Final Research Report

PATIENT-CENTERED OUTCOMES RESEARCH INSTITUTE FINAL RESEARCH REPORT

Creating Recommendations on Types of Data to Present in Patient-Reported Outcome Measure Development Studies

Joel J. Gagnier, PhD, ND, MSc1; Wieneke Mokkink, PhD2; Caroline B. Terwee, PhD2

AFFILIATIONS: 1Department of Orthopaedic Surgery, University of Michigan, Ann Arbor; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor 2Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands

Institution Receiving Award: University of Michigan Original Project Title: Development of Reporting Guidelines for Psychometric Research on Patient- Reported Outcome Measures PCORI ID: ME-1606-35556 HSRProj ID: HSRP20181636

______To cite this document, please use: Gagnier JJ, Mokkink W, Terwee CB. (2021). Creating Recommendations on Types of Data to Present in Patient-Reported Outcome Measure Development Studies. Patient-Centered Outcomes Research Institute (PCORI). https://doi.org/10.25302/03.2021.ME.160635556

TABLE OF CONTENTS

ABSTRACT ...... 4 BACKGROUND ...... 5 Criteria for Reporting Patient-Reported Outcomes ...... 5 Purpose of This Study ...... 8 PATIENT AND STAKEHOLDER ENGAGEMENT ...... 10 METHODS ...... 11 Phase 1: Conducting an Extensive Literature Review ...... 11 Phase 2: Preparing for the Delphi Process ...... 13 Phase 3. Conducting the Delphi Rounds ...... 14 Phase 4: Developing Recommendations and Guidance Documents ...... 15 Departure From Original Protocol ...... 16 RESULTS ...... 17 Phase 1: Conducting the Literature Review ...... 17 Table 1. Common Items Relevant to Any Investigation of MPs Relating to 8 Report Sections ...... 20 Table 2. Specific Items for Each of the 9 MPs Relating to 8 Report Sections ...... 24 Phases 2 and 3: Preparing for and Conducting the Delphi Process ...... 30 Table 3. Characteristics of Panelists Completing Delphi Round 1 ...... 31 Delphi Round 1 Results ...... 32 Figure 1. Results of Delphi Round 1 Voting: Items in the “Common” Set ...... 33 Figure 2. Results of Delphi Round 1 Voting: Items in the “Specific Measurement Properties” Set ...... 34 Table 4. Summary of Voting for Common Set of Items for All Studies of PROM MPs ...... 35 Table 5. Delphi Round 1 Results of Specific Items for All PROM MPs ...... 37 Delphi Round 2 Results ...... 38 Table 6. Results of Delphi Round 2 Voting ...... 38 Figure 3. Results of Delphi Round 2 Voting ...... 40 Delphi Round 3 Results ...... 42 Table 7. Results of Delphi Round 3 Voting About Agreement to Remove the First 6 Items and Keep the Seventh Item ...... 43 Figure 4. Results of Delphi Round 3 Voting ...... 44

2 Final Items for Reporting Guidelines ...... 45 Table 8. Final List for the Common Set of Items for Reporting of Studies of PROMs ...... 46 Table 9. Final List for the Specific Set of Items, Relating to MPs, for Reporting of Studies of PROMs ...... 50 Phase 4: Developing Guidance Documents ...... 54 DISCUSSION ...... 55 Limitations and Strengths of the Project ...... 55 Future Research ...... 58 CONCLUSIONS ...... 59 REFERENCES ...... 60 RELATED PUBLICATIONS ...... 63 Submitted for Publication ...... 63 Published ...... 63 ACKNOWLEDGMENTS ...... 64 APPENDICES ...... 65 Appendix A. Search Strategies ...... 65 Appendix B. Reporting Item Survey Round 1 ...... 67 Appendix C. Nonduplicate Search Results ...... 107 Appendix D. Comments From Round 1 ...... 373

ABSTRACT

Background: Patient-reported outcome measures (PROMs) are key tools when performing clinical research or monitoring patient progress. One barrier to interpreting individual studies on the measurement properties (MPs) of PROMs is the frequent underreporting of important information. Although a checklist for investigating the methodological quality of studies on MPs of health status measurement instruments has been developed, guidelines for reporting these studies in the peer-reviewed literature do not exist.

Objective: To develop a set of consensus and empirically based reporting recommendations for primary studies of the MPs of PROMs.

Methods: This study included 4 phases: (1) conducting an extensive literature review of methods for performing or reporting studies testing MPs of PROMs; (2) preparing for a Delphi process to develop a consensus about reporting requirements by identifying experts to participate; (3) conducting the Delphi rounds of voting on the item lists developed in phase 1; and (4) developing recommendation and guidance documents.

Results: The literature review resulted in our including 92 reporting items in the Delphi survey. A total of 83 individuals (from 12 countries) agreed to participate in the Delphi survey, with 47, 30, and 25 responding in rounds 1, 2, and 3, respectively. After 3 rounds, we achieved consensus on a set of 71 items separated into a set of 35 “common” items (relevant to all studies on MPs) and 36 “specific” items (exclusively relevant to 1 of the 9 MPs: (1) reliability, (2) measurement error, (3) internal consistency, (4) content validity, (5) face validity, (6) construct validity [including structural validity, hypothesis testing, and cross-cultural validity], (7) criterion validity, (8) responsiveness, and (9) interpretability). We created a manuscript for publication of the protocol, a PCORI final report, and similar to the final report, but much shorter, a manuscript also meant for publication of this work.

Conclusions: Consensus was achieved on 2 nonduplicative sets of items, 71 in total, for inclusion in a reporting guideline for studies on MPs of PROMs. These items will guide researchers on the necessary information to include in their reports of investigations of MPs of PROMs. This guidance will likely improve the completeness of reporting of these important studies.

Limitations: One potential drawback is the possibility of having missed important and salient resources in our search of the literature, which may have restricted our initial items list. In addition, the individuals who volunteered to be part of our Delphi panel could have been a selective group with specific unique characteristics that could be different in a repeated study. Consequently, their views on reporting specific MPs may have made them more likely to volunteer and respond, biasing the voting and the resultant final item list. Finally, another potential drawback is the use of the Delphi process instead of a face-to-face consensus process.

BACKGROUND

Patient-reported outcome measures (PROMs) are key tools when performing clinical research or monitoring patient progress.1-7 Many PROMs are available across all areas of health care. In particular, PROMs are often developed because experts identify drawbacks in existing PROMs through testing of their measurement properties (MPs).

One barrier to interpreting individual studies on the MPs of PROMs is the frequent underreporting of important information.8-13 Put differently, studies examining MPs are often missing key information that may allow a reader (eg, clinician, scientist, funder) of these studies to determine which methods were used, what the results are, and ultimately what the research means for the evidence of a particular measure. Poor reporting of scientific research undermines the applicability of and contributions to scientific knowledge.13,14

As a result, when based on outcomes research using poor PROMs, patient monitoring and quality of care are compromised, causing unnecessary health care expenditures, increased patient suffering, and potentially inappropriate funding allocation. Currently, no reporting guidelines for psychometric research on PROMs exist. Here, we will explain several sets of criteria that are related to our proposed work but that are not themselves reporting standards.

Criteria for Reporting Patient-Reported Outcomes This section will focus on contrasting our study intent with prior work in the area. The work by Calvert et al1 appearing in 2013 is an extension of the CONSORT statement23 and is meant to guide the reporting of patient-reported outcomes within 2-arm, prospective clinical trials. This Calvert guideline is not meant or intended to address studies that assess a psychometric property of a PROM. The Calvert 2013 CONSORT Patient-Reported Outcomes (CONSORT PRO) extension “aims to improve the reporting of PROMs in trials to facilitate the use of results to inform clinical practice and health policy.” This reporting guidance does not address studies that investigate psychometric properties; it addresses patient-reported outcomes used within clinical trials. We intend to create guidance for primary studies of MPs of PROMs.

Next, the 2013 work by Reeve et al15 outlines the International Society of Quality of Life (ISOQOL) minimum standards for PROMs used in patient-centered outcomes research (PCOR) and comparative effectiveness research (CER). These standards are for choosing PROMs for research. As these authors say: “This initiative’s goal was to identify minimum standards for the design and selection of a PROM for use in PCOR and CER.” That is, these standards help researchers design, develop, and choose PROMs for use in PCOR and CER. These standards provide no guidance on studies that examine a psychometric property of a PROM. Thus, although important, these criteria do not address the reporting of studies that test the psychometric property of a PROM.

The COnsensus based Standards for the selection of health status Measurement INstruments (COSMIN) criteria10,14 are not reporting standards for studies that investigate the psychometric properties of PROMs; rather, they are methodological quality criteria, or risk of bias criteria, for studies that assess a PROM’s psychometric properties. Thus, these are not reporting guidelines, but guidelines for conducting methodologic studies of the psychometric properties of PROMs.

By analogy, the Jadad methodological quality criteria or the Cochrane risk of bias criteria are meant to assess the methodology of a randomized clinical study and contain a small number (5-8) of criteria, specifically directed at the methods of randomized trials (such as randomization methods, blinding, and allocation concealment). The intent of risk of bias criteria is to determine or estimate the degree of bias in the results that stem from methodological flaws.

In contrast, the CONSORT statement,23 which outlines reporting recommendations for 2-arm parallel randomized controlled trials (RCTs), is meant to direct those reporting, for publication in peer-reviewed journals, all sections of their randomized clinical study. These include many components of a typical clinical research article: title, abstract, introduction, methods, results, discussion, and conclusions. The statement specifies the content such that readers may have all the required information available to judge what the study objective was,

what the methods were, and what the results and conclusions are. In this way, readers can determine whether and how they might apply the findings to decision-making.

Complete reporting allows clinicians, administrators, or researchers to apply findings. Thus, the 2 separate concepts here are risk of bias vs completeness of reporting: put differently, methodological quality vs reporting quality.

The COSMIN criteria are analogous to the Cochrane risk of bias criteria, but no CONSORT-like analogous set of reporting recommendations exists for studies that investigate the psychometric properties of a PROM. The COSMIN criteria are not reporting recommendations, as noted in the COSMIN publication: The “aim of the COSMIN study was to develop a consensus-based checklist to evaluate the methodological quality of studies on measurement properties.”10

Additionally, 2 other sets of recommendations should be noted.16,17 One set is the Core Outcome Measures in Effectiveness Trials (COMET) recommendation for selecting outcome measurement instruments for outcomes included in a core outcome set (COS). A COS has been defined as an agreed upon minimum set of outcomes that should be used and reported in clinical trials of a specific disease or trial population.16 Therefore, although this guidance is very important for COS development, it does not address the completeness of reporting or provide reporting guidance for studies that investigate the psychometric properties of PROMs.

Last, we focus on a set of recommendations called the Guidelines for Reporting Reliability and Agreement Studies (GRRAS).17 Of all the above-mentioned criteria, these are the most relevant to our current proposal. The GRRAS “objective was to develop guidelines for reporting reliability and agreement studies. The specific aim was to establish items that should be addressed when reliability and agreement studies are reported.”

This concept of reliability is one of the 9 psychometric properties we aimed to address in creating our reporting guidelines. Therefore, although the GRRAS reporting guideline has addressed reliability, another 8 properties must be elaborated; reporting guidelines are needed for these as well. That is, a complete and comprehensive guidance document for all 9

psychometric properties is required to help those planning, implementing, and reporting as well as reading studies that investigate and report the psychometric properties of PROMs. We propose to develop reporting guidance for all 9 properties. Therefore, GRRAS, albeit important and relevant, does not fill the gap that we will address.

A related tool worth mentioning here is the Evaluating the Measurement of Patient- Reported Outcomes (EMPRO)18 assessment tool. EMPRO was developed to assess the quality of MPs of PROMs. The goal was to help investigators choose between alternative PROMs. This tool, developed using consensus methods, used as a starting point a set of criteria developed by the Medical Outcomes Trust.19 EMPRO has 39 items related to 8 PROM attributes: (1) conceptual and measurement model, (2) reliability, (3) validity, (4) responsiveness, (5) interpretability, (6) burden, (7) alternative modes of administration, and (8) cross-cultural and linguistic adaptations. EMPRO does not focus at all on the requirements for reporting investigations of MPs of PROMs. Instead, it is used to assess existing evidence for particular PROMs.

Therefore, these various tools and criteria do not fill the gap we are proposing to address in this project. We will create detailed and specific reporting guidelines for all sections of a manuscript. These explicitly include 8 components: (1) title, (2) abstract, (3) introduction, (4) objectives, (5) methods, (6) results, (7) discussion, and (8) conclusions for all 9 psychometric properties of concern. These properties are (1) reliability, (2) measurement error, (3) internal consistency, (4) content validity, (5) face validity, (6) construct validity (including structural validity, hypothesis testing, and cross-cultural validity), (7) criterion validity, (8) responsiveness, and (9) interpretability, which can be investigated and reported within studies exploring the psychometric properties of PROMs.

Purpose of This Study The purpose of this project was to create detailed and specific reporting guidelines for all typical sections of a manuscript about PROMs—title, abstract, introduction, objectives, methods, results, discussion, and conclusions. Furthermore, we sought to make these reporting recommendations specific to 9 psychometric properties of usual interest: (1) reliability, (2)

measurement error, (3) internal consistency, (4) content validity, (5) face validity, (6) construct validity (including structural validity, hypothesis testing, and cross-cultural validity), (7) criterion validity, (8) responsiveness, and (9) interpretability.

These all can be investigated and reported within studies exploring the MPs of PROMs. Our recommendations and specific guidance for reporting these studies will improve the methods that investigators use to conduct and report on their studies. This in turn will allow increased applicability and reproducibility of the findings.

PATIENT AND STAKEHOLDER ENGAGEMENT

For this specific study, the project team decided, given the highly technical nature of the subject matter, that the primary stakeholders were experts in MPs of PROMs. Therefore, we performed a Delphi process inviting and including a wide range of expert stakeholders from a dozen countries.

METHODS

This project on PROMs consisted of 4 phases. Phase 1 entailed an extensive review of the literature on recommendations for reporting psychometric studies of PROMs and the collation of a list of items to be used in the Delphi process of phase 3. Phase 2 involved identifying and inviting experts to participate in the work. In phase 3, we conducted a 3-round Delphi process to create a set of consensus-based reporting guidelines. In phase 4, we completed 1 manuscript reporting our protocol and another on our findings and resulting recommendations. This study had IRB approval from the University of Michigan (#HUM00101151).

Phase 1: Conducting an Extensive Literature Review First, the investigators included known key publications from which to start extracting reporting items and to design the literature search. These included the following, some of which were described in more detail in the Background section:

1. The CONSORT-PRO, which is an extension of the CONSORT statement and is meant to guide the reporting of patient-reported outcomes within 2-arm, prospective clinical trials1

2. The ISOQOL minimum standards document,15 which outlines how to choose PROMs used in PCOR and CER

3. The COSMIN criteria,14 which are methodological quality criteria for assessing a PROM’s MPs

4. The Core Outcome Measurement Instrument Selection (COMIS) guideline on how to select outcome measurement instruments for inclusion in a COS16

5. The GRRAS,17 which are guidelines for reporting reliability and agreement studies

6. Good practices for real-world data studies of treatment and/or comparative effectiveness: recommendations from the Joint International Society for Pharmacoepidemiology–International Society for Pharmacoeconomics and Outcomes Research (ISPE-ISPOR) Special Task Force on Real-World Evidence in Health Care Decision Making2

7. US Food and Drug Administration. Guidance for Industry. Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims. US Department of Health and Human Services. Published December 2009. Accessed January 2017. https://www.fda.gov/regulatory-information/search-fda-guidance- documents/patient-reported-outcome-measures-use-medical-product-development- support-labeling-claims

Second, as a part of the development of the COSMIN checklist, we had performed an extensive literature review of methods of psychometric studies in the fall of 2005 (results available on request). Then, aided by an information scientist, we updated this work focusing more specifically on reporting through a modification and updating of the search terms.

We searched the following databases up to the end of 2017: MEDLINE, EMBASE, CINAHL, Health Technology Assessment, PsycInfo, the Cochrane Library, Dissertation Abstracts, Scopus, and other relevant sources. Appendix A presents the search terms used in each of these databases as well as search time frame and other pertinent information.

We also reviewed reference lists from review papers, relevant textbooks, and conference proceedings. Finally, we contacted scientific groups and content experts and asked them to provide any relevant materials.

Third, we included both published and unpublished information sources that specifically gave guidance on the methods for reporting some component of any study that examined the MPs of PROMs. We then used these guidance recommendations for methods to construct individual items for the Delphi process (as described below). We also included information sources that provided empirical evidence that not performing specific methods or not reporting specific information biases the results of such studies.

Fourth, 2 individuals working together thematically grouped the retrieved resources, suggestions, or techniques (eg, statistical vs qualitative recommendations) into a set of discrete items. The project team reviewed these items and discussed them at length on several occasions until we achieved consensus on their content. This consensus occurred through discussion and debate among the 3 members of the project team. We also described the

reporting recommendations and highlighted any empirical support cited for each recommendation.

Finally, we summarized the found recommendations into a list of 150 starting items. We used these initial items in the Delphi process described below for phases 2 and 3 to develop the final reporting guidelines for psychometric properties of PROMs.

We did not plan to assess the risk of bias of the found resources.

Phase 2: Preparing for the Delphi Process In phase 2, we identified and invited the participation of an international group of experts for our Delphi process. We identified these individuals by reviewing relevant publications and conference proceedings and by contacting content experts for suggestions. Based on the findings and methods in other research,14 we determined that we would need a minimum of 30 participants in each of the 3 rounds of the Delphi activity.

We contacted individuals fulfilling any 1 of the following 5 inclusion criteria:

1. Publication of method or reporting guidelines for studies of the MPs of PROMs

2. Publication of a manual, handbook, or other book on psychometrics, clinimetrics, or measurement

3. Publication of a systematic review of methods for measurement studies of PROMs or a systematic review of the reporting of measurement studies of PROMs

4. Publication of other reporting guidelines for clinical research

5. An individual considered by the investigative team to be an international expert on PROMs

We kept the final list of selected panelists confidential; it was known only to the project team. We identified 140 potential participants; we invited all by email to participate in the project.

Phase 3. Conducting the Delphi Rounds For phase 3, we conducted a total of 3 Delphi rounds. We invited all 140 panel members to participate in each round unless they explicitly indicated at some point during the study that they did not wish to receive further invitations. Using the 92 items found in phase 1, the project team designed the complete Delphi questionnaire (see Appendix B), sent invitations and reminders to panel members, analyzed responses, and formulated feedback reports. The Results section documents the results for all 3 Delphi round materials.

We pilot tested the initial Delphi questionnaire with 3 individuals to gain feedback on design and revised the questionnaire accordingly. Specifically, we revised the wording of several items to make them clearer and corrected several spelling mistakes. We used the online software SurveyMonkey for the Delphi surveys. We made each round of the questionnaire available to participants for approximately 4 weeks and sent a reminder each week after the initial invitation.

Delphi Rounds For Delphi round 1, we first gave the 140 participants information about the objectives of the study and the Delphi process. We then asked them to respond to several demographic questions, including educational and professional backgrounds, and their experience with psychometric or measurement property research relevant to PROMs. We did not ask for participant names, keeping their participation anonymous.

