{"paper_id":"271aa2c1-8501-4f23-823f-7ecea6710ed2","body_text":"1 \n \n \nMeasurement of changes to the menstrual cycle: A transdisciplinary \nsystematic review evaluating measure quality and utility for clinical trials \nAmelia C.L. Mackenzie1*, Stephanie Chung2,3, Emily Hoppes2, Alexandria K. Mickler4#a, Alice F. \nCartwright2,3#b \n1 Global Health and Population, FHI 360, Washington, District of Columbia, United States of America \n2 Global Health and Population, FHI 360, Durham, North Carolina, United States of America \n3 Department of Maternal and Child Health, University of North Carolina Gillings School of Global Public \nHealth, Chapel Hill, North Carolina, United States of America \n4 Research, Technology, and Utilization Division, Office of Population and Reproductive Health, Bureau \nfor Global Health, United States Agency for International Development and the Public Health Institute, \nWashington, District of Columbia, United States of America \n \n#a Current address: Independent Consultant, Washington, District of Columbia, United States of America \n#b Current address: Guttmacher Institute, New York, New York, United States of America \n \n* Corresponding author \nEmail: amackenzie@fhi360.org (AM)  \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \nNOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.\n\n \n2 \n \n \nABSTRACT \nDespite the importance of menstruation and the menstrual cycle to health, human rights, and \nsociocultural and economic wellbeing, the study of menstrual health suffers from a lack of funding, and \nresearch remains fractured across many disciplines. We sought to systematically review validated \napproaches to measure four aspects of changes to the menstrual cycle—bleeding, blood, pain, and \nperceptions—caused by any source and used within any field. We then evaluated the measure quality \nand utility for clinical trials of the identified instruments. We searched MEDLINE, Embase, and four \ninstrument databases and included peer-reviewed articles published between 2006 and 2023 that \nreported on the development or validation of instruments assessing menstrual changes using \nquantitative or mixed-methods methodology. From a total of 8,490 articles, 8,316 were excluded, \nyielding 174 articles reporting on 94 instruments. Almost half of articles were from the United States or \nUnited Kingdom and over half of instruments were only in English, Spanish, French, or Portuguese. Most \ninstruments measured bleeding parameters, uterine pain, or perceptions, but few assessed \ncharacteristics of blood. Nearly 60% of instruments were developed for populations with menstrual or \ngynecologic disorders or symptoms. Most instruments had fair or good measure quality or clinical trial \nutility; however, most instruments lacked evidence on responsiveness, question sensitivity and/or \ntransferability, and only three instruments had good scores of both quality and utility. Although we took \na novel, transdisciplinary approach, our systematic review found important gaps in the literature and \ninstrument landscape, pointing towards a need to examine the menstrual cycle in a more \ncomprehensive, inclusive, and standardized way. Our findings can inform the development of new or \nmodified instruments, which—if used across the many fields that study menstrual health and within \nclinical trials—can contribute to a more systemic and holistic understanding of menstruation and the \nmenstrual cycle.  \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n3 \n \n \nINTRODUCTION \nMenstrual health across disciplines \nMenstruation and the wider menstrual cycle play a notable role in the health, human rights, and \nsociocultural and economic wellbeing of people who menstruate [1]. In addition, although its \nsignificance should not be utilitarianly reduced to only reproductive function, continuity of the human \nspecies would not occur without the menstrual cycle. Despite its importance, the study of menstruation \nand the menstrual cycle continues to suffer from a historical lack of funding and research across \ndisciplines, including within the biological, clinical, public health, and social sciences. Within biomedical \nresearch, for example, a publication reporting on a recent technical meeting on menstruation convened \nby the United States (US) National Institutes of Health (NIH) decried a “lack of understanding of basic \nuterine and menstrual physiology” among researchers [2]. Indeed, many foundational, field-defining \nworks have only recently emerged in the past five to ten years following increased attention to \nmenstrual health, which the Global Menstrual Collective defined in 2021 as “a state of complete \nphysical, mental, and social well-being and not merely the absence of disease or infirmity, in relation to \nthe menstrual cycle” [3]. The contemporary growth of the menstrual health field is—at least partly—due \nto grassroots menstrual activism, which resulted in 2015 being labeled as “the year of the period” in the \nlay press [4]. Other examples of recent fundamental work within menstrual health across disciplines \ninclude recommendations for the menstrual cycle to be considered a vital sign and the advent of the \nfield of critical menstruation studies [5,6]. Despite these recent efforts, insufficient research on \nmenstrual health persists. In addition, the study of menstrual health remains fractured across many \nfields and disciplines, many of which are siloed despite adjacent or even overlapping subject matters \n(e.g., menstrual health and hygiene within wider sexual and reproductive health; or gynecology, \nendocrinology, and many other specialties within medicine) [7,8]. As a result, we still lack a complete, \nsystemic, and holistic understanding of menstruation and the wider menstrual cycle. \nThe type of interdisciplinary, comprehensive global efforts needed to address such large gaps in \nmenstrual health research can greatly benefit from standardization—of terminology, of measurement, \nof analysis, and of outcomes or indicators. The widest global effort at standardization to date has taken \nplace within medicine; the International Federation of Gynecology and Obstetrics (FIGO) established \nclinical standards of normal and abnormal uterine bleeding occurring outside of pregnancy via a \nconsensus-building process over a series of years [9–12]. These FIGO standards dictate four parameters \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n4 \n \n \nfor menstrual bleeding: the frequency, duration, volume, and regularity of bleeding. FIGO defines \nnormal uterine bleeding as bleeding occurring every 24-38 days (frequency), bleeding lasting no more \nthan 8 days (duration), bleeding of a ‘normal’ amount as defined by the patient that does not interfere \n“with physical, social, emotional, and/or material quality of life” (volume), and bleeding within a \nmenstrual cycle that only varies in length by plus or minus 4 days (regularity). FIGO further defines \nbleeding outside these normal parameters as abnormal uterine bleeding, which is divided into standard \ncategories based on whether it is acute or chronic and the source or etiology of the abnormality \naccording to the acronym PALM-COEIN (i.e., Polyp, Adenomyosis, Leiomyoma, Malignancy and \nhyperplasia, Coagulopathy, Ovulatory dysfunction, Endometrial disorders, Iatrogenic, and Not otherwise \nclassified). Other examples of efforts at standardization include menstrual hygiene indicators within the \nWater, Sanitation and Hygiene (WASH) field and defining how contraception can impact the menstrual \ncycle and analyzing these data in contraceptive studies [13–18]. \nRelated to terminology, this review uses the phrase, “people who menstruate”, which we define as \nthose who can menstruate, do menstruate, or have menstruated. Although people who menstruate may \nor may not identify as women or girls, and not all women and girls menstruate [19], we do use the terms \n‘women’ and ’girls’ in some instances, especially when citing primary literature and because menstrual \nhealth cannot “be adequately addressed without attention to the gender norms and dynamics \nexperienced by individuals in the cultures and communities in which they live” [7]. As much as possible, \nhowever, we use gender inclusive terms and other people-first language. \nReview scope \nTo aid in efforts for standardized measurement across the study of menstruation and the menstrual \ncycle, we systematically reviewed approaches to measure four aspects of changes to the menstrual \ncycle: bleeding, blood, pain, and perceptions of bleeding, blood, or pain. We use the term ‘menstrual \nchanges’ to refer to these four aspects for the remainder of the paper. We sought to include all types of \nmeasures or methods for assessing menstrual changes (e.g., quantitative assays, biomarkers, data \nreported by clinicians, researchers, or directly by the person who menstruates). We use the term \n‘instruments’ to refer to any of these measures or methods for the remainder of the paper. Our aim was \nto identify any instruments that have been developed and validated within any field of study to measure \nmenstrual changes, examine how these instruments measured menstrual changes, and assess the \nmeasure quality of the identified instruments and their utility for the clinical trial context.  \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n5 \n \n \nRelated reviews have been conducted: (a) within fields such as menstrual hygiene or the study of heavy \nmenstrual bleeding (HMB) [20,21]; (b) to measure single parameters like volume of menstrual blood loss \n[22]; and (c) for specific approaches like pictorial methods to diagnose HMB [23]. However, given the \ngaps and silos within menstrual health research, our aim was to conduct an expansive and \ntransdisciplinary review to inform more standardized measurement across menstrual health research \nand clinical trials. For this reason, we sought to include menstrual changes caused by any etiology or \nsource. There are many factors that can result in menstrual changes, including those endogenous and \nexogenous to the person who menstruates. Examples of these etiologies or sources include menstrual or \ngynecologic disorders like adenomyosis, use of hormonal or intrauterine contraceptives, use of other \ndrugs or devices to treat or prevent disease, environmental exposures, infectious disease, injury, \ncoagulation disorders, and diet and exercise.  