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Interessen for å samle og syntetisere kvalitative studier i systematiske oversikter er voksende. Det pekes blant annet på at sammenstillinger av kvalitativ forskning har stor verdi når det gjelder potensialet til å informere politikk og praksis. Systematiske oversikter om effekt gir innsikt i hvorvidt et tiltak virker; systematiske oversikter med kvalitativ forskning gir innsikt i hvordan og hvorfor eventuelle virkninger oppstår. Nytten av denne type oversikter erkjennes nå bl.a. av internasjonale organisasjoner som Cochrane og Campbell-samarbeidene. I Cochrane-håndboka vises det til at kvalitativ forskning kan bidra med nyttig informasjon på flere måter: Kvalitative datasett kan informere, styrke, utvide og supplere systematiske oversikter om effekt av tiltak. Metodene for gjennomføring av oversikter med kvalitativ forskning er i rask utvikling, og det fins for øyeblikket ingen standard tilnærming. Når det gjelder søk etter kvalitative studier må disse ofte være bredere, men forøvrig gjelder mange av de samme prinsippene som for litteratursøk innen systematiske oversikter om effekt av tiltak. Det forskes på og debatteres om hva slags kriterier som bør benyttes i utvelgelsen av kvalitative studier og hvorvidt man skal ekskludere studier basert på metodologisk kvalitet. Det fins flere ulike måter å syntetisere resultater fra kvalitative studier på, og det er også mulig å sammenstille resultater fra både kvalitative og kvantitative studier i én analyse. De mest hyppig brukte metodene er metaetnografi og tematisk analyse.Berg RC, Munthe-Kaas H. Systematic reviews in qualitative research. Nor J Epidemiol 2013; 23 (2): 131-139.ENGLISH SUMMARYThere is growing interest in summarising and synthesising qualitative research in systematic reviews. Among other things, this indicates an increasing appreciation for the potential role of qualitative evidence in informing policy and practice. While systematic reviews of effect studies can establish whether an intervention works, systematic reviews of qualitative research can offer insights into the "how" and "why" of potential effects. The importance of such questions, and the value of systematic reviews of qualitative research, is now recognized by a number of international organizations, including the Cochrane and Campbell Collaborations. The Cochrane Handbook describes four ways in which qualitative research can contribute to evidence-based practice, namely by informing, enhancing, extending, and supplementing systematic reviews of the effect of interventions. The methodology for conducting reviews of qualitative research is rapidly developing, and at present there is no standard approach. Systematic searches for qualitative research are often more broadly cast but otherwise follow many of the same principles of a literature search within a systematic review of effect. There are ongoing debates and research regarding criteria for inclusion of studies in general, and whether to include studies of low methodological quality in particular. An array of methods to synthesise qualitative evidence exists, and such evidence may also be synthesised together with quantitative evidence. Meta-ethnography and thematic analysis are the most commonly used synthesis methods.

AbstractIntroductionQualitative evidence is increasingly incorporated into decision‐making processes. Assessing the methodological limitations of primary studies is critical to making an overall assessment of confidence in findings from qualitative evidence syntheses (QES) using GRADE‐CERQual. Current critical appraisal tools were not developed specifically for use in Cochrane reviews or GRADE‐CERQual, and few are evidence‐based. The aim of CochrAne qualitative Methodological LimitatiOns Tool (CAMELOT) was to address this gap.MethodsWe undertook this project in four stages: (1) systematic literature search to identify existing tools, (2) identification of evidence to support inclusion of potential CAMELOT domains (3) consensus survey to agree on the inclusion and definition of CAMELOT domains, and (4) human‐centered design approach to develop and refine CAMELOT by exploring user experience.ResultsCAMELOT is a new evidence‐based tool for assessing the methodological strengths and limitations of primary qualitative research studies in a QES. CAMELOT is comprised of 12 domains: four Meta domains that encourage review authors to consider those characteristics of the primary study that are beyond how the study was carried out, but which inform the conduct and design of the study, and eight Method domains which encourage review authors to consider how the study was designed, planned and/or conducted, and how study conduct and design fits with the information provided in the four meta domains. Review authors make an assessment by identifying any concerns regarding the methods used in the study and considering the appropriateness of fit between the Meta and Method domains.ConclusionCAMELOT provides review authors with a transparent and systematic method to assess methodological limitations of primary qualitative studies. CAMELOT incorporates qualitative principles and focuses on appropriateness of fit between Meta and Method domains. In line with iterative tool development approach, CAMELOT will continue to be revised over time following extensive user testing and piloting.

Source at https://doi.org/10.1186/s13012-017-0694-5 . Licensed CC BY-NC-ND 4.0. ; Background : The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on a probable fifth component, dissemination bias. Given its exploratory nature, we are not yet able to provide guidance on applying this potential component of the CERQual approach. Instead, we focus on how dissemination bias might be conceptualised in the context of qualitative research and the potential impact dissemination bias might have on an overall assessment of confidence in a review finding. We also set out a proposed research agenda in this area. Methods : We developed this paper by gathering feedback from relevant research communities, searching MEDLINE and Web of Science to identify and characterise the existing literature discussing or assessing dissemination bias in qualitative research and its wider implications, developing consensus through project group meetings, and conducting an online survey of the extent, awareness and perceptions of dissemination bias in qualitative research. Results : We have defined dissemination bias in qualitative research as a systematic distortion of the phenomenon of interest due to selective dissemination of studies or individual study findings. Dissemination bias is important for qualitative evidence syntheses as the selective dissemination of qualitative studies and/or study findings may distort our understanding of the phenomena that these syntheses aim to explore and thereby undermine our confidence in these findings. Dissemination bias has been extensively examined in the context of randomised controlled trials and systematic reviews of such studies. The effects of potential dissemination bias are formally considered, as publication bias, within the GRADE approach. However, the issue has received almost no attention in the context of qualitative research. Because of very limited understanding of dissemination bias and its potential impact on review findings in the context of qualitative evidence syntheses, this component is currently not included in the GRADE-CERQual approach. Conclusions : Further research is needed to establish the extent and impacts of dissemination bias in qualitative research and the extent to which dissemination bias needs to be taken into account when we assess how much confidence we have in findings from qualitative evidence syntheses.