Development of an Online Dance Injury Surveillance System (ODISS): A Delphi Consensus,Usability,and Feasibility Study

Abstract

Objectives:

To develop an optimal outline for an online dance injury surveillance system (ODISS) based on expert consensus from a Delphi survey and evaluate the system’s usability and feasibility within a fictional folk-dance academy setting.

Background:

Dance is characterized by intensive training and performance, which can elevate susceptibility to injuries. Robust surveillance systems are required to understand and mitigate this injury risk. Current systems exhibit limitations and lack uniformity.

Methods:

A Delphi panel of 35 stage 1 experts were recruited through snowball sampling from online professional networks, professional dance associations, organizations, and academies. Inclusion criteria were ≥18 years of age, fluent in English, and worked as dance academics or researchers, clinicians, instructors, managers, or competitive or professional dancers. These stage 1 experts were provided with a preliminary outline of a dance injury surveillance system that covered 6 domains: dancer demographics and screening, exposure monitoring, injury identification and classification, injury management, dancer recovery and system access. Stage 1 experts then voted on the importance of and provided feedback on different design elements within each domain across 2 Delphi survey rounds to determine a consensus system design outline. A pilot system was then developed and evaluated by stage 2 experts, who were end-users and included dance instructors and administrators from various dance academies/institutions recruited through direct invitations. These stage 2 experts utilized the System Usability Scale (SUS) and System Feasibility Measure (SFM) based on application to a fictional folk-dance injury scenario.

Results:

In survey round 1, the stage 1 experts reached consensus to include 30 elements and exclude 3 elements and demonstrated mixed opinion on 30 elements that were revised into 14 elements for further consideration in round 2. All but 1 element reached consensus to include after round 2. System testing demonstrated low marginal usability (SUS score: 58.2% ± 11.6%). Stage 2 experts agreed or strongly agreed the system was feasible for 86.7% ± 10.3% of SFM statement ratings. Key areas for improvement identified from stage 2 expert feedback were a need for an improved user interface and strategies to reduce data entry time burdens. A common suggestion was to integrate more dropdown and checkbox response options within the interface to increase efficiency of data entry.

Conclusion:

This study established a Delphi-consensus on the essential design elements for an ODISS. Expert evaluation resulted in a usable and feasible online system that can be used to improve future dance injury surveillance research across dance populations.

Level of Evidence

The usability and feasibility portion of the study falls under Level 3 evidence according to the Centre for Evidence-Based Medicine (CEBM) hierarchy. Whereas the Delphi portion of the study is at Level 5 Evidence on the CEBM hierarchy.

Keywords

dance screening injury surveillance performing arts physical therapy/physiotherapy technology prospective monitoring injury epidemiology

Key Points

Stage 1 expert consensus yielded a comprehensive outline for the Online Dance Injury Surveillance System (ODISS), addressing key design elements across multiple domains.

Usability testing indicated low marginal usability performance, with stage 2 expert feedback affirming the feasibility of ODISS implementation in a mock folk-dance setting.

Stage 2 expert feedback emphasized the need for interface enhancement and strategies to alleviate data entry burdens, crucial for refining ODISS usability and effectiveness.

Introduction

Dance is a popular activity involving hours of training, repetitive movements, and minimal recovery. Dancers experience high risk of musculoskeletal injury during competitions and productions.^1,2 A high incidence of gradual onset injuries appears to be a risk in ballet, modern, and contemporary dance training, rehearsals and classes as well.^1,2 Dance injury surveillance systems developed by applying injury surveillance principles to dance-specific context can aid injury prevention and protect dancer health by tracking physical wellbeing over a period of time and helping to determine the likelihood of dancer injuries.^3
-9 However, current dance-specific injury surveillance systems^10-12 are limited to classical ballet and modern dance and are not widely used in dance injury research.^9
-13 Existing dance injury surveillance systems include the International Performing Arts Injury Reporting Survey (IPAIRs)^14,15 and Performing Artist and Athlete Health Monitor (PAHM),^11,12 developed by the NYU Harkness Centre for Dance Injuries, and Performing Artist Research Lab (PEARL) at Codarts, Rotterdam, respectively. While both systems incorporate elements recommended by the World Health Organisation (WHO) surveillance guidelines,³ they were not developed through a consensus process. Furthermore, IPAIRS has been utilized with inconsistent exposure measurement methods, such as relying on dancer timetables¹⁴ or trainer and therapist records,¹⁵ and does not appear to support a standardized protocol for capturing injury-per-exposure data as recommended by the International Association for Dance Medicine and Science (IADMS).^16,18 Conversely, the PAHM system relies on self-reported injury information, which was initially not aligned with early IADMS recommendations.^11,12-14,15 However, a more recent IADMS update emphasizes aligning injury definitions with the specific purpose of the research and adopting valid approaches,^11,12-^14,15,17,^19
-21 which is achieved by The PAHM system.

It is possible to adapt general sport and physical activity injury surveillance approaches to a dance setting. For example, the Oslo Sports Trauma Research Centre Questionnaire on Health Problems (OSTRC-H) was developed by sports injury epidemiologists and athletes from cross-country skiing, floorball, handball, road cycling and volleyball,^22,23 and has been used in many high-quality dance injury research studies.^24,25 However, there was no apparent dance stakeholder involvement in the development or subsequent update of the OSTRC. As a result, it remains unclear whether a dance-specific expert panel would prioritize the same design elements included in the OSTRC. The lack of dance-specific input into the development of sport and physical activity surveillance systems may contribute to the highly variable surveillance methods used in existing dance injury epidemiology research, which limits the potential to synthesize dance injury findings across studies.^26,27 There is a clear need to explore standardized dance injury surveillance approaches developed through consultation with dancers and dance injury experts to address this problem.

The development of optimal systems requires systematically identifying key design elements based on stakeholder feedback.³ Application of this design approach to dance injury surveillance systems may help establish a system suitable for widespread uptake and support standardization of dance injury data which has been a problem for existing research. Recent International Olympic Committee (IOC) consensus statements on reporting sport injuries highlight the importance of standardized methods for injury surveillance.^26,28,29 The Delphi technique could inform systematic development of a dance-specific injury surveillance system that is optimized for dance and based on expert inputs from key stakeholder groups (eg, dancers, instructors, researchers, and clinicians).^30-35 The Delphi technique has been used to establish consensus on injury definition and standardized injury reporting in runners³⁶ and badminton players,³⁷ but has not been previously used to inform dance injury surveillance research and practice.³³,³⁵,³⁸

The implementation of injury surveillance within dance presents unique challenges, primarily due to the need for comprehensive data collection while effectively addressing the associated time burden of data collection on dancers, instructors, researchers, and clinicians. Particularly, existing studies on ballet, modern, and contemporary dance injury surveillance frequently contend with time constraints, leading to limited availability for data collection, which subsequently hinders the rigor and depth of the scope of research.^3,10,³⁹,⁴⁰ To overcome these limitations, future research should focus on achieving a balance between the high expectations of injury surveillance guidelines and the practical challenges experienced by dancers, instructors, researchers, and clinicians involved in the research. This can be accomplished through the development and refinement of data collection methodologies with the guidance of stakeholder groups, as well as the utilization of technological advancements to streamline the process.^41
-43 Additionally, formal evaluation of the usability and feasibility of dance injury surveillance systems is critical to facilitate the implementation and ongoing refinement of these systems in real-world settings.^3,44

The aims of our study were to (1) utilize a Delphi survey method to determine stage 1 expert consensus on the optimal outline for an online dance injury surveillance system (ODISS) and (2) evaluate the usability and feasibility of the ODISS developed using this outline, by applying it to an injury scenario within a fictional folk-dance academy setting involving stage 2 experts from key stakeholder groups.