We then asked all participants to rate their agreement with the 92 items identified in phase 1 above. Participants were specifically asked to indicate, for each item, the importance of being included in a reporting guideline for studies investigating MPs of PROMs. Panelists were asked to rate their agreement for the inclusion of specific items on a 5-point scale: 1 = strongly disagree, 2 = disagree, 3 = no opinion, 4 = agree, and 5 = strongly agree.14

We included options for participants to comment on each item and encouraged them to provide a rationale for their ratings and to suggest modifications of definitions or wording of the items. Furthermore, we asked participants to indicate whether they saw any overlap

between items, to suggest whether some items might be aggregated, and to suggest potential items not included in the list.

We then calculated frequencies for the responses for the importance of each item across all participants. The investigative team reviewed the responses to open questions to evaluate whether respondents presented significant arguments against the overall trend in frequencies. We considered consensus for including an item when at least 70% of the participating panelists indicated a 4 (agree) or 5 (strongly agree). If <70% agreed on any specific items, or if items were modified (wording or description), then we listed that item again in the next Delphi round with summarized arguments for or against inclusion.

Through discussion, the project team considered suggestions for the aggregation of certain items and the strength of the arguments.

We organized all survey findings for each round into a feedback report, which we emailed to all Delphi participants together with a link to the next round of the Delphi process. Participants were asked to comment on the feedback report to inform us of any overwhelming and convincing arguments against any of the item changes.

We then modified the Delphi survey items for each successive round to reflect these findings. We asked participants to vote only on items with substantial wording or content changes and on those for which consensus was not achieved in the previous Delphi round.

We completed 3 rounds using these methods and concluded that we had achieved consensus at that point.

Phase 4: Developing Recommendations and Guidance Documents During phase 4, we finalized the set reporting items that included all items that the Delphi panelists had agreed on for inclusion for each item. From this we drafted a manuscript suitable for publication and the PCORI final report. We previously developed a proposal suitable for publication that is currently under review.

Departure From Original Protocol We had originally planned to carry out a Delphi process followed by an in-person focus group. We decided, however, given the many items found, that the Delphi process would be much more extensive than originally anticipated. Therefore, we conducted only the 3 rounds of the Delphi process with experts. We included only experts in our Delphi process because the nature of the information to be reviewed and voted on was highly technical.

In our protocol, we stated a 67% cutoff for achieving consensus for items in the Delphi process. In our implementation of this research, we raised this to a 70% cutoff to reflect more current recommendations by the COMET group.16 The COMET group is an international organization whose aim is to broaden methodology in COS development and thus has created guidance for methods, such as Delphi consensus cutoffs. We followed these new method guidelines.

In the protocol, we planned to complete an explanation and elaboration document meant for publication. Instead, and in line with the COSMIN group procedures, we created a manual that will be freely available on the COSMIN website. This manual will be completed following the publication of the main manuscript for this project.

RESULTS

We report our findings on items to include in guidance about reporting on studies of MPs of PROMs. The findings are given by phase; phases 2 and 3 for the Delphi process are combined.

Phase 1: Conducting the Literature Review Phase 1 consisted of 4 main steps. The first was to examine the key resources cited in the Methods section and extract candidate items for reporting guidelines for PROM studies from them. Second, we conducted the literature search and extracted additional candidate items from the articles reviewed in full. The third task was to organize the eventual universe of items into 2 sets (1 with items that could be used by any study investigating MPs, and 1 with items pertaining to a specific measurement property). The final step entailed preparing materials for use in the Delphi process.

Key Resources Known to Investigators For phase 1, we collected an initial set of key resources known to the investigators. These included the following key resources:

1. The CONSORT-PRO, which is an extension of the CONSORT statement and is meant to guide the reporting of patient-reported outcomes within 2-arm, prospective clinical trials1

2. The ISOQOL minimum standards document,15 which outlines how to choose PROMs used in PCOR and CER

3. The COSMIN criteria,14 which are methodological quality criteria for assessing a PROM’s MPs

4. The COMIS guideline on how to select outcome measurement instruments for inclusion in a COS16

5. The GRRAS,17 which are guidelines for reporting reliability and agreement studies

6. Good practices for real-world data studies of treatment and/or comparative effectiveness: recommendations from the ISPE-ISPOR Special Task Force on Real-World Evidence in Health Care Decision Making2

From these resources, a single member of the research team extracted a total of 148 items. A second researcher cross-checked these. We also reviewed a large selection of relevant textbooks.

Yields of the Literature Searches Using the peer-reviewed publications in the peer-reviewed papers in our key resources as sentinel articles, our library and information scientist developed a search strategy and implemented it across several databases (see Appendix A). Our initial searches of the electronic databases yielded 2976 nonduplicate peer-reviewed citations; based on a review of titles and abstracts, we excluded 1318 nonrelevant citations that did not offer reporting guidance or were gray literature. The remaining 1658 citations had potentially important recommendations and were reviewed in full for relevant items (see Appendix C). These papers included reviews, expert opinions, statistical methods, clinical research, and evidence-based guidelines.

From these additional publications we extracted a total of 150 items; 2 did not overlap with the 148 items extracted from the key resources described above. These items were given titles and a description (ie, an operational definition) as suggested by the resources that recommended the item. The investigative team discussed all 150 items and descriptions in detail.

We refined the list to 127 unique items and again into 92 nonoverlapping items relevant to 2 main topics. One is the various parts of a manuscript: title, abstract, introduction, methods,

results, discussion, conclusions, and other information. The other concerns MPs of interest— namely, (1) reliability, (2) measurement error, (3) internal consistency, (4) content validity, (5) face validity, (6) construct validity (including structural validity, hypothesis testing, and cross- cultural validity), (7) criterion validity, (8) responsiveness, and (9) interpretability. Refining this list occurred over a period of 8 months; it yielded a very detailed and specific list of items for our follow-up Delphi process.

We then separated the 92-item list into 2 sets of items. The first set comprised 39 common items, relevant to any investigation of MPs for PROMs (see Table 1). The second set included 53 items, each one specific for 1 of the 9 MPs of PROMs (see Table 2).

After additional discussion among the investigators, we determined that cross-cultural validity and interpretability should be eliminated from the Delphi process because these are, strictly speaking, not MPs; they require much more elaboration in separate work. We reasoned that it was not within the scope of this research to develop a comprehensive set of items for these 2 properties; this could be done in follow-up work. Therefore, eliminating these 14 items left us with a total of 39 specific items for each of the MPs of PROMs, or a total of 78 items. The first round of the Delphi survey is reported in Appendix B, which contains all items in Tables 1 and 2.

Table 1. Common Items Relevant to Any Investigation of MPs Relating to 8 Report Sections

Item No. Item name Item description (1) Report section: Title T1 PROM Name the PROM instrument(s) (and version if relevant) being studied. T2 MP Describe which MPs (eg, reliability, internal consistency) are being studied, or more generally, which MP/psychometric properties/scale properties (or other synonym) are being studied (eg, if there are many properties being investigated.) T3 Study design Describe the type of study being used to test the properties (eg, cohort, cross-sectional, case series, randomized) and other details of the study design if relevant (intervention, comparators, outcome). T4 Study sample Provide a general description of relevant study sample characteristics (eg, condition of interest, language) and any intervention or exposure used (eg, treatments). (2) Report section: Abstract A1 PROM Name the PROM instrument(s) (and version, if relevant) being studied (ie, the MOS SF-36 or SF- 12) or if it concerns an item bank (eg, PROMIS instruments), as well as the type of instrument (eg, a questionnaire, a performance-based measure). A2 MP Describe which MPs (eg, reliability, internal consistency) are being studied, or more generally, which MP/psychometric properties/scale properties (or other synonym) are being studied (eg, if there are many properties being investigated). A3 Design Describe the type of study being used to test the properties (eg, cohort, cross-sectional, case series, randomized) and other details of the study design if relevant (intervention/exposure, comparators, outcome other than PROMs). A4 Sample Provide inclusion/exclusion criteria and a general description of relevant study sample characteristics (eg, condition of interest, geographic location, language, other relevant demographic and baseline characteristics). A5 Methods Briefly describe the methods for investigating each MP, including statistical analyses. A6 Results Provide the main results for all MPs investigated, reporting statistics for each result with measures of precision where appropriate.

Item No. Item name Item description A7 Discussion/Conclusions Briefly describe the results in the context of existing evidence, main strengths and drawbacks, and the need for future research on the PROMs investigated. (3) Report section: Introduction I1 Name and description of the Specify the name, type, language, and version (if the PROM is adapted) of the PROM being PROM of interest investigated and how it was developed: This may include the number of items, scoring algorithm, relevant instructions (eg, time period), and number or type of response categories. Describe the construct the PROM aims to measure and the structure of the PROM (eg, the number of factors and their constructs). State whether the PROM is based on a reflective or formative model. Note: This information may also appear in the methods section in greater detail. I2 Target population Describe the specific target population for whom the PROM was designed and to what it applied. The authors need to provide the appropriate and necessary characteristics of this population. I3 Citation for the original The citation for the original development papers should be provided, as well as other highly development of the PROM relevant citations relative to the specific PROM under investigation. I4 State of knowledge and A description of the current scientific knowledge (what is known) regarding the MPs for the rationale PROM under investigation should be provided. The authors should provide a literature review of all existing evidence of the version (eg, language, short form) of the PROM and explain why the new study is necessary and important. The rationale for the current proposed study should be given. I5 Definitions Specialized terms should be defined or explained. I6 Objectives and hypotheses State the specific objectives of the research and hypotheses related to the specific PROM under investigation. (4) Report section: General methods (relevant to the reporting of investigation of any measurement property of a PROM) GM1 Study design State the key elements of the study design. GM2 Participants State how the participants were chosen relative to the specific PROM under investigation (eg, if it is a PROM for a specific condition, the eligibility and selection criteria should reflect this).

Item No. Item name Item description GM3 PROM administration Provide an explicit description of how the PROMs were administered (eg, in what setting), including data collection devices/system (eg, paper based, electronic administration), to patients. GM4 Data collection procedures Provide information about other data collection, exposure methods (eg, allocation to interventions), and time points/follow-up points. GM5 Power/sample size Provide a power calculation or sample size for all MP analyses. Alternatively, if a rule of thumb calculation is used, state it and the source/citation. GM6 Statistical analyses Statistical analyses and tests corresponding to all hypotheses for all MPs should be reported. Where appropriate, a cutoff for statistical significance should be reported (eg, P < .05). A description of all statistics to be used to estimate the magnitude and direction of effect should also be reported, together with measures of variability or precision. Report the statistical package used. GM7 Missing data State approaches or plan for dealing with missing data. GM8 Post hoc analysis The report should specify analyses that used data after the data collection period concluded (ie, if the analyses were post hoc) and describe the rationale for any post hoc analyses. GM9 RCT If the authors defined the study as an RCT, the report should include all information suggested in the CONSORT statement. GM10 Observational study If the authors defined the study as an observational study, the report should include all information suggested in the STROBE guidelines. GM11 Other study design Use additional appropriate reporting guidelines for the specific study design used. See www.equator-network.org for specific reporting guidance for other study designs. (5) Report section: General results (relevant to the reporting of investigation of any measurement property of a PROM) GR1 Missing data The amount and reasons for missing data should be explained for all analyses for all PROMs and relevant groups. GR2 Participant/patient The study patients’ characteristics should be described, including baseline PROM scores. characteristics GR3 Sample size If 1 study contained >1 analysis with different sample sizes used, the authors need to report the sample size for each analysis.

Item No. Item name Item description (6) Report section: Discussion D1 MP evidence Per MP, you should compare the result with the criteria for good MPs and determine if the specific quality aspect (ie, MP) is sufficient or not. D2 Practical relevance The authors need to discuss the practical relevance, which depends on the purpose of the research, and the consequences of PROM scores. D3 Strengths and limitations Strengths and limitations of the study should be discussed. For example, discuss if there were any significant potential biases in the study that could have affected the findings for each hypothesis. D4 Generalizability Generalizability issues related to the PROM results should be discussed. For example, discuss if the results could be generalized to other populations given the sample studied. D5 Instrument changes Discuss the need for modifications to the existing PROM or new PROM development. If you conclude that one of the MPs is insufficient, you could suggest some modification, or if it is really poor, you could suggest stopping use of the PROM. D6 Future research Report specifically the type of research needed to answer new questions arising from these findings for the particular MP(s) and PROM(s) investigated. (7) Report section: Conclusions C1 Conclusions State the overall conclusions for each MP and PROM investigated. (8) Report section: Other information O1 Conflict of interest State any relevant conflict of interest related to the PROM under investigation (eg, an author being the PROM developer; funding body). Abbreviations: MPs, measurement properties; MOS SF-12, Medical Outcomes Survey–Short Form 12; MOS SF-36, Medical Outcomes Survey–Short Form 36; PROM, patient-reported outcome measure; PROMIS, Patient-Reported Outcomes Measurement Information System; RCT, randomized controlled trial; STROBE, STandards for the Reporting of OBservational studies in Epidemiology.

Table 2. Specific Items for Each of the 9 MPs Relating to 8 Report Sections

Item No. Item name Item description (1) Report section: Reliability R1 PROM administrations The process of administering the measurements to the patients should be described, including who administered it (ie, did the patient complete it or was there a proxy); when, how, and any time intervals between administrations should be reported. This should include time interval between repeated measurements, justification that the patient was stable (eg, single-item perceived change scale), the general conditions underlying the measurement situation (eg, setting, location, other instruments or measurements accompanying the repeated PROM), and instructions given. Also, if relevant, the independence of the administrations should be described. If the PROM was delivered by interview, describe the interviewers for each administration. R2 Statistical analyses All statistical analyses specific to the reliability assessments should be described and their use justified (eg, the ICC model or type of κ coefficient used). Also, describe the weighting scheme used for ordinal scores (eg, linear or quadratic weights). R3 Methods to improve Report any methods used to improve reliability, such as restriction, training and reliability standardization, and averaging of repeated measurements. (2) Report section: Measurement error ME1 PROM administration The process of administrating the measurements to the patients should be described, including who administered it (ie, did the patient complete it or was there a proxy); when, how, and any time intervals between administrations should be reported. This should include time interval between repeated measurements (eg, whether the patient was stable or not), the general conditions underlying the measurement situation, the test type (eg, a self-administered questionnaire, an interview-based PROM), the setting in which the instrument was administered (eg, at the hospital or at home), and the instructions given for completing it. If relevant, other instruments or measurements accompanying the repeated PROM should be described. Also, if relevant, the independence of the administrations should be described.

Item No. Item name Item description ME2 Statistical analyses All statistical analyses specific to measurement error assessments should be described and their use justified. For example, for continuous scores, report the SEM. Specify the exact model used to calculate the SEM (ie, SEM consistency or SEM agreement), SDC, or LoA. For dichotomous/nominal/ordinal scores, report the percentage of (positive and negative) agreement. (3) Report section: Internal consistency IC1 Unit of measurement Report internal consistency statistic for each unidimensional scale or subscale. Report assumptions associated with unidimensionality. IC2 Continuous scores Report Cronbach α or ω statistics. Report other statistics calculated for internal consistency of continuous scores. IC3 Dichotomous scores Report Cronbach α or Kuder-Richardson coefficient. Report other statistics calculated for internal consistency of dichotomous scores. IC4 IRT-based scores Report the SE of the θ or reliability coefficient of estimated latent trait value (index of [subject or item] separation). (4) Report section: Content validity CV1 Relevance Report if and how patients and/or professionals were asked whether each item is relevant for their experience with the condition. CV2 Comprehensiveness Report if and how patients and/or professionals were asked whether all key concepts are included. CV3 Comprehensibility Report if and how the comprehensibility of the PROM instructions, items, response options, and recall period was assessed. CV4 Relevance results Report if all items were considered relevant for the construct, population, and context of use of interest by patients and/or professionals. CV5 Response options and recall Report whether the response options and recall period were considered appropriate by period patients and/or professionals. CV6 Comprehensiveness results Report whether patients and/or professionals considered all key concepts to be included in the PROM.

Item No. Item name Item description CV7 Comprehensibility results Report whether patients understood the PROM instructions, items, and response options as intended. CV8 Qualitative methods and Use the COREQ reporting guidelines for reporting the methods and results of qualitative results studies. See www.equator-network.org (5) Report section: Construct validity (a) General construct validity ConV1 Comparator instruments The comparator instruments should be appropriately described in terms of the construct they intend to measure. Report the MPs of the comparator instruments and related citations or data. ConV2 Comparator groups Report characteristics of groups being compared. Include sample sizes in each group. ConV3 Hypotheses Report all hypotheses, including the direction and magnitude of the expected results of relationships between the PROM of interest and another measurement instrument, or of differences in scores of the PROM between groups. ConV4 Statistical analyses Report all statistical methods used to test each hypothesis. ConV5 Result Report which specific results are in accordance with all hypotheses. (b) Structural validity SV1 Conceptual framework Report the conceptual framework on which the PROM relied. Structural validity is only relevant for instruments with items based on a reflective model. These kinds of items are called effect indicators, and they should be fully and completely reported together with descriptions and definitions. SV2 Factor analyses: CTT PROMs Report details of the methods for any exploratory or confirmatory factor analyses. The factor structure of tested models should be described. Methods for checking of the assumptions should be described, type of factor analysis, the method of estimation, goodness-of-fit statistics and cutoff points for good model fit, including factor loadings of best-fitting model. For confirmatory factor analysis, state the hypotheses regarding the factor structure being tested. Report any theory on which such hypotheses are based. State the rationale for any exploratory factor analyses (eg, no clear a priori hypotheses).

Item No. Item name Item description SV3 IRT analyses Type of IRT/Rasch model should be reported. Also report the method of estimation, methods and results for checking of the assumptions (unidimensionality [see factor analyses], local dependency [eg, residual correlations], monotonicity [eg, Mokken scaling]), goodness-of-fit statistics, and cutoff points for goodness of item/model fit, and all item parameters. (c) Hypothesis testing HT1 Hypothesis The hypotheses about change scores should be reported. HT2 Direction of effect State the expected direction of correlation or mean differences between subgroups of the change (positive or negative) scores for the PROM. HT3 Magnitude of effect State expected absolute or relative magnitude of correlations or mean differences of the change scores for the PROM. HT4 Comparator instruments The construct measured on the comparator instruments should be described. If comparators are not used, describe the “known groups” and any differences between the “known” groups, or describe the intervention/exposure. HT5 Comparator instrument MPs All known MPs of the comparator instruments should be described or references should be provided to studies in which these properties are described. (d) Translation and cross-cultural validity CCV1 Translation Describe the processes of translating the PROM (eg, who performed the translation, from which language, to which language, and whether back translation was performed). Describe the results of the translation including items and scoring and any errors in back translation. Describe pilot testing procedures and results. CCV2 Sample characteristics Describe the sample characteristics and how the samples were similar or not for relevant characteristics. CCV3 Cultural adaptation Describe all the processes of culturally adapting the PROM. Describe the results of the adaptation including items and scoring. Describe pilot testing procedures and results. CCV4 Statistical analyses Report regression models, factor analytic model details or differential item functioning analyses, and results.

