Best practices for data management and sharing in experimental biomedical research.

Effective data management is crucial for scientific integrity and reproducibility, a cornerstone of scientific progress. Well-organized and well-documented data enable validation and building on results. Data management encompasses activities including organization, documentation, storage, sharing, and preservation. Robust data management establishes credibility, fostering trust within the scientific community and benefiting researchers' careers. In experimental biomedicine, comprehensive data management is vital due to the typically intricate protocols, extensive metadata, and large datasets. Low-throughput experiments, in particular, require careful management to address variations and errors in protocols and raw data quality. Transparent and accountable research practices rely on accurate documentation of procedures, data collection, and analysis methods. Proper data management ensures long-term preservation and accessibility of valuable datasets. Well-managed data can be revisited, contributing to cumulative knowledge and potential new discoveries. Publicly funded research has an added responsibility for transparency, resource allocation, and avoiding redundancy. Meeting funding agency expectations increasingly requires rigorous methodologies, adherence to standards, comprehensive documentation, and widespread sharing of data, code, and other auxiliary resources. This review provides critical insights into raw and processed data, metadata, high-throughput versus low-throughput datasets, a common language for documentation, experimental and reporting guidelines, efficient data management systems, sharing practices, and relevant repositories. We systematically present available resources and optimal practices for wide use by experimental biomedical researchers.

Adherence of studies involving artificial intelligence in the analysis of ophthalmology electronic medical records to AI-specific items from the CONSORT-AI guideline: a systematic review.

PURPOSE: In the context of ophthalmologic practice, there has been a rapid increase in the amount of data collected using electronic health records (EHR). Artificial intelligence (AI) offers a promising means of centralizing data collection and analysis, but to date, most AI algorithms have only been applied to analyzing image data in ophthalmologic practice. In this review we aimed to characterize the use of AI in the analysis of EHR, and to critically appraise the adherence of each included study to the CONSORT-AI reporting guideline. METHODS: A comprehensive search of three relevant databases (MEDLINE, EMBASE, and Cochrane Library) from January 2010 to February 2023 was conducted. The included studies were evaluated for reporting quality based on the AI-specific items from the CONSORT-AI reporting guideline. RESULTS: Of the 4,968 articles identified by our search, 89 studies met all inclusion criteria and were included in this review. Most of the studies utilized AI for ocular disease prediction (n = 41, 46.1%), and diabetic retinopathy was the most studied ocular pathology (n = 19, 21.3%). The overall mean CONSORT-AI score across the 14 measured items was 12.1 (range 8-14, median 12). Categories with the lowest adherence rates were: describing handling of poor quality data (48.3%), specifying participant inclusion and exclusion criteria (56.2%), and detailing access to the AI intervention or its code, including any restrictions (62.9%). CONCLUSIONS: In conclusion, we have identified that AI is prominently being used for disease prediction in ophthalmology clinics, however these algorithms are limited by their lack of generalizability and cross-center reproducibility. A standardized framework for AI reporting should be developed, to improve AI applications in the management of ocular disease and ophthalmology decision making.

Endorsement of reporting guidelines and clinical trial registration across Scopus-indexed rheumatology journals: a cross-sectional analysis.

The purpose of this study was to investigate the instructions for authors of rheumatology journals and analyze their endorsement of reporting guidelines and clinical trial registration. Sixty rheumatology journals were selected by a research librarian and an investigator through the 2021 Scopus CiteScore tool. The instructions for authors' subsection of each journal was assessed to determine endorsement of study design-specific reporting guidelines or clinical trial registration. Descriptive statistics were calculated using R (version 4.2.1) and RStudio. Of the 58 journals analyzed, 34 (34/58; 59%) mentioned the EQUATOR Network: an online compendium of best practice reporting guidelines. The most commonly mentioned reporting guidelines were CONSORT with 44 journals (44/58; 75%), and PRISMA with 35 journals (35/58; 60%). The least mentioned guidelines were QUOROM with 56 journals not mentioning the guideline (56/58; 97%), and SRQR with 53 journals not mentioning the guideline (53/57, 93%). Clinical trial registration was required by 38 journals (38/58; 66%) and recommended by 8 journals (8/58; 14%). Our study found that endorsement of reporting guidelines and clinical trial registration within rheumatology journals was suboptimal with great room for improvement. Endorsement of reporting guidelines have shown to not only mitigate bias, but also improve research methodologies. Therefore, we recommend rheumatology journals broadly expand their endorsement of reporting guidelines and clinical trial registration to improve the quality of evidence they publish.

Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS).

The number of papers presenting machine learning (ML) models that are being submitted to and published in the Journal of Medical Internet Research and other JMIR Publications journals has steadily increased. Editors and peer reviewers involved in the review process for such manuscripts often go through multiple review cycles to enhance the quality and completeness of reporting. The use of reporting guidelines or checklists can help ensure consistency in the quality of submitted (and published) scientific manuscripts and, for example, avoid instances of missing information. In this Editorial, the editors of JMIR Publications journals discuss the general JMIR Publications policy regarding authors' application of reporting guidelines and specifically focus on the reporting of ML studies in JMIR Publications journals, using the Consolidated Reporting of Machine Learning Studies (CREMLS) guidelines, with an example of how authors and other journals could use the CREMLS checklist to ensure transparency and rigor in reporting.

Little Strokes Fell Big Oaks: How Repeated Recommendations for Suicide Reporting Drive the Quality of Suicide News in South Korea.

This study investigates how far repeated releases of recommendations for responsible reporting on suicide (RRS) are associated with changes in the quality of suicide reporting. A content analysis was conducted on suicide news articles (N = 606) by the Korean newspapers Hankyoreh Sinmun and Chosun Ilbo in four six-month periods from 2004 to 2019, which covered the periods before and after the releases of three versions of suicide reporting guidelines. Elements for RRS served as a proxy for the reporting quality, which includes both avoiding negative elements and providing positive ones. Not only the number of suicide news stories reduced by half in the last two observation periods, overall RRS scores and most individual RRS elements increased in the third period, compared to the first or second period. The avoidance RRS for headline, however, was not significantly improved. Korean news media also tended to be sensationalistic in using photos.

Completeness of reporting in systematic reviews and meta-analyses in vascular surgery.

OBJECTIVE: Systematic reviews (SRs) and meta-analyses are essential in informing clinical guidelines and decision-making. Complete reporting of SRs through compliance to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines promotes transparency, reproducibility, and consistency across the literature. The purpose of this meta-epidemiological study is to assess the completeness of reporting of SRs in the vascular surgery literature. METHODS: MEDLINE and Embase were used to search through four major vascular surgery journals and four high impact general medical journals for SRs published between 2018 and October 2022 evaluating clinical treatments for any pathology treated by a vascular surgeon. Data screening and extraction were conducted in duplicate. The reporting completeness of each included SR was measured with reference to the 27-item PRISMA checklist, and methodological quality was evaluated using the Assessing the Methodological Quality of Systematic Reviews 2 (AMSTAR 2) tool. Parametric tests were used to evaluate for associations between PRISMA score and study funding, protocol registration, publication in a higher impact factor journal, and AMSTAR 2 score. The protocol is available online: 10.17605/OSF.IO/VBC5N. RESULTS: Of 1653 articles captured in the initial search, 162 SRs were included in the final analysis. All SRs had more than one incomplete PRISMA item. The mean PRISMA score was 21.2/27 (standard deviation: 2.9, 78.5% compliance), and the mean AMSTAR 2 score was 11.7/16 (standard deviation: 1.9, 73%). SRs that had a prospectively registered protocol had a higher PRISMA score (22.9 vs 20.6, P < .001) as did those that were published in higher impact factor journals (23.3 vs 21.0, P = .017). There was a large positive correlation between an SR's PRISMA and AMSTAR 2 scores (Pearson r = 0.655, 95% confidence interval: 0.55-0.74). There were no associations between the PRISMA score and publication year (P = .067) or funding status (P = .076). CONCLUSIONS: Overall, the reporting of SRs and meta-analyses in vascular surgery is less than ideal, with several key items being consistently under-reported. Prospective registration and methodological quality as measured by AMSTAR 2 scores are positively associated with improved reporting. Authors, reviewers, and journal editors should consider these findings moving forward to encourage completeness of SR reporting. Raising awareness surrounding the value of complete reporting of SRs can aid in enhancing the quality of evidence, and journals should consider these findings in methods used to promote SR reporting.

