A consensus-based transparency checklist.
Ontology highlight
ABSTRACT:
SUBMITTER: Aczel B
PROVIDER: S-EPMC8324470 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
Publications
A consensus-based transparency checklist.
Aczel Balazs B Szaszi Barnabas B Sarafoglou Alexandra A Kekecs Zoltan Z Kucharský Šimon Š Benjamin Daniel D Chambers Christopher D CD Fisher Agneta A Gelman Andrew A Gernsbacher Morton A MA Ioannidis John P JP Johnson Eric E Jonas Kai K Kousta Stavroula S Lilienfeld Scott O SO Lindsay D Stephen DS Morey Candice C CC Munafò Marcus M Newell Benjamin R BR Pashler Harold H Shanks David R DR Simons Daniel J DJ Wicherts Jelte M JM Albarracin Dolores D Anderson Nicole D ND Antonakis John J Arkes Hal R HR Back Mitja D MD Banks George C GC Beevers Christopher C Bennett Andrew A AA Bleidorn Wiebke W Boyer Ty W TW Cacciari Cristina C Carter Alice S AS Cesario Joseph J Clifton Charles C Conroy Ronán M RM Cortese Mike M Cosci Fiammetta F Cowan Nelson N Crawford Jarret J Crone Eveline A EA Curtin John J Engle Randall R Farrell Simon S Fearon Pasco P Fichman Mark M Frankenhuis Willem W Freund Alexandra M AM Gaskell M Gareth MG Giner-Sorolla Roger R Green Don P DP Greene Robert L RL Harlow Lisa L LL de la Guardia Fernando Hoces FH Isaacowitz Derek D Kolodner Janet J Lieberman Debra D Logan Gordon D GD Mendes Wendy B WB Moersdorf Lea L Nyhan Brendan B Pollack Jeffrey J Sullivan Christopher C Vazire Simine S Wagenmakers Eric-Jan EJ
Nature human behaviour 20200101 1
Similar Datasets
Project description: Not available
| S-EPMC8481359 | biostudies-literature
Project description:ObjectivesTo develop a consensus-based checklist that can be used as a minimum standard to appraise the comprehensiveness, transparency and consistency of cost-of-illness (COI) studies. This is important when, for instance, reviewing and assessing COI studies as part of a systematic review or when building an economic model.MethodsThe development process of the consensus-based checklist involved six steps: (i) a scoping review, (ii) an assessment and comparison of the different checklists and their questions, (iii) the development of a (preliminary) checklist, (iv) expert interviews, (v) the finalization of the checklist, and (vi) the development of guidance statements explaining each question.ResultsThe result was a consensus-based checklist for the critical appraisal of COI studies, comprising seventeen main questions (and some additional subquestions) across three domains: (i) study characteristics; (ii) methodology and cost analysis; and (iii) results and reporting. Guidance statements were developed describing the purpose and meaning behind each question and listing examples of best practice. The following answer categories were suggested to be applied when answering the questions in the checklist: Yes, Partially, No, Not Applicable, or Unclear.ConclusionsThe consensus-based checklist for COI studies is a first step toward standardizing the critical appraisal of COI studies and is one that could be considered a minimum standard. The checklist can help to improve comprehensiveness, transparency and consistency in COI studies, to address heterogeneity, and to enable better comparability of methodological approaches across international studies.
| S-EPMC11574538 | biostudies-literature
Project description:Situational factors can influence cognitive performance and should be considered for conducting cognitive assessments. The objective of this project was to develop a checklist for Cognitive Assessment Requirements (CARE) to identify these situational factors before conducting cognitive assessments and account for them. This study employed a four-round Delphi approach involving 22 experts to identify situational factors that can impact cognitive assessment results. The development of a robust and well-balanced checklist was guided by a consensus-driven approach, which considered metrics such as Interquartile Deviation (IQD) (> 1.00), Percentage of Positive Responses (PPR, above 60%), and mean importance ratings (< 3 on a 5-point Likert scale) to assess both degree of agreement and item importance. Consensus was reached, leading to a 14-item checklist to evaluate cognitive assessment requirements. These items were categorized into six groups: Acute Illness or Physical Discomfort, Medication Effects and Substance Use, Sleep Quality and Fatigue, Emotional State, Language factors, and Environmental factors. The CARE can be employed prior to cognitive assessments to identify situational factors of relevance to the individual client, thereby creating a more favorable environment for cognitive evaluation, and enhancing the reliability of the assessment findings. Furthermore, the CARE can help determine the level of confidence in the results by assessing whether the conditions are conducive to testing or if situational factors may undermine the validity of the evaluation.
