A systematic review of psychometric properties of physical fitness and physical functioning outcome measures applied in adult people with hemophilia

Authors

  • Pierrette Baschung Pfister Directory of Research and Education, Physiotherapy-Occupational Research Center, University Hospital Zurich - Switzerland
  • Andrea Bärlocher Directory of Research and Education, Physiotherapy-Occupational Research Center, University Hospital Zurich - Switzerland
  • Anne Juanós Solé Department of Physiotherapy and Occupational Therapy, University Hospital Zurich, Zurich, Switzerland
  • Ruud H. Knols Directory of Research and Education, Physiotherapy-Occupational Research Center, University Hospital Zurich - Switzerland and Department of Health Sciences and Technology, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich - Switzerland
  • Nadja Pecorelli Directory of Research and Education, Physiotherapy-Occupational Research Center, University Hospital Zurich - Switzerland https://orcid.org/0009-0001-1340-7972
  • Eling de Bruin Department of Health Sciences and Technology, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich – Switzerland, OST – Eastern Swiss University of Applied Sciences, Department of Health, St. Gallen - Switzerland and Division of Physiotherapy, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm - Sweden https://orcid.org/0000-0002-6542-7385

DOI:

https://doi.org/10.33393/aop.2026.3928

Keywords:

Adult hemophilia, Outcome assessment, Physical fitness, Physical functioning, Psychometric properties, Systematic

Abstract

Introduction: Psychometric properties of clinical measurement instruments are crucial because they indicate quality, reliability, and validity of data collected in clinical settings as well as how accurately and consistently a tool measures change. The aim was to systematically review and report the measurement properties of performance-based (PerFOMS) or clinicianreported (ClinROM) outcome measurement instruments (OMIs) in adult people with hemophilia (PwH). The second aim was to evaluate the methodological quality and the level of evidence of the reported measurement properties.
Methods: Data search, extraction, and evaluation were conducted in accordance with the COSMIN methodology while following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
Results: The literature search identified 2557 articles. After title and abstract screening, 166 were included for full-text screening. The 14 included studies reported measurement properties of 11 OMI’s (5 ClinROM & 6 PerFOMS). Reliability (intra-rater, inter-rater, or test-retest), measurement error, internal consistency, criterion validity, convergent validity, discriminant validity, and responsiveness were reported. The most reported measurement property was convergent validity. The OMI Hemophilia Joint Health Score (HJHS 2.1) fulfilled sufficient methodological quality for convergent validity and moderate Quality of Evidence (QE). None of the other included OMI’s reported sufficient measurement properties.
Conclusion: Researchers and clinicians are challenged when comparing studies and selecting appropriate OMI’s when evaluating the functioning of adult PwH, due to unsatisfactory reporting of measurement properties, hampered methodological quality, and a low level of evidence. Therefore, studies investigating measurement properties of ClinROM and PerFOMS in adult PwH with rigorous methodology are required.

What’s already known about this topic ?

  • For physical fitness and physical functioning outcome measures, there is still limited consensus on the most appropriate measures for tracking long-term physical sustainability, and tools may not effectively distinguish differences at mid-to-high levels of physical capacity in adult people with hemophilia (PwH).

What does the study add?

  • This study gives a comprehensive overview of the measurement properties and the quality of evidence of performance-based and clinician-reported outcome measurement instruments (OMIs) assessing physical fitness and physical function in adult PwH.

Introduction

Hemophilia is a rare bleeding disorder affecting primarily men with an estimated worldwide prevalence of 29.6 cases per 100 000 males (1). It causes prolonged bleeding, especially in hinge joints, leading to joint inflammation, arthropathy, and muscle problems (2). These issues result in pain, limited range of motion, and weaker muscles, which can promote a sedentary lifestyle. This inactivity further reduces cardiovascular fitness, proprioception, bone health, overall fitness, quality of life, and increases the risk of falls (3-9).

Exercise for adult people with hemophilia (PwH) is safe and has the potential to counteract these health issues, with evidence showing that exercise can improve range of motion, muscle strength, endurance, balance, proprioception, and bone mineralization (2,4,10). A Cochrane review revealed positive effects of exercise without accompanying adverse effects. Nevertheless, the review authors considered their results cautiously because the number of included studies was small, with considerable heterogeneity in outcome measures. This Cochrane report could not pool results and draw definite conclusions regarding the effects of exercise programs in adult PwH (11).

To evaluate the treatment effects of physical exercise programs in adult PwH, assessments with acceptable psychometric measurement properties are required. Otherwise, it cannot be determined whether treatment is (in-) effective, or rather the assessment applied is inadequate for assessing change. The COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN) taxonomy distinguishes three domains of measurement properties: reliability, validity, and responsiveness (12,13).

To date, there is no consensus as to which assessments are most adequate for evaluating changes in physical fitness and physical functions in adult PwH. Physical fitness, defined as “the capacity of an individual to carry out daily tasks with vigor and alertness”, is operationalized as “a set of measurable health and skill-related attributes” such as muscle strength, balance, flexibility, and endurance (14). Physical function is defined as the capacity of an individual to carry out physical activities of daily living such as standing up from a chair or walking (15). The validity, reliability, and responsiveness of assessments that are used in adult PwH have been criticized for being insufficiently described (16). De Kleijn et al. suggested developing a new core set of clinimetric instruments to assess functional health status (17); however, such a set of measures remains to be defined (2).

A first step towards determining recommendable outcome measurement instruments (OMIs) in adult PwH is conducting a systematic review of existing literature to uncover measurement properties of OMIs used.

Several systematic reviews evaluated measurement properties of OMIs in adult PwH (18-23). However, none of them provides an overview of the measurement properties of performance-based and clinician-reported OMIs that evaluate physical fitness and physical function in adult PwH.

The aim of this systematic review is to investigate the measurement properties (reliability, validity and responsiveness) of performance-based and clinician-reported OMIs assessing physical fitness and physical function in adult PwH, as well as to evaluate the methodological quality of the studies and the level of evidence for the measurement properties.

This PROSPERO-registered study (registration number CRD42023311199) was conducted according to the COSMIN methodology and followed the PRISMA guidelines (24-26).