Methods

Study Design

This study used a 2-round Delphi survey (stage 1) combined with usability and feasibility testing of an ODISS (stage 2). Reporting of this study followed the proposed Delphi reporting guidelines for the health science sector.^45-48

Participants

Stage 1 experts were recruited through snowball sampling from online professional networks (LinkedIn and ResearchGate), professional dance associations, organizations, and academies (vocational and pre-professional dance schools). Potential stage 1 experts were contacted via publicly available information and if meeting the eligibility criteria, were recruited to the Delphi panel. Inclusion criteria were ≥18 years of age, fluent in English, and worked as dance academics or researchers, clinicians (eg, sports medicine doctors, physiotherapists), accredited exercise physiologists, instructors (eg, rehearsal directors, studio managers), managers, or competitive or professional dancers. Working only within recreational dance forms such as aerobic dance, dance fitness, and dance therapy was an exclusion criterion. Stage 2 experts consisted of (i) all stage 1 experts who were willing to conduct ODISS usability and feasibility testing and (ii) researchers (not including study authors) with surveillance system proficiency in relatable areas to dance (e.g., performing arts and sports settings) who were invited only to participate in stage 2.

Study Procedures

Overview

A literature review⁴⁹ and key injury surveillance guidelines^{3,26,28,50,51} were used to develop a preliminary dance injury surveillance system outline. The outline consisted of 6 key injury surveillance domains (dancer demographics and screening, exposure monitoring, injury identification and classification, injury management, dancer recovery and level of system access) each with suggested design elements (63 proposed in total). A panel of recruited stage 1 experts assessed the preliminary system outline across 2 Delphi rounds in stage 1. Elements that received mixed consensus in round 1 were revised by the study authors before round 2. Elements that achieved consensus for inclusion after round 2 were used to develop the ODISS. In stage 2, usability and feasibility of the ODISS was evaluated by stage 2 experts who applied the system to a fictional case scenario created by the study authors based on an injured professional folk dancer from their past clinical experiences.

Delphi Survey Round 1

Stage 1 experts completed the round 1 Delphi survey online via REDCap 10.0.6 (Vanderbilt University). Participants were asked to rate the importance of each design element from the preliminary injury surveillance system outline. Ratings were made on a ten-point importance scale⁵² or by selecting the most important design elements from a list. The 10-point scale from 0 to 9 was categorized such that scores of 1 to 3 represented “not important,” 4 to 6 “somewhat important,” 7 to 9 “critically important,” and a value of 0 indicated an “unsure” rating. The threshold cut off for elements in the Delphi process was agreed upon by the study authors at 75%. This decision was based on other Delphi literature where it was found consensus decreases when there is less than 75% group agreement.⁵³ Elements rated with ≥75% consensus were included in the system if consensus ratings were “critically important,” not included if the ratings were “not important” and considered discretionary if the ratings were “somewhat important.” Elements with <75% consensus were considered discretionary based on demonstrating mixed importance. Open text responses were collected for each element to enable participants to expand on their ratings if they wished.

Delphi Survey Round 2

Stage 1 experts who completed round 1 were invited to Delphi survey round 2. They were presented a summary of round 1 elements that reached consensus for being included or not included in the system. The stage 1 experts were invited to provide commentary on round 1 inclusion elements and then asked to vote “yes” or “no” to the inclusion of revised discretionary elements from round 1. Revised elements that achieved ≥75% “yes” consensus were included and those ≥75% “no” were excluded from the final injury surveillance system. Elements still rated with ≤75% consensus were discussed by the study authors before making a final decision.

Stage 2—Usability and Feasibility Testing of the Dance Injury Surveillance System

The consensus ODISS was developed in REDCap (template available from corresponding author upon reasonable request). The stage 1 experts from Delphi rounds 1 and 2, alongside researchers with surveillance systems proficiency were invited to participate in usability and feasibility testing as stage 2 experts. Participants tested the ODISS via an interactive 1:1 session using videoconferencing (Zoom version 5.10.0). Screen sharing and remote desktop functionality were used to allow participants to view, access and use the REDCap system. The investigator explained the basic layout of the REDCap system and Zoom’s remote desktop functionality to participants at the beginning of their session.

A fictional dance injury case scenario tailored to the scope of the system was used to facilitate usability and feasibility testing. Stage 2 experts were designated sections of the scenario and associated aspects of the injury surveillance system relevant to their scope of practice. Dancers were designated exposure monitoring and optional psychological screening. Clinicians were designated dancer demographics, injury identification and classification, injury management, and dancer recovery sections of the ODISS. Lastly, academics (education professionals, lecturers, and researchers) were designated dancer demographics and dancer recovery sections of the ODISS. REDCap questionnaire versions of the System Usability Scale (SUS)^44,54
-56 and SFM⁵⁷ were completed after each scenario. The SUS is an information technology industry-standard tool involving scoring 10 usability statements on a 5-point Likert scale.^58,
59 Total SUS score out of 100 is interpreted with acceptability ranges: acceptable (70-100), high marginal (62.5-70), low marginal (50-62.5), and not acceptable (<50).^56,
57,^60
-62 We modified the Feasibility of Intervention Measure (FIM)^47,63 by including 2 additional items, dubbed the System Feasibility Measure (SFM), scored on a 5-point Likert scale, measuring the extent to which implementation can be successful. Higher scores indicate greater implementation feasibility.⁵⁷ Participants were also asked open-ended questions related to system strengths and weaknesses, difficulties experienced, barriers to translating the system to their practice, and overall recommendations.