We are not aware of any previous efforts to look at \nmenstrual changes across disciplines in this way. \nClinical trial context  \nAs mentioned, one area for which we intend our review to be quite relevant is for data collection in \nclinical trials, although our broad approach does not preclude the use of our results to inform the \nmeasurement of menstrual changes across other research contexts. The importance of data on \nmenstrual changes in the clinical trial context was recently highlighted during the introduction of COVID \nvaccinations. Because vaccine trials did not collect data on the impact to the menstrual cycle or \nmenopausal uterine bleeding, there were concerns among vaccinated people who menstruate when \nthey experienced these changes, which can erode trust in clinical research and public health \ninterventions [24–28]. As authors working across various sexual and reproductive health spaces, our \ninterest in conducting this review stemmed from a shared goal to improve and standardize the \nmeasurement of menstrual changes in contraceptive clinical trials; however, our broad methodological \napproach permits the utility of our findings across all clinical trials.  \nClinical trials, and the preclinical research that precedes them, collect data on key organ functioning and \nvital signs as part of standard toxicology and pharmacodynamics. Given the importance of the menstrual \ncycle, it may seem surprising that data on how investigational drugs may impact the menstrual cycle are \nnot already routinely collected in clinical trials; however, research typically reflect the people, priorities, \nand purposes of those within the clinical trial ecosystem—that is, the individuals and systems that fund \nclinical research, conduct clinical trials, and regulate the drugs tested in trials, as well as the individuals \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n6 \n \n \nwho participate in trials. Historically, there has been an underrepresentation of people who menstruate \nwithin the clinical trial ecosystem [29]. This exclusion is true for much of the preclinical research that \ninforms clinical trials across many biomedical fields as well, and even cell lines used in in vitro studies are \npredominantly derived from male animals [30,31]. Although proof-of-concept studies for drugs intended \nfor use in women that are known to impact the menstrual cycle, such as hormonal contraceptives, do \ntypically use female animals when the model organism has an estrous or menstrual cycle, other \npreclinical research disproportionately relies on only male animals. Using both female and male animals \nin the research that informs clinical trials, however, could provide early indications of any impacts on \ncycles, as well as many other sex-specific effects or differences. Despite decades of concrete efforts, sex \nand gender disparities persist in the clinical trial ecosystem [32–34]. \nWithin the current clinical trial context, another element relevant to our review is how trials typically \nincorporate outcomes, like menstrual changes, that are reported by trial participants. The US Food and \nDrug Administration (FDA) and NIH refer to these data as patient-reported outcomes (PROs), which they \ndefine as “a measurement based on a report that comes directly from the patient (i.e., study subject) \nabout the status of a patient’s health condition without amendment or interpretation of the patient’s \nresponse by a clinician or anyone else.” PROs can include “symptoms or other unobservable concepts \nknown only to the patient (e.g., pain severity or nausea) [that] can only be measured by PRO measures,” \nas well as “the patient perspective on functioning or activities that may also be observable by others” \n[35]. Unless an assay or biomarker are used, all outcomes on menstrual changes are reported by the \nperson who menstruates and, therefore, are PROs. The FDA has a series of methodological guidance \ndocuments on the development, validation, and use of PROs in clinical trials as part of patient-focused \ndrug development efforts [36–39]. \nReview questions and objective \nGiven the aim of the review, our review questions were: (a) What instruments have been developed to \nassess menstrual changes caused by any etiology or source? and (b) What is the quality of these \ninstruments and their utility for clinical trials? The objective of our systematic review was to compile a \ncomplete list of validated instruments used to measure menstrual changes with an assessment of their \nquality and clinical trial utility. \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n7 \n \n \nMATERIALS AND METHODS \nWe conducted our systematic review in alignment with Preferred Reporting Items for Systematic \nReviews and Meta-Analysis (PRISMA) guidelines [40–42], including a protocol registered in PROSPERO \n(Protocol ID: CRD42023420358) [43]. A completed PRISMA checklist for this review is in Table S1, and \nAppendix S2 includes additional details on the search strategy, inclusion/exclusion criteria, title/abstract \nscreening, full text review, data extraction, and data analysis. \nSearch strategy \nWe searched for peer reviewed articles in the MEDLINE and Embase literature databases and for any \nrelevant instruments measuring menstrual changes in four instrument databases: (a) the NIH Common \nData Element (CDE) Repository [44], (b) the COSMIN database of systematic reviews of outcome \nmeasurement instruments [45], (c) the Core Outcome Measures in Effectiveness Trials (COMET) \nDatabase [46], and (c) ePROVIDE databases [47]. Table 1 shows the final search strategy for MEDLINE, \nand Appendix S2 includes search strategies for other databases. We uploaded articles from the \nliterature database searches and articles for any relevant instruments identified via the instrument \ndatabases into Covidence [48]. Following screening and review of these articles in Covidence, we \nidentified relevant review articles and extracted primary articles published since 1980 from those \nreviews. During data extraction, we identified any original articles for instruments developed before \n2006. We uploaded these primary articles and original development articles into Covidence for \nscreening.  \nTable 1. MEDLINE search strategy \nMenstrual \nchanges \n(\"menstrual cycle\"[MeSH Major Topic] OR \"menstruation disturbances\"[MeSH \nMajor Topic] OR \"Endometriosis\"[MeSH Major Topic] OR \"Uterine Diseases\"[MeSH \nMajor Topic] OR \"menstrua*\"[Title/Abstract] OR \"menses\"[Title/Abstract] OR \n\"uterine bleeding\"[Title/Abstract] OR \"vaginal bleeding\"[Title/Abstract] OR \n\"amenorrhea\"[Title/Abstract] OR \"dysmenorrhea\"[Title/Abstract] OR \n\"menorrhagia\"[Title/Abstract] OR \"oligomenorrhea\"[Title/Abstract] OR \n\"metrorrhagia\"[Title/Abstract] OR \"hypermenorrhea\"[Title/Abstract] OR \n\"hypomenorrhea\"[Title/Abstract] OR \"polymenorrhea\"[Title/Abstract])  \n AND \nInstruments \n(\"Surveys and Questionnaires\"[MeSH Major Topic] OR \"Pain Measurement\"[MeSH \nMajor Topic] OR \"Patient Reported Outcome Measures\"[MeSH Major Topic] OR \n\"psychometrics\"[MeSH Major Topic] OR \"Sensitivity and Specificity\"[MeSH Major \nTopic] OR \"Validation Study\"[Publication Type] OR \"Validation Studies as \nTopic\"[MeSH Major Topic] OR \"measur*\"[Title] OR \"method*\"[Title] OR \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n8 \n \n \n\"questionnaire*\"[Title] OR \"scale\"[Title] OR \"tool*\"[Title] OR \"patient reported \noutcome measure*\"[Title/Abstract] OR \"psychometr*\"[Title/Abstract])  \n AND \nDates (\"2006/01/01\"[Date - Publication] : \"2023/10/05\"[Date - Publication]) \nInclusion/exclusion criteria \nWe included all peer-reviewed articles—including those with prospective, retrospective, or cross-\nsectional study designs, and review papers—that met our inclusion and did not meet our exclusion \ncriteria, listed in Table 2. \nTable 2. Inclusion and exclusion criteria and related definitions \nInclusion \ncriteria \n1. Articles primarily focused on developing, validating, and/or evaluating \ninstruments measuring menstrual changes or perceptions of menstrual \nchanges, with information reported to assess instrument and/or study quality \n2. Articles published between January 1, 2006 and October 5, 2023 \n3. Articles published in any language \n4. Articles from any geographic region \nExclusion \ncriteria \n1. Articles with only qualitative data \n2. Articles that were conference abstracts, editorials, and commentaries \n3. Articles whose primary purpose was not validating instruments measuring \nmenstrual changes, such as studies focusing on biomarkers or biological \npathways of menstrual changes, cancer screening instruments, or studies of \nsocial-behavioral correlates of menstrual changes \n4. Articles reporting only on data from people in menopause \nMenstrual \nchanges \ndefinition \nFour aspects of changes to the menstrual cycle*:  \na. Bleeding  \n• Including four parameters: duration, volume, frequency, and/or \nregularity/predictability \nb. Blood  \n• Including three parameters: consistency, color, and/or smell \nc. Uterine pain or cramping \nd. Perceptions of bleeding, blood, or pain \nPerceptions \ndefinition \nThe perspectives on, attitudes about, experiences with, and acceptability of \nmenstrual changes at the individual-level, interpersonal-level, community-level, \nand wider levels, including social norms \nInstrument \ndefinition \nAny measure, method, or approach to assess menstrual changes, including \nhealthcare provider-reported, menstruator-reported, researcher-based, \nbiomarker-based, or assay-based methods, and including those that may be \ndeemed “objective” or “subjective” and both directly observable and personal \nperceptions of menstrual changes (adapted from [49]) \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n9 \n \n \nDevelopment \nor validation \ndefinition \nBroadly defined to include any manner of validation or evaluation (e.g., reporting \nany evidence on validity, reliability, responsiveness, interpretability, and other \nattributes of measure quality or utility) and any development or validation \ninformed by input from research participants who menstruate \n*Examples are: (a) an increase in how long bleeding lasts (bleeding duration), (b) a reduction of clotting \n(blood consistency), (c) a decrease in dysmenorrhea (pain), and (d) an impact on quality of life or \nattitudes (perceptions of changes).  \nTitle/abstract screening, full text review, and data extraction \nWe held weekly author meetings to discuss progress, questions, and discordance, and to document \ndecisions in a shared Word document. We began title/abstract screening with an ‘inter-reviewer \nreliability’ meeting where all authors completed title/abstract screening on the same 50 articles to \nestablish and confirm group standards. Then, two authors independently screened each remaining \ntitle/abstract and two authors independently reviewed each relevant full text in Covidence. We resolved \nany discordance during weekly meetings via consensus conversations. We conducted data extraction in \nExcel using a template data extraction form that collected information  on article information, study \ndesign, sample information, details on the instrument, measure quality attributes, and clinical trial utility \nattributes. For articles not in English, we used the text translation feature of Google Translate to review \ntitles and abstracts, we used the document translation feature of Google Translate and/or consulted a \nfluent colleague to review full text articles, and we completed data extraction with a fluent colleague for \nincluded articles.  \nFor assessing measure quality and clinical trial utility, we followed the recent Patient-Reported \nOutcomes Tools: Engaging Users and Stakeholders (PROTEUS) Consortium recommendations to use the \nInternational Society for Quality of Life Research (ISOQOL) standards for PRO measures [50,51]. We \nmade two adjustments to the ISOQOL standards: (a) we added an attribute on sensitivity of questions \ngiven the topic of menstruation has a noted amount of stigma surrounding it [52]; and (b) we separated \nout participant burden from investigator burden given these two can differ greatly for instruments \nmeasuring menstrual changes. We categorized six attributes as related primarily to the quality of the \ninstrument (i.e., measure quality: conceptual/measurement model, reliability, content validity, \nconstruct validity, responsiveness, and sensitive nature of questions) and four attributes as related \nprimarily to the utility of the instrument in clinical trials (i.e., clinical trial utility: interpretability of \nresults, the transferability of the instrument, participant burden, and investigator burden). We scored \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n10 \n \n \neach attribute of measure quality and clinical trial utility on a scale from 0 to 3 (0= no data, 1=poor, \n2=fair, and 3=good) based on criteria in line with ISOQOL standards [51] that were reviewed by \nmeasurement and clinical experts at FHI 360 and within a related global task force. We show the \nmeasure quality and clinical trial utility attributes and scoring criteria in Table 3, and Appendix S2 \nincludes details on the other fields of the data extraction form. \nTable 3. Measure quality and clinical trial utility scoring criteria* \nAttribute Poor quality (1) Fair quality (2) Good quality (3) \nMeasure quality \nConceptual and Measurement \nModel \nDefinition: The conceptual \nmodel provides a description \nand framework for targeted \nconstruct(s) in the measure. The \nmeasurement model maps \nindividual measure items to the \nconstruct(s). \nScore 0 if not assessed in article.  \nMinimal discussion of \nconceptual model or \nmeasurement model \nthat maps measure \nitems to the \nconstruct(s).  \nOr minimal discussion of \nintended population or \ncontext for measure \nuse. \nSome discussion of \nconceptual and/or \nmeasurement model \nthat maps measure \nitems to the \nconstruct(s). \nOr some discussion of \nintended population \nand/or context for \nmeasure use. \nClearly defines and \ndescribes concept(s) \nincluded in model and \nintended population(s) \nand context for \nmeasure use.  \nOr clearly describes \nhow concept(s) are \norganized into \nmeasurement model, \nincluding evidence for \ndimensionality of the \nmeasure, how items \nrelate to each \nmeasured concept, \nand the relationship \namong concepts. \nReliability \nDefinition: The degree to which \na measure is free from \nmeasurement error. \nScore 0 if not assessed in article.  \nThere is minimal \nevidence for measure \nreliability (e.g., internal \nconsistency reliability, \ntest-retest reliability, or \nitem response theory) \nUnclear or unjustified \nmethodology used for \nassessing reliability.  \nOr, if used, reliability \nCronbach α <0.70 for \ngroup-level \ncomparisons without \njustification. \n \n \nMethodology for \ncollecting data is \njustified (e.g., a multi-\nitem measure is \nassessed for internal \nconsistency reliability \nand a single-item \nmeasure is assessed by \ntest-retest reliability or \nitem response theory). \nOr, if used, reliability \nCronbach α ≥0.70 for \ngroup-level \ncomparisons. If lower, \nthere is clear and \nappropriate \njustification.  \nContent Validity \nDefinition: The extent to which \nthe measure includes the most \nrelevant and important aspects \nMinimal evidence \nparticipants or experts \nconsider the measure \nSome evidence \nparticipants and \nexperts consider the \nmeasure relevant \nClear evidence \nparticipants and \nexperts consider the \nmeasure relevant and \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n11 \n \n \nAttribute Poor quality (1) Fair quality (2) Good quality (3) \nof a concept in the context of a \ngiven measurement application. \nScore 0 if not assessed in article. \nrelevant and \ncomprehensive.  \nOr minimal \ndocumentation of \nmethodology for \nevaluating content \nvalidity.  \nand/or comprehensive \nfor the concept, \npopulation, and/or \nintended application. \nOr some evidence of \nmethodology used to \nevaluate content \nvalidity. \nOr the paper mentions \npast validation research \n(i.e., focus groups, pilot \nstudies, formative \nresearch) but does not \nprovide detail on these \nstudies. \ncomprehensive for the \nconcept, population, \nand intended \napplication. \nAnd clear evidence of \nmethodology used to \nevaluate content \nvalidity, including for \nassessing the \nrelevance of measured \nconcept(s), comparing \nvalidation study \nsample to the wider \ntarget population, and \njustification for recall \nperiod. \nConstruct Validity \nDefinition: The degree to which \nscores on the measure relate to \nother measures (e.g., patient-\nreported or clinical indicators) in \na manner that is consistent with \ntheoretically derived a priori \nhypotheses concerning the \nconcepts being measured. \nScore 0 if not assessed in article.  \n \nMinimal evidence \nsupporting pre-\ndetermined hypotheses \nrelated to construct \nvalidity. \nSome evidence \nsupporting pre-\ndetermined hypotheses \nrelated to construct \nvalidity. \nClear evidence \nsupporting pre-defined \nhypotheses on the \nexpected associations \namong other measures \nsimilar or dissimilar to \nthe studied measure. \nResponsiveness/dynamism \nDefinition: The extent to which \na measure can detect changes in \nthe construct being measured \nover time. \nScore 0 if not assessed in article.  \nMinimal evidence the \nmeasure can detect \nchanges consistent with \npre-defined hypotheses \nrelated to \nresponsiveness. \nOr minimal evidence the \nmeasure can detect \nchanges within or \namong participant \ngroups. \nSome evidence the \nmeasure can detect \nchanges consistent \nwith pre-defined \nhypotheses related to \nresponsiveness. \nOr some evidence the \nmeasure can detect \nchanges within or \namong participant \ngroups. \n \nClear evidence the \nmeasure can detect \nchanges consistent \nwith pre-defined \nhypotheses in the \ntarget population for \nthe intended \napplication.  \nAnd clear evidence the \nmeasure can detect \nchanges within or \namong participant \ngroups. \nSensitive nature of items \nDefinition: How measure \naddresses questions of sensitive \ntopics, including those that are \nseen as intrusive, posing a \nthreat of disclosure, or eliciting \nsocially desirable answers. \nScore 0 if not assessed in article. \nMinimal evidence about \nmeasure or item \nsensitivity \nOr evidence of \nsensitivity that may \nresult in biased \nresponses \nSome evidence or \ndiscussion about \nmeasure or item \nsensitivity \nOr some evidence of \nreduced sensitivity that \nwould not result in \nbiased responses \nClear evidence about \nmeasure or item \nsensitivity \nAnd clear evidence of \nreduced sensitivity \nthat would not result \nin biased responses \nClinical trial utility \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n12 \n \n \nAttribute Poor quality (1) Fair quality (2) Good quality (3) \nInterpretability of results \nDefinition: The degree to which \none can easily understand a \nmeasure’s results (e.g., scores, \nlevels). \nScore 0 if not provided in article. \n \nMinimal evidence for \ninterpreting results. \nOr minimal evidence \nresults are understood \nby relevant \nstakeholders. There is \nno clinically relevant \nminimum change or no \nassessment of clinical \nrelevance. \nSome evidence for \ninterpreting results.  \nOr some evidence \nresults are understood \nby relevant \nstakeholders, including \npatients, clinicians, \nand/or researchers. \nThere is an agreement \non clinically relevant \nminimum change \nand/or assessment of \nclinical relevance.  \nClear evidence of \ninterpreting results, \nincluding \ndifferentiating \nbetween differing \noutcomes (e.g., high \nand low scores), \nand/or what \nconstitutes a large or \nsmall change in the \nmeasured concept. \nAnd evidence results \nare clearly understood \nby multiple relevant \nstakeholders, including \npatients, clinicians, \nand researchers. There \nis an accepted \nclinically relevant \nminimum change. \nTransferability \nDefinition: The degree to which \nthe measure can be transferred \nbetween linguistic and \nsociocultural groups. \nScore 0 if not provided in article. \n \nMinimal evidence \nmeasurement \nproperties are \nmaintained across \nlinguistic and/or cultural \ngroups. \nSome evidence \nmeasurement \nproperties are \nmaintained across \nlinguistic and/or \ncultural groups. \nClear evidence \nmeasurement \nproperties are \nmaintained across \nlinguistic or cultural \ngroups, including \nqualitative testing of \nthe translated \nmeasure. \nParticipant Burden \nDefinition: The time, effort, \nresource (e.g., use or ownership \nof smart phone, internet access \nrefrigeration), and other \ndemands placed on those to \nwhom the measure is \nadministered. \nScore 0 if not provided in article. \n \n \nMeasure requires more \nthan 20 minutes† to \ncomplete (>40 \nquestions), requires \ndata collection daily or \nmultiple times a day, \nand/or multiple clinic \nvisits or daily data \ncollection outside the \nhome. Or there is no \ninformation on \nexpected participant \ntime burden. \nOr the measure requires \nresources not available \nto most participants.   \nOr there is minimal \ninformation on literacy \ndemand of measure \nitems or \nMeasure requires \nbetween 15-20 \nminutes† to complete \n(20-40 questions), \nand/or one or two \nclinic visits, including \nthose that are a burden \nto participant. Or there \nis limited information \non expected participant \ntime burden, including \nlimited or no input \nfrom participant review \npanels. Or the measure \nmay require some \nresources can be a \nbarrier to some \nparticipants.  \nOr literacy demand of \nmeasure items is above \na 6th grade level (i.e., \nMeasure requires less \nthan 15 minutes† to \ncomplete (<20 \nquestions), no daily \ndata collection, and no \nmore than one clinic \nvisit. Or there is an \naccurate description of \nthe expected \nparticipant time \nburden with approval \nfrom participant \nreview panels. \nOr there are no \nresource barriers to \nparticipants.  \nAnd literacy demand \nof measure items is at \na 6th grade level or \nlower (i.e., ≤12-year-\nold), or literacy level is \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n13 \n \n \nAttribute Poor quality (1) Fair quality (2) Good quality (3) \nappropriateness for \nproposed context. \n>12-year-old) and not \nappropriately justified \nfor proposed context. \nappropriately justified \nfor proposed context. \nInvestigator Burden \nDefinition: The time, effort, \nresource, and other demands \nplaced on those who administer \nthe measure. \nScore 0 if not provided in article. \n \n \nThere is a high burden \non the data collection \nteam due to: (a) data \ncollector training being \ntime or cost prohibitive \nwith a lack of available \ntraining materials; (b) a \nhigh data monitoring \nburden to maintain \nquality data; (c) \nmeasure scoring being \ncomplex; or (d) measure \ninflexible or resource \nintensiveness (e.g., can \nonly be interviewer-\nadministered or \nrequires tablet or \ncomputer). \nOr there is minimal \ninformation on \ninvestigator burden. \nThere is a modest \nburden on the data \ncollection team due to: \n(a) the time and cost of \ndata collector training \nor lack of training \nmaterials; (b) data \nmonitoring burden; (c) \nmodest measure \nscoring complexity; or \n(d) the measure being \neither flexible or not \nresource intensive. \nOr there is limited \ninformation on \ninvestigator burden. \nThere is a low burden \non a data collection \nteam due to (a) \nminimal requirement \nfor data collector \ntraining and \navailability of training \nmaterials; (b) low data \nmonitoring burden, (c) \nmeasure scoring being \nsimple, or (d) the \nmeasure being flexible \nand not resource \nintensive (e.g., either \nmeasure is completed \nby the participant or is \neasily explained and \ncompleted).  \nOr there is an accurate \ndescription of the \nexpected investigator \nburden. \n* Attributes and definitions from Reeve et al. 2013 [51] per PROTEUS-Trials Consortium guidance [50], with \nmodified as specified in the text. \n† Crossnohere et al., 2021 [53] \nData analysis \nWe conducted data analysis in Excel and included counts and frequencies, as well as specific analyses to \nassess instrument measure quality and clinical trial utility. For the measure quality score and clinical \ntrial utility score of an instrument, we used an average of the highest score for each attribute of \nmeasure quality or clinical trial utility across all articles on an instrument. Because instruments could \nhave more than one article providing data on measure quality and/or clinical trial utility and not every \narticle evaluated all attributes of an instrument, we did not include scores of zero (i.e., no data reported) \nin these averages. To reflect these differences in the number of articles and attributes reported in the \narticle(s), we also calculated a total evidence score, which was the total of all scores—including zeros—\nacross all attributes of measure quality and clinical trial utility. The total evidence scores, therefore, \n‘penalize’ instruments for a lower level of evidence due to fewer articles or less attribute data and vice \nversa.  \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n14 \n \n \nThese three scores—measure quality (ranging from 1-3), clinical trial utility (ranging from 1-3), and total \nevidence (ranging 0+)—reflect different dimensions of an instrument. For example, two instruments \nmight both have a score of 2.5 for measure quality, but one instrument might have an evidence score of \n10 and the other, 100, indicating the latter has considerably more evidence and likely more certainty in \nthe measure quality score. Alternately, two instruments may have similar measure quality and evidence \nscores, but one may have a clinical trial utility score of 1 and the other a score of 3, indicating the latter \nis likely better suited for use in clinical trials despite the similar levels of measure quality and evidence. \nRESULTS \nSearch results \nAcross databases, our searches yielded 8,490 articles. We removed 376 duplicates, excluded 7,704 \narticles during title and abstract screening, and excluded 236 articles during full text review. In total, we \nidentified 174 relevant full text articles. We present additional details on our search results and \nscreening in the PRISMA diagram in Figure 1. \nFig. 1. PRISMA Diagram* \n \n* Per Page et al., 2021 [40] \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n15 \n \n \nWe found some similarities across papers that we excluded for not meeting our inclusion criteria. For \nexample, we excluded conference presentations that never became full papers, studies that focused on \nvalidating instruments among only menopausal populations (e.g., [54,55]), and studies that only \nvalidated surgical or treatment outcomes (e.g., [56,57]). In addition, there were two recent papers on \ncore outcome sets for HMB and endometriosis relevant to the wider topic of measuring changes to the \nmenstrual cycle, but we excluded them because there were no instrument details to extract [58,59]. \nIncluded article characteristics \nOver 85% of the 174 articles were from either Europe (43%), North America (32%) or Asia (13%), and \nthere were less than 15 articles from South America (n=13), from the Middle East (n=11), from Oceania \n(n=8) and from Africa (n=5). Just under half of articles were from only the United States (28%) or the \nUnited Kingdom (16%), although we did identify articles from a total of 50 countries. Nearly all articles \nwere in English—even those reporting on instruments in other languages—except for two in Portuguese \n[60,61]. The most common study designs were cross-sectional or prospective cohort. We present details \nof all 174 included articles in Table S3. \nInstrument characteristics \nFrom the 174 included articles, we extracted 94 instruments. Almost three quarters (72%, n=68) were \nfull instruments, collecting data on one or more menstrual change. Nearly a quarter (n=21) were \nbroader instruments that included sub-scales (9%, n=8) or a small number of items (14%, n=13) on \nmenstrual changes. Five percent (n=5) were general instruments validated in menstruating populations \non one or more menstrual change. The instruments with the most articles in our review were the \nEndometriosis Health Profile-30 (EHP-30; 20 articles), the Pictorial Blood Loss Assessment Charts & \nMenstrual Pictograms (PBAC; 11 articles), the Uterine Fibroid Symptom and Quality of Life questionnaire \n(UFS-QOL; 9 articles), the Polycystic Ovary Syndrome Quality of Life scale (PCOS-QOL; 8 articles), and the \nEndometriosis Health Profile-5 (EHP-5), Menstrual Attitudes Questionnaire (MAQ), and menstrual \ncollection (5 articles each). About a third (38%, n=26) of full instruments used electronic data collection, \nand almost all full instruments (97%, n=66) were completed by only the patient/participant who \nmenstruated (i.e., they were PROs per the FDA and NIH definition). We present the list of the 68 full \ninstruments and instrument characteristics in Table 4. The remainder of results reported below are for \nthese full instruments, with details on the sub-scales, items, and general instruments in Table S4. \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n16 \n \n \nTable 4. List of full instruments and characteristics \nSee end of file for Table 4. \nLanguage(s) \nOf the 68 full instruments, two-thirds were in English (66%, n=45), followed by Spanish (13%, n=9), \nFrench (9%, n=6), and Portuguese (9%, n=6); however, we identified instruments in 28 languages. About \nforty percent of instruments (41%, n=28) were only in English, although about a quarter of instruments \n(26%) were in more than one language, and six instruments were in at least 4 languages. These \ninstruments included the EHP-30 (13 languages), UFS-QOL (5 languages), MAQ (5 languages), PBAC (4 \nlanguages), Endometriosis Daily Diary (EDD; 4 languages), and the Daily Diary (4 languages).  \nSpecific Populations  \nNearly 60% (n=40) of the 68 full instruments were developed and/or validated in populations with \nmenstrual or gynecologic disorders or symptoms (i.e., 18 for endometriosis, 10 for HMB, 9 for \ndysmenorrhea, and 3 for uterine fibroids). Less than a quarter (24%, n=16) of full instruments were \ndeveloped for and validated with adolescents (mean ages less than 18, n=10) or young people (mean \nages early 20s, n=6). Three full instruments were specifically developed for those in perimenopause. A \nfew instruments were developed or validated in populations of athletes or people in the military. No \ninstruments or articles indicated inclusion of trans and gender nonbinary people who menstruate. \nMenstrual change(s) measured \nAmong the 68 full instruments, half (49%, n=33) measured bleeding, nearly half (47%, n=32) measured \nuterine cramping or pain, and almost three quarters (74%, n=50) measured perceptions. Only eight \n(12%) measured blood characteristics. Three instruments assessed all four of the parameters of \nbleeding—duration, volume, frequency, and regularity/predictability (i.e., the Aberdeen Menorrhagia \nSeverity Scale [AMSS], the New Zealand Survey of Adolescent Girls' Menstruation, and the World \nEndometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonisation Project \nStandard Questionnaire [WERF EPHect EPQ-S]). No instrument assessed all three parameters of blood—\ncolor, consistency, and smell.  \nAcross the four aspects of menstrual changes (i.e., bleeding, blood, pain, and perceptions), no \ninstrument measured all parameters for each aspect, and only seven instruments measured at least a \nsingle parameter of each aspect. These instruments were the AMSS; electronic Personal Assessment \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n17 \n \n \nQuestionnaire - Menstrual, Pain, and Hormonal (ePAQ-MPH); Endometriosis Self-Assessment Tool \n(ESAT); Fibroid Symptom Diary (FSD); Menstrual Bleeding Questionnaire (MBQ); Menstrual Insecurity \nTool; and the New Zealand Survey of Adolescent Girls' Menstruation.  \nHow instruments measured menstrual changes \nWe present in Table 5 details on how the 68 full instruments measured bleeding (i.e., the four \nparameters of duration, volume, frequency, and regularity/predictability), blood (i.e., the three \nparameters of color, consistency, and smell), uterine cramping/pain, and perceptions.  \nTable 5: How full instruments measured aspects of menstrual changes, including bleeding, blood, \nuterine pain, and perceptions \nAspect of \nmenstrual \nchanges Parameter \nNumber of \ninstruments How instruments measured \nBleeding* Any 33  \n \nDuration 12 \n• One instrument only measured bleeding duration and \nno other parameter of bleeding or other aspects of \nmenstrual changes. \no It used prospective diaries to record the first and \nlast days of menses/bleeding episodes just to \nmeasure duration.  \n• 11 instruments measured bleeding duration and other \naspects of menstrual changes. \no Three measured duration and another parameter \nof bleeding, either using diaries and/or annual \ninterviews or a question on days of bleeding for \nevery menstrual period over four months.  \no Eight measured bleeding duration along with \nother menstrual changes (i.e., blood, pain, or \nperceptions). \n▪ Seven were questionnaires generally asking \nrespondents to note how many days their \nmenses/bleeding episodes last on average, \neither in general or in the last three months. \nThree specifically asked if respondents had \nbleeding for more than seven days per month.  \n▪ One diary asked respondents to note if they \nhad bleeding on specific days. \no Six were developed for people with menstrual or \ngynecologic disorders and symptoms (e.g., HMB, \nendometriosis, or fibroids).  \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n18 \n \n \nAspect of \nmenstrual \nchanges Parameter \nNumber of \ninstruments How instruments measured \n \nVolume 26 \n• Five instruments only measured bleeding volume and \nno other parameter of bleeding or other aspects of \nmenstrual changes. \no Three semi-quantitatively measured blood volume \nvia used menstrual products, including alkaline \nhematin assays and menstrual collection or record \nand recall measures. \no One relied on respondents to estimate bleeding \nvolume through the Mansfield-Voda-Jorgensen \nMenstrual Bleeding Scale. \no One was a statistical model for estimating blood \nloss that was developed based on previously \ncollected hematological values, daily diaries, and \npatient age among participants with HMB. \n• 21 instruments measured bleeding volume and other \naspects of menstrual changes. \no 14 were questionnaires, five were diaries, one \nused pictorial references, and one was a visual \nanalog scale (VAS) where volume was rated on a \nscale from 0 (no bleeding) to 100 (the heaviest \npossible bleeding ever experienced). \n▪ Most asked about perceived volume of blood \nloss, usually by asking respondents to describe \ntheir bleeding in some range of light, medium, \nor heavy and/or reporting on the number of \nmenstrual products (pads and/or tampons) \nthey used on the heaviest day of their period. \n∙ Terms like ‘light’, ‘heavy’ and/or ‘spotting’ \nwere not always or consistently defined \nacross instruments, and there was a wide \nrange for the frame of reference for recall, \nwith diaries asking every day, other \ninstruments asking about the last month or \nlast menses/bleeding episode, and others \nasking more generally about experiences \npeople typically have during \nmenses/bleeding episodes. \n▪ Some instruments also asked how many days \nof heavy bleeding the respondent experienced \nduring the last cycle and how many days \nrequired double protection with multiple \nproducts at the same time. A few asked \nwhether respondents had bleeding heavy \nenough to stain clothing or required getting up \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n19 \n \n \nAspect of \nmenstrual \nchanges Parameter \nNumber of \ninstruments How instruments measured \nin the middle of the night to change menstrual \nproducts. \n▪ PBAC and other similar pictorial assessments \nhad respondents estimate the amount of \nbleeding via pictorials of used pads and/or \ntampons. \no 18 were designed for use by people with \nmenstrual or gynecologic disorders and \nsymptoms. \n \nFrequency 8 \n• Three instruments only measured bleeding frequency \nand no other parameter of bleeding or other aspects \nof menstrual changes. \no They asked respondents a few retrospective \nquestions (i.e., “‘How long is your menstrual cycle, \non average? In other words, how many days are \nthere from the first day of one menstrual period to \nthe first day of the next period?”) or to recall the \nfirst date of their last menstrual period. Another \nused a retrospective questionnaire on usual, \nshortest, and longest menstrual cycle length in the \npast 12 months, and this was compared to a \nprospective diary for two menses/bleeding \nepisodes. \n• Five instruments measured bleeding frequency and \nother aspects of menstrual changes. \no One was a diary. \no Four were questionnaires asking respondents to \nstate how many days there were, on average, \nbetween the start or first day of one \nmenses/bleeding episode to the first day of the \nnext menses/bleeding episode, or asking whether \ntheir menstrual cycle was between 21 and 45 \ndays. \n \nRegularity/ \npredictability 9 \n• No instruments only measured bleeding \nregularity/predictability without other parameters of \nbleeding or other aspects of menstrual changes. \n• Nine instruments measured bleeding \nregularity/predictability and other aspects of \nmenstrual changes. \no All were questionnaires, generally asking \nrespondents to report if their bleeding was \n“regular” or “irregular” in general or over the past \nthree months, but regularity was not defined \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n20 \n \n \nAspect of \nmenstrual \nchanges Parameter \nNumber of \ninstruments How instruments measured \nfurther. One, the MBQ, asked respondents if both \ntheir bleeding start and end dates in the last \nmonth were completely, somewhat, or not at all \npredictable. One, the ePAQ-MPH, contained a \nregularity domain, which asked about both \nregularity of timing and predictability. \no Five were specifically developed for those with \nmenstrual or gynecologic disorders and \nsymptoms.  \nBlood** Any 8  \n Color 0 • No instruments measured blood color. \n \nConsistency 7 \n• Seven instruments asked about blood consistency. \no They were the PBAC/pictorial assessments, five \nquestionnaires, and one diary.  \n▪ The questionnaires and diary specifically asked \nabout blood clots—either ever or during the \npast month—while one also asked about \n“thick bleeding” during menstrual periods. \n \nSmell 1 \n• One instrument collected information about blood \nsmell. \no The Menstrual Insecurity Tool asked about smell \nof the “menstrual cloth, napkin, or [respondent’s] \nbody”. \nUterine \npain† Total 32  \n \n- - \n• Five instruments only measured uterine pain and no \nother aspects of menstrual changes. \no Two were VAS or numeric rating scales (NRS), \nwhere pain experienced was rated on a scale from \n0 (no pain) to 10 or 100 (worst or unbearable \npain).  \no One used a rubber bulb, which participants \nsqueezed and corresponding measurements were \nrecorded in reference to pain experienced.  \no One gave participants a diagram of the body and \nasked to paint the areas affected by pain during \ntheir current menstrual period.  \no One included a single, retrospective question \nasking respondents to classify their frequency of \nmenstrual discomfort as “always,” “often,” \n“sometimes,” or “never”. \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n21 \n \n \nAspect of \nmenstrual \nchanges Parameter \nNumber of \ninstruments How instruments measured \n• 27 instruments measured uterine pain and other \naspects of menstrual changes. \no 17 were questionnaires and eight were diaries. \n▪ Ten used NRS measures, 8 asked about the \nuse of and/or dosage of pain medications, 12 \nasked about whether pain affected daily \nactivities or quality of life, and 11 asked about \npain and sexual activity/vaginal penetration.  \n▪ Four instruments had extensive sections on \npain, covering multiple aspects. These \nincluded the ePAQ-MPH, the Endometriosis \nPain and Bleeding Diary, the New Zealand \nSurvey of Adolescent Girls' Menstruation, and \nWERF EPHect EPQ-S. \no 19 were developed for use with those with \nmenstrual or gynecologic disorders and \nsymptoms, including 12 specifically for \nendometriosis. \nPerceptions‡ Total 50  \n \n- - \n• 50 instruments measured perceptions about the \nimpact of menstruation on life. \no 41 were questionnaires and 9 were diaries asking \nabout daily activities, sexual activity, sleep, \nemotions, and management of materials to absorb \nor collect menstrual blood. \n▪ 38 assessed how aspects of the menstrual \ncycle impacted people’s daily activities, \nincluding work, social/leisure activities, \nwalking or sitting. 15 asked specifically about \npain limiting activities, and 19 asked more \ngenerally about the impact of menstruation or \ndisorders on activities. Some instruments \nasked about the impact of multiple symptoms \non activities.  \n▪ 16 asked about impact or limits on sexual \nactivity, including 7 on the general impact, 11 \non the impact from pain, or 3 on the impact \nfrom bleeding. Some instruments asked about \nthe impact of multiple symptoms on sexual \nactivity.  \n▪ 13 asked about the impact of menstrual \nchanges on sleep, 7 on the general impact and \n6 that were specific to pain.  \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n22 \n \n \nAspect of \nmenstrual \nchanges Parameter \nNumber of \ninstruments How instruments measured \n▪ 32 asked about emotions, either changes \nduring the menstrual cycle or the impact of \nsymptoms—such as in bleeding or pain—on \ntheir emotions.  \n▪ 6 had items on management of menstrual \nmaterials, most of which were in low- and \nmiddle-income country settings. \no 29 were developed for those with menstrual or \ngynecologic disorders and symptoms. \n* There were 7 instruments with sub-scales that collected data on bleeding, 8 instruments with one to \nfive items on bleeding, and two general instruments with items that asked about bleeding. Most sub-\nscales and items were for bleeding volume or regularity/predictability, often using terms not clearly \ndefined or elaborated (e.g., ‘regular’ and ‘normal’). See Table S4 for details. \n** One instrument had a subscale that collected data on blood color, consistency, and smell (i.e., the \nMenstrual Cycle-Related Signs and Symptoms Questionnaire subscale Section 1), and one other \ninstrument had an item that asked about blood consistency (i.e., the Stellenbosch Endometriosis Quality \nof Life Measure). See Table S4 for details. \n† Four instruments with subscales, seven instruments with one to five items, and three general \ninstruments asked about pain. See Table S4 for details. \n‡ Two instruments with subscales, six instruments with one to five items, and four general instruments \nasked about perceptions. See Table S4 for details. \nMeasure quality of full instruments \nWhen assessing measure quality, we found only five of the 68 full instruments (7%) had data on each of \nthe six attributes of measure quality (i.e., conceptual or measurement model, reliability, content \nvalidity, construct validity, responsiveness, and sensitive nature of questions). These were the PBAC, \nEHP-30, Dysmenorrhea Daily Diary, MBQ, and a quantitative model for menstrual blood loss [62], each \nindicated by †† in Table 4. All but three instruments (96%, n=65) had evidence of a conceptual or \nmeasurement model and most also included evidence of content validity (81%, n=55), construct validity \n(84%, n=57) and reliability (66%, n=45); however, less than a third of instruments had evidence on \nresponsiveness (31%, n=21), and less than a fifth (19%, n=13) had evidence on question sensitivity \n(Figure 2).  \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n23 \n \n \nFig. 2. Instrument measure quality by attribute for full instruments \nOf the 68 full instruments, 18% (n=12) had an overall good measure quality score, about three quarters \n(74%, n=50) had a fair measure quality score, and 9% (n=6) had a poor measure quality score (Table 4 \nand Figure 2). When we looked at individual attributes of measure quality, over half of instruments had \na good score for content validity (56%, n=38), 47% had a good score for reliability (n=32), 44% had a \ngood score for conceptual or measurement model (n=30), and over a third of instruments (35%, n=24) \nhad a good score for construct validity; however, only a quarter had a good score for responsiveness \n(25%, n=17), and only 4 instruments (6%) had a good score for question sensitivity.  \nUtility for clinical trials of full instruments \nWhen assessing clinical trial utility, we found 11 full instruments (16%) had data on each of the five \nattributes of utility (i.e., interpretability of results, transferability, participant burden, and investigator \nburden), each indicated by ‡ in Table 4. All but three instruments (96%) had information on participant \nburden, 84% (n=57) had evidence of the interpretability of the instrument results, and slightly less than \ntwo thirds (60%, n=41) had documented investigator burden; however, only just over one third (37%, \nn=25) had evidence of transferability (Figure 3). \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n24 \n \n \nFig. 3. Instrument utility in clinical trials by attribute for full instruments \nOf the 68 full instruments, 22% (n=15) had an overall good clinical trial utility score, almost two thirds \n(62%, n=42) had a fair score, and 13% (n=9) had a poor score (Table 4 and Figure 3). When we looked at \nindividual attributes of clinical trial utility, almost half of instruments (49%, n=33) had a good score for \nthe interpretability of results, about 40% had good scores for participant burden (41%, n=28) or \ninvestigator burden (40%, n=27), but only 8 instruments (12%) had good scores for transferability. \nOverall full instrument evidence \nOnly the PBAC had evidence on all attributes of measure quality and all attributes of clinical trial utility, \nand only three instruments had both a good measure quality score and a good clinical trial utility score: \nEHP-5, the Spanish Society of Contraception Quality-of-Life (SEC-QOL), and the SAMANTA \nQuestionnaire. Thirteen instruments had both measure quality scores and clinical trial utility scores \ngreater than 2.5. Only one instrument, the Squeezing Pain Bulb, had both poor measure quality and \npoor clinical trial utility. Full instrument total evidence scores ranged from 4 for the World Health \nOrganization Disability Assessment Schedule 2.0 to 332 for the EHP-30, with an overall median score \nacross instruments of 16 and mean score of 27 (Table 4). Overall, the following instruments had the five \nhighest scores across measure quality, clinical trial utility, and total evidence: EHP-30, EHP-5, UFS-QOL, \nPBAC, and MBQ.  \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n25 \n \n \nDISCUSSION \nOur broad, transdisciplinary systematic review on the measurement of menstrual changes caused by any \nintrinsic or extrinsic factor, etiology, or source yielded 174 relevant articles and 94 instruments. Through \nour data extraction and analysis of these articles and instruments, we found several strengths and \nnotable gaps in this literature around geographic and linguistic representation, how menstrual changes \nwere measured, measure quality and clinical trial utility, and menstrual stigma, among others. \nGeographic and linguistic representation \nWe identified articles from all geographic regions and 50 countries, and full instruments in 28 languages, \nincluding over a quarter in more than one language. Despite this evidence of the breadth of the \nliterature, three quarters of articles were from North America or Europe and almost half were from just \nthe United States and United Kingdom. In addition, over half of full instruments were only in English, \nSpanish, French, or Portuguese. These findings indicate the existing instrument landscape centers \naround the US and Western Europe, as well as colonial languages.  \nHow menstrual changes were measured \nWe again found promising strengths mixed with important gaps when examining the menstrual changes \ninstruments measured and how they were measured. Although many full instruments measured \nperceptions and at least one parameter of bleeding or pain, only 8 full instruments measured blood. It is \npossible this lack of data collection on blood is due to the wide influence of menstrual stigma, especially \nthe common perspective that menstrual blood is ‘dirty’ and requires ‘hygiene’ products to cleanse, \nabsorb, and hide blood or odor [52,63,64]. No full instruments measured all parameters for each of the \nfour aspects of menstrual changes we assessed, and only 7 instruments measured at least one \nparameter for all four aspects. In addition, across all aspects of menstrual changes, we did not find high \nlevels of uniformity between instruments regarding how they measured each menstrual change, and \nmany did not explain or define key terms (e.g., ‘heavy’, ‘regular’), leaving their interpretation up to each \nrespondent. This lack of clarity and specificity raises concerns about measurement error for a topic like \nmenstruation and the wider menstrual cycle, around which there is high stigma and low health literacy \nand therefore, reduced shared understanding and references. These findings indicate there is a lack of \ninstruments that examine all parameters and aspects of changes to the menstrual cycle in a \ncomprehensive and standardized way. \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n26 \n \n \nNearly 60%  of full instruments we identified were developed for those with menstrual or gynecologic \ndisorders and symptoms. In fact, the 3 instruments that accounted for almost a quarter of all identified \narticles—the EHP-30, PBAC, and USF-QOL—were each developed for use in populations with \nendometriosis, HMB, and fibroids, respectively. Instruments for these populations are of crucial \nimportance, and it is encouraging to see over 70% of identified articles published in the last 5 years \nexamine menstrual or gynecologic disorders and symptoms. However, the measurement of menstrual \nchanges resulting from these disorders, such as very heavy bleeding and high levels of pain, may not \ntranslate to the menstrual changes experienced by the wider menstruating population or to the range of \nmenstrual changes likely to occur across clinical trials and related research. For example, the extension \nof an instrument developed for those with HMB to a clinical trial of a hormonal contraceptive—which \ngenerally decreases bleeding volume—is yet to be supported by evidence. This difference is important \nbecause we could hypothesize, for example, there would be a difference in recall from a bleeding \nepisode that resulted in stained clothing (i.e., from HMB) compared to a bleeding episode that did not \ninterfere with daily activities (i.e., from a hormonal contraceptive). Because of these findings, \ninstruments likely need to be developed or modified to capture a wider array of changes in bleeding, \nblood, and pain, as well as changes that are of smaller—but still meaningful—magnitude.  \nInstrument quality and utility \nFrom our assessments of measure quality and clinical trial utility for full instruments, we also found \nvariability in our outcomes. Over 80% of instruments had either fair or good scores for measure quality \nor clinical trial utility, and only one had both poor measure quality and poor clinical trial utility. On the \nother hand, only three instruments had both good measure quality and good clinical trial utility.  \nWe also note almost all instruments had evidence supporting some quality and utility attributes but not \nothers. Sixty percent or more of instruments had evidence of a conceptual or measurement model, \nreliability, content validity, or construct validity for measure quality, or had evidence of interpretability \nof results, participant burden, or investigator burden for clinical trial utility; almost a quarter of \ninstruments had evidence of each of these seven attributes. On the other hand, only one instrument—\nthe PBAC—had evidence for all attributes of quality and utility, and over 60% of instruments did not \nhave evidence of responsiveness, question sensitivity, or transferability, with nearly 40% not having \nevidence of any of the three. Each of these largely missing attributes are likely to be important for any \ninstrument used broadly, especially in clinical trials. Such an instrument will need to: (a) capture changes \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n27 \n \n \nduring investigational drug use (responsiveness); (b) not be viewed as too intrusive or stigmatizing \n(question sensitivity); and (c) be used in multiple linguistic and sociocultural contexts (transferability). \nMenstrual stigma and other notable gaps \nOur findings on the limited measurement for blood and lack of evidence for question sensitivity highlight \nthe importance of menstrual stigma. We often found a contradiction during the development and \nvalidation of instruments; although menstrual stigma was frequently acknowledged as part of the \nsociocultural milieu surrounding menstruation, instruments generally did not adequately address \nmenstrual stigma or how stigma may relate to question sensitivity and the potential impact of this on \ndata quality or measurement error.  \nBeyond the difficulty of measurement due to menstrual stigma, there is innate complexity in measuring \nchanges to a biological process that, itself, consists of so many facets that change over time and vary \nbetween individuals [65,66]. For example, there are changes between days of a single menstrual cycle \n(e.g., different bleeding and/or pain experienced on different days of a cycle), differences among \nmenstrual cycles during the same year, and shifts over the menstruating life course for one individual \nperson who menstruates, as well as a multitude of differences between people [67–69]. These factors \nare important when we consider just under half of articles for the identified full instruments had cross-\nsectional study designs. In fact, this study design limitation could be the reason we found a lack of \nevidence on instrument responsiveness and measurement of more temporally-related parameters like \nbleeding frequency and regularity/predictability.  \nIn addition to the gaps in the literature and instrument landscape already mentioned, three additional \nfindings warrant attention. First, only just over a third of instruments used electronic data collection. \nAlthough this may be partly due to our review extending through 2006, new and refined instruments \nshould strongly consider this approach given the data quality and monitoring benefits of electronic data \ncollection and with the current proliferation of period tracking and other FemTech applications [70,71]. \nIn addition, there is a need to establish the equivalence between existing paper instruments and any \nelectronic versions developed, ideally in accordance with established approaches like the International \nProfessional Society for Health Economics and Outcomes Research (ISPOR) good research practices on \nuse of mixed mode PROs [72]. \nSecond, there is a lack of attention paid to the two ends of the menstruating life course. There were only \nten instruments specifically developed with data from adolescents and three instruments developed for \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n28 \n \n \nthose in perimenopause, both groups who can experience an increased amount of variability and \nchange in their menstrual cycles as compared to the middle of the menstruating years [73]. In addition, \ndata on older menstruators were often collapsed for people who were in perimenopause and \nmenopause/post-menopause, or age was commonly used as a proxy for this process and transition. \nAlthough the age range for menopause is narrower than that of menarche, given the general lack of \nresearch around menopause and the preceding and succeeding years, it seems the opposite should be \ntrue (i.e., more data and larger sample sizes among people around the end of their menstruating years is \nwarranted) [74].  \nThird, we found a lack of inclusion for trans and gender nonbinary populations in all articles for all \ninstruments. As we note in the introduction of this paper, people who menstruate may or may not \nidentify as women or girls, and not all women and girls menstruate. It is important to engage all \npopulations who menstruate in the development of instruments to measure changes to the menstrual \ncycle. Inclusion of sexual and gender minority (SGM) individuals who menstruate in clinical trials is a \nnoted priority among NIH and other funders and researchers. In addition to NIH establishing its SGM \nResearch Office in 2015, clinical research is the first theme of the current Strategic Plan to Advance \nResearch on the Health and Well-being of SGM populations [75].   \nLimitations of the review \nAlthough we followed PRISMA guidelines and included ‘inter-reviewer reliability’ checks, weekly \nmeetings, and multiple reviewers per article, there are a few limitations to note about our review \nprocess. The most important limitations are related to decisions made regarding the scope of the review \nto make it focused and feasible. First, we only included four aspects of changes to the menstrual cycle: \nchanges in bleeding, blood, pain, and perceptions of bleeding, blood, or pain. Although these aspects are \nlikely the most studied thus far, there are many other important changes to the menstrual cycle, \nincluding in hormone levels, the phases of the menstrual cycle, characteristics of those phases, and \nother symptoms besides pain. As the study of menstrual health grows, it will be important for future \nreviews to consider these areas of research. We also limited our scope to the menstrual cycle, excluding \nother types of uterine bleeding, such as bleeding during pregnancy, while breastfeeding, and after \nmenopause. Future insights into how these types of bleeding relate to bleeding during the menstrual \ncycle will be important to the research and understanding of all uterine bleeding. \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n29 \n \n \nWe also note a few limitations related to our review process. First, although all authors have training \nand experience across multiple disciplines, none are experts in all fields from which we drew our \nliterature given our transdisciplinary approach. We aimed to address this limitation by consulting other \nexperts internally at FHI 360 and members of a related global task force when we encountered a \nquestion or issue outside of our knowledgebase, but it is still possible we missed articles, data for \nextraction, or other elements due to this limitation. Second, the primary impetus for the review among \nthe authors was to inform measurement of menstrual changes in the context of contraceptive clinical \ntrials, so we cannot completely rule out the possibility this internal aim may have influenced our \ndecisions about including or excluding articles. From the very beginning of the review, however, we \nsought for the review to be useful across contexts and disciplines, so our protocol and process were \ndesigned and implemented with that purpose in mind. Third, we may have missed articles by deciding to \nnot include the CINAHL and PsycINFO databases in addition to those we did include (i.e., MEDLINE, \nEmbase, and the instrument databases). Despite reviewing at least 50 articles most relevant to search \nstrategies for CINAHL and PsycINFO and finding none aligned with our inclusion criteria, it is possible \nthere were articles relevant to our review in the rest of the search results from these two databases. \nFourth, because we did not want to exclude articles from any region or language but are not fluent in all \nlanguages, we used Google Translate for some screening and review. It is, therefore, possible this \ntranslation did not allow us to sufficiently evaluate articles per our inclusion and exclusion criteria. For \nthe two relevant articles not written in English, we did complete data extraction with a fluent colleague. \nOverall, there may be additional limitations about which we are not aware that may have biased the \nresults of our systematic review. Our hope is, however, we took steps to mitigate as many as possible by \nhaving our protocol and instrument evaluation criteria reviewed by other experts, following best \npractice guidelines, and taking steps to reduce individual variability and biases. \nCONCLUSION \nDespite the novel, broad, and transdisciplinary approach to our systematic review, the current \ninstrument landscape, limitations in the literature, and gaps in evidence on measure quality and clinical \ntrial utility indicate there is a need to examine changes to the menstrual cycle in a more complete, \ninclusive, and standardized way. Rigorous formative research—across sociocultural contexts—that is \nfocused on how all people who menstruate experience and understand their menstrual cycles and more \nfully addresses menstrual stigma can inform the development of new or modified instruments to meet \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n30 \n \n \nthis need. We also identified a need for greater evidence of the validity for existing and new \ninstruments. For the clinical trial context, FDA guidance on selecting, developing, or modifying patient-\nreported outcomes like menstrual changes indicate there must be evidence to support the use of an \ninstrument for the specific concepts of interest and context of use [37]. At a minimum, per this \nguidance, evidence would be needed to support the use of the instruments identified and assessed in \nthis review in the clinical trial context with a broader patient population (i.e., context of use) and to \nmeasure the full scope of menstrual changes that people experience (i.e., concept of interest). In \naddition, the recent emergence of core outcome sets within areas like HMB and endometriosis will be \nuseful to promote standardization of validated instruments, especially if these efforts are \ninterdisciplinary and coordinated across research areas. \nThe findings of our review will be helpful in developing new or modified instruments that assess \nmenstrual changes in a validated, comprehensive way. If used across the many fields that study \nmenstrual health, data from these standardized instruments can contribute to an interdisciplinary, \nsystemic, and holistic understanding of menstruation and the menstrual cycle. In turn, this improved \nunderstanding can be translated into ways to enhance the health and wellbeing of people who \nmenstruate. \nACKNOWLEDGEMENTS \nThe authors would like to thank Laneta Dorflinger, Rebecca Callahan, and members of the Global \nContraceptive Induced Menstrual Changes (CIMC) Task Force for their feedback on the draft review \nprotocol. We are very grateful for the guidance and assistance provided by the FHI 360 health sciences \nlibrary throughout the development and implementation of our literature search strategy (Allison Burns \nand Carol Manion) and during retrieval of full text articles (Tamara Fasnacht). We would also like to \nacknowledge Betsy Costenbader, Kavita Nanda, and Global CIMC Task Force members for their feedback \non the draft data extraction forms, and Kavita Nanda for clinical advice. We would also like to thank \nValeria Bahamondes for her assistance in the full text review and data extraction of the two Portuguese \npapers that were included. The authors also appreciate Laneta Dorflinger and Kate McQueen for their \nreview of and feedback on drafts of this manuscript. \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n31 \n \n \nSUPPORTING INFORMATION \nS1 Table. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist \nS2 Appendix. Details on Review Methods. \nS3 Table. All articles included after title/abstract screening and full text review. \nS4 Table. Characteristics of sub-scales, items, and general instruments. \nREFERENCES \n1.  Radačić I, Bennoune K, Pūras D, Boly Barry K, Heller L, Šimonovic D, et al. Women’s menstrual \nhealth should no longer be a taboo. 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Development and \nPsychometric Validation of a Screening Questionnaire to Detect Excessive Menstrual Blood Loss \nThat Interferes in Quality of Life: The SAMANTA Questionnaire. J Womens Health (Larchmt). \n2020;29: 1021–1031. doi:10.1089/jwh.2018.7446 \n199.  