Item No. Item name Item description CCV5 Measurement invariance Describe item functioning at scale or item level in the comparison populations. Describe the methods and results of any confirmatory factor analyses or regression analyses completed. For IRT, report item characteristic curves of the 2 versions (ie, item functioning). (6) Report section: Criterion validity CriV1 Criterion Report the details of the criterion used and why it was used. Justification of the gold standard must be reported. Also, describe (if applicable) how the criterion was dichotomized or classified and how it was administered (eg, if independent from the PROM). CriV2 Continuous scores Report correlations or the AUROC. If the scores on the gold standard comparator are dichotomous, report the AUROC. CriV3 Categorical scores Described how (and why) the PROM was dichotomized. Report sensitivity and specificity statistics. (7) Report section: Responsiveness Resp1 Comparison instruments Report each comparison instrument (ie, the constructs measured, their MPs) and its structure. Resp2 Measurement procedures Report if measurements were applied to the same samples using the same instruments. Describe the measurement procedures, including time intervals. Resp3 Interim period The interim period between time points should be described, especially if there were relevant events that occurred that could influence the scores (eg, intervention given). Resp4 Intervention/exposure Describe the intervention given or exposure if relevant. Resp5 Patients changed Report the proportion of patients that improved or deteriorated (and any related anchor used) on the construct measured on all PROMs. Report any changes in the measured PROM in the target population for the research application relative to the predefined hypotheses. Resp6 Subgroups For known-group type of design, describe important characteristics (eg, demographics, disease characteristics) of the subgroups. (8) Report section: Interpretability Int1 Important changes Report the ability of the questionnaire to detect clinically important changes over time. Report statistics such as MIC/MID, SDC, and LoA.

Item No. Item name Item description Int2 Anchor-based change For MIC/MID, report what the change on the PROM was anchored to (ie, what was the external criterion). If using a GRC anchor, report the details of the global rating values used and what was considered minimal or not. If using another PROM or measurement instrument as an anchor, describe the details of this measure, including its MPs and what component of that PROM was used as the anchor. Int3 Distribution-based change If using distribution-based methods to arrive at the MIC/MID, describe which measure of distribution was used (eg, 1/3 SD) and the methods used to arrive at it. Int4 ROC curve If using ROC curve method to establish the MID, state the dichotomization methods and which groups were included in the analyses. Report sensitivity and specificity statistics. Int5 Distribution of scores Report the distributions of scores (eg, SD, IQRs, CIs) on the PROM. For IRT, report the position of items on ranges of the underlying trait. Int6 Floor and ceiling effects Report any analyses and results related to investigating floor and ceiling effects. Int7 Norm comparisons Report any comparisons to established norms for PROM items and scores. Int8 SDC Report all methods for calculating the SDC (also termed minimal detectable change, minimal real change, true change). State what the SDC is in relation to (eg, pretreatment score vs posttreatment score). Report other relevant statistics, such as LoA or reliable change index. Int9 Response shift Report methods (qualitative or quantitative) to investigate response shift and related results. Report how any response shift was controlled for or accounted for in other analyses (eg, adjusting for response shift). Abbreviations: AUROC, area under the receiver operating characteristic curve; COREQ, Consolidated Criteria for Reporting Qualitative Research; CTT, classical test theory; GRC, global rating of change; ICC, intraclass correlation coefficient; IQRs, interquartile ranges; IRT, item response theory; LoA, limits of agreement; MIC, minimally important change; MID, minimally important difference; MPs, measurement properties; PROM, patient-reported outcome measure; ROC, receiver operating characteristic; SDC, smallest detectable change; SEM, standard error of measurement.

Phases 2 and 3: Preparing for and Conducting the Delphi Process

Numbers of Invitees and Participants For phase 2, we initially emailed 140 potential participants to gauge their willingness to participate. Of these, 84 individuals responded affirmatively. We then sent these 84 individuals the Delphi survey for round 1 of the Delphi process. We received responses from 47 participants (response rate, 56%). Because of self-reported personal reasons, 1 panel member quit our study at this point. Therefore, for rounds 2 and 3, we invited 83 individuals to participate.

In round 2, we received responses from 30 of the 83 participants (response rate, 36%); in round 3, 25 of the 83 participants finished the survey (response rate, 30%). We did not determine how many participants completed multiple Delphi rounds owing to the anonymity of the survey.

Demographic Characteristics of Participants (Round 1) We collected demographic characteristics only from the 47 participants in the first round so as not to burden our panelists with questions that they may have previously answered (Table 3). The median time spent working in their field was 18 years. They were a very international group, from a total of 12 countries; of these, 43% were from the United States. The majority (85%) were health care researchers across several fields: 53% were primarily in the measurement field; 57% were involved with developing a reporting guideline; and 47% had been involved in developing methods or reporting guidelines for psychometric properties of PROMs.

Table 3. Characteristics of Panelists Completing Delphi Round 1

Characteristic Values N 47 Years of work Median (range) 18 (3-40)

Country of work, No. (%) Germany 2 (4) Switzerland 3(6) Sweden 3 (6) United Kingdom 6 (13) The Netherlands 8 (17) Canada 8 (17) US 20 (43) Other (Austria, Belgium, Denmark, France, Singapore) 5 (11)

Job function, No. (%) Health care provider 8 (17) Health care researcher 40 (85) Other 9 (19)

Field of work, No. (%) Epidemiology 6 (13) Statistics/biostatistics 9 (19) Clinical epidemiology 10 (21) Psychometrics 15 (32) Measurement 25 (53) Other 20 (43)

Research experience, No. (%) Conducted a systematic review of methods for PROM psychometric properties 14 (30) Developed method or reporting guidelines for psychometric properties of PROMs 22 (47) Developed of a reporting guideline of any kind 27 (57) Abbreviation: PROM, patient-reported outcome measure.

Delphi Round 1 Results To determine which items reached some threshold of acceptance by the Delphi participants, we set a consensus cutoff of 70%, shown as a black vertical line in Figures 1 and 2. In total, 33 items (Figure 1) in the common item set (set 1) and 35 items (Figure 2) in the specific item set met our consensus cutoff of 70%. Figures 1 and 2 list each item, and they show the proportion of participants voting yes to keep the item (in blue), voting no to exclude it (in orange), or unsure (in gray). The items are listed in descending order of the proportion of yes votes, “yes” indicating agreement with being a key component of reporting, “no” indicating the item as not being key for reporting, and “unsure” as being uncertain whether the item is key for reporting.

For accepting items for the common set, the 47 panelists achieved high consensus on most of the items in the following sections: title, abstract, results, discussion, conclusions, and other information (conflict of interest) (Table 4). Of the specific item names, 6 did not reach the 70% level of consensus for inclusion.

Figure 1. Results of Delphi Round 1 Voting: Items in the “Common” Set

Abbreviation: PROM, patient-reported outcome measure.

Figure 2. Results of Delphi Round 1 Voting: Items in the “Specific Measurement Properties” Set

Abbreviation: PROM, patient-reported outcome measure.

Table 4. Summary of Voting for Common Set of Items for All Studies of PROM MPs

Report section Item name Yes, % No, % Unsure, % Title PROM 93.48 4.35 2.17 MP 73.91 19.57 6.52 Study designa 58.70 28.26 13.04 Study sample 89.13 8.70 2.17 Abstract PROM 100.00 0.00 0.00 MP 97.83 2.17 0.00 Design 95.65 2.17 2.17 Sample 93.48 6.52 0.00 Methods 84.78 6.52 8.70 Results 93.48 2.17 4.35 Discussion/Conclusions 80.43 8.70 10.87 Introduction Name and description of the PROM of 74.42 16.28 9.30 interest Target population 83.72 11.63 4.65 Citation for the original development of the 90.70 6.98 2.33 PROM State of knowledge and rationale 88.37 2.33 9.30 Definitionsa 67.44 20.93 11.63 Objectives and hypotheses 90.70 4.65 4.65 General methods Study design 95.35 4.65 0.00 Participants 97.67 0.00 2.33 PROM administration 95.35 2.33 2.33 Data collection procedures 90.70 4.65 4.65 Power/sample size calculation 76.74 6.98 16.28 Statistical analyses 93.02 2.33 4.65 Missing data 90.70 4.65 4.65 Post hoc analysisa 69.77 9.30 20.93 RCTa 55.81 23.26 20.93 Observational studya 53.49 20.93 25.58 Other study designa 51.16 16.28 32.56 General results Missing data 85.37 9.76 4.88 Participant/patient characteristics 100.00 0.00 0.00 Sample size 92.68 0.00 7.32

Report section Item name Yes, % No, % Unsure, % Discussion MP evidence 85.37 4.88 9.76 Practical relevance 92.68 0.00 7.32 Strengths and limitations 100.00 0.00 0.00 Generalizability 82.93 9.76 7.32 Instrument changes 87.80 4.88 7.32 Future research 73.17 9.76 17.07 Conclusions Conclusions 97.56 0.00 2.44 Other information Conflict of interest 95.12 2.44 2.44 Abbreviations: MPs, measurement properties; PROM, patient-reported outcome measure; RCT, randomized controlled trial. aItems achieved <70% agreement to retain.

As shown in Table 5, participants in round 1 also agreed to include all the items in the following 5 sections from the specific set: (1) reliability, (2) measurement error, (3) construct validity, (4) criterion validity, and (5) responsiveness. Three items fell below the 70% threshold for acceptance.

In all, 9 items (across Tables 4 and 5) did not reach consensus for inclusion (70% agreement); no item met consensus for exclusion (70% agreement). For those items that did not reach consensus for inclusion, the indication of uncertainty (ie, unsure) was high.

Participants offered many suggestions on rewording or moving items (see Appendix D for all Delphi participant comments). The investigators reviewed these 9 items and the associated comments in depth. We reworded these 9 items as suggested by the Delphi participants.

In light of the extensive comments, we also revised 1 additional item even though it reached our predetermined 70% “yes” cutoff, albeit only by 0.01%. This item in the hypothesis- testing section was titled, “Comparator instrument MPs.” We revised these 10 items and brought them forward for reconsideration in round 2.

Table 5. Delphi Round 1 Results of Specific Items for All PROM MPs

Report section Item name Yes, % No, % Unsure, % Reliability PROM administrations 97.56 2.44 0.00 Statistical analyses 90.24 2.44 7.32 Methods to improve reliability 82.93 7.32 9.76 Measurement PROM administrations 90.24 0.00 9.76 error Statistical analyses 87.80 0.00 12.20 Internal Unit of measurement 78.05 4.88 17.07 consistency Continuous scores 82.93 0.00 17.07 Dichotomous scores 73.17 2.44 24.39 IRT-based scoresa 63.41 4.88 31.71 Content validity Relevance 95.12 2.44 2.44 Comprehensiveness 97.56 0.00 2.44 Comprehensibility 92.68 2.44 4.88 Relevance results 87.80 2.44 9.76 Response options and recall period 87.80 2.44 9.76 Comprehensiveness results 82.93 7.32 9.76 Comprehensibility results 82.93 4.88 12.20 Qualitative methods and resultsa 53.66 9.76 36.59 Structural validity Conceptual frameworka 68.29 4.88 26.83 Factor analyses: CTT PROMs 82.93 4.88 12.20 IRT analyses 75.61 2.44 21.95 Construct validity Comparator instruments 87.80 7.32 4.88 Comparator groups 90.24 2.44 7.32 Hypotheses 85.37 0.00 14.63 Statistical analyses 95.12 0.00 4.88 Result 97.56 0.00 2.44 Criterion validity Criterion 90.00 2.50 7.50 Continuous scores 75.00 5.00 20.00 Categorical scores 77.50 2.50 20.00

Report section Item name Yes, % No, % Unsure, % Responsiveness Comparison Instruments 77.50 7.50 15.00 Measurement procedures 95.00 0.00 5.00 Interim period 90.00 0.00 10.00 Intervention/exposure 97.50 0.00 2.50 Patients changed 90.00 2.50 7.50 Subgroups 90.00 5.00 5.00 Hypothesis testing Hypothesis 87.50 0.00 12.50 Direction of effect 90.00 2.50 7.50 Magnitude of effect 82.50 2.50 15.00 Comparator instruments 87.50 0.00 12.50 Comparator instrument MPsb 70.01 10.00 19.99 Abbreviations: CTT, classical test theory; IRT, item response theory; ; MPs, measurement properties; PROM, patient-reported outcome measure. aItems achieved agreement <70%. bItems that had extensive comments or were very near to the 70% cutoff (within 1%).

Delphi Round 2 Results We invited the original 83 participants from round 1 to complete round 2; of these, 30 completed the survey. For this second round, we gave the 83 invited Delphi panelists the voting results for each item from round 1. We asked them to vote and comment on just the 9 items that did not reach consensus and the rewording of the single additional item, for a total of 10 items.

The voting results on these 10 items are reported in Table 6 and Figure 3. The Delphi participants in round 2 reached consensus in the second round of voting for including the following items: “definitions” in the introduction, “post hoc analysis” in the methods, and “comparator instrument MPs” in the hypothesis-testing section.

Table 6. Results of Delphi Round 2 Voting

Report section Item name Yes, % No, % Unsure, % Title Study designa 55.17 44.83 0.00

Introduction Definitions 75.86 10.34 13.79

General methods Post hoc analysis 75.86 6.90 17.24 RCTa 55.17 31.03 13.79 Observational studya 55.17 31.03 13.79 Other study designa 55.17 27.59 17.24 Internal consistency IRT-based scoresa 50.00 10.71 39.29 Content validity Qualitative methods and resultsa 60.71 25.00 14.29 Structural validity Conceptual frameworka 67.86 10.71 21.43 Hypothesis testing Comparator instrument MPs 85.71 14.29 0.00 Abbreviations: IRT, item response theory; MPs, measurement properties; RCT, randomized controlled trial. aItems achieved <70% agreement in round 2 of the Delphi process.

Figure 3. Results of Delphi Round 2 Voting

Abbreviation: IRT, item response theory.

Of the 7 items that did not reach the threshold for inclusion, 6 had many comments. The investigative team discussed them at length and decided to remove these 6 items as formal items for round 3 of the Delphi process because they did not reach consensus in both rounds. However, we made sure to notify the panelists in the third round about the reasons for having removed them.

For the item “Conceptual framework” in the “Structural validity” specific section, we noted that we were removing this item because of several comments that it was already recommended in the introduction section.

Furthermore, we noted that several of the items we removed that did not reach consensus referred to specific study design reporting recommendations and were covered by other well-known reporting guidelines, such as the item on qualitative methods (eg, Consolidated Criteria for Reporting Qualitative Research [COREQ] recommendations),21 observational studies (eg, STandards for the Reporting of OBservational studies in Epidemiology [STROBE] recommendations),22 and randomized studies (eg, the CONSORT recommendations).23 For these items, we noted our intent to stress the importance of these details and to refer to specific reporting recommendations in the associated user manual. We also noted that we removed the item study design from the “title” section of the common reporting recommendations because it was already covered in the abstract items.

For the final item concerning scores based on item response theory (IRT) in the internal consistency-specific section, 50% of the participants in round 2 of the Delphi process had voted to include it, 11% said to omit it, and 39% said they were uncertain. Based on the comments, many respondents were not familiar with this topic area (eg, “not my expertise”) or found it difficult to understand or to distinguish from other items.

Therefore, for Delphi round 3, we provided some additional explanation of this IRT item and asked the panelists to reconsider whether we should remove this item and instead mention or discuss it only in the user manual. This was the description included in materials sent to the panelists:

This item specifically refers to internal consistency; item fit and model fit are covered under the item SV3 Structural Validity–Item Response Theory (IRT) analyses, which states:

“Type of IRT/Rasch model should be reported. Also report the method of estimation, methods and results for checking of the assumptions (eg, unidimensionality [see factor analysis], local dependency [eg, residual correlations], monotonicity [eg, Mokken scaling]), goodness-of-fit statistics, and cutoff points for goodness of item/model fit, and all item parameters.”

We will recommend in the reporting guidelines that assumptions need to be met for IRT/Rasch models.

Delphi Round 3 Results We presented a total of 7 items in this third Delphi round – namely, those that did not reach consensus in round 2 as well as comments associated with these items from previous rounds. The focus for the first 6 items was on asking panelists whether they agreed these items should be removed. The 25 respondents in this round agreed to remove these 6 items (see Table 7 and Figure 4).

For the final item about IRT-based scores, the Delphi panelists did not come to a consensus on whether to remove the item. Of the 25 respondents, 68% indicated that we should remove this item; 24% were still uncertain. The investigators discussed and debated this item and decided, based on the near-consensus vote to exclude it, as well as the voting results of rounds 1 and 2, that we would exclude it but would discuss it in depth in the user manual.

Table 7. Results of Delphi Round 3 Voting About Agreement to Remove the First 6 Items and Keep the Seventh Item

Report section Item name Yes, % No, % Unsure, % Title 1. Study design 92.31 3.85 3.85 General methods 2. RCT 96.15 3.85 0.00 3. Observational study 96.15 3.85 0.00 4. Other study design 96.15 3.85 0.00 Content validity 5. Qualitative methods and results 84.62 3.85 11.54 Structural validity 6. Conceptual framework 80.77 15.38 3.85 Internal consistency 7. IRT-based scoresa 68.00 8.00 24.00 Abbreviations: IRT, item response theory; RCT, randomized controlled trial. aItem achieved <70% agreement.

Figure 4. Results of Delphi Round 3 Voting

Abbreviation: IRT, item response theory.

Final Items for Reporting Guidelines We started with 78 potential items. We ended up with 2 sets of items to include in reporting guidelines related to studies of psychometric properties of PROMs. In the final list for the first set, we retained 35 common reporting items (Table 8) relevant to any study of the MPs of PROMs. These reporting items are organized by section of the manuscript. Similarly, we retained 36 specific reporting recommendations across 9 MPs (Table 9). Therefore, our final item list included 71 items. Although the number of final items was similar to the starting number, the titles and descriptions of most had changed during the Delphi process. The wording of all item names and descriptions in Tables 8 and 9 are the final versions of these items.

Table 8. Final List for the Common Set of Items for Reporting of Studies of PROMs

Item No. Item name Item description (1) Title T1 PROM Name the PROM instruments (and versions if relevant) being studied. T2 MP Describe which MPs (eg, reliability, internal consistency) are being studied, or more generally, which MP/psychometric properties/scale properties (or other synonym) are being studied (eg, if there are many properties being investigated). T3 Study sample Provide a general description of relevant study sample characteristics (eg, condition of interest, language) and any intervention or exposure (eg, treatments). (2) Abstract A1 PROM Name the PROM instruments (and versions, if relevant) being studied (ie, the SF-36 or SF-12) or if they concern an item bank (eg, PROMIS instruments), as well as the type of instrument (eg, a questionnaire, a performance-based measure). A2 MP Describe which MPs (eg, reliability, internal consistency) are being studied, or more generally, which MP/psychometric properties/scale properties (or other synonym) are being studied (eg, if there are many properties being investigated). A3 Design Describe the type of study being used to test the properties (eg, cohort, cross-sectional, case series, randomized) and other details of the study design, if relevant (intervention/exposure, comparators, outcome other than PROMs). A4 Sample Provide inclusion/exclusion criteria and a general description of relevant study sample characteristics (eg, condition of interest, geographic location, language, other relevant demographic and baseline characteristics). A5 Methods Briefly describe the methods for investigating each MP, including statistical analyses. A6 Results Provide the main results for all MPs investigated, reporting statistics for each result with measures of precision where appropriate.