| S-EPMC11760535 | biostudies-literature
Project description:BackgroundWithin today's competency-based medical education, traditional set number proficiency benchmarks have been called into question. Checklists may help guide individualized training and standardized outcomes. However, multicenter expert consensus checklists based on established guidelines with supporting validity evidence have not been published for specific emergency ultrasound (EUS) applications. We describe a robust national EUS expert consensus methodology for developing a checklist for the extended focused assessment with sonography in trauma (eFAST examination).MethodsUtilizing the ACEP imaging compendium as a primary reference, 10 national EUS experts iteratively refined and agreed upon a final checklist. To obtain initial reliability and validity evidence, two different EUS experts blinded to resident experience then assessed 24 residents performing an eFAST in a simulated environment. Inter-rater reliability of the checklist was assessed using Cohen's kappa coefficient. Validity was assessed by comparing mean performance with the Student's t-test and discriminant ability of individual checklist items using item-total correlation.ResultsThe 10 EUS experts agreed on the final checklist items after two rounds of iterations. When evaluating 24 emergency medicine (EM) PGY-1 to -4 residents, the kappa correlation between two blinded EUS faculty raters was moderate at 0.670. Kappa and agreement were near-perfect or perfect in right and left chest image optimization, right upper quadrant (RUQ) probe placement, RUQ anatomy identification, and pelvic first-view anatomy identification. The difference in checklist performance between junior and senior EM residents was significant at -8.1% (p = 0.004). Identification of pelvic structures and placement of the probe for pelvic views were found to have an excellent item-total correlation with values of >0.4.ConclusionsWe have described a robust national EUS expert consensus methodology for developing an eFAST checklist based on the ACEP imaging guidelines. Based on this encouraging initial reliability and validity evidence, further research and checklist development is warranted for additional EUS applications.
| S-EPMC9348840 | biostudies-literature
Project description:The use of head kinematic measurement devices has recently proliferated owing to technology advances that make such measurement more feasible. In parallel, demand to understand the biomechanics of head impacts and injury in sports and the military has increased as the burden of such loading on the brain has received focused attention. As a result, the field has matured to the point of needing methodological guidelines to improve the rigor and consistency of research and reduce the risk of scientific bias. To this end, a diverse group of scientists undertook a comprehensive effort to define current best practices in head kinematic measurement, culminating in a series of manuscripts outlining consensus methodologies and companion summary statements. Summary statements were discussed, revised, and voted upon at the Consensus Head Acceleration Measurement Practices (CHAMP) Conference in March 2022. This manuscript summarizes the motivation and methods of the consensus process and introduces recommended reporting checklists to be used to increase transparency and rigor of future experimental design and publication of work in this field. The checklists provide an accessible means for researchers to apply the best practices summarized in the companion manuscripts when reporting studies utilizing head kinematic measurement in sport and military settings.
| S-EPMC9652170 | biostudies-literature
Project description:PurposeRecent expert consensus publications have highlighted the issue of poor reproducibility in magnetic resonance spectroscopy (MRS) studies, mainly due to the lack of standardized reporting criteria, which affects their clinical applicability. To combat this, guidelines for minimum reporting standards (MRSinMRS) were introduced to aid journal editors and reviewers in ensuring the comprehensive documentation of essential MRS study parameters. Despite these efforts, the implementation of MRSinMRS standards has been slow, attributed to the diverse nomenclature used by different vendors, the variety of raw MRS data formats, and the absence of appropriate software tools for identifying and reporting necessary parameters. To overcome this obstacle, we have developed the REproducibility Made Easy (REMY) standalone toolbox.MethodsREMY software supports a range of MRS data formats from major vendors like GE (p. file), Siemens (.twix, .rda, .dcm), Philips (.spar/.sdat), and Bruker (.method), facilitating easy data import and export through a user-friendly interface. REMY employs external libraries such as spec2nii and pymapVBVD to accurately read and process these diverse data formats, ensuring compatibility and ease of use for researchers in generating reproducible MRS research outputs. Users can select and import datasets, choose the appropriate vendor and data format, and then generate an MRSinMRS table, log file, and methodological documents in both Latex and PDF formats.ResultsREMY effectively populated key sections of the MRSinMRS table with data from all supported file types. In the hardware section, it successfully read and filled in fields for Field Strength [T], Manufacturer Name, and Software Version, covering three of the five required hardware fields. However, it could not input data for RF coil and additional hardware information due to their absence in the files. For the acquisition section, REMY accurately read and populated fields for the pulse sequence name, nominal voxel size, repetition time, echo time, number of acquisitions/excitations/shots, spectral width [Hz], and number of spectral points, significantly contributing to the completion of the Acquisition fields of the table. Furthermore, REMY generates a boilerplate methods text section for manuscripts.ConclusionThis approach reduces effort and obstacles associated with writing and reporting acquisition parameters and should lead to the widespread adoption of MRSinMRS within the MRS community.
