Maya B. Mathur’s research while affiliated with Stanford University and other places

Observational studies are critical tools in clinical research and public health response, but challenges arise in ensuring the data produced by these studies are scientifically robust and socially valuable. Resolving these challenges requires careful attention to prioritising the most valuable research questions, ensuring robust study design, strong data management practices, expansive community engagement, and access and benefit sharing of results and research materials. This paper opens with a discussion of how well-designed observational studies contribute to biomedical evidence and provides examples from across the clinical literature of how these methods generate hypotheses for future research and uncover otherwise unattainable insights by providing examples from across the clinical literature. Then, we present obstacles that remain in ensuring observational studies are optimally designed, conducted and communicated.

Psychologists are often interested in the effect of an internal state, such as ego depletion, that cannot be directly assigned in an experiment. Instead, they assign participants to a manipulation intended to produce this state and use manipulation checks to assess the manipulation’s effectiveness. In this article, I discuss statistical analyses for experiments in which researchers are primarily interested in the average treatment effect (ATE) of the target internal state rather than that of the manipulation. Often, researchers estimate the association of the manipulation itself with the dependent variable, but this intention-to-treat (ITT) estimator is typically biased for the ATE of the target state, and the bias could be either toward the null (conservative) or away from the null. I discuss the fairly stringent assumptions under which this estimator is conservative. Given this, I argue against the status-quo practice of interpreting the ITT estimate as the effect of the target state without any explicit discussion of whether these assumptions hold. Under a somewhat weaker version of the same assumptions, one can alternatively use instrumental-variables (IVs) analysis to directly estimate the effect of the target state. IVs analysis complements ITT analysis by directly addressing the central question of interest. As a running example, I consider a multisite replication study on the ego-depletion effect, in which the manipulation’s partial effectiveness led to criticism and several reanalyses that arrived at varying conclusions. I use IVs analysis to directly account for the manipulation’s partial effectiveness; this corroborated the replication authors’ reported null results.

This survey study examines population trends in sexual identity and patterns of individual sexual identity fluidity in Stockholm County, Sweden, from 2010 to 2021.

We respond to Madley-Dowd et al's recent article in American Journal of Epidemiology. We show that standard imputation algorithms can fail for simple graphs (such as those used in Madley-Dowd et al's simulation study) even when the full data distribution is identified and an appropriate imputation estimator would be straightforward to design.

Importance Occupational burnout syndrome is characterized by emotional exhaustion, depersonalization, and a diminished sense of personal accomplishment and is prevalent among nurses. Although previous meta-analyses have explored the correlates of nurse burnout, none have estimated their association with health care quality and safety and patient morbidity and mortality. Objective To evaluate the magnitude and moderators of the association between nurse burnout and patient safety, patient satisfaction, and quality of care. Data Source The Web of Science, Scopus, MEDLINE, Embase, PsycINFO, CINAHL, and ProQuest databases were searched from January 1, 1994, to February 29, 2024. Study Selection Two reviewers independently identified studies that reported a quantifiable association between nurse burnout and any of the outcomes of patient safety, patient satisfaction, or quality of health care. Data Extraction and Synthesis The PRISMA 2020 guideline was followed. Two reviewers independently extracted the standardized mean difference (SMD) (Cohen d ) estimates for a random-effects meta-analysis. Subgroup analyses and meta-regressions were conducted using prespecified variables. Main Outcomes and Measures Any measure of patient safety, patient satisfaction, or quality of health care previously associated with nurse burnout. Results A total of 85 studies (81 cross-sectional and 4 longitudinal) involving 288 581 nurses from 32 countries (mean [SD] age, 33.9 (2.1) years; 82.7% female; mean [SD] burnout prevalence rate with study-specific ascertainments, 30.7% [9.7%]) were included. Nurse burnout was associated with a lower safety climate or culture (SMD, −0.68; 95% CI, −0.83 to −0.54), lower safety grade (SMD, −0.53; 95% CI, −0.72 to −0.34), and more frequent nosocomial infections (SMD, −0.20; 95% CI, −0.36 to −0.04), patient falls (SMD, −0.12; 95% CI, −0.22 to −0.03), medication errors (SMD, −0.30; 95% CI, −0.48 to −0.11), adverse events or patient safety incidents (SMD, −0.42; 95% CI, −0.76 to −0.07), and missed care or care left undone (SMD, −0.58; 95% CI, −0.91 to −0.26) but not with the frequency of pressure ulcers. Nurse burnout was also associated with lower patient satisfaction ratings (SMD, −0.51; 95% CI, −0.86 to −0.17) but not with the frequencies of patient complaints or patient abuse. Finally, nurse burnout was associated with lower nurse-assessed quality of care (SMD, −0.44; 95% CI, −0.57 to −0.30) but not with standardized mortality rate. The associations were consistent across nurses’ age, sex, work experience, and geography and persistent over time. For patient safety outcomes, the association was smaller for the low personal accomplishment subcomponent of burnout than for emotional exhaustion or depersonalization, as well as for nurses with a college education. Conclusions and Relevance In this systematic review and meta-analysis, nurse burnout was found to be associated with lower health care quality and safety and lower patient satisfaction. This association was consistent across nurse and study characteristics.

