Reptiles and amphibians are popular in the exotic pet trade, where Australian species are valued for their rarity and uniqueness. Despite a near-complete ban on the export of Australian wildlife, smuggling and subsequent international trade frequently occur in an unregulated and unmonitored manner. In 2022, Australia listed over 100 squamates in Appendix III of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) to better monitor this trade. We investigated current trade and assessed the value of this Australian CITES listing using web-scraping methods to monitor the online pet trade in Australian reptiles and amphibians, with additional data from published papers, trade databases, and seizure records. Despite the export ban, we identified 170 endemic herpetofauna (reptile and amphibian) species in international trade, 33 of which were not recorded previously in the international market, including 6 newly recorded genera. Ninety-two traded species were included in CITES appendices (59 added in 2022), but at least 78 other traded species remained unregulated. Among these, 5 of the 10 traded threatened species were unlisted, and we recommend they be considered for inclusion in CITES Appendix III. We also recommend the listing of all Diplodactylidae genera in Appendix III. Despite this family representing the greatest number of Australian species in trade, only one genus (of 7 traded) was included in the recent CITES amendments. Overall, a large number of Australian reptile and amphibian species are traded internationally and, although we acknowledge the value of Australia\'s recent CITES listing, we recommend the consideration of other taxa for similar inclusion in CITES.
Escala del mercado internacional no regulado de reptiles y anfibios australianos Resumen Los reptiles y anfibios son populares en el comercio de mascotas exóticas, en el que las especies australianas son valoradas por su rareza y singularidad. A pesar de la prohibición casi total de la exportación de fauna silvestre australiana, el contrabando y el comercio internacional posterior se producen con frecuencia de forma no regulada y no supervisada. En 2022, Australia incluyó más de 100 escamosos en el apéndice III de la Convención sobre el Comercio Internacional de Especies Amenazadas de Fauna y Flora Silvestres (CITES) para controlar mejor este comercio. Investigamos el comercio actual y evaluamos el valor de esta inclusión en CITES con métodos de raspado web para monitorear el comercio virtual de reptiles y anfibios australianos como mascotas, con datos adicionales de artículos publicados, bases de datos comerciales y registros de incautaciones. A pesar de la prohibición de las exportaciones, identificamos 170 especies endémicas de herpetofauna (reptiles y anfibios) en el comercio internacional, 33 de las cuales no se habían registrado previamente en el mercado internacional, incluidos 6 géneros registrados recientemente. Noventa y dos especies comercializadas se incluyeron en los apéndices de CITES (59 añadidas en 2022), pero al menos otras 78 especies comercializadas permanecieron sin regular. Entre ellas, cinco de las diez especies amenazadas comercializadas no estaban incluidas y recomendamos que se considere su inclusión en el apéndice III de CITES. También recomendamos la inclusión de todos los géneros de Diplodactylidae en el apéndice III. A pesar de que esta familia representa el mayor número de especies australianas en el comercio, sólo un género (de 7 comercializados) fue incluido en las recientes enmiendas de CITES. En general, un gran número de especies de reptiles y anfibios australianos son objeto de comercio internacional y, aunque reconocemos el valor de la reciente inclusión de Australia en CITES, recomendamos que se consideren otros taxones para su similar inclusión.
爬行动物和两栖动物在外来宠物贸易中很受欢迎, 其中, 澳大利亚的生物因其稀有性和独特性而备受青睐。尽管澳大利亚几乎全面禁止野生动物出口, 但仍频繁出现不受管理和监督的走私及随后发生的国际贸易。2022年, 澳大利亚将100多种有鳞类动物列入《濒危野生动植物种国际贸易公约》 (CITES) 附录III, 以更好地监管相关贸易。本研究采用网络抓取数据的方法监测澳大利亚两栖和爬行动物的在线宠物贸易数据, 并从已发表论文、贸易数据库和罚没记录中补充了更多数据, 以研究当前的贸易情况并评估这些澳大利亚物种列入CITES附录的价值。尽管存在出口禁令, 我们仍在国际贸易中发现了170种特有的两栖和爬行动物, 其中33种以前在国际市场上没有记录, 包含6个新记录的属。有92个贸易物种已被列入CITES附录 (其中59个为2022年新增物种), 但至少有另外78个贸易物种仍未受到监管。其中, 10个濒危的贸易物种中有5个未列入附录, 我们建议考虑将其列入CITES附录III。我们还建议将澳洲蜥虎科 (Diplodactylidae) 所有属都列入附录III。这个科在澳大利亚贸易物种中所占数量最多, 但在最近的CITES修订中只列入了一个属 (共7个贸易物种) 。总体而言, 大量澳大利亚两栖和爬行动物存在国际贸易, 尽管我们承认澳大利亚最近新增CITES附录列入物种的价值, 但我们仍建议考虑将其他类群同样列入CITES附录。【翻译: 胡怡思; 审校: 聂永刚】.

