This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Climate change is altering our world as we know it. Unfortunately, there’s no one-size-fits-all solution for making our environment resilient. From planners to scientists to farmers and ranchers, the lens through which climate change is viewed is dynamic. So how can anyone plan the best course of action with the best available data? Researchers led by Aavudai Anandhi at Florida A&M University might have just the right tool for the job. Their evidence-based approach combines three climate research methods to tailor action plans to the needs of a given ecosystem—whether that’s an entire country or state, or a single community, and whether for now or for the future. The approach begins with gathering evidence of climate change over a geographical region—the state of Florida for example. That’s done by pulling from trusted research to understand how factors like temperature or rainfall have evolved or are projected to evolve over time..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Climate change is altering our world as we know it Despite general guidelines for mitigating harmful changes Climate change affects different areas in different ways And those effects aren’t always clear Now, a new evidence-based tool could provide the resolution to tailor plans of action around the globe It starts with a meta-analysis that gathers climate change data for a given ecosystem That data provides the input needed to draw conclusions about future climate trends, or scenarios Such as increases or decreases in temperature The effects those changes are likely to set in motion are then linked together in a causal chain Which can reveal how crops, natural resources, or animal species will fare amid climate change Although the tool becomes limited when data for a given area are scarce It could be a powerful new way to develop custom-made plans for fighting climate change.."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

To increase transparency in research, the International Committee of Medical Journal Editors required, in 2005, prospective registration of clinical trials as a condition to publication. However, many trials remain unregistered or retrospectively registered. We aimed to assess the association between trial prospective registration and treatment effect estimates. Methods This is a meta-epidemiological study based on all Cochrane reviews published between March 2011 and September 2014 with meta-analyses of a binary outcome including three or more randomised controlled trials published after 2006. We extracted trial general characteristics and results from the Cochrane reviews. For each trial, we searched for registration in the report’s full text, contacted the corresponding author if not reported and searched ClinicalTrials.gov and the International Clinical Trials Registry Platform in case of no response. We classified each trial as prospectively registered (i.e. registered before the start date); retrospectively registered, distinguishing trials registered before and after the primary completion date; and not registered. Treatment effect estimates of prospectively registered and other trials were compared by the ratio of odds ratio (ROR) (ROR <1 indicates larger effects in trials not prospectively registered). Results We identified 67 meta-analyses (322 trials). Overall, 225/322 trials (70 %) were registered, 74 (33 %) prospectively and 142 (63 %) retrospectively; 88 were registered before the primary completion date and 54 after. Unregistered or retrospectively registered trials tended to show larger treatment effect estimates than prospectively registered trials (combined ROR = 0.81, 95 % CI 0.65–1.02, based on 32 contributing meta-analyses). Trials unregistered or registered after the primary completion date tended to show larger treatment effect estimates than those registered before this date (combined ROR = 0.84, 95 % CI 0.71–1.01, based on 43 contributing meta-analyses). Conclusions Lack of trial prospective registration may be associated with larger treatment effect estimates.

