Effectiveness and safety of non-steroidal anti-inflammatory drugs and opioid treatment for knee and hip osteoarthritis: network meta-analysis.

OBJECTIVE To assess the effectiveness and safety of different preparations and doses of non-steroidal anti-inflammatory drugs (NSAIDs), opioids, and paracetamol for knee and hip osteoarthritis pain and physical function to enable effective and safe use of these drugs at their lowest possible dose. DESIGN Systematic review and network meta-analysis of randomised trials. DATA SOURCES Cochrane Central Register of Controlled Trials (CENTRAL), Medline, Embase, regulatory agency websites, and ClinicalTrials.gov from inception to 28 June 2021. ELIGIBILITY CRITERIA FOR SELECTING STUDIES Randomised trials published in English with ≥100 patients per group that evaluated NSAIDs, opioids, or paracetamol (acetaminophen) to treat osteoarthritis. OUTCOMES AND MEASURES The prespecified primary outcome was pain. Physical function and safety outcomes were also assessed. REVIEW METHODS Two reviewers independently extracted outcomes data and evaluated the risk of bias of included trials. Bayesian random effects models were used for network meta-analysis of all analyses. Effect estimates are comparisons between active treatments and oral placebo. RESULTS 192 trials comprising 102 829 participants examined 90 different active preparations or doses (68 for NSAIDs, 19 for opioids, and three for paracetamol). Five oral preparations (diclofenac 150 mg/day, etoricoxib 60 and 90 mg/day, and rofecoxib 25 and 50 mg/day) had ≥99% probability of more pronounced treatment effects than the minimal clinically relevant reduction in pain. Topical diclofenac (70-81 and 140-160 mg/day) had ≥92.3% probability, and all opioids had ≤53% probability of more pronounced treatment effects than the minimal clinically relevant reduction in pain. 18.5%, 0%, and 83.3% of the oral NSAIDs, topical NSAIDs, and opioids, respectively, had an increased risk of dropouts due to adverse events. 29.8%, 0%, and 89.5% of oral NSAIDs, topical NSAIDs, and opioids, respectively, had an increased risk of any adverse event. Oxymorphone 80 mg/day had the highest risk of dropouts due to adverse events (51%) and any adverse event (88%). CONCLUSIONS Etoricoxib 60 mg/day and diclofenac 150 mg/day seem to be the most effective oral NSAIDs for pain and function in patients with osteoarthritis. However, these treatments are probably not appropriate for patients with comorbidities or for long term use because of the slight increase in the risk of adverse events. Additionally, an increased risk of dropping out due to adverse events was found for diclofenac 150 mg/day. Topical diclofenac 70-81 mg/day seems to be effective and generally safer because of reduced systemic exposure and lower dose, and should be considered as first line pharmacological treatment for knee osteoarthritis. The clinical benefit of opioid treatment, regardless of preparation or dose, does not outweigh the harm it might cause in patients with osteoarthritis. SYSTEMATIC REVIEW REGISTRATION PROSPERO number CRD42020213656

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

In COVID-19 Health Messaging, Loss Framing Increases Anxiety with Little-to-No Concomitant Benefits: Experimental Evidence from 84 Countries

The COVID-19 pandemic (and its aftermath) highlights a critical need to communicate health information effectively to the global public. Given that subtle differences in information framing can have meaningful effects on behavior, behavioral science research highlights a pressing question: Is it more effective to frame COVID-19 health messages in terms of potential losses (e.g., "If you do not practice these steps, you can endanger yourself and others") or potential gains (e.g., "If you practice these steps, you can protect yourself and others")? Collecting data in 48 languages from 15,929 participants in 84 countries, we experimentally tested the effects of message framing on COVID-19-related judgments, intentions, and feelings. Loss- (vs. gain-) framed messages increased self-reported anxiety among participants cross-nationally with little-to-no impact on policy attitudes, behavioral intentions, or information seeking relevant to pandemic risks. These results were consistent across 84 countries, three variations of the message framing wording, and 560 data processing and analytic choices. Thus, results provide an empirical answer to a global communication question and highlight the emotional toll of loss-framed messages. Critically, this work demonstrates the importance of considering unintended affective consequences when evaluating nudge-style interventions

A global experiment on motivating social distancing during the COVID-19 pandemic

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. On the other hand, the autonomy-supportive message lowered feelings of defiance compared with the controlling message, but the controlling message did not differ from receiving no message at all. Unexpectedly, messages did not influence autonomous motivation (a highly internalized form of motivation relying on one’s core values) or behavioral intentions. Results supported hypothesized associations between people’s existing autonomous and controlled motivations and self-reported behavioral intentions to engage in social distancing. Controlled motivation was associated with more defiance and less long-term behavioral intention to engage in social distancing, whereas autonomous motivation was associated with less defiance and more short- and long-term intentions to social distance. Overall, this work highlights the potential harm of using shaming and pressuring language in public health communication, with implications for the current and future global health challenges