The Sleep Benefit in Episodic Memory: An Integrative Review and a Meta-Analysis

People recall more information after sleep than after an equally long period of wakefulness. This sleep benefit in episodic memory has been documented in almost a century of research. However, an integrative review of hypothesized underlying processes, a comprehensive quantification of the benefit, and a systematic investigation of potential moderators has been missing so far. Here, we address these issues by analyzing 823 effect sizes from 271 independent samples that were reported in 177 articles published between 1967 and 2019. Using multilevel meta-regressions with robust variance estimates, we found a moderate overall sleep benefit in episodic memory (g = 0.44). Moderator analyses revealed four important findings: First, the sleep benefit is larger when stimuli are studied multiple times instead of just once. Second, for word materials, the effect size depends on the retrieval procedure: It is largest in free recall, followed by cued recall and recognition tasks. Third, the sleep benefit is stronger in pre-post difference measures of retention than in delayed memory tests. Fourth, sleep benefits are larger for natural sleep and nighttime naps than foralternative sleep-study designs (e.g., SWS-deprived sleep, daytime naps). Although there was no obvious evidence for selective reporting, it is a potential threat to the validity of the results. When accounting for selective reporting bias, the overall effect of sleep on episodic memory is reduced but still significant (g = 0.28). We argue that our results support an integrative, multi-causal theoretical account of sleep-induced episodic memory benefits and provide guidance to increase their replicability.

What Do Participants Think of Our Research Practices? An Examination of Behavioral Psychology Participants’ Preferences

What research practices should be considered acceptable? Historically, scientists have set the standards for what constitutes acceptable research practices. However, there is value in considering non-scientists’ perspectives, including research participants’. 1,873 participants from MTurk and university subject pools were surveyed after their participation in one of eight minimal-risk studies. We asked participants how they would feel if common research practices were applied to their data: p-hacking/cherry-picking results, selective reporting of studies, Hypothesizing After Results are Known (HARKing), committing fraud, conducting direct replications, sharing data, sharing methods, and open access publishing. An overwhelming majority of psychology research participants think questionable research practices (e.g., p-hacking, HARKing) are unacceptable (68.3--81.3%), and were supportive of practices to increase transparency and replicability (71.4--80.1%). A surprising number of participants expressed positive or neutral views toward scientific fraud, raising concerns about the quality of our data. We grapple with this concern and interpret our results in light of the limitations of our study. Despite ambiguity in our results, we argue that there is evidence (from our study and others’) that researchers may be violating participants’ expectations and should be transparent with participants about how their data will be used.

Compliance of Clinical Trial Protocols for Foods with Function Claims (FFC) in Japan: Consistency between Clinical Trial Registrations and Published Reports

Background: A new type of foods with a health claims notification system, the Foods with Function Claims (FFC), was introduced in Japan in April 2015. This cross-sectional study sought to clarify compliance of clinical trial protocols reported as the scientific basis of efficacy in the FFC system. Methods: All articles based on clinical trials published on the Consumer Affairs Agency website from 1 July 2018 to 30 June 2021 were reviewed. Items assessed included first author characteristics (for-profit or academia), journal name, year published, journal impact factor in 2020, article language, name of clinical trial registration (CTR), and seven compliance items (Title: T, Participant: P, Intervention: I, Comparison: C, Outcome: O, Study design: S, and Institutional Review Board, IRB). Among studies that conducted CTR, consistency with these seven compliance items was evaluated. Results: Out of 136 studies that met all inclusion criteria, 103 (76%) performed CTR, and CTR was either not performed or not specified for 33 (24%). Compliance between the protocol and the text was high (≥96%) for items P and S, but considerably lower for items T, I, C, O, and IRB (52%, 15%, 13%, 69%, and 27%, respectively). Furthermore, 43% of protocols did not include functional ingredients or food names in items T or I. The total score was 3.7 ± 1.1 pts (out of 7). Conclusions: Some CTs had no protocol registration, and even registered protocols were suboptimal in transparency. In addition to selective reporting, a new problem identified was that the content of the intervention (test food) was intentionally concealed.

