Compliance with sport injury prevention interventions in randomised controlled trials : A systematic review
- van Reijen, Miriam, Vriend, Ingrid, van Mechelen, Willem, Finch, Caroline, Verhagen, Evert
- Authors: van Reijen, Miriam , Vriend, Ingrid , van Mechelen, Willem , Finch, Caroline , Verhagen, Evert
- Date: 2016
- Type: Text , Journal article , Review
- Relation: Sports Medicine Vol. 46, no. 8 (2016), p. 1125-1139
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- Description: Introduction Sport injury prevention studies vary in the way compliance with an intervention is defined, measured and adjusted for. Objective The objective of this systematic review was to assess the extent to which sport injury prevention randomised controlled trials (RCTs) have defined, measured and adjusted results for compliance with an injury prevention intervention. Methods An electronic search was performed in MEDLINE, PubMed, the Cochrane Center of Controlled Trials, CINAHL (Cumulative Index to Nursing and Allied Health Literature), PEDro (Physiotherapy Evidence Database) and SPORTDiscus. English RCTs, quasi-RCTs and cluster-RCTs were considered eligible. Trials that involved physically active individuals or examined the effects of an intervention aimed at the prevention of sport-or physical activity-related injuries were included. Results Of the total of 100 studies included, 71.6 % mentioned compliance or a related term, 68.8 % provided details on compliance measurement and 51.4 % provided compliance data. Only 19.3 % analysed the effect of compliance rates on study outcomes. While studies used heterogeneous methods, pooled effects could not be presented. Conclusions Studies that account for compliance demonstrated that compliance significant affects study outcomes. The way compliance is dealt with in preventions studies is subject to a large degree of heterogeneity. Valid and reliable tools to measure and report compliance are needed and should be matched to a uniform definition of compliance.
- Authors: van Reijen, Miriam , Vriend, Ingrid , van Mechelen, Willem , Finch, Caroline , Verhagen, Evert
- Date: 2016
- Type: Text , Journal article , Review
- Relation: Sports Medicine Vol. 46, no. 8 (2016), p. 1125-1139
- Full Text:
- Reviewed:
- Description: Introduction Sport injury prevention studies vary in the way compliance with an intervention is defined, measured and adjusted for. Objective The objective of this systematic review was to assess the extent to which sport injury prevention randomised controlled trials (RCTs) have defined, measured and adjusted results for compliance with an injury prevention intervention. Methods An electronic search was performed in MEDLINE, PubMed, the Cochrane Center of Controlled Trials, CINAHL (Cumulative Index to Nursing and Allied Health Literature), PEDro (Physiotherapy Evidence Database) and SPORTDiscus. English RCTs, quasi-RCTs and cluster-RCTs were considered eligible. Trials that involved physically active individuals or examined the effects of an intervention aimed at the prevention of sport-or physical activity-related injuries were included. Results Of the total of 100 studies included, 71.6 % mentioned compliance or a related term, 68.8 % provided details on compliance measurement and 51.4 % provided compliance data. Only 19.3 % analysed the effect of compliance rates on study outcomes. While studies used heterogeneous methods, pooled effects could not be presented. Conclusions Studies that account for compliance demonstrated that compliance significant affects study outcomes. The way compliance is dealt with in preventions studies is subject to a large degree of heterogeneity. Valid and reliable tools to measure and report compliance are needed and should be matched to a uniform definition of compliance.
Time-to-event analysis for sports injury research part 1 : Time-varying exposures
- Nielsen, Rasmus, Bertelsen, Michael, Ramskov, Daniel, Møller, Merete, Hulme, Adam, Theisen, Daniel, Finch, Caroline, Fortington, Lauren, Mansournia, Mohammad, Parner, Erik
- Authors: Nielsen, Rasmus , Bertelsen, Michael , Ramskov, Daniel , Møller, Merete , Hulme, Adam , Theisen, Daniel , Finch, Caroline , Fortington, Lauren , Mansournia, Mohammad , Parner, Erik
- Date: 2019
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 53, no. 1 (2019), p. 61-68
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- Description: Background: 'How much change in training load is too much before injury is sustained, among different athletes?' is a key question in sports medicine and sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous injury, biomechanics, sleep/stress) when studying sports injury aetiology. Aim: To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and injury-related outcomes. Content: Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills. Conclusion: To increase knowledge about the association between changes in training load and injury, we encourage sports injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective sports injury data. This will ensure appropriate interpretation of time-to-event data. © 2019 Author(s).
