Anisa Rowhani-Farid’s research while affiliated with University of Maryland, Baltimore and other places

Introduction The development and use of digital tools in various stages of research highlight the importance of novel open science methods for an integrated and accessible research system. The objective of this study was to design and validate a conceptual model of open science on healthcare research processes. Methods This research was conducted in three phases using a mixed-methods approach. The first phase employed a qualitative method, namely purposive sampling and semi-structured interview guides to collect data from healthcare researchers and managers. Influential factors of open science on research processes were extracted for refining the components and developing the proposed model; the second phase utilized a panel of experts and collective agreement through purposive sampling. The final phase involved purposive sampling and Delphi technique to validate the components of the proposed model according to researchers’ perspectives. Findings From the thematic analysis of 20 interview on the study topic, 385 codes, 38 sub-themes, and 14 main themes were extracted for the initial proposed model. These components were reviewed by expert panel members, resulting in 31 sub-themes, 13 main themes, and 4 approved themes. Ultimately, the agreed-upon model was assessed in four layers for validation by the expert panel, and all the components achieved a score of > 75% in two Delphi rounds. The validated model was presented based on the infrastructure and culture layers, as well as supervision, assessment, publication, and sharing. Conclusion To effectively implement these methods in the research process, it is essential to create cultural and infrastructural backgrounds and predefined requirements for preventing potential abuses and privacy concerns in the healthcare system. Applying these principles will lead to greater access to outputs, increasing the credibility of research results and the utilization of collective intelligence in solving healthcare system issues.

The impact and effectiveness of clinical trial data sharing initiatives may differ depending on the data sharing model used. We characterized outcomes associated with models previously used by the U.S. National Institutes of Health (NIH): National Heart, Lung, and Blood Institute’s (NHLBI) centralized model and National Cancer Institute’s (NCI) decentralized model. We identified trials completed in 2010–2013 that met NIH data sharing criteria and matched studies based on cost and/or size, determining whether trial data were shared, and for those that were, the frequency of secondary internal publications (authored by at least one author from the original research team) and shared data publications (authored by a team external to the original research team). We matched 77 NHLBI-funded trials to 77 NCI-funded trials; among these, 20 NHLBI-sponsored trials (26%) and 4 NCI-sponsored trials (5%) shared data (OR 6.4, 95% CI: 2.1, 19.8). From the 4 NCI-sponsored trials sharing data, we identified 65 secondary internal and 2 shared data publications. From the 20 NHLBI-sponsored trials sharing data, we identified 188 secondary internal and 53 shared data publications. The NHLBI’s centralized data sharing model was associated with more trials sharing data and more shared data publications when compared with the NCI’s decentralized model.

Objectives To synthesise research investigating data and code sharing in medicine and health to establish an accurate representation of the prevalence of sharing, how this frequency has changed over time, and what factors influence availability. Design Systematic review with meta-analysis of individual participant data. Data sources Ovid Medline, Ovid Embase, and the preprint servers medRxiv, bioRxiv, and MetaArXiv were searched from inception to 1 July 2021. Forward citation searches were also performed on 30 August 2022. Review methods Meta-research studies that investigated data or code sharing across a sample of scientific articles presenting original medical and health research were identified. Two authors screened records, assessed the risk of bias, and extracted summary data from study reports when individual participant data could not be retrieved. Key outcomes of interest were the prevalence of statements that declared that data or code were publicly or privately available (declared availability) and the success rates of retrieving these products (actual availability). The associations between data and code availability and several factors (eg, journal policy, type of data, trial design, and human participants) were also examined. A two stage approach to meta-analysis of individual participant data was performed, with proportions and risk ratios pooled with the Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis. Results The review included 105 meta-research studies examining 2 121 580 articles across 31 specialties. Eligible studies examined a median of 195 primary articles (interquartile range 113-475), with a median publication year of 2015 (interquartile range 2012-2018). Only eight studies (8%) were classified as having a low risk of bias. Meta-analyses showed a prevalence of declared and actual public data availability of 8% (95% confidence interval 5% to 11%) and 2% (1% to 3%), respectively, between 2016 and 2021. For public code sharing, both the prevalence of declared and actual availability were estimated to be <0.5% since 2016. Meta-regressions indicated that only declared public data sharing prevalence estimates have increased over time. Compliance with mandatory data sharing policies ranged from 0% to 100% across journals and varied by type of data. In contrast, success in privately obtaining data and code from authors historically ranged between 0% and 37% and 0% and 23%, respectively. Conclusions The review found that public code sharing was persistently low across medical research. Declarations of data sharing were also low, increasing over time, but did not always correspond to actual sharing of data. The effectiveness of mandatory data sharing policies varied substantially by journal and type of data, a finding that might be informative for policy makers when designing policies and allocating resources to audit compliance. Systematic review registration Open Science Framework doi: 10.17605/OSF.IO/7SX8U .

