Portrait of Professor Louis Passfield

Professor Louis Passfield



I started at Kent in 2007 as Head of School and held this role until last year. Prior to taking on this role I worked with British Cycling as their sports scientist leading their preparation for the Beijing Olympics. In the past I've also been sports scientist for the Barcelona 1992 and Atlanta 1996 British Olympic Cycling teams.

Research interests

A significant part of my research has focused on different aspects of Cycling.

Key themes of this work include data modelling, training and performance. I've also worked extensively as an applied scientist and therefore I've a particular interest in mentoring and developing excellence in practitioners, especially those working in sport.

I'm excited by conducting research that may help change the way we understand the process of training. In particular, looking at how we can use data from wearables, GPS devices and other instruments to help optimise an individual's training process. In addition, I'm exploring how people train, and how people learn, and whether there are important links between these. The above is likely an exercise in complexity science and therefore I'm also very interested helping people better understand the implications of this in their work.


I lead the Professional Doctorate programme which is designed for practitioners in sport and exercise who want to develop themselves and their professional practice.


Showing 50 of 77 total publications in the Kent Academic Repository. View all publications.


  • Earl, S. et al. (2019). Young adolescent psychological need profiles: Associations with classroom achievement and well-being. Psychology in the Schools [Online]. Available at: https://doi.org/10.1002/pits.22243​.
    Drawing on self‐determination theory, a person‐centered methodology was adopted to identify distinct pupil profiles based on their psychological need satisfaction. A sample of 586 pupils (387 male, 199 female; mean age = 12.6, range 11–15 years old) from three secondary schools reported their psychological need satisfaction, and well‐ and ill‐being, with teachers rating pupil achievement. Hierarchical cluster analysis revealed five distinct profiles. Four profiles indicated synergy existed between the three needs, showing similar in‐group levels of satisfaction across the needs but in varying amounts. Univariate and multivariate analyses, controlling for school and taught subject, revealed the satisfied group displayed the highest classroom performance (F4,540 = 7.03; p < 0.001; ηp2 = 0.05), well‐being (F8,1,136 = 45.63; p < 0.001; Wilk's Λ = 0.57; ηp2 = 0.24) and lowest ill‐being (F8,1,134 = 23.39; p < 0.001; Wilk's Λ = 0.74, ηp2 = 0.14), whereas the dissatisfied group displayed the most adverse outcomes. The findings illustrate that the three psychological needs may operate interdependently and should be considered in combination rather than in isolation. The research offers practical insights into why pupils may function differently in classrooms and could inform targeted initiatives towards pupils with psychological need satisfaction deficits.
  • Madigan, D. et al. (2019). Development of perfectionism in junior athletes: A three-sample study of coach and parental pressure. Journal of Sport & Exercise Psychology [Online]. Available at: https://doi.org/10.1123/jsep.2018-0287.
    Perfectionism predicts cognitions, emotions, and behaviors in sport. Nonetheless, our understanding of the factors that influence its development is limited. We sought to address this issue by examining the role of coach and parental pressure in the development of perfectionism in sport. Using three samples of junior athletes (16-19 years; cross-sectional: N = 212; 3-month longitudinal: N = 101; 6-month longitudinal: N = 110), we examined relations between coach pressure to be perfect, parental pressure to be perfect, perfectionistic strivings, and perfectionistic concerns. Mini meta-analysis of the combined cross-sectional data (N = 423) showed that both coach pressure and parental pressure were positively correlated with perfectionistic strivings and perfectionistic concerns. In contrast, longitudinal analyses showed that only coach pressure predicted increased perfectionistic strivings and perfectionistic concerns over time. Overall, our findings provide preliminary evidence that coaches may play a more important role in the development of junior athletes’ perfectionism than parents.
  • Madigan, D. et al. (2018). Perfectionism and training performance: The mediating role of other-approach goals. European Journal of Sport Science [Online] 18:1271-1279. Available at: http://dx.doi.org/10.1080/17461391.2018.1508503.
    Recent research found perfectionistic strivings to predict performance in a novel basketball task among novice basketball players. The current study builds on this research by examining whether this is also the case for performance in a familiar basketball training task among experienced basketball players, and whether achievement goals mediated any observed relationships. Perfectionistic strivings, perfectionistic concerns, and 3 × 2 achievement goals were assessed prior to basketball training performance in 90 basketball players (mean age 20.9 years). Regression analyses showed that perfectionistic strivings predicted better performance. Furthermore, mediation analyses showed that other-approach goals (e.g., beliefs that one should and can outperform others) accounted for this relationship. The findings suggest that perfectionistic strivings may predict better performance in both novel and familiar athletic contexts. In addition, beliefs about the importance and ability to outperform others may explain this relationship.
  • Madigan, D. et al. (2018). Perfectionism predicts injury in junior athletes: Preliminary evidence from a prospective study. Journal of Sports Sciences [Online] 36:545-550. Available at: http://dx.doi.org/10.1080/02640414.2017.1322709.
    According to the stress-injury model (Williams & Andersen, 1998), personality factors predisposing athletes to elevated levels of stress may increase the risk of injury. As perfectionism has been associated with chronic stress, it may be one such personality factor. So far, however, no study has investigated the relationships between perfectionism and injury utilising a prospective design. Therefore, the present study examined perfectionistic strivings, perfectionistic concerns, and injury in 80 junior athletes from team and individual sports (mean age 17.1 years, range 16-19 years) over 10 months of active training. The results of logistic regression analyses showed that perfectionism positively predicted injury, but only perfectionistic concerns emerged as a significant positive predictor. The likelihood of sustaining an injury was increased by over 2 times for each 1 SD increase in perfectionistic concerns. The findings suggest that perfectionistic concerns may be a possible factor predisposing athletes to an increased risk of injury.
  • De Coninck, K. et al. (2018). Measuring the morphological characteristics of thoracolumbar fascia in ultrasound images: an inter-rater reliability study. BMC Musculoskeletal Disorders [Online] 19. Available at: http://dx.doi.org/10.1186/s12891-018-2088-5.
