Facts versus values: why legislators vote against injury control laws
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Updated: Nov 8, 2026

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Published on: September 21, 2017
S R Lowenstein1, J Koziol-McLain, G Satterfield
1Colorado Emergency Medicine Research Center, University of Colorado Health Sciences Center, Denver 80262.
Background:
Control of motor vehicle-related injuries depends upon passage of mandatory safety belt and other injury control laws. Unfortunately, state legislators often oppose these laws.
Methods:
In 1988, a 62-item questionnaire was mailed to the 97 Colorado legislators who voted on a 1987 safety belt law to identify factors (knowledge, experiences, attitudes, and beliefs) associated with "yes" and "no" votes. To test for associations between these attributes and the legislators' recorded votes, odds ratios (OR) and 95% confidence intervals (CIs) were calculated. A stepwise logistic regression identified independent predictors of "vote."
Results:
Fifty-three (55%) of the legislators responded. Responders and nonresponders were demographically similar. "Vote" was not associated with age; sex; having young children in the family; perceived injury risk; recent traffic tickets; family or personal crash experience; or knowledge of the fatality risk reductions attributable to wearing safety belts. Ninety-six percent of the legislators knew that safety belts reduce the risk of death and 87% believed a safety belt law would save lives. The strongest predictors of a "yes" vote were impression that constituents favored the law (OR = 31, CI 95 = 3.5, 270); belief that a mandatory safety belt law will save lives (OR = 20, CI 95 = 2.1, 203); and "extreme" importance paid in the voting decision to effectiveness of the law in reducing deaths (OR = 19, CI 95 = 3.5, 107). Legislators who considered restrictions on individual freedoms an "extremely" important decision criterion were 43 times (CI 95 = 7, 267) more likely to vote "no." In the logistic model only extreme importance assigned to individual freedoms (beta = 3.7; OR = .025; p = 0.002) and policy effectiveness (beta = +3.1; OR = 22; p = 0.01) predicted "vote." The logistic model correctly predicted 90% of legislators' votes.
Conclusions:
In this study the strongest predictors of voting behavior were concern for individual freedoms, perceived constituents' support and attention paid to policy effectiveness. Those seeking to persuade legislators to vote for mandatory safety belt laws must pay attention to attitudes and values in addition to scientific facts.
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