Literature DB >> 29449994

Reporting guidelines for health care simulation research: extensions to the CONSORT and STROBE statements.

Adam Cheng1, David Kessler2, Ralph Mackinnon3,4, Todd P Chang5, Vinay M Nadkarni6, Elizabeth A Hunt7, Jordan Duval-Arnould7, Yiqun Lin8, David A Cook9, Martin Pusic10, Joshua Hui11, David Moher12, Matthias Egger13, Marc Auerbach14.   

Abstract

BACKGROUND: Simulation-based research (SBR) is rapidly expanding but the quality of reporting needs improvement. For a reader to critically assess a study, the elements of the study need to be clearly reported. Our objective was to develop reporting guidelines for SBR by creating extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statements.
METHODS: An iterative multistep consensus-building process was used on the basis of the recommended steps for developing reporting guidelines. The consensus process involved the following: (1) developing a steering committee, (2) defining the scope of the reporting guidelines, (3) identifying a consensus panel, (4) generating a list of items for discussion via online premeeting survey, (5) conducting a consensus meeting, and (6) drafting reporting guidelines with an explanation and elaboration document.
RESULTS: The following 11 extensions were recommended for CONSORT: item 1 (title/abstract), item 2 (background), item 5 (interventions), item 6 (outcomes), item 11 (blinding), item 12 (statistical methods), item 15 (baseline data), item 17 (outcomes/ estimation), item 20 (limitations), item 21 (generalizability), and item 25 (funding). The following 10 extensions were recommended for STROBE: item 1 (title/abstract), item 2 (background/rationale), item 7 (variables), item 8 (data sources/measurement), item 12 (statistical methods), item 14 (descriptive data), item 16 (main results), item 19 (limitations), item 21 (generalizability), and item 22 (funding). An elaboration document was created to provide examples and explanation for each extension.
CONCLUSIONS: We have developed extensions for the CONSORT and STROBE Statements that can help improve the quality of reporting for SBR (Sim Healthcare 00:00-00, 2016).

Entities:  

Keywords:  Extension; Health care; Reporting guidelines; Research; Simulation

Year:  2016        PMID: 29449994      PMCID: PMC5806464          DOI: 10.1186/s41077-016-0025-y

Source DB:  PubMed          Journal:  Adv Simul (Lond)        ISSN: 2059-0628


Background

Simulation has seen growing use in health care as a “tool, device, and/or environment (that) mimics an aspect of clinical care” [1] to improve health care provider performance, health care processes, and ultimately patient outcomes [1-5]. The use of simulation in health care has been accompanied by an expanding body of simulation-based research (SBR) addressing both educational and clinical issues [6-15]. Broadly speaking, SBR can be broken down into 2 categories: (1) research addressing the efficacy of simulation as a training methodology (ie, simulation-based education as the subject of research) and (2) research using simulation as an investigative methodology (ie, simulation as the environment for research) [16, 17]. Many features of SBR overlap with traditional clinical or educational research. However, the use of simulation in research introduces a unique set of features that must be considered when designing the methodology and reported when publishing the study [16-19]. As has been shown in other fields of medicine [20], the quality of reporting in health professions education research is inconsistent and sometimes poor [1, 11, 21–23]. Systematic reviews in medical education have quantitatively documented missing elements in the abstracts and main texts of published reports, with particular deficits in the reporting of study design, definitions of independent and dependent variables, and study limitations [21-23]. In research specific to simulation for health care professions education, a systematic review noted many studies failing to “clearly describe the context, instructional design, or outcomes.” [1] Another study found that only 3 % of studies incorporating debriefing in simulation education reported all the essential characteristics of debriefing [11]. Failure to adequately describe the key elements of a research study impairs the efforts of editors, reviewers, and readers to critically appraise strengths and weaknesses [24, 25] or apply and replicate findings [26]. As such, incomplete reporting represents a limiting factor in the advancement of the field of simulation in health care. Recognition of this problem in clinical research has led to the development of a growing number of reporting guidelines in medicine and other fields, including the Consolidated Standards of Reporting Trials (CONSORT) Statement for randomized trials [27-30], the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement for observational studies [31, 32], and the Preferred Reporting Items for Systematic Review and Meta-Analyses Statement [33-35], among more than 250 others [36]. Transparent reporting of research allows readers to clearly identify and understand “what was planned, what was done, what was found, and what conclusions were drawn.” [31] In addition to these statements, experts have encouraged [37] and published extensions to existing statements that focus on specific methodological approaches [38, 39] or clinical fields [40, 41]. In this study, we aimed to develop reporting guidelines for SBR by creating extensions to the CONSORT Statement and the STROBE Statement specific to the use of simulation in health care research. These reporting guidelines are meant to be used by authors submitting manuscripts involving SBR and to assist editors and journal reviewers when assessing the suitability of simulation-based studies for publication.

