As the Chat Generative Pre-trained Transformer (ChatGPT) achieves increased proficiency in diverse language tasks, its potential implications for academic integrity and plagiarism risks have become ...concerning. Traditional plagiarism detection tools primarily analyze text passages, which may fall short when identifying machine-generated text. This study aims to introduce a method that uses both prompts and essays to differentiate between machine-generated and human-written text, with the goal of enhancing classification accuracy and addressing concerns of academic integrity. Leveraging a dataset of student-written essays responding to eight distinct prompts, we generated comparable essays with ChatGPT. Similarity scores within machine-generated essays (“within” scores) and between human-written and machine-generated essays (“between” scores) were computed. Subsequently, we used the percentile scores of the “between” scores within the “within” scores distribution to gauge the probability of an essay being machine-generated. Our proposed method achieved high classification accuracy, with an AUC score of 0.991, a false positive rate of 0.01, and a false negative rate of 0.037 in the test set. This validates its effectiveness in distinguishing between machine-generated and human-written essays and shows that it outperforms existing approaches based solely on text passages. This research presents a straightforward and effective method to detect machine-generated essays using prompts, providing a reliable solution to maintain academic integrity in the era of advanced language models like ChatGPT. Nevertheless, the method is not without its limitations, warranting further research to investigate its performance across diverse educational contexts, various prompts, and different model hyperparameters.
As a primary source of added sugars in the US diet, sugar-sweetened beverage (SSB) consumption is presumed to contribute to obesity prevalence and poor oral health. We systematically synthesized and ...quantified evidence from US-based natural experiments concerning the impact of SSB taxes on beverage prices, sales, purchases, and consumption.
A keyword and reference search was performed in PubMed, Web of Science, Cochrane Library, Scopus, and EconLit from the inception of an electronic bibliographic database to Oct 31, 2022. Meta-analysis was conducted to estimate the pooled effect of soda taxes on SSB consumption, prices, passthrough rate, and purchases.
Twenty-six natural experiments, all adopting a difference-in-differences approach, were included. Studies assessed soda taxes in Berkeley, Oakland, and San Francisco in California, Philadelphia in Pennsylvania, Boulder in Colorado, Seattle in Washington, and Cook County in Illinois. Tax rates ranged from 1 to 2 ¢/oz. The imposition of the soda tax was associated with a 1.06 ¢/oz. (95% confidence interval CI = 0.90, 1.22) increase in SSB prices and a 27.3% (95% CI = 19.3, 35.4%) decrease in SSB purchases. The soda tax passthrough rate was 79.7% (95% CI = 65.8, 93.6%). A 1 ¢/oz. increase in soda tax rate was associated with increased prices of SSBs by 0.84 ¢/oz (95% CI = 0.33, 1.35).
Soda taxes could be effective policy leverage to nudge people toward purchasing and consuming fewer SSBs. Future research should examine evidence-based classifications of SSBs, targeted use of revenues generated by taxes to reduce health and income disparities, and the feasibility of redesigning the soda tax to improve efficiency.
•We systematically synthesized the influence of state laws governing school physical education (PE) on PE attendance and physical activity (PA) in class and throughout the day among students in the ...USA.•Seventeen studies were included in the review and 5 in the meta-analyses.•The presence and strength of state PE laws positively affected PE attendance and the frequency and duration of PA during PE classes and throughout the school day.•State PE laws affected girls’ PA more than boys’.•Differing aspects of state PE laws affected students’ PE attendance differently.•Disparities in the implementation of state PE laws existed across schools.
This study systematically synthesized and quantified the relationship linking state laws governing school physical education (PE) to PE attendance and physical activity (PA) in class and throughout the day and week among students in the USA.
A keyword search was performed in PubMed, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Academic Search Complete, and EconLit. Meta-analyses were performed to estimate the effects of state PE laws.
A total of 17 studies were included in the review, and five contributed to the meta-analyses. A total of 8 studies used nationally representative school- or student-level data, three focused on multiple states, and the remaining six examined the PE laws of a single state. The presence and strength of state PE laws were positively associated with PE attendance and the frequency and duration of PA during PE classes and throughout the school day. Compared to those residing in states with weak or no PE laws, students in states with strong PE laws had an additional 0.2 days (95% confidence interval (95%CI): 0.1–0.4) of PE attendance per week and spent an additional 33.9 min (95%CI: 22.7–45.0) participating PE classes per week. State PE laws affected girls’ PA more than boys’. Different aspects of state PE laws tended to affect students’ PE attendance differently. Disparities in the implementation of state PE laws existed across schools.
Future studies should adopt objective measures on PE and PA participation and examine the roles schools and districts play in mediating the effect of state PE laws on students’ PE attendance and PA.