Density strips: visualisation of uncertainty in clinical data summaries and research findings

The disproportionate focus on statistical significance in reporting and interpreting clinical research studies contributes to publication bias and encourages selective reporting. This highlights a need for alternative approaches that clearly communicate the uncertainty in the data, enabling researchers to provide a more nuanced interpretation of clinical research findings.Our purpose in this article is to introduce the density strip method as one potential approach that might act as a bridge between data visualisation for descriptive purposes and formal statistical inference. We build on existing theory, translating it to the applied research context to illustrate its utility to clinical researchers.We achieve this by considering an exemplar clinical trial, Multiple Sclerosis-Secondary Progressive Multi-Arm Randomisation Trial (MS-SMART). MS-SMART was a multiarm randomised placebo-controlled trial of three potentially neuroprotective drugs in secondary progressive MS. We illustrate through MS-SMART the potential of the density strip as an effective visualisation of the distribution of clinical trial outcomes and as a complementary approach to aid the interpretation of formal, inferential, statistical analysis.We conclude by summarising the advantages and disadvantages of the density strip methodology and provide suggestions for its potential extensions and possible further uses.

The current global perspective of the knowledge-attitude-behavior of the general public towards the corona virus disease -19 pandemic: Systematic review and meta-analysis on 67,143 participants

Background Determining the success of infectious disease outbreak prevention is dependent mainly on public knowledge and compliance regarding the guidelines of precautionary behaviors and practices. While the current literature about the COVID-19 pandemic extensively addresses clinical and laboratory-based studies, a gap remains still present in terms of evaluating the general public knowledge and behaviors towards the COVID-19 pandemic. The aim of this review was to form a preliminary and contemporary understanding of the general public knowledge, attitude, and behaviors towards the COVID-19 pandemic globally. Methods A systematic search was conducted in various databases until May 2020. Each study’s characteristics including the sample size, region, and study type were examined individually. A meta-analysis with a random-effects model and pooled prevalence with 95% confidence interval (CI) of all evaluated outcomes such as adequate knowledge, positive feelings, worrisome about the COVID-19 pandemic, and practice were recorded and reported from each study. Parameters such as random distribution, blinding, incomplete outcome data, selective reporting, and other biases were utilized to assess the quality of each retrieved record. Both Begg’s and Egger’s tests were employed to evaluate symmetry of funnel plots for assessment of publication bias. The overall quality of evidence was evaluated using GRADEpro software. Results A total of 26 studies with 67,143 participants were analyzed. The overall prevalence of knowledge, positive attitude, worrisome, and practice of precautionary measures were 0.87 (95%CI, 0.84–0.89), 0.85 (95%CI, 0.77–0.92), 0.71 (95%CI, 0.61–0.81), and 0.77 (95%CI, 0.70–0.83), respectively. Subgroup analysis demonstrated that social distancing was less practiced in Africa than other regions (p = 0.02), while knowledge of prevention of COVID-19 was reported higher in Asia (p = 0.001). Furthermore, people in developing countries had a higher prevalence of worrisome towards the COVID-19 pandemic with a p-value of less than 0.001. The quality of evidence was noted to be of low certainty in practice domain but moderate in the remaining outcomes. Conclusion Assessing the public’s risk perception and precautionary behaviors is essential in directing future policy and health population research regarding infection control and preventing new airborne disease outbreaks.

Irish Media Coverage of COVID-19 Evidence-Based Research Reports From one National Agency

Background: How research findings are presented through domestic news can influence behaviour and risk perceptions, particularly during emergencies such as the COVID-19 pandemic. Monitoring media communications to track misinformation and find information gaps is an important component of emergency risk communication. Therefore, this study investigated the traditional media coverage of nine selected COVID-19 evidence-based research reports and associated press releases published during the initial phases of the pandemic (April to July 2020) by one national agency. Methods: NVivo was used for summative content analysis. ‘Key messages’ from each research report were proposed and 488 broadcast, print, and online media sources were coded at the phrase level. Manifest content was coded and counted to locate patterns in the data (what and how many) while latent content was analysed to further investigate these patterns (why and how). This included the coding of the presence of political and public health actors in coverage. Results: Coverage largely did not misrepresent the results of the reports, however, selective reporting and the variability in the use of quotes from governmental and public health stakeholders changed and contextualised results in different manners than perhaps originally intended in the press release. Reports received varying levels of media attention. Coverage focused on more ‘human-interest’ stories (e.g., spread of COVID-19 by children and excess mortality) as opposed to more technical reports (e.g., focusing on viral load, antibodies, testing, etc.). Conclusion: Our findings provide a case-study of European media coverage of evidence reports produced by a national agency. Results highlighted several strengths and weaknesses of current communication efforts.