The aim of this study was to conduct a comprehensive literature review of the dimensions of open science in research processes. A total of four databases and snowball searching were used for the comprehensive literature review during 2011–2020; then, we were able to find 98 studies based on the inclusion criteria. Also, we used thematic method to review the relevant studies and identified three categories of dimensions in the research process, namely (1) the publication and sharing category including open access, open data, transparency and reproducibility, citizen science, and crowd sourcing; (2) the infrastructure and cultural category including open infrastructure, open education, open tools, budget mechanism, open culture, and communication; and (3) governance and evaluation including policies, governance, and the ethical principles associated with open science. Open science emphasizes the efforts to open and make the scientific research process more inclusive so as to engage the inside and outside actors in the research process.

Background Sharing research outputs with open science methods for different stakeholders causes better access to different studies to solve problems in diverse fields, which leads to equal access conditions to research resources, as well as greater scientific productivity. Therefore, the aim of this study was to perceive the concept of openness in research among Iranian health researchers. Methods From the beginning of August to the middle of November 2021, twenty semi-structured interviews were held with Iranian health researchers from different fields using purposeful, snowball, and convenience sampling. The interviews continued until data saturation. Data analysis was performed with thematic analysis using MAXQDA 20. Finally, seven main issues related to open science were identified. Results Through analysis of the interviews, 235 primary codes and 173 main codes were extracted in 22 subclasses. After careful evaluation and integration of subclasses and classes, they were finally classified into nine categories and three main themes. Analysis showed that openness in research was related to three main themes: researchers’ understanding of open science, the impact of open science on publication and sharing of research, concerns and reluctance to open research. Conclusion The conditions of access to research output should be specified given the diversity of studies conducted in the field of health; issues like privacy as an important topic of access to data and information in the health system should also be specified. Our analysis indicated that the conditions of publication and sharing of research processes should be stated according to different scopes of health fields. The concept of open science was related to access to findings and other research items regardless of cost, political, social, or racial barriers, which could create collective wisdom in the development of knowledge. The process of publication and sharing of research related to open access applies to all types of outputs, conditions of access, increasing trust in research, creation of diverse publication paths, and broader participation of citizens in research. Open science practices should be promoted to increase the circulation and exploitation rates of knowledge while adjusting and respecting the limits of privacy, intellectual property and national security rights of countries.

Background/aims: Inadequate description of trial interventions in publications has been repeatedly reported, a problem that extends to the description of placebo controls. Without describing placebo contents, it cannot be assumed that a placebo is inert. Pharmacologically active placebos complicate accurate estimation and interpretation of efficacy and safety data. In this study, we sought to assess whether placebo contents are described in study protocols and publications of trials published in high-impact medical journals. Methods: We identified all placebo-controlled randomized clinical trials (RCTs) published in 2016 in Annals of Internal Medicine, The BMJ, the Journal of the American Medical Association (JAMA), The Lancet, and the New England Journal of Medicine (NEJM). We included all trials with publicly available study protocols. From journal publications and associated study protocols, we searched and recorded: description of placebo contents; the amount of each placebo ingredient; and investigators' stated rationale for selection of placebo ingredients. Results: We included 113 placebo-controlled RCTs. Of the 113 trials, placebo content was described in 22 (19.5%) journal publications and 51 (45.1%) study protocols. The amount of each placebo ingredient was described in 15 (13.3%) journal publications and 47 (41.6%) study protocols. None of the journal publications explained the rationale for the choice of placebo ingredients, whereas a rationale was provided in 4 (3.5%) study protocols. The stated rationales were to ensure the placebo was visually indistinguishable from the experimental intervention (N = 3) and ensure comparability with a previous study (N = 1). Conclusion: There is no accessible record of the composition of placebos for approximately half of high-impact RCTs, even with access to study protocols. This impedes reproducibility and raises unanswerable questions about what effects-beneficial or harmful-the placebo may have had on trial participants, potentially confounding an accurate assessment of the experimental intervention's safety and efficacy. Considering that study protocols are unabridged, detailed documents describing the trial design and methodology, the fact that less than half of the study protocols described the placebo contents raises concerns about clinical trial transparency. To improve the reproducibility and potential of placebo-controlled RCTs to provide reliable evidence on the efficacy and safety profile of drugs and other experimental interventions, more detail regarding placebo contents must be included in trial documents.

