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Although polling is not irredeemably broken, changes in technology and society create challenges that, if not addressed well, can threaten the quality of election polls and other important surveys on topics such as the economy. This essay describes some of these challenges and recommends remediations to protect the integrity of all kinds of survey research, including election polls. These 12 recommendations specify ways that survey researchers, and those who use polls and other public-oriented surveys, can increase the accuracy and trustworthiness of their data and analyses. Many of these recommendations align practice with the scientific norms of transparency, clarity, and self-correction. The transparency recommendations focus on improving disclosure of factors that affect the nature and quality of survey data. The clarity recommendations call for more precise use of terms such as representative sample and clear description of survey attributes that can affect accuracy. The recommendation about correcting the record urges the creation of a publicly available, professionally curated archive of identified technical problems and their remedies. The paper also calls for development of better benchmarks and for additional research on the effects of panel conditioning. Finally, the authors suggest ways to help people who want to use or learn from survey research understand the strengths and limitations of surveys and distinguish legitimate and problematic uses of these methods.

Previous research has shown that increasing the size of incentives can increase response rates for probability-based, cross-sectional surveys. However, the effects of incentives on web panels have not been extensively studied. We sought to answer the question: What is the effect of larger, postpaid incentives on (1) response, (2) data quality, and (3) nonresponse bias for individuals in a web panel? We analyzed data from the 2015 and 2016 National Internet Flu Survey, a survey that uses the GfK KnowledgePanel® as its sampling frame. We compare panel members who received a postpaid, standard 1,000-point (the equivalent of US$1) incentive in 2015 to panelists who received a larger, 5,000-point (the equivalent of US$5) incentive in 2016. We found that larger incentives were associated with increased interview completion rates with minimal impact on data quality or bias.

Objective: Opioid use disorder (OUD) affects approximately 5.6 million people in the United States annually, yet rates of the use of effective medication for OUD (MOUD) treatment are low. We conducted an observational cohort study from August 2017 through May 2021, the MOUD Study, to better understand treatment engagement and factors that may influence treatment experiences and outcomes. In this article, we describe the study design, data collected, and treatment outcomes. Methods: We recruited adult patients receiving OUD treatment at US outpatient facilities for the MOUD Study. We collected patient-level data at 5 time points (baseline to 18 months) via self-administered questionnaires and health record data. We collected facility-level data via questionnaires administered to facility directors at 2 time points. Across 16 states, 62 OUD treatment facilities participated, and 1974 patients enrolled in the study. We summarized descriptive data on the characteristics of patients and OUD treatment facilities and selected treatment outcomes. Results: Approximately half of the 62 facilities were private, nonprofit organizations; 62% focused primarily on substance use treatment; and 20% also offered mental health services. Most participants were receiving methadone (61%) or buprenorphine (32%) and were predominately non-Hispanic White (68%), aged 25-44 years (62%), and female (54%). Compared with patient-reported estimates at baseline, 18-month estimates suggested that rates of abstinence increased (55% to 77%), and rates of opioid-related overdoses (7% to 2%), emergency department visits (9% to 4%), and arrests (15% to 7%) decreased. Conclusions: Our results demonstrated the benefits of treatment retention not only on abstinence from opioid use but also on other quality-of-life metrics, with data collected during an extended period. The MOUD Study produced rich, multilevel data that can lay the foundation for an evidence base to inform OUD treatment and support improvement of care and patient outcomes. [ABSTRACT FROM AUTHOR]

In his letter Curtis (1) raises an important consideration: Because the paraoxonase-1 (PONI) Q192R genotype has long been known to vary across racial/ethnic groups, (2) the gene-environment (G X E) [...]

Introduction In the 1991 Persian Gulf War, approximately 700,000 U.S. military personnel and 300,000 people from 41 Coalition countries were deployed to the Kuwaiti Theater of Operations (KTO) for a [...], Background: Consensus on the etiology of 1991 Gulf War illness (GWI) has been limited by lack of objective individual- level environmental exposure information and assumed recall bias. Objectives: We investigated a prestated hypothesis of the association of GWI with a gene-environment (GxE) interaction of the paraoxonase-1 (PON1) Q192R polymorphism and low-level nerve agent exposure. Methods: A prevalence sample of 508 GWI cases and 508 nonpaired controls was drawn from the 8,020 participants in the U.S. Military Health Survey, a representative sample survey of military veterans who served during the Gulf War. The PON1 Q192R genotype was measured by real-time polymerase chain reaction (RT-PCR), and the serum Q and R isoenzyme activity levels were measured with PON1- specific substrates. Low-level nerve agent exposure was estimated by survey questions on having heard nerve agent alarms during deployment. Results: The GxE interaction of the Q192R genotype and hearing alarms was strongly associated with GWI on both the multiplicative [prevalence odds ratio (POR) of the interaction = 3.41; 95% confidence interval (CI): 1.20, 9.72] and additive (synergy index = 4.71; 95% CI: 1.82, 12.19) scales, adjusted for measured confounders. The Q192R genotype and the alarms variable were independent (adjusted POR in the controls = 1.18; 95% CI: 0.81, 1.73; p = 0.35), and the associations of GWI with the number of R alleles and quartiles of Q isoenzyme were monotonic. The adjusted relative excess risk due to interaction (aRERI) was 7.69 (95% CI: 2.71, 19.13). Substituting Q isoenzyme activity for the genotype in the analyses corroborated the findings. Sensitivity analyses suggested that recall bias had forced the estimate of the GxE interaction toward the null and that unmeasured confounding is unlikely to account for the findings. We found a GxE interaction involving the Q-correlated PON1 diazoxonase activity and a weak possible GxE involving the Khamisiyah plume model, but none involving the PON1 R isoenzyme activity, arylesterase activity, paraoxonase activity, butyrylcholinesterase genotypes or enzyme activity, or pyridostigmine. Discussion: Given gene-environment independence and monotonicity, the unconfounded aRERI >0 supports a mechanistic interaction. Together with the direct evidence of exposure to fallout from bombing of chemical weapon storage facilities and the extensive toxicologic evidence of biochemical protection from organophosphates by the Q isoenzyme, the findings provide strong evidence for an etiologic role of low- level nerve agent in GWI. https://doi.org/10.1289/EHP9009

Objective: The Mental and Substance Use Disorders Prevalence Study (MDPS) builds upon previous epidemiologic studies to provide estimates of prevalence and treatment rates of mental and substance use disorders among adults aged 18–65 in the U.S. The study background and methods are described. Method: The MDPS employed novel techniques such as the inclusion of household, prison, homeless and state psychiatric hospital populations, a semi‐structured clinical interview administered by trained clinical interviewers to assess disorders, the assessment of both past year and lifetime schizophrenia spectrum disorder (SSD) using full Diagnostic and Statistical Manual 5 criteria, as well as other mental and substance use disorders, and video‐based interviewing. Population specific and combined sample weights were developed to estimate nationally representative prevalence and treatment rates. Results: Data collection was conducted between October 2020 and October 2022 resulting in 5679 clinical interviews. The statistical weighting and analytic plan are described. Weighted response rates and reasons for non‐response are provided for each study population. Conclusions: The MDPS successfully developed and employed novel techniques to estimate the prevalence and treatment rates of mental and substance use disorders in both household and non‐household populations, including some of the most impairing disorders such as SSD. [ABSTRACT FROM AUTHOR]