Item No. Item name Item description A7 Discussion/Conclusions Briefly describe the results in the context of existing evidence, main strengths and drawbacks, and the need for future research on the PROMs investigated. (3) Introduction I2 Target population Describe the specific target population for whom the PROM was designed for and applied to. The authors need to provide the appropriate and necessary characteristics of this population. I3 Citation for the original The citation for the original development papers should be provided, as well as other highly development of the relevant citations relative to the specific PROM under investigation. PROM I4 State of knowledge and Describe the current scientific knowledge (what is known) regarding the MPs for the PROM rationale under investigation. Provide a literature review of all existing evidence of the version (eg, language, short form) of the PROM and explain why the new study is necessary and important. The rationale for the current proposed study should be given. I5 Definitions Specialized terms should be defined or explained. I6 Objectives and State the specific objectives of the research and hypotheses related to the specific PROM under hypotheses investigation. (4) Methods GMa1 Study design State the key elements of the study design. GM2 Participants State how the participants were chosen relative to the specific PROM under investigation (eg, if it was a PROM for a specific condition, the eligibility and selection criteria should reflect this). GM3 PROM administration Provide an explicit description of how the PROMs were administered (eg, in what setting), including data collection devices/system (eg, paper based, electronic administration/ePRO) to patients. GM4 Data collection Provide information about other data collection, exposure methods (eg, allocation to procedures interventions), and time points/follow-up points.

Item No. Item name Item description GM5 Power/sample size Provide a power calculation or sample size for all MP analyses. Alternatively, if a rule of thumb calculation is used, state it and the source/citation. GM6 Statistical analyses Statistical analyses and tests corresponding to all hypotheses for all MPs should be reported. Where appropriate, a cutoff for statistical significance should be reported (eg, P < .05). A description of all statistics to be used to estimate the magnitude and direction of effect should also be reported, together with measures of variability or precision. Report the statistical package used. GM7 Missing data State approaches or plan for dealing with missing data. GM8 Post hoc analysis The report should specify analyses that used data after the data collection period concluded (ie, if the analyses were post hoc) and describe the rationale for any post hoc analyses. (5) Results GR1 Missing data The amount of and reasons for missing data should be explained for all analyses for all PROMs and relevant groups. GR2 Participant/patient The study patients’ characteristics should be described, including baseline PROM scores. characteristics GR3 Sample size If 1 study contained >1 analysis with different sample sizes used, the authors need to report the sample size for each analysis. (6) Discussion D1 MP evidence Per MP, the authors should compare the result with the criteria for good MPs and determine whether the specific quality aspect (ie, MP) is sufficient or not. D2 Practical relevance The authors should discuss the practical relevance, which depends on the purpose of the research, and the consequences of PROM scores. D3 Strengths and limitations Strengths and limitations of the study should be discussed. For example, discuss whether there were any significant potential biases in the study that could have affected the findings for each hypothesis.

Item No. Item name Item description D4 Generalizability Generalizability issues related to the PROM results should be discussed. For example, discuss whether the results could be generalized to other populations given the sample studied. D5 Instrument changes Discuss the need for modifications to the existing PROM or new PROM development. If you conclude that one of the MPs is insufficient, you could suggest some modification, or if it is really poor, you could suggest stopping use of the PROM. D6 Future research Report specifically the type of research needed to answer new questions arising from these findings for the particular MP and PROM investigated. (7) Conclusions C1 Conclusions State the overall conclusions for each MP and PROM investigated. (8) Other information O1 Conflict of interest State any relevant conflict of interest related to the PROM under investigation (eg, an author being the PROM developer, funding body). Abbreviations: ePRO, electronic patient-reported outcome; GM, general methods; MOS SF-12, Medical Outcomes Survey–Short Form 12; MOS SF-36, Medical Outcomes Survey–Short Form 36; MP, measurement property; PROM, patient-reported outcome measure; PROMIS, Patient-Reported Outcomes Measurement Information System. aGM for “general methods” signifies that each of these items refers to any paper on MPs to distinguish these items from those in Table 7, which refer to specific MPs.

Table 9. Final List for the Specific Set of Items, Relating to MPs, for Reporting of Studies of PROMs

Item No. Item name Item description (1) Reliability R1 PROM administrations The process of administering the measurements to the patients should be described, including who administered it (ie, did the patient complete it or was there a proxy); when, how, and any time intervals between administrations should be reported. This should include time interval between repeated measurements, justification that the patient was stable (eg, single-item perceived change scale), the general conditions underlying the measurement situation (eg, setting, location, other instruments or measurements accompanying the repeated PROM), and instructions given. Also, if relevant, the independence of the administrations should be described. If the PROM was delivered by interview, describe the interviewers for each administration. R2 Statistical analyses All statistical analyses specific to the reliability assessments should be described and their use justified (eg, the ICC model or type of κ coefficient used). Also, describe the weighting scheme used for ordinal scores (eg, linear or quadratic weights). R3 Methods to improve Report any methods used to improve reliability, such as restriction, training and standardization, reliability and averaging of repeated measurements. (2) Measurement error ME1 PROM administration Report the total number of measurements made and if the measurements were applied to the same samples using the same PROM. The process of administering the measurements to the patients should be described, including who administered them (ie, did the patient complete them or was there a proxy); when, how, and any time intervals between administrations should be reported. This should include time interval between repeated measurements (eg, whether the patient was stable or not), the general conditions underlying the measurement situation, the test type (eg a self-administered questionnaire, an interview-based PROM), the setting in which the instrument was administered (eg, at the hospital or at home), and the instructions given for completing it. If relevant, other instruments or measurements accompanying the repeated PROM should be described. Also, if relevant, the independence of the administrations should be described. ME2 Statistical analyses All statistical analyses specific to measurement error assessments should be described and their

Item No. Item name Item description use justified. Specifically, for continuous scores, report the SEM (specify the exact model used to calculate the SEM [ie, SEM consistency or SEM agreement]), SDC, or LoA. For dichotomous/nominal/ordinal scores, report the percentage of (positive and negative) agreement. (3) Internal consistency IC1 Unit of measurement Report internal consistency statistic for each unidimensional scale or subscale. Report assumptions associated with unidimensionality. IC2 Continuous scores Report Cronbach α or ω statistics. Report other statistics calculated for internal consistency of continuous scores. IC3 Dichotomous scores Report Cronbach α or Kuder-Richardson coefficient. Report other statistics calculated for internal consistency of dichotomous scores. (4) Content validity CV1 Relevance Report if and how patients and/or professionals were asked whether each item is relevant for their experience with the condition. CV2 Comprehensiveness Report if and how patients and/or professionals were asked whether all key concepts are included. CV3 Comprehensibility Report if and how the comprehensibility of the PROM instructions, items, response options, and recall period was assessed. CV4 Relevance results Report if all items were considered relevant for the construct, population, and context of use of interest by patients and/or professionals. CV5 Response options and Report whether the response options and recall period were considered appropriate by patients recall period and/or professionals. CV6 Comprehensiveness Report whether patients and/or professionals considered all key concepts to be included in the results PROM. CV7 Comprehensibility results Report whether patients understood the PROM instructions, items, and response options as intended. (5) Structural validity SV1 Factor analyses: CTT Report details of the methods for any exploratory or confirmatory factor analyses. The factor

Item No. Item name Item description PROMs structure of tested models should be described. Methods for checking of the assumptions should be described, type of factor analysis, the method of estimation, goodness-of-fit statistics, and cutoff points for good model fit, including factor loadings of best-fitting model. For confirmatory factor analysis, state the hypotheses regarding the factor structure being tested. Report any theory on which such hypotheses are based. State the rationale for any exploratory factor analyses (eg, no clear a priori hypotheses). SV2 IRT analyses Type of IRT/Rasch model should be reported. Also, report the method of estimation, methods and results for checking of the assumptions (unidimensionality [see factor analyses], local dependency [eg, residual correlations], monotonicity [eg, Mokken scaling]), goodness-of-fit statistics, cutoff points for goodness of item/model fit, and all item parameters. (6) Construct validity ConV1 Comparator instruments The comparator instruments should be appropriately described in terms of the construct they intend to measure. Report the MPs of the comparator instruments and related citations or data. ConV2 Comparator groups Report characteristics of groups being compared. Include sample sizes in each group. ConV3 Hypotheses Report all hypotheses, including the direction and magnitude of the expected results of relationships between the PROM of interest and another measurement instrument, or of differences in scores of the PROM between groups. ConV4 Statistical analyses Report all statistical methods used to test each hypothesis. ConV5 Result Report which specific results are in accordance with all hypotheses. (7) Criterion validity CriV1 Criterion Report the details of the criterion used and why it was used. Justification of the gold standard must be reported. Also, describe (if applicable) how the criterion was dichotomized or classified. Also, describe how the criterion was administered (eg, if independent from the PROM). CriV2 Continuous scores Report correlations or the AUROC. If the scores on the gold standard comparator are dichotomous, report the AUROC. CriV3 Categorical scores Described how (and why) the PROM was categorized. Report sensitivity and specificity statistics. (8) Responsiveness Resp1 Comparison Instruments Report each comparison instrument (ie, the constructs measured, its MPs), its structure, and

Item No. Item name Item description citations for the MPs. Resp2 Measurement procedures Report whether measurements were applied to the same samples using the same instruments. Describe the measurement procedures, including time intervals. Resp3 Interim period The interim period between time points should be described, especially if there were relevant events that occurred that could influence the scores (eg, intervention given). Resp4 Intervention/exposure Describe the intervention given or exposure if relevant. Resp5 Patients changed Report the proportion of patients that improved or deteriorated (and any related anchor used) on the construct measured on all PROMs. Report any changes in the measured PROM in the target population for the research application relative to the predefined hypotheses. Resp6 Subgroups For known-group type of design, describe important characteristics (eg, demographics, disease characteristics) and sample size of the subgroups. (9) Hypothesis testing HT1 Hypothesis The hypotheses about change scores should be reported. HT2 Direction of effect State the expected direction of correlation or mean differences between subgroups of the change (positive or negative) scores for the PROM. HT3 Magnitude of effect State expected absolute or relative magnitude of correlations or mean differences of the change scores for the PROM. HT4 Comparator instruments The construct measured on the comparator instruments should be described. If comparators are not used, describe the known groups and any differences between the known groups, or describe the intervention/exposure. HT5 Comparator instrument All known MPs of the comparator instruments should be described, or references should be MPs provided to studies in which these properties are described. Abbreviations: AUROC, area under the receiver operating characteristic curve; CTT, classical test theory; ICC, intraclass correlation coefficient; IRT, item response theory; LoA, limits of agreement; PROM, patient-reported outcome measure; SDC, smallest detectable change; SEM, standard error of measurement.

Phase 4: Developing Guidance Documents During phase 4, we drafted both the PCORI final report and a manuscript suitable for publication; the latter is a concise version of the PCORI final research report. We also submitted the protocol for publication; it is currently under review (see Related Publications).

We plan to apply for additional funding to complete a user manual and to provide workshops on our material. We completed 1 invited scientific talk at the ISOQOL Research Annual Meeting in San Diego, California, on October 21, 2019.

DISCUSSION

Through a 4-phase process, we developed and refined 2 sets of items that we now recommend be adopted for reporting investigations of MPs of PROMs. This is the first reporting recommendation of its kind for all main MPs for PROMs, making it an important contribution to the literature. After conducting a literature review and 3 rounds of a Delphi process with an international group of experts, we agreed on a list of 71 items: a set of 35 common items and a set of 36 specific items.

We submitted the protocol for this research for publication and have completed a manuscript describing our findings that is under review for publication. Also, to help with understanding and applying these reporting recommendations, we will complete a user manual that will include detailed descriptions of each item and examples of good reporting of each one. These reporting recommendations will help guide those reporting on or reading these documents regarding the essential recommended information to include.

Limitations and Strengths of the Project

Limitations This project has both drawbacks and strengths. One potential drawback includes the possibility of missing important and salient resources in our search of the literature, which may have restricted our initial items list. However, we did search a large selection of electronic databases, hand-searched the reference lists of relevant articles, and consulted our own personal libraries. This yielded a lengthy review of many citations and supported creation of many items to be used in our consensus process. Overall, we believe that the substantial work in phase 1 of the project meant that we were not likely to have missed important papers or items therein.

The individuals who volunteered to be part of our Delphi panel could have been a selective group. That is, our Delphi panel composition could have been subject to selection bias. Although we invited 140 individuals, 83 agreed to participate initially. Of this larger group

expressing interest in participating in the Delphi process, we had 47 Delphi panelists in round 1, 30 in round 2, and 25 in round 3.

Consequently, the characteristics of these individuals (eg, their views on the reporting of specific MPs) may have made them more likely to respond to the Delphi survey in 1 or more of the rounds, biasing the voting and the resulting final item list. From our initial survey of the make-up of this group, they appear to be quite diverse, but generally they were health services researchers in the areas of measurement or psychometrics, and a large proportion (43%) were from the United States. We have no way to know how a different group would have responded, but generally we had very high consensus and easily reached agreement after 3 Delphi rounds. Therefore, we would expect, if we repeated this Delphi process, that our final item list would be very similar to the one we produced and documented in this report. Further, we did not collect demographic data on the responders in Delphi rounds 2 and 3. Therefore, we are not able to characterize the panelists in rounds 1 and 2.

Another potential drawback is the use of the blinded Delphi process instead of a face-to- face consensus process. Both methods have benefits and drawbacks for achieving consensus,21 with face-to-face processes generating real-time and sometimes lively debate on certain topics. Our item list might have been different had we used a face-to-face consensus process. Therefore, we intend to supplement the findings in this set of recommendations with several face-to-face meetings over time and to revise our checklist accordingly to ensure our item list is comprehensive and representative. Furthermore, the Delphi panel did not allow us to develop or maintain a coherent model of measurement (ie, general and latent variable models), as this was not a goal of our research. We hope that our future face-to-face meetings will allow for this. For these face-to-face meetings, we will convene a group of 10 to 30 individuals within the next 1 to 2 years at international conferences on quality-of-life research.

Also, the third round of our Delphi process did not include our prespecified number of panelists (n = 30). Therefore, the results of this round could have been skewed by the small number of panelists; that is, the results of this round could have been different for a larger set

of panelists. However, in this round we presented very few items to vote on and consensus was mostly very high, giving us confidence in our findings.

The analysis of MPs of PROMs can be done using a wide variety of analytic methods. These include classical psychometric theory, IRT, and Rasch analysis. Within each area, there are many analytic methods, each having unique characteristics. Although our reporting recommendations are meant to be relevant to all such areas, some detail is likely missing in sections. Some guidance does exist for structural equation modeling and IRT analyses that can be useful as adjuncts to our reporting recommendations.24,25

An additional point of discussion, which could be considered a drawback, is that we did not differentiate between recommendations for item-level psychometric investigations and composite/subscale-level psychometric investigations. We tried to address each of these areas where relevant. In the end, our recommendations are meant to be guidance for all such investigations. Furthermore, we did not find any work that made recommendations for validating scoring algorithms for PROMs. Thus, this topic was not included as an item in the Delphi process. Follow-up work might carefully distinguish item- and composite-level analyses and explore reporting for PROM scoring algorithms.

Strengths Our work reflects several strengths, including a comprehensive review of literature, a large international Delphi process comprising 3 rounds, and the generally very strong consensus we eventually achieved. Moreover, the reporting recommendations are comprehensive but also concise; these attributes make them easy to use. Finally, we will ensure that the follow-up user manual will be a complete, useful tool for others to understand and apply these recommendations.

Given that this project was purely methodological, we did not consider subpopulations, risk factors, or comorbidities; that is, the reporting recommendations we created apply to all studies on MPs of PROMs.

Future Research Our future research involves holding face-to-face consensus meetings to discuss and update our findings. Face-to-face meetings often generate discussion that is not possible with Delphi procedures. We also plan to develop additional reporting recommendations for instruments based on IRT, for instrument development, and for cross-cultural validity and translations.

Finally, funding organizations should consider supporting projects aimed at improving the evidence base for the MPs of PROMs.

CONCLUSIONS

These recommendations about items to use in reporting the findings of studies of the MPs of PROMs can help to improve and direct how investigators present the results of their studies. Improving reporting of such studies increases their transparency, which in turn makes obvious both their risk of bias and their importance to scientific knowledge.

Our work is a foundation for making both accurate methodological assessment of these papers and reliable application of their findings (eg, to clinical research). We hope that all relevant international scientific groups adopt these recommendations and that pertinent peer- reviewed journals endorse and enforce them as they have for other reporting recommendations.

59 REFERENCES

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7. Bryan S, Whitehurst D. Patient-reported outcome measurement (PROMs) in British Columbia: what has been achieved so far and where next? Vancouver Coastal Health Research Institute; 2013. https://qualityforum.ca/qf2013/2013-quality-forum/patient- reported-outcome-measurement-prom-in-british-columbia-what-has-been-achieved-so- far-and-where-next/ [Link no longer active]

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10. Terwee CB, Prinsen CA, Ricci Garotti MG, Suman A, de Vet HC, Mokkink LB. The quality of systematic reviews of health-related outcome measurement instruments. Qual Life Res. 2015;25(4):767-769.

11. Huang S, Grant J, Miller B, Mirza FM, Gagnier JJ. A systematic review of psychometric properties of patient-reported outcome instruments for use in patients with rotator cuff disease. Am J Sports Med. 2015;43(10):2572-2582.

12. Gagnier JJ, Mullins M, Huang W, et al. Patient reported outcome questionnaires for total knee arthroplasty: a systematic review of psychometric properties and methodological quality. J Arthroplasty. 2017;32(5):1688-1697.

13. Ioannidis JPA. How to make more published research true. PLoS Med. 2014;11(10):e1001747. doi:10.1371/journal.pmed.1001747

14. Mokkink LB, Terwee CB, Patrick DL, et al. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Qual Life Res. 2010;19:539- 549.

15. Reeve BB, Wyrwich KW, Wu AW, et al. ISOQOL recommends minimum standards for patient-reported outcome measures used in patient-centered outcomes and comparative effectiveness research. Qual Life Res. 2013;22(8):1889-1905.

16. Prinsen CA, Vohra S, Rose MR, et al. Core Outcome Measures in Effectiveness Trials (COMET) initiative: protocol for an international Delphi study to achieve consensus on how to select outcome measurement instruments for outcomes included in a ‘core outcome set’. Trials. 2014;15:247. doi:10.1186/1745-6215-15-247

17. Kottner J, Audigé L, Brorson S, et al. Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed. J Clin Epidemiol. 2011;64(1):96-106.

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61 23. Moher D, Hopewell S, Shulz KF, et al; Consolidated Standards of Reporting Trials Group. CONSORT 2010 explanation and elaboration: updated guideline for reporting parallel group randomized trials. J Clin Epidemiol. 2010;63(8):e1-e37. doi:10.1016/j.jclinepi.2010.03.004

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RELATED PUBLICATIONS Submitted for Publication Gagnier JJ, Mokkink W, Terwee CB. Development of reporting recommendations for investigations of measurement properties of patient reported outcome measures: a protocol.

Published Gagnier JJ, Lai J, Mokkink LB, Terwee CB. COSMIN reporting guideline for studies on measurement properties of patient-reported outcome measures. Qual Life Res. 2021; online ahead of print. doi:10.1007/s11136-021-02822-4

63 ACKNOWLEDGMENTS

We would like to thank the participants of the Delphi rounds for their invaluable contributions. We would also like to thank our information scientist for helping with the literature search during phase 1 of this project.