Methods

The study protocol was reviewed by Yale University Biomedical Institutional Review Board and was granted exempt status. We conducted a multistep consensus process on the basis of previously described steps for developing health research reporting guidelines [42]. These steps involved the following: (1) developing a steering committee, (2) defining the scope of the reporting guidelines, (3) identifying a consensus panel, (4) generating a list of items for discussion, (5) conducting a consensus meeting, and (6) drafting reporting guidelines and an explanation and elaboration document.

Development of the steering committee

A steering committee was formed consisting of 12 members with expertise in simulation-based education and research, medical education research, study design, statistics, epidemiology, and clinical medicine. The steering committee defined the scope of the reporting guidelines, identified participants for the consensus process, generated a premeeting survey, planned and conducted the consensus meeting, and ultimately drafted and refined the final version of the reporting guidelines and the explanation and elaboration document.

Defining the scope of the reporting guidelines

To clarify the scope of the reporting guideline extensions, we defined simulation as encompassing a diverse range of products including computer-based virtual reality simulators, high-fidelity and static mannequins, plastic models and task trainers, live animals, inert animal products, human cadavers, and standardized or simulated patients (ie, individuals trained to portray a patient). Our definition excluded research using computational simulation and mathematical modeling, because the guidelines were developed for research using human participants, either as learners or health care providers [1]. The steering committee determined to create reporting guidelines encompassing the following 2 categories of SBR: (1) studies evaluating simulation for educational use and (2) studies using simulation as investigative methodology [16]. We identified the CONSORT [28] and STROBE [31, 32] Statements as reflecting the current reporting standards in health care research and aimed to develop extensions of these 2 statements for quantitative SBR. The CONSORT Statement and extensions were developed for randomized trials, and the STROBE Statement and extensions were developed for observational studies (cohort, case–control, and cross-sectional study designs). Our guideline extensions are not intended for qualitative research, mixed methods research, or validation studies.

Identification of consensus panel participants

The steering committee aimed to identify a consensus group with a broad range of expertise in SBR, including experience in conducting single and multicenter simulation-based studies, expertise in educational research, statistics, clinical epidemiology, and research methodology, and with varying clinical backgrounds. We invited the editor-in-chief and editorial board members of the following 3 health care simulation journals: Simulation in Healthcare, BMJ Simulation and Technology-Enhanced Learning, and Clinical Simulation in Nursing, and editorial board members from the following 2 medical education journals: Medical Education and Advances in Health Sciences Education. In total, 60 expert participants were invited to complete the online survey.

Generating a list of items for discussion

Before the consensus meeting, we surveyed the expert participants via a premeeting survey (www.surveymonkey.com) to identify items in the CONSORT and STROBE Statements that required an extension for SBR. The survey included all items from both the CONSORT and STROBE Statements and was pilot tested among steering committee members before being posted online. Participants were asked to provide suggested wording for the items they identified as requiring an extension. Participants were also given the option of suggesting new simulation-specific items for both the CONSORT and STROBE Statements. On the basis of methods previously used to develop extensions to the CONSORT Statement [40], we used a cutoff of endorsement by at least one third of respondents to identify high priority items for discussion during the consensus meeting.

Consensus meeting

A 5-h consensus conference was conducted in January 2015 in New Orleans, during the annual International Network for Simulation-Based Pediatric Innovation, Research and Education (INSPIRE) meeting. The initial 60 consensus panel participants were invited to attend the consensus conference as well as INSPIRE network members (ie, clinicians, researchers, educators, psychologists, statisticians, and epidemiologists). The INSPIRE network is the world’s largest health care simulation research network with a proven track record of conducting rigorous simulation-based studies in health care [43-50]. The results of the online survey were circulated to each member of the steering committee, who were then assigned to review specific items from the CONSORT and STROBE statements on the basis of their expertise. The consensus meeting started with a brief didactic presentation reviewing the CONSORT and STROBE Statements, followed by a description of the study objectives and consensus process. In small groups, each steering committee member led a discussion with 4 or 5 individuals tasked with determining whether a simulation-specific extension was required for their assigned items and if so to recommend wording for the extension. Consensus panel participants were evenly distributed among small groups and specifically assigned to review items on the basis of their area of expertise. High priority items were discussed at length, but all other checklist items were also discussed in the small groups. After small group discussion, the recommended simulation-specific extensions for both the CONSORT and STROBE Statements were presented to the entire group of participants. Each proposed extension was discussed before recommended wording was established. Minutes from the small and large group discussions were used to inform the development of the explanation and elaboration document [42].

