Explore the vast range of titles available.

Vitamin E was proposed as treatment for Alzheimer’s disease many years ago. However, the effectiveness of the drug is not clear. Vitamin E is an antioxidant and neuroprotector and it has anti-inflammatory and hypocholesterolemic properties, driving to its importance for brain health. Moreover, the levels of vitamin E in Alzheimer’s disease patients are lower than in non-demented controls. Thus, vitamin E could be a good candidate to have beneficial effects against Alzheimer’s. However, evidence is consistent with a limited effectiveness of vitamin E in slowing progression of dementia; the information is mixed and inconclusive. The question is why does vitamin E fail to treat Alzheimer’s disease? In this paper we review the studies with and without positive results in Alzheimer’s disease and we discuss the reasons why vitamin E as treatment sometimes has positive results on cognition but at others, it does not.

Network sampling emerged as a set of methods for drawing statistically valid samples of hard-to-reach populations. The first form of network sampling, multiplicity sampling, involved asking respondents about events affecting those in their personal networks; it was subsequently applied to studies of homicide, HIV, and other topics, but its usefulness is limited to public events. Link-tracing designs employ a different approach to study hard-to-reach populations, using a set of respondents that expands in waves as each round of respondents recruit their peers. Link-tracing as applied to hidden populations, often described as snowball sampling, was initially considered a form of convenience sampling. This changed with the development of respondent-driven sampling (RDS), a widely used network sampling method in which the link-tracing design is adapted to provide the basis for statistical inference. The literature on RDS is large and rapidly expanding, involving contributions by numerous independent research groups employing data from dozens of different countries. Within this literature, many important research questions remain unresolved, including how best to choose among alternative RDS estimators, how to refine existing estimators to make them less dependent on assumptions that are sometimes counterfactual, and perhaps the greatest unresolved issue, how best to calculate the variability of the estimates.

How does terrorism affect citizens’ political attitudes? Over the years, many scholars have tried to answer this question. This article performs a meta-analysis on this literature, reviewing about 325 studies conducted between 1985 and 2020 on more than 400,000 respondents. The findings confirm that terrorism is associated—to a small but significant extent—with outgroup hostility, political conservatism and rally-‘round-the-flag effects. At the same time, the effects of terrorism vary widely, with studies on Islamist violence, conducted in the United States or Israel, and using cross-sectional data yielding stronger results on average. Finally, the review reveals remaining gaps in this field of study, including a lack of research on non-Islamist violence or conducted in non-Western contexts. Taken together, this meta-analysis consolidates existing evidence, determines which results hold across contexts, and identifies key gaps in our current knowledge. Its data can also be accessed interactively via a Shiny App.

Conjoint analysis is a common tool for studying political preferences. The method disentangles patterns in respondents’ favorability toward complex, multidimensional objects, such as candidates or policies. Most conjoints rely upon a fully randomized design to generate average marginal component effects (AMCEs). They measure the degree to which a given value of a conjoint profile feature increases, or decreases, respondents’ support for the overall profile relative to a baseline, averaging across all respondents and other features. While the AMCE has a clear causal interpretation (about the effect of features), most published conjoint analyses also use AMCEs to describe levels of favorability. This often means comparing AMCEs among respondent subgroups. We show that using conditional AMCEs to describe the degree of subgroup agreement can be misleading as regression interactions are sensitive to the reference category used in the analysis. This leads to inferences about subgroup differences in preferences that have arbitrary sign, size, and significance. We demonstrate the problem using examples drawn from published articles and provide suggestions for improved reporting and interpretation using marginal means and an omnibus F-test. Given the accelerating use of these designs in political science, we offer advice for best practice in analysis and presentation of results.

Manipulation checks are often advisable in experimental studies, yet they rarely appear in practice. This lack of usage may stem from fears of distorting treatment effects and uncertainty regarding which type to use (e.g., instructional manipulation checks [IMCs] or assessments of whether stimuli alter a latent independent variable of interest). Here, we first categorize the main variants and argue that factual manipulation checks (FMCs)—that is, objective questions about key elements of the experiment—can identify individual-level attentiveness to experimental information andy as a consequence, better enable researchers to diagnose experimental findings. We then find, through four replication studies, little evidence that FMC placement affects treatment effects, and that placing FMCs immediately post-outcome does not attenuate FMC passage rates. Additionally, FMC and IMC passage rates are only weakly related, suggesting that each technique identifies different sets of attentive subjects. Thus, unlike other methods, FMCs can confirm attentiveness to experimental protocols.

