Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration

In this explanatory and elaboration document Mattias Egger and colleagues provide the meaning and rationale of each checklist item on the STROBE Statement

Methods for the thematic synthesis of qualitative research in systematic reviews

<p>Abstract</p> <p>Background</p> <p>There is a growing recognition of the value of synthesising qualitative research in the evidence base in order to facilitate effective and appropriate health care. In response to this, methods for undertaking these syntheses are currently being developed. Thematic analysis is a method that is often used to analyse data in primary qualitative research. This paper reports on the use of this type of analysis in systematic reviews to bring together and integrate the findings of multiple qualitative studies.</p> <p>Methods</p> <p>We describe thematic synthesis, outline several steps for its conduct and illustrate the process and outcome of this approach using a completed review of health promotion research. Thematic synthesis has three stages: the coding of text 'line-by-line'; the development of 'descriptive themes'; and the generation of 'analytical themes'. While the development of descriptive themes remains 'close' to the primary studies, the analytical themes represent a stage of interpretation whereby the reviewers 'go beyond' the primary studies and generate new interpretive constructs, explanations or hypotheses. The use of computer software can facilitate this method of synthesis; detailed guidance is given on how this can be achieved.</p> <p>Results</p> <p>We used thematic synthesis to combine the studies of children's views and identified key themes to explore in the intervention studies. Most interventions were based in school and often combined learning about health benefits with 'hands-on' experience. The studies of children's views suggested that fruit and vegetables should be treated in different ways, and that messages should not focus on health warnings. Interventions that were in line with these suggestions tended to be more effective. Thematic synthesis enabled us to stay 'close' to the results of the primary studies, synthesising them in a transparent way, and facilitating the explicit production of new concepts and hypotheses.</p> <p>Conclusion</p> <p>We compare thematic synthesis to other methods for the synthesis of qualitative research, discussing issues of context and rigour. Thematic synthesis is presented as a tried and tested method that preserves an explicit and transparent link between conclusions and the text of primary studies; as such it preserves principles that have traditionally been important to systematic reviewing.</p

A stimulus to define informatics and health information technology

<p>Abstract</p> <p>Background</p> <p>Despite the growing interest by leaders, policy makers, and others, the terminology of health information technology as well as biomedical and health informatics is poorly understood and not even agreed upon by academics and professionals in the field.</p> <p>Discussion</p> <p>The paper, presented as a Debate to encourage further discussion and disagreement, provides definitions of the major terminology used in biomedical and health informatics and health information technology. For informatics, it focuses on the words that modify the term as well as individuals who practice the discipline. Other categories of related terms are covered as well, from the associated disciplines of computer science, information technolog and health information management to the major application categories of applications used. The discussion closes with a classification of individuals who work in the largest segment of the field, namely clinical informatics.</p> <p>Summary</p> <p>The goal of presenting in Debate format is to provide a starting point for discussion to reach a documented consensus on the definition and use of these terms.</p

Epidemiology and Reporting Characteristics of Systematic Reviews

BACKGROUND: Systematic reviews (SRs) have become increasingly popular to a wide range of stakeholders. We set out to capture a representative cross-sectional sample of published SRs and examine them in terms of a broad range of epidemiological, descriptive, and reporting characteristics, including emerging aspects not previously examined. METHODS AND FINDINGS: We searched Medline for SRs indexed during November 2004 and written in English. Citations were screened and those meeting our inclusion criteria were retained. Data were collected using a 51-item data collection form designed to assess the epidemiological and reporting details and the bias-related aspects of the reviews. The data were analyzed descriptively. In total 300 SRs were identified, suggesting a current annual publication rate of about 2,500, involving more than 33,700 separate studies including one-third of a million participants. The majority (272 [90.7%]) of SRs were reported in specialty journals. Most reviews (213 [71.0%]) were categorized as therapeutic, and included a median of 16 studies involving 1,112 participants. Funding sources were not reported in more than one-third (122 [40.7%]) of the reviews. Reviews typically searched a median of three electronic databases and two other sources, although only about two-thirds (208 [69.3%]) of them reported the years searched. Most (197/295 [66.8%]) reviews reported information about quality assessment, while few (68/294 [23.1%]) reported assessing for publication bias. A little over half (161/300 [53.7%]) of the SRs reported combining their results statistically, of which most (147/161 [91.3%]) assessed for consistency across studies. Few (53 [17.7%]) SRs reported being updates of previously completed reviews. No review had a registration number. Only half (150 [50.0%]) of the reviews used the term “systematic review” or “meta-analysis” in the title or abstract. There were large differences between Cochrane reviews and non-Cochrane reviews in the quality of reporting several characteristics. CONCLUSIONS: SRs are now produced in large numbers, and our data suggest that the quality of their reporting is inconsistent. This situation might be improved if more widely agreed upon evidence-based reporting guidelines were endorsed and adhered to by authors and journals. These results substantiate the view that readers should not accept SRs uncritically

Lay perceptions of evidence-based information – a qualitative evaluation of a website for back pain sufferers