    BACKGROUND: Chronic lower back pain is still regarded as a poorly understood multifactorial condition. Recently, the thoracolumbar fascia complex has been found to be a contributing factor. Ultrasound imaging has shown that people with chronic lower back pain demonstrate both a significant decrease in shear strain, and a 25% increase in thickness of the thoracolumbar fascia. There is sparse data on whether medical practitioners agree on the level of disorganisation in ultrasound images of thoracolumbar fascia. The purpose of this study was to establish inter-rater reliability of the ranking of architectural disorganisation of thoracolumbar fascia on a scale from ‘very disorganised’ to ‘very organised’.
    METHODS: An exploratory analysis was performed using a fully crossed design of inter-rater reliability. Thirty observers were recruited, consisting of 21 medical doctors, 7 physiotherapists and 2 radiologists, with an average of 13.03 ± 9.6 years of clinical experience. All 30 observers independently rated the architectural disorganisation of the thoracolumbar fascia in 30 ultrasound scans, on a Likert-type scale with rankings from 1 = very disorganised to 10 = very organised. Internal consistency was assessed using Cronbach’s alpha. Krippendorff’s alpha was used to calculate the overall inter-rater reliability.
    RESULTS: The Krippendorf’s alpha was .61, indicating a modest degree of agreement between observers on the different morphologies of thoracolumbar fascia.The Cronbach’s alpha (0.98), indicated that there was a high degree of consistency between observers. Experience in ultrasound image analysis did not affect constancy between observers (Cronbach’s range between experienced and inexperienced raters: 0.95 and 0.96 respectively).
    CONCLUSIONS: Medical practitioners agree on morphological features such as levels of organisation and disorganisation in ultrasound images of thoracolumbar fascia, regardless of experience. Further analysis by an expert panel is required to develop specific classification criteria for thoracolumbar fascia.
  • Bossi, A. et al. (2018). Pacing strategy and tactical positioning during cyclo-cross races. International Journal of Sports Physiology and Performance [Online]. Available at: https://doi.org/10.1123/ijspp.2017-0183.
    Purpose: To describe pacing strategy and competitive behaviour in elite-level cyclo-cross races. Methods: Data from 329 men and women competing in 5 editions (2012–2016) of UCI Cyclo-cross World Championships were compiled. Individual mean racing speeds from each lap were normalised to the mean speeds of the whole race. Lap-by-lap and final rankings were also explored. Pacing strategy was compared between sexes and between top- and bottom-placed cyclists. Results: A significant main effect of laps was found in 8 out of 10 races (4 positive, 3 variable, 2 even and 1 negative pacing strategies) and an interaction effect of ranking-based groups was found in 2 (2016, male and female races). Kendall's tau-b correlations revealed an increasingly positive relationship between intermediate and final rankings throughout the races. The number of overtakes during races decreased from start to finish, as suggested by significant Friedman tests. In the first lap, normalised cycling speeds were different in 3 out of 5 editions—men were faster in 1 and slower in 2 editions. In the last lap, however, normalised cycling speeds of men were lower than those of women in 4 editions. Conclusions: Elite cyclo-cross competitors adopt slightly distinct pacing strategies in each race, but positive pacing strategies are highly probable in most events, with more changes in rankings during the first laps. Sporadically, top- and bottom-placed groups might adopt different pacing strategies during either male or female races. Men and women seem to distribute their efforts differently, but this effect is of small magnitude.
  • Kordi, M. et al. (2018). Influence of Upright versus Time Trial Cycling Position on Determination of Critical Power and W' in Trained Cyclists. European Journal of Sports Sciences [Online] 19:192-198. Available at: https://doi.org/10.1080/17461391.2018.1495768.
    Body position is known to alter power production and affect cycling performance. The aim of this study was to compare mechanical power output in two riding positions, and to calculate the effects on critical power (CP) and W' estimates. Seven trained cyclists completed three peak power output efforts and three fixed-duration trials (3-, 5- and 12-min) riding with their hands on the brake lever hoods (BLH), or in a time-trial position (TTP). A repeated-measures analysis of variance showed that mean power output during the 5-min trial was significantly different between BLH and TTP positions, resulting in a significantly lower estimate of CP, but not W’, for the TTP trial. In addition, TTP decreased performance during each trial and increased the percentage difference between BLH and TTP with greater trial duration. There were no differences in pedal cadence or heart rate during the 3-min trial; however, TTP results for the 12-min trial showed a significant fall in pedal cadence and a significant rise in heart rate. The findings suggest that cycling position affects power output and influences consequent CP values. Therefore, riders and coaches should consider the cycling position used when calculating CP.
  • Iannetta, D. et al. (2018). Metabolic and performance-related consequences of exercising at and slightly above MLSS. Scandinavian Journal of Medicine & Science in Sports [Online]. Available at: https://doi.org/10.1111/sms.13280.
    Exercising at the maximal lactate steady state (MLSS) results in increased but stable metabolic responses. We tested the hypothesis that even a slight increase above MLSS (10 W), by altering the metabolic steady?state, would reduce exercise performance capacity. Eleven trained men in our study performed: one ramp?incremental tests; two to four 30?min constant?load cycling exercise trials to determine the PO at MLSS (MLSSp), and ten watts above MLSS (MLSSp+10), which were immediately followed by a time?to?exhaustion test; and a time?to?exhaustion test with no?prior exercise. Pulmonary O2 uptake (V?O2) and blood lactate concentration ([La?]b) as well as local muscle O2 extraction ([HHb]) and muscle activity (EMG) of the vastus lateralis (VL) and rectus femoris (RF) muscles were measured during the testing sessions. When exercising at MLSSp+10, although V?O2 was stable, there was an increase in ventilatory responses and EMG activity, along with a non?stable [La?]b response (P<0.05). The [HHb] of VL muscle achieved its apex at MLSSp with no additional increase above this intensity, whereas the [HHb] of RF progressively increased during MLSSp+10 and achieved its apex during the time?to?exhaustion trials. Time?to?exhaustion performance was decreased after exercising at MLSSp (37.3±16.4%) compared to the no?prior exercise condition, and further decreased after exercising at MLSSp+10 (64.6±6.3%) (P<0.05). In summary, exercising for 30 min slightly above MLSS led to significant alterations of metabolic responses which disproportionately compromised subsequent exercise performance. Furthermore, the [HHb] signal of VL seemed to achieve a “ceiling” at the intensity of exercise associated with MLSS.
  • Mattioni Maturana, F. et al. (2017). Critical power: How different protocols and models affect its determination. Journal of Science and Medicine in Sport [Online]. Available at: https://doi.org/10.1016/j.jsams.2017.11.015.