Drafting reporting guidelines

The proposed extensions were circulated for comment among all meeting participants and consensus panel participants who could not attend the meeting. The steering committee used the comments to further refine the extension items. To evaluate these items in practice, 4 members of the steering committee independently pilot tested both the CONSORT and STROBE Statements with simulation-specific extensions. They used 2 published SBR studies (ie, one for each type of SBR), while ensuring that 1 study was a randomized trial and the other an observational study. Feedback from pilot testing informed further revisions. The final reporting guidelines with extensions were circulated to the steering committee 1 last time to ensure the final product accurately represented discussion during and after the consensus conference. An explanation and elaboration document was developed by the steering committee to provide further detail for each item requiring a simulation-specific extension [42].

Results

Premeeting survey

There was a 75 % response rate for the survey, with 45 of the 60 participants completing the entire survey. An additional 12 other participants (20 %) partially completed the survey. Of the 57 participants who responded to the survey, 17 were medical journal editors or editorial board members, 24 had advanced degrees (Masters, PhD), 16 with advanced degrees in medical education or educational psychology, 6 were nurses, 1 was a psychologist, and 54 were physicians (representing anesthesiology, critical care, emergency medicine, pediatrics, and surgery). Of the 3 participants who did not complete the survey, 2 were physicians and 1 was a scientist. The results of the survey are described in Additional file 1: Supplemental Digital Content 1. In total, 35 consensus panel participants who completed the premeeting survey attended the consensus conference. An additional 30 attendees were INSPIRE network members. Of the 65 total attendees at the consensus conference, 12 were medical journal editors or editorial board members, 18 had advanced degrees (Masters, PhD), 4 were nurses, 1 was a psychologist, and 60 were physicians (representing anesthesiology, critical care, emergency medicine, pediatrics, and surgery). The following 11 simulation-specific extensions were recommended for the CONSORT Statement: item 1 (title and abstract), item 2 (background), item 5 (interventions), item 6 (outcomes), item 11 (blinding), item 12 (statistical methods), item 15 (baseline data), item 17 (outcomes and estimation), item 20 (limitations), item 21 (generalizability), and item 25 (funding). Participants agreed on the importance of describing the rationale for and design of the simulation-based intervention. Because many simulation-based studies use assessment tools as an outcome measure, participants thought that it was important to report the unit of analysis and evidence supporting the validity and reliability of the assessment tool(s) when available. In the discussion section, participants thought that it was important to describe the limitations of SBR and the generalizability of the simulation-based outcomes to clinical outcomes (when applicable). Participants also agreed that it was important to identify the simulator brand used in the study and if conflicts of interest for intellectual property existed among investigators. The group did not feel that modifications to the CONSORT flow diagram were required for SBR. See Table 1 for CONSORT extensions for SBR.
Table 1

Simulation-Based Research Extensions for the CONSORT Statement

ItemItem numberCONSORT description (Randomized Controlled Trials)Extension for SBR
Title and abstract1a. Identification as a randomized trial in the titleb. Structured summary of trial design, methods, results, and conclusionsIn abstract or key terms, the MESH or searchable keyword term must have the word “simulation” or “simulated.”
Introduction
 Background2a. Scientific background and explanation of rationaleb. Specific objectives or hypothesesClarify whether simulation is subject of research or investigational method for research.
Methods
 Trial design3a. Description of trial design (such as parallel, factorial) including allocation ratiob. Important changes to methods after trial commencement (such as eligibility criteria), with reasons
 Participants4a. Eligibility criteria for participantsb. Settings and locations where the data were collected
 Interventions5The interventions for each group with sufficient details to allow for replication, including how and when they were actually administered.Describe the theoretical and/or conceptual rationale for the design of each intervention.Clearly describe all simulation-specific exposures, potential confounders, and effect modifiers.
 Outcomes6a. Completely defined prespecified primary and secondary outcome measures, including how and when they were assessedb. Any changes to trial outcomes after the trial commenced, with reasonsIn describing the details of methods of assessment, include (when applicable) the setting, instrument, simulator type, timing in relation to the intervention, along with any methods used to enhance the quality of measurements.Provide evidence to support the validity and reliability of assessment tools in this context (if available).
 Sample size/study size7a. How sample size was determinedb. When applicable, explanation of any interim analyses and stopping guidelines
 Randomization: sequence generation8a. Method used to generate the random allocation sequenceb. Type of randomization and details of any restriction (such as blocking and block size)
 Randomization: allocation concealment mechanism9Mechanism used to implement the random allocation sequence (such as sequentially numbered containers), describing any steps taken to conceal the sequence until interventions were assigned
 Randomization: implementation10Who generated the random allocation sequence, who enrolled participants, and who assigned participants to interventions
 Blinding (masking)11a. If done, who was blinded after assignments to interventions (e.g., participants, care providers, those assessing outcomes) and howb. If relevant, description of the similarity of interventionsDescribe strategies to decrease risk of bias, when blinding is not possible.
 Statistical methods12a. Statistical methods used to compare groups for primary and secondary outcomesb. Methods for additional analyses, such as subgroup analyses and adjusted analysesClearly indicate the unit of analysis (e.g., individual, team, system), identify repeated measures on subjects, and describe how these issues were addressed.
Results
 Participant flow (a diagram is strongly recommended)13a. For each group, the numbers of participants who were randomly assigned, received intended treatment, and were analyzed for the primary outcomeb. For each group, losses and exclusions after randomization, together with reasons
 Recruitment14a. Dates defining the periods of recruitment and follow-upb. Why the trial ended or was stopped
 Baseline data15A table showing baseline demographic and clinical characteristics of each groupIn describing characteristics of study participants, include their previous experience with simulation and other relevant features as related to the intervention(s).
 Numbers analyzed16For each group, number of participants (denominator) included in each analysis and whether analysis was by original assigned groups
 Outcomes and estimation17a. For each primary and secondary outcome, results for each group, and the estimated effect size and its precision (such as 95 % confidence interval)b. For binary outcomes, presentation of both absolute and relative effect sizes is recommendedFor assessments involving >1 rater, interrater reliability should be reported.
 Ancillary analyses18Results of any other analyses performed, including subgroup analyses and adjusted analyses, distinguishing prespecified from exploratory
 Adverse events19All important harms or unintended effects in each group (for specific guidance, see CONSORT for harms)
Discussion
 Limitations20Trial limitations, addressing sources of potential bias, imprecision, and, if relevant, multiplicity of analysesSpecifically discuss the limitations of SBR.
 Generalizability21Generalizability (external validity, applicability) of the trial findingsDescribe generalizability of simulation-based outcomes to patient-based outcomes (if applicable).
 Interpretation22Interpretation consistent with results, balancing benefits and harms, and considering other relevant evidence
Other information
 Registration23Registration number and name of trial registry
 Protocol24Where the full trial protocol can be accessed, if available
 Funding25Sources of funding and other support (such as supply of drugs), role of fundersList simulator brand and if conflict of interest for intellectual property exists.