Search strategy

A comprehensive search strategy was developed in cooperation with a professional librarian. Electronic database searches of MEDLINE, EMBASE, CINAHL, Cochrane, PsycINFO, Scopus, PEDRO, and COSMIN were performed between February 25 and April 1, 2022. An update by the librarian was performed in August 2023, and a hand search was performed in November 2025. Key search terms were defined using two individual search filters for the population (hemophilia) and the measurement construct (physical fitness and physical function). These individual filters were combined with an adapted COSMIN search filter for measurement properties recommended by Terwee et al. (27).

Inclusion and exclusion criteria

Included were [1] studies containing hemophilia-specific and generic performance-based outcome measures (PerFOMs) or clinician-reported outcome measures (ClinROMs) aiming to measure physical fitness and physical function (e.g., strength, endurance, range of motion, coordination, balance, postural control, or gait), [2] when the study sample included a mean age of at least 18 years old PwH, [3] in case the aim of the study was to evaluate one or more measurement properties and [4] studies published as an original article in full text written in English or German.

Studies were excluded if they [1] only used PerFOMS or ClinROMS as an OMI (e.g., randomized controlled trials) without evaluating measurement properties, [2] used PerFOMS or ClinROMS to validate other instruments, or [3] only included PROMS or laboratory values.

Study selection

Search results were exported to EndNote 20 (Clarivate, Philadelphia, USA), where duplicate articles were removed. Article titles and abstracts were screened independently by one of three reviewer pairs (AJS&PBP, NP&RHK, PBP&RHK). Disagreements were discussed until a consensus was reached. Full-text articles were reviewed when the title or abstract did not provide sufficient information to discern eligibility. The same reviewer pairs performed full-text screening and discussed differences. If consensus could not be reached, a third reviewer (NP or PBP) was consulted. A manual search of the references in the included articles was performed, and eligible articles were included following the process described above.

Data extraction

Data were extracted by two pairs of reviewers (PBP&AJS, NP&RHK), using a prepared table (25). Extracted information included the country of the performed study, study aim(s), study design and setting, name and version of the evaluated OMI, construct measured by the OMI, characteristics of the raters (profession, professional experience, and training for the OMI), inclusion and exclusion criteria, sample size, patient characteristics (age, type and severity of hemophilia, bleeding history, and medication), the evaluated measurement properties, and the study results.

Process to evaluate measurement properties

The stepwise procedure to evaluate the measurement properties is shown in Figure 1.

Methodological quality (COSMIN Risk of Bias checklist)

The methodological quality of each included study was evaluated by two independent reviewers (AB&PBP) using the COSMIN Risk of Bias (RoB) checklist. The COSMIN RoB checklist was used as a modular tool, and scores were determined by consensus (24,28).

Structural validity, cross-cultural validity, convergent validity, and discriminative validity or known-groups validity were considered as separate measurement properties. The measurement properties of reliability were defined as follows: 1) test-retest reliability if the rater does not play a role, e.g., PROMs, or if there is no information about the rater; 2) inter-rater reliability as reliability between different raters, including the distinction between scoring and administration; 3) intra-rater reliability as reliability based on repeated measurements by the same rater. As PROMS are excluded, criterion box 1 “PROM development” was not used in this systematic review.

Each item of a criteria box was scored as “very good”, “adequate”, “doubtful”, “inadequate”, or “not applicable”, according to the RoB checklist. The RoB of each measurement property reported in an article was determined as the lowest rating of any standard in that criteria box (the worst-score-count method) (24,25).

Criteria for good measurement properties

The results of measurement properties reported in the selected articles were evaluated according to the criteria of good measurement properties as “sufficient”, “insufficient”, or “indeterminate” by two reviewers (AB&PB) (29). The final rating was determined by consensus. To determine whether construct validity (convergent validity, discriminative validity) and responsiveness (construct approach) were “sufficient” or “insufficient”, the hypotheses regarding correlations between the OMI of interest and the corresponding comparator instruments, as well as hypotheses regarding differences between groups (e.g. healthy control group compared with adult PwH), subgroups (e.g. different severity, age groups), or changes over time (before and after intervention) had to be reported in the selected articles. The rating “indeterminate” was given for no reported hypothesis.

Summary and quality of evidence

The evidence of the measurement properties was summarized for each OMI separately. If different studies evaluated the same OMI measurement property, results were qualitatively summarized and compared against the criteria for good measurement properties to determine whether the overall measurement property of the OMI was “sufficient”, “insufficient”, “inconsistent”, or “indeterminate”. To decide if the measurement properties of construct validity (convergent validity, discriminative validity) and responsiveness (construct approach) were sufficient or not, the review team formulated a set of hypotheses for studies that did not describe a priori hypothesis (24). For convergent validity, the review team developed a grid visualizing the expected correlations between the evaluated constructs of the OMIs of interest and those of the used comparator instruments. The comparator instrument was rated “high quality” if there was reported information about validity and/or responsiveness in any study population.

Separate hypotheses for subscales were only formulated if there was information regarding the measurement properties for the subscales. The interpretation of the correlation coefficients used to formulate the hypothesis was determined as: low or very low (0-0.25), low (0.26-0.49), moderate (0.50-0.69), high (0.70-0.89), very high (0.90-1.00) (30). Where possible, the review team also formulated a hypothesis for discriminative validity. In cases without any described expectations of differences between the groups or subgroups, or if the review team was unable to formulate a good hypothesis because the minimal important change was unknown, the respective results were ignored as proposed in the COSMIN methodology. Hypotheses for responsiveness were formulated analogously (expected correlation with comparator instruments, expected group/subgroup differences, and/or expected changes over time). The study results were then compared against the retrospectively defined hypotheses. If at least 75% of all results were in accordance with the hypothesis, the measurement property was deemed “sufficient”. If, within one study, the OMI of interest was compared with different comparator instruments or if different groups/subgroups were compared, the worst-score count method was applied for the RoB of convergent and discriminative validity.

Figure 1 -. Flow chart search results and screening process. COSMIN: (COnsensus-based Standards for the selection of health Measurement INstruments) GRADE: Grading of Recommendations, Assessment, Development and Evaluation

Point estimates were considered, and confidence intervals were ignored to rate correlation coefficients for convergent validity and intraclass correlations for reliability. The reason for this is that not all authors presented confidence intervals, and we intended to apply a uniform approach, in addition to avoiding harsher judgment in those instances where confidence intervals were given.