    In cycling, critical power (CP) and work above CP (W’) can be estimated through linear and nonlinearmodels. Despite the concept of CP representing the upper boundary of sustainable exercise,
    overestimations may be made as the models possess inherent limitations and the protocol design is not always appropriate. Objectives: to measure and compare CP and W’ through the exponential (CPexp), 3- parameter hyperbolic (CP3-hyp), 2-parameter hyperbolic (CP2-hyp), linear (CPlinear), and linear 1/time (CP1/time) models, using different combinations of TTE trials of different durations (approximately 1 to 20 min). Design: repeated measures. Methods: Thirteen healthy young cyclists (26±3yrs; 69.0±9.2kg; 174±10cm; 60.4±5.9mL·kg-1·min-1) performed five TTE trials on separate days. CP and W’ were modeled using two, three, four, and/or five trials. All models were compared against a criterion method (CP3-hyp with five trials; confirmed using the leaving-one-out cross-validation analysis) using smallest worthwhile change (SWC) and concordance correlation coefficient (CCC) analyses. Results: CP was considerably overestimated when only trials lasting less than 10 min were included, independent of the mathematical model used. Following CCC analysis, a number of alternative methods were able to predict our criterion method with almost a perfect agreement. However, the application of other common approaches resulted in an overestimation of CP and underestimation of W’, typically these methods only
    included TTE trials lasting less than 12 min. Conclusions: Estimations from CP3-hyp were found to be the most accurate, independently of TTE range. Models that include two trials between 12 and 20 min provide good agreement with the criterion method (for both CP and W’).
  • Passfield, L. and Hopker, J. (2017). A mine of information: can sports analytics provide wisdom from your data? International journal of sports physiology and performance [Online] 12:851-855. Available at: http://dx.doi.org/10.1123/ijspp.2016-0644.
    This paper explores the notion that the availability and analysis of large datasets has the capacity to improve practice and change the nature of science in the sport and exercise setting. The increasing use of data and information technology in sport is giving rise to this change. Websites hold large data repositories and the development of wearable technology, mobile phone applications and related instruments for monitoring physical activity, training and competition, provide large data sets of extensive and detailed measurements. Innovative approaches conceived to exploit more fully these large datasets could provide a basis for more objective evaluation of coaching strategies and new approaches to how science is conducted. The emergence of a new discipline, sports analytics, could help overcome some of the challenges involved in obtaining knowledge and wisdom from these large datasets. Examples of where large datasets have been analyzed, to evaluate the career development of elite cyclists, and to characterize and optimize the training load of well-trained runners are discussed. Careful verification of large datasets is time consuming and imperative before useful conclusions can be drawn. Consequently, it is recommended that prospective studies are preferred to retrospective analyses of data. It is concluded that rigorous analysis of large datasets could enhance our knowledge in the sport and exercise sciences, inform competitive strategies, and allow innovative new research and findings.
  • Coakley, S. and Passfield, L. (2017). Cycling performance is superior for time-to-exhaustion versus time-trial in endurance laboratory tests. Journal of Sports Sciences [Online]:1228-1234. Available at: http://dx.doi.org/10.1080/02640414.2017.1368691.
    Time-to-exhaustion trials (TTE) are used in a laboratory setting to measure endurance performance. However, there is some concern with their ecological validity compared with time-trials (TT). Consequently, we aimed to compare cycling performance in TTE and TT where the duration of the trials was matched. Seventeen trained male cyclists completed three TTE at 80, 100 and 105% of maximal aerobic power (MAP). On a subsequent visit they performed three TT over the same duration as the TTE. Participants were blinded to elapsed time, power output, cadence and heart rate (HR). Average TTE was 865 ± 345 s, 165 ± 98 s and 117 ± 45 s for the 80, 100 and 105% trials respectively. Average power output was higher for TTE (294 ± 44 W) compared to TT (282 ± 43 W) at 80% MAP (P<0.01), but not at 100 and 105% MAP (P>0.05). There was no difference in cadence, HR, or RPE for any trial (P>0.05). Critical power (CP) was also higher when derived from TTE compared to TT (P<0.01). It is concluded that TTE results in a higher average power output compared to TT at 80% MAP. When determining CP, TTE rather than TT protocols appear superior.
  • Coakley, S. and Passfield, L. (2017). Individualised training at different intensities, in untrained participants, results in similar physiological and performance benefits. Journal of Sports Sciences [Online]:1-8. Available at: http://dx.doi.org/10.1080/02640414.2017.1346269.
    The impact of individualising exercise duration on training adaptations has not been explored, in particular when comparing different intensities of exercise. This study compared effects of training at moderate, high, or a combination of the two intensities (mixed) on performance and physiological adaptations, when training durations were individualised. 34 untrained participants were assigned to a moderate, high, or mixed group. Maximal oxygen uptake (V?O2max), power output at V? 43 O2max (MAP), time-to-exhaustion and cycling gross efficiency were recorded before and after four weeks of supervised cycling training (four times per week). The moderate group cycled at 60% MAP in blocks of 5 min with 1 min recovery, and training duration was individualised to 100% of pre-training time-to-exhaustion. The high group cycled at 100% MAP for 2 min with 3 min recovery, and training duration was set as the maximum number of repetitions completed in the first training session. The mixed group completed two moderate- and two high-intensity sessions each week, on alternate days. The V?O2max (d = 0.29; 0.59; 0.29), MAP (d = 0.45; 0.63; 0.61), time-to-exhaustion (d = 1.18; 0.88; 1.00) and cycling gross efficiency at 50% MAP (d = 0.19; 0.11; 1.06) increased after four weeks of moderate-, high- and mixed-intensity training respectively (P<0.05), but there were no differences between groups (P>0.05). When training durations are individualised in untrained participants, similar improvements in performance and physiological measures occur, despite differences in exercise intensity.
  • Passfield, L. (2017). Cycling Science. Journal of Sports Sciences [Online] 35:1327-1327. Available at: http://dx.doi.org/10.1080/02640414.2017.1313625.
  • Nicolò, A., Massaroni, C. and Passfield, L. (2017). Respiratory Frequency during Exercise: The Neglected Physiological Measure. Frontiers in Physiology [Online]. Available at: https://doi.org/10.3389/fphys.2017.00922.