Guidelines for the estimation and reporting of plasmid conjugation rates.

Conjugation is a central characteristic of plasmid biology and an important mechanism of horizontal gene transfer in bacteria. However, there is little consensus on how to accurately estimate and report plasmid conjugation rates, in part due to the wide range of available methods. Given the similarity between approaches, we propose general reporting guidelines for plasmid conjugation experiments. These constitute best practices based on recent literature about plasmid conjugation and methods to measure conjugation rates. In addition to the general guidelines, we discuss common theoretical assumptions underlying existing methods to estimate conjugation rates and provide recommendations on how to avoid violating these assumptions. We hope this will aid the implementation and evaluation of conjugation rate measurements, and initiate a broader discussion regarding the practice of quantifying plasmid conjugation rates.

Improving social justice in observational studies: protocol for the development of a global and Indigenous STROBE-equity reporting guideline.

BACKGROUND: Addressing persistent and pervasive health inequities is a global moral imperative, which has been highlighted and magnified by the societal and health impacts of the COVID-19 pandemic. Observational studies can aid our understanding of the impact of health and structural oppression based on the intersection of gender, race, ethnicity, age and other factors, as they frequently collect this data. However, the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline, does not provide guidance related to reporting of health equity. The goal of this project is to develop a STROBE-Equity reporting guideline extension. METHODS: We assembled a diverse team across multiple domains, including gender, age, ethnicity, Indigenous background, disciplines, geographies, lived experience of health inequity and decision-making organizations. Using an inclusive, integrated knowledge translation approach, we will implement a five-phase plan which will include: (1) assessing the reporting of health equity in published observational studies, (2) seeking wide international feedback on items to improve reporting of health equity, (3) establishing consensus amongst knowledge users and researchers, (4) evaluating in partnership with Indigenous contributors the relevance to Indigenous peoples who have globally experienced the oppressive legacy of colonization, and (5) widely disseminating and seeking endorsement from relevant knowledge users. We will seek input from external collaborators using social media, mailing lists and other communication channels. DISCUSSION: Achieving global imperatives such as the Sustainable Development Goals (e.g., SDG 10 Reduced inequalities, SDG 3 Good health and wellbeing) requires advancing health equity in research. The implementation of the STROBE-Equity guidelines will enable a better awareness and understanding of health inequities through better reporting. We will broadly disseminate the reporting guideline with tools to enable adoption and use by journal editors, authors, and funding agencies, using diverse strategies tailored to specific audiences.

Publications on the diagnostic accuracy of dermatopathology tests: A cross-sectional quality analysis.

BACKGROUND: Ancillary diagnostic tests are frequent in dermatopathology practice. Publications on their accuracy influence their utilization. The transparency and completeness of these publications are unknown. METHODS: We performed a cross-sectional study on diagnostic accuracy studies in dermatopathology published between 2020 and 2022 for compliance with Standards for Reporting of Diagnostic Accuracy Studies (STARD) and the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). RESULTS: 14.67 ± 3.02 STARD items were reported in 62 publications (range, 9.5-23.5 out of the recommended total of 30). More items were reported in high-impact factor journals (16.01 vs. 13.32, p = 0.0002) and journals that endorsed STARD in their author instructions (17.22 vs. 14.11, p = 0.0039). Less than 10% of publications reported quantifiable hypotheses, sample size calculations, flow diagrams, or study registrations. The risk of bias by our analysis of QUADAS-2 criteria was high or uncertain for index test interpretation (36/62, 58%) and patient selection (44/62, 71%). CONCLUSIONS: Publications on dermatopathology tests are exploratory studies without prespecified hypotheses or study designs. They do not meet the criteria for transparent reporting. We suggest that medical journal leadership should consider updating their instructions with more explicit guidance on recommended manuscript elements.

Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology.

