Effect of Wireless Substitution in a NJ Health Care Opinion Poll

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Effect of Wireless Substitution in a NJ Health Care Opinion Poll January 13, 2009 SHADAC Workshop Current Issues in Survey Methods for State Health Surveys Washington, DC Joel Cantor*,^, Susan Brownlee*, and Cliff Zukin^ * ^Edward J. Bloustein School of Planning and Public Policy Funded by a grant from the Robert Wood Johnson Foundation

NJ Health Care Opinion Poll Design (1) Purpose: Gauge concerns about health care issues and support for reform in NJ Field period: June 1 to July 9, 2007 Questions: Drawn from prior national and state polls, when possible Interviews: English and Spanish Calling design: Up to 18 contact attempts Incentives: $10 for wireless respondents Length: 20.2 min (landline) & 22.8 min (wireless) 2

NJ Health Care Opinion Poll Design (2) Final sample: 1,104 adults total 804 landline 300 wireless wireless only (197) and wireless mainly (103) Response rate (AAPOR RR-3) 34.4% (landline) & 36.2% (wireless) Weights Probability of selection NHIS Northeastern US wireless-only (trended) Extrapolate from our screener for wireless mainly incidence Post-hoc adjustment to Census distributions (age, sex, education) 3

Wireless Screening Strategy In addition to having a cell phone, do you also have at least one land line phone in your house at which you or anyone else in the household NORMALLY receive in-coming phone calls? IF YES: Please do not include modem only lines, fax only lines, lines used just for a home security system, beepers, pagers, or the cell phone. (IF YES) Thinking just about the land line home phone, NOT your cell phone, if that telephone rang, and someone was home, under normal circumstances how likely would it be answered? Would you say: Extremely likely Very likely Somewhat likely Somewhat unlikely Not at all likely Screen Out Wireless Mainly Sample 4

Analysis Estimate of wireless-only and wireless-mainly populations Landline-wireless differences in 81 variables 78 interview questions Region, urban location, language of interview Multivariate analysis of support for three coverage reforms (with bivariate landline-wireless difference at p<0.01) Model 1 Unadjusted Model 2 Adjusted for socio-demographic variables (selected using backward-elimination stepwise regression) Model 3 Adjusted for socio-demographic variables plus health status and coverage variables (selected the same way) 5

Estimated Population Size by Wireless Status 100% 5.4% 14.0% 17.3% 80% 14.4% Wireless Mainly/Mostly 77.3% 71.6% Wireless Only 60% Landline 40% 20% 0% Wireless Mainly Somewhat Unlikely or Not At All Likely to Answer Landline CSHP NJ Poll June-July '07 Wireless Mostly All or Most Calls Received on Cell Phones NHIS US July-Dec '07* *Blumberg and Luke, Wireless Substitution: Early Release of Estimates from the National Health Interview Survey. July-December 2007. National Center for Health Statistics, May 13, 2008. 6

Percentage of Variables With Differences Between Landline and Wireless Respondents by Level of Significance and Survey Domain Other Health Reforms (10) p<.001 p<.01 p<.05 Health Issue Worry (7) Priorities for Reform (14) Coverage Reforms (12) Need for & Following Reform (7) General Issue Worry (7) Own Health, Cost & Coverage (8) Socio-Demograhics (16) 0% 20% 40% 60% 80% 100% Note: Number of variables in each domain shown in parentheses. 7

Patterns of Bivariate Differences Demographics, SES, coverage same as NHIS Health status wireless more likely to report excellent and fair self-assessed health Health coverage reforms (p<0.01) Favor expanding public programs +1.8% points in combined sample vs. landline only No difference when if it meant higher taxes added Strongly favor individual coverage mandate +2.7% points in combined sample vs. landline only Favor state subsidies for low-income uninsured +2.4% points in combined sample vs. landline only Few wireless-only vs. wireless-mainly differences Little power 8

Unadjusted and Adjusted Relative Odds of Support for Selected Reforms by Landline-Wireless Status Odds Ratio Expand Public Coverage Individual Mandate Subsidies for Low-Income Uninsured Model 1: Unadjusted 1.89 (1.17-3.07) 1.65 (1.13-2.42) 1.70 (1.22-2.38) Model 2: Adjusted for sociodemographic differences 1.55 (0.94-2.56) 1.86 (1.21-2.84) 1.55 (1.10-2.19) Model 3: Adjusted for sociodemographic, coverage, & health differences 1.31 (0.78-2.21) 1.67 (1.04-2.53) 1.62 (1.14-2.29) Note: Significant odds ratios shown in bold. 9

Conclusions Adding wireless sample to a state poll is feasible Our wireless-mainly smaller than NHIS wirelessmostly Differences in demographics, SES, & coverage consistent with prior research Not sure what to make of self-assessed health difference Modest but significant bias observed in support for key health coverage reforms Two of three remain significant after controlling for population differences These differences and continuing growth of wireless substitution (17% growth in 6 mo.) suggest including wireless sample is prudent 10