Background Sexual fluidity is key to understanding the size of sexual minority populations and analyzing the socioeconomic disparities these populations face. This study explores the stability and changes in sexual identity over time, and identifies key demographic factors that predict shifts in sexual identity. Methods We analyzed longitudinal data from the Stockholm Public Health Cohort, following 36,398 participants from 2010 to 2021. Sexual identity was measured using a self-administered questionnaire in 2010, 2014, and 2021. Demographic data from 2010 were collected from the Swedish national registers. Multivariate Poisson regression with robust variance estimators was used to identify demographic factors that predicted identity changes. Results were presented as proportion or risk ratio (RR) with 95% confidence interval (CI). Results Overall, 12.1% (95% CI 11.8%-12.5%) changed sexual identity at least once in 2010-2021, including 10.4% (10.0%-10.7%) among those initially identifying as heterosexual in 2010, 41.3% (37.1%-45.6%) as homosexual, 59.6% (55.0%-64.0%) as bisexual, and 65.0% (59.4%-70.3%) as uncertain. Multivariate analyses showed that sexual minorities (homosexual: RR 5.00, 95% CI 4.45-5.61; bisexual: 6.68, 6.04-7.38; uncertain: 3.88, 3.30-4.55), females (1.28, 1.21-1.35), younger (18-29 years: 1.49, 1.30-1.70) and older ( > =60 years: 2.07, 1.92-2.22) ages, born outside Sweden (Europe: 1.21, 1.11-1.32; Outside Europe: 2.90, 2.62-3.21), and lower education ( < =9 years: 2.14, 1.98-2.31; 10-12 years: 1.43, 1.34-1.53) and income (100 SEK/year) ( < =2,500: 1.83, 1.66-2.02; (2,500, 3,500]: 1.32, 1.19-1.46) independently predicted a higher probability of identity changes. Conclusions This study provides the first insights into sexual identity fluidity in a large general population sample in Sweden, highlighting its fluid nature. Future research is needed to unravel the intricate mechanisms underlying the demographic disparities in sexual identity fluidity. Key messages • This study provides the first insights into sexual identity fluidity in Sweden, highlighting its fluid nature. • Future research is needed to unravel the intricate mechanisms underlying the demographic disparities in sexual identity fluidity.