Data Analysis

Microsoft Excel v16.65 was used to calculate descriptive statistics, participant attrition, and determine level of consensus for Delphi question responses. A heat-map visualization was created to summarize the level of consensus achieved in Delphi round 1 across the 6 injury surveillance domains. Shades of green, orange, and red were used to indicate overall ratings of “consensus include,” “mixed consensus,” and “consensus exclude,” respectively. A minimum of 10 experts is required for consensus on a topic of expertise.⁶⁴ The percentage of stage 1 experts rating the element as critically important (for importance scale questions) or most important to include (for multichoice questions) was used to determine heat map color grade. The light to dark green, light to dark orange, and light to dark red represented 75-100%, 25-74%, and 24-0% importance, respectively. Open-ended questionnaire responses underwent thematic analysis, whereby the most recurring text-string phrases were aggregated to identify common themes.^65,66 The analysis commenced with a thorough review of all responses to achieve a comprehensive understanding of the data. Subsequently, frequently mentioned phrases and words were highlighted and initially coded.^66,67 These codes were tallied using Microsoft Excel V16.0 to quantify the frequency of each idea mentioned. The codes were then organized into broader themes, which were reviewed and refined to ensure they accurately represented the main ideas from the responses. Finally, these themes were clearly defined and named, and the findings were compiled into a detailed report.

Equity, Diversity, and Inclusion Statement

We facilitated stage 1 and stage 2 expert diversity by inviting people from a variety of stakeholder groups in dance and injury surveillance-related fields using a broad recruitment strategy. Effort was made to approach individuals from diverse cultural backgrounds and gender identities for both stages of this study. Styles of dance represented in this study by stage 1 and 2 experts, and study authors included ballet, modern, hip-hop, contemporary, Chinese folk, Turkish folk, Irish folk, Bollywood dance, and Punjabi folk-dances. No person was excluded based on identification with specific social groups. Indeed, the stage 1 and 2 experts in this study included a balance of men and women. Although most of the stage 1 and 2 experts resided in Australia with diverse cultural backgrounds, some stage 1 and 2 experts were from North America, Europe, Asia, and the Middle East. We acknowledge that there were no stage 1 or stage 2 experts in this study from South America and Africa. The author team comprised junior, early, and mid-career researchers from physiotherapy, sports, and psychology, and individuals from marginalized groups.

Patient and Public Involvement

We carried out a Delphi survey with the aim to develop a surveillance system based on the ongoing input of stakeholder groups interested in the use of this system including dancers, instructors, clinicians, academics, and professionals in injury surveillance research. The system was also tested by stage 2 experts who were representative of potential key-stakeholder groups (eg, dancers, instructors, researchers, and clinicians) that would use the system.

Results

Fifty-three stage 1 experts (Table 1) were invited for the Delphi survey, with a 66% round 1 recruitment rate (n = 35) and 37% participant attrition by round 2 (n = 22). Eleven stage 1 experts and 5 additional dance research and injury surveillance experts participated as stage 2 experts in the usability and feasibility testing. Participants typically had 6 to 10 years of dance-related experience with most living in Australia.

Table 1.

Participant Characteristics.

Participant data	Stage 1		Stage 2
Participant data	Round 1	Round 2	User testing
Total invitees	n = 53	n = 35	n = 51
Total participants	n = 35	n = 22	n = 16
Male	n = 15 (42.8%)	n = 13 (59.1%)	n = 9 (56.3%)
Female	n = 20 (57.2%)	n = 9 (40.9%)	n = 7 (43.7%)
Gender diverse or non-binary	n = 0	n = 0	n = 0
Stakeholder participant groups
Dance clinicians^f	9 (25.7%)	4 (18.2%)	3 (18.8%)
Dance instructors^f	5 (14.3%)	5 (22.7%)	2 (12.5%)
Dance research academic^f	6 (17.1%)	4 (18.2%)	2 (12.5%)
Dancers^f	12 (34.3%)	8 (36.4%)	7 (43.8%)
Others^f	3 (8.6%)^a	1 (4.5%)^b	2 (12.5%)^c
Dance disciplines
Ballet and sub-disciplines^d	19 (54.2%)	11 (50.0%)	2 (12.5%)
Modern	15 (42.9%)	7 (31.8%)
Hip-Hop	11 (31.4%)	7 (31.8%)
Folk^e	32 (91.4%)	14 (63.6%)	7 (43.8%)
Jazz	10 (28.6%)	4 (18.2%)
Tap-dance	7 (20.0%)	3 (13.6%)
Musical theater	7 (20.0%)	1 (4.5%)
Contemporary	7 (20.0%)	1 (4.5%)	1 (6.3%)
Performance	7 (20.0%)	1 (4.5%)
Pole	7 (20.0%)	1 (4.5%)
Ballroom	4 (11.4%)	1 (4.5%)
Acrobats	3 (8.6%)	1 (4.5%)
Relatable, non-dance expertise	0	0	2 (12.5%)
Years of dance experience
1-5	7 (20.0%)	4 (18.2%)	1 (6.3%)
6-10	11 (31.4%)	8 (36.4%)	2 (12.5%)
11-15	5 (14.3%)	3 (13.6%)	1 (6.3%)
16-20	8 (22.9%)	4 (18.2%)	1 (6.3%)
20+	4 (11.4%)	3 (13.6%)	2 (12.5%)
Residential regional breakdown
Australia	31 (88.6%)	20 (91.0%)	11 (68.8%)
Europe	1 (2.9%)	0	2 (12.5%)
North America	3 (8.6%)	2 (9.1%)	2 (12.5%)
Asia and Middle East	0	0	1 (6.3%)

Two Physio/research educator, 1 dietician.

Physio/research educator.

Injury surveillance experts.

Traditional and modern ballet.

Bhangra, Bollywood, Irish dancing, Bharatanatyam, Turkish dance, and Thai traditional.

Dance clinicians—registered health professionals working in or with experience in dance. Dance instructors—trainers, team leaders, instructor staff, company directors, managers working in dance. Dance research academics—tertiary level career academics such as professors, lecturers, teachers, post-graduate researchers working in dance at universities or professional bodies. Dancers—competitive, student, pre-professional, and professional dancers from any discipline. Others—administration staff and sport injury surveillance experts.

Delphi Round 1

Figure 1 demonstrates the round 1 level of consensus. Thirty elements were rated as consensus include (mean percentage importance [SD]: 85.9 [7.8]). Three elements were rated as consensus not include (mean percentage importance [SD]: 14.6 [4.8]) and no elements were rated “somewhat important.” No concerns were raised regarding the elements chosen. Thirty elements had mixed consensus (mean percentage importance [SD]: 52.5 [14.6]). The domains with the most mixed consensus elements were System Access (12/21 elements), Injury Identification and Classification (6/15 elements), and Injury Management (6/7 elements).

Figure 1.

Round 1 Delphi panel consensus on dance injury surveillance system elements heat map. Shades of green, orange, and red were used to indicate overall ratings of consensus include element, mixed consensus element, and consensus exclude element, respectively. The percentage of stage 1 experts rating the element as critically important or most important to include (for multichoice questions) was used to determine the heat map color grade. The light to dark green, light to dark orange, and light to dark red represented 75% to 100%, 25% to 74%, and 24% to 0% importance, respectively.

Delphi Round 2

Table 2 describes the 30 round 1 mixed consensus elements, which were refined into 14 revised elements for round 2. Thirteen of 14 revised elements reached consensus for inclusion after round 2 and were combined with 30 consensus “critically important” elements from round 1.