BACKGROUND: Online food delivery services (OFDS) enable individuals to conveniently access foods from any deliverable location. The increased accessibility to foods may have implications on the consumption of healthful or unhealthful foods. Concerningly, previous research suggests that OFDS offer an abundance of energy-dense and nutrient-poor foods, which are heavily promoted through deals or discounts.
OBJECTIVE: In this paper, we describe the development of the DIGIFOOD dashboard to monitor the digitalization of local food environments in New South Wales, Australia, resulting from the proliferation of OFDS.
METHODS: Together with a team of data scientists, we designed a purpose-built dashboard using Microsoft Power BI. The development process involved three main stages: (1) data acquisition of food outlets via web scraping, (2) data cleaning and processing, and (3) visualization of food outlets on the dashboard. We also describe the categorization process of food outlets to characterize the healthfulness of local, online, and hybrid food environments. These categories included takeaway franchises, independent takeaways, independent restaurants and cafes, supermarkets or groceries, bakeries, alcohol retailers, convenience stores, and sandwich or salad shops.
RESULTS: To date, the DIGIFOOD dashboard has mapped 36,967 unique local food outlets (locally accessible and scraped from Google Maps) and 16,158 unique online food outlets (accessible online and scraped from Uber Eats) across New South Wales, Australia. In 2023, the market-leading OFDS operated in 1061 unique suburbs or localities in New South Wales. The Sydney-Parramatta region, a major urban area in New South Wales accounting for 28 postcodes, recorded the highest number of online food outlets (n=4221). In contrast, the Far West and Orana region, a rural area in New South Wales with only 2 postcodes, recorded the lowest number of food outlets accessible online (n=7). Urban areas appeared to have the greatest increase in total food outlets accessible via online food delivery. In both local and online food environments, it was evident that independent restaurants and cafes comprised the largest proportion of food outlets at 47.2% (17,437/36,967) and 51.8% (8369/16,158), respectively. However, compared to local food environments, the online food environment has relatively more takeaway franchises (2734/16,158, 16.9% compared to 3273/36,967, 8.9%) and independent takeaway outlets (2416/16,158, 14.9% compared to 4026/36,967, 10.9%).
CONCLUSIONS: The DIGIFOOD dashboard leverages the current rich data landscape to display and contrast the availability and healthfulness of food outlets that are locally accessible versus accessible online. The DIGIFOOD dashboard can be a useful monitoring tool for the evolving digital food environment at a regional scale and has the potential to be scaled up at a national level. Future iterations of the dashboard, including data from additional prominent OFDS, can be used by policy makers to identify high-priority areas with limited access to healthful foods both online and locally.

Inspired by significant technical advancements, a rapidly growing stream of research explores human lay beliefs and reactions surrounding AI tools, which employ algorithms to mimic elements of human intelligence. This literature predominantly documents negative reactions to these tools or the underlying algorithms, often referred to as algorithm aversion or, alternatively, a preference for humans. This article proposes a third interpretation: people may be averse to their labels, but appreciative of their output. This perspective offers three core insights for how we study people\'s reactions to algorithms. Research would benefit from (1) carefully considering the labeling of AI tools, (2) broadening the scope of study to include interactions with these tools, and (3) accounting for their technical configuration.

BACKGROUND: People diagnosed with multiple sclerosis (MS) often seek to modify their diet guided by online advice, however this advice may not align with national dietary guidelines. The aim of this study was to simulate an online search for dietary advice conducted by a person with MS and evaluate the content. It was hypothesised that a variety of eating patterns are promoted for MS online and these dietary approaches can be contradictory.
METHODS: An online search was simulated using Google Trends-informed search terms and Google and Bing search engines. URLs were extracted using R. Nutrition data were extracted including recommendations for diets, foods, supplements, and health professional consultation. Statistical analyses were conducted using R.
RESULTS: 73 URLs from 49 websites were extracted, with only 14 results common to both search engines. Dietary recommendations included overall eating patterns (58 webpages, 79%), individual foods (55 webpages, 75%), and supplements (33 webpages, 45%). The most promoted eating pattern for MS was a balanced diet (33 recommendations, 48%), more likely by nonprofit organisations and health information websites (14 and 17 recommendations, 100% and 89%); lifestyle program websites were more likely to recommend restrictive diets (19 recommendations, 100%) (p<0.001). 52% pages advised consulting a health professional, most often a doctor or dietitian.
CONCLUSIONS: A balanced diet is the most recommended eating pattern for MS online, though advice promoting restrictive diets persists.