INTRODUCTION: Clinical trial designs based on the assumption of independent observations are well established. Clustered clinical trial designs, where all observational units belong to a cluster and outcomes within clusters are expected to be correlated, have also received considerable attention. However, many clinical trials involve partially clustered data, where only some observational units belong to a cluster. Examples of such trials occur in neonatology, where participants include infants from both singleton and multiple births, and ophthalmology, where one or two eyes per participant may need treatment. Partial clustering can also arise in trials of group-based treatments (e.g. group education or counselling sessions) or treatments administered individually by a discrete number of health care professionals (e.g. surgeons or physical therapists), when this is compared to an unclustered control arm. Trials involving partially clustered data have received limited attention in the literature and the current lack of standardised terminology may be hampering the development and dissemination of methods for designing and analysing these trials. METHODS AND EXAMPLES: In this article, we present an overarching definition of partially clustered trials, bringing together several existing trial designs including those for group-based treatments, clustering due to facilitator effects and the re-randomisation design. We define and describe four types of partially clustered trial designs, characterised by whether the clustering occurs pre-randomisation or post-randomisation and, in the case of pre-randomisation clustering, by the method of randomisation that is used for the clustered observations (individual randomisation, cluster randomisation or balanced randomisation within clusters). Real life examples are provided to highlight the occurrence of partially clustered trials across a variety of fields. To assess how partially clustered trials are currently reported, we review published reports of partially clustered trials. DISCUSSION: Our findings demonstrate that the description of these trials is often incomplete and the terminology used to describe the trial designs is inconsistent, restricting the ability to identify these trials in the literature. By adopting the definitions and terminology presented in this article, the reporting of partially clustered trials can be substantially improved, and we present several recommendations for reporting these trial designs in practice. Greater awareness of partially clustered trials will facilitate more methodological research into their design and analysis, ultimately improving the quality of these trials.

The Werther effect following the suicides of three korean celebrities (2017-2018): an ecological time-series study.

BACKGROUND: The suicide rate in Korea was the highest among the member countries of the Organization for Economic Cooperation and Development(OECD) for 2013-2016 and 2018-2020. In korea, suicide was the leading cause of death among individuals aged 10-39, and the second leading cause of death for aged 40-59. Thus, this study aimed to examine the Werther effect of the suicides of three Korean idol singers (Jonghyun: December 18, 2017, Sulli: October 14, 2019, and Hara Gu: November 24, 2019). METHODS: The study conducted Poisson regression and used the cause-of-death statistics microdata from 2016 to 2020 provided by Statistics Korea. The case periods ranged from the day of the suicide of each celebrity to 10 weeks after. The control periods were all weeks from 2016 to 2020, excluding the case periods. RESULTS: The suicide rates in Korea significantly increased by 1.21, 1.30, and 1.28 times after the deaths of Jonghyun, Sulli, and Hara Gu, respectively. The Werther effect was more evident in women than men. Suicide rate among individuals aged 10-29 years was greater than those for other age groups. CONCLUSIONS: This study confirmed that the rate of copycat suicides increased after three celebrity singers in Korea died by suicide. Nevertheless, the rate of suicide after the suicide of the three celebrity singers was lower than those in previous studies in Korea.

Remote patient monitoring for COVID-19 patients: comparisons and framework for reporting.

BACKGROUND: COVID-19 has challenged health services throughout the world in terms of hospital capacity and put staff and vulnerable populations at risk of infection. In the face of these challenges, many health providers have implemented remote patient monitoring (RPM) of COVID-19 patients in their own homes. However systematic reviews of the literature on these implementations have revealed wide variations in how RPM is implemented; along with variations in particulars of RPM reported on, making comparison and evaluation difficult. A review of reported items is warranted to develop a framework of key items to enhance reporting consistency. The aims of this review of remote monitoring for COVID-19 patients are twofold: (1) to facilitate comparison between RPM implementations by tabulating information and values under common domains. (2) to develop a reporting framework to enhance reporting consistency. METHOD: A review of the literature for RPM for COVID-19 patients was conducted following PRISMA guidelines. The Medline database was searched for articles published between 2020 to February 2023 and studies reporting on items with sufficient detail to compare one with another were included. Relevant data was extracted and synthesized by the lead author. Quality appraisal was not conducted as the the articles considered were evaluated as informational reports of clinical implementations rather than as studies designed to answer a research question. RESULTS: From 305 studies retrieved, 23 studies were included in the review: fourteen from the US, two from the UK and one each from Africa, Ireland, China, the Netherlands, Belgium, Australia and Italy. Sixteen generally reported items were identified, shown with the percentage of studies reporting in brackets: Reporting Period (82%), Rationale (100%), Patients (100%), Medical Team (91%) Provider / Infrastructure (91%), Communications Platform (100%), Patient Equipment (100%), Training (48%), Markers (96%), Frequency of prompt / Input (96%),Thresholds (82%), Discharge (61%), Enrolled (96%), Alerts/Escalated (78%), Patient acceptance (43%), and Patient Adherence (52%). Whilst some studies reported on patient training and acceptance, just one reported on staff training and none on staff acceptance. CONCLUSIONS: Variations in reported items were found. Pending the establishment of a robust set of reporting guidelines, we propose a reporting framework consisting of eighteen reporting items under the following four domains: Context, Technology, Process and Metrics.

Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Modeling Studies: Development and Validation.

BACKGROUND: The reporting of machine learning (ML) prognostic and diagnostic modeling studies is often inadequate, making it difficult to understand and replicate such studies. To address this issue, multiple consensus and expert reporting guidelines for ML studies have been published. However, these guidelines cover different parts of the analytics lifecycle, and individually, none of them provide a complete set of reporting requirements. OBJECTIVE: We aimed to consolidate the ML reporting guidelines and checklists in the literature to provide reporting items for prognostic and diagnostic ML in in-silico and shadow mode studies. METHODS: We conducted a literature search that identified 192 unique peer-reviewed English articles that provide guidance and checklists for reporting ML studies. The articles were screened by their title and abstract against a set of 9 inclusion and exclusion criteria. Articles that were filtered through had their quality evaluated by 2 raters using a 9-point checklist constructed from guideline development good practices. The average κ was 0.71 across all quality criteria. The resulting 17 high-quality source papers were defined as having a quality score equal to or higher than the median. The reporting items in these 17 articles were consolidated and screened against a set of 6 inclusion and exclusion criteria. The resulting reporting items were sent to an external group of 11 ML experts for review and updated accordingly. The updated checklist was used to assess the reporting in 6 recent modeling papers in JMIR AI. Feedback from the external review and initial validation efforts was used to improve the reporting items. RESULTS: In total, 37 reporting items were identified and grouped into 5 categories based on the stage of the ML project: defining the study details, defining and collecting the data, modeling methodology, model evaluation, and explainability. None of the 17 source articles covered all the reporting items. The study details and data description reporting items were the most common in the source literature, with explainability and methodology guidance (ie, data preparation and model training) having the least coverage. For instance, a median of 75% of the data description reporting items appeared in each of the 17 high-quality source guidelines, but only a median of 33% of the data explainability reporting items appeared. The highest-quality source articles tended to have more items on reporting study details. Other categories of reporting items were not related to the source article quality. We converted the reporting items into a checklist to support more complete reporting. CONCLUSIONS: Our findings supported the need for a set of consolidated reporting items, given that existing high-quality guidelines and checklists do not individually provide complete coverage. The consolidated set of reporting items is expected to improve the quality and reproducibility of ML modeling studies.

Critical analysis of the reporting quality of animal studies within Endodontics using the Preferred Reporting Items for Animal Studies in Endodontics (PRIASE) 2021 quality standard checklist.