64 APPENDICES Appendix A. Search Strategies

Reporting recommendations for PROMs • Sentinel articles (DOI numbers) o 28137831 12513067 20298572 22036893 22019563 20352064 20346629 23443445 26786084 18194398 17034633 21514934 21130355 22987144 23796281 19804437 19900250 25128043 23796280 19138309 23288613 25350641 17161752 o Not in Ovid, Embase results 17161752 o Not in Scopus results: 25128043, 20298572, 17161752 • Excluded conference papers, conference abstracts, conference reviews from Embase • Cochrane Methodology Register ceased in 2012 • All searches run on September 8, 2017. Exception: Proquest Dissertations, which was run on September 11, 2017.

Note: all search strategies were constructed using MeSH terms and text terms from the sentinel articles above.

Ovid MEDLINE; Ovid MEDLINE In-Process & Other Non-Indexed Citations; Ovid Medline Epub Ahead of Print (1953 results on August 28, 2017) ((comet or consort or cosmin or empro or grras or ispor or isoqol or stard) and reporting).ti. or ((((report or reporting) adj4 (checklist* or guidance or guideline* or measures or measurement* or recommendation* or standard*)) or (report* adj5 (outcome* or properties) adj2 measure*) or (comet or consort or cosmin or empro or grras or ispor or isoqol or stard)).ti. and (exp patient reported outcome measures/ or exp psychometrics/ or ((self or patient) adj1 report*).tw. or (psychometr* or clinimetr* or clinometr*).tw.))

Embase.com (1698 results on September 5, 2017) 1. (comet:ti OR consort:ti OR cosmin:ti OR empro:ti OR grras:ti OR ispor:ti OR isoqol:ti OR stard:ti) AND (reporting:ti OR standard*:ti) 2. ((((report OR reporting) NEAR/3 (checklist* OR guidance OR measures OR measurement* OR recommendation* OR standard*)):ti) OR ((report* NEAR/5 (outcome* OR properties) NEAR/2 measure*):ti) OR comet:ti OR consort:ti OR cosmin:ti OR empro:ti OR grras:ti OR ispor:ti OR isoqol:ti OR stard:ti) AND ((((self OR patient) NEAR/1 report*):ti,ab) OR 'patient-reported outcome'/exp OR 'psychometry'/exp OR psychometr*:ti,ab OR clinimetr*:ti,ab OR clinometr*:ti,ab) 3. (#2 OR #3) NOT ('conference abstract':it OR 'conference paper':it OR 'conference review':it)

Cochrane Methodology Register (100 results on September 5, 2017) ((comet or consort or cosmin or empro or grras or ispor or isoqol or stard) and reporting):ti or ((((report or reporting) near/4 (checklist* or guidance or measures or measurement* or recommendation* or standard*)) or (report* near/5 (outcome* or properties) near/2 measure*) or (comet or consort or cosmin or empro or grras or ispor or isoqol or stard)):ti and ([mh "patient reported outcome measures"] or [mh psychometrics] or ((self or patient) near/1 report*):ti,ab or (psychometr* or clinimetr* or clinometr*):ti,ab))

CINAHL via EBSCOhost (1136 results on September 5, 2017)

65 S1 TI (comet OR consort OR cosmin OR empro OR grras OR ispor OR isoqol OR stard) AND TI (reporting OR evaluat* OR standard*) S2 TI ( ((report OR reporting) N4 (checklist* OR guidance OR measures OR measurement* OR recommendation* OR standard*)) ) OR TI ( (report* N5 (outcome* OR properties) N2 measure*) ) OR TI ( (comet OR consort OR cosmin OR empro OR grras OR ispor OR isoqol OR stard) ) S3 TI ( ((self OR patient) N1 report*) OR psychometr* OR clinimetr* OR clinometr* ) OR AB ( ((self OR patient) N1 report*) OR psychometr* OR clinimetr* OR clinometr* ) S4 (MH "Patient-Reported Outcomes") OR (MH "Psychometrics") S5 S3 OR S4 S6 S2 AND S5 S7 S1 OR S6

PsycINFO via EBSCOhost (1484 results on September 5, 2017) S1 TI (comet OR consort OR cosmin OR empro OR grras OR ispor OR isoqol OR stard) AND TI (reporting OR evaluat* OR standard*) S2 TI ( ((report OR reporting) N4 (checklist* OR guidance OR measures OR measurement* OR recommendation* OR standard*)) ) OR TI ( (report* N3 (outcome* OR properties) N2 measure*) ) OR TI ( (comet OR consort OR cosmin OR empro OR grras OR ispor OR isoqol OR stard) ) S3 TI ((self OR patient) N1 report*) OR TI psychometr* OR TI clinimetr* OR TI clinometr* OR AB ((self OR patient) N1 report* N3 outcome*) OR AB psychometr* OR AB clinimetr* OR AB clinometr* S4 DE "self report" OR DE psychometrics OR MA psychometrics OR MA "patient reported outcome measures" S5 S3 OR S4 S6 S2 AND S5 S7 S1 OR S6

Proquest Dissertations (224 results on September 11, 2017) ti((comet OR consort OR cosmin OR empro OR grras OR ispor OR isoqol OR stard) AND (reporting OR standard*)) OR (ti(((self OR patient) NEAR/2 report* NEAR/2 (measure* OR outcome*)) OR psychometr* OR clinimetr* OR clinometr*) AND (ti((report OR reporting) NEAR/4 (checklist* OR guidance OR measures OR measurements OR recommendation* OR standard*)) OR ti((report* NEAR/3 (outcome* OR properties) NEAR/2 measure*))))

Scopus (1990 results on September 8, 2017) (TITLE (comet OR consort OR cosmin OR empro OR grras OR ispor OR isoqol OR stard) AND TITLE(reporting OR standard*)) OR (((TITLE((report OR reporting) Pre/2 (checklist* OR guidance OR guideline* OR instrument OR instruments OR measures OR measurements OR recommendation* OR standard*))) OR (TITLE (report* PRE/2 (outcome* OR properties) PRE/2 measure*) OR TITLE(comet OR consort OR cosmin OR empro OR grras OR ispor OR isoqol OR stard))) AND (TITLE((patient OR self) PRE/3 report* PRE/2 (outcome* OR measure*)) OR TITLE(psychometr* OR clinometr* OR clinimetr*)))

66 Appendix B. Reporting Item Survey Round 1

67 9/10/2018 Qualtrics Survey Software

Appendix B: Reporting Item Survey Round 1

Thank you so much for agreeing to be one of our panels!

The aim of this survey is to develop a reporting guideline for studies on psychometric properties of patientreported outcome measures (PROMs).

The survey consists of three parts:

Part I. Personal information of the respondents;

Part II. Items for studies of any measurement property of PROM. You will be asked to choose whether these items should be reported in eight sections of an article (e.g., title, abstract, introduction, methods, results, discussion, conclusion and other information)

Part III. Items for studies of nine speciﬁc measurement properties of PROM. For each section, you will be asked to choose whether these items should be reported for the speciﬁc measurement properties.

The following survey has 21 pages. It will take approximately 30 minutes of your time to complete this survey.

We really appreciate your time in participation.

Personal Information

Part I: Personal Information

In which country do you work at the moment? If you work in more than one country, please indicate all the countries where you work.

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Which of the following options best describe your current job function? Please select all options that apply to your current job function.

Health Care Provider Health Care Researcher Other (please specify)

Other (please specify)

Which of the following options best describe the field in which you are currently working? Please select all options that apply to the field in which you are currently working.

Epidemiology Clinical Epidemiology Measurement Psychometrics Statistics/biostatistics Other (please specify)

Other (please specify)

How many years have you been working in this field?

Have you been involved in the development of a reporting guideline of any kind?

Yes (if so, please specify the number of reporting guidelines) No

Please specify the number of reporting guidelines https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 2/41 9/10/2018 Qualtrics Survey Software

Have you ever taken part in developing method or reporting guidelines for psychometric properties of PROMs?

Yes (if so, please specify the number of studies) No

Please specify the number of studies.

Have you ever conducted a systematic review of methods for PROMs' psychometric properties?

Yes (if so, please specify the number of systematic reviews) No

Please specify the number of systematic reviews.

Page 1/21

Section A: Common Reporting Recommendations

Part II: General Reporting Recommendations for all Studies Investigating PRO Measurement Properties

Please indicate which items you agree should be included in a set of reporting recommendations for investigations of PROM Measurement Properties. Please feel free to provide comments below each of your responses.

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Page 2/21

Title

Report section: Title

Patient Reported Outcome Measure (PROM)

Item Description: The name of the PROM instrument(s) (and version if relevant) being studied

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Measurement Property (MP)

Item Description: What MP (e.g. reliability, internal consistency) are being studied or more generally, what MP/psychometric properties/scale properties (or other synonym) are being studied (if there are many properties being investigated, for example).

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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Study design

Item Description: The type of study being used to test the properties (e.g., cohort, cross sectional, case series, randomized etc). Other details of the study design if relevant (intervention, comparators, outcome).

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Study sample

Item Description: General description of relevant study sample characteristics (e.g., condition of interest, language) and also any intervention or exposure (e.g., treatments)

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Page 3/21

Abstract

Report section: Abstract

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Patient Reported Outcome Measure (PROM)

Item Description: The name of the PROM instrument(s) (and version if relevant) being studied (i.e. the SF36 or SF12) or if it concerns an item bank (e.g., PROMIS instruments). The type of instrument (e.g. a questionnaire, a performancebased measure).

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Measurement Property (MP)

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Design

Yes No https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 6/41 9/10/2018 Qualtrics Survey Software Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Sample

Item Description: Inclusion / exclusion criteria. General description of relevant study sample characteristics (e.g., condition of interest, geographic location, language, other relevant demographic and baseline characteristics).

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Methods

Item Description: A brief description of the methods for investigating each MP including statistical analyses.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Results

Item Description: https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 7/41 9/10/2018 Qualtrics Survey Software The main results for all MPs investigated reporting statistics for each result with measures of precision where appropriate.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Discussion/Conclusions

Item Description: A brief description of the results in the context of existing evidence, main strengths and drawbacks and the need for future research on the PROM(s) investigated.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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Introduction

Report section: Introduction

Name and describe the PROM of interest

Item Description: Specify the name, type, language, and version (if the PROM is adapted) of the PROM being investigated and how it was developed. This may include the number of items, scoring algorithm, relevant https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 8/41 9/10/2018 Qualtrics Survey Software instructions (like time period), and number or type of response categories. Describe the construct the PROM aims to measure, and the structure of the PROM (e.g., the number of factors, and their constructs). State whether the PROM is based on a reflective or formative model.

Note: This information may also appear in the methods section in greater detail.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Target population

Item Description: Describe the specific target population that the PROM was designed for and applied to. The authors need to provide the appropriate and necessary characteristics of this population.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Citation for the original development of the PROM

Item Description: The citation for the original development paper(s) should be provided and other highly relevant citations relative to the specific PROM under investigation.

Yes No

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State of Knowledge & Rationale

Item Description: A description of the current scientific knowledge (what is known) regarding the MPs for the PROM under investigation. The authors should provide a literature review of all existing evidence of the version (e.g., language, short form) of the PROM and explain why the new study is necessary and important. The rational for the current proposed study should be given.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Definitions

Item Description: Specialized terms should be defined or explained.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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Objectives and Hypotheses

Item Description: State the specific objective(s) of the research and hypotheses related to the specific PROM under investigation.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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General Methods

Report section: General Methods (relevant to the reporting of investigation of any measurement property of a PROM)

Study Design

Item Description: State the key elements of the study design.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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Participants

Item Description: State how the participants were chosen relative to the specific PROM under investigation (e.g., if a PROM for a specific condition, then the eligibility and selection criteria should reflect this).

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

PROM administration

Item Description: An explicit description of how the PROM(s) were administered (e.g., in what setting) including data collection devices/system (e.g. paper based, electronic administration / ePRO) to patients should be provided.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Data collection procedures

Item Description: Provide information about other data collection, exposure methods (e.g., allocation to interventions) and time points / followup points.

Yes No Unsure/I do not know

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Power/sample size calculation

Item Description: Provide a power calculation or sample size for all MP analyses. Alternatively, if a rule of thumb is used, state it and the source/citation.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Statistical analyses

Item Description: Statistical analyses and tests corresponding to all hypotheses for all MPs should be reported. Where appropriate, a cutoff for statistical significance should be reported (e.g., pvalue less than 0.05). A description of all statistics to be used to estimate the magnitude and direction of effect should also be reported, together with measures of variability or precision. Report statistical package used.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Missing data

Item Description: State approaches or plan for dealing with missing data. https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 13/41 9/10/2018 Qualtrics Survey Software

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Post hoc analysis

Item Description: The report should specify analyses that used data after the data collection period concluded (i.e., if the analyses were post hoc) and describe the rationale for any post hoc analyses.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Randomized controlled trial

Item Description: If the authors defined the study as randomized controlled trial, the report should include all information suggested in the CONSORT statement.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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Observational study

Item Description: If the authors defined the study as observational study, the report should include all information suggested in STROBE guidelines.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Other study design

Item Description: Use additional appropriate reporting guidelines for the specific study design used. See www.equator network.org for specific reporting guidance for other study designs.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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General Results

Report section: General Results (relevant to the reporting of investigation of any measurement property of a PROM)

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Missing data

Item Description: The amount and reasons for missing data should be explained for all analyses for all PROMs and relevant groups.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Participant/patient Characteristics

Item Description: The study patients’ characteristics should be described, including baseline PROM scores.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Sample size

Item Description: If one study contained more than one analysis with different sample size used, the authors need to report the sample size for each analysis.

Yes No Unsure/I do not know

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Page 7/21

Discussion

Report section: Discussion

Measurement Property (MP) evidence

Item Description: Per measurement property the authors should compare the result to the criteria for good measurement properties, and determine if the specific quality aspect (i.e., MP) is sufficient or not.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Practical relevance

Item Description: The authors need to discuss the practical relevance, which depends on the purpose of the research, and the consequences of PROM scores.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 17/41 9/10/2018 Qualtrics Survey Software

Strengths and limitations

Item Description: Strengths and limitations of the study should be discussed. For example, discuss if there were any significant potential biases in the study that could have impacted the findings for each hypothesis.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Generalizability

Item Description: Generalizability issues related to the PROM results should be discussed. For example, discuss if the results could be generalized to other populations given the sample studied.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Instrument changes

Item Description: Discuss the need for modifications to the existing PROM or new PROM development. If you conclude that one of the measurement properties is insufficient, you could suggest some modification, or if it is really poor, you could suggest stopping use of the PROM.

Yes https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 18/41 9/10/2018 Qualtrics Survey Software No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Future Research

Item Description: Report specifically the type of research needed to answer new questions arising out of these findings for the particular MP and PROM investigated.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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Conclusions

Report section: Conclusions

Conclusions

Item Description: State the overall conclusions for each MP and PROM investigated.

Yes No Unsure/I do not know https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 19/41 9/10/2018 Qualtrics Survey Software

Please provide any comments you wish to justify your response to the above question

Page 9/21

Other information

Report section: Other Information

Conflict of Interest

Item Description: State any relevant conflict if interest related to the PROM under investigation (e.g., an author being the PROM developer, funding body etc).

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Page 10/21

Section B: Speciﬁc Recommendations

Part III: Specific Measurement Property Reporting Recommendations for Studies Investigating PRO Measurement Properties Please indicate which items for each psychometric property below do you agree should be included in a reporting recommendation for studies on psychometric properties of patientreported outcome measures. Please provide comments below each item if necessary. https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 20/41 9/10/2018 Qualtrics Survey Software

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Reliability

Report section: Reliability

PROM Administrations

Item Description: The process of administrating the measurements to the patients should be described, including who administered it (i.e., did the patient complete it or was there a proxy), when, how and any time intervals between administrations should be reported. This should include: time interval between repeated measurements, justification that the patient was stable (e.g., single item perceived change scale), the general conditions underlying the measurement situation (e.g., setting, location, other instruments or measurements accompanying the repeated PROM measurement) and instructions given. Also, if relevant, the independence of the administrations. If the PROM was delivered by interview, describe the interviewers for each administration.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Statistical analyses

Item Description: All statistical analyses specific to the reliability assessment(s) should be described and their use justified (e.g., the intraclass correlation coefficient (ICC) model or type of Kappa coefficient used). Also, describe the weighting scheme used for ordinal scores (e.g., linear or quadratic weights).

Yes No

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Methods to improve reliability

Item Description: Report any methods used to improve reliability such as restriction, training and standardization, and averaging of repeated measurements.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Page 12/21

Measurement Error

Report section: Measurement Error

PROM administration

Item Description: Report the total number of measurements made and if the measurements were applied to the same samples using the same PROM. The process of administrating the measurements to the patients should be described, including who administered it (i.e., did the patient complete it or was there a proxy), when, how and any time intervals between administrations should be reported. This should include: time interval between repeated measurements (e.g., was the patient stable or not), the general conditions underlying the measurement situation, the test type (e.g. a self‐administered questionnaire, an interview based PROM), the setting in which the instrument was administered (e.g., at the hospital, or at home), https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 22/41 9/10/2018 Qualtrics Survey Software and the instructions given for completing it. If relevant, other instruments or measurements accompanying the repeated PROM measurement. Also, if relevant, the independence of the administrations.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Statistical analyses

Item Description: All statistical analyses specific to measurement error assessment(s) should be described and their use justified. Specifically, for continuous scores report the Standard Error of Measurement (SEM; Specify the exact model used to calculate the SEM (i.e., SEM consistency or SEM agreement)), Smallest Detectable Change (SDC) or Limits of Agreement (LoA). For dichotomous/nominal/ordinal scores report the percentage of (positive and negative) agreement.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Page 13/21

Internal Consistency

Report section: Internal Consistency

Unit of measurement

Item Description: https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 23/41 9/10/2018 Qualtrics Survey Software Report internal consistency statistic for each unidimensional scale or subscale. Report assumptions associated with unidimensionality.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Continuous scores

Item Description: Report Cronbach’s alpha or omega statistics. Report other statistics calculated for internal consistency of continuous scores.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Dichotomous scores

Item Description: Report Cronbach’s alpha or KuderRichardson coefficient. Report other statistics calculated for internal consistency of dichotomous scores.

Yes No Unsure/I do not know

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IRTbased scores

Item Description: Report the standard error of the theta (SE (θ)) or reliability coefficient of estimated latent trait value (index of (subject or item) separation).

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Page 14/21

Content Validity

Report section: Content Validity

Relevance

Item Description: Report if and how patients and/or professionals were asked whether each item is relevant for their experience with the condition

Yes No Unsure/I do not know

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Comprehensiveness

Item Description: Report if and how patients and/or professionals were asked whether all key concepts are included.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Comprehensibility

Item Description: Report if and how the comprehensibility of the PROM instructions, items, response options, and recall period was assessed.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Relevance results

Item Description: https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 26/41 9/10/2018 Qualtrics Survey Software Report if all items were considered relevant for the construct, population, and context of use of interest by patients and/or professionals.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Response options and recall period

Item Description: Report whether the response options and recall period were considered appropriate by patients and/or professionals.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Comprehensiveness results

Item Description: Report whether patients and/or professionals considered all key concepts to be included in the PROM.