Table 2.

Stage 1 Expert Delphi-Panel Consensus and Feedback on Revised Mixed Consensus Elements in Round 2.

Domains and elements	Round 1		Round 2
Domains and elements	Consensus (%)	Interpretation	Solution	Consensus (%)
Demographic information and screening
The online system should allow dancer psychological screening information to be captured	66	Comments highlighted privacy concerns	Capture of psychological screening information will be optional	100
How frequently should the online system capture demographic information?	25	Large heterogeneity across options ranging from daily to half-yearly	Weekly capture of demographic information will cater to majority	99
Exposure monitoring
The online system should allow non-dance related activity exposure (other physical activities) to be captured	53	Type of non-dance exposures requires further clarification	Only capture non-dance related exposures if physically demanding	91
The online system should capture exposure information: daily, weekly, or monthly	53	Heterogeneity across options ranging from daily to monthly	Weekly capture of exposure information will cater to majority	91
Exposure information should include a written description of the exposure	66	Comments highlighted concerns about user burden	Exposure description will be limited to selecting from preset exposure modes	95
Injury identification and classification
The online system should allow illness, not just injury to be captured	59	Mixed consensus but no comments against inclusion of element	Record dancer illnesses that impact on dance participation	99
The online system should only allow initial injury assessment recording by a RHP	38	Comments highlighted importance of RHP scope of practice	Initial injury assessment completed by RHPs with appropriate expertise	77
Injury identification should incorporate dancer self-reported status, and restriction level	69	Comments highlighted importance of RHP diagnosis	Injury Identification will be based on RHP diagnosis	84
How frequently should the system record absences from dance sessions?	72	Large heterogeneity across options from daily to months	Weekly capture of absence information will cater to majority	86
Initial injury management information should include referral details	63	Mixed consensus but no comments against inclusion of element	Details of the type of RHP referred to will be captured	82
Injury management
The online system should capture information about injured dancer rehabilitation	63	Mixed consensus; comments highlighted key themes related to the high burden of Injury Management tracking and the lack of perceived relevance to injury surveillance	Detailed Injury Management information will not be captured; type and frequency of consults will be captured along with estimated health costs and time	78
The online system should allow for routine follow-up medical assessment information to be captured	56
The online system should integrate existing system medical records to describe rehabilitation	38
The online system should capture the qualified specialists and RHP that injured dancers are seeing	59
Injury management information should include costs and time in-addition to number of consults	56	Mixed consensus; comments highlighted user burden concerns	Health costs and time will be estimated from number of consults	68
Dancer recovery
Full recovery status includes a dance instructor or director assessment of dance ability	59	Mixed consensus but no comments against inclusion of element	Retain this element alongside other markers of recovery status	82
Level of system access
The online system should facilitate the distribution of reports on dancer injuries	56	Mixed consensus and concerns re: individual dancer identification	Overall group summary reports to describe injury trends overtime	95
Dancer should be involved in entering injury management information	63	Mixed consensus and no comments strongly indicating a need for dancers to enter this information	Dancers can review Injury Management and return to dance data at all stages, and request amendments	99
Dancer should be involved in entering return to dance and recovery status information	72			99
Health professionals should be involved in entering dancer demographics information	53	Mixed consensus and comments highlighting importance of dancer information being autonomous	RHPs will have read-only access to approved demographics and exposure information	99
Health professionals should be involved in entering dancer exposure information	43			99
Instructors should be involved in entering dancer demographics information	38	Mixed consensus and comments highlighting instructors’ accessing demographics, no indications for data entry by instructors	Instructors will have read-only access to approved demographics information	77
Instructors should be involved in entering injury identification information	28
Instructors should be involved in entering injury management information	41
Instructors should be involved in entering return to dance information	72

Abbreviation: RHPs, registered health professionals.

The element related to determining financial burden of injuries did not reach consensus in round 1 and 2 (56.3% and 68.0% consensus, respectively) but was included in the final system based on moderate importance ratings and no strong arguments against its inclusion within open-ended question responses. The final system is available in a Supplemental File.

Stage 2: Usability and Feasibility Testing of ODISS

The mean (SD) overall SUS score was 58.2% (11.6), with stage 2 experts who were dance clinicians (registered health professionals working in or with experience in dance) and researchers (51.8% [11.9]) scoring lower than those who were dancers and instructors (65.6% [5.2]). SUS scores fell within the “low marginal” acceptability range for system usability.⁶⁰ All the positive usability statements were commonly rated as “agree” or “strongly agree” and 4 of the 5 negative usability statements were commonly rated as “disagree” or “strongly disagree” (Figure 2). Sixty percent of stage 2 experts agreed or strongly agreed the system was unnecessarily complex. All 6 system feasibility statements were most commonly rated “agree” or “strongly agree” (Figure 2).

Figure 2.

Usability and feasibility responses in stage 2.

Open-ended responses highlighted reoccurring qualitative themes that related to (1) the system facilitating rich data collection that would support high-quality research, (2) the user interface needing improvement with integration of more dropdown and checkbox response options within the interface to increase efficiency of data entry, and (3) time burden being a barrier to integrating the system into real-world dance settings and scenarios.

Discussion

The objective of this study was to develop an ODISS based on consensus from a Delphi survey (stage 1) and evaluate the system’s usability and feasibility within a fictional folk-dance academy setting (stage 2). This study achieved stage 1 expert consensus on the 6 key injury surveillance domains (dancer demographics and screening, exposure monitoring, injury identification and classification, injury management, dancer recovery and level of system access) required for building the ODISS using the Delphi technique. Stage 2 expert evaluation of the resulting system demonstrated low marginal usability and high feasibility. Commonly identified areas for improvement included enhancing the ODISS user interface through the addition of dropdown menus and checkboxes to streamline data entry processes. These potential improvements would aim to reduce the overall time burden by requiring less information to be recorded.

Injury identification by a registered health professional (RHP) was considered crucial for injury surveillance by the stage 1 experts, aligning with the recommendations of IADMS for dance injury surveillance.¹⁶,¹⁸ Consequently, the ODISS was developed to standardize injury identification and classification based on weekly RHP assessment. This was achieved by integrating 2 distinct injury definitions, supporting the selection of medical attention or time-loss definitions in the system.²⁶,¹⁹ Other systems such as the IPAIRS^14,15 and PAHM^11,12 offer different approaches. The IPAIRS,^14,15 for instance, involves a collaborative process between RHPs and dancers in determining injury-related information. Specifically, RHPs conduct regular health assessments and document any medical issues. Concurrently, dancers provide their input by self-reporting any discomfort, pain, or potential injuries they experience during their performances. This dual-input approach allows for a comprehensive and accurate understanding of the dancers’ health and injury status. On the other hand, the PAHM^11,12 system relies solely on dancer self-reported injury information, providing a more subjective but personally relevant perspective on injury incidence.^11,12,^14
,15 This approach of relying on dancers to self-report injuries can reduce the workload and financial burden associated with providing adequate RHP coverage in surveillance projects. However, using RHP is likely to lead to more accurate and valid injury classification compared to dancer self-reported information. Indeed, a previous injury surveillance study demonstrated discrepancies between injury information reported by dancer compared to RHP evaluations over a 10-month period.⁶⁸ Such inaccuracies can potentially skew injury prevalence estimates, misinform prevention strategies, and hinder the identification of important injury trends and risk factors, and misinform prevention strategies which leads to wasted resources and funding.