A focus on novel, confirmatory, and statistically significant results leads to substantial bias in the scientific literature. One type of bias, known as “p-hacking,” occurs when researchers collect or select data or statistical analyses until nonsignificant results become significant. Here, we use text-mining to demonstrate that p-hacking is widespread throughout science. We then illustrate how one can test for p-hacking when performing a meta-analysis and show that, while p-hacking is probably common, its effect seems to be weak relative to the real effect sizes being measured. This result suggests that p-hacking probably does not drastically alter scientific consensuses drawn from meta-analyses.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Laying hens are predominantly kept in small battery cages. These cages are so small, in fact, that the birds usually cannot extend their wings or exhibit other natural behaviors like foraging and nesting. Public criticism of this practice is driving egg producers to change to higher welfare cage-free aviaries. But there have been some claims that cage-free systems could have higher mortality rates than battery cages. A recent meta-analysis used data from 6,040 commercial flocks – 176 million birds – spanning 16 countries to investigate this claim. They found that, while mortality in cage-free flocks was higher in the past, it decreased over time. In fact, data from recent years shows no difference in mortality between caged and cage-free systems. The decrease in mortality likely reflects an increase in flock managers' experience. More research is needed into causes of death in different egg production systems..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Diabetes and chronic kidney disease are common comorbid conditions, with reports suggesting that chronic kidney disease affects up to half of all patients with type 2 diabetes. Renal impairment complicates the management of diabetes because it increases the risk of heart disease and excessively low blood glucose levels called hypoglycemia. These risks limit the options for glucose-lowering treatment. Insulin remains a viable treatment option for people with diabetes and chronic kidney disease. However, there is limited data from large studies that compare how different insulins impact treatment outcomes in this patient population. A recent patient-level meta-analysis of the phase III EDITION trials helps bridge this data gap by investigating the impact of renal function on the safety and efficacy of insulin glargine 100 versus the newer insulin glargine 300..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Online resource for running a meta-analysis. Base on R and the package metafor.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Increasing evidence of gut microbe-metabolite-host health interactions has prompted increasing research on the human gut microbiome and metabolome. Statistical and machine learning-based methods have been widely used to identify microbial metabolites that can be modulated to improve gut health, but whether the findings of individual studies are applicable across studies remains unclear. In a recent meta-analysis, researchers searched for metabolites whose levels in the human gut could be reliably predicted from microbiome composition, using a machine learning approach with data processed from 1733 samples in 10 independent studies. While the predictability of many metabolites varied considerably among studies, the search identified 97 robustly well-predicted metabolites that were involved in processes such as bile acid transformation and polyamine metabolism..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Numerous biases are believed to affect the scientific literature, but their actual prevalence across disciplines is unknown. To gain a comprehensive picture of the potential imprint of bias in science, we probed for the most commonly postulated bias-related patterns and risk factors, in a large random sample of meta-analyses taken from all disciplines. The magnitude of these biases varied widely across fields and was overall relatively small. However, we consistently observed a significant risk of small, early, and highly cited studies to overestimate effects and of studies not published in peer-reviewed journals to underestimate them. We also found at least partial confirmation of previous evidence suggesting that US studies and early studies might report more extreme effects, although these effects were smaller and more heterogeneously distributed across meta-analyses and disciplines. Authors publishing at high rates and receiving many citations were, overall, not at greater risk of bias. However, effect sizes were likely to be overestimated by early-career researchers, those working in small or long-distance collaborations, and those responsible for scientific misconduct, supporting hypotheses that connect bias to situational factors, lack of mutual control, and individual integrity. Some of these patterns and risk factors might have modestly increased in intensity over time, particularly in the social sciences. Our findings suggest that, besides one being routinely cautious that published small, highly-cited, and earlier studies may yield inflated results, the feasibility and costs of interventions to attenuate biases in the literature might need to be discussed on a discipline-specific and topic-specific basis.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"A new study investigated the efficacy of micronized purified flavonoid fraction, or MPFF, in the treatment of patients with hemorrhoidal disease. Hemorrhoidal disease affects an estimated 4.4% of the global population. The disease occurs when hemorrhoids become inflamed and swollen with venous blood. While severe cases are typically treated with surgery, banding, or other outpatient procedures, some cases can be treated conservatively, through diet, lifestyle modification, topical treatments, or agents known as veno-active drugs. Veno-active drugs are designed to reduce inflammation and reduce pressure in veins, improving their overall tone and translating to symptom relief in patients. One evidence based veno-active treatment for hemorrhoids is MPFF..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"When it comes to immune functioning, cancers and autoimmune diseases are opposites. The key immune-related defect in cancer is subverting and evading the immune system, while autoimmune disease is, broadly speaking, an overactive immune system targeting the self. The immune system and the gut microbial community have a reciprocal influence on each other. Therefore, it is possible that cancers and autoimmune diseases have analogous but inverted impacts on the gut microbiome. To test this, researchers conducted a systematic literature review. The included studies covered over 10,000 people from 27 countries. This data revealed a set of microbiome features that show consistent, opposite changes in cancers compared to autoimmune diseases. Fusobacterium and Peptostreptococcus were the most consistently increased bacterial genera in cancer cases. While Bacteroides stood out as a group increased in autoimmune disease and decreased in cancers..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Objective To investigate the replication validity of biomedical association studies covered by newspapers. Methods We used a database of 4723 primary studies included in 306 meta-analysis articles. These studies associated a risk factor with a disease in three biomedical domains, psychiatry, neurology and four somatic diseases. They were classified into a lifestyle category (e.g. smoking) and a non-lifestyle category (e.g. genetic risk). Using the database Dow Jones Factiva, we investigated the newspaper coverage of each study. Their replication validity was assessed using a comparison with their corresponding meta-analyses. Results Among the 5029 articles of our database, 156 primary studies (of which 63 were lifestyle studies) and 5 meta-analysis articles were reported in 1561 newspaper articles. The percentage of covered studies and the number of newspaper articles per study strongly increased with the impact factor of the journal that published each scientific study. Newspapers almost equally covered initial (5/39 12.8%) and subsequent (58/600 9.7%) lifestyle studies. In contrast, initial non-lifestyle studies were covered more often (48/366 13.1%) than subsequent ones (45/3718 1.2%). Newspapers never covered initial studies reporting null findings and rarely reported subsequent null observations. Only 48.7% of the 156 studies reported by newspapers were confirmed by the corresponding meta-analyses. Initial non-lifestyle studies were less often confirmed (16/48) than subsequent ones (29/45) and than lifestyle studies (31/63). Psychiatric studies covered by newspapers were less often confirmed (10/38) than the neurological (26/41) or somatic (40/77) ones. This is correlated to an even larger coverage of initial studies in psychiatry. Whereas 234 newspaper articles covered the 35 initial studies that were later disconfirmed, only four press articles covered a subsequent null finding and mentioned the refutation of an initial claim. Conclusion Journalists preferentially cover initial findings although they are often contradicted by meta-analyses and rarely inform the public when they are disconfirmed.