Assessments of risk of bias in systematic reviews of observational nutritional epidemiologic studies are often not appropriate or comprehensive: a methodological study

BackgroundAn essential component of systematic reviews is the assessment of risk of bias. To date, there has been no investigation of how reviews of non-randomised studies of nutritional exposures (called ‘nutritional epidemiologic studies’) assess risk of bias.ObjectiveTo describe methods for the assessment of risk of bias in reviews of nutritional epidemiologic studies.MethodsWe searched MEDLINE, EMBASE and the Cochrane Database of Systematic Reviews (Jan 2018–Aug 2019) and sampled 150 systematic reviews of nutritional epidemiologic studies.ResultsMost reviews (n=131/150; 87.3%) attempted to assess risk of bias. Commonly used tools neglected to address all important sources of bias, such as selective reporting (n=25/28; 89.3%), and frequently included constructs unrelated to risk of bias, such as reporting (n=14/28; 50.0%). Most reviews (n=66/101; 65.3%) did not incorporate risk of bias in the synthesis. While more than half of reviews considered biases due to confounding and misclassification of the exposure in their interpretation of findings, other biases, such as selective reporting, were rarely considered (n=1/150; 0.7%).ConclusionReviews of nutritional epidemiologic studies have important limitations in their assessment of risk of bias.

Protocol: Benefits and harms of remdesivir for COVID-19 in adults: A systematic review with meta-analysis

Background Effective drug treatments for Covid-19 are needed to decrease morbidity and mortality for the individual and to alleviate pressure on health care systems. Remdesivir showed promising results in early randomised trials but subsequently a large publicly funded trial has shown less favourable results and the evidence is interpreted differently in clinical guidelines. Systematic reviews of remdesivir have been published, but none have systematically searched for unpublished data, including regulatory documents, and assessed the risk of bias due to missing evidence. Methods We will conduct a systematic review of randomised trials comparing remdesivir to placebo or standard of care in any setting. We will include trials regardless of the severity of disease and we will include trials examining remdesivir for indications other than Covid-19 for harms analyses. We will search websites of regulatory agencies, trial registries, bibliographic databases, preprint servers and contact trial sponsors to obtain all available data, including unpublished clinical data, for all eligible trials. Our primary outcomes will be all-cause mortality and serious adverse events. Our secondary outcomes will be length of hospital stay, time to death, severe disease, and adverse events. We will assess the risk of bias using the Cochranes Risk of Bias 2 tool and the risk of bias due to missing evidence (e.g. publication bias, selective reporting bias) using the ROB-ME tool. Where appropriate we will synthesise study results by conducting random-effects meta-analysis. We will present our findings in a Summary of Findings table and rate the certainty of the evidence using the GRADE approach. Discussion By conducting a comprehensive systematic review including unpublished data (where available), we expect to be able to provide valuable information for patients and clinicians about the benefits and harms of remdesivir for the treatment of Covid-19. This will help to ensure optimal treatment for individual patients and optimal utilisation of health care resources. Systematic review registration CRD42021255915.

The Ethical Use of Fit Indices in Structural Equation Modeling: Recommendations for Psychologists

Fit indices provide helpful information for researchers to assess the fit of their structural equation models to their data. However, like many statistics and methods, researchers can misuse fit indices, which suggest the potential for questionable research practices that might arise during the analytic and interpretative processes. In the current paper, the author highlights two critical ethical dilemmas regarding the use of fit indices, which are (1) the selective reporting of fit indices and (2) using fit indices to justify poorly-fitting models. The author highlights the dilemmas and provides potential solutions for researchers and journals to follow to reduce these questionable research practices.

Multi-Ideology ISIS/Jihadist White Supremacist (MIWS) Dataset for Multi-Class Extremism Text Classification

Social media platforms are a popular choice for extremist organizations to disseminate their perceptions, beliefs, and ideologies. This information is generally based on selective reporting and is subjective in content. However, the radical presentation of this disinformation and its outreach on social media leads to an increased number of susceptible audiences. Hence, detection of extremist text on social media platforms is a significant area of research. The unavailability of extremism text datasets is a challenge in online extremism research. The lack of emphasis on classifying extremism text into propaganda, radicalization, and recruitment classes is a challenge. The lack of data validation methods also challenges the accuracy of extremism detection. This research addresses these challenges and presents a seed dataset with a multi-ideology and multi-class extremism text dataset. This research presents the construction of a multi-ideology ISIS/Jihadist White supremacist (MIWS) dataset with recent tweets collected from Twitter. The presented dataset can be employed effectively and importantly to classify extremist text into popular types like propaganda, radicalization, and recruitment. Additionally, the seed dataset is statistically validated with a coherence score of Latent Dirichlet Allocation (LDA) and word mover’s distance using a pretrained Google News vector. The dataset shows effectiveness in its construction with good coherence scores within a topic and appropriate distance measures between topics. This dataset is the first publicly accessible multi-ideology, multi-class extremism text dataset to reinforce research on extremism text detection on social media platforms.