Perelló-Capo J, Rius-Tarruella J, Andeyro-García M, Calaf-Alsina J. Sensitivity to Change of the \nSAMANTA Questionnaire, a Heavy Menstrual Bleeding Diagnostic Tool, after 1 Year of Hormonal \nTreatment. J Womens Health. 2023;32. doi:10.1089/jwh.2022.0155 \n200.  Pérez-Campos E, Dueñas JL, de la Viuda E, Gómez MÁ, Lertxundi R, Sánchez-Borrego R, et al. \nDevelopment and validation of the SEC-QOL questionnaire in women using contraceptive \nmethods. Value Health. 2011;14: 892–9. doi:10.1016/j.jval.2011.08.1729 \n201.  Perelló J, Pujol P, Pérez M, Artés M, Calaf J. Heavy Menstrual Bleeding-Visual Analog Scale, an \nEasy-to-Use Tool for Excessive Menstrual Blood Loss That Interferes with Quality-of-Life \n . 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Vitonis AF, Vincent K, Rahmioglu N, Fassbender A, Buck Louis GM, Hummelshoj L, et al. World \nEndometriosis Research Foundation Endometriosis Phenome and biobanking harmonization \nproject: II. Clinical and covariate phenotype data collection in endometriosis research. Fertil \nSteril. 2014;102: 1223–1232. doi:10.1016/j.fertnstert.2014.07.1244 \n  \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n48 \n \n \nADDITIONAL TABLE \nTable 4: List of full instruments and characteristics \nFull Name of instrument Available Languages \nAvailable \nElectronically? * \nWho fills out \ninstrument? \nBLEEDING BLOOD UTERINE \nPAIN \nPERCEP-\nTIONS \nQuality \nScore \nUtility \nScore \nEvidence \nScore** References Duration Volume Frequency Regularity Color Consistency Smell \nInstruments that Measure Bleeding and/or Blood (n=13)                \nAlkaline Hematin Assay NA No Patient/Participant  X        2.00 2.00 8† [76] \nDaily Diary, Menstrual Cycle Length English Yes Patient/Participant X X        1.25 2.00 14† [77] \nDaily Diary, Menopause Classification‡ English, Cantonese, Japanese, Spanish No Patient/Participant X  X       2.00 2.50‡ 16 [78] \nMansfield-Voda-Jorgensen Menstrual Bleeding \nScale \nEnglish No Patient/Participant  X        2.00 3.00 9 [79] \nMenstrual Blood Loss Score Questionnaire Spanish No Patient/Participant X X        2.25 2.67 17 [80] \nMenstrual Collection English, Icelandic No Patient/Participant  X        2.67 1.53 9 [81–85] \nMenstrual Record and Recall English No Patient/Participant  X        2.00 2.67 14 [86] \nPictorial Blood Loss Assessment Charts & \nMenstrual Pictograms†† ‡ \nDutch, English, German, Norwegian No Patient/Participant  X    X    2.67†† 2.00‡ 84 [87–97] \nProspective Self Report, Menstrual Regularity Not Reported No Patient/Participant X         2.00 2.33 13† [98] \nQuantitative Model for Menstrual Blood Loss†† Multi-Site Study No Researcher  X        2.83†† 1.67 16 [62] \nRetrospective Self-Report, Last Menstrual Period English No Patient/Participant   X       1.67 3.00 14 [99] \nRetrospective Self Report, Menstrual Length \n(Small & Jukic) \nEnglish No Patient/Participant   X       2.33 2.83 30 [100,101] \nRetrospective Self Report, Menstrual Length \n(Bachand) \nEnglish No Patient/Participant   X       2.00 3.00 13 [102] \nInstruments that Measure Uterine Pain (n=4)                \nNumeric Rating Scale English, Portuguese, Spanish Yes Patient/Participant        X  2.60 2.00 30 [103,104] \nPain Drawing  Portuguese Yes Patient/Participant        X  2.67 3.00 17 [105] \nRetrospective Self Report, Menstrual Discomfort English No Patient/Participant        X  2.50 3.00 14 [106] \nSqueezing Pain Bulb English Yes Patient/Participant        X  1.50 1.00 8 [107] \nVisual Analogue Scales: Pain Multi-Site Study No Patient/Participant        X  2.00 2.00 20 [108,109] \nInstruments that Measure Perceptions (n=19)                \nAdolescent Dysmenorrhic Self-Care Scale ‡ Cantonese, Mandarin No Patient/Participant         X 3.00 2.88‡ 45 [110,111] \nDysmenorrhea Symptom Interference Scale English Yes Patient/Participant         X 2.80 3.00 20 [112] \nEndometriosis Health Profile-30†† \nChinese, Danish, Dutch, English, French, Italian, Portuguese, \nPortuguese (Brazilian), Malay, Norwegian, Swedish, Turkish, \nPersian \nYes (French) Patient/Participant         X 3.00†† 2.52 332 \n[60,61,113–\n130] \nEndometriosis Health Profile-5 Croatian, English, French Yes (Croatian) Patient/Participant         X 3.00 3.00 53 [131–134] \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n49 \n \n \nFull Name of instrument Available Languages \nAvailable \nElectronically? * \nWho fills out \ninstrument? \nBLEEDING BLOOD UTERINE \nPAIN \nPERCEP-\nTIONS \nQuality \nScore \nUtility \nScore \nEvidence \nScore** References Duration Volume Frequency Regularity Color Consistency Smell \nEndometriosis Impact Scale‡ English, French, German Yes Patient/Participant         X 3.00 2.75‡ 17 [135] \nEndometriosis Treatment Satisfaction \nQuestionnaire \nEnglish No Patient/Participant         X 2.75 3.00 20 [136] \nFunctional and Emotional Measure of \nDysmenorrhea \nChinese No Patient/Participant         X 2.25 0.00 9 [137] \nInjustice Experience Questionnaire-Chronic and \nthe Contribution of Perceived Injustice \nJapanese Yes Patient/Participant         X 2.00 2.67 14 [138] \n(Menorrhagia) Multi-Attribute Utility Score English No Patient/Participant         X 2.40 2.50 25 [139–141] \nMenstrual Attitudes Questionnaire Bengali, English, Greek, Nepali, Turkish No Patient/Participant         X 2.25 1.73 29 [142–146] \nMenstrual Health Seeking Behaviors \nQuestionnaire \nPersian No Patient/Participant         X 2.75 2.00 15 [147] \nMenstrual Hygiene Management Scale Hindi Yes Patient/Participant         X 2.33 3.00 10 [148] \nMenstrual Joy Questionnaire English No Patient/Participant         X 1.50 3.00 9 [149] \nMenstrual Practices Questionnaire English No Patient/Participant         X 2.60 2.50 18 [150] \nMenstrual Self-Evaluation Scale English No Patient/Participant         X 2.00 2.50 11 [151] \nMenstruation-Related, Activity Restriction \nQuestionnaire \nEnglish, Hindi No Patient/Participant         X 2.00 2.67 14 [152] \nMilitary Women's Attitudes Toward Menstrual \nSuppression Scale  \nEnglish No Patient/Participant         X 2.50 1.67 15 [153] \nUterine Fibroid Symptom and Quality of Life \nQuestionnaire‡ \nChinese, Dutch, English, Portuguese, Spanish Yes (Dutch) \nPatient/Participant; \nResearcher \n        X 2.80 2.67‡ 164 [154–162] \nWorking Stressors and Coping Strategies \nAssociated with Menstrual Symptoms among \nNurses \nNot Reported Yes Patient/Participant         X 2.75 1.67 16 [163] \nWorld Health Organization Disability Assessment \nSchedule 2.0 \nPortuguese Yes Patient/Participant         X 2.00 0.00 4 [164] \nInstruments that Measure Multiple CIMCs (n=28)                \nAberdeen Menorrhagia Severity Scale‡ Arabic, English No Patient/Participant X X X X  X  X X 2.50 2.88‡ 19 [165,166] \nBleeding and Pelvic Discomfort Scale English No Patient/Participant        X X 2.80 3.00 23 [167] \nelectronic Personal Assessment Questionnaire - \nMenstrual, Pain, and Hormonal \nEnglish Yes Patient/Participant X X  X  X  X X 2.00 2.00 14 [168] \nDysmenorrhea Daily Diary†† English Yes Patient/Participant X X      X X 2.67†† 2.17 34 [169,170] \nEndometriosis Daily Diary English, Cantonese, Japanese, Spanish Yes Patient/Participant        X X 1.83 2.00 17 [171] \nEndometriosis Daily Pain Impact Diary English Yes Patient/Participant        X X 2.80 2.33 21 [172] \nEndometriosis Impact Questionnaire‡ English Yes Patient/Participant  X  X    X X 2.75 2.50‡ 21 [173] \nEndometriosis Pain and Bleeding Diary English Yes Patient/Participant  X      X X 2.75 2.00 17 [174] \nEndometriosis Pain Daily Diary English, Japanese Yes Patient/Participant        X X 3.00 2.33 13 [175] \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint \n\n \n50 \n \n \nFull Name of instrument Available Languages \nAvailable \nElectronically? * \nWho fills out \ninstrument? \nBLEEDING BLOOD UTERINE \nPAIN \nPERCEP-\nTIONS \nQuality \nScore \nUtility \nScore \nEvidence \nScore** References Duration Volume Frequency Regularity Color Consistency Smell \nEndometriosis Reproductive Health \nQuestionnaire \nPersian No Patient/Participant  X      X X 2.25 2.50 14 [176] \nEndometriosis Self-Assessment Tool Korean No Patient/Participant  X    X  X X 3.00 2.67 20 [177] \nEndometriosis Symptom Diary‡ English, French, German Yes Patient/Participant  X      X X 3.00 2.25‡ 15 [135] \nENDOPAIN-4D‡ French, Persian No Patient/Participant        X X 2.80 2.29‡ 52 [178–180] \nEndowheel‡ English No Patient/Participant  X  X    X X 3.00 2.50‡ 16 [181] \nFibroid Symptom Diary English Yes Patient/Participant  X    X  X X 2.50 2.00 11 [182] \nMeasure Compilation (Olliges) German Yes Patient/Participant  X      X X 2.00 1.67 11 [183] \nMenorrhagia Impact Questionnaire English No Patient/Participant  X       X 3.00 2.50 20 [184] \nMenstrual Bleeding Questionnaire†† English, Portuguese, Thai No Patient/Participant X X  X  X  X X 3.00†† 2.33 60 [185–188] \nMenstrual Distress Questionnaire (Moos) English No Patient/Participant        X X 2.25 2.33 16 [189,190] \nMenstrual Distress Questionnaire (Vannuccini) English, Italian Yes Patient/Participant        X X 2.75 2.50 33 [191,192] \nMenstrual Health Instrument Korean No Patient/Participant   X X    X X 2.60 2.50 18 [193] \nMenstrual Insecurity Tool Oriya (Odia) No Patient/Participant    X   X X X 2.75 3.00 17 [194] \nNew Zealand Survey of Adolescent Girls' \nMenstruation \nEnglish Yes Patient/Participant X X X X  X  X X 2.33 1.33 11 [195] \nPeriod ImPact and Pain Assessment English No Patient/Participant        X X 2.00 3.00 12 [196] \nPERIOD-QOL English Yes Patient/Participant X X      X X 2.75 2.00 15 [197] \nSAMANTA Questionnaire Spanish No Patient/Participant X X       X 3.00 3.00 35 [198,199] \nSpanish Society of Contraception Quality-of-Life Spanish No Patient/Participant        X X 3.00 3.00 24 [200] \nVisual Analogue Scales: Bleeding Spanish No Patient/Participant  X       X 2.00 2.50 9 [201] \nWorking Ability, Location, Intensity, Days of Pain, \nDysmenorrhea Score \nSpanish No Patient/Participant        X X 1.75 2.00 13 [202] \nWorld Endometriosis Research Foundation \nEndometriosis Phenome and Biobanking \nHarmonisation Project Standard Questionnaire‡ \nEnglish, French No Patient/Participant X X X X    X X 2.25 1.50‡ 21 [203,204] \nTotal Number of full Instruments  68  Total/Average 12 26 8 9 0 7 1 32 50 2.44 2.33 25.59  \n* According to publications, \"Yes\" indicates either fully or partly electronic \n** Sum of quality and utility scores for studies conducted after 2006. \n† Evidence score based on only one study before 2006 \n†† Score provided for every aspect of quality (no scores of 0 in any category) \n‡ Score provided for every aspect of utility (no scores of 0 in any category) \n . CC-BY-ND 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 12, 2024. ; https://doi.org/10.1101/2024.04.04.24305348doi: medRxiv preprint","source_license":"CC0","license_restricted":false}