- Authors: Nielsen, Rasmus , Bertelsen, Michael , Ramskov, Daniel , Møller, Merete , Hulme, Adam , Theisen, Daniel , Finch, Caroline , Fortington, Lauren , Mansournia, Mohammad , Parner, Erik
- Date: 2019
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 53, no. 1 (2019), p. 61-68
- Full Text:
- Reviewed:
- Description: Background: 'How much change in training load is too much before injury is sustained, among different athletes?' is a key question in sports medicine and sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous injury, biomechanics, sleep/stress) when studying sports injury aetiology. Aim: To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and injury-related outcomes. Content: Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills. Conclusion: To increase knowledge about the association between changes in training load and injury, we encourage sports injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective sports injury data. This will ensure appropriate interpretation of time-to-event data. © 2019 Author(s).
Time-to-event analysis for sports injury research part 2 : Time-varying outcomes
- Nielsen, Rasmus, Bertelsen, Michael, Ramskov, Daniel, Møller, Merete, Hulme, Adam, Theisen, Daniel, Finch, Caroline, Fortington, Lauren, Mansournia, Mohammad, Parner, Erik
- Authors: Nielsen, Rasmus , Bertelsen, Michael , Ramskov, Daniel , Møller, Merete , Hulme, Adam , Theisen, Daniel , Finch, Caroline , Fortington, Lauren , Mansournia, Mohammad , Parner, Erik
- Date: 2019
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 53, no. 1 (2019), p. 70-78
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- Description: Background: Time-to-event modelling is underutilised in sports injury research. Still, sports injury researchers have been encouraged to consider time-to-event analyses as a powerful alternative to other statistical methods. Therefore, it is important to shed light on statistical approaches suitable for analysing training load related key-questions within the sports injury domain. Content: In the present article, we illuminate: (i) the possibilities of including time-varying outcomes in time-to-event analyses, (ii) how to deal with a situation where different types of sports injuries are included in the analyses (ie, competing risks), and (iii) how to deal with the situation where multiple subsequent injuries occur in the same athlete. Conclusion: Time-to-event analyses can handle time-varying outcomes, competing risk and multiple subsequent injuries. Although powerful, time-to-event has important requirements: researchers are encouraged to carefully consider prior to any data collection that five injuries per exposure state or transition is needed to avoid conducting statistical analyses on time-to-event data leading to biased results. This requirement becomes particularly difficult to accommodate when a stratified analysis is required as the number of variables increases exponentially for each additional strata included. In future sports injury research, we need stratified analyses if the target of our research is to respond to the question: 'how much change in training load is too much before injury is sustained, among athletes with different characteristics?' Responding to this question using multiple time-varying exposures (and outcomes) requires millions of injuries. This should not be a barrier for future research, but collaborations across borders to collecting the amount of data needed seems to be an important step forward.