Objectives Many meta-research studies have investigated rates and predictors of data and code sharing in medicine. However, most of these studies have been narrow in scope and modest in size. We aimed to synthesise the findings of this body of research to provide an accurate picture of how common data and code sharing is, how this frequency has changed over time, and what factors are associated with sharing. Design Systematic review with meta-analysis of individual participant data (IPD) from meta-research studies. Data sources: Ovid MEDLINE, Ovid Embase, MetaArXiv, medRxiv, and bioRxiv were searched from inception to July 1 st , 2021. Eligibility criteria Studies that investigated data or code sharing across a sample of scientific articles presenting original medical and health research. Data extraction and synthesis Two authors independently screened records, assessed risk of bias, and extracted summary data from study reports. IPD were requested from authors when not publicly available. Key outcomes of interest were the prevalence of statements that declared data or code were publicly available, or ‘available on request’ (declared availability), and the success rates of retrieving these products (actual availability). The associations between data and code availability and several factors (e.g., journal policy, data type, study design, research subjects) were also examined. A two-stage approach to IPD meta-analysis was performed, with proportions and risk ratios pooled using the Hartung-Knapp-Sidik-Jonkman method for random-effects meta-analysis. Three-level random-effects meta-regressions were also performed to evaluate the influence of publication year on sharing rate. Results 105 meta-research studies examining 2,121,580 articles across 31 specialties were included in the review. Eligible studies examined a median of 195 primary articles (IQR: 113-475), with a median publication year of 2015 (IQR: 2012-2018). Only eight studies (8%) were classified as low risk of bias. Useable IPD were assembled for 100 studies (2,121,197 articles), of which 94 datasets passed independent reproducibility checks. Meta-analyses revealed declared and actual public data availability rates of 8% (95% CI: 5-11%, 95% PI: 0-30%, k=27, o=700,054) and 2% (95% CI: 1-3%, 95% PI: 0-11%, k=25, o=11,873) respectively since 2016. Meta-regression indicated that only declared data sharing rates have increased significantly over time. For public code sharing, both declared and actual availability rates were estimated to be less than 0.5% since 2016, and neither demonstrated any meaningful increases over time. Only 33% of authors (95% CI: 5-69%, k=3, o=429) were estimated to comply with mandatory data sharing policies of journals. Conclusion Code sharing remains persistently low across medicine and health research. In contrast, declarations of data sharing are also low, but they are increasing. However, they do not always correspond to the actual sharing of data. Mandatory data sharing policies of journals may also not be as effective as expected, and may vary in effectiveness according to data type - a finding that may be informative for policymakers when designing policies and allocating resources to audit compliance.