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Abstract Purpose Media exaggerations of health research may confuse readers’ understanding, erode public trust in science and medicine, and cause disease mismanagement. This study built artificial ...intelligence (AI) models to automatically identify and correct news headlines exaggerating obesity-related research findings. Design/methodology/approach We searched popular digital media outlets to collect 523 headlines exaggerating obesity-related research findings. The reasons for exaggerations include: inferring causality from observational studies, inferring human outcomes from animal research, inferring distant/end outcomes (e.g., obesity) from immediate/intermediate outcomes (e.g., calorie intake), and generalizing findings to the population from a subgroup or convenience sample. Each headline was paired with the title and abstract of the peer-reviewed journal publication covered by the news article. We drafted an exaggeration-free counterpart for each original headline and fined-tuned a BERT model to differentiate between them. We further fine-tuned three generative language models—BART, PEGASUS, and T5 to autogenerate exaggeration-free headlines based on a journal publication’s title and abstract. Model performance was evaluated using the ROUGE metrics by comparing model-generated headlines with journal publication titles. Findings The fine-tuned BERT model achieved 92.5% accuracy in differentiating between exaggeration-free and original headlines. Baseline ROUGE scores averaged 0.311 for ROUGE-1, 0.113 for ROUGE-2, 0.253 for ROUGE-L, and 0.253 ROUGE-Lsum. PEGASUS, T5, and BART all outperformed the baseline. The best-performing BART model attained 0.447 for ROUGE-1, 0.221 for ROUGE-2, 0.402 for ROUGE-L, and 0.402 for ROUGE-Lsum. Originality/value This study demonstrated the feasibility of leveraging AI to automatically identify and correct news headlines exaggerating obesity-related research findings.
Introduction: This study systematically reviewed scientific evidence concerning the influence of green space on obesity in China. Methods: Keyword and reference search was conducted in PubMed, Web of ...Science, Scopus, EBSCO, and CNKI. Predetermined selection criteria included study designs: experimental and observational studies; subjects: people of all ages; exposures: green space (i.e., any open land partly or entirely covered with grass, trees, shrubs, or other vegetation); outcomes: body weight status (e.g., body mass index BMI, overweight, or obesity); and country: China. Results: Ten studies met the selection criteria and were included in the review. All studies adopted a cross-sectional design. Overall greenness measures were found to be inversely associated with BMI, overweight, and obesity in most included studies. Street greenness, which measures the perceived greenness at the eye level on streets, was found to be inversely associated with BMI and obesity. By contrast, mixed results were observed for the relationship between green space accessibility and weight outcomes. Air quality was found to mediate the relationship between greenness and obesity. The influence of green space on obesity tended to vary by residents’ gender, age, and socioeconomic status. Boys, women, older residents, and those with lower education or household income were more likely to benefit from greenness exposure. Conclusion: The literature on green space exposure in relation to obesity in China remains limited. Longitudinal and quasi-experimental studies are warranted to assess the causal link between green space and obesity. Future measures should better capture the self-perception, quality, and attractiveness of green space. The underlying pathways through which green space affects residents’ weight outcomes should be further elucidated.
(1) Background: This study assessed the influence of beef consumption on nutrient intakes and diet quality among U.S. adults. (2) Methods: Nationally-representative sample (
= 27,117) from 2005⁻2016 ...National Health and Nutrition Examination Survey was analyzed. First-difference estimator addressed confounding bias from time-invariant unobservables (e.g., eating habits, taste preferences) by using within-individual variations in beef consumption between 2 nonconsecutive 24 h dietary recalls. (3) Results: Approximately 54%, 39%, 12%, and 7% of U.S. adults consumed beef, lean beef, fresh beef, and fresh lean beef, respectively. Overall diet quality measured by the Health Eating Index-2015 (HEI-2015) score among beef, fresh beef, lean beef, and fresh lean beef consumers was lower than beef non-consumers. Regression analyses found that beef, fresh beef, lean beef, and fresh lean beef consumption was associated with higher daily intakes of total energy, protein, sodium, choline, iron, selenium, zinc, phosphorus, and multiple B vitamins. Beef, fresh beef, and lean beef consumption but not fresh lean beef consumption was associated with higher saturated fat intake. Beef consumption was not found to be associated with overall dietary quality measured by the HEI-2015 score. (4) Conclusions: Beef consumers may increase the intake of fresh and lean beef over total beef consumption to maximize the nutritional gains from beef portions while minimizing the resulting increases in energy, saturated fat, and sodium.