The modified GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach was used to define the summarized results. Quality of Evidence (QoE) indicates the extent of confidence that the evidence is trustworthy. QoE is based on [1] overall RoB (quality and number of the studies), [2] inconsistency (of the results of the studies), [3] imprecision (total sample size of the studies), and [4] indirectness (evidence from different populations than the population of interest). QoE was evaluated as “high”, “moderate”, “low”, or “very low”. Reviewers AB&PBP rated QoE, with disagreements resolved by consensus (31). The definition of the quality levels and the downgrading process is shown in Appendix 4. All results, their ratings, and the grading of the evidence were finally summarized in Summary of Findings (SoF) Tables.

Results

The literature search (initial search and update) identified 3335 articles, of which 2557 remained after duplicates were removed. After screening titles and abstracts, 116 articles were included for full-text screening. Fourteen articles met the inclusion criteria and were included in the systematic review (Fig. 2).

The measurement properties of eleven different OMIs were investigated in the included articles: five ClinROMS (Colorado Adult Joint Assessment Scale (CAJAS), the Functional Independence Score in Hemophilia (FISH), and three versions of the Hemophilia Joint Health Score (HJHS 1.0, HJHS 1.0short, HJHS 2.1)) and six PerFOMS (Four Square Step Test (FSST), M3 diagnosis (SCHNELL®), Microsoft Kinect V2 sensor, Three-Dimensional Gait Analysis (3DGA), Timed Up and Go (TUG), and Short Physical Performance Battery (SPPB)). Constructs included: Joint health and gait (32-39), functional independence in self-care, transfers and locomotion (40, 41), voluntary maximal isometric muscle strength (42), and gait and joint function (43), dynamic balance (44), mobility (44), and a combination of lower extremity function, mobility and risk of falling (44). Four articles (33, 34, 37, 45) reported that the included professionals (mostly PTs) were “experienced,” and four articles (34-37) stated that a training session or instruction manual was given.

A summary of the descriptive characteristics of each included study (inclusion and exclusion criteria, sample size, patient characteristics (age, type and severity of hemophilia, bleeding history, and medication), and characteristics of the raters (profession, professional experience, and training for the OMI)) is given in Table 1. A total of 948 adult PwH and 157 healthy controls were included in the review. In seven studies, the age of some patients was lower than 18 years (33-36, 38, 40, 41). However, as these studies also included patients over 18 years of age and reported a mean age of 18 years or above, we included them in our systematic review. Sample sizes were between 10 and 240 individuals, and two articles evaluated the same study sample (32, 39). Table 2 describes the evaluated OMIs and the underlying constructs.

Methodological quality and Measurement Properties

An overview of the COSMIN RoB checklist scores and the measurement properties is presented in Table 3. The most frequently evaluated measurement property is convergent validity, which was mostly rated as “doubtful”. In total, 28 different comparator instruments were used to assess convergent validity. For discriminant validity, values from adult PwH were compared with those from healthy controls, and comparisons of 18 different subgroups were analyzed. The most evaluated subgroups were severity groups. Only one study (37) reported hypotheses regarding correlations between the OMI of interest and the comparator instruments or expected subgroup/group differences. The results were in accordance with the hypothesis and therefore rated as “sufficient”. The convergent and discriminative validity of all other studies was—due to the missing hypothesis—rated as “indeterminate”. Reliability was examined nine times, with methodological quality rated as doubtful eight times. The most common reasons were that the authors did not document whether the patients were stable between the repeated measurements and/or did not supply enough information about whether the raters were blinded to the scores or values of other repeated measurement(s) in the same patients. In one case, the methodological quality was rated as inadequate because a time interval of 18 ± 5 weeks (range: 13-33) was deemed to be too long to assess reliability (43). As the minimal important change of the evaluated OMIs was not defined, measurement errors were deemed “indeterminate” for all cases. Internal consistency depends on structural validity, and its QoE cannot be higher than that of structural validity. Because of the lack of information on structural validity for the OMIs of interest, internal consistency was rated as “indeterminate”. One study evaluated criterion validity and had a very high methodological quality, but the rating was “indeterminate” since no correlations with the gold standard were analyzed (45). Responsiveness was only evaluated for CAJAS, and no hypothesis was formulated; consequently, the study had to be rated “indeterminate”. No studies evaluated content, structural, or cross-cultural validity of an evaluated OMI. Also, the criterion approach for responsiveness had not been assessed.

Figure 2 -. Flow chart search results and screening process. n: number, OMI: Outcome Measurement Instrument

Table 1 -. Summary of the descriptive characteristics of the included studies

Table 2 -. Description of the evaluated OMIs

Table 3 -. Methodological quality

Summary and quality of evidence

The findings are summarized in a Summary of Findings table (SoF table) per OMI (Table 4). Only two OMIs were evaluated in more than one study: HJHS 2.1 was evaluated in four different studies (33, 35, 37, 38) and FISH (7 activities) in two different studies (40, 41). Regarding convergent validity, only St. Louis et al. formulated hypotheses (37). To perform a uniform assessment of all studies, the review team adapted those hypotheses to fit into the developed grid. Thus, all hypotheses mentioned in the SoF tables are formulated by the review team based on the same assumptions. The described QoE is only valid for the specific population described in the last column.

CAJAS, HJHS 1.0 (total score), HJHS1.0short (total score), and M3 diagnosis have “sufficient” reliability and convergent validity, but the QoE of all these measurement properties is “very low”. HJHS 2.1 has also “sufficient” reliability and convergent validity. QoE for convergent validity is moderate, and that of validity is “very low”. FSST has “sufficient” reliability, but the rating for convergent validity was “insufficient”. Twenty-five of 32 parameters of the 3DGA have “sufficient” reliability, and FISH (7 activities) has “sufficient” convergent validity. QoE for convergent validity and reliability of FSST, FISH (7 activities), and 3DGA is “very low”. All other measurement properties (54% of all 35 investigated measurement properties) were rated as “indeterminate”.

The main reason for downgrading the QoE in all investigated measurement properties was overall RoB, which means that the methodological quality and number of the included studies were low, except for the discriminative validity, which had “no” overall RoB in five studies and was only downgraded once by one point. Inconsistency was “not applicable” (because the measurement properties were only evaluated in one study), or the results were consistent. Imprecision, which is an indication of the sample size, had to be downgraded by 2 points in almost two-thirds of the studies, while “no” imprecision could be found in three studies. Indirectness was only relevant in a few studies.