- Authors: Nielsen, Rasmus , Bertelsen, Michael , Ramskov, Daniel , Møller, Merete , Hulme, Adam , Theisen, Daniel , Finch, Caroline , Fortington, Lauren , Mansournia, Mohammad , Parner, Erik
- Date: 2019
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 53, no. 1 (2019), p. 70-78
- Full Text:
- Reviewed:
- Description: Background: Time-to-event modelling is underutilised in sports injury research. Still, sports injury researchers have been encouraged to consider time-to-event analyses as a powerful alternative to other statistical methods. Therefore, it is important to shed light on statistical approaches suitable for analysing training load related key-questions within the sports injury domain. Content: In the present article, we illuminate: (i) the possibilities of including time-varying outcomes in time-to-event analyses, (ii) how to deal with a situation where different types of sports injuries are included in the analyses (ie, competing risks), and (iii) how to deal with the situation where multiple subsequent injuries occur in the same athlete. Conclusion: Time-to-event analyses can handle time-varying outcomes, competing risk and multiple subsequent injuries. Although powerful, time-to-event has important requirements: researchers are encouraged to carefully consider prior to any data collection that five injuries per exposure state or transition is needed to avoid conducting statistical analyses on time-to-event data leading to biased results. This requirement becomes particularly difficult to accommodate when a stratified analysis is required as the number of variables increases exponentially for each additional strata included. In future sports injury research, we need stratified analyses if the target of our research is to respond to the question: 'how much change in training load is too much before injury is sustained, among athletes with different characteristics?' Responding to this question using multiple time-varying exposures (and outcomes) requires millions of injuries. This should not be a barrier for future research, but collaborations across borders to collecting the amount of data needed seems to be an important step forward.
Adiposity as a risk factor for sport injury in youth : a systematic review
- Toomey, Clodagh, Whittaker, Jackie, Richmond, Sarah, Owoeye, Oluwatoyosi, Patton, Declan, Emery, Carolyn
- Authors: Toomey, Clodagh , Whittaker, Jackie , Richmond, Sarah , Owoeye, Oluwatoyosi , Patton, Declan , Emery, Carolyn
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Clinical Journal of Sport Medicine Vol. 32, no. 4 (2022), p. 418-426
- Full Text: false
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- Description: Objective: To determine whether high or low adiposity is associated with youth sport-related injury.Data Sources: Ten electronic databases were searched to identify prospective studies examining the association between adiposity [body mass index (BMI) or body fat] and a future time-loss or medical attention sport-related musculoskeletal injury or concussion in youth aged 20 years and younger. Two independent raters assessed the quality (Downs and Black criteria) and risk of bias (Joanna Briggs Institute Critical Appraisal Tool). Random-effects meta-analyses were used to calculate pooled odds ratio [95% confidence interval (CI)] of injury.Main Results: Of 11 424 potentially relevant records, 38 articles were included with 17 eligible for meta-analyses. In qualitative synthesis, no clear association was identified between adiposity and any sport injury; however, 16/22 studies identified high adiposity as a significant risk factor for lower-extremity injury. Meta-analyses revealed higher BMI in youth with any sport-related injury and lower BMI in youth who developed a bone stress injury (BSI) compared with noninjured controls. The pooled OR (95% CI) examining the association of BMI and injury risk (excluding bone injury) was 1.18 (95% CI: 1.03-1.34). A major source of bias in included articles was inconsistent adjustment for age, sex, and physical activity participation.Conclusions: Level 2b evidence suggests that high BMI is associated with greater risk of youth sport injury, particularly lower-extremity injury and excluding BSI or fracture. Although pooled mean differences were low, anthropometric risk of injury seems to be dependent on type and site of injury in youth sport. © 2021 Wolters Kluwer Health, Inc.
- Lindsay, Riki, McNeil, Dominic, Spittle, Michael
- Authors: Lindsay, Riki , McNeil, Dominic , Spittle, Michael
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Journal of Imagery Research in Sport and Physical Activity Vol. 18, no. 1 (2023), p.
- Full Text: false
- Reviewed:
- Description: Returning to sport and exercise following injury requires the athlete to become more confident in the ability to gradually explore the use of the injured area in increasingly complex and challenging ways. Emotional responses, such as fear of re-injury, are a key mental health barrier to a performer's return to sport and exercise. To navigate such psychological responses, performers need well-developed psychological strategies, like mental imagery (MI), to facilitate a successful return to pre-injury levels of sport and exercise. MI is a well-established strategy for dealing with negative symptoms associated with injury, providing a safe and less intimidating environment to practice movements that may be perceived as risky and otherwise performed within physical training due to the fear of causing further injury. This paper aims to provide sport psychologists with recommendations on how to utilize MI to reduce fear of re-injury during the rehabilitation process to successfully facilitate return to sport and exercise. Specific examples are also outlined and discussed. © 2023 Walter de Gruyter GmbH, Berlin/Boston.
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