Background Spin is the misrepresentation of study findings, which may positively or negatively influence the reader’s interpretation of the results. Little is known regarding the prevalence of spin in abstracts of systematic reviews, specifically systematic reviews pertaining to the management and treatment of acne vulgaris. Objective The primary objective of this study was to characterize and determine the frequency of the most severe forms of spin in systematic review abstracts and to evaluate whether various study characteristics were associated with spin. Methods Using a cross-sectional study design, we searched PubMed and EMBASE for systematic reviews focusing on the management and treatment of acne vulgaris. Our search returned 316 studies, of which 36 were included in our final sample. To be included, each systematic review must have addressed either pharmacologic or nonpharmacologic treatment of acne vulgaris. These studies were screened, and data were extracted in duplicate by two blinded investigators. We analyzed systematic review abstracts for the nine most severe types of spin. Results Spin was present in 31% (11/36) of abstracts. A total of 12 examples of spin were identified in the 11 abstracts containing spin, with one abstract containing two instances of spin. The most common type of spin, selective reporting of or overemphasis on efficacy outcomes or analysis favoring the beneficial effect of the experimental intervention, was identified five times (5/12, 42%). A total of 44% (16/36) of studies did not report a risk of bias assessment. Of the 11 abstracts containing spin, six abstracts (55%) had not reported a risk of bias assessment or performed a risk of bias assessment but did not discuss it. Spin in abstracts was not significantly associated with a specific intervention type, funding source, or journal impact factor. Conclusions Spin is present in the abstracts of systematic reviews and meta-analyses covering the treatment of acne vulgaris. This paper raises awareness of spin in abstracts and emphasizes the importance of its recognition, which may lead to fewer incidences of spin in future studies.

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Editorials are not included in this analysis. x 2 determines associations between PCL adherence (yes/no) to the categorical study characteristics. No results listed here were statistically significant (p , 0.05).

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Introduction: Following Stay-at-Home (SAH) orders issued for COVID-19, state-level economic concerns increased and many let these orders expire. As a method to measure public preparedness, we sought to explore the association between public interest in preventive measures and easing of SAH orders—specifically the increases in COVID-19 cases and fatalities after their expiration. Methods: Search volume collected from Google Trends for “hand sanitizer,” “social distancing,” “COVID testing,” and “contact tracing,” for each state. Bivariate correlations were computed to analyze associations between public interest in preventive measures, changes in confirmed COVID-19 cases after SAH expirations, COVID-19 case-fatality rates, and by-state presidential voting percentages. Results: Higher interest in preventative measures was associated with lower rates of confirmed cases after SAH orders had expired (r = -.33), higher state-wide deaths per capita (r = .42), case-fatality rates (r = .60). Moderate to strong negative correlations were found between states’ percentage of voters supporting the Republican nominee in 2016 and POQ for average preventative measures (r = -.77). Conclusion: Our investigation shows that increased public interest in COVID-19 prevention was associated with longer SAH orders and less COVID-19 cases after the SAH orders’ expiration; however, it was also associated with higher case-fatality rates.

Background The emergency authorization of COVID-19 vaccines has offered the first means of long-term protection against COVID-19–related illness since the pandemic began. It is important for health care professionals to understand commonly held COVID-19 vaccine concerns and to be equipped with quality information that can be used to assist in medical decision-making. Objective Using Google’s RankBrain machine learning algorithm, we sought to characterize the content of the most frequently asked questions (FAQs) about COVID-19 vaccines evidenced by internet searches. Secondarily, we sought to examine the information transparency and quality of sources used by Google to answer FAQs on COVID-19 vaccines. Methods We searched COVID-19 vaccine terms on Google and used the “People also ask” box to obtain FAQs generated by Google’s machine learning algorithms. FAQs are assigned an “answer” source by Google. We extracted FAQs and answer sources related to COVID-19 vaccines. We used the Rothwell Classification of Questions to categorize questions on the basis of content. We classified answer sources as either academic, commercial, government, media outlet, or medical practice. We used the Journal of the American Medical Association’s (JAMA’s) benchmark criteria to assess information transparency and Brief DISCERN to assess information quality for answer sources. FAQ and answer source type frequencies were calculated. Chi-square tests were used to determine associations between information transparency by source type. One-way analysis of variance was used to assess differences in mean Brief DISCERN scores by source type. Results Our search yielded 28 unique FAQs about COVID-19 vaccines. Most COVID-19 vaccine–related FAQs were seeking factual information (22/28, 78.6%), specifically about safety and efficacy (9/22, 40.9%). The most common source type was media outlets (12/28, 42.9%), followed by government sources (11/28, 39.3%). Nineteen sources met 3 or more JAMA benchmark criteria with government sources as the majority (10/19, 52.6%). JAMA benchmark criteria performance did not significantly differ among source types (χ24=7.40; P=.12). One-way analysis of variance revealed a significant difference in mean Brief DISCERN scores by source type (F4,23=10.27; P<.001). Conclusions The most frequently asked COVID-19 vaccine–related questions pertained to vaccine safety and efficacy. We found that government sources provided the most transparent and highest-quality web-based COVID-19 vaccine–related information. Recognizing common questions and concerns about COVID-19 vaccines may assist in improving vaccination efforts.

Introduction: One method of monitoring public preparedness is through measuring public interest in preventive measures. The objective of this study was to analyze public interest in the coronavirus disease 2019 (COVID-19) preventive measures and to identify variables associated with timely stay-at-home (SAH) orders issued by governors. Methods: State-level search volume was collected from Google Trends. Average preventive measure interest was calculated for the query terms “hand sanitizer,” “hand washing,” “social distancing,” and “COVID testing.” We then calculated the delay in statewide SAH orders from March 1, 2020, to the date of issuance and by-state presidential voting percentage. Bivariate correlations were computed to assess the relationship between interest in preventive measures and SAH order delay. Results: The correlation between average preventive measure interest and length of time before the SAH order was placed was −0.47. Average preventive measure interest was also inversely related to voting for a Republican presidential nominee in the 2016 election (R = −0.75), the latter of which was positively associated with longer delays in SAH orders (R = 0.48). Conclusions: States with greater public interest in COVID-19 preventive measures were inversely related to governor issuance of timely SAH orders. Increasing public interest in preventive measures may slow the spread of the virus that causes COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), by improving preparedness.

<b><i>Background:</i></b> Spin – the misrepresentation of a study’s results – has been identified in abstracts of studies focused on a variety of disorders from multiple fields of medicine. <b><i>Objectives:</i></b> This study’s primary objective was to evaluate the abstracts of systematic reviews and meta-analyses focused on the treatment of atopic dermatitis for the nine most severe forms of spin. <b><i>Methods:</i></b> We systematically searched Embase and MEDLINE for systematic reviews of atopic dermatitis therapies. Screening and data extraction occurred in a masked, duplicate fashion. Each included study was evaluated for the nine most severe types of spin and other study characteristics. <b><i>Results:</i></b> Our searches retrieved 2,456 studies, of which 113 were included for data extraction. Spin was found in 74.3% of our included studies (84/113). Spin type 6 occurred most frequently (68/113, 60.2%). Spin types 1, 2, and 9 were not identified. All industry-funded systematic reviews contained spin in their abstract. The presence of spin was not associated with any specific study characteristics, including the methodological quality of the study. <b><i>Conclusions:</i></b> Severe forms of spin were found in the majority of abstracts for systematic reviews of atopic dermatitis treatments. Steps should be taken to prevent spin to improve the quality of reporting in abstracts.