Discussion

This systematic review included 14 articles evaluating five ClinROMS (CAJAS, FISH with 7 activities, HJHS 1.0, HJHS 1.0short, and HJHS 2.1) and six PerFOMS (FSST, M3 diagnos (SCHNELL®), Microsoft Kinect V2 sensor, 3DGA, SPPB, and TUG) in adult PwH. The most evaluated measurement property was convergent validity. The OMIs that showed at least moderate quality of evidence were the FSST (discriminative validity), HJHS 2.1 (internal consistency, convergent validity, and discriminative validity), SPPB (discriminative validity), and the TUG (discriminative validity).

Evaluated sample and external validity

The studies in our review were very heterogeneous regarding inclusion criteria, setting, and age. Most studies included adult PwH A or B, but some studies included only people with severe hemophilia or excluded people with mild hemophilia. The lower age limit varied considerably, from > 10 years to ≥ 18 years. We included studies with individuals with an age below 18 years; however, we required a mean sample age of at least 18 years, since the portion of PwH under 18 years could not be distinguished. As Stephenson et al. excluded all studies where data on those aged ≤18 years were not clearly distinguished from the adult data, we did not include studies that were already evaluated in the review by Stephenson et al. (46). Most studies included consecutive adult PwH attending the hemophilia comprehensive center or local hospital, but two studies included participants of a special event [downhill skiing trip (34) or hemophilia workshop (38)]. Therefore, the external validity of these results must be considered with caution, and results should be confirmed with studies including all types and severity stages of hemophilia to improve generalizability.

Included OMI and measured constructs

The included OMIs measure physical fitness and physical function. HJHS and CAJAS, primarily measuring the construct of joint health, were also included since attributes of physical fitness such as strength and flexibility are also part of joint health. Three OMIs included in our study have already been examined in previous systematic reviews: FISH and TUG were included in the review of Timmer et al. (23), and HJHS was included in the review of Gouw et al. (19). Both systematic reviews included only articles published before June 2016. Several assessments with variable underlying constructs were included because this has major advantages, such as capturing holistic health and addressing biologic variability of adult PwH (47). Conversely, however, heterogeneity of measurement instruments may challenge metric standardization and enhance methodological bias. Heterogeneity of assessments may be improved by establishing standardized core outcome sets for adult PwH; e.g., consensus-driven frameworks in which researchers in the area of PwH research agree on a minimum set of specific outcomes that should be measured and reported in clinical trials for this specific condition.

Table 4 -. Summary of findings

Timmer et al. revealed moderate QoE for hypothesis testing (convergent/discriminative validity) and limited evidence for reliability of the FISH (23). In contrast to their review, we did not adjust the COSMIN criteria for minimum sample size to 20 and therefore rated the QoE of all evaluated measurement properties of the FISH as “very low”. They included three articles (48-50) that reported on the TUG; none of them aimed to evaluate measurement properties. The only study assessing measurement properties of the TUG was published after 2016 (44).

Gouw et al. (19) concluded that the HJHS is the most extensively studied OMI to assess joint health and yielded moderate QoE for hypothesis testing (convergent and discriminative validity) in adult PwH. Although six articles evaluating the HJHS in 610 adult PwHs were published since their review, the level of evidence has not changed. The reason is that the RoB of all additional studies on convergent validity was “doubtful”. Consequently, overall RoB was downgraded by one level for HJHS 2.1 and by two levels for HJHS 1.0 and HJHS 1.0short, leading to moderate or very low QoE, respectively. As no study assessed structural validity following the COSMIN guidelines, we rated structural validity and internal consistency as “indeterminate,” and as the minimal important change of the HJHS is not known, we rated discriminative validity as “indeterminate.”

In accordance with our review, Stephensen et al. (46) identified the HJHS as the best-evaluated OMI in children with promising measurement properties, as we identified the HJHS 2.1 as the only OMI with a measurement property (convergent validity) with “moderate” QoE. The HJHS is the most widely used clinical tool to evaluate joint health and its impact on physical function in adult PwH. The HJHS 2.1 is the current standard. Since certain measurement properties of the older versions (HJHS 1.0 full and short version) were also examined, we have included these as well.

We included 11 OMIs measuring eight different constructs for adult PwH. Still, relevant aspects of physical fitness and physical function are not covered by those OMIs. Although aerobic capacity is crucial in adult PwH (51), no study could be found that included an OMI evaluating cardiovascular endurance, while Stephensen et al. found OMIs measuring maximal aerobic capacity in children with hemophilia (46). Zetterberg et al. (4) listed several additional constructs measured in hemophilia that are not covered in our review, such as endurance, proprioception, as well as joint range of motion and muscle strength for the mostly affected joints in hemophilia [knee, elbow, ankle, hip, and shoulder (52)]. The presently available OMIs for adult PwH do not reflect all elements of physical fitness and physical function, demonstrating a clear scientific gap.

For optimal use in daily clinical practice, point-of-care tests are most helpful and can save time and money (53). Three OMIs of this review (m3 diagnosis, 3DGA, Microsoft Kinect V2 sensor) need specific, high-cost equipment. This might be relevant for clinical studies. But for clinical use, there is a considerable need for more evidence for point-of-care tests. A recent study identified the following assessments of performance-based physical function that are practical in the clinical setting: the one-leg balance, tandem stance, 6-min walk test, timed up and down stairs, 30-s sit-to-stand, and timed up and go test (54). Our review reveals that none of these assessments has been sufficiently examined regarding their measurement properties in adult PwH.

Depending on the aim of the study, hemophilia-specific or generic instruments should be used. Hemophilia-specific instruments capture more micro-level data such as joint damage and are more responsive than generic instruments (55). On the other hand, generic tools are more suitable for comparisons with healthy controls or other patients with other, more common chronic diseases (56). Given these different objectives, it can also be assumed that their psychometric properties will differ.

Methodological quality and Measurement Properties

Terminologies in the field of measurement properties are very diverse, and the COSMIN methodology and definitions were only published in 2018 and 2020, respectively (24, 25). Especially for validity and responsiveness, different terms and definitions were used. The concept of reliability was used more homogeneously: although the terminology differed, the meaning was the same (relative reliability was used for consistency of measurement and evaluated with ICC, and absolute reliability was used for measuring standard error of measurement) (57). In this review, we adhered strictly to the COSMIN methodology. Measurement properties were specified according to COSMIN and, if necessary, renamed.