Diet quality scores are designed mainly based on Western-style dietary patterns. They were demonstrated to be good indicators of obesity in developed but not developing countries. Several diet ...quality scores were developed based on the Chinese dietary guidelines, yet no systematic review exists regarding how they were related to obesity. We searched research articles published between 2000 and 2021 in PubMed, CINAHL, and Scopus databases. Both cross-sectional and prospective studies that examined the relationship between a diet quality score and weight, body mass index, obesity, or waist circumference conducted in a Chinese population were selected. From the 602 articles searched, 20 articles were selected (12 are cross-sectional studies and 8 are prospective cohort studies). The relationship between internationally used scores and obesity was inconsistent among studies. Scores tailored to the Chinese diet demonstrated a strong relationship with both being underweight and obesity. The heterogeneity of the populations and the major nutrition transition in China may partially explain the discrepancies among studies. In conclusion, diet quality scores tailored to the Chinese diet may be associated with both undernutrition and overnutrition, as well as being underweight and obesity outcomes.
Purpose:
To examine the determinants and impacts of implementing the mitigation interventions to combat the COVID-19 disease in the United States during the first 5 weeks of the pandemic.
Method:
A ...content analysis identified nine types of mitigation interventions and the timing at which states enacted these strategies. A proportional hazard model, a multiple-event survival model, and a random-effect spatial error panel model in conjunction with a robust method analyzing zero-inflated and skewed outcomes were employed in the data analysis.
Findings:
Contradictory to the study hypothesis, states initially with a high COVID-19 prevalence rate enacted mitigation strategies slowly. Three mitigation strategies (nonessential business closure, large-gathering bans, and restaurant/bar limitations) showed positive impacts on reducing cumulative cases, new cases, and death rates across states.
Conclusion:
Some states may have missed optimal timing to implement mitigations. Swift implementation of mitigations is crucial. Reopening economy by fully lifting mitigation interventions is risky.
Background: Chatbots are computer programs, often built upon large artificial intelligence models, that employ dialogue systems to enable online, natural language conversations with users via text, ...speech, or both. Body image, broadly defined as a combination of thoughts and feelings about one’s physical appearance, has been implicated in many risk behaviors and health problems, especially among adolescents and young adults. Little is known about how chatbots respond to questions about body image. Methods: This study assessed the responses of 14 widely-used chatbots (eight companion and six therapeutic chatbots) to ten body image-related questions developed upon validated instruments. Chatbots’ responses were documented, with qualities systematically assessed by nine pre-determined criteria. Results: The overall quality of the chatbots’ responses was modest (an average score of five out of nine), with substantial variations in the content and quality of responses across chatbots (individual scores ranging from one to eight). Companion and therapeutic chatbots systematically differed in their responses (e.g., focusing on comforting users vs. trying to identify the causes of negative body image and recommending potential remedies). Some therapeutic chatbots recognized potential mental health crises (self-harm) in test users’ messages. Conclusion: Substantial heterogeneities in the responses were present across chatbots and assessment criteria. Adolescents and young adults struggling with body image could be vulnerable to misleading or biased remarks made by chatbots. Still, the technical and supervision challenges to prevent those adverse consequences remain paramount and unsolved.
High prices remain a formidable barrier for many people, especially those of low socioeconomic status, to adopt a healthier diet. The Food, Conservation, and Energy Act of 2008 mandated the U.S. ...Department of Agriculture (USDA) to conduct a pilot study to assess the impact of making fruits and vegetables more affordable for households in the Supplemental Nutrition Assistance Program (SNAP). Based on the USDA final report of the Healthy Incentives Pilot (HIP), a large-scale randomized trial in 2011–2012 that provided 30% rebate on targeted fruits and vegetables to 7500 study participants enrolled in the SNAP, we constructed a decision model to evaluate the cost-effectiveness of an expansion of the HIP to all SNAP households nationwide. The estimated life-time per capita costs of the HIP to the Federal government is $1323 in 2012 U.S. dollars, and the average gains in quality-adjusted life expectancy to a SNAP participant is 0.082 quality-adjusted life year (QALY), resulting in an incremental cost-effectiveness ratio (ICER) of $16,172 per QALY gained. Sensitivity analysis using Monte Carlo simulations indicates a 94.4% and 99.6% probability that the estimated ICER would be lower than the cost-effective threshold of $50,000 and $100,000 per QALY gained, respectively. Moreover, the estimated ICER of the HIP expansion tends to be competitive in comparison to other interventions that aimed at promoting fruit/vegetable intake among adult population. Findings from this study suggest that a nationwide expansion of the HIP is likely to nudge SNAP households towards purchasing and consuming more targeted fruits and vegetables. However, diet behavior modification is proportional to price change. When people's actual eating behaviors and what dietary guidelines recommend differ by several folds, even a 30% rebate closes just a small fraction of that gap and has limited beneficial impact on participants' weight management, disease prevention, and health-related quality of life.
•Healthy Incentives Pilot (HIP) offers SNAP households 30% rebate on produce purchase.•We assess the cost-effectiveness of HIP expansion to all SNAP households nationwide.•The estimated cost-effectiveness ratio is well below commonly adopted thresholds.•HIP expansion would increase SNAP households' fruit/vegetable purchase and intake.•Beneficial effect is only modest as behavior change is proportional to price change.
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