BackgroundSocial isolation and loneliness have each been associated with cognitive decline, but most previous research is limited to Western populations. This study examined the relationships of social isolation and loneliness on cognitive function among Chinese older adults.MethodsThis study used two waves of data (2011 and 2015) from the China Health and Retirement Longitudinal Study and analyses were restricted to those respondents aged 50 and older. Social isolation, loneliness, and cognitive function were measured at baseline. Follow-up measures on cognitive function were obtained for 7761 participants (mean age = 60.97, s.d. = 7.31; male, 50.8%). Lagged dependent variable models adjusted for confounding factors were used to evaluate the association between baseline isolation, loneliness, and cognitive function at follow-up.ResultsLoneliness was significantly associated with the cognitive decline at follow-up (episodic memory: β = −0.03, p < 0.01; mental status: β = −0.03, p < 0.01) in the partially adjusted models. These associations became insignificant after additional confounding variables (chronic diseases, health behaviors, disabilities, and depressive symptoms) were taken into account (all p > 0.05). By contrast, social isolation was significantly associated with decreases in all cognitive function measures at follow-up (episodic memory: β = −0.05, p < 0.001; mental status: β = −0.03, p < 0.01) even after controlling for loneliness and all confounding variables.ConclusionsSocial isolation is associated with cognitive decline in Chinese older adults, and the relationships are independent of loneliness. These findings expand our knowledge about the links between social relationships and the cognitive function in non-Western populations.

Research Summary We used interviews with elite informants as a case study to illustrate the need to expand the discussion of transparency and replicability to qualitative methodology. An analysis of 52 articles published in Strategic Management Journal revealed that none of them were sufficiently transparent to allow for exact replication, empirical replication, or conceptual replication. We offer 12 transparency criteria, and behaviorally‐anchored ratings scales to measure them, that can be used by authors as they plan and conduct qualitative research as well as by journal reviewers and editors when they evaluate the transparency of submitted manuscripts. We hope our article will serve as a catalyst for improving the degree of transparency and replicability of future qualitative research. Managerial Summary If organizations implement practices based on published research, will they produce results consistent with those reported in the articles? To answer this question, it is critical that published articles be transparent in terms of what has been done, why, and how. We investigated 52 articles published in Strategic Management Journal that reported interviewing elite informants (e.g., members of the top management team) and found that none of the articles were sufficiently transparent. These results lead to thorny questions about the trustworthiness of published research, but also important opportunities for future improvements about research transparency and replicability. We offer recommendations on 12 transparency criteria, and how to measure them, that can be used to evaluate past as well as future research using qualitative methods.

Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for human immunodeficiency virus or acquired immune deficiency syndrome. Data are collected through a peer referral process over social networks. RDS has proven practical for data collection in many difficult settings and has been adopted by leading public health organizations around the world. Unfortunately, inference from RDS data requires many strong assumptions because the sampling design is partially beyond the control of the researcher and not fully observable. We introduce diagnostic tools for most of these assumptions and apply them in 12 high risk populations. These diagnostics empower researchers to understand their RDS data better and encourage future statistical research on RDS sampling and inference.

Despite widespread support for gender-egalitarianism, men’s and women’s household labor contributions remain strikingly unequal. This article extends prior research on barriers to equality by closely examining how couples negotiate contradictions between their egalitarian ideals and admittedly non-egalitarian practices. Data from 64 in-depth interviews with members of 32 different-sex, college-educated couples show that respondents distinguish between labor allocation processes and outcomes. When they understand the processes as gender-neutral, they can write off gendered outcomes as the incidental result of necessary compromises made among competing values. Respondents “de-gender” their allocation process, or decouple it from gender ideology and gendered social forces, by narrowing their temporal horizon to the present moment and deploying an adaptable understanding of constraint that obscures alternative paths. This de-gendering helps prevent spousal conflict, but it may also facilitate behavioral stasis by directing attention away from the inequalities that continue to shape domestic life.

Purpose Enhancing green innovation for corporate sustainability is one of the recent issues globally. Knowledge management has been determined as a core factor that hamstrings green innovation. The existing literature was limited to expose the importance of the knowledge management process for corporate sustainable performance. Thus, this paper aims to examine the role of the knowledge management process for corporate sustainable performance with the integration of green innovation and organizational agility following the resource-based view theory. Design/methodology/approach Cross-sectional design was used in this study. Data were gathered through convenience sampling from 475 respondents of multinational manufacturing corporations of Pakistan, analyzed by using structural equation modeling. Findings This study revealed that the knowledge management process and its all constructs (acquisition, dissemination and application) lead toward green innovation; further, green innovation influences corporate sustainable performance and its all constructs (environment, economic and social). Green innovation partially mediates the association between the knowledge management process and corporate sustainable performance. Besides, organizational agility has a positive effect on green innovation and corporate sustainable performance but was not found moderating these relations. The study educates that organizations investing in innovative technologies and adopting greener strategies are not only adequate for achieving sustainable performance, soft issues such as knowledge management and organizational agility but also important factors in the current knowledge base economy. Originality/value This study is an attempt to examine the previously undiscovered multi-dimensional relationships among the knowledge management process, green innovation, organizational agility and corporate sustainable performance. The presence of a positive correlation among these constructs was observed, proving the conceptual framework for this study.