The most frequently evaluated measurement property is convergent validity, which was mostly rated as “doubtful”. This is explained by the fact that the methodological quality depends on the measurement properties of the comparator instruments. Since only a few of the comparator instruments had been evaluated previously in adult PwH, only a few studies reached the methodological quality “adequate”. In addition, very often QoE had to be downgraded by one or two levels due to the small sample size. However, four studies (32, 36, 37, 39) were able to include the recommended minimum of 100 participants.

In this systematic review, only one study evaluated criterion validity using the goniometer as the gold standard. Even though the reliability of the goniometer has been questioned, it is a commonly used instrument for measuring ROM in clinical practice and research and is often used as a gold standard (58-60). For many constructs such as joint health, joint function, or lower extremity function, a gold standard is missing, and criterion validity can therefore not be evaluated (12).

One important finding of the review is that the rating of internal consistency, measurement error, discriminative validity, and responsiveness had to be rated as “indeterminate” in all included OMIs. Although this rating has no relevance and cannot be interpreted, we included the results in the SoF tables. The reason is that this rating depends on other findings, such as structural validity and minimal important change (31). In other words, once this missing finding is known, the QoE can be derived using our SoF table.

Summary and quality of evidence

Quality of evidence (QoE) was predominantly very low or low (85%), with no high QoE ratings; only a few properties reached moderate QoE (15%). The HJHS 2.1 is the only OMI in adult PwH with one measurement property rated as sufficient (namely convergent validity) and at least moderate QoE, and may be recommended for use in research and clinical practice. All other OMIs have either “insufficient” or “indeterminate” ratings for the criteria for good measurement properties or “low” or “very low” QoE in this population. These results emphasize the need for more rigorous studies to validate existing OMIs measuring physical fitness and physical function in adult PwH. Current OMIs should be used cautiously, as their measurement properties and evidence supporting their use are generally weak, which could impact the validity of clinical outcomes and research findings.

Strengths and limitations of the review

Strengths of the current study are that our search strategy was open, and we did not use a preselection of OMIs by expert opinion. Independent analysis of the studies included by two investigators was given at all phases, and the COSMIN guideline was strictly followed. The scientific gaps are clearly displayed in the SoF tables. New evidence gained can simply be added, facilitating future reporting of an updated QoE of the included OMIs.

Our study also has some limitations. First, as we focused on measurement properties of physical fitness and physical function, feasibility and interpretability were neither evaluated nor discussed. Second, we also evaluated studies that included PwH who were younger than 18 years, as long as the mean of the included sample was at least 18 years. These different age cutoffs could bias our results. Third, we excluded PROMs from our review. Lastly, the studies included were heterogeneous; their methodological quality was mainly poor, and not all measurement properties were evaluated. In particular, content validity, which is supposed to be the most important measurement property, was never addressed (61). If a measure fails to assess what it intends to capture, evaluating other properties is meaningless. Content validity should therefore be evaluated in future studies.

Conclusion

Overall, through this review we were able to critically appraise, compare and summarize the measurement properties of 11 assessments reported in scientific literature that measure physical fitness and physical function in adult PwH. None of the included OMIs have sufficiently reported measurement properties, and the quality of evidence is mostly low or very low. The HJHS 2.1 is the most promising OMI with moderate quality of evidence for sufficient convergent validity. Due to the not satisfactory quality of the available studies and the retrieved QoE of the OMIs, and regarding the rating “indeterminate” for the criteria for good measurement properties in 54% of the studies, it remains challenging for clinicians to select appropriate instruments when assessing adult PwH. For researchers, it is difficult to compare studies with each other.

There is an identified need for reliable, valid, and responsive OMIs to evaluate physical fitness and physical function in adult PWH. Therefore, future studies should evaluate the measurement properties of OMIs such as FSST, SPPB, and TUG. Development of a reliable, valid, and responsive set of tests will allow future determination of the effectiveness of training programs which, in turn, may enhance the credibility and accountability of clinical interventions. We recommend following COSMIN reporting guidelines (62) when conducting future studies evaluating assessments in adult PwH.

Acknowledgments

The authors thank Dr. Martina Gosteli (Librarian at Zurich University) for performing the search strategy. Further thanks go to Dr. Anna Grynfeld Smith for proofreading the manuscript for English and structure. NOVO Nordisk Pharma AG, Zurich, Switzerland, is cordially acknowledged for their independent research grant.

Other information

This article includes supplementary materials

Corresponding author:

Eling D. de Bruin

email:

Disclosures

Conflict of interest: No potential conflict of interest was reported by the authors during any stage of this systematic review.

Financial support: The authors received a free research Grant for this systematic review from NOVO NORDISK PHARMA, Zurich, Switzerland.

Data Availability Statement: The data presented in this study are available as supplementary material to this article upon reasonable request.

Clinical Trial Protocol number: This study was registered at the International Prospective Register of Systematic Reviews (PROSPERO, registration number CRD42023311199).