MESH Medical Subject Headings

Simulation-Based Research Extensions for the CONSORT Statement MESH Medical Subject Headings The following 10 extensions were drafted for the STROBE Statement: item 1 (title and abstract), item 2 (background/ rationale), item 7 (variables), item 8 (data sources/measurement), item 12 (statistical methods), item 14 (descriptive data), item 16 (main results), item 19 (limitations), item 21 (generalizability), and item 22 (funding). A similar emphasis was placed on the importance of describing all simulation-specific exposures, confounders, and effect modifiers, as was discussed for the CONSORT. Other extensions for the STROBE were under similar categories as the proposed extensions for the CONSORT. See Table 2 for STROBE extensions for SBR.
Table 2

Simulation-Based Research Extensions for the STROBE Statement

ItemItem numberSTROBE description (Observational Studies)Extension for SBR
Title and abstract1a. Indicate the study’s design with a commonly used term in the title or the abstract.b. Provide in the abstract an informative and balanced summary of what was done and what was found.In abstract or key terms, the MESH or searchable keyword term must have the word simulation or simulated.
Introduction
 Background/rationale2Explain the scientific background and rationale for the investigation being reported.Clarify whether simulation is subject of research or investigational method for research.
 Objectives3State specific objectives, including any prespecified hypotheses.
Methods
 Study design4Present key elements of study design early in the paper.
 Setting5Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection.
 Participants6a. Cohort study: give the eligibility criteria and the sources and methods of selection of participants. Describe methods of follow-up.Case–control study: give the eligibility criteria and the sources and methods of case ascertainment and control selection. Give the rationale for the choice of cases and controls.Cross-sectional study: give the eligibility criteria and the sources and methods of selection of participants.b. Cohort study: for matched studies, give matching criteria and number of exposed and unexposed.Case–control study: for matched studies, give matching criteria and the number of controls per case.
 Variables7Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers.Give diagnostic criteria, if applicable.Describe the theoretical and/or conceptual rationale for the design of the intervention/exposure.Describe the intervention/exposure with sufficient detail to permit replication.Clearly describe all simulation-specific exposures, potential confounders, and effect modifiers.
 Data sources/measurement8For each variable of interest, give sources of data and details of methods of assessment (measurement).Describe comparability of assessment methods if there is >1 group.In describing the details of methods of assessment, include (when applicable) the setting, instrument, simulator type, timing in relation to the intervention, along with any methods used to enhance the quality of measurements.Provide evidence to support the validity and reliability of assessment tools in this context (if available).
 Bias9Describe any efforts to address potential sources of bias.
 Study size10Explain how the study size was arrived.
 Quantitative variables11Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why.
 Statistical methods12a. Describe all statistical methods, including those used to control for confounding.b. Describe any methods used to examine subgroups and interactions.c. Explain how missing data were addressed.d. Cohort study: if applicable, explain how loss to follow-up was addressed.Case–control study: if applicable, explain how matching of cases and controls was addressed.Cross-sectional study: if applicable, describe analytical methods taking account of sampling strategy.e. Describe any sensitivity analyses.Clearly indicate the unit of analysis (e.g., individual, team, system), identify repeated measures on subjects, and describe how these issues were addressed.
Results
 Participants13a. Report the numbers of individuals at each stage of the study (e.g., numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analyzed).b. Give reasons for nonparticipation at each stage.c. Consider use of a flow diagram.
 Descriptive data14a. Give characteristics of study participants (e.g., demographic, clinical, social) and information on exposures and potential confounders.b. Indicate the number of participants with missing data for each variable of interest.c. Cohort study: summarize follow-up time (e.g., average and total amount).In describing characteristics of study participants, include their previous experience with simulation and other relevant features as related to the intervention(s).
 Outcome data15Cohort study: report numbers of outcome events or summary measures over time.Case–control study: report numbers in each exposure category or summary measures of exposure.Cross-sectional study: report numbers of outcome events or summary measures.
 Main results16a. Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (e.g., 95 % confidence intervals).Make clear which confounders were adjusted for and why they were included.b. Report category boundaries when continuous variables were categorized.c. If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period.For assessments involving >1 rater, interrater reliability should be reported.
 Other analyses17Report other analyses done (e.g., analyses of subgroups and interactions and sensitivity analyses).
Discussion
 Key results18Summarize key results with reference to study objectives.
 Limitations19Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias.Specifically discuss the limitations of SBR.
 Interpretation20Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence.
 Generalizability21Discuss the generalizability (external validity) of the study results.Describe generalizability of simulation-based outcomes to patient-based outcomes (if applicable).
Other information
 Funding22Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the present article is based.List simulator brand and if conflict of interest for intellectual property exists.

