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不同求职信内容和激励措施对申请退伍军人事务部残疾福利的退伍军人样本中无应答偏倚的影响:一项随机、3X2X2 析因试验。

Impact of different cover letter content and incentives on non-response bias in a sample of Veterans applying for Department of Veterans Affairs disability benefits: a randomized, 3X2X2 factorial trial.

机构信息

Section of General Internal Medicine, Minneapolis VA Health Care System, One Veterans Drive (111-0), Minneapolis, MN, 55417, USA.

Center for Care Delivery and Outcomes Research, Minneapolis VA Health Care System, One Veterans Drive (152), Minneapolis, MN, 55417, USA.

出版信息

BMC Med Res Methodol. 2022 Mar 6;22(1):61. doi: 10.1186/s12874-022-01531-x.

Abstract

BACKGROUND

Non-random non-response bias in surveys requires time-consuming, complicated, post-survey analyses. Our goal was to see if modifying cover letter information would prevent non-random non-response bias altogether. Our secondary goal tested whether larger incentives would reduce non-response bias.

METHODS

A mailed, survey of 480 male and 480 female, nationally representative, Operations Enduring Freedom, Iraqi Freedom, or New Dawn (OEF/OIF/OND) Veterans applying for Department of Veterans Affairs (VA) disability benefits for posttraumatic stress disorder (PTSD). Cover letters conveyed different information about the survey's topics (combat, unwanted sexual attention, or lifetime and military experiences), how Veterans' names had been selected (list of OEF/OIF/OND Veterans or list of Veterans applying for disability benefits), and what incentive Veterans would receive ($20 or $40). The main outcome, non-response bias, measured differences between survey respondents' and sampling frame's characteristics on 8 administrative variables, including Veterans' receipt of VA disability benefits and exposure to combat or military sexual trauma. Analysis was intention to treat. We used ANOVA for factorial block-design, logistic, mixed-models to assess bias and multiple imputation and expectation-maximization algorithms to assess potential missing mechanisms (missing completely at random, missing at random, or not random) of two self-reported variables: combat and military sexual assault.

RESULTS

Regardless of intervention, men with any VA disability benefits, women with PTSD disability benefits, and women with combat exposure were over-represented among respondents. Interventions explained 0.0 to 31.2% of men's variance and 0.6 to 30.5% of women's variance in combat non-response bias and 10.2 to 43.0% of men's variance and 0.4 to 31.9% of women's variance in military sexual trauma non-response bias. Non-random assumptions showed that men's self-reported combat exposure was overestimated by 19.0 to 28.8 percentage points and their self-reported military sexual assault exposure was underestimated by 14.2 to 28.4 percentage points compared to random missingness assumptions. Women's self-reported combat exposure was overestimated by 8.6 to 10.6 percentage points and military sexual assault exposure, by 1.2 to 6.9 percentage points.

CONCLUSIONS

Our interventions reduced bias in some characteristics, leaving others unaffected or exacerbated. Regardless of topic, researchers are urged to present estimates that include all three assumptions of missingness.

摘要

背景

调查中的非随机无应答偏倚需要耗时且复杂的事后分析。我们的目标是观察修改封面信信息是否可以完全避免非随机无应答偏倚。我们的次要目标是测试较大的激励是否会减少无应答偏倚。

方法

对 480 名男性和 480 名女性进行了邮寄调查,这些男性和女性均为来自持久自由行动、伊拉克自由行动或新黎明行动(OEF/OIF/OND)的、正在申请退伍军人事务部(VA)创伤后应激障碍(PTSD)残疾津贴的退伍军人。封面信传达了有关调查主题(战斗、非自愿性性关注或终身和军事经历)、退伍军人姓名选择方式(OEF/OIF/OND 退伍军人名单或申请残疾津贴的退伍军人名单)以及退伍军人将获得的激励($20 或 $40)的不同信息。主要结果,无应答偏倚,衡量了调查受访者和抽样框架在 8 个行政变量上的特征差异,包括退伍军人是否获得 VA 残疾津贴以及是否接触过战斗或军事性创伤。分析采用意向治疗。我们使用方差分析(ANOVA)进行因子设计、逻辑回归、混合模型评估偏差以及多重插补和期望最大化算法评估两个自报告变量的潜在缺失机制(完全随机缺失、随机缺失或非随机缺失):战斗和军事性侵犯。

结果

无论干预措施如何,有任何 VA 残疾津贴的男性、有 PTSD 残疾津贴的女性以及有战斗经历的女性在受访者中所占比例过高。干预措施解释了男性在战斗中无应答偏倚的 0.0 到 31.2%的方差和女性在战斗中无应答偏倚的 0.6 到 30.5%的方差,以及男性在军事性创伤中无应答偏倚的 10.2 到 43.0%的方差和女性在军事性创伤中无应答偏倚的 0.4 到 31.9%的方差。非随机假设表明,与随机缺失假设相比,男性自我报告的战斗经历被高估了 19.0 到 28.8 个百分点,他们自我报告的军事性侵犯经历被低估了 14.2 到 28.4 个百分点。女性自我报告的战斗经历被高估了 8.6 到 10.6 个百分点,而军事性侵犯经历则被低估了 1.2 到 6.9 个百分点。

结论

我们的干预措施减少了某些特征的偏差,但对其他特征没有影响或加剧了偏差。无论主题如何,研究人员都应提供包括缺失的所有三种假设在内的估计值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/109a/8898515/1d2387fc4fb2/12874_2022_1531_Fig1_HTML.jpg

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