Impact of COVID-19 on Endometriosis Patients: An Integrative Review

Zahra Behboodi Moghadam, Masoumeh Namazi
Current women's health reviews · 2024 · vol. 21(2) · doi:10.2174/0115734048281548231218113958 · W4391263471
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This integrative review of 23 articles found that the COVID-19 pandemic negatively impacted the physical symptoms, mental well-being, and medical care of women with endometriosis.

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This document presents the Mixed Methods Appraisal Tool (MMAT), version 2018, describing its purpose, development process, and the methodological quality criteria and scoring guidance for appraising empirical studies using qualitative, randomized controlled trial, non-randomized, quantitative descriptive, and mixed methods designs. It outlines screening questions, how to select the appropriate study category for appraisal, and criteria such as adequacy of data collection, derivation of findings, risk of bias considerations, and integration of qualitative and quantitative components in mixed methods. The paper also provides explicit caveats, including that MMAT cannot be used for non-empirical papers (e.g., reviews or theoretical papers) and that some study designs like economic or diagnostic accuracy studies require other tools. This paper is centrally about endometriosis — specifically, it frames how integrative reviews of endometriosis patients’ impacts (including COVID-19) can be methodologically appraised using MMAT.

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Abstract

Background: During the Covid-19 pandemic, people's lives worldwide have undergone extensive changes. The pandemic has worsened the condition of patients with chronic diseases like women with endometriosis. Objective: This study aims to summarize available evidence on the impact of the COVID-19 pandemic on physical symptoms, mental health, and medical care of patients with endometriosis. Methods: In the present integrative review using PRISMA guidelines, related articles published from December 2019 to July 2023 in databases including MEDLINE, Science Direct, Scopus, and Google Scholar in the English language were extracted. Results: After evaluating the criteria for inclusion and exclusion, a total of 23 articles were chosen and examined. This study represents an open window to investigate the impact of COVID-19 on women with endometriosis. The COVID-19 pandemic has affected the symptoms, mental well-being, and medical care of women with endometriosis. Conclusions: There is a perceived necessity to provide supportive care for patients during pandemic restrictions. Remote work has had an unanticipated advantage, and it is recommended that women with endometriosis continue to work from home after COVID-19 to maintain their workplace effectiveness.
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Method

are combined; (b) each method is used rigorously in accordance to the generally accepted criteria in the area (or tradition) of research invoked; and (c) the combination of the methods is carried out at the minimum through a MM design (defined a priori, or emerging) and the integration of the QUAL and QUAN phases, results, and data. Common designs include (this list if not exhaustive): Convergent design The QUAL and QUAN components are usually (but not necessarily) concomitant. The purpose is to examine the same phenomenon by interpreting QUAL and QUAN results (bringing data analysis together at the interpretation stage), or by integrating QUAL and QUAN datasets (e.g., data on same cases), or by transforming data (e.g., quantization of qualitative data). Sequential explanatory design

Results

of the phase 1 - QUAN component inform the phase 2 - QUAL component. The purpose is to explain QUAN results using QUAL findings. E.g., the QUAN results guide the selection of QUAL data sources and data collection, and the QUAL findings contribute to the interpretation of QUAN results. Sequential exploratory design

Results

of the phase 1 - QUAL component inform the phase 2 - QUAN component. The purpose is to explore, develop and test an instrument (or taxonomy), or a conceptual framework (or theoretical model). E.g., the QUAL findings inform the QUAN data collection, and the QUAN

Results

allow a statistical generalization of the QUAL findings. Key references: Creswell et al. (2011); Creswell and Plano Clark, (2017); O'Cathain (2010) 5.1. Is there an adequate rationale for using a mixed methods design to address the research question? Explanations The reasons for conducting a mixed methods study should be clearly explained. Several reasons can be invoked such as to enhance or build upon qualitative findings with quantitative results and vice versa; to provide a comprehensive and complete understanding of a phenomenon or to develop and test instruments (Bryman, 2006). 5.2. Are the different components of the study effectively integrated to answer the research question? Explanations Integration is a core component of mixed methods research and is defined as the “explicit interrelating of the quantitative and qualitative component in a mixed methods study” (Plano Clark and Ivankova, 2015, p. 40). Look for information on how qualitative and quantitative phases, results, and data were integrated (Pluye et al., 2018). For instance, how data gathered by both research methods was brought together to form a complete picture (e.g., joint displays) and when integration occurred (e.g., during the data collection-analysis or/and during the interpretation of qualitative and quantitative results). 5.3. Are the outputs of the integration of qualitative and quantitative components adequately interpreted? Explanations This criterion is related to meta-inference, which is defined as the overall interpretations derived from integrating qualitative and quantitative findings (Teddlie and Tashakkori, 2009). Meta-inference occurs during the interpretation of the findings from the integration of the qualitative and quantitative components, and shows the added value of conducting a mixed methods study rather than having two separate studies. 5.4. Are divergences and inconsistencies between quantitative and qualitative results adequately addressed? Explanations When integrating the findings from the qualitative and quantitative components, divergences and inconsistencies (also called conflicts, contradictions, discordances, discrepancies, and dissonances) can be found. It is not sufficient to only report the divergences; they need to be explained. Different strategies to address the divergences have been suggested such as reconciliation, initiation, bracketing and exclusion (Pluye et al., 2009b). Rate this criterion ‘Yes’ if there is no divergence. 5.5. Do the different components of the study adhere to the quality criteria of each tradition of the methods involved? Explanations The quality of the qualitative and quantitative components should be individually appraised to ensure that no important threats to trustworthiness are present. To appraise 5.5, use criteria for the qualitative component (1.1 to 1.5), and the appropriate criteria for the quantitative component (2.1 to 2.5, or 3.1 to 3.5, or 4.1 to 4.5). The quality of both components should be high for the mixed

Methods

study to be considered of good quality. The premise is that the overall quality of a mixed methods study cannot exceed the quality of its weakest component. For example, if the quantitative component is rated high quality and the qualitative component is rated low quality, the overall rating for this criterion will be of low quality. *Adapted from National Institute for Health Care Excellence. (2012). Methods for the development of nice public health guidance. London: National Institute for Health and Care Excellence; and Scottish Intercollegiate Guidelines Network. (2017). Algorithm for classifying study design for questions of effectiveness. Retrieved December 1, 2017, from http://www.sign.ac.uk/assets/study_design.pdf.                    8 Algorithm for selecting the study categories to rate in the MMAT* . 9

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