To enhance the comprehensiveness of injury surveillance, the Oslo Sports Trauma Research Centre Questionnaire on Health Problems (OSTRC-H)²³ has been widely utilized in dance injury studies. This athlete-completed questionnaire is designed to capture a broad spectrum of health issues, identifying not only time-loss and medical-attention injuries but also subclinical and recurrent health problems that can impact performance and well-being.^22,23 This expanded definition of injury acknowledges the prevalence of “silent” injuries in dance, which may go underreported due to stigma, fear, or lack of healthcare access but still impose a meaningful burden on the dancer’s health and career.^23,69 It achieves this by assessing injuries on 4 key dimensions: severity, impact on participation, degree of symptoms, and overall impact on performance.^22,23,69 This approach has demonstrated reliability and validity across various sports,²³ including dance.⁶⁹ Integrating the OSTRC-H questionnaire into the ODISS could enhance the system’s comprehensiveness by capturing self-reported health problems that extend beyond RHP medical-attention and time-loss injuries alone.⁶⁹ However, these benefits need to be balanced against the potential limitations of self-reported data, especially recall errors and inconsistencies in symptom interpretation.⁶⁹ Therefore, corroborative assessments from RHPs will likely be needed to enhance data accuracy and consistency.

High-quality dance injury studies have demonstrated that physical complaints, as defined by several IOC consensus reports, are critical to understanding the full scope of injury burden in dancers.^26,28 The debate around self-reporting in injury surveillance is multifaceted and directly relates to the different approaches of ODISS and OSTRC-H. ODISS primarily relies on RHP assessments and time-loss injury definitions, with dancer input serving as a supplementary source of information, ensuring data is grounded in professional medical evaluation while considering the dancer’s personal experience. This aligned with the preferences of the stage 1 experts. Conversely, OSTRC-H is based solely on athlete self-report, capturing both medical attention and time-loss injuries, providing a personal perspective on injury incidence but highlighting the need for corroborative assessment due to potential subjective biases. Both systems aim for comprehensive injury surveillance but differ in their balance between professional medical assessment and athlete self-report, underscoring the complexity of injury surveillance and the ongoing debate around self-reporting.

In this Delphi study, stage 1 experts agreed that hours of dance activity per week was the preferred exposure measure. This represents a practical measure that dancers and instructors can reliably report.⁷⁰ The PAHM^11,12 and IPAIRS^14,15 also track exposure hours, but researchers using these systems have focused on varying exposure intervals.^10,14,15 Identification of a standardized unit of measure that can be consistently applied across studies will allow easier comparisons between studies and facilitate meta-analyses. This ability to make comparisons over time and between different cohorts is critical to understanding injury incidence.²⁶ Accurate exposure data is necessary to calculate injury rates (ie, injuries per 1000 hours of dance).² Without exposure data, it is difficult to determine whether a higher number of injuries is due to the presence of a potential injury risk factor, or simply due to more time spent dancing. The IOC consensus statement²⁶ considered the gold standard in the field, alongside the 2024 IADMS recommendations^17,71 and Research Methods in the Dance Sciences guide,⁷² supports the practice of monitoring and accounting for exposure when investigating sports injuries and illnesses.

The stage 1 experts agreed on the importance of capturing dance exposure frequency and intensity, as well as weekly non-dance related activity, despite some concerns about the associated time burden. To record 1 component of intensity, detailed logs can be used where dancers rate their perceived exertion for training sessions, performances, and other physical activities on a standardized scale (e.g., Borg CR10 scale⁷³). This method, which aligns with the principles of training load monitoring in dance science,⁷⁴ allows for a subjective measure of internal training load (physiological response to exercise), which, alongside training frequency and duration, may provide a comprehensive description of dancer workload.⁷⁵ This additional exposure information allows for rich exploration of how different exposure patterns may influence dance injury risk, a variable explored by only a small number of studies.^42,23

The IOC consensus statement recommends surveillance systems record exposure subcategories such as different training intensities, performances, and other physical activities.^26,28 Researchers using the IPAIRS^14,15 and PAHM^11,12 systems have not tracked exposure intensities nor exposure types (training, performance, competition, rehearsal, and other relevant exposure types) in their studies. The ODISS can support greater depth and quality of dance exposure information collected by future studies, which should improve injury risk estimation. By recording both the frequency and intensity of dance and non-dance activities, ODISS will enable a more nuanced understanding of the relationship between different exposure patterns and injury risk. This comprehensive approach aligns with the recommendations of the IOC and ensures that future research can better identify and mitigate factors contributing to dance injuries.

The injury management domain had the poorest initial consensus, required the most adjustment to achieve consensus, and received notable concern from stage 1 experts about user burden. In round 2, stage 1 experts advocated for focusing on the frequency, type, and estimated cost of healthcare consults instead of detailed injury management information. Injury financial burden remained an element that stage 1 experts demonstrated mixed consensus on after round 2, despite financial cost being an outcome of concern for sporting events inclusive of dance according to the IOC sport injury surveillance guidelines.^26,28 Studies involving the PAHM^11,12 and IPAIRS^14,15 dance surveillance systems did not report financial costs in their Data Analysis and Results sections, nor did the systems reference any collection of financial data related to dancing injuries. This is consistent with uncertainties the stage 1 experts expressed regarding the inclusion of the financial cost design element. The ODISS facilitates collecting the minimum information required to estimate injury costs, addressing a literature gap on the financial burden of dance injuries.

Currently, there exists no standardized guidelines for reporting financial burden within the realm of dance or other prominent sports. A potential future approach for study authors to explore when reporting financial burden may include instructing researchers to report costs in local currency (eg, AUD)^76,77,⁷⁸ and then converting to a common standard currency (eg, USD) for comparisons. Additionally, specifying the type of healthcare system (eg, public, private) in their context could provide further clarity. This approach, may provide important insights into the financial burden of dance injuries that help justify injury prevention initiatives to the relevant organizations and funding bodies that support them.⁷⁹

Upon further deliberation, our stage 1 experts highlighted the importance of 3 additional domains—demographic information and screening, dancer recovery, and level of ODISS access. Dancer demographic information and screening were seen as vital components for contextualizing injury data and identifying at-risk groups.⁸⁰,^78,81 Our stage 1 experts emphasized that understanding the background and pre-existing conditions of dancers allows for a more nuanced interpretation of injury data and may help tailor prevention strategies to specific populations. Information about the dancer recovery and progress of injured dancers was identified as critical for understanding how to facilitate safe return to dance participation and prevent recurrent injuries. Additionally, the stage 1 experts highlighted the importance of ensuring clinicians, dancers, and academics had access to the correct parts of the ODISS to optimize the efficiency and accuracy of injury surveillance data. By integrating these considerations into the future implementation of ODISS, we can provide a more comprehensive framework for dance injury surveillance.