MESH Medical Subject Headings

Simulation-Based Research Extensions for the STROBE Statement MESH Medical Subject Headings For both the CONSORT and STROBE Statements, extensive discussion occurred in the consensus meeting related to the educational intervention and controlling for simulation-specific variables that pose as potential threats to the internal validity of simulation studies. A group of consensus panel participants with expertise in simulation-based education and instructional design used their knowledge of educational theory, existing educational research guidelines [51], and systematic reviews of SBR [1, 5–8, 11] to address this issue (Table 3). Table 3 offers an additional checklist of key elements specific to SBR, for item 5 (interventions) on the CONSORT Statement and item 7 (variables) on the STROBE Statement, that should be reported for all simulation studies, for both the intervention and control groups (if applicable).
Table 3

Key Elements to Report for Simulation-Based Research

Elementsa Subelementsb Descriptor
Participant orientationOrientation to the simulatorDescribe how participants were oriented to the simulator (e.g., method, content, duration).
Orientation to the environmentDescribe how participants were oriented to the environment (e.g., method, content, duration).
Simulator type [16]Simulator make and modelDescribe the simulator make and model.
Simulator functionalityDescribe functionality and/or technical specifications that are relevant to the research question. Describe modifications, if any. Describe limitations of the simulator.
Simulation environment [16]LocationDescribe where the simulation was conducted (e.g., in situ clinical environment, simulation center, etc.).
EquipmentDescribe the nature of the equipment available (e.g., type, amount, location, size, etc.).
External stimuliDescribe any external stimuli (e.g., background noise).
Simulation event/scenario [16]Event descriptionDescribe if the event was programmed and/or scripted (e.g., orientation to event, scenario progression, triggers). If a scenario was used, the scenario script should be provided as an appendix.
Learning objectivesList the learning objectives and describe how they were incorporated into the event.
Group vs. individual practiceDescribe if the simulation was conducted in groups or as individuals.
Use of adjunctsDescribe if adjuncts (e.g., moulage, media, props) were used.
Facilitator/operator characteristicsDescribe experience (e.g., clinical, educational), training (e.g., fellowship, courses), profession.
Pilot testingDescribe if pilot testing was conducted (e.g., number, duration, frequency).
Actors/confederates/standardized/simulated patients [16]Describe experience (e.g., clinical, educational), training (e.g., fellowship, courses), profession, sex. Describe various roles, including training, scripting, orientation, and compliance with roles.
Instructional design (for educational interventions) [53] or exposure (for simulation as investigative methodology) [16]DurationDescribe the duration of the educational intervention. If the intervention involves more than one segment, describe the duration of each segment.
TimingDescribe the timing of the educational intervention relative to the time when assessment/data collection occurs (e.g., just-in-time training).
Frequency/repetitionsDescribe how many repetitions were permitted and/or the frequency of training (e.g., deliberate practice).
Clinical variationDescribe the variation in clinical context (e.g., multiple different patient scenarios).
Standards/assessmentDescribe predefined standards for participant performance (e.g., mastery learning) and how these standards were established.
Adaptability of interventionDescribe how the training was responsive to individual learner needs (e.g., individualized learning).
Range of difficultyDescribe the variation in difficulty or complexity of the task.
Nonsimulation interventions and adjunctsDescribe all other nonsimulation interventions (e.g., lecture, small group discussion) or educational adjuncts (e.g., educational video), how they were used, and when they were used relative to the simulation intervention.
IntegrationDescribe how the intervention was integrated into curriculum.
Feedback and/or debriefing [11]SourceDescribe the source of feedback (e.g., computer, simulator, facilitator).
DurationDescribe the amount of time spent.
Facilitator presenceDescribe if a facilitator was present (yes/no), and if so, how many facilitators.
Facilitator characteristicsDescribe experience (e.g., clinical, educational), training (e.g., fellowship, courses), profession, sex.
ContentDescribe content (e.g., teamwork, clinical, technical skills, and/or inclusion of quantitative data, etc.).
Structure/methodDescribe the method of debriefing/feedback and debriefing framework used (ie, phases).
TimingDescribe when the feedback and/or debriefing was conducted relative to the simulation event (e.g., terminal vs. concurrent).
VideoDescribe if video was used (yes/no) and how it was used.
ScriptingDescribe if a script was used (yes/no) and provide script details as an appendix.