Science journalism is a critical way for the public to learn about and benefit from scientific findings. Such journalism shapes the public\'s view of the current state of science and legitimizes experts. Journalists can only cite and quote a limited number of sources, who they may discover in their research, including recommendations by other scientists. Biases in either process may influence who is identified and ultimately included as a source. To examine potential biases in science journalism, we analyzed 22,001 non-research articles published by Nature and compared these with Nature-published research articles with respect to predicted gender and name origin. We extracted cited authors\' names and those of quoted speakers. While citations and quotations within a piece do not reflect the entire information-gathering process, they can provide insight into the demographics of visible sources. We then predicted gender and name origin of the cited authors and speakers. We compared articles with a comparator set made up of first and last authors within primary research articles in Nature and a subset of Springer Nature articles in the same time period. In our analysis, we found a skew toward quoting men in Nature science journalism. However, quotation is trending toward equal representation at a faster rate than authorship rates in academic publishing. Gender disparity in Nature quotes was dependent on the article type. We found a significant over-representation of names with predicted Celtic/English origin and under-representation of names with a predicted East Asian origin in both in extracted quotes and journal citations but dampened in citations.

The transformative potential of web scraping in surgical research through a comprehensive analysis of its revolutionary applications and profound impact is now within reach. This manuscript unveils the pivotal role of web scraping in driving innovation, enabling more effective management of human capital dynamics, and enhancing patient outcomes in the surgical field. As an example, we demonstrate how web scraping can uncover insights into international collaboration in surgery research revealing limited collaboration between surgeons in developed and developing countries.

OBJECTIVE: Individuals with health conditions often use online patient forums to share their experiences. These patient data are freely available and have rarely been used in patient-reported outcomes (PRO) research. Web scraping, the automated identification and coding of webpage data, can be employed to collect patient experiences for PRO research. The objective of this study was to assess the feasibility of using web scraping to support the development of a new PRO measure for breast implant illness (BII).
METHODS: Nine publicly available BII-specific web forums were chosen post-consultation with two prominent BII advocacy leaders. The Python Selenium and Pandas packages were used to automate extraction of de-identified text from the individual posts/comments into a spreadsheet. Data were coded using a line-by-line approach and constant comparison was used to create top-level domains and sub-domains.
RESULTS: 6362 unique codes were identified and organized into four top-level domains of information needs, symptom experiences, life impact of BII, and care experiences. Information needs of women included seeking/sharing information pre-breast implant surgery, post-breast implant surgery, while contemplating explant surgery, and post-explant surgery. Symptoms commonly described by women included fatigue, brain fog, and musculoskeletal symptoms. Many comments described BII\'s impact on daily activities and psychosocial wellbeing. Lastly, some comments described negative care experiences and experiences related to advocating for themselves to providers.
CONCLUSIONS: This proof-of-concept study demonstrated the feasibility of employing web scraping as a cost-effective, efficient method to understand the experiences of women with BII. These data will be used to inform the development of a BII-specific PROM.

BACKGROUND: Contextual variables that capture the characteristics of delimited geographic or jurisdictional areas are vital for health and social research. However, obtaining data sets with contextual-level data can be challenging in the absence of monitoring systems or public census data.
OBJECTIVE: We describe and implement an 8-step method that combines web scraping, text mining, and spatial overlay analysis (WeTMS) to transform extensive text data from government websites into analyzable data sets containing contextual data for jurisdictional areas.
METHODS: This tutorial describes the method and provides resources for its application by health and social researchers. We used this method to create data sets of health assets aimed at enhancing older adults\' social connections (eg, activities and resources such as walking groups and senior clubs) across the 374 health jurisdictions in Catalonia from 2015 to 2022. These assets are registered on a web-based government platform by local stakeholders from various health and nonhealth organizations as part of a national public health program. Steps 1 to 3 involved defining the variables of interest, identifying data sources, and using Python to extract information from 50,000 websites linked to the platform. Steps 4 to 6 comprised preprocessing the scraped text, defining new variables to classify health assets based on social connection constructs, analyzing word frequencies in titles and descriptions of the assets, creating topic-specific dictionaries, implementing a rule-based classifier in R, and verifying the results. Steps 7 and 8 integrate the spatial overlay analysis to determine the geographic location of each asset. We conducted a descriptive analysis of the data sets to report the characteristics of the assets identified and the patterns of asset registrations across areas.
RESULTS: We identified and extracted data from 17,305 websites describing health assets. The titles and descriptions of the activities and resources contained 12,560 and 7301 unique words, respectively. After applying our classifier and spatial analysis algorithm, we generated 2 data sets containing 9546 health assets (5022 activities and 4524 resources) with the potential to enhance social connections among older adults. Stakeholders from 318 health jurisdictions registered identified assets on the platform between July 2015 and December 2022. The agreement rate between the classification algorithm and verified data sets ranged from 62.02% to 99.47% across variables. Leisure and skill development activities were the most prevalent (1844/5022, 36.72%). Leisure and cultural associations, such as social clubs for older adults, were the most common resources (878/4524, 19.41%). Health asset registration varied across areas, ranging between 0 and 263 activities and 0 and 265 resources.
CONCLUSIONS: The sequential use of WeTMS offers a robust method for generating data sets containing contextual-level variables from internet text data. This study can guide health and social researchers in efficiently generating ready-to-analyze data sets containing contextual variables.