Usability of the ODISS was “marginal low,” despite being rated as highly feasible.⁶² Systems with low usability are recommended to undergo further iterations before wide-scale rollout.^57,60-62 The high requirements of injury surveillance guidelines and stage 1 expert recommendations created a substantial demand for the ODISS to streamline many processes which negatively impacted on user experience. The tension between injury surveillance best practice and optimized usability may explain why existing ballet, modern, and contemporary dance injury research has often demonstrated methods such as estimating exposure hours based on dancers’ schedules, rather than directly measuring exposure and using unclear criteria for including and excluding injuries.^14,41 Incorporating systems such as Athlete 360,⁸² which facilitate dancers in self-reporting their weekly dance hours, can yield valuable insights. Despite the considerable potential of this practice, it remains underrepresented in current research. Many studies subtly refer to the use of a surveillance system, without elaborating on the system’s name or the approach adopted for the accumulation of self-reported dance hours. When amalgamated with activity trackers, this approach provides a comprehensive overview of a dancer’s activity, thereby informing injury prevention initiatives. Consequently, the significance of these self-reporting systems in dance injury surveillance warrants further emphasis and extensive discussion in academic research. Researchers are encouraged to increase their efforts on improving injury surveillance systems usability, and systems such as the ODISS may provide a benefit toward future dance injury research by supporting greater adherence to best practice injury surveillance guidelines.

Limitations

A study limitation was the higher-than-expected participant attrition over the Delphi rounds. As a result, we had to expand recruitment in stage 2, which included participants less familiar with previous context of the project. However, this led to the inclusion of injury epidemiology and surveillance system stage 2 experts as a valuable stakeholder group to evaluate our system. Although the study participants represented a variety of stakeholder groups and dance disciplines, the majority were from Australia with only minor representation from North America, Europe, Asia, and the Middle East, with notable gaps in South America and Africa. Further diversification of the stage 1 and stage 2 experts may have led to a more international perspective on the system and greater consideration of diverse dance disciplines from under-represented regions.

Future Directions

In future research, it will be essential to explore ways to enhance the usability of the ODISS. This could involve iterative focus groups with end-users to develop ways to improve the usability of the ODISS in a collaborative manner. Additionally, piloting ODISS in various dance disciplines, including those with limited injury surveillance data, could help assess and optimize its usability across diverse settings. Investigating factors such as system uptake, adherence, and compliance, as well as understanding facilitators and barriers to its implementation, will provide valuable insights for refining the system to maximize user engagement and effectiveness in practice.

Conclusion

This study established a Delphi-consensus on the essential design elements for building the ODISS that aligns with current guidelines and recommendations. This study was the first to systematically evaluate the usability and feasibility of a dance injury surveillance system, which was rated as highly feasible, though with low marginal usability. There is scope for ongoing system development to improve usability. Overall, the system enables an agreed, systematic, standardized, and accessible method to collect dance injury data and assess the burden of injury in dance.

Footnotes

Acknowledgements

We would like to acknowledge the participants for their helpful contribution and devoting their valuable time toward the study.

Author Contributions

AT, JF and EI: collaborated on the initial study design. AT designed the initial Delphi surveys, JF and EI contributed to revisions until final versions were agreed and finalized. All authors were involved in determining the stakeholder groups. AT completed recruitment for stage 1 and 2 and conducted stage 2 sessions. The qualitative analysis was performed by all investigators. AT prepared the first full manuscript draft, with JF and EI contributing to editing of the paper and agreed on the final submission.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethics Approval

Ethics approval was gained from the Macquarie University Human Research Ethics Committee (HREC; reference number 520211057733817).

Consent to Participate

All participants provided informed consent prior to participation.

ORCID iDs

Amitoj Singh Thind

Emre Ilhan

Supplemental Material

Supplemental material for this article is available online.

References

Kenny

Whittaker

Emery

CA.

Risk factors for musculoskeletal injury in preprofessional dancers: a systematic review. Br J Sports Med. 2016;50(16):997-1003.

Vassallo

Hiller

Pappas

, et al. Safe dance report iv: investigating injuries in australia’s professional dancers [Internet]. 2017. Updated 2017. Accessed December 9, 2022. https://ausdance.org.au/?ACT=73&file=2404

Holder

Peden

Krug

, et al. Injury Surveillance Guidelines. World Health Organisation (WHO); 2001. Updated 2001. Accessed December 9, 2022. https://apps.who.int/iris/handle/10665/42451

van Mechelen

. Sports injury surveillance systems. Sports Med. 1997;24(3):164-168.

Hincapié

Morton

Cassidy

JD.

Musculoskeletal injuries and pain in dancers: a systematic review. Arch Phys Med Rehabil. 2008;89(9):1819-1829.

Ani

Ibikunle

Useh

, et al. A systematic review of ankle injury epidemiology in dance. Afr J Heal Sci Technol. 2021;3(1):142-155.

Bronner

Ojofeitimi

Rose

Injuries in a modern dance company: effect of comprehensive management on injury incidence and time loss. Am J Sports Med. 2003;31(3):365-373. doi:10.1177/03635465030310030701

Samitz

Egger

Zwahlen

Domains of physical activity and all-cause mortality: systematic review and dose–response meta-analysis of cohort studies. Int J Epidemiol. 2011;40(5):1382-1400. doi:10.1093/ije/dyr112

Caine

Maffulli

Caine

Epidemiology of injury in child and adolescent sports: injury rates, risk factors, and prevention. Clin Sports Med. 2008;27(1):19-vii. doi:10.1016/j.csm.2007.10.008

10.

Bronner

Ojofeitimi

Mayers

Comprehensive surveillance of dance injuries a proposal for uniform reporting guidelines for professional companies. J Dance Med Sci. 2006;10(3-4):69-80.

11.

Karreman

Keizer-Hulsebosch

Stubbe

JH.

Performing artist and athlete health monitor: user experience, content, and conditions for use of an online dance-health surveillance system in a professional ballet company. BMJ Open Sport Exerc Med. 2019;5(1):e000566.

12.

van Winden

van Rijn

Savelsbergh

GJP

Oudejans

RRD

Stubbe

JH.

Limited coping skills, young age, and high bmi are risk factors for injuries in contemporary dance: a 1-year prospective study. Front Psychol. 2020;11:1452.

13.

Cahalan

O’Sullivan

Purtill

Bargary

Ni Bhriain

O’Sullivan

. Inability to perform because of pain/injury in elite adult Irish dance: a prospective investigation of contributing factors. Scand J Med Sci Sports. 2015;26(6):694-702.