aThese elements may apply for the simulation intervention (e.g., randomized controlled trial or observational study with simulation as an educational intervention) or when simulation is the environment for research (e.g., randomized controlled trial or observational study using simulation as an investigative methodology). Elements should be described in sufficient detail to permit replication

bDescription is required only if applicable

Key Elements to Report for Simulation-Based Research aThese elements may apply for the simulation intervention (e.g., randomized controlled trial or observational study with simulation as an educational intervention) or when simulation is the environment for research (e.g., randomized controlled trial or observational study using simulation as an investigative methodology). Elements should be described in sufficient detail to permit replication bDescription is required only if applicable In modeling the explanation and elaboration document after other similar documents published in conjunction with reporting guidelines [28, 32], we provide a specific example for each item requiring a new extension coupled with the background and rationale for including that information for that item. We encourage readers to refer to the explanation and elaboration document to seek further detail about the nature and type of recommended reporting for each new extension (see Additional file 2: Supplemental Digital Content 2).

Discussion

We have developed reporting guidelines for SBR by creating extensions to both the CONSORT [28] and STROBE [31] Statements. These new extensions were developed via a consensus-building process with multiple iterative steps involving an international group of experts with diverse backgrounds and expertise. By creating extensions to both the CONSORT and STROBE Statements that can be applied to studies in both categories of SBR, we have developed reporting guidelines that are applicable to most studies involving simulation in health care research. To further assist authors in reporting SBR studies, we have published an explanation and elaboration document as an appendix that provides specific examples and details for all the new simulation-specific extensions for both the CONSORT and STROBE Statements. The CONSORT and STROBE Statements with accompanying SBR extensions are meant to serve as a guide to reporting. As with other CONSORT and STROBE Statements, the items are not meant to “prescribe the reporting in a rigid format,” but rather the “order and format for presenting information depend on author preferences, journal style, and the traditions of the research field.” [28, 31] We encourage authors to refer to the explanation and elaboration document that provides details regarding specific elements related to individual items that should be reported for SBR. The use of reporting guidelines can have positive effects on various health care simulation stakeholders, including funders of SBR and those applying for funding (ie, use as a template for grant applications), educators (ie, use as a training tool), and students (ie, use to develop protocols for coursework or research) [33]. The application of these reporting guidelines will help enhance quality of reporting for quantitative SBR and assist journal reviewers and editors when faced with assessing the strengths and weaknesses of simulation-based studies in health care [24, 52, 53]. We encourage journals publishing SBR to consider endorsing the simulation-specific extensions for the CONSORT and STROBE Statements and adding these to their “instructions for authors.” Simulation-based research has several unique factors that prompted us to develop simulation-specific extensions for both the CONSORTand STROBE Statements. First, there are a wide variety of simulators and simulation modalities available for use in research [16]. This, coupled with a plethora of instructional design features in simulation-based educational research, makes describing the simulation intervention a critically important component of any educational study involving simulation (Table 3) [6, 8, 19]. Second, SBR provides opportunity for the investigator to standardize the simulated environment and/or simulated patient condition. Standardization of the environment and patient condition allows the investigator to account for many of the potential threats to internal validity that are associated with simulation. Clear reporting of standardization strategies helps the reader understand how the independent variable was isolated (Table 3) [16]. Third, many simulation studies involve capturing outcomes from a variety of data sources (e.g., observation, video review, simulator data capture). When assessment instruments are used (e.g., expert raters assessing performance), it is imperative to discuss the psychometric properties of these instruments [5]. Existing guidelines fall short in this regard, and these new guidelines help address this issue. Lastly, simulation-based studies assessing outcomes in the simulated environment only (e.g., clinical performance) should attempt to provide evidence to support how the findings in the simulated environment translate to a valid representation of performance in the real clinical environment [3]. By doing so, authors help convey the relevance and importance of their findings.