Psychology is designed to meet scope and sequence requirements for the single-semester introduction to psychology course. The book offers a comprehensive treatment of core concepts, grounded in both classic studies and current and emerging research. The text also includes coverage of the DSM-5 in examinations of psychological disorders. Psychology incorporates discussions that reflect the diversity within the discipline, as well as the diversity of cultures and communities across the globe.Senior Contributing AuthorsRose M. Spielman, Formerly of Quinnipiac UniversityContributing AuthorsKathryn Dumper, Bainbridge State CollegeWilliam Jenkins, Mercer UniversityArlene Lacombe, Saint Joseph's UniversityMarilyn Lovett, Livingstone CollegeMarion Perlmutter, University of Michigan

By the end of this section, you will be able to:Understand what is meant by consciousnessExplain how circadian rhythms are involved in regulating the sleep-wake cycle, and how circadian cycles can be disruptedDiscuss the concept of sleep debt

P values represent a widely used, but pervasively misunderstood and fiercely contested method of scientific inference. Display items, such as figures and tables, often containing the main results, are an important source of P values. We conducted a survey comparing the overall use of P values and the occurrence of significant P values in display items of a sample of articles in the three top multidisciplinary journals (Nature, Science, PNAS) in 2017 and, respectively, in 1997. We also examined the reporting of multiplicity corrections and its potential influence on the proportion of statistically significant P values. Our findings demonstrated substantial and growing reliance on P values in display items, with increases of 2.5 to 14.5 times in 2017 compared to 1997. The overwhelming majority of P values (94%, 95% confidence interval [CI] 92% to 96%) were statistically significant. Methods to adjust for multiplicity were almost non-existent in 1997, but reported in many articles relying on P values in 2017 (Nature 68%, Science 48%, PNAS 38%). In their absence, almost all reported P values were statistically significant (98%, 95% CI 96% to 99%). Conversely, when any multiplicity corrections were described, 88% (95% CI 82% to 93%) of reported P values were statistically significant. Use of Bayesian methods was scant (2.5%) and rarely (0.7%) articles relied exclusively on Bayesian statistics. Overall, wider appreciation of the need for multiplicity corrections is a welcome evolution, but the rapid growth of reliance on P values and implausibly high rates of reported statistical significance are worrisome.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"What’s the best way to control pain after a cesarean section? Women who give birth by C-section typically receive a spinal anesthetic, usually with a small amount of morphine to control pain after surgery. A more novel technique known as the quadratus lumborum block, in which anesthetic is injected into the waist area, might be able to provide even more pain relief. But the method hasn’t been consistently studied. Now, a meta-analysis from researchers from the Universities of Ottawa and Toronto in Canada and the Ohio State University finds that the quadratus lumborum block doesn’t offer a benefit on top of or in place of morphine -- but it does improve pain control when morphine isn’t used. Some scientists have reported that the quadratus lumborum block improves pain control after a C-section. Because the anesthetic is given next to the quadratus lumborum muscle, the block might be able to treat the somatic pain of the C-section incision along with the surgery’s visceral pain..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Background The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias and outcome reporting bias have been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. Methodology/Principal Findings In this update, we review and summarise the evidence from cohort studies that have assessed study publication bias or outcome reporting bias in randomised controlled trials. Twenty studies were eligible of which four were newly identified in this update. Only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Fifteen of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7). In comparing trial publications to protocols, we found that 40–62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. Conclusions This update does not change the conclusions of the review in which 16 studies were included. Direct empirical evidence for the existence of study publication bias and outcome reporting bias is shown. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be concentrated on improving the reporting of trials.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Untreated portal vein thrombosis (PVT) leads to the onset or worsening of portal hypertension Anticoagulation is the mainstay of PVT treatment but its efficacy is not ideal Transjugular intrahepatic portosystemic shunt (TIPSS) can be used for portal vein recanalization after thrombosis This systematic review and meta-analysis evaluated published data on the efficacy and safety of endovascular therapy in PVT The results from 399 patients showed that TIPSS placement was feasible in 95% Major complications occurred in 10%, and additional catheter‐directed thrombolysis was associated with more complications The portal vein recanalization rate was 79% at 12 months The results were limited by a small sample size, largely heterogeneous data and the use of non-controlled, retrospective cohorts This study concluded that TIPSS for PVT recanalization was highly feasible, effective, and safe Randomized trials comparing TIPSS to anticoagulation are therefore needed These future studies will guide c.."

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There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.