14.

Lee

Reid

Cadwell

Palmer

Injury incidence, dance exposure and the use of the movement competency screen (MCS) to identify variables associated with injury in full-time pre-professional dancers. Int J Sports Phys Ther. 2017;12(3):352-370.

15.

Liederbach

Dilgen

Rose

DJ.

Incidence of anterior cruciate ligament injuries among elite ballet and modern dancers: a 5-year prospective study. Am J Sports Med. 2008;36(9):1779-1788.

16.

International Association for Dance Medicine and Science (IADMS). Recommendations and Implementation Strategies for the Assessment and Reporting of Dancer Capacities, Risk Factors, and Injuries: Steps Toward Consensus. International Association for Dance Medicine and Science (IADMS) [Internet]; 2012. Accessed November 24, 2022. https://iadms.org/media/3594/iadms-smci-report-recommendations-and-implementation-strategies-for-the-assessment-and-reporting-of-dancer-capacities.pdf

17.

Kenny

Stubbe

Swain

CTV

, et al. An update on the six recommendations from the 2012 IADMS standard measures initiative: Assessing and reporting dancer capacities, risk factors, and injuries. J Dance Med Sci. Published online October 11, 2024. doi:10.1177/1089313X241288998

18.

Liederbach

Hagins

Gamboa

Welsh

TM.

Assessing and reporting dancer capacities, risk factors, and injuries. Recommendations from the IADMS standard measures consensus initiative. J Dance Med Sci. 2012;16(4):139-153.

19.

Finch

CF.

An overview of some definitional issues for sports injury surveillance. Sports Med. 1997;24(3):157-163.

20.

Liederbach

Richardson

The importance of standardized injury reporting in dance. J Dance Med Sci. 2007;11(2):45-48.

21.

Orchard

Meeuwisse

Derman

, et al. Sport medicine diagnostic coding system (SMDCS) and the orchard sports injury and illness classification system (OSIICS): revised 2020 consensus versions. Br J Sports Med. 2020;54(7):397-401.

22.

Clarsen

Bahr

Myklebust

, et al. Improved reporting of overuse injuries and health problems in sport: an update of the Oslo Sport Trauma Research Center questionnaires. Br J Sports Med. 2020;54(7):390-396. doi:10.1136/bjsports-2019-101337

23.

Clarsen

Myklebust

Bahr

Development and validation of a new method for the registration of overuse injuries in sports injury epidemiology: the Oslo Sports Trauma Research Centre (OSTRC) overuse injury questionnaire. Br J Sports Med. 2013;47(8):495-502.

24.

Ursej

Sekulic

Prus

Gabrilo

Zaletel

Investigating the prevalence and predictors of injury occurrence in competitive hip hop dancers: prospective analysis. Int J Environ Res Public Health. 2019;16(17):3214. doi:10.3390/ijerph16173214

25.

van Winden

Van Rijn

Richardson

Savelsbergh

Oudejans

Stubbe

JH.

Detailed injury epidemiology in contemporary dance: a 1-year prospective study of 134 students. BMJ Open Sport Exerc Med. 2019;5(1):e000453. doi:10.1136/bmjsem-2018-000453

26.

Bahr

Clarsen

Derman

, et al. International olympic committee consensus statement: methods for recording and reporting of epidemiological data on injury and illness in sport 2020 (including strobe extension for sport injury and illness surveillance (STROBE-SIIS). Br J Sports Med. 2020;54(7):372-389.

27.

Finch

Cook

Categorizing sports injury prevention strategies and interventions. OA Sports Med. 2021;51(6):1041-1055. doi:10.1007/s40279-020-01364-4

28.

Junge

Engebretsen

Alonso

, et al. Injury surveillance in multi-sport events: the international olympic committee approach. Br J Sports Med. 2008;42(6):413-421.

29.

Mountjoy

Ackerman

Bailey

, et al. 2023 International Olympic Committee’s (IOC) consensus statement on Relative Energy Deficiency in sport (REDs). Br J Sports Med. 2023;57(17):1073-1098.

30.

Keeney

Hasson

McKenna

HP.

A critical review of the delphi technique as a research methodology for nursing. Int J Nurs Stud. 2001;38(2):195-200.

31.

Eubank

Mohtadi

Lafave

, et al. Using the modified delphi method to establish clinical consensus for the diagnosis and treatment of patients with rotator cuff pathology. BMC Med Res Methodol. 2016;16:56.

32.

Dalkey

Helmer

. An experimental application of the delphi method to the use of experts. J Manag Sci. 1963;9(3):458-467.

33.

Haber

Schärli

Defining spotting in dance: a delphi method study evaluating expert opinions. Front Psychol. 2021;12:540396.

34.

Paré

Cameron

Poba-Nzaou

Templier

A systematic assessment of rigor in information systems ranking-type delphi studies. Inf Manage. 2013;50(5):207-217.

35.

Goodman

CM.

The Delphi technique: a critique. J Adv Nurs. 1987;12(6):729-734.

36.

Yamato

Saragiotto

Lopes

AD.

A consensus definition of running-related injury in recreational runners: a modified Delphi approach. J Orthop Sports Phys Ther. 2015;45(5):375-380.

37.

Gijon-Nogueron

Ortega-Avila

Kaldau

, et al. Data collection procedures and injury definitions in badminton: a consensus statement according to the delphi approach. Clin J Sport Med. 2022;32(5):e444-e450.

38.

Diamond

Grant

Feldman

, et al. Defining consensus: a systematic review recommends methodologic criteria for reporting of delphi studies. J Clin Epidemiol. 2014;67(4):401-409.

39.

Shaw

Mattiussi

Brown

, et al. Dance exposure, individual characteristics, and injury risk over five seasons in a professional ballet company. Med Sci Sports Exerc. 2021;53:2290-2297.

40.

McCormack

Bird

de Medici

Haddad

Simmonds

The physical attributes most required in professional ballet: a delphi study. Sports Med Int Open. 2018;3(1):E1-E5.

41.

Honrado

Bay

Lam

KC.

Epidemiology of patients with dance-related injuries presenting to emergency departments in the united states, 2014-2018. Sports Health. 2021;13(5):471-475.

42.

Wyon

Twitchett

Angioi

Clarke

Metsios

Koutedakis

Time motion and video analysis of classical ballet and contemporary dance performance. Int J Sports Med. 2011;32(11):851-855.

43.

Kozai

Twitchett

Morgan

Wyon

MA.

Workload intensity and rest periods in professional ballet: connotations for injury. Int J Sports Med. 2020;41(6):373-379.

44.

Peres

Pham

Phillips

Validation of the system usability scale (SUS): sus in the wild. Proc Hum Factors Ergon Soc. 2013;57(1):192-196.

45.

Dalkey

Helmer

An experimental application of the Delphi method to the use of experts. Manage Sci. 1963;9(3):458-467.

46.