Limitations

Our consensus process has several limitations. Although we had a 75 % response rate for our survey, an additional 20 % of participants only partially completed the survey. This may have potentially introduced a selection bias, although the survey represented only 1 step in our consensus-building process. We include a wide variety of experts in our consensus meeting, but many of them had a pediatric clinical background. We minimized this potential bias by ensuring that each breakout group had at least 1 expert participant with a background outside of pediatrics. Furthermore, the principles of SBR are common across specialties and professions, and INSPIRE network members represent researchers who are recognized internationally for being leaders in SBR. We based our reporting guidelines on the CONSORT and STROBE guidelines developed by clinical researchers. Other guidelines could have been used as a starting point such as the American Education Research Association standards developed in 2006 [54]. Our logic was to start with reporting guidelines that were applicable to all types of research, thus providing us more flexibility in generating extensions for both types of SBR. Cross-checking against the American Education Research Association guideline does not reveal areas that we might have missed. Although we tried to develop reporting guidelines for all types of SBR, we recognize that there may be specific types of research that may require new items or different extensions. For example, studies designed to evaluate the validity of simulation-based assessments vary in their reporting requirements. The Standards for Reporting of Diagnostic Accuracy Statement addresses these points [55], and a recent review operationalized these standards and applied them to SBR [56]. Other reporting guidelines that might be amenable for simulation-specific extensions include the Consolidated Criteria for Reporting Qualitative Research [57], and the Standards for Quality Improvement Reporting Excellence [58] guidelines for reporting quality improvement studies. Because the field of SBR grows, the simulation-specific extensions for the CONSORT and STROBE Statements may need to be revised or refined. We encourage authors, reviewers, and editors to visit our Web site (http://inspiresim.com/simreporting/) and provide feedback that will be used to inform subsequent revisions to these reporting guidelines.

Conclusions

The unique features of SBR highlight the importance of clear and concise reporting that helps readers understand how simulation was used in the research. Poor and inconsistent reporting makes it difficult for readers to interpret results and replicate interventions and hence less likely for research to inform change that will positively influence patient outcomes. The use of standardized reporting guidelines will serve as a guide for authors wishing to submit manuscripts for publication, and in doing so, it draws attention to the important elements of SBR and ultimately improves the quality of simulation studies conducted in the future. Supplemental Digital Content 1. (DOCX 111 kb) Supplemental Digital Content 2. (DOCX 205 kb)
  55 in total

Review 1.  Simulation training for breast and pelvic physical examination: a systematic review and meta-analysis.

Authors:  C A Dilaveri; J H Szostek; A T Wang; D A Cook
Journal:  BJOG       Date:  2013-06-11       Impact factor: 6.531

Review 2.  Research regarding debriefing as part of the learning process.

Authors:  Daniel Raemer; Mindi Anderson; Adam Cheng; Ruth Fanning; Vinay Nadkarni; Georges Savoldelli
Journal:  Simul Healthc       Date:  2011-08       Impact factor: 1.929

Review 3.  Technology-enhanced simulation to assess health professionals: a systematic review of validity evidence, research methods, and reporting quality.

Authors:  David A Cook; Ryan Brydges; Benjamin Zendejas; Stanley J Hamstra; Rose Hatala
Journal:  Acad Med       Date:  2013-06       Impact factor: 6.893

Review 4.  Designing and conducting simulation-based research.

Authors:  Adam Cheng; Marc Auerbach; Elizabeth A Hunt; Todd P Chang; Martin Pusic; Vinay Nadkarni; David Kessler
Journal:  Pediatrics       Date:  2014-05-12       Impact factor: 7.124

Review 5.  Simulation-based training in anaesthesiology: a systematic review and meta-analysis.

Authors:  G R Lorello; D A Cook; R L Johnson; R Brydges
Journal:  Br J Anaesth       Date:  2013-12-23       Impact factor: 9.166

Review 6.  Patient outcomes in simulation-based medical education: a systematic review.