    The use of wearable sensor technology for athlete training monitoring is growing exponentially, but some important measures and related wearable devices have received little attention so far. Respiratory frequency (fR), for example, is emerging as a valuable measurement for training monitoring. Despite the availability of unobtrusive wearable devices measuring fR with relatively good accuracy, fR is not commonly monitored during training. Yet fR is currently measured as a vital sign by multiparameter wearable devices in the military field, clinical settings, and occupational activities. When these devices have been used during exercise, fR was used for limited applications like the estimation of the ventilatory threshold. However, more information can be gained from fR. Unlike heart rate, VO2, and blood lactate, fR is strongly associated with perceived exertion during a variety of exercise paradigms, and under several experimental interventions affecting performance like muscle fatigue, glycogen depletion, heat exposure and hypoxia. This suggests that fR is a strong marker of physical effort. Furthermore, unlike other physiological variables, fR responds rapidly to variations in workload during high-intensity interval training (HIIT), with potential important implications for many sporting activities. This Perspective article aims to (i) present scientific evidence supporting the relevance of fR for training monitoring; (ii) critically revise possible methodologies to measure fR and the accuracy of currently available respiratory wearables; (iii) provide preliminary indication on how to analyze fR data. This viewpoint is expected to advance the field of training monitoring and stimulate directions for future development of sports wearables.
  • Madigan, D., Stoeber, J. and Passfield, L. (2017). Athletes’ perfectionism and reasons for training: Perfectionistic concerns predict training for weight control. Personality and Individual Differences [Online] 115:133-136. Available at: https://doi.org/10.1016/j.paid.2016.03.034.
    Exercise and training for sports are associated with a number of psychological and health benefits. Research on exercise, however, suggests that such benefits depend on the reasons why individuals participate in sport. The present study investigated whether individual differences in perfectionism predicted different reasons for training and examined four dimensions of perfectionism (perfectionistic strivings, perfectionistic concerns, coach pressure to be perfect, parental pressure to be perfect) and three reasons for training (avoidance of negative affect, weight control, mood improvement) in 261 athletes (mean age 20.9 years). Regression analyses showed that perfectionistic concerns positively predicted avoidance of negative affect and weight control, whereas perfectionistic strivings positively predicted mood improvement. The findings suggest that individual differences in perfectionism help explain why athletes train for different reasons.
  • Passfield, L. et al. (2016). Knowledge is Power: Issues of Measuring Training and Performance in Cycling. Journal of Sports Sciences [Online] 35:1426-1434. Available at: http://dx.doi.org/10.1080/02640414.2016.1215504.
    Mobile power meters provide a valid means of measuring cyclists’ power output in the field. These field measurements can be performed with very good accuracy and reliability making the power meter a useful tool for monitoring and evaluating training and race demands. This study examines power meter data from a Grand Tour cyclist’s training and racing and explores the inherent complications created by its stochastic nature. Simple summary methods cannot reflect a session’s variable distribution of power output or indicate its likely metabolic stress. Binning power output data, into training zones for example, provides information on the detail but not the length of efforts within a session. An alternative approach is to track changes in cyclists’ modelled training and racing performances. Both Critical Power and Record Power Profiles have been used for monitoring training-induced changes in this manner. Ultimately, new methods for quantifying the effects of training loads and modelling their implications for future performance are required. Although first proposed 40 years ago, our ability to model the effects of training on performance remain limited and merits further research.
  • Hardiman, N. et al. (2016). Pilot testing of a sampling methodology for assessing seed attachment propensity and transport rate in a soil matrix carried on boot soles and bike tires. Environmental Management [Online]:1-9. Available at: http://dx.doi.org/10.1007/s00267-016-0773-4.
    Land managers of natural areas are under pressure to balance demands for increased recreation access with protection of the natural resource. Unintended dispersal of seeds by visitors to natural areas has high potential for weedy plant invasions, with initial seed attachment an important step in the dispersal process. Although walking and mountain biking are popular nature-based recreation activities there are few studies quantifying propensity for seed attachment and transport rate on boot soles and none for bike tires. Attachment and transport rate can potentially be affected by a wide range of factors for which field testing can be time-consuming and expensive. We pilot tested a sampling methodology for measuring seed attachment and transport rate in a soil matrix carried on boot soles and bike tires traversing a known quantity and density of a seed analog (beads) over different distances and soil conditions. We found % attachment rate on boot soles was much lower overall than previously reported but that boot soles had a higher propensity for seed attachment than bike tires in almost all conditions. We believe our methodology offers a cost-effective option for researchers seeking to manipulate and test effects of different influencing factors on these two dispersal vectors.
  • Madigan, D., Stoeber, J. and Passfield, L. (2016). Perfectionism and attitudes towards doping in junior athletes. Journal of Sports Sciences [Online] 34:700-706. Available at: http://dx.doi.org/10.1080/02640414.2015.1068441.
    Recent theory and research suggest that perfectionism is a personal factor contributing to athletes’ vulnerability to doping (using banned substances/drugs to enhance sporting performance). So far, however, no study has examined what aspects of perfectionism suggest a vulnerability in junior athletes. Employing a cross-sectional design, this study examined perfectionism and attitudes towards doping in 129 male junior athletes (mean age 17.3 years) differentiating four aspects of perfectionism: perfectionistic strivings, perfectionistic concerns, parental pressure to be perfect, and coach pressure to be perfect. In the bivariate correlations, only parental pressure showed a positive relationship with positive doping attitudes. In a multiple regression analysis controlling for the overlap between the four aspects, perfectionistic strivings additionally showed a negative relationship. Moreover, a structural equation model examining the relationships between all variables suggested that coach pressure had a negative indirect effect on attitudes towards doping via perfectionistic strivings. The findings indicate that perceived parental pressure to be perfect may be a factor contributing to junior athletes’ vulnerability to doping, whereas perfectionistic strivings may be a protective factor.
  • Passfield, L. (2016). Diagnosis and Management of Iliac Artery Endofibrosis: Results of a Delphi Consensus Study. European Journal of Vascular and Endovascular Surgery [Online] 52:90-98. Available at: http://dx.doi.org/10.1016/j.ejvs.2016.04.004.