Objective This study examined the extent to which trials presented at major international medical conferences in 2016 consistently reported their study design, end points and results across conference abstracts, published article abstracts and press releases. Design Cross-sectional analysis of clinical trials presented at 12 major medical conferences in the USA in 2016. Conferences were identified from a list of the largest clinical research meetings aggregated by the Healthcare Convention and Exhibitors Association and were included if their abstracts were publicly available. From these conferences, all late-breaker clinical trials were included, as well as a random selection of all other clinical trials, such that the total sample included up to 25 trial abstracts per conference. Main outcome measures First, it was determined if trials were registered and reported results in an International Committee of Medical Journal Editors-approved clinical trial registry. Second, it was determined if trial results were published in a peer-reviewed journal. Finally, information on trial media coverage and press releases was collected using LexisNexis. For all published trials, the consistency of reporting of the following characteristics was examined, through comparison of the trials’ conference and publication abstracts: primary efficacy endpoint definition, safety endpoint identification, sample size, follow-up period, primary end point effect size and characterisation of trial results. For all published abstracts with press releases, the characterisation of trial results across conference abstracts, press releases and publications was compared. Authors determined consistency of reporting when identical information was presented across abstracts and press releases. Primary analyses were descriptive; secondary analyses included χ ² tests and multiple logistic regression. Results Among 240 clinical trials presented at 12 major medical conferences, 208 (86.7%) were registered, 95 (39.6%) reported summary results in a registry and 177 (73.8%) were published; 82 (34.2%) were covered by the media and 68 (28.3%) had press releases. Among the 177 published trials, 171 (96.6%) reported the definition of primary efficacy endpoints consistently across conference and publication abstracts, whereas 96/128 (75.0%) consistently identified safety endpoints. There were 107/172 (62.2%) trials with consistent sample sizes across conference and publication abstracts, 101/137 (73.7%) that reported their follow-up periods consistently, 92/175 (52.6%) that described their effect sizes consistently and 157/175 (89.7%) that characterised their results consistently. Among the trials that were published and had press releases, 32/32 (100%) characterised their results consistently across conference abstracts, press releases and publication abstracts. No trial characteristics were associated with reporting primary efficacy end points consistently. Conclusions For clinical trials presented at major medical conferences, primary efficacy endpoint definitions were consistently reported and results were consistently characterised across conference abstracts, registry entries and publication abstracts; consistency rates were lower for sample sizes, follow-up periods, and effect size estimates. Registration This study was registered at the Open Science Framework ( https://doi.org/10.17605/OSF.IO/VGXZY ).

Background: The impact and value of clinical trial data sharing, including the number and quality of publications that result from shared data — shared data publications — may differ depending on the data sharing model used. Methods: We characterized the outcomes associated with two data sharing models previously used by Institutes of the U.S. National Institutes of Health (NIH): NHLBIs centralized model, which uses a repository to manage data sharing requests, and NCIs decentralized model, which entrusted research groups to independently manage data sharing requests. We identified trials completed in 2010 that met NIH data sharing criteria and matched studies sponsored by each Institute based on cost or size, determining whether trial data were shared and the frequency of shared data publications. Results: We identified 14 NHLBI-funded trials and 48 NCI-funded trials that met NIH data sharing criteria. We matched 14 NCI-funded trials to the 14 NHLBI-funded trials; among these, 4 NHLBI-sponsored trials (29%) and 2 NCI-sponsored trials (14%) shared data. From the 2 NCI-sponsored trials sharing data, we identified 2 shared data publications, one per trial, both of which were meta-analyses. From the 4 NHLBI-sponsored trials sharing data, we identified 7 shared data publications, all using data from 1 trial, 5 of which were pooled analyses and 2 reported secondary outcomes. Conclusion: When characterizing the outcomes associated with two NIH data sharing models, both the NHLBI and the NCI models resulted in only 21% of trials sharing data and few shared data publications. There are opportunities to optimize clinical trial data sharing efforts both to enhance clinical trial data sharing and increase the number of shared data publications.

Numerous studies have demonstrated low but increasing rates of data and code sharing within medical and health research disciplines. However, it remains unclear how commonly data and code are shared across all fields of medical and health research, as well as whether sharing rates are positively associated with implementation of progressive policies by publishers and funders, or growing expectations from the medical and health research community at large. Therefore this systematic review aims to synthesise the findings of medical and health science studies that have empirically investigated the prevalence of data or code sharing, or both. Objectives include the investigation of: (i) the prevalence of public sharing of research data and code alongside published articles (including preprints), (ii) the prevalence of private sharing of research data and code in response to reasonable requests, and (iii) factors associated with the sharing of either research output (e.g., the year published, the publisher’s policy on sharing, the presence of a data or code availability statement). It is hoped that the results will provide some insight into how often research data and code are shared publicly and privately, how this has changed over time, and how effective some measures such as the institution of data sharing policies and data availability statements have been in motivating researchers to share their underlying data and code.