References

  1. Iorio A, Stonebraker JS, Chambost H, et al.; Data and Demographics Committee of the World Federation of Hemophilia. Establishing the prevalence and prevalence at birth of hemophilia in males: a meta-analytic approach using national registries. Ann Intern Med. 2019;171(8):540-546. https://doi.org/10.7326/M19-1208 PMID:31499529 DOI: https://doi.org/10.7326/M19-1208
  2. Srivastava A, Santagostino E, Dougall A, et al. WFH guidelines for the management of hemophilia, 3rd edition. Haemophilia. 2020: 26(Suppl 6): 1-158. https://doi.org/10.1111/hae.14046 DOI: https://doi.org/10.1111/hae.14046
  3. Groen WG, Takken T, van der Net J, et al. Habitual physical activity in Dutch children and adolescents with haemophilia. Haemophilia. 2011;17(5):e906-e912. https://doi.org/10.1111/j.1365-2516.2011.02555.x PMID:21539696 DOI: https://doi.org/10.1111/j.1365-2516.2011.02555.x
  4. Zetterberg E, Ljungkvist M, Salim M. Impact of exercise on hemophilia. Semin Thromb Hemost. 2018;44(8):787-795. https://doi.org/10.1055/s-0038-1675381 PMID:30357762 DOI: https://doi.org/10.1055/s-0038-1675381
  5. Negrier C, Seuser A, Forsyth A, et al. The benefits of exercise for patients with haemophilia and recommendations for safe and effective physical activity. Haemophilia. 2013;19(4):487-498. https://doi.org/10.1111/hae.12118 PMID:23534844 DOI: https://doi.org/10.1111/hae.12118
  6. Forsyth AL, Quon DV, Konkle BA. Role of exercise and physical activity on haemophilic arthropathy, fall prevention and osteoporosis. Haemophilia. 2011;17(5):e870-e876. https://doi.org/10.1111/j.1365-2516.2011.02514.x PMID:21435116 DOI: https://doi.org/10.1111/j.1365-2516.2011.02514.x
  7. Wang M, Álvarez-Román MT, Chowdary P, et al. Physical activity in individuals with haemophilia and experience with recombinant factor VIII Fc fusion protein and recombinant factor IX Fc fusion protein for the treatment of active patients: a literature review and case reports. Blood Coagul Fibrinolysis. 2016;27(7):737-744. https://doi.org/10.1097/MBC.0000000000000565 PMID:27116081 DOI: https://doi.org/10.1097/MBC.0000000000000565
  8. Rehm H, Schmolders J, Koob S, et al. Falling and fall risk in adult patients with severe haemophilia. Hämostaseologie. 2017;37(2):97-103. https://doi.org/10.5482/HAMO-16-03-0009 PMID:27658358 DOI: https://doi.org/10.5482/HAMO-16-03-0009
  9. Boycott KM, Rath A, Chong JX, et al. International cooperation to enable the diagnosis of all rare genetic diseases. Am J Hum Genet. 2017;100(5):695-705. https://doi.org/10.1016/j.ajhg.2017.04.003 PMID:28475856 DOI: https://doi.org/10.1016/j.ajhg.2017.04.003
  10. Wagner B, Krüger S, Hilberg T, et al. The effect of resistance exercise on strength and safety outcome for people with haemophilia: a systematic review. Haemophilia. 2020;26(2):200-215. https://doi.org/10.1111/hae.13938 PMID:32091659 DOI: https://doi.org/10.1111/hae.13938
  11. Strike K, Mulder K, Michael R. Exercise for haemophilia. Cochrane Database Syst Rev. 2016;12(12):CD011180. PMID:27992070 DOI: https://doi.org/10.1002/14651858.CD011180.pub2
  12. de Vet HCW, Terwee CB, Mokkink LB, et al. Measurement in medicine: a practical guide. Practical guides to biostatistics and epidemiology. 2011: Cambridge : Cambridge University Press. https://doi.org/10.1017/CBO9780511996214 DOI: https://doi.org/10.1017/CBO9780511996214
  13. 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(4):539-549. https://doi.org/10.1007/s11136-010-9606-8 PMID:20169472 DOI: https://doi.org/10.1007/s11136-010-9606-8
  14. Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 1985;100(2):126-131. PMID:3920711
  15. Garber CE, Blissmer B, Deschenes MR, et al.; American College of Sports Medicine. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc. 2011;43(7):1334-1359. https://doi.org/10.1249/MSS.0b013e318213fefb PMID:21694556 DOI: https://doi.org/10.1249/MSS.0b013e318213fefb
  16. Stephensen D, Bladen M, McLaughlin P. Recent advances in musculoskeletal physiotherapy for haemophilia. Ther Adv Hematol. 2018;9(8):227-237. https://doi.org/10.1177/2040620718784834 PMID:30181843 DOI: https://doi.org/10.1177/2040620718784834
  17. De Kleijn P, Heijnen L, Van Meeteren NL. Clinimetric instruments to assess functional health status in patients with haemophilia: a literature review. Haemophilia. 2002;8(3):419-427. https://doi.org/10.1046/j.1365-2516.2002.00640.x PMID:12010444 DOI: https://doi.org/10.1046/j.1365-2516.2002.00640.x
  18. Boehlen F, Graf L, Berntorp E. Outcome measures in haemophilia: a systematic review. Eur J Haematol Suppl. 2014;76(s76):2-15. https://doi.org/10.1111/ejh.12369 PMID:24957102 DOI: https://doi.org/10.1111/ejh.12369
  19. Gouw SC, Timmer MA, Srivastava A, et al. Measurement of joint health in persons with haemophilia: a systematic review of the measurement properties of haemophilia-specific instruments. Haemophilia. 2019;25(1):e1-e10. https://doi.org/10.1111/hae.13631 PMID:30427100 DOI: https://doi.org/10.1111/hae.13631
  20. Holdsworth C, Bladen M, Harbidge H, et al. Measuring physical function capacity in persons with haemophilia: a systematic review of performance-based methods. Haemophilia. 2025;31(5):840-864. https://doi.org/10.1111/hae.70081 PMID:40685771 DOI: https://doi.org/10.1111/hae.70081
  21. Limperg PF, Terwee CB, Young NL, et al. Health-related quality of life questionnaires in individuals with haemophilia: a systematic review of their measurement properties. Haemophilia. 2017;23(4):497-510. https://doi.org/10.1111/hae.13197 PMID:28429867 DOI: https://doi.org/10.1111/hae.13197
  22. Szende A, Schramm W, Flood E, et al. Health-related quality of life assessment in adult haemophilia patients: a systematic review and evaluation of instruments. Haemophilia. 2003;9(6):678-687. https://doi.org/10.1046/j.1351-8216.2003.00823.x PMID:14750933 DOI: https://doi.org/10.1046/j.1351-8216.2003.00823.x