Background Sexual identity, linked to experiences of disadvantage and discrimination, is crucial in equality monitoring. Sweden’s gender-neutral marriage laws, introduced in 2009, provide a unique context. This study examines the population trends and demographic disparities in sexual identity over time. Methods We analyzed three population surveys (2010, 2014, 2021) from the Stockholm Public Health Cohort, including around 50,000 individuals per survey. Sexual identity was assessed via self-administered questionnaires. Demographic data were sourced from Swedish national registers. Weighted multivariate Poisson regression with robust variance estimators was used to identify demographic disparities in sexual identity. Results were presented as proportion ratio (PR) with 95% confidence interval (CI). Results Overall, 29,607 (2010), 20,249 (2014), and 22,558 (2021) individuals reported sexual identity. Heterosexual identity decreased from 95.7% (95% CI 95.4-96.0%) in 2010 to 89.0% (88.5-89.4%) in 2021, while bisexual identity increased from 1.4% (1.2-1.6%) in 2010 to 2.0% (1.8-2.3%) in 2014, and further up to 2.7% (2.4-2.9%) in 2021. Homosexual identity increased slightly from 1.5% (1.4-1.7%) in 2010 to 1.8% (1.6-2.0%) in 2021. Multivariate analyses showed that female, older age, and lower education were inversely associated, while never-married status and living alone were positively associated, with homosexual identity. In contrast, female, younger age, lower income (100 SEK/year) ( < =2,500 vs > 4,500: 2010: PR 3.32 [95% CI 1.92-5.75]; 2014: 1.83 [1.28-2.60]; 2021: 1.51 [1.14-2.01]), and never-married status (never vs currently married: 2010: 2.03 [1.47-2.80]; 2014: 1.92 [1.39-2.65]; 2021: 1.50 [1.15-1.95]) were positively associated with bisexual identity. Conclusions Heterosexual identity decreased while homosexual/bisexual identities increased in Stockholm County during 2010-2021. Socioeconomic disparities persist in sexual minorities and vary by sexual identity. Key messages • Marked socioeconomic disparities persist in sexual minorities and vary by sexual identity in Stockholm County, although income and marital status disparities in bisexual group seem narrowing. • Future studies are warranted to investigate the social dynamics that continue to produce sexual minority disadvantages.

Complete-case analysis (CCA) is often criticized on the belief that CCA is only valid if data are missing-completely-at-random (MCAR). Influential papers have thus recommended abandoning CCA in favor of methods that make a weaker missing-at-random (MAR) assumption. We argue for a different view: that CCA with principled covariate adjustment provides a valuable complement to MAR-based methods, such as multiple imputation. When estimating treatment effects, appropriate covariate control can, for some causal structures, eliminate bias in CCA. This can be true even when data are missing-not-at-random (MNAR) and when MAR-based methods are biased. We describe principles for choosing adjustment covariates for CCA, and we characterize the causal structures for which covariate adjustment does, or does not, eliminate bias. Even when CCA is biased, principled covariate adjustment will often reduce the bias of CCA, and this method will sometimes be less biased than MAR-based methods. When multiple imputation is used under a MAR assumption, adjusted CCA thus still constitutes an important sensitivity analysis. When conducted with the same attention to covariate control that epidemiologists already afford to confounding, adjusted CCA belongs in the suite of reasonable methods for missing data. There is thus good justification for resurrecting CCA as a principled method.

By revisiting imputation from the modern perspective of missing data graphs, we correct common guidance about which auxiliary variables should be included in an imputation model. We propose a generalized definition of missingness at random (MAR), called “z-MAR'', which makes explicit the set of variables to be analyzed and a separate set of auxiliary variables that are included in the imputation model, but not analyzed. We provide a graphical equivalent of z-MAR that we call the “m-backdoor criterion”. In a sense we formalize, a standard imputation model trained on complete cases is valid for a given analysis if and only if the m-backdoor criterion holds. As the criterion indicates, the standard recommendations to use all available auxiliary variables, or all that are associated with missingness status, can lead to invalid imputation models and biased estimates. This bias arises from collider stratification and can occur even with non-causal estimands. Instead, the set of auxiliary variables should be restricted to those that affect incomplete variables or missingness indicators. These auxiliary variables will always suffice to have a valid imputation model, if such a set does exist among the candidate auxiliary variables. Applying this result does not require full knowledge of the graph.

The present study examined the effectiveness of a brief self-directed secular REACH Forgiveness workbook in improving state forgiveness, state hope, mental health, and flourishing among Indonesian Christians. A subset of data (all self-identified Christians; N = 203; Mage = 21.17 ± 3.28 years, female = 75.86%, 78.33% college students) from a large, randomized waitlist controlled trial in Indonesia was used. The participants were assigned randomly to an immediate treatment (IT) or delayed treatment condition and were assessed three times. Evidence of posttreatment improvements was found in state forgiveness and to a lesser extent state hope, flourishing, and mental health in both conditions, regardless of Christian denomination, frequency of religious service attendance, or frequency of engagement in private religious/spiritual activities. For those in the IT condition, increases in all outcomes were maintained at 2-week follow-up; for those in the delayed treatment condition, gains while they completed the workbook were comparable to those in the IT condition. The secular workbook intervention was efficacious for Christians in dealing with interpersonal transgression.