AIM: To critically evaluate the reporting quality of a random sample of animal studies within the field of endodontics against the Preferred Reporting Items for Animal Studies in Endodontics (PRIASE) 2021 checklist and to investigate the association between the quality of reporting and several characteristics of the selected studies. METHODOLOGY: Fifty animal studies related to endodontics were randomly selected from the PubMed database with publication dates from January 2017 to December 2021. For each study, a score of '1' was given when the item of the PRIASE 2021 checklist was fully reported, whereas a score of '0' was given when an item was not reported; when the item was inadequately or partially reported, a score of '0.5' was given. Based on the overall scores allocated to each manuscript, they were allocated into three categories of reporting quality: low, moderate and high. Associations between study characteristics and reporting quality scores were also analysed. Descriptive statistics and Fisher's exact tests were used to describe the data and determine associations. The probability value of .05 was selected as the level of statistical significance. RESULTS: Based on the overall scores, four (8%) and 46 (92%) of the animal studies evaluated were categorized as 'High' and 'Moderate' reporting quality, respectively. A number of items were adequately reported in all studies related to background (Item 4a), relevance of methods/results (7a) and interpretation of images (11e), whereas only one item related to changes in protocol (6d) was not reported in any. No associations were confirmed between reporting quality scores and number of authors, origin of the corresponding author, journal of publication (endodontic specialty vs. non- specialty), impact factor or year of publication. CONCLUSIONS: Animal studies published in the specialty of endodontics were mostly of 'moderate' quality in terms of the quality of reporting. Adherence to the PRIASE 2021 guidelines will enhance the reporting of animal studies in the expectation that all future publications will be high quality.

Reporting and conducting patient journey mapping research in healthcare: A scoping review.

AIM: To identify how patient journey mapping is being undertaken and reported. DESIGN: A scoping review of the literature was undertaken using JBI guidance. DATA SOURCES: Databases were searched in July 2021 (16th-21st), including Ovid's Medline, Embase, Emcare and PsycINFO; Scopus; Web of Science Core Collection, the Directory of Open Access Journals; Informit and; ProQuest Dissertations and Theses Global. REVIEW METHODS: Eligible articles included peer-reviewed literature documenting journey mapping methodologies and studies conducted in healthcare services. Reviewers used Covidence to screen titles and abstracts of located sources, and to screen full-text articles. A table was used to extract data and synthesize results. RESULTS: Eighty-one articles were included. An acceleration of patient journey mapping research was observed, with 76.5% (n = 62) of articles published since 2015. Diverse mapping approaches were identified. Reporting of studies was inconsistent and largely non-adherent with relevant, established reporting guidelines. CONCLUSION: Patient journey mapping is a relatively novel approach for understanding patient experiences and is increasingly being adopted. There is variation in process details reported. Considerations for improving reporting standards are provided. IMPACT: Patient journey mapping is a rapidly growing approach for better understanding how people enter, experience and exit health services. This type of methodology has significant potential to inform new, patient centred models of care and facilitate clinicians, patients and health professionals to better understand gaps and strategies in health services. The synthesised results of this review alert researchers to options available for journey mapping research and provide preliminary guidance for elevating reporting quality.

Reporting guidelines enhance the quality and impact of research in Dental Traumatology.

Reporting guidelines assist basic scientists, translational healthcare researchers and clinicians to publish manuscripts of the highest standard by improving the accuracy, transparency and completeness of the publications they submit to journals. This paper provides an overview of reporting guidelines relevant for the specialty of dental traumatology and discusses their application, significance and potential impact. The Preferred Reporting Items for study Designs in Endodontology (PRIDE) suite of reporting guidelines includes a range of study designs that can be used within the broad field of Endodontics but they are also applicable to dental traumatology and other dental disciplines (Preferred Reporting Items for Case reports in Endodontics [PRICE] 2020, Preferred Reporting Items for RAndomized Trials in Endodontics [PRIRATE] 2020; Preferred Reporting Items for Animal Studies in Endodontology [PRIASE] 2021; Preferred Reporting Items for Laboratory studies in Endodontology [PRILE] 2021 and Preferred Reporting items for OBservational studies in Endodontics [PROBE] 2023). The PRIDE guidelines were developed by an extensive network of globally renowned academics, researchers and expert clinicians working within dentistry using an accepted and validated consensus methodology. The aim of the PRIDE guidelines is to improve the overall quality of manuscripts describing case reports, randomized trials, animal research, laboratory studies and observational studies. Although attention to reporting guidelines adds a degree of complexity when writing reports, such guidelines provide a template for authors to develop standardized manuscripts of the highest quality, which will allow colleagues, readers and the wider public to have confidence that their findings are valid and robust. They also provide evidence to editors that manuscripts submitted to journals comply with the highest global standards of reporting within their respective discipline. Endorsement of the PRIDE guidelines by editors will lead to improvements in the reporting quality of manuscripts submitted to their journals.