    Iliac endofibrosis is a rare condition that may result in a reduction of blood flow to the lower extremity in young, otherwise healthy individuals. The data to inform everyday clinical management are weak and therefore a Delphi consensus methodology was used to explore areas of consensus and disagreement concerning the diagnosis and management of patients with suspected iliac endofibrosis.

    A three-round Delphi questionnaire approach was used among vascular surgeons, sports physicians, sports scientists, radiologists, and clinical vascular scientists with experience of treating this condition to explore diagnosis and clinical management issues for patients with suspected iliac artery endofibrosis. Analysis is based on 18 responses to round 2 and 14 responses to round 3, with agreement reported when 70% of respondents were in agreement.

    Initially there was agreement on the typical symptoms at presentation and the need for an exercise test in the diagnosis. Round 3 clarified that duplex ultrasound was a useful tool in the diagnosis of endofibrosis. There was consensus on the most appropriate type of surgery (endarterectomy and vein patch) and that endovascular interventions were inadvisable. The final round helped to inform aspects of the natural history and post-operative surveillance. Progression of the disease was likely with continued exercise but cessation may prevent progression. Surveillance after surgery is generally recommended yearly with at least a clinical assessment.

    There is broad agreement about the presenting symptoms and the investigations required to confirm (or exclude) the diagnosis of iliac endofibrosis. There was consensus on the surgical approach to repair. Disagreement existed about the specific diagnostic criteria that should be applied during non-invasive testing and about post-operative care and resumption of exercise.
  • Madigan, D., Stoeber, J. and Passfield, L. (2016). Perfectionism and changes in athlete burnout over three months: Interactive effects of personal standards and evaluative concerns perfectionism. Psychology of Sport and Exercise [Online] 26:32-39. Available at: https://doi.org/10.1016/j.psychsport.2016.05.010.
    Objectives: A recent longitudinal study with junior athletes (Madigan, Stoeber, & Passfield, 2015) found perfectionism to predict changes in athlete burnout: evaluative concerns perfectionism predicted increases in burnout over a 3-month period, whereas personal standards perfectionism predicted decreases. The present study sought to expand on these findings by using the framework of the 2 × 2 model of perfectionism (Gaudreau & Thompson, 2010) to examine whether evaluative concerns perfectionism and personal standards perfectionism show interactions in predicting changes in athlete burnout. Design: Two-wave longitudinal design. Method: The present study examined self-reported evaluative concerns perfectionism, personal standards perfectionism, and athlete burnout in 111 athletes (mean age 24.8 years) over 3 months of active training. Results and Conclusion: When moderated regression analyses were employed, interactive effects of evaluative concerns perfectionism × personal standards perfectionism were found indicating that personal standards perfectionism buffered the effects of evaluative concerns perfectionism on total burnout and physical/emotional exhaustion. To interpret these effects, the 2 × 2 model of perfectionism provides a useful theoretical framework.
  • Arkesteijn, M. et al. (2016). The effect of cycling intensity on cycling economy during seated and standing cycling. International journal of sports physiology and performance [Online] 11:907-912. Available at: http://www.dx.doi.org/10.1123/ijspp.2015-0441.
    Previous research has shown that cycling in a standing position reduces cycling economy compared with seated cycling. It is unknown whether the cycling intensity moderates the reduction in cycling economy while standing.

    The aim was to determine whether the negative effect of standing on cycling economy would be decreased at a higher intensity.

    Ten cyclists cycled in 8 different conditions. Each condition was either at an intensity of 50% or 70% of maximal aerobic power, at a gradient of 4% or 8% and in the seated or standing cycling position. Cycling economy and muscle activation level of 8 leg muscles were recorded.