  23. Timmer MA, Gouw SC, Feldman BM, et al. Measuring activities and participation in persons with haemophilia: a systematic review of commonly used instruments. Haemophilia. 2018;24(2):e33-e49. https://doi.org/10.1111/hae.13367 PMID:29178149 DOI: https://doi.org/10.1111/hae.13367
  24. Mokkink LB, de Vet HCW, Prinsen CAC, et al. COSMIN Risk of Bias checklist for systematic reviews of Patient-Reported Outcome Measures. Qual Life Res. 2018;27(5):1171-1179. https://doi.org/10.1007/s11136-017-1765-4 PMID:29260445 DOI: https://doi.org/10.1007/s11136-017-1765-4
  25. Mokkink LB, Boers M, van der Vleuten CPM, et al. COSMIN Risk of Bias tool to assess the quality of studies on reliability or measurement error of outcome measurement instruments: a Delphi study. BMC Med Res Methodol. 2020;20(1):293. https://doi.org/10.1186/s12874-020-01179-5 PMID:33267819 DOI: https://doi.org/10.1186/s12874-020-01179-5
  26. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. https://doi.org/10.1136/bmj.n71 PMID:33782057 DOI: https://doi.org/10.1136/bmj.n71
  27. Terwee CB, Jansma EP, Riphagen II, et al. Development of a methodological PubMed search filter for finding studies on measurement properties of measurement instruments. Qual Life Res. 2009;18(8):1115-1123. https://doi.org/10.1007/s11136-009-9528-5 PMID:19711195 DOI: https://doi.org/10.1007/s11136-009-9528-5
  28. Elsman EBM, Mokkink LB, Terwee CB, et al. Guideline for reporting systematic reviews of outcome measurement instruments (OMIs): PRISMA-COSMIN for OMIs 2024. J Clin Epidemiol. 2024;173:111422. https://doi.org/10.1016/j.jclinepi.2024.111422 PMID:38849061 DOI: https://doi.org/10.1016/j.jclinepi.2024.111422
  29. Terwee CB, Mokkink LB, Knol DL, et al. Rating the methodological quality in systematic reviews of studies on measurement properties: a scoring system for the COSMIN checklist. Qual Life Res. 2012;21(4):651-657. https://doi.org/10.1007/s11136-011-9960-1 PMID:21732199 DOI: https://doi.org/10.1007/s11136-011-9960-1
  30. Munro BH. Statistical methods for health care research. 4th ed. Lippincott; 2001.
  31. Prinsen CAC, Mokkink LB, Bouter LM, et al. COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res. 2018;27(5):1147-1157. https://doi.org/10.1007/s11136-018-1798-3 PMID:29435801 DOI: https://doi.org/10.1007/s11136-018-1798-3
  32. Buckner TW, Wang M, Cooper DL, et al. Known-group validity of patient-reported outcome instruments and hemophilia joint health score v2.1 in US adults with hemophilia: results from the Pain, Functional Impairment, and Quality of Life (P-FiQ) study. Patient Prefer Adherence. 2017;11:1745-1753. https://doi.org/10.2147/PPA.S141392 PMID:29066870 DOI: https://doi.org/10.2147/PPA.S141392
  33. De la Corte-Rodriguez H, Rodriguez-Merchan EC, Alvarez-Roman MT, et al. HJHS 2.1 and HEAD-US assessment in the hemophilic joints: how do their findings compare? Blood Coagul Fibrinolysis. 2020;31(6):387-392. https://doi.org/10.1097/MBC.0000000000000934 PMID:32815914 DOI: https://doi.org/10.1097/MBC.0000000000000934
  34. Fischer K, de Kleijn P. Using the Haemophilia Joint Health Score for assessment of teenagers and young adults: exploring reliability and validity. Haemophilia. 2013;19(6):944-950. https://doi.org/10.1111/hae.12197 PMID:23730725 DOI: https://doi.org/10.1111/hae.12197
  35. Fischer K, Nijdam A, Holmström M, et al. Evaluating outcome of prophylaxis in haemophilia: objective and self-reported instruments should be combined. Haemophilia. 2016;22(2):e80-e86. https://doi.org/10.1111/hae.12901 PMID:26856807 DOI: https://doi.org/10.1111/hae.12901
  36. Funk SM, Engelen S, Benjamin K, et al. Validity and reliability of the Colorado Adult Joint Assessment Scale in adults with moderate-severe hemophilia A. J Thromb Haemost. 2020;18(2):285-294. https://doi.org/10.1111/jth.14651 PMID:31557391 DOI: https://doi.org/10.1111/jth.14651
  37. St-Louis J, Abad A, Funk S, et al. The Hemophilia Joint Health Score version 2.1 Validation in Adult Patients study: a multicenter international study. Res Pract Thromb Haemost. 2022;6(2):e12690. https://doi.org/10.1002/rth2.12690 PMID:35356667 DOI: https://doi.org/10.1002/rth2.12690
  38. 38. Uğur MC, Tamsel İ, Tat NM, et al. Investigation of the relationship between hemophilia joint health score and haemophilia early arthropathy detection with ultrasound score in hemophilic arthropathy. Turk Klin Tıp Bilim Derg. 2021;41(1):46-50. https://doi.org/10.5336/medsci.2020-78772 DOI: https://doi.org/10.5336/medsci.2020-78772
  39. Wang M, Batt K, Kessler C, et al. Internal consistency and item-total correlation of patient-reported outcome instruments and hemophilia joint health score v2.1 in US adult people with hemophilia: results from the Pain, Functional Impairment, and Quality of life (P-FiQ) study. Patient Prefer Adherence. 2017;11:1831-1839. https://doi.org/10.2147/PPA.S141391 PMID:29123383 DOI: https://doi.org/10.2147/PPA.S141391
  40. Poonnoose PM, Manigandan C, Thomas R, et al. Functional Independence Score in Haemophilia: a new performance-based instrument to measure disability. Haemophilia. 2005;11(6):598-602. https://doi.org/10.1111/j.1365-2516.2005.01142.x PMID:16236109 DOI: https://doi.org/10.1111/j.1365-2516.2005.01142.x
  41. Tasbihi M, Pishdad P, Haghpanah S, et al. A comparison between MRI, sonography and Functional Independence Score in Haemophilia methods in diagnosis, evaluation and classification of arthropathy in severe haemophilia A and B. Blood Coagul Fibrinolysis. 2016;27(2):131-135. https://doi.org/10.1097/MBC.0000000000000376 PMID:26218970 DOI: https://doi.org/10.1097/MBC.0000000000000376
  42. Herbsleb M, Tutzschke R, Czepa D, et al. Maximal isometric strength measures of the quadriceps muscles. Feasibility and reliability in patients with haemophilia. Hämostaseologie. 2010;30(suppl 1):S97-S103. PMID:21046058 DOI: https://doi.org/10.1055/s-0037-1619086