Harvey

Holmes

Carless

Beyond nominal group technique: a Delphi study to identify key criteria for developing effective group processes for patient and public involvement in research. Health Expect. 2019;22(5):1074-1083.

47.

Kiker

Bridges

Varghese

Seager

Linkov

Application of multi-criteria decision analysis in environmental decision making. Integr Environ Assess Manag. 2005;1(2):95-108.

48.

Spranger

Homberg

Sonnberger

Niederberger

Reporting guidelines for delphi techniques in health sciences: a methodological review. Z Evid Fortbild Qual Gesundhwes. 2022;172:1-11.

49.

Thind

Fuller

Ilhan

A scoping review of prospective dance-related injury research. Public registration updates. Open Science Framework. 2022;(12). doi:10.25949/25180895.v1

50.

Sports Medicine Australia. Australian-Sports-Injury-Data-Dictionary. (1st ed). Sports Medicine Australia [Internet]; 2018. Accessed November 24, 2022. https://sma.org.au/wp-content/uploads/2009/12/datadictionary.pdf

51.

Australia Institute of Health and Welfare. Injury Surveillance National Minimum Data Set: National Health Data Dictionary. (12th ed). Australia Institute of Health and Welfare [Internet]; 2003. Accessed November 24, 2022. https://www.aihw.gov.au/getmedia/81931b0a-eb13-41d4-ada6-38a05f0aaaae/is.pdf.aspx?inline=true

52.

Guyatt

Oxman

Kunz

, et al. GRADE guidelines: 2. Framing the question and deciding on important outcomes. J Clin Epidemiol. 2011;64(4):395-400.

53.

Barrios

Guilera

Nuño

Gómez-Benito

Consensus in the delphi method: what makes a decision change?

Technol Forecast Soc Change. 2021;163:120484. doi:10.1016/j.techfore.2020.120484

54.

Kenny

Palacios-Derflingher

Whittaker

Emery

CA.

The influence of injury definition on injury burden in preprofessional ballet and contemporary dancers. J Orthop Sports Phys Ther. 2018;48(3):185-193.

55.

Lewis

. The system usability scale: past, present, and future. Int J Hum-Comput Int. 2018;34(7):577-90.

56.

Bangor

Kortum

Miller

JT.

An empirical evaluation of the system usability scale. Int J Hum Comput Interact. 2008;24(6):574-594.

57.

Lutter

Jacquet

Verhagen

Seil

Tischer

Does prevention pay off? Economic aspects of sports injury prevention: a systematic review. Br J Sports Med. 2022;56(8):470-476.

58.

ISO. Ergonomics of Human-System Interaction – Part 11: Usability: Definitions and Concepts. International Organization for Standardization [Internet]; 2018. Updated 2018. Accessed December 9, 2022. https://www.iso.org/standard/63500.html

59.

Proctor

Silmere

Raghavan

, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2001;38(2):65-76.

60.

Bangor

Kortum

Miller

Determining what individual SUS scores mean: adding an adjective rating scale. J Usability Stud. 2009;4(6):114-123.

61.

Brooke

SUS: a quick and dirty usability scale. Usability Eval Ind. 1995;189:3-6.

62.

Brooke

SUS: a retrospective. J Usability Stud. 2013;8(1):29-40.

63.

Weiner

Lewis

Stanick

, et al. Psychometric assessment of three newly developed implementation outcome measures. Implement Sci. 2017;12(1):108.

64.

Okoli

Pawlowski

SD.

The delphi method as a research tool: an example, design considerations and applications. Inf Manage. 2004;42(1):15-29.

65.

Creswell

JW.

Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Pearson; 2012.

66.

Vaismoradi

Turunen

Bondas

Content analysis and thematic analysis: implications for conducting a qualitative descriptive study. Nurs Health Sci. 2013;15(3):398-405.

67.

Guest

MacQueen

Namey

EE.

Applied Thematic Analysis. Sage Publication; 2012.

68.

Baker

Scott

Watkins

Keegan-Turcotte

Wyon

Self-reported and reported injury patterns in contemporary dance students. Med Probl Perform Art. 2010;25(1):10-15.

69.

Harrison

Ruddock

O'Halloran

Mayes

Cook

Ruddock-Hudson

Wellness monitoring for professional ballet dancers - a pilot study. J Dance Med Sci. 2021;25(2):80-85. doi:10.12678/1089-313X.061521b

70.

El-Kotob

Giangregorio

LM.

Pilot and feasibility studies in exercise, physical activity, or rehabilitation research. Pilot Feasibility Stud. 2018;4:137.

71.

International Association for Dance Medicine & Science. 34th Annual conference proceedings. 2024. Accessed February 20, 2025. https://www.dancemagazine.com/2024-iadms-conference/

72.

Mainwaring

Ambegaonkar

Welsh

. Research Methods in the Dance Sciences. University Press of Florida; 2023. Accessed February 20, 2025. https://muse.jhu.edu/book/109711

73.

Williams

The Borg rating of perceived exertion (RPE) scale. Occup Med. 2017;67(5):404-405. doi:10.1093/occmed/kqx063

74.

Volkova

Räisänen

Benson

Ferber

Kenny

SJ.

Systematic review of methods used to measure training load in dance. BMJ Open Sport Exerc Med. 2023;9(3):e001484. doi:10.1136/bmjsem-2022-001484

75.

Hutt

. Using technology to monitor workload in dance training. One Dance UK, 2023. Accessed February 20, 2025. https://www.onedanceuk.org/media/h4wh5ry4/using-technology-to-monitor-workload-in-dance-training.pdf

76.

Australian Institute of Health and Welfare. Economics of sport and physical activity. n.d. Accessed February 20, 2025. https://www.aihw.gov.au/reports/sports-injury/economics-of-sport-and-physical-activity/contents/summary

77.

Australian Institute of Health and Welfare. Economics of sports injuries. n.d. Accessed February 20, 2025. https://www.aihw.gov.au/reports/sports-injury/economics-of-sports-injuries/contents/summary

78.

Poder

Coulibaly

Gaudreault

Berthelot

Laberge

Validated Tools to measure costs for patients: a systematic review. Patient Patient Cent Outcomes Res. 2021;15(1):3-19.

79.

Garrick

Requa

RK.

Ballet injuries. An analysis of epidemiology and financial outcome. Am J Sports Med. 1993;21(4):586-590. doi:10.1177/036354659302100417

80.

Duijvestijn

de Wit

van Gils

Wendel-Vos

GCW

. Impact of physical activity on healthcare costs: a systematic review. BMC Health Serv Res. 2023;23(1):572. doi:10.1186/s12913-023-09556-8

81.

AthleteMonitoring.com. Athlete management system, athlete monitoring software. n.d. Accessed June 14, 2024. https://www.athletemonitoring.com

82.

Jason

CKK

. Screening and injury surveillance for a contemporary dance company: a pilot study. Int J Sports Exerc Med. 2019;5(10):131. doi:10.23937/2469-5718/1510131

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.23 MB