Yes No Unsure/I do not know

Comprehensibility results

Item Description: Report whether patients understood the PROM instructions, items, and response options as intended.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Qualitative methods and results

Item Description: Use the COREQ reporting guidelines for reporting the methods and results of qualitative studies. See www.equatornetwork.org

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Page 15/21

Structural Validity

Report section: Structural Validity

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Conceptual framework

Item Description: Report the conceptual framework upon which the PROM relied. Structural validity is only relevant for instruments with items based on a reflective model. These kinds of items are called effect indicators and they should be fully and completely reported together with descriptions and definitions.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Factor Analyses: Classical Test Theory (CTT) PROMs

Item Description: Report details of the methods for any exploratory or confirmatory factor analyses. The factor structure of tested models should be described. Methods for checking of the assumptions should be described, type of factor analysis, the method of estimation, goodnessoffit statistics and cutoff points for good model fit, including factor loadings of bestfitting model. For confirmatory factor analysis state the hypotheses regarding the factor structure being tested. Report any theory such hypotheses are based on. State the rational for any explorative factor analyses (e.g., no clear a priori hypotheses).

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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Item Response Theory (IRT) analyses

Item Description: Type of IRT/Rasch model should be reported. Also report the method of estimation, methods and results for checking of the assumptions (unidimensionality (see factor analysis), local dependency (e.g., residual correlations), monotonicity (e.g. Mokken scaling)), goodnessoffit statistics, and cutoff points for goodness of item/model fit, and all item parameters.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Page 16/21

Construct Validity

Report section: Construct Validity

Comparator instrument(s)

Item Description: The comparator instruments should be appropriately described in terms of the construct they intend to measure. Report the measurement properties of the comparator instruments and related citations or data.

Yes No Unsure/I do not know

Comparator Group(s)

Item Description: Report characteristics of groups being compared. Include sample sizes in each group.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Hypotheses

Item Description: Report all hypotheses including the direction and magnitude of the expected results of relationships between the PROM of interest and another measurement instrument, or of differences in scores of the PROM between groups.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Statistical analyses

Item Description: Report all statistical methods used to test each hypothesis.

Yes https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 31/41 9/10/2018 Qualtrics Survey Software No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Result

Item Description: Report which specific results are in accordance with all hypotheses.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Page 17/21

Criterion Validity

Report section: Criterion Validity

Criterion

Item Description: Report the details of the criterion used and why it was used. Justification of the gold standard must be reported. Also, describe (if applicable) how the criterion was dichotomized or classified. Also, how the criterion was administered (e.g., if independent from the PROM).

Yes https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 32/41 9/10/2018 Qualtrics Survey Software No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Continuous scores

Item Description: Report correlations or the area under the receiver operating characteristic (ROC) curve. If the scores on the gold standard comparator are dichotomous, report the area under the ROC curve.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Categorical scores

Item Description: Described how (and why?) the PROM was dichotomized. Report sensitivity and specificity statistics.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Page 18/21 https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 33/41 9/10/2018 Qualtrics Survey Software

Hypothesis testing

Report section: Hypothesis testing

Hypothesis

Item Description: The hypotheses about change scores should be reported.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Direction of effect

Item Description: State expected direction of correlation or mean differences between subgroups of the change (positive or negative) scores for PROM.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Magnitude of effect

https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 34/41 9/10/2018 Qualtrics Survey Software Item Description: State expected absolute or relative magnitude of correlations or mean differences of the change scores PROM.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Comparator instrument(s)

Item Description: The construct measured on the comparator instrument(s) should be described. If comparators are not used, describe the “known groups” and any differences between the “known” groups, or describe the intervention/exposure.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Comparator instrument measurement properties

Item Description: All known measurement properties of the comparator instrument(s) should be described or references should be provided to studies in which these properties are described.

Yes No Unsure/I do not know

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Page 19/21

Responsiveness

Report section: Responsiveness

Comparison Instrument(s)

Item Description: Report each comparison instrument (i.e. the construct(s) measured, its measurement properties), its structure, and citations for the measurement properties.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Measurement procedures

Item Description: Report if measurements were applied to the same samples using the same instruments. Describe the measurement procedures, including time intervals.

Yes No Unsure/I do not know

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Interim period

Item Description: The interim period between time points should be described, especially if there were relevant events that occurred which could influence the scores (e.g. intervention given).

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Intervention/Exposure

Item Description: Describe the intervention given or exposure if relevant.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Patients changed

Item Description: Report the proportion of patients that improved or deteriorated (and any related anchor used) on the construct measured on all PROMs. Report any changes in the measured PROM in the target population for the research application relative to the predefined hypotheses. https://umich.ca1.qualtrics.com/ControlPanel/Ajax.php?action=GetSurveyPrintPreview 37/41 9/10/2018 Qualtrics Survey Software Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

Subgroups

Item Description: For ‘knowngroup’ type of design describe important characteristics (e.g, demographics, disease characteristics) and sample size of the subgroups.

Yes No Unsure/I do not know

Please provide any comments you wish to justify your response to the above question

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End

Ending Question

(Optional) This is the last question of this survey. If you have any additional reporting item suggestions that have not appeared in this survey, or other comments, please feel free to write them here.

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107 Appendix C: Nonduplicate Search Results

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980. Erratum to A symptom self-report measure for preschool children (1990, 29, 594-600). Journal of the American Academy of Child and Adolescent Psychiatry, 1990. 29(5): p. 841.

981. Karpouzis, F., et al., Erratum to: "Quality of reporting of randomised controlled trials in chiropractic using the CONSORT checklist" [Chiropr Man Therap. 2016;16(24). doi:10.1186/s12998-016-0120-0]. Chiropractic and Manual Therapies, 2016. 24(1).

982. Erratum to: Functional Reading Independence (FRI) Index: A new Patient- Reported Outcome Measure for Patients With Geographic Atrophy (Invest Ophthalmol Vis Sci, (2016) 57, (6298-6304), 10.1167/iovs.16-20361). Investigative Ophthalmology and Visual Science, 2017. 58(9): p. 3825.

983. Thabane, L., et al., Erratum to: Methods and processes for development of a CONSORT extension for reporting pilot randomized controlled trials.[Erratum for Pilot Feasibility Stud. 2016 May 20;2:25; PMID: 27965844]. Pilot & Feasibility Studies, 2016. 2: p. 35.

984. Erratum to: Quality of reporting of randomised controlled trials in chiropractic using the CONSORT checklist. Chiropractic & Manual Therapies, 2016. 24: p. 1-1.

985. Karpouzis, F., et al., Erratum to: Quality of reporting of randomised controlled trials in chiropractic using the CONSORT checklist.[Erratum for Chiropr Man Therap. 2016;24:19; PMID: 27284400]. Chiropractic & manual therapies, 2016. 24: p. 36.

986. Erratum: A symptom self-report measure for preschool children (Journal, July 1990, 29, 594-600). Journal of the American Academy of Child and Adolescent Psychiatry, 1990. 29(5): p. 841.

987. Matthey, S., et al., Erratum: Comparison of four self-report measures, and a generic mood question, to screen for anxiety during pregnancy in English-speaking women (Journal of Affective Disorders (2013) 148:2 (347-351)). Journal of Affective Disorders, 2014. 155(1): p. 307.

988. Moher, D., et al., Erratum: CONSORT 2010 Explanation and Elaboration: Updated guidelines for reporting parallel group randomised trials (JJournal of Clinical Epidemiology (2010) 63:8 (e1-e37) DOI: 10.1016/j.jclinepi.2010.03.004). Journal of Clinical Epidemiology, 2012. 65(3): p. 351.

989. Schulz, K.F., et al., Erratum: CONSORT 2010 statement: Updated guidelines for reporting parallel group randomised trials ORIGINAL (NON-ENGLISH) TITLE Erratum: CONSORT 2010: Aktualisierte Leitlinie für Berichte randomisierter Studien im Parallelgruppen-Design. Deutsche Medizinische Wochenschrift, 2011. 136(15): p. e26.

990. Stice, E., C.F. Telch, and S.L. Rizvi, Erratum: Development and validation of the eating disorder diagnostic scale. A brief self-report measure of anorexia, bulimia, and binge-eating disorder (Psychological Assessment (2000) 12:2 (123-131)). Psychological Assessment, 2000. 12(3): p. 252.

991. Spiegel, B.M.R., et al., Erratum: Development of the NIH patient-reported outcomes measurement information system (PROMIS) Gastrointestinal Symptom Scales (American Journal of Gastroenterology (2014) 109 (1804-1814) DOI: 10.1038/ajg.2014.237). American Journal of Gastroenterology, 2015. 110(4): p. 608.

992. Christensen, S.B., I. Haugen, and T.K. Kvien, Erratum: Distribution of joint involvement in women with hand osteoarthritis and associations between joint counts and patient-reported outcome measures (Annals of the Rheumatic Diseases (2010) 69 (198-201)). Annals of the Rheumatic Diseases, 2014. 73(10): p. 1910.

993. Forchhammer, L., et al., Erratum: Inter-laboratory variation in DNA damage using a standard comet assay protocol (Mutagenesis (2012) 27:6 (665-672)). Mutagenesis, 2013. 28(2): p. 241.

994. Pozzebon, J.A., et al., Erratum: Psychometric characteristics of a public- domain self-report measure of vocational interests: The oregon vocational interest scales (Journal of Personality Assessment (2010) 92: 2 (168-174)). Journal of Personality Assessment, 2010. 92(6): p. 618.

995. Erratum: Reporting of noninferiority and equivalence randomized trials: An extension of the CONSORT statement (Journal of American Medical Association (2006) 295 (1152-1160)). Journal of the American Medical Association, 2006. 296(15): p. 1842.

996. Bolignano, D., et al., Erratum: The quality of reporting in clinical research: The CONSORT and STROBE initiatives (Aging - Clinical and Experimental Research DOI: 10.1007/s40520-013-0007-z)). Aging Clinical and Experimental Research, 2013. 25(3): p. 353.

997. Lee, Z., et al., Erratum: The Validity of the Antisocial Process Screening Device as a Self-Report Measure of Psychopathy in Adolescent Offenders (Behavioral Sciences and the Law (2003) 21, 6 (771-786)). Behavioral Sciences and the Law, 2004. 22(2): p. 287.

998. Johnston, K.C. and R.G. Holloway, Erratum: There is nothing staid about STARD - Progress in the reporting of diagnostic accuracy studies (Neurology (2006) 67 (740-741)). Neurology, 2007. 68(7): p. 534.

999. Johnston, K.C. and R.G. Holloway, Erratum: There is nothing staid about STARD: Progress in the reporting of diagnostic accuracy studies (Neurology (2006) 67 (740-741)). Neurology, 2008. 71(2): p. 152.

1000. Bossuyt, P.M., et al., Erratum: Towards complete and accurate reporting of studies of diagnostic accuracy: The STARD initiative ORIGINAL (NON-ENGLISH) TITLE Erratum: Vollständiges und präzises Berichten von Studien zur Diagnostischen Genauigkeit: Die STARD-Initiative. Deutsche Medizinische Wochenschrift, 2011. 136(15): p. e24.

1001. Boers, M., et al., Erratum: Updated Consolidated Standards of Reporting Trials (CONSORT): It just gets better (Journal of Clinical Epidemiology (2010) 63 (813-814)). Journal of Clinical Epidemiology, 2011. 64(3): p. 343.

1002. Petrillo, J., et al., Erratum: Using classical test theory, item response theory, and Rasch measurement theory to evaluate patient-reported outcome measures: a comparison of worked examples (Value Health (2015) 18 (25-34)). Value in Health, 2015. 18(4): p. 547.

1003. Morgan, E.M., et al., Establishing clinical meaning and defining important differences for Patient-Reported Outcomes Measurement Information System (PROMIS) measures in juvenile idiopathic arthritis using standard setting with patients, parents, and providers. Quality of Life Research, 2017. 26(3): p. 565-586.

1004. Li, Y.P., et al., Establishing collaboration of dissemination of CONSORT statement in China to improve the quality of reporting of randomized clinical trials. Chinese Journal of Evidence-Based Medicine, 2005. 5(8): p. 591-592.

1005. Watt, T., et al., Establishing construct validity for the thyroid-specific patient reported outcome measure (ThyPRO): an initial examination. Quality of Life Research, 2009. 18(4): p. 483-96.

1006. Withers, K.L., et al., Establishing content validity in a novel patient reported outcome measure for cardiac arrhythmia ablation patients. Health & Quality of Life Outcomes, 2015. 13: p. 38.

1007. Withers, K.L., et al., Establishing content validity in a novel patient reported outcome measure for cardiac arrhythmia ablation patients. Health & Quality of Life Outcomes, 2015. 13(1): p. 1-7.

1008. Withers, K.L., et al., Establishing content validity in a novel patient reported outcome measure for cardiac arrhythmia ablation patients. Health & Quality of Life Outcomes, 2015. 13(1): p. 1-14.

1009. Fuller, R.L.M., et al., Establishing Equivalence of Electronic Clinician-Reported Outcome Measures. Therapeutic Innovation & Regulatory Science, 2016. 50(1): p. 30-36.

1010. Halsten, J.W., Establishing the criterion validity of self-report interpersonal competence measures. 1993, University of Illinois at Chicago: Ann Arbor. p. 109.

1011. Swanholm, E., et al., Estimates of Minimally Important Differences (MIDs) for Two Patient-Reported Outcomes Measurement Information System (PROMIS) Computer-Adaptive Tests in Chronic Pain Patients. Journal of Applied Biobehavioral Research, 2014. 19(4): p. 217-232.

1012. Shields, M., S. Connor Gorber, and M.S. Tremblay, Estimates of obesity based on self-report versus direct measures. Health Reports, 2008. 19(2): p. 61-76.

1013. Hutchings, A., et al., Estimating recruitment rates for routine use of patient reported outcome measures and the impact on provider comparisons. BMC Health Services Research, 2014. 14: p. 66.

1014. Lesser, I.M., et al., Ethnicity/race and outcome in the treatment of depression: results from STAR D. Medical Care, 2007. 45(11): p. 1043-51.

1015. Sallis, J.F., et al., Evaluating a brief self-report measure of neighborhood environments for physical activity research and surveillance: Physical Activity Neighborhood Environment Scale (PANES). Journal of Physical Activity and Health, 2010. 7(4): p. 533-540.

1016. Evaluating accessibility design features in patient reported outcome measures of functional performance for use by youth with neurodevelopmental disabilities. Developmental Medicine & Child Neurology, 2017. 59: p. 27-28.

1017. Bee, P., et al., Evaluating and Quantifying User and Carer Involvement in Mental Health Care Planning (EQUIP): Co-Development of a New Patient-Reported Outcome Measure. PLoS ONE [Electronic Resource], 2016. 11(3): p. e0149973.

1018. Zukauskiene, R., et al., Evaluating behavioral and emotional problems with the Child Behavior Checklist and Youth Self-Report scales: cross-informant and longitudinal associations. Medicina (Kaunas, Lithuania), 2004. 40(2): p. 169-77.

1019. Lin, F.J., et al., Evaluating change using patient-reported outcome measures in knee replacement: the complementary nature of the EQ-5D index and VAS scores. European Journal of Health Economics, 2014. 15(5): p. 489-96.

1020. Tietschert, M.V., et al., Evaluating Cross-Cultural Applicability of Patient Reported Outcome Measures of Integrated Care. International Journal of Integrated Care (IJIC), 2016. 16(6): p. 1-2.

1021. Lidder, A.K., et al., Evaluating metrics of responsiveness using patient- reported outcome measures in chronic rhinosinusitis. International Forum of Allergy & Rhinology, 2017. 7(2): p. 128-134.

1022. Dalal, A.A., et al., Evaluating patient-reported outcome measurement comparability between paper and alternate versions, using the lung function questionnaire as an example. Value in Health, 2011. 14(5): p. 712-20.

1023. Babcock-Parziale, J., P.E. McKnight, and D.N. Head, Evaluating psychometric properties of a clinical and a self-report blind rehabilitation outcome measure. Journal of Rehabilitation Research & Development, 2005. 42(4): p. 487-98.

1024. Ackerman, R.A. and M.B. Donnellan, Evaluating Self-Report Measures of Narcissistic Entitlement. Journal of Psychopathology & Behavioral Assessment, 2013. 35(4): p. 460-474.

1025. Diallo, S., et al., Evaluating Single-incision Slings in Female Stress Urinary Incontinence: The Usefulness of the CONSORT Statement Criteria. Urology, 2012. 80(a3): p. 535-541.

1026. Bird, V.J., et al., Evaluating the feasibility of complex interventions in mental health services: standardised measure and reporting guidelines. British Journal of Psychiatry, 2014. 204: p. 316-21.

1027. Palsgrove, A.C., et al., Evaluating the impacts of the FDAs guidance for patient-reported outcomes (PROs) measures on clinical trial-based approved drug product labeling claims, 2006-2014. Clinical Research and Regulatory Affairs, 2015. 32(3): p. 77-84.

1028. Fishbein, L., Evaluating the psychometric properties of a parent-report measure of sibling responsibility. 2015, State University of New York at Binghamton: Ann Arbor. p. 95.

1029. Moberg-Mogren, E. and D.L. Nelson, Evaluating the quality of reporting occupational therapy randomized controlled trials by expanding the CONSORT criteria. American Journal of Occupational Therapy, 2006. 60(2): p. 226-35.

1030. Cleary, R.K., et al., Evaluating the Use of a Novel Patient-Reported Outcomes Measure in Cancer Care: A Pilot Study in Patients Receiving Radiation Therapy. International Journal of Radiation Oncology, Biology, Physics, 2017. 99: p. E549- E550.

1031. Sirard, J.R., et al., Evaluation of 2 self-report measures of physical activity with accelerometry in young adults. Journal of Physical Activity & Health, 2013. 10(1): p. 85-96.

1032. Cooper, P., et al., Evaluation of a modified self-report measure of social adjustment. British Journal of Psychiatry, 1982. 141(1): p. 68-75.

1033. Rose, M., et al., Evaluation of a preliminary physical function item bank supported the expected advantages of the Patient-Reported Outcomes Measurement Information System (PROMIS). Journal of Clinical Epidemiology, 2008. 61(1): p. 17- 33.

1034. Cunningham, V.L., Evaluation of a self -report measure of low -vision functional ability. 2003, The University of Arizona: Ann Arbor. p. 73.

1035. Haywood, K.L., et al., Evaluation of ankylosing spondylitis quality of life (EASi-QoL): reliability and validity of a new patient-reported outcome measure. Journal of Rheumatology, 2010. 37(10): p. 2100-9.

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1038. Jaffer, A.M., et al., Evaluation of CONSORT compliance in TRANSFUSION. Transfusion, 2016. 56(4): p. 789-790.

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1040. Cok, I., et al., Evaluation of DNA Damage in Common Carp (Cyprinus carpio L.) by Comet Assay for Determination of Possible Pollution in Lake Mogan (Ankara). Scientific World Journal, 2011. 11: p. 1455-1461.

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1044. Francielli de Oliveira, P., et al., Evaluation of Genotoxicity and Antigenotoxicity of Artepillin C in V79 Cells by the Comet and Micronucleus Assays. Nutrition & Cancer, 2013. 65(7): p. 1098-1103.

1045. Hill, B., et al., Evaluation of Internal Construct Validity and Unidimensionality of the Brachial Assessment Tool, A Patient-Reported Outcome Measure for Brachial Plexus Injury. Archives of Physical Medicine & Rehabilitation, 2016. 97(12): p. 2146- 2156.