    There was an interaction between cycling intensity and position for cycling economy (P = 0.03), the overall activation of the leg muscles (P = 0.02) and the activation of the lower leg muscles (P = 0.05). The interaction showed decreased cycling economy when standing compared with seated cycling, but the difference was reduced at higher intensity. The overall activation of the leg muscles and the lower leg muscles respectively increased and decreased, but the differences between standing and seated cycling were reduced at higher intensity.

    Cycling economy was lower during standing cycling than seated cycling, but the difference in economy diminishes when cycling intensity increases. Activation of the lower leg muscles did not explain the lower cycling economy while standing. The increased overall activation therefore suggests that increased activation of the upper leg muscles explains part of the lower cycling economy while standing.
  • Madigan, D., Stoeber, J. and Passfield, L. (2016). Motivation mediates the perfectionism–burnout relationship: A three-wave longitudinal study with junior athletes. Journal of Sport & Exercise Psychology [Online] 38:341-354. Available at: http://dx.doi.org/10.1123/jsep.2015-0238.
    Perfectionism in sports has been shown to predict longitudinal changes in athlete burnout. What mediates these changes over time, however, is still unclear. Adopting a self-determination theory perspective and using a three-wave longitudinal design, the present study examined perfectionistic strivings, perfectionistic concerns, autonomous motivation, controlled motivation, and athlete burnout in 141 junior athletes (mean age 17.3 years) over 6 months of active training. When multilevel structural equation modeling was employed to test a mediational model, a differential pattern of between- and within-person relationships emerged. Whereas autonomous motivation mediated the negative relationship that perfectionistic strivings had with burnout at the between- and within-person level, controlled motivation mediated the positive relationship that perfectionistic concerns had with burnout at the between-person level only. The present findings suggest that differences in autonomous and controlled motivation explain why perfectionism predicts changes in athlete burnout over time.
  • Shah, Y. et al. (2016). The acute effects of integrated myofascial techniques on lumbar paraspinal blood flow compared with kinesio taping: A pilot study. Journal of Bodywork and Movement Therapies [Online] 21:459-467. Available at: http://dx.doi.org/10.1016/j.jbmt.2016.08.012.
    Myofascial techniques and Kinesio Taping are therapeutic interventions used to treat low back pain. However, limited research has been conducted into the underlying physiological effects of these types of treatments.

    The purpose of this study was to compare the acute effects of integrated myofascial techniques (IMT) and Kinesio Tape (KT) on blood flow at the lumbar paraspinal musculature.

    Forty-four healthy participants (18 male and 26 female) (age, 26 ± SD 7) volunteered for this study and were randomly assigned to one of three interventions, IMT, KT or a control group (Sham TENS). Paraspinal blood flow was measured at the L3 vertebral level, using Near Infrared Spectroscopy (NIRS), before and after a 30-minute treatment. Pain Pressure Threshold (PPT) was also measured before and after treatments.

    A one-way ANOVA indicated a significant difference between groups for O2Hb [F (2-41) = 41.6, P<0.001], HHb [F (2-41) = 14.6, P<0.001] and tHb [F (2-41) = 42.2, P <0.001]. Post hoc tests indicated that IMT was significantly greater, from the KT and the control treatments (P<0.001), for changes in O2Hb, HHb, and tHb. There were no significant differences for PPT [F (2-41) = 2.69, p = 0.08], between groups.

