Center (2015)

By choosing to use [grid] question formats, the survey designers trade data quality for space efficiency. -Dillman, Smyth, & Christian (2014) 10

Justifying the use of Grids Sometimes grids cannot be avoided: Longitudinal studies (compare data to earlier waves) Mail surveys (space constraints) Multi-mode surveys (compare findings across modes) 11

World Trade Center Health Registry Established 2002 Monitor long-term physical and mental health of people exposed to 9/11 Assess post-disaster needs Wave 4 survey: launched April 2015 Wave 1 Wave 2 Wave 3 Wave 4 Year(s) 2003-2004 2006-2007 2011-2012 2015 Sample Size 71,437 68,959 67,670 67,480 Modes CATI CAPI CATI Web Mail CATI Web Mail Web Mail Response Rate 59% 68% 63% TBD Retained 5 grids for better comparison to Wave 3 grid data and to save space in the mail mode 12

Modifying grids for mobile respondents Used responsive web design Screen width automatically detected If < 760 px, display stacked format If 760 px, display traditional format Stacked format displays each item above the response options to save space 13

Traditional vs. Stacked Format Traditional Stacked 14

Research Purpose Do the stacked and traditional formats result in differences in data quality? We examined: Response distributions Missing data Straight-lining Inconsistent responses 15

Methods Used preliminary data: 4,358 Web respondents through first 4 weeks of data collection 92% completed survey on large screen (computer or large tablet); 8% on small screen (smartphone) Respondent characteristics: Avg. age 55 63% male 62% Bachelor s degree or higher Smartphone respondents: Slightly younger Less educated Both differences statistically significant Used predicted probabilities from models that controlled for age, sex, education 16

Response Distributions Clear pattern of stacked respondents choosing more negative response in 4 of 5 grids No discernible pattern in 5 th grid 17

PTSD Average Response Selected by Item & Format 18 *p <.05

Depression Symptoms Average Response Selected by Item & Format 19 *p <.05

Psychological Distress Symptoms Average Response Selected by Item & Format 20 *p <.05

Availability of Social Support Average Response Selected by Item & Format 21 *p <.05

Diagnosed Health Conditions Average Response Selected by Item & Format 22 *p <.05

Skipping 1+ Items: Predicted Probability by Grid & Format 23 *p <.05

Skipping Entire Grid: Predicted Probability by Grid & Format 24 *p <.05

Straight-Lining: Predicted Probability by Grid & Format Straight-lining: selecting same response for all items 25 *p <.05

Inconsistent Responses Wave 3 and Wave 4 surveys both contained a grid asking about lifetime diagnosis of medical conditions. Respondents who indicated they had a condition were then asked for year of diagnosis Any condition diagnosed in 2010 or earlier should have been reported in Wave 3 and Wave 4. Looked at average # of conditions with discrepancies across waves Average: ~1.5 discrepancies per respondent No statistically significant differences for stacked vs. traditional grid formats 26

Summary Grids have both advantages and disadvantages We kept grids in our survey to make longitudinal comparisons Respondents will utilize option to respond via smartphone Must modify grids to work on small screens But must do so without introducing mode/device effects Stacked format: good compromise No consistent evidence of decreased data quality Some evidence of increased data quality Stacked format may be a good option for all devices 27

More Information Ashley Richards Survey Methodologist ashrichards@rti.org 28

References (1/2) Callegaro, M., Shand-Lubbers, J., & Dennis, J. M. (2009). Presentation of a single item versus a grid: Effects on the vitality and mental health subscales of the sf-36v2 health surveys. Paper presented at the annual meeting of the American Association for Public Opinion Research, Hollywood, FL. Couper, M. P., Tourangeau, R., Conrad, F.G., & Zhang, C. (2013). The design of grids in web surveys. Social Science Computer Review, 31, 322-345. Couper, M. P., Traugott, M., & Lamias, M. (2001). Web survey design and administration. Public Opinion Quarterly, 65, 230-253. Dillman, D.A., Smyth, J. D., & Christian, L. M. (2014). Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method. Hoboken, NJ: John Wiley & Sons. Iglesias, C. P., Birks, Y. F., & Torgerson, D. J. (2001). Improving the measurement of quality of life in older people: The York SF-12. Quarterly Journal of Medicine, 94, 695-698. 29

References (2/2) Link, M. W., Murphy, J., Schober, M. F., Buskirk, T. D., Childs, J. H., Tesfaye, C. L. (2014). Mobile technologies for conducting, augmenting, and potentially replacing surveys: Report of the AAPOR Task Force on Emerging Technologies in Public Opinion Research. Available at https://www.aapor.org/aaporkentico/aapor_ Main/media/MainSiteFiles/REVISED_Mobile_Technology_Report_Final_revi sed10june14.pdf Pew Research Center (2015). Device ownership over time. Retrieved April 26, 2015 from http://www.pewinternet.org/data-trend/mobile/deviceownership/ Toepoel, Das, & Van Soest (2009). Design of web questionnaires: The effects of the number of items per screen. Field Methods, 21, 200-213. Tourangeau, R., Couper, M. P., & Conrad, F. G. (2004). Spacing, position, and order: Interpretive heuristics for visual features of survey questions. Public Opinion Quarterly, 68, 368-393. Yan, T. (2005). Gricean effects in self-administered surveys. College Park, MD: University of Maryland, unpublished doctoral dissertation. 30