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1054. Tierney, D.W. and M.P. McCabe, An evaluation of self-report measures of cognitive distortions and empathy among Australian sex offenders. Archives of Sexual Behavior, 2001. 30(5): p. 495-519.

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1065. Cook, K.F., et al., Evaluation of the Validity and Response Burden of Patient Self-Report Measures of the Pain Assessment Screening Tool and Outcomes Registry (PASTOR). Military Medicine, 2017. 182(7): p. e1851-e1861.

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1067. Torgerson, C., et al., Every Child Counts: Testing policy effectiveness using a randomised controlled trial, designed, conducted and reported to CONSORT standards. Research in Mathematics Education, 2013. 15(2): p. 141-153.

1068. Scott, G., Evidence for factorial and construct validity of a self-report survey that measures implementation of mathematics reform. 2005, Queen's University (Canada): Ann Arbor. p. 100.

1069. Wolfe-Christensen, C., et al., Evidence of Need to Use Self-Report Measures of Psychosocial Functioning in Older Children and Adolescents with Voiding Dysfunction. Journal of Urology, 2016. 195(5): p. 1570-4.

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1072. Asbjornsen, A.E., et al., An examination of shared variance in self-report and objective measures of attention in the incarcerated adult population. Journal of Attention Disorders, 2010. 14(2): p. 182-93.

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Appendix D. Comments From Round 1

373 ITEM Item Name # Comments NUMBER T1 Patient Reported 1 The language in which the PROM was tested should be included Outcome Measure 2 Accurate identification of the exact instrument is essential, especially if there are (PROM) multiple versions 3 hard to fit version information, though, into a title 4 One should report also the language and if that is a cross-cultural adaptation, but that is probably mentioned later in the survey 5 Absolutely, is transparent and allows full replication. 6 include language version (s) used 7 Are you asking if the name needs to be in the title? I am a bit confused about the layout of this screen and what you are asking. 8 name, language version and version number are required 9 Being very concrete and transparent about what the instrument is about is helpful T2 Measurement 1 too much detail for a title Property (MP) 2 Please have a look at www.cosmin.nl All this has already been done and summarized in excellent tools. 3 There are over 150 types of validity out there. I think we should specify which ones NEED to be reported 4 necessary if only a single property being investigated. 5 The exact focus of the psychometric analyses completed is important. 6 Always 7 minimally important difference 8 Should strive for studies where more than one MP is being reported, always. 9 item reduction, how scoring was developed, methods to interpret change scores and context 10 can't determine what this question is asking 11 Never heard "mp" before....what about responsiveness, IRT properties, etc. 12 Unsure whether it is possible to put everything in the title, maybe a subtitle? T3 Study design 1 that is for the method section 2 Often journals want a short and concise title and study design information is probably the least important, except when it is a randomized trial. 3 The design is often irrelevant in establishing psychometric properties of an instrument. 4 Essential information on the study research design 5 It may be good to specify cross-sectional or longitudinal in the title 6 Most important the study population on which the PROM is tested and how it is selected 7 cohort, cross sectional 8 The study design has substantial impact on frame of reference to or within which all empirical findings apply. 9 can go in the abstract, not needed in the title 10 Only, when relevant. e.g. for responsiveness interventions received might be relevant 11 Unsure whether it is possible to put everything in the title. Put it in a subtitle or short description? T4 Study sample 1 Language is very important for translation articles. Condition of interest should in my opinion always be mentioned. 2 Measures are not "validated" for all purposes. It is therefore critical to report the context (including study sample details) within which a PRO measure was developed and evaluated. 3 Important to describe the study sample, in terms of diagnosis, recruiting and data collection and research design. 4 I guess this depends if belongs to the main research question or not. For example, if it's a paper where testing invariance is one of the most important topics, then it's important to mention the subpopulation under study. 5 see above comment 6 Also how recruited and how many refused 7 movement disorders, neurodevelopmental and degenerative conditions 8 can go in the abstract 9 this really depends on whether you are using CTT or IRT 10 condition and language are relevant , see previous questions. Construct to be measured by PROM should be described in detail (is separate from study sample characteristics) 11 In a title it is relevant to be concrete about the what and on second place the how A1 PROM 1 subcomponents of SF-36, VAS for pain 2 including the specific version A2 Measurement 1 With the underpinning measurement model- if using CTT methods- specify results are Property sample dependent (versus Rasch Measurement methods where results are invariant) 2 Minimally important different especially to customize to use for rare genetic disorders 3 item reduction scoring as relevant A3 Design 1 cohort, cross sectional 2 for reliability this is not very relevant, so depends on which measurement property A4 Sample 1 Only a short description of the sample including the underlying pathology and basic baseline characteristics 2 only key criteria of subjects; not as precise as would be in methods section of paper 3 In my opinion, any key eligibility parameters should be provided in a general description of the study population within the abstract, but full I/E criteria isn't needed until the body of the report/paper. 4 basic description is all that will fit in an abstract, but that should be included 5 An abstract cannot include all details, but the main inclusion criteria of course 6 Any of those listed, depending on context of use, and as measures of response to an intervention 7 see previous comment on study sample characteristics A5 Methods 1 not necessarily as it might get too much for an abstract when multiple MPs are assessed in one study 2 not always possible to limitations in the maximum allowed amount of words. 3 INCLUDING THE UNDERPINNING MEASUREMENT MODEL 4 Important for evaluating quality of the and focus for the psychometric analyses 5 anything more than a list of what properties will be analyzed in a paper is likely too detailed for an abstract 6 I depends what do you mean by "description of the methods". I don't think that a "description" of the methods needs to be include, but at least mentioning the name of the methods yes for sure (just the name, without detail about how do they work). 7 I feel this is not going to be possible in an abstract. 8 often qualitative if sample size small (usually the case in a rare disease) 9 may make abstract exceed limits 10 If that is possible to keep it brief it could be too much information A6 Results 1 When multiple properties are studied, it is not always possible to report all MP and their results. 2 Some estimation of measurement uncertainty MUST be included. 3 summary of MP could be listed in abstract A7 Discussion/Conclusions 1 probably this is what most people read, so this should be mandatory 2 I find this less important for the abstract. I would focus in the abstract on clinical relevance and implications. 3 I suggest to only include a conclusion, as there is usually no space for main strengths and drawbacks an abstract. 4 It totally depends on the abstract word limit. If there is enough space, one could absolutely talk about what you have described above. Otherwise, a brief description of the main findings of the study and future direction would be enough. 5 Forget "need for future research." Every study says that; it's a meaningless phrase. 6 in abstract limit to conclusions; not discussion. 7 In most cases, this will need to be limited to 1-2 sentences at most within an abstract, but can be used to highlight key aspects of the study context. 8 This is too much for an abstract. The essence of the evaluation yes, but a detailed discussion is not possible. 9 properties in other contexts if they were evaluated e.g., other disease area, target sample, context 10 but only a very short section to help the reader to understand the results and what is relevant for the future I1 Name and describe the 1 agree with the statement: This information may also appear in the methods section in PROM of interest greater detail. 2 General information (construct to be measured, language) needs to be presented in the introduction, however, some items described above are more appropriate for the methods section. 3 I suggest to provide the scoring algorithm in the methods. 4 Essential for understand the targeted PRO measure 5 This is a multi-barreled question. :) of course it should include title, language, and the target construct, but the rest could be left to methods. 6 Yes, without methodological details, but it should be mentioned all basic description of the PROM. I find very important to mention if it's "reflective" or "formative", because it's often omitted - and quite likely making mistakes using 'reflective' techniques to validate 'formative' questionnaires. I think the reflective-formative description should be always there. 7 I am concerned that there is too much details in the introduction. No need to repeat it in the methods section. 8 Details should be provided in the Methods section. Here just a description of the importance, relevance of the instrument in general 9 There does need to be contextualization for the project and the PROM, but this degree of detail may be better served to methods sections 10 Goes in Methods 11 Reporting guidelines are a minimum set, not an optimal set. While some of the elements of this item meet this bar, some do not. It should be revised to be more consistent with a minimum reporting requirement, not an optimal one. 12 Only name, type and version are required in the Introduction 13 However it should be very general to help the reader to know what is already known, what is unclear in order to show the reader that there is a so called research gap what is relevant to research I2 Target population 1 to me that is method section 2 not in the Intro necessary 3 Because of invariance issues, should be clear to which population is applied. 4 Only the relevance of this instrument for this population 5 mention other samples MP may have already been explored in 6 Methods I3 Citation for the original 1 For profile instruments such as the SF-36, each subscale needs to be defined in itself development of the (see previous comment re validity) as well as in relation to the overall concept. PROM 2 Methods 3 Either in the introduction or in the Methods section 4 In an introduction the state of the art/ the science has to be reported I4 State of Knowledge & 1 current scientific knowledge should be mandatory in an introduction Rationale 2 "The authors should provide a literature review of all existing evidence." Authors should provide a summary of the available evidence of the MP under study. 3 including a rationale for the measurement approach selected 4 Existing evidence by version may be too much, unless there are substantial differences by version, which should be highlighted 5 lit review need not be exhaustive 6 A summary of all known MPs could be presented in table format. 7 Reader need background information in order to find out what this study will add to the current knowledge 8 As per earlier comment. Some text reflects essential, minimum reporting requirements, while some reflects optimal reporting, and therefore does not belong in a reporting guideline. 9 Previous research on the instrument should be given wither in Introduction or in Discussion (comparison with other studies). 10 A brief description and relevant citations are important but not necessarily an in-depth comprehensive explanation 11 Maybe not all evidence but the relevant ones and also maybe counterintuitive evidence or differences in studies I5 Definitions 1 maybe method is more appropriate? 2 method section 3 The detailed definition of the different measurement properties (e.g. internal consistency) should be reported in the methods 4 It depends on the terms. Some specialized terms are exclusively related to the methodology, then they do not need to be in the introduction. Only the Specialized terms related to the description of the instrument or its field of application. 5 or in the method section if not mentioned in the introduction 6 This can be done using a glossary if required 7 In the Methods 8 Methods 9 unclear what is meant by this I6 Objectives and 1 but the hypotheses as in 'hypotheses testing' is method section Hypotheses 2 There are often no hypotheses; simply questions (e.g., "What is the scale's reliability?") 3 what is the hypothesis except that it will have evidence for reliability and validity, and maybe responsiveness? 4 May not be formal hypotheses, but research questions. 5 This should be ".. related to the specific MPs of the PROM under investigation." 6 This is absolutely essential GM1 Study Design 1 make sure that this means: the study design as for this CLINIMETRICAL study into the MP and NOT the original design when the clinimetrical study is based on already collected data. 2 The design is irrelevant if you're looking at, say, internal consistency. 3 Sometimes more measurement properties are examined in one paper with various designs, which makes it difficult to state one single design. 4 But very short before starting the more detailed information to help the reader to know what to expect GM2 Participants 1 Mandatory, as psychometric properties are dependent on the population. 2 This is basic and fundamental. 3 Yes this should be consistent 4 Transparency is key; so not only what exactly but also the why GM3 PROM administration 1 Important to mention also if it was self-reported or not. 2 This part should be brief. 3 Before you may consider describing the PROM in details (if not in the introduction) 4 Absolutely, to allow full replication and to advise and support other researchers 5 Reporting guidelines should be minimum sets, not optimal sets. 6 Transparency is key; so not only what exactly but also the why GM4 Data collection 1 and how non-response and missing values are going to be treated - oh, now I see that procedures there is a question about missing below in the questionnaire ;). 2 This part should appear as well, but it should be brief. 3 I assume this includes any other PROMs or Instruments used in addition to the targeted PROM 4 As a minimum 5 intervention often not relevant in psychometric studies; follow up moments only for responsiveness 6 Transparency is key; so not only what exactly but also the why if possible however sometimes you have to make choices about how detailed you can be GM5 Power/sample size 1 This is not straightforward nor agreed. But sample size justification is required as some calculation level. 2 Power calculations are rarely (never?) required for these type(s) of analyses. Rather, it is a matter of estimation precision, not null hypothesis testing. 3 Often irrelevant. Power applies to hypothesis testing and, again, there often are no hypotheses. 4 Important for reader understanding of the statistical power of the study's planned psychometric analyses 5 power analyses for measurement property studies are poorly defined. 6 Power analyses will be challenging for most analyses. Agree that available rules of thumb should be included 7 Sometimes is possible, sometimes not. Power analyses is quite a vague analyses, with a lot of uncertainty and variability. I don't find it very relevant and it can be ignored. 8 definitely 9 power calculation not generally possible in the exploratory setting of a psychometric study. Sample size needs to be discussed 10 It depends on the type of tests. Some justification should be given. Rules of thumb are always problematic but sometimes indispensable. Providing a quote changes little. It does not make it more justified in the end. 11 A sample size calculation is often not necessary or possible. The authors should justify their sample sizes, though 12 I am not an expert in sample size calculation. In qualitative research you should use a purposeful representative sample GM6 Statistical analyses 1 The reporting of the statistical package is not requested in some journals 2 But once again there are no definitive guidelines for statistical cut-offs, which are ultimately arbitrary 3 Agree, but absolute statistical testing/interpretation should NOT be emphasized/encouraged. Also, types of reliability/-ies tested + applied methods specified (not just, e.g., ICC but also type of ICC spelt out in words). Validity (as well as other properties) requirements needs to spell out a priori (e.g., in methods section) including motivations and references - that is, it should be as clear and detailed as possible what is expected in order for the PROM to be considered valid (i.e., the less specified, the less strong the conclusions), and it must be recalled that any such evidence (construct/convergent/divergent/known groups validity) are no more than tentative and circumstantial. The best evidence is a clear description of the definition of the variable (measurand), its operational definition as it changes from less to more, and the connection between these aspects and its operationalization (i.e., the items). Without this, the rest is essentially no more than superficial... Descriptions of analyses should also be detailed enough to make a reasonable judgement of its appropriateness in relation to distributional properties, data levels, and study design. 4 Including the measurement structure of the items. This is necessary to inform clinical care 5 The purpose of each statistical test should be stated. I think much of science is moving away from statistical cut off criteria and toward reporting p values. This makes sense to me for statistical analyses. Starred significance tests for correlational analyses drives me batty, given the null. 6 This is not my expertise; so I do not now how detailed you should be. Furthermore there is an ongoing discussion (and research in our university) how important the p values actually are GM7 Missing data 1 Should be in a digital supplement 2 Absolutely follow the PROM instructions for dealing with this 3 missing data does not need to be dealt in a psychometric study, they bring information on the quality of the questionnaire and are therefore a MP per se 4 It depends on the type of instrument and construct. GM8 Post hoc analysis 1 This is applicable to intervention studies, rarely to studies of psychometrics. 2 It depends on how much 'post' these analyses are. If they are not part of the main research question, they can be mentioned just on the results section. 3 I think that when it is relevant to do such an analysis you state why you have done that and then also report about that GM9 Randomized controlled 1 CONSORT is for optimal presenting intervention trial results. The design to measure trial PROs properties should be optimized to measure the concepts of interest (e.g. reliability). Therefore these design aspects must be reported, that are relevant only, not the whole trial. 2 a brief summary with a ref is sufficient as this is not the design for this clinimetrical study 3 In my opinion, the information regarding the RCT has not be as detailed as given in the Consort statement. For example, the interventions and harms sections can be abbreviated. The randomisation and blinding procedures don't need to be reported. 4 Depends. If it is a secondary or pre-RCT analysis I do not think this is necessary, but should be reserved to the RCT report. 5 Totally irrelevant insofar as testing for psychometric properties. Doesn't matter if the data came from an RCT, cohort study, cross-sectional survey, or whatever. 6 It may also be acceptable to provide a citation to the appropriate clinical trial registry entry where this information can be located, rather than including it all in the manuscript itself. 7 If the main results of the clinical trial have been presented elsewhere, it may be sufficient to cite the separate publication. 8 It depends on what kind of validation of the PROM is going to be tested. In some PROMs validation the "causality" inference is often not important. 9 Only the CONSORT items that should be known in relation to THIS assessment. If the RCT was conducted primarily to assess the effectiveness of 2 interventions, why should the group outcome difference be reported? 10 Better to refer to a separate paper describing the outcomes of such a study 11 If data come from RCT but the psychometric study is a secondary analysis, not sure that all CONSORT info need to be provided in the psychometric report (vs reference to primary RCT publication) 12 CONSORT is about the results of clinical trial. the assessment of MP is a different objective and the CONSORT items don't necessarily apply 13 provide a citation or include in a supplement 14 IF this is secondary analysis from a published trial this may be available in original publication and should not be repeated here 15 Almost none of the study on measurement properties are RCTs. So I would not include any of the items relating to RCTs. 16 The most relevant so the question is how detailed you should be or is it possible to report on the headlines and make references to relevant literature? GM10 Observational study 1 See above. 2 a brief summary with a ref is sufficient 3 See above, the information doesn't need to be too detailed. 4 Same comment as for RCT 5 I don't think all suggested guidelines are always necessary. 6 Same comment as above, one should report only relevant items from that checklist. No necessarily ALL items. 7 Better to refer to a separate paper describing the outcomes of such a study 8 same comment as above 9 provide in a supplement 10 same comment as above. Some o this information would need to go into supplemental material 11 They should use the COSMIN checklist for all psychometric studies 12 The most relevant so the question is how detailed you should be or is it possible to report on the headlines and make references to relevant literature GM11 Other study design 1 a brief summary with a ref is sufficient 2 As above. 3 Guidelines are useful just as guidelines, not necessary they are always a must. 4 See above comments. To be used as guidance. 5 will make it too lengthy- provide in supplement/appendix 6 IF original study already published, just reference that study where presumably most of the data would be already. 7 They should use the COSMIN guidelines 8 The most relevant so the question is how detailed you should be or is it possible to report on the headlines and make references to relevant literature; in case of qualitative research some guidelines are not always adequate. As a researcher to have to think about what is relevant for your readers to understand what you have done an why GR1 Missing data 1 not in the general part, but for each MP different analyses could have been done, so the missings should be reported per MP not general 2 I suggest to only show the number of missing data. The explanation can briefly be included in the limitation section. 3 Put in digital supplement 4 Proactive detailing of how missing data would be managed is adequate in my opinion 5 As much as possible. (Although quite often we just end up assuming that they were "at random" regardless of the cause, but it's important to mention it and be transparent) 6 Yes this is essential for transparency and to cultivate good reporting practice 7 As a qualitative researcher you report in the methods about that and later on in the discussion but not in the results GR2 Participant/patient 1 but same as above, if for different MPs (slightly) different populations were included Characteristics this should be mentioned 2 May be consider the time needed to complete the PROM 3 This is a must GR3 Sample size 1 but again, if the number differs per MP, than the sample size per MP should be reported 2 Depends on whether samples are from the same population or not (if not, separate descriptions are needed) 3 Yes, this avoids misleading 4 that could be a n= in data tables 5 As a qualitative researcher I prefer to show as much methods details in the methods section so that the focus on the results section can be on the most important results. D1 MP evidence 1 Comparing estimates to references values is ok, but finally the interpretation of what is high or low or good or bad depends on the context. 2 Use the COSMIN criteria 3 Need to define good measurement properties 4 And this needs to be respecified in Methods. And the fact that results do not meet criteria should NOT be a reason for rejection/not publishing. 5 In the context of the measurement model selected 6 Authors should compare results to relevant criteria, but whether a property is "sufficient" depends on the study. Care needs to be taken in how this is stated because people take the results and report that a measure has been found to be "sufficiently valid"--assuming that that will be the case whenever the measure is used. I do agree that authors should weigh evidence and comment on its sufficiency in the current context. 7 The recommendation should provide resources regarding criteria for good measurement properties D2 Practical relevance 1 If appropriate to the particular objectives of the study. 2 may be hard to fit all of these in one paper---some of this may require separate samples and multiple papers, but perhaps its ok to just acknowledge all of the possible consequences of using a PROM are unknown based off of one study alone 3 This is one way to promote the use of PROMs D3 Strengths and 1 and these could differ between different MPs limitations 2 Absolutely D4 Generalizability 1 this may get an endless discussion. this is up to the next user of this PROM 2 In the context of the measurement model selected. This is critical or the whole process is mute 3 unless multiple populations were included, these statements likely do not represent the results of the study but instead the hopes of the authors 4 It is difficult to generalize the result of a PROM for a specific population. I observe an important problem here. D5 Instrument changes 1 Suggestions are OK, but only to be implemented in practice after another clinimetric evaluation 2 In principle my answer is YES, but it depends since it may relate to other factors, such as sampling issues. 3 Yes if the authors are validating an existing instrument or a cross-culturally adapted translation (because they cannot modify it unless it is considered a modification of the original PROM), but I disagree if they are developing a new instrument. There is no point publishing a poor instrument, so the author should better review their PROM and re-assess in an iterative process until it is adequate for the purpose. 4 Only really key modifications. Do not change instruments to much and to often D6 Future Research 1 Optional 2 Can be included if appropriate, but may not be required in all cases. 3 Sometimes is relevant, sometimes not. 4 Pointing out the issues that need to be addressed should be enough. The methodology to be used is not necessary. 5 There should be specific recommendations and not only a broad statement like "more research is needed" 6 This may be desirable, but is not part of a minimum set (which is the preferred approach for reporting guidelines) C1 Conclusions 1 Definitely, this will ensure that PROMs are not just used as a token 2 I prefer to do that in the discussion section and in the end conclusion only a sort of overall summary O1 Conflict of Interest 1 NOTABLY PROMIS involvement 2 This should probably go in a funding disclosure, acknowledgements section, or COI section, if the journal has one 3 previously has been describe in detail the PROM characteristics (authors, version, etc), and the "funding body" is usually requires to be mentioned in every output/product anyway. So to some extent the conflict of interests are already there - in implicit way. R1 PROM Administrations 1 Again: COSMIN has sorted out all this already 2 But also include specified analyses (e.g., type/s of ICC, alpha etc.) 3 The independence of the repeated administrations is always relevant. Reliability assessment should not be overestimated because the repeated applications were too close one to the other. The time between two applications should be justified. 4 Yes, good idea all these factors can influence uptake and completion 5 Some elements of this are part of a minimum set; others are part of an optimal set. 6 Transparency is key in order to give the reader sufficient information to make a decision about the quality of the research R2 Statistical analyses 1 See above 2 In the context of the measurement model selected. 3 Same as before. Cannot mix essential elements with those that are optimal or preferred. 4 Not my expertise but it should be possible for the reader to make a decision about the quality so sufficient relevant information is important R3 Methods to improve 1 Optional reliability 2 Not unless actually tested. Repeated measures WILL improve reliability/measurement uncertainty, but this is generally an experimental procedure unless repeated measures is part of the intended use of the instrument. 3 In the context of the measurement model selected. 4 these generally should be avoided or if they were used, listed as a potential limitation or qualification to the study 5 Possibly but this depends on the purpose of the assessment. For PROM, I am not sure what is meant by "training" if that is not related to the instruction given at the start of any PROM instruments. Recommendations for improvement of reliability should ideally be evidence-based. 6 This may be optimal, but I am not convinced it is part of a minimum reporting set. ME1 PROM Administrations 1 But for clinical applications and most research also responsiveness is important 2 This seems to be a slight duplication of the previous section. The focus should be on a single section summarising the practical implementation of measure completion 3 report of this information seems redundant with information cited for reliability; not clear to me under what circumstances you expect it to be different 4 There are too many issues to agree at the same time. The yes would be general, but should not be considered necessary for the whole. Measurement error does not need other instruments and must be based on independent measurements, so I disagree with the "if relevant". Also the question are very much repeated. Some MP are using the same data settings and that should be consistent within the same study. One option which is not addressed is whether the repeated administration is done at baseline of at follow-up because the variability of the values differ (in particular in the context of ceiling effects). 5 Are you asking if this information should be in the Reliability section or Measurement Error section? If so, I don't care about the location. 6 Be careful - this is still drifting towards an optimal set, rather than a minimum set ME2 Statistical analyses 1 But this depends on other aspects. If, e.g., basic properties are not met, this will be meaningless. 2 In the context of the measurement model selected. 3 This may come later in the survey, but other than the SDC, a threshold for meaningful change should be evaluated and reported. This is not just the smallest detectable change, but a change that is of a large enough magnitude that patients find the change meaningful to them. 4 Also, sometimes important to report conditional standard errors of measurement along the score scale 5 Again, you are mixing optimal reporting with minimum reporting. I think these items must differentiate between the two 6 Not my expertise but I think it is relevant IC1 Unit of measurement 1 Yes, but unidimensionality should not be over emphasized in terms of statistics, substantive/theoretical arguments are more valid (see above) 2 In the context of the measurement model selected. A unit is only interpretable with one measurement paradigm. This is critical for PROMs developed for clinical practice 3 Use model based approach to derive internal consistency (e.g., use structural equation modeling to derive Coefficient Omega, McDonald, 1999). This is a superior approach compared to coefficient alpha. 4 I'm unsure because internal consistency statistics are not always indicative of dimensionality. 5 Unidimensionality is important to be discussed/tested. 6 Unidimensionality needs a separate section 7 I think yes, report internal consistency stat. I don't think it is required that you report the assumptions associated with unidimensionality. Are you asking if I think both of these are required or is the text an example of what could be included? 8 Not part of a minimum set 9 depends, some scales have domain scores and total and report for specific scoring under investigation IC2 Continuous scores 1 Not clear what this actually refers to 2 In the context of the measurement model selected. 3 Be aware of limitations to alpha -- inflated with number of items, and requires scales to be parallel or tau-equivalent. 4 Cronbach's alpha should be avoided (I think at least) -- too many limitations 5 Though I think it is good to report these, explanation of what the statistic actually assesses should be stated. 6 not if a single item IC3 Dichotomous scores 1 Cronbach’s alpha is not relevant for dichotomous scores. 2 Same comment as above. 3 Cronbach's alpha should be avoided (I think at least) -- too many limitations 4 same issues as above IC4 IRT-based scores 1 Locations and SE should be reported for both persons and items. For items, expectations regarding item hierarchy (based on substantive reasoning/theory/construct equation, as well as comparisons (when available) with previous data should be reported along with an item/person map. 2 For Rasch-based scores....different reporting. this is why the context of the measurement model selected matters and is critical to this whole project 3 See Raju, etc al. 2007 (Applied Psychological Measurement) on a model for estimating CSEMs/reliability that works for CTT & IRT 4 I am lacking competence about the details in IRT-based scores 5 depends on circumstance CV1 Relevance 1 Rather in the eye of the beholder, but descriptive information is important 2 For new PROMS and possibly translations. 3 In the context of the measurement model selected. 4 Assists in developing a comprehensive validity argument. 5 It would also be useful to include any qualitative data that was collected prior to the initial drafting of the instrument items. 6 This would be useful practice to adopt 7 evidence of concept elicitation if available or at least evidence of testing relevance in target sample 8 Do you mean for studies evaluating content validity or for all studies of PROMs? I am answering questions assuming you mean all studies about PROMs. CV2 Comprehensiveness 1 For new PROMS and possibly translations. 2 Yes this would be useful 3 as above in content validity CV3 Comprehensibility 1 For new PROMS and possibly translations. 2 Include readability scores 3 I've hardly seen this discussed. Sometimes it is just assumed to be 'Comprehensible'. It would be interesting to mention in cases of target population with low health literacy, for example. 4 Good, these all affect PROM results CV4 Relevance results 1 For new PROMS and possibly translations. 2 yes, if this was part of the study. I accept that one study may not cover everything and therefore this may not be reported in some studies. CV5 Response options and 1 For new PROMS and possibly translations. recall period 2 yes, if this was part of the study. I do not think, for example, that it should be required to do interviews to find out if pain interference in the last week is relevant. In planning a study, the time frame most relevant to the goals of the study should be considered. 3 This would be useful CV6 Comprehensiveness 1 For new PROMS and possibly translations. results 2 yes, if this was part of the study. this is certainly ideal to include it when developing a measure, but not necessarily critical in a follow-up study 3 This duplicates what is written earlier re: relevance results 4 It is always important to know the perspectives of patients and professionals CV7 Comprehensibility 1 For new PROMS and possibly translations. results 2 If this is the origin paper for the measure, yes. I would not expect to be included in every study after that. 3 only mention in case that there are issues with it. 4 Yes, we often assume this. I have done work on checking patient understanding using cognitive interviews 5 Very important but also how you have researched whether patients understood of not the instructions etc. CV8 Qualitative methods 1 Only, if the whole qualitative research was aimed to develop/test the PROM and results 2 If relevant. Otherwise in parallel/other paper. 3 The guidelines are often over-kill. 4 ok but I wonder if that is not too detailed and complicated. It would be important to identify which parameters are common for 2 or more MPs and which are specific. 5 may be too lengthy- include as supplement/appendix 6 these do not easily apply to one on one cognitive interviews for this purpose 7 Coreq is not helpful for a types of qualitative research SV1 Conceptual framework 1 In the context of the measurement model selected. 2 Very important the discussion between formative and reflective. Need to justify that you have a reflective model before testing structural validity. 3 Not sure, would like to know more about this 4 depends 5 Reporting about assumptions is always important whether you use a framework (deductive) or whether you are inspired by theory (more inductive) SV2 Factor Analyses: 1 But hypotheses (if any - there should not be any...) should also be stated AND (this is Classical Test Theory probably the most important thing) rationale for conducting a PCA/EFA must be stated (CTT) PROMs (in reality this applies to situations where the investigator(s) don't know what they want to "measure") including rationale for choosing PCA vs EFA. 2 Be sure people know the difference between factor analysis and principal components analysis, and to never use the latter. 3 Caution should be taken when using exploratory factor analyses. In the past, disparate items (symptoms, impacts, treatment-related symptoms) have been put into an exploratory factor analyses that then combines those disparate items into a single scale. For FDA purposes, this type of scale will not be suitable for evaluation of treatment benefit/labeling. There must be conceptual underpinnings to each scale created and thus the selection of items to be put into an exploratory factor analysis. Symptoms combined only with symptoms. physical impacts combined only with physical impacts, and so on. The conceptual underpinnings and the rationale for which items are placed into an exploratory factor analyses should be clearly described. 4 It is sometimes useful to have multiple factor loadings for EFAs if models change substantially. Also, all factor loadings should be shown, not just above some cut value. 5 These methods provide inconclusive evidence, though. 6 as relevant 7 I think it is essential to differentiate between minimal and optimal reporting, and that a reporting guideline is intended to improve/ensure minimum reporting. SV3 Item Response Theory 1 If not RMT, authors MUST rectify why they chose an IRT model instead, since IRT (IRT) analyses models do not specify measurement requirements but instead model data. 2 Both measurement models are very different and should be respected as different cut offs. One is a statistically driven model, one is a conceptually-driven model 3 as relevant ConV1 Comparator 1 I'm not happy with still using the historical nomenclature of construct, criterion etc. instrument(s) validity. There are overlaps and every 'validation is a 'construct validation'. This makes researchers to think in boxes but in fact it is about accumulating evidence from useful perspectives. It is also a major problem, that the PROMs discussions in healthcare are disconnected from psychology and educational testing. The latest Standards by the AERA and APA 2014 are much more 'modern' and comprehensive. A PROM is a classical test to which the standards apply and this creates a lot of confusion. 2 But evidence for validity and reliability (in the relevant population) of the comparator instrument need to be presented. 3 A comprehensive description of the MPs would not be required; citations would be sufficient. 4 the citation of the instruments should be reported but not necessarily all the details concerning their measurement properties. ConV2 Comparator Group(s) 1 the sample sizes in my opinion should be reported for EACH MP. E.G. FOR RELIABILITY THERE MIGHT BE A DIFFERENT 'n' as compared to the 'n' for the measurement error. so I don’t think there is one 'n' (could be the case, but very often not), but an 'n' per MP 2 If applicable ConV3 Hypotheses 1 plus the 'n' (and this is for each MP) I will not include this comment for the other MPs 2 Expectations need to be expressed explicitly and A PRIORI (not OK with psychometric/MP interpretations after the fact). 3 In the context of the measurement model selected. 4 When appropriate. Not appropriate if looking at internal consistency, for example. 5 direction and magnitude are not always known a priori 6 In principle yes. A specific expected magnitude is typically hard to state. ConV4 Statistical analyses No comments from the panels