    This study demonstrated that IMT increases peripheral blood flow at the paraspinal muscles in healthy participants compared to KT and sham TENS. The change in blood flow had no impact on pain perception in the asymptomatic population group.
  • Madigan, D., Stoeber, J. and Passfield, L. (2016). Perfectionism and training distress in junior athletes: A longitudinal investigation. Journal of Sports Sciences [Online] 35:470-475. Available at: http://dx.doi.org/10.1080/02640414.2016.1172726.
    Perfectionistic athletes may train harder and for longer than non-perfectionistic athletes, leaving them susceptible to elevated levels of training distress. So far, however, no study has investigated the relationships between perfectionism and training distress, a key indicator of overtraining syndrome. Furthermore, no study has determined psychological predictors of overtraining syndrome. Using a two-wave design, the present study examined perfectionistic strivings, perfectionistic concerns, and training distress in 141 junior athletes (mean age 17.3 years, range 16-19 years) over 3 months of active training. Multiple regression analyses were employed to test cross-sectional and longitudinal relationships between perfectionism and training distress. In all analyses, perfectionism emerged as a significant predictor, but strivings and concerns showed differential relationships. When the cross-sectional relationships were regarded, perfectionistic concerns positively predicted training distress (p < .01), whereas perfectionistic strivings negatively predicted training distress (p < .001). When the longitudinal relationships were regarded, only perfectionistic concerns predicted increases in training distress (p < .05), whereas perfectionistic strivings did not (p > .05). The findings suggest that sports scientists who wish to identify athletes at risk of overtraining syndrome may monitor athletes’ perfectionistic concerns as a possible risk factor.
  • Passfield, L. (2016). Determining optimal cadence for an individual road cyclist from field data. European Journal of Sport Science [Online] 16:903-911. Available at: http://dx.doi.org/10.1080/17461391.2016.1146336.
    The cadence that maximises power output developed at the crank by an individual cyclist is conventionally determined using a laboratory test. The purpose of this study was two-fold: (i) to show that such a cadence, which we call the optimal cadence, can be determined using power output, heart-rate, and cadence measured in the field and (ii) to describe methodology to do so. For an individual cyclist's sessions, power output is related to cadence and the elicited heart-rate using a non-linear regression model. Optimal cadences are found for two riders (83 and 70 revolutions per minute, respectively); these cadences are similar to the riders’ preferred cadences (82–92?rpm and 65–75?rpm). Power output reduces by approximately 6% for cadences 20?rpm above or below optimum. Our methodology can be used by a rider to determine an optimal cadence without laboratory testing intervention: the rider will need to collect power output, heart-rate, and cadence measurements from training and racing sessions over an extended period (>6 months); ride at a range of cadences within those sessions; and calculate his/her optimal cadence using the methodology described or a software tool that implements it.
  • Madigan, D., Stoeber, J. and Passfield, L. (2016). Perfectionism and achievement goals revisited: The 3 × 2 achievement goal framework. Psychology of Sport and Exercise [Online] 28:120-124. Available at: https://doi.org/10.1016/j.psychsport.2016.10.008.
    Objectives: Perfectionistic strivings (PS) and perfectionistic concerns (PC) have shown different profiles with the 2 × 2 achievement goals in sport. Whether PS and PC also show comparable profiles with the achievement goals of the expanded 3 × 2 framework, however, is unclear. Design: Cross-sectional. Method: We examined self-reported perfectionistic strivings, perfectionistic concerns, and the 3 × 2 achievement goals in 136 junior athletes (mean age 17.0 years). Results: The results of structural equation modeling showed that PS were positively associated with task-, self-, and other-approach goals and negatively with task- and self-avoidance goals. In contrast, PC were positively associated with task-, self-, and other-avoidance goals and negatively with task- and self-approach goals. Conclusions: The findings suggest that PS and PC show different profiles also with the 3 × 2 achievement goals which may help explain why the two perfectionism dimensions show differential relations with achievement-related outcomes in sport.
  • Earl, S. et al. (2016). Autonomy and Competence Frustration in Young Adolescent Classrooms: Different Associations with Active and Passive Disengagement. Learning and Instruction [Online] 49:32-40. Available at: http://dx.doi.org/10.1016/j.learninstruc.2016.12.001.
    Few studies have attempted to identify distinct psychological correlates of different forms of classroom disengagement. Drawing from basic psychological needs theory (Deci & Ryan, 2000), this study investigated two divergent mechanisms predicting active and passive classroom disengagement. Pupils (N= 647; age = 11–14 years) and their respective teachers completed a questionnaire measuring the study variables. Using structural equation modelling, pupils’ perceptions of teacher psychological control positively predicted pupils’ autonomy and competence frustration in class. Pupils’ competence frustration indirectly and positively associated with teacher-rated passive disengagement (e.g. daydreaming in class), via reduced feelings of vitality. Pupils’ autonomy frustration demonstrated positive associations with both active disengagement (e.g. talking and making noise) and passive disengagement but neither relationship was explained by feelings of vitality. These distinct mechanisms may have implications for educators, identifying potential causes of different forms of pupil disengagement and the importance of avoiding psychological control in classrooms.
  • Coleman, D., Hopker, J. and Passfield, L. (2015). Age differences in efficiency of locomotion and maximal power output in well-trained triathletes. European Journal of Applied Physiology 115:221.
  • Kosmidis, I. and Passfield, L. (2015). Linking the performance of endurance runners to training and physiological effects via multi-resolution elastic net. arXiv [Online]:1-8. Available at: http://arxiv.org/abs/1506.01388v2.
    A multiplicative effects model is introduced for the identification of the factors that are influential to the performance of highly-trained endurance runners. The model extends the established power-law relationship between performance times and distances by taking into account the effect of the physiological status of the runners, and training effects extracted from GPS records collected over the course of a year. In order to incorporate information on the runners' training into the model, the concept of the training distribution profile is introduced and its ability to capture the characteristics of the training session is discussed. The covariates that are relevant to runner performance as response are identified using a procedure termed multi-resolution elastic net. Multi-resolution elastic net allows the simultaneous identification of scalar covariates and of intervals on the domain of one or more functional covariates that are most influential for the response. The results identify a contiguous group of speed intervals between 5.3 to 5.7 m?s?1 as influential for the improvement of running performance and extend established relationships between physiological status and runner performance. Another outcome of multi-resolution elastic net is a predictive equation for performance based on the minimization of the mean squared prediction error on a test data set across resolutions.
