The scientific community’s response to COVID-19 has resulted in a large volume of research moving through the publication pipeline at extraordinary speed, with a median time from receipt to acceptance of 6 days for journal articles. Although the nature of this emergency warrants accelerated publishing, measures are required to safeguard the integrity of scientific evidence.

Purpose: Lipid-lowering medications are often prescribed to decrease the risk of micro- and macro-cardiovascular complications related to dyslipidaemia. Despite widespread prescription of lipid-lowering drugs, including statins, adherence to therapy is a challenge worldwide. This systematic review of reviews aimed to conduct a critical appraisal and synthesis of review findings and to provide an overview of the factors that were found to affect adherence to lipid-lowering drugs, focusing on statins, in the reviews. Patients and Methods: A systematic review methodology was used. MEDLINE, Embase, and Epistemonikos databases were searched for relevant publications. AMSTAR 2 criteria were used to assess the quality of the selected publications. Results: From a total of 763 screened publications, 9 met all inclusion criteria and were included in this synthesis. Several factors were identified as being associated with adherence to lipid-lowering agents. Among them, high socio-economic and educational position, and middle age had a positive effect on adherence to lipid-lowering agents. Contrary, female sex, older and younger age, non-white race, low socio-economic position, high co-payments, being a new statin user, comorbidities, side effects, regimen complexity, type and intensity of statin dose, smoking, alcohol consumption, imperceptible benefits, and medical distrust contributed to non-adherence. The overall quality of the included reviews was considered critically low to moderate. Conclusion: This review of reviews has evaluated the impact of factors on adherence statins. Further research related to modifiable predictors for non-adherence is warranted.

Background: Systematic reviews are essential but time‐consuming and expensive. Large language models (LLMs) and artificial intelligence (AI) tools could potentially automate data extraction, but no comprehensive workflow has been tested for different review types. Objective: To evaluate Elicit's and ChatGPT's abilities to extract data from journal articles as a replacement for one of two human data extractors in systematic reviews. Methods: Human‐extracted data from three systematic reviews (30 articles in total) was compared to data extracted by Elicit and ChatGPT. The AI tools extracted population characteristics, study design, and review‐specific variables. Performance metrics were calculated against human double‐extracted data as the gold standard, followed by a detailed error analysis. Results: Precision, recall and F1‐score were all 92% for Elicit and 91%, 89% and 90% for ChatGPT. Recall was highest for study design (Elicit: 100%; ChatGPT: 90%) and population characteristics (Elicit: 100%; ChatGPT: 97%), while review‐specific variables achieved 77% in Elicit and 80% in ChatGPT. Elicit had four instances of confabulation while ChatGPT had three. There was no significant difference between the two AI tools' performance (recall difference: 3.3% points, 95% CI: –5.2%–11.9%, p = 0.445). Conclusion: AI tools demonstrated high and similar performance in data extraction compared to human reviewers, particularly for standardized variables. Error analysis revealed confabulations in 4% of data points. We propose adopting AI‐assisted extraction to replace the second human extractor, with the second human instead focusing on reconciling discrepancies between AI and the primary human extractor.

Background: People living with chronic conditions such as diabetes turn to peers on social media to obtain and share information. Although social media use has grown dramatically in the past decade, little is known about its implications for the relationships between people with chronic conditions and health care professionals (HCPs). Objective: We aimed to systematically review the content and quality of studies examining what the retrieval and sharing of information by people with chronic conditions on social media implies for their relationships with HCPs. Methods: We conducted a search of studies in MEDLINE (Ovid), Embase (Ovid), PsycINFO (Ovid), and CINAHL (EBSCO). Eligible studies were primary studies; examined social media use; included adults with any type of diabetes, cardiovascular diseases that are closely linked with diabetes, obesity, hypertension, or dyslipidemia; and reported on the implications for people with chronic conditions–HCP relationships when people with chronic conditions access and share information on social media. We used the Mixed Methods Appraisal Tool version 2018 to assess the quality of the studies, and the included studies were narratively synthesized. Results: Of the 3111 screened studies, 17 (0.55%) were included. Most studies (13/17, 76%) were of low quality. The narrative synthesis identified implications for people with chronic conditions–HCP relationships when people with chronic conditions access and share information on social media, divided into 3 main categories with 7 subcategories. These categories of implications address how the peer interactions of people with chronic conditions on social media can influence their communication with HCPs, how people with chronic conditions discuss advice and medical information from HCPs on social media, and how relationships with HCPs are discussed by people with chronic conditions on social media. The implications are illustrated collectively in a conceptual model. Conclusions: More evidence is needed to draw conclusions, but the findings indicate that the peer interactions of people with chronic conditions on social media are implicated in the ways in which people with chronic conditions equip themselves for clinical consultations, evaluate the information and advice provided by HCPs, and manage their relationships with HCPs. Future populations with chronic conditions will be raised in a digital world, and social media will likely remain a strategy for obtaining support and information. However, the generally low quality of the studies included in this review points to the relatively immature state of research exploring social media and its implications for people with chronic conditions–HCP relationships. Better study designs and methods for conducting research on social media are needed to generate robust evidence.

The aim of this systematic review and meta-analysis was to examine the effects of plant-based diets on markers of insulin sensitivity in people with overweight/obesity, prediabetes, or type 2 diabetes (T2D). A systematic literature search in MEDLINE, Embase, CINAHL, and CENTRAL was conducted, and randomised controlled trials (RCTs) investigating the effect of plant-based diets (vegan, ovo-vegetarian, lacto-vegetarian, and lacto-ovo-vegetarian) for ≥14 d on markers of insulin sensitivity in adults (≥18 years) with BMI ≥ 25 kg/m², prediabetes, or T2D were eligible. We identified eight RCTs, including 716 participants. In comparison with control diets, plant-based diets improved Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) (−0.97, 95% confidence interval (CI) (−1.67, −0.27), p = 0.007) and fasting insulin (−4.13 µU/mL, 95% CI (−7.22, −1.04), p = 0.009) in people with overweight/obesity. In people with prediabetes, one study compared vegan and vegetarian diets and found no difference in HOMA-IR, or fasting insulin. One study of people with T2D reported no difference in immunoreactive insulin and metabolic glucose clearance compared with a conventional diabetes diet. In conclusion, adhering to plant-based diets for ≥14 d improved HOMA-IR and fasting insulin in people with overweight/obesity. Long-term RCTs are needed to determine whether plant-based diets can result in prolonged improvements in insulin sensitivity in people at risk of or with T2D.

Objectives: Family involvement plays a key role in diabetes management. Problems and challenges related to type 2-diabetes often affect the whole family, and relatives are at increased risk of developing diabetes themselves. We highlight these issues in our objectives: (1) to uncover specific family problems associated with mutual involvement in life with type 2-diabetes and (2) to analytically look at ways of approaching these problems in healthcare settings. Methods: Qualitative data were gathered in participatory problem assessment workshops. The data were analysed in three rounds using radical hermeneutics. Results: Problems were categorized in six domains: knowledge, communication, support, everyday life, roles and worries. The final cross-analysis focusing on the link between family identity and healthcare authenticity provided information on how the six domains can be approached in healthcare settings. Conclusion: The study generated important knowledge about problems associated with family involvement in life with type 2 diabetes and about how family involvement can be supported in healthcare practice.