BACKGROUND: In an evidence-informed patient choice the patient has access to research-based information about the effectiveness of health care options and is encouraged to use this information in treatment decisions. This concept has seen growing popularity in recent years. However, we still know relatively little about users' attitudes to the use of research-based information, possibly because people have been unexposed to this type of information. After developing the BackInfo website where the results of Cochrane systematic reviews on the effects of low back pain were adapted and presented to lay users we evaluated how users responded to this information. METHODS: Focus group meetings were held with 18 chronic back pain sufferers, after they had been sent a link to the website before the meetings. RESULTS: The focus groups suggest that the most important challenges to the use of BackInfo's research-based information are not primarily tied to the comprehension or presentation of the information, but are mainly associated with participants' attitudes towards the credibility of research and researchers, and the applicability of research results to themselves as individuals. Possible explanations for participants' lack of trust in research and their apparent difficulties in applying this research to their own situations include aspects that may be typical for the general public including the media's presentation of research, and a lack of familiarity with and feelings of distance to research evidence. Other aspects may be typical for patient groups with chronic and unclear medical conditions, such as a lack of trust in the health care establishment in general. CONCLUSION: In order to enhance the credibility and applicability of research evidence, providers of research-based information could explore a number of possibilities including the use of including personal stories to illustrate the research outcomes

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension

The SPIRIT 2013 (The Standard Protocol Items: Recommendations for Interventional Trials) statement aims to improve the completeness of clinical trial protocol reporting, by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there is a growing recognition that interventions involving artificial intelligence need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI extension is a new reporting guideline for clinical trials protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI. Both guidelines were developed using a staged consensus process, involving a literature review and expert consultation to generate 26 candidate items, which were consulted on by an international multi-stakeholder group in a 2-stage Delphi survey (103 stakeholders), agreed on in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items, which were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations around the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer-reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration

Much medical research is observational. The reporting of observational studies is often of insufficient quality. Poor reporting hampers the assessment of the strengths and weaknesses of a study and the generalisability of its results. Taking into account empirical evidence and theoretical considerations, a group of methodologists, researchers, and editors developed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations to improve the quality of reporting of observational studies. The STROBE Statement consists of a checklist of 22 items, which relate to the title, abstract, introduction, methods, results and discussion sections of articles. Eighteen items are common to cohort studies, case-control studies and cross-sectional studies and four are specific to each of the three study designs. The STROBE Statement provides guidance to authors about how to improve the reporting of observational studies and facilitates critical appraisal and interpretation of studies by reviewers, journal editors and readers. This explanatory and elaboration document is intended to enhance the use, understanding, and dissemination of the STROBE Statement. The meaning and rationale for each checklist item are presented. For each item, one or several published examples and, where possible, references to relevant empirical studies and methodological literature are provided. Examples of useful flow diagrams are also included. The STROBE Statement, this document, and the associated Web site (http://www.strobe-statement.org/) should be helpful resources to improve reporting of observational research

Mejorar la comunicación de estudios observacionales en epidemiología (STROBE): explicación y elaboración

Gran parte de la investigación biomédica es de tipo observacional. Los informes de los estudios observacionales a menudo poseen una calidad insuficiente, lo que dificulta la evaluación de sus fortalezas y debilidades para generalizar los resultados. Teniendo en cuenta la evidencia empírica y consideraciones teóricas, un grupo de expertos en metodología, investigadores y editores de revistas científicas, desarrollaron una lista de recomendaciones para aumentar la calidad de las publicaciones de los estudios observacionales: (STROBE). La Declaración STROBE consiste en una lista de verificación de 22 puntos que guardan relación con las diferentes secciones de un artículo: título, resumen, introducción, metodología, resultados y discusión. De ellos, 18 puntos son comunes a los tres diseños de estudio: cohorte, casos y controles, y transversales; los otros cuatro son específicos para cada una de estas tres modalidades. La Declaración STROBE proporciona a los autores información sobre cómo mejorar la calidad de los artículos sobre estudios observacionales y facilita a los revisores, editores de revistas y lectores su apreciación crítica y su interpretación. Este documento explicativo tiene el propósito de impulsar el uso, la comprensión y la difusión de la Declaración STROBE. Se presentan el significado y el análisis razonado para cada punto de la lista de verificación, proporcionando uno o varios ejemplos publicados en la literatura y, en lo posible, referencias de estudios empíricos relevantes y literatura metodológica. También se incluyen ejemplos de diagramas de flujo. La Declaración STROBE, el presente documento y la página Web asociada () son recursos útiles para mejorar la divulgación de la investigación observacional.Much medical research is observational. The reporting of observational studies is often of insufficient quality. Poor reporting hampers the assessment of the strengths and weaknesses of a study and the generalisability of its results. Taking into account empirical evidence and theoretical considerations, a group of methodologists, researchers, and editors developed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations to improve the quality of reporting of observational studies. The STROBE Statement consists of a checklist of 22 items, which relate to the title, abstract, introduction, methods, results and discussion sections of articles. Eighteen items are common to cohort studies, case-control studies and cross-sectional studies and four are specific to each of the three study designs. The STROBE Statement provides guidance to authors about how to improve the reporting of observational studies and facilitates critical appraisal and interpretation of studies by reviewers, journal editors and readers. This explanatory and elaboration document is intended to enhance the use, understanding, and dissemination of the STROBE Statement. The meaning and rationale for each checklist item are presented. For each item, one or several published examples and, where possible, references to relevant empirical studies and methodological literature are provided. Examples of useful flow diagrams are also included. The STROBE Statement, this document, and the associated Web site () should be helpful resources to improve reporting of observational research

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human–AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret, and critically appraise the design and risk of bias for a planned clinical trial