BACKGROUND: Cancer survivors frequently experience cancer-related financial burdens. The extent to which Lesbian, Gay, Bisexual, Transgender, Queer, Plus (LGBTQ+) populations experience cancer-related cost-coping behaviors such as crowdfunding is largely unknown, owing to a lack of sexual orientation and gender identity data collection and social stigma. Web-scraping has previously been used to evaluate inequities in online crowdfunding, but these methods alone do not adequately engage populations facing inequities.
OBJECTIVE: We describe the methodological process of integrating technology-based and community-engaged methods to explore the financial burden of cancer among LGBTQ+ individuals via online crowdfunding.
METHODS: To center the LGBTQ+ community, we followed community engagement guidelines by forming a study advisory board (SAB) of LGBTQ+ cancer survivors, caregivers, and professionals who were involved in every step of the research. SAB member engagement was tracked through quarterly SAB meeting attendance and an engagement survey. We then used web-scraping methods to extract a data set of online crowdfunding campaigns. The study team followed an integrated technology-based and community-engaged process to develop and refine term dictionaries for analyses. Term dictionaries were developed and refined in order to identify crowdfunding campaigns that were cancer- and LGBTQ+-related.
RESULTS: Advisory board engagement was high according to metrics of meeting attendance, meeting participation, and anonymous board feedback. In collaboration with the SAB, the term dictionaries were iteratively edited and refined. The LGBTQ+ term dictionary was developed by the study team, while the cancer term dictionary was refined from an existing dictionary. The advisory board and analytic team members manually coded against the term dictionary and performed quality checks until high confidence in correct classification was achieved using pairwise agreement. Through each phase of manual coding and quality checks, the advisory board identified more misclassified campaigns than the analytic team alone. When refining the LGBTQ+ term dictionary, the analytic team identified 11.8% misclassification while the SAB identified 20.7% misclassification. Once each term dictionary was finalized, the LGBTQ+ term dictionary resulted in a 95% pairwise agreement, while the cancer term dictionary resulted in an 89.2% pairwise agreement.
CONCLUSIONS: The classification tools developed by integrating community-engaged and technology-based methods were more accurate because of the equity-based approach of centering LGBTQ+ voices and their lived experiences. This exemplar suggests integrating community-engaged and technology-based methods to study inequities is highly feasible and has applications beyond LGBTQ+ financial burden research.

The aim of this work was to assess the feasibility and effect of applying a nationally representative and highly disaggregated food costing measure across Canada, through the novel application of web-scraping technology to the methods of the National Nutritious Food Basket (NNFB). Further, this study tested the hypothesis that a product-matched digital NNFB (dNNFB) correlates with existing market basket measures and quantified any differences in costs. This was an observational cross-sectional study using web scraped food price data collected in November 2021. Food price data was collected from the majority of Loblaw\'s banners across Canada, resulting in a final store sample of 751 stores sourced from 11 retail banners. Stores were located across all five Statistics Canada regions, including all provinces and territories with the exception of Nunavut. Store-level dNNFB costs were computed, adjusted by age-sex group, and summarized by geographic region and banner. dNNFB costs were then compared with existing national statistics office estimates (Market Basket Measure thresholds for reference families). dNNFB costs varied widely across the country, with notable differences by regional, store-level, and age-sex group characteristics. When compared to reported national statistics, our estimates exceeded the national market basket measure in every comparison in corresponding sub-national geography across the country, with correlation varying from 0.49 to 0.78 dependent on summary comparator. Digital collection of food price data was a feasible strategy for market basket costing. Our findings suggest we may be routinely underestimating the impact of food inflation for consumers, particularly those restricted to certain food environments.