ConV5 Result 1 also a priori define what % of hypothesis need to be confirmed for adequate construct validity CriV1 Criterion 1 There is RARELY a gold standard available against which to test PROs. Therefore we rely more on concurrent and discriminant validity tests, as well as looking at known groups, and those should be described and reported. 2 Too many elements are included in this item - some are optimal, some are minimal. 3 transparent about the what and how are important but also stay open and do not try data to fit in a scheme which is not actually fitting; this is a remark essential for a lot of items here CriV2 Continuous scores 1 ROC analyses are typically not applicable.

CriV3 Categorical scores 1 Use the STARD 2015 guideline if this applies 2 If applicable 3 It is rare that I have seen PRO measures dichotomized, but if they are, then details of this should be reported with a rationale for the dichotomization. 4 if applicable (if scores are categorized). But no need to categorize all instruments. 5 Dichotomization should be carried out with extreme care. Better use model for polytomous data. 6 depends on the hypothesis and what the test is evaluating HT1 Hypothesis 1 If applicable 2 Again, not always necessary or appropriate. The aim of the study may be to estimate this. 3 and relevant transition items reported by patients 4 this may not always be available in cross-sectional studies and may vary by context 5 not sure what this is asking or the circumstances of the change scores (responsiveness or score interpretation?) HT2 Direction of effect 1 Yes in case of CTT - but still dubious... 2 Same as above, if exploratory. HT3 Magnitude of effect 1 If applicable. Either is dubious in case of raw total scores. 2 Again, may not know and the purpose of the study is to determine this. HT4 Comparator 1 If applicable, but still of limited value instrument(s)

HT5 Comparator 1 referenced I would say instrument 2 All MP or all relevant MP? measurement 3 References should be reported for the comparator instruments, but would not properties recommend taking the space to report on their known measurement properties. 4 Full description of measurement properties may be too much, especially in situations where there are multiple other instruments, references to relevant psychometric information is sufficient 5 Citations would be sufficient 6 If available 7 Could be a space problem. 8 This is optimal, not minimal. Resp1 Comparison 1 this is important information but suppose the comparator is the sf-36... there should be Instrument(s) a balance between full information and readability, maybe this could be summarised in tables or appendices. 2 For responsiveness, a comparison instrument is not necessary, in my opinion. I suggest to include an additional item: Statistics used to support responsiveness, e.g. Effect sizes or SRM 3 In the context of the measurement model selected. 4 Just report the constructs it measures and citations - no need to report its measurement properties. Only report its structure if that is relevant to the analyses being performed (e.g., if a selected domain from a larger instrument is being used as the comparator, then the instrument's domain structure should be described) 5 see previous comment 6 This information could be given in 'supplementary information' rather than the main body of text 7 Could be a space problem. 8 clinical measures are often used 9 report the properties OR provide a reference to where this is 10 for those used in the analysis 11 only the relevant ones? you always have to make choices about how detailed the description has to be Resp2 Measurement 1 In the context of the measurement model selected. procedures 2 not sure what this question is asking Resp3 Interim period 1 if relevant should be reported but if there were events, analysis considerations should be made to use available data or potentially longitudinal models that can include covariates or predictors Resp4 Intervention/Exposure 1 these may or may not be captured in certain observational studies

Resp5 Patients changed 1 In the context of the measurement model selected. One measurement model can handle this 2 May not be relevant to all responsiveness evaluations Resp6 Subgroups 1 It is important that the correct statistics is used for responsiveness. In our last meta- analysis 85% of the articles reporting responsiveness could not be included because of incorrect statistics (effect size) 2 depending on study may not be sufficient numbers or power to address subgroups. For rare diseases this may be an impossible task End Overall Comments 1 I'm not happy with still using the historical nomenclature of construct, criterion etc. Question validity. There are overlaps and every 'validation is a 'construct validation'. This makes researchers to think in boxes but in fact it is about accumulating evidence from useful perspectives. It is also a major problem, that the PROMs discussions in healthcare are disconnected from psychology and educational testing. The latest Standards by the AERA and APA 2014 are much more 'modern' and comprehensive. A PROM is a classical test to which the standards apply and this creates a lot of confusion. 2 once more, make a distinction in sample size (general) and sample size, missing data etc per MP 3 In my opinion, in the explanation of the guideline it should be stated, that it is not mandatory to investigate all measurement properties, as the investigation depends on the study design. Thank you very much for inviting me to be part in your Delphi study. I would be happy to answer further questions and support your project. Kind regards, Miriam Marks 4 Not very exciting. We know all this already. I do not understand why you needed another survey. 5 There is a clash of paradigms in the intent to combine CTT, RMT and IRT in the same document, and this complicates things to the extent that questions sometimes are difficult or impossible to answer. I suggest dividing the document into three (possible 2) separate ones. 6 It appears that this project has not emphasized the measurement models of the tools and the evolution of using modern measurement methods. This is an opportunity to put this at the forefront, explain ALL three measurement models, and have check lists for all three- with CTT at the back end- given its antiquity and lack of clinical applicability. 7 no further comments 8 Some of my answers to questions would vary depending on whether the study in question was the origin study for a measure or a follow-up study. More qualitative analyses would be expected in the former. 9 refer to COSMIN checklist 10 These are very useful and important measurement criteria which will further the use of PROMs in the scientific community 11 In IRT: specific information on the targeting. Not sure whether it was mentioned explicitly. 12 Due to word limit, it may not be possible to report the content validity according to all the elements described in this survey. 13 I think this is well done and thorough, but too many items had too many parts, which meant that it was not easy to answer "yes" or "no", when some elements were part of a minimum set, and others part of an optimal or preferred set. It is better to clarify your intention - my advice would be to follow CONSORT guidance and have the goal be a minimum set, not an optimal set, for greater buy-in and adherence. 14 I hope my comments were useful. Guidelines are perfect fore improving quality however sometimes people use these as a checklist and do not anymore really critically think about their work; their is never a one size fits all solution.

Disclaimer: The [views, statements, opinions] presented in this report are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute® (PCORI®), its Board of Governors or Methodology Committee.

Acknowledgment: Research reported in this report was funded through a Patient-Centered Outcomes Research Institute® (PCORI®) Award (ME-1606-35556). Further information available at: https://www.pcori.org/research-results/2016/creating-recommendations-types-data- present-patient-reported-outcome-measure

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