Authors:  Benjamin Zendejas; Ryan Brydges; Amy T Wang; David A Cook
Journal:  J Gen Intern Med       Date:  2013-08       Impact factor: 5.128

7.  Neonatal intubation performance: room for improvement in tertiary neonatal intensive care units.

Authors:  Laura Y Haubner; James S Barry; Lindsay C Johnston; Lamia Soghier; Philip M Tatum; David Kessler; Katheryne Downes; Marc Auerbach
Journal:  Resuscitation       Date:  2013-04-03       Impact factor: 5.262

8.  Reducing waste from incomplete or unusable reports of biomedical research.

Authors:  Paul Glasziou; Douglas G Altman; Patrick Bossuyt; Isabelle Boutron; Mike Clarke; Steven Julious; Susan Michie; David Moher; Elizabeth Wager
Journal:  Lancet       Date:  2014-01-08       Impact factor: 79.321

9.  Effect of using reporting guidelines during peer review on quality of final manuscripts submitted to a biomedical journal: masked randomised trial.

Authors:  E Cobo; J Cortés; J M Ribera; F Cardellach; A Selva-O'Callaghan; B Kostov; L García; L Cirugeda; D G Altman; J A González; J A Sànchez; F Miras; A Urrutia; V Fonollosa; C Rey-Joly; M Vilardell
Journal:  BMJ       Date:  2011-11-22

Review 10.  Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration.

Authors:  Jan P Vandenbroucke; Erik von Elm; Douglas G Altman; Peter C Gøtzsche; Cynthia D Mulrow; Stuart J Pocock; Charles Poole; James J Schlesselman; Matthias Egger
Journal:  PLoS Med       Date:  2007-10-16       Impact factor: 11.069

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  32 in total

Review 1.  Randomized controlled trials of simulation-based interventions in Emergency Medicine: a methodological review.

Authors:  Anthony Chauvin; Jennifer Truchot; Aida Bafeta; Dominique Pateron; Patrick Plaisance; Youri Yordanov
Journal:  Intern Emerg Med       Date:  2017-11-16       Impact factor: 3.397

2.  ASPiH Conference 2019 keynote paper. Quality improvement through simulation: a missed opportunity?

Authors:  Paul O'Connor
Journal:  BMJ Simul Technol Enhanc Learn       Date:  2020-03-04

3.  Peer-assisted learning in simulation-based medical education: a mixed-methods exploratory study.

Authors:  Leo Nunnink; Andrea Thompson; Nemat Alsaba; Victoria Brazil
Journal:  BMJ Simul Technol Enhanc Learn       Date:  2020-12-16

4.  GENESISS 2-Generating Standards for In-Situ Simulation project: a systematic mapping review.

Authors:  Kerry Evans; Jenny Woodruff; Alison Cowley; Louise Bramley; Giulia Miles; Alastair Ross; Joanne Cooper; Bryn Baxendale
Journal:  BMC Med Educ       Date:  2022-07-11       Impact factor: 3.263

5.  Continuous monitoring of surgical bimanual expertise using deep neural networks in virtual reality simulation.

Authors:  Recai Yilmaz; Alexander Winkler-Schwartz; Nykan Mirchi; Aiden Reich; Sommer Christie; Dan Huy Tran; Nicole Ledwos; Ali M Fazlollahi; Carlo Santaguida; Abdulrahman J Sabbagh; Khalid Bajunaid; Rolando Del Maestro
Journal:  NPJ Digit Med       Date:  2022-04-26

6.  An overview of realist evaluation for simulation-based education.

Authors:  Alastair C Graham; Sean McAleer
Journal:  Adv Simul (Lond)       Date:  2018-07-17

7.  The STROBE extensions: protocol for a qualitative assessment of content and a survey of endorsement.

Authors:  Melissa K Sharp; Ana Utrobičić; Guadalupe Gómez; Erik Cobo; Elizabeth Wager; Darko Hren
Journal:  BMJ Open       Date:  2017-10-22       Impact factor: 2.692

8.  Real-world virtual patient simulation to improve diagnostic performance through deliberate practice: a prospective quasi-experimental study.

Authors:  Susrutha Kotwal; Mehdi Fanai; Wei Fu; Zheyu Wang; Anand K Bery; Rodney Omron; Nana Tevzadze; Daniel Gold; Brian T Garibaldi; Scott M Wright; David E Newman-Toker
Journal:  Diagnosis (Berl)       Date:  2021-03-08

9.  Assessing validity evidence for a serious game dedicated to patient clinical deterioration and communication.

Authors:  Antonia Blanié; Michel-Ange Amorim; Arnaud Meffert; Corinne Perrot; Lydie Dondelli; Dan Benhamou
Journal:  Adv Simul (Lond)       Date:  2020-05-27

10.  Higher resuscitation guideline adherence in paramedics with use of real-time ventilation feedback during simulated out-of-hospital cardiac arrest: A randomised controlled trial.

Authors:  Rasmus Meyer Lyngby; Lyra Clark; Julie Samsoee Kjoelbye; Roselil Maria Oelrich; Annemarie Silver; Helle Collatz Christensen; Charlotte Barfod; Freddy Lippert; Dimitra Nikoletou; Tom Quinn; Fredrik Folke
Journal:  Resusc Plus       Date:  2021-01-30
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