The Revolution Will Be Hard to Evaluate: How Co-Occurring Policy Changes Affect Research on the Health Effects of Social Policies.
The Revolution Will Be Hard to Evaluate: How Co-Occurring Policy Changes Affect Research on the Health Effects of Social Policies.
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DOI：
10.1093/epirev/mxab009
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发表时间：
2022-01-14
影响因子：
5.5
通讯作者：
Glymour MM
中科院分区：
文献类型：
--
作者：
Matthay EC;Hagan E;Joshi S;Tan ML;Vlahov D;Adler N;Glymour MM
广泛的经验性健康研究利用政策变化的时机和地点的差异作为准实验。可以在同一地点同时采用多个社会政策，从而创建必须通过分析解决的共同发生，以便进行有效的推断。共生政策的普及性和后果受到的关注有限。我们分析了涵盖贫困、带薪家庭假和烟草使用等不同领域的13个社会政策数据库的系统样本。我们将每个数据库中的策略同时出现量化为每个策略度量在不同司法管辖区和时间之间的差异比例，这可以通过与其他策略的协变来解释。我们使用模拟来估计在观察到的策略共同出现下的效果估计的方差与策略独立时的方差的比率。政策同时出现的情况从国家一级的大麻政策很高到国家一级的性少数权利政策很低不等。对于65%的政策，超过90%的地点-时间差异是由其他政策解释的。政策的共同出现使效果估计的方差增加了57倍。共同发生的政策很常见，对严格评估个别社会政策的健康影响构成了重大的方法学挑战。当不受控制时，同时发生的政策相互混淆，而当受到控制时，由此产生的积极违规可能会极大地夸大估计效果的差异。需要工具来提高评估共生政策的有效性和精确度。
Extensive empirical health research leverages variation in the timing and location of policy changes as quasi-experiments. Multiple social policies may be adopted simultaneously in the same locations, creating co-occurrence that must be addressed analytically for valid inferences. The pervasiveness and consequences of co-occurring policies have received limited attention. We analyzed a systematic sample of 13 social policy databases covering diverse domains including poverty, paid family leave, and tobacco use. We quantified policy co-occurrence in each database as the fraction of variation in each policy measure across different jurisdictions and times that could be explained by covariation with other policies. We used simulations to estimate the ratio of the variance of effect estimates under the observed policy co-occurrence to variance if policies were independent. Policy co-occurrence ranged from very high for state-level cannabis policies to low for country-level sexual minority-rights policies. For 65% of policies, greater than 90% of the place-time variation was explained by other policies. Policy co-occurrence increased the variance of effect estimates by a median of 57-fold. Co-occurring policies are common and pose a major methodological challenge to rigorously evaluating health effects of individual social policies. When uncontrolled, co-occurring policies confound one another, and when controlled, resulting positivity violations may substantially inflate the variance of estimated effects. Tools to enhance validity and precision for evaluating co-occurring policies are needed.
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