| S-EPMC10996772 | biostudies-literature
Project description: Not available
| S-EPMC4955793 | biostudies-literature
Project description:IntroductionAcademic medicine continues to struggle in its efforts to compensate scholarly productivity. Academic achievements receive less recognition compared to clinical work, evidenced by a lack of reduced clinical hours or financial incentive. Core departmental education responsibilities are often distributed inequitably across academic departments. An approach using an incentive program, which emphasizes transparency, equity, and consensus may help academic departments share core education responsibilities and reward scholarly activity.MethodsWe launched a two-stage approach to confront the inequitable distribution of educational responsibilities and to recognize the scholarly work among our faculty. In the first stage, baseline education expectations were implemented for all faculty members, which included accountability procedures tied to a financial incentive. The second stage involved the creation of an aAcademic rRelative vValue uUnit (ARVU) system which contained additional activities that were derived and weighted based on stakeholder consensus. The points earned in the ARVU system were applied towards additional financial incentive at academic year-end. We compared education contributions before and after implementation as well as total points earned in the ARVU system.ResultsIn the first year of implementing education expectations, 87% of faculty fulfilled requirements. Those with a heavier clinical load made up the majority of deficient faculty. Those who did not meet education expectations were notified and had their year-end incentive reduced to reflect this. Faculty conference attendance increased by 21% (P<.001) and the number of resident assessments completed increased by 30% (P<.001) compared to the previous year. To date, faculty across the department have logged a total of 1,240 academic activities in the database, which will be converted into financial bonus amounts at year-end.ConclusionWe have seen significant increases in faculty participation in educational activities and learner assessments as well as documentation of activities in the ARVU system. A similar system using different specialty-specific activities may be generalizable and employed at other institutions.
| S-EPMC6860393 | biostudies-literature
Project description:Increasing concerns about climate change imply that decisions on the digitization of healthcare should consider evidence about its carbon footprint (CF). This study aims to develop a transparency catalogue for reporting CF calculations, to compare results, and to assess the transparency (reporting quality) of the current evidence of virtual care (VC) intervention. We developed a checklist of transparency criteria based on the consolidation of three established standards/norms for CF calculation. We conducted a systematic review of primary studies written in English or German on the CF of VC interventions to check applicability. Based on our checklist, we extracted methodological information. We compared the results and calculated a transparency score. The checklist comprises 22 items in the aim, scope, data and analysis categories. Twenty-three studies out of 1466 records were included, mostly addressing telemedicine. The mean transparency score was 38% (minimum 14%, maximum 68%). On average, 148 kg carbon dioxide equivalents per patient were saved. Digitization may have co-benefits, improving care and reducing the healthcare CF. However, the evidence for this is weak, and CF reports are heterogeneous. Our transparency checklist may serve as a reference for developing a standard to assess the CF of virtual and other healthcare and public health services.
| S-EPMC9223517 | biostudies-literature
Project description:BackgroundThere is no consensus on reporting light characteristics in studies investigating non-visual responses to light. This project aimed to develop a reporting checklist for laboratory-based investigations on the impact of light on non-visual physiology.MethodsA four-step modified Delphi process (three questionnaire-based feedback rounds and one face-to-face group discussion) involving international experts was conducted to reach consensus on the items to be included in the checklist. Following the consensus process, the resulting checklist was tested in a pilot phase with independent experts.FindingsAn initial list of 61 items related to reporting light-based interventions was condensed to a final checklist containing 25 items, based upon consensus among experts (final n = 60). Nine items were deemed necessary to report regardless of research question or context. A description of each item is provided in the accompanying Explanation and Elaboration (E&E) document. The independent pilot testing phase led to minor textual clarifications in the checklist and E&E document.InterpretationThe ENLIGHT Checklist is the first consensus-based checklist for documenting and reporting ocular light-based interventions for human studies. The implementation of the checklist will enhance the impact of light-based research by ensuring comprehensive documentation, enhancing reproducibility, and enabling data aggregation across studies.FundingNetwork of European Institutes for Advanced Study (NETIAS) Constructive Advanced Thinking (CAT) programme; Sir Henry Wellcome Postdoctoral Fellowship (Wellcome Trust, 204686/Z/16/Z); Netherlands Organisation for Health Research and Development VENI fellowship (2020-09150161910128); U.S. Department of Defense Grant (W81XWH-16-1-0223); National University of Singapore (NUHSRO/2022/038/Startup/08); and National Research Foundation Singapore (NRF2022-THE004-0002).
| S-EPMC10704221 | biostudies-literature