Eye tracking: empirical foundations for a minimal reporting guideline.

In this paper, we present a review of how the various aspects of any study using an eye tracker (such as the instrument, methodology, environment, participant, etc.) affect the quality of the recorded eye-tracking data and the obtained eye-movement and gaze measures. We take this review to represent the empirical foundation for reporting guidelines of any study involving an eye tracker. We compare this empirical foundation to five existing reporting guidelines and to a database of 207 published eye-tracking studies. We find that reporting guidelines vary substantially and do not match with actual reporting practices. We end by deriving a minimal, flexible reporting guideline based on empirical research (Section "An empirically based minimal reporting guideline").

Minimal reporting guideline for research involving eye tracking (2023 edition).

A guideline is proposed that comprises the minimum items to be reported in research studies involving an eye tracker and human or non-human primate participant(s). This guideline was developed over a 3-year period using a consensus-based process via an open invitation to the international eye tracking community. This guideline will be reviewed at maximum intervals of 4 years.

The child abuse reporting guideline compliance in Korean newspapers.

The rate of child abuse has sharply increased worldwide, especially during the COVID-19 pandemic. As the media's role in addressing child abuse cases is crucial, several international and formal organizations have established child abuse reporting guidelines. This study investigated how closely journalists follow reporting guidelines in addressing child abuse cases. Five major Korean presses and 189 articles from January 1, 2018, to January 31, 2021, were selected using the keyword "child abuse." Each article was analyzed using a guideline framework consisting of 13 items regarding the five principles of the Korean Ministry of Health and Welfare and Central Child Protection Agency reporting guidelines. This study identified a radical growth in media reporting on child abuse cases in South Korea; almost 60% of the articles analyzed came from 2020 and 2021. More than 80% of the articles analyzed did not provide abuse resources, and 70% did not provide factual information. 57.1% of the articles instigated negative stereotypes, and about 30% explicitly mentioned certain family types in the headlines. Nearly 20% of the articles provided excessive details about the method used. Approximately 16% exposed victims' identities. Some articles (7.9%) also described victims as sharing responsibility for the abuse. This study indicates that the media reports of child abuse in South Korea did not follow the guidelines in many facets. The present study discusses the limitations of the current guidelines and suggests future directions for the news media in reporting on child abuse cases nationwide.

Structured reporting to improve transparency of analyses in prognostic marker studies.

BACKGROUND: Factors contributing to the lack of understanding of research studies include poor reporting practices, such as selective reporting of statistically significant findings or insufficient methodological details. Systematic reviews have shown that prognostic factor studies continue to be poorly reported, even for important aspects, such as the effective sample size. The REMARK reporting guidelines support researchers in reporting key aspects of tumor marker prognostic studies. The REMARK profile was proposed to augment these guidelines to aid in structured reporting with an emphasis on including all aspects of analyses conducted. METHODS: A systematic search of prognostic factor studies was conducted, and fifteen studies published in 2015 were selected, three from each of five oncology journals. A paper was eligible for selection if it included survival outcomes and multivariable models were used in the statistical analyses. For each study, we summarized the key information in a REMARK profile consisting of details about the patient population with available variables and follow-up data, and a list of all analyses conducted. RESULTS: Structured profiles allow an easy assessment if reporting of a study only has weaknesses or if it is poor because many relevant details are missing. Studies had incomplete reporting of exclusion of patients, missing information about the number of events, or lacked details about statistical analyses, e.g., subgroup analyses in small populations without any information about the number of events. Profiles exhibit severe weaknesses in the reporting of more than 50% of the studies. The quality of analyses was not assessed, but some profiles exhibit several deficits at a glance. CONCLUSIONS: A substantial part of prognostic factor studies is poorly reported and analyzed, with severe consequences for related systematic reviews and meta-analyses. We consider inadequate reporting of single studies as one of the most important reasons that the clinical relevance of most markers is still unclear after years of research and dozens of publications. We conclude that structured reporting is an important step to improve the quality of prognostic marker research and discuss its role in the context of selective reporting, meta-analysis, study registration, predefined statistical analysis plans, and improvement of marker research.