  43. Lobet S, Detrembleur C, Francq B, et al. Natural progression of blood-induced joint damage in patients with haemophilia: clinical relevance and reproducibility of three-dimensional gait analysis. Haemophilia. 2010;16(5):813-821. https://doi.org/10.1111/j.1365-2516.2010.02245.x PMID:20398067 DOI: https://doi.org/10.1111/j.1365-2516.2010.02245.x
  44. Taylor S, Pemberton S, Barker K. Validity of the four-square step test in persons with haemophilia. Haemophilia. 2022;28(2):334-342. https://doi.org/10.1111/hae.14482 PMID:35020243 DOI: https://doi.org/10.1111/hae.14482
  45. Mateo F, Carrasco JJ, Aguilar-Rodríguez M, et al. Assessment of Kinect V2 for elbow range of motion estimation in people with haemophilia using an angle correction model. Haemophilia. 2019;25(3):e165-e173. https://doi.org/10.1111/hae.13744 PMID:30994246 DOI: https://doi.org/10.1111/hae.13744
  46. Stephensen D, Drechsler WI, Scott OM. Outcome measures monitoring physical function in children with haemophilia: a systematic review. Haemophilia. 2014;20(3):306-321. https://doi.org/10.1111/hae.12299 PMID:24252123 DOI: https://doi.org/10.1111/hae.12299
  47. Chmelo EA, Crotts CI, Newman JC, et al. Heterogeneity of physical function responses to exercise training in older adults. J Am Geriatr Soc. 2015;63(3):462-469. https://doi.org/10.1111/jgs.13322 PMID:25752778 DOI: https://doi.org/10.1111/jgs.13322
  48. Baumgardner J, Elon L, Antun A, et al. Physical activity and functional abilities in adult males with haemophilia: a cross-sectional survey from a single US haemophilia treatment centre. Haemophilia. 2013;19(4):551-557. https://doi.org/10.1111/hae.12134 PMID:23574421 DOI: https://doi.org/10.1111/hae.12134
  49. Fearn M, Hill K, Williams S, et al. Balance dysfunction in adults with haemophilia. Haemophilia. 2010;16(4):606-614. https://doi.org/10.1111/j.1365-2516.2010.02200.x PMID:20331756 DOI: https://doi.org/10.1111/j.1365-2516.2010.02200.x
  50. van Genderen FR, Westers P, Heijnen L, et al. Measuring patients' perceptions on their functional abilities: validation of the Haemophilia Activities List. Haemophilia. 2006;12(1):36-46. https://doi.org/10.1111/j.1365-2516.2006.01186.x PMID:16409173 DOI: https://doi.org/10.1111/j.1365-2516.2006.01186.x
  51. Tomschi F, Ransmann P, Hilberg T. Aerobic exercise in patients with haemophilia: a systematic review on safety, feasibility and health effects. Haemophilia. 2022;28(3):397-408. https://doi.org/10.1111/hae.14522 PMID:35226779 DOI: https://doi.org/10.1111/hae.14522
  52. Luck JV Jr, Silva M, Rodriguez-Merchan EC, et al. Hemophilic arthropathy. J Am Acad Orthop Surg. 2004;12(4):234-245. https://doi.org/10.5435/00124635-200407000-00004 PMID:15473675 DOI: https://doi.org/10.5435/00124635-200407000-00004
  53. Sumita NM, Ferreira CES, Martino MDV, et al. Clinical applications of point-of-care testing in different conditions. Clin Lab. 2018;64(7):1105-1112. https://doi.org/10.7754/Clin.Lab.2018.171021 PMID:30146832 DOI: https://doi.org/10.7754/Clin.Lab.2018.171021
  54. Bladen M, Harbidge H, Drechsler W, et al. Identifying performance-based outcome measures of physical function in people with haemophilia (IPOP). Haemophilia. 2023;29(6):1611-1620. https://doi.org/10.1111/hae.14886 PMID:37840142 DOI: https://doi.org/10.1111/hae.14886
  55. Wiebe S, Guyatt G, Weaver B, et al. Comparative responsiveness of generic and specific quality-of-life instruments. J Clin Epidemiol. 2003;56(1):52-60. https://doi.org/10.1016/S0895-4356(02)00537-1 PMID:12589870 DOI: https://doi.org/10.1016/S0895-4356(02)00537-1
  56. Klamroth R, Pollmann H, Hermans C, et al. The relative burden of haemophilia A and the impact of target joint development on health-related quality of life: results from the ADVATE Post-Authorization Safety Surveillance (PASS) study. Haemophilia. 2011;17(3):412-421. https://doi.org/10.1111/j.1365-2516.2010.02435.x PMID:21332888 DOI: https://doi.org/10.1111/j.1365-2516.2010.02435.x
  57. Overend T, Anderson C, Sawant A, et al. Relative and absolute reliability of physical function measures in people with end-stage renal disease. Physiother Can. 2010;62(2):122-128. https://doi.org/10.3138/physio.62.2.122 PMID:21359043 DOI: https://doi.org/10.3138/physio.62.2.122
  58. Li MK, Robinson PM, van Rensburg L. Accuracy of patient-reported range of elbow motion. Shoulder Elbow. 2016;8(2):118-123. https://doi.org/10.1177/1758573215626104 PMID:27583009 DOI: https://doi.org/10.1177/1758573215626104
  59. Horsch A, Kleiber S, Ghandour M, et al. Validation of a new equinometer device for measuring ankle range of motion in patients with cerebral palsy: an observational study. Medicine (Baltimore). 2022;101(17):e29230. https://doi.org/10.1097/MD.0000000000029230 PMID:35512083 DOI: https://doi.org/10.1097/MD.0000000000029230
  60. Chapleau J, Canet F, Petit Y, et al. Validity of goniometric elbow measurements: comparative study with a radiographic method. Clin Orthop Relat Res. 2011;469(11):3134-3140. https://doi.org/10.1007/s11999-011-1986-8 PMID:21779866 DOI: https://doi.org/10.1007/s11999-011-1986-8
  61. Terwee CB, Prinsen CAC, Chiarotto A, et al. COSMIN methodology for evaluating the content validity of patient-reported outcome measures: a Delphi study. Qual Life Res. 2018;27(5):1159-1170. https://doi.org/10.1007/s11136-018-1829-0 PMID:29550964 DOI: https://doi.org/10.1007/s11136-018-1829-0
  62. Gagnier JJ, Lai J, Mokkink LB, et al. COSMIN reporting guideline for studies on measurement properties of patient-reported outcome measures. Qual Life Res. 2021;30(8):2197-2218. https://doi.org/10.1007/s11136-021-02822-4 PMID:33818733 DOI: https://doi.org/10.1007/s11136-021-02822-4

Most read articles by the same author(s)