  • Madigan, D., Stoeber, J. and Passfield, L. (2015). Perfectionism and burnout in junior athletes: A three-month longitudinal study. Journal of Sport and Exercise Psychology [Online] 37:305-315. Available at: http://dx.doi.org/10.1123/jsep.2014-0266.
    Perfectionism in sports has been shown to be associated with burnout in athletes. Whether perfectionism predicts longitudinal changes in athlete burnout, however, is still unclear. Using a two-wave cross-lagged panel design, the present study examined perfectionistic strivings, perfectionistic concerns, and athlete burnout in 101 junior athletes (mean age 17.7 years) over 3 months of active training. When structural equation modeling was employed to test a series of competing models, the best-fitting model showed opposite patterns for perfectionistic strivings and perfectionistic concerns. Whereas perfectionistic concerns predicted increases in athlete burnout over the 3 months, perfectionistic strivings predicted decreases. The present findings suggest that perfectionistic concerns are a risk factor for junior athletes contributing to the development of athlete burnout whereas perfectionistic strivings appear to be a protective factor.
  • Hopker, J. et al. (2015). Using retrospective analysis of race results to determine success in elite cycling. Journal of Science and Cycling Volume [Online] 4. Available at: https://search.proquest.com/openview/3b5543748ad7d995f2b4d21f7cef0146/1?pq-origsite=gscholar&cbl=2031905.
  • Galbraith, A., Hopker, J. and Passfield, L. (2015). Modeling Intermittent Running from a Single-visit Field Test. International journal of sports medicine [Online] 36:365-370. Available at: http://dx.doi.org/10.1055/s-0034-1394465.
    This study assessed whether the distance-time relationship could be modeled to predict time to exhaustion (TTE) during intermittent running. 13 male distance runners (age: 33±14 years) completed a field test and 3 interval tests on an outdoor 400?m athletic track. Field-tests involved trials over 3?600?m, 2?400?m and 1?200?m with a 30-min rest between each run. Interval tests consisted of: 1?000?m at 107% of CS with 200?m at 95% CS; 600?m at 110% of CS with 200?m at 90% CS; 200?m at 150% of CS with 200?m at 80% CS. Interval sessions were separated by 24?h recovery. Field-test CS and D' were applied to linear and non-linear models to estimate the point of interval session termination. Actual and predicted TTE using the linear model were not significantly different in the 1?000?m and 600?m trials. Actual TTE was significantly lower (P=0.01) than predicted TTE in the 200?m trial. Typical error was high across the trials (range 334-1?709?s). The mean balance of D' remaining at interval session termination was significantly lower when estimated from the non-linear model (-21.2 vs. 13.4?m, P<0.01), however no closer to zero than the linear model. Neither the linear or non-linear model could closely predict TTE during intermittent running.
  • Thomas, T. et al. (2015). Effectiveness of a tailored training programme in behaviour change counselling for community pharmacists: A pilot study. Patient Education and Counseling [Online] 99:132-138. Available at: http://dx.doi.org/10.1016/j.pec.2015.08.004.
    Objective: To undertake a pilot study assessing effectiveness of a tailored training programme in
    behaviour change counselling (BCC) for community pharmacists on, their competence and confidence in
    delivering behaviour change consultations, skill retention over time and impact on practice.
    Methods: Community pharmacists (N = 87) attending Primary Care Trust training were given study
    information and invited to take part. Baseline BCC competence of consenting pharmacists (n = 17) was
    assessed using the Behaviour Change Counselling Index (BECCI). Following BCC training, competence was
    reassessed at 1, 3 and 6 months. Friedman’s test was used to compare median BECCI item scores at
    baseline and after 6 months. Structured interviews were conducted to assess pharmacists’ confidence in
    BCC consultations after training.
    Results: Baseline BECCI scores of 0–2 demonstrated pharmacists had not reached competence threshold.
    Six months after training, BECCI scores improved significantly from baseline (p < 0.05). Competence in
    delivering BCC (scores of 3–4) was achieved at 3 months, but lost at 6 months for some items. After
    training, pharmacists felt confident in delivering BCC.
    Conclusion: Training pharmacists enabled them to deliver BCC competently and confidently.
    Practice implications: BCC aligns with pharmacist-patient consultations. It took 3 months to achieve
    competence. Ongoing support may be needed to maintain competence long-term
  • Galbraith, A., Hopker, J. and Passfield, L. (2015). Modeling Intermittent Running from a Single-visit Field Test. International Journal of Sports Medicine [Online] 36:365-370. Available at: http://dx.doi.org/10.1055/s-0034-1394465.
    This study assessed whether the distance-time relationship could be modeled to predict time to exhaustion (TTE) during intermittent running. 13 male distance runners (age: 33±14 years) completed a field test and 3 interval tests on an outdoor 400?m athletic track. Field-tests involved trials over 3600?m, 2400?m and 1200?m with a 30-min rest between each run. Interval tests consisted of: 1000?m at 107% of CS with 200?m at 95% CS; 600?m at 110% of CS with 200?m at 90% CS; 200?m at 150% of CS with 200?m at 80% CS. Interval sessions were separated by 24?h recovery. Field-test CS and D? were applied to linear and non-linear models to estimate the point of interval session termination. Actual and predicted TTE using the linear model were not significantly different in the 1000?m and 600?m trials. Actual TTE was significantly lower (P=0.01) than predicted TTE in the 200?m trial. Typical error was high across the trials (range 334–1709?s). The mean balance of D? remaining at interval session termination was significantly lower when estimated from the non-linear model (?21.2 vs. 13.4?m, P<0.01), however no closer to zero than the linear model. Neither the linear or non-linear model could closely predict TTE during intermittent running.
  • Karsten, B. et al. (2014). The 3-min Test Does not Provide a Valid Measure of Critical Power Using the SRM Isokinetic Mode. International journal of sports medicine [Online] 35:304-309. Available at: http://dx.doi.org/10.1055/s-0033-1349093.
    Recent datas suggest that the mean power over the final 30 s of a 3-min all-out test is equivalent to Critical Power (CP) using the linear ergometer mode. The purpose of the present study was to identify whether this is also true using an "isokinetic mode". 13 cyclists performed: 1) a ramp test; 2) three 3-min all-out trials to establish End Power (EP) and work done above EP (WEP); and 3) 3 constant work rate trials to determine CP and the work done above CP (W') using the work-time (=CP1/W'1) and 1/time (=CP2/W'2) models. Coefficient of variation in EP was 4.45% between trials 1 and 2, and 4.29% between trials 2 and 3. Limits of Agreement for trials 1-2 and trials 2-3 were -2±38 W. Significant differences were observed between EP and CP1 (+37 W, P<0.001), between WEP and W'1(-6.2 kJ, P=0.001), between EP and CP2 (+31 W, P<0.001) and between WEP and W'2 (-4.2 kJ, P=0.006). Average SEE values for EP-CP1 and EP-CP2 of 7.1% and 6.6% respectively were identified. Data suggest that using an isokinetic mode 3-min all-out test, while yielding a reliable measure of EP, does not provide a valid measure of CP.
  • Galbraith, A. et al. (2014). A Single-Visit Field Test of Critical Speed. International journal of sports physiology and performance [Online] 9:931-935. Available at: http://dx.doi.org/10.1123/ijspp.2013-0507.

    To compare critical speed (CS) measured from a single-visit field test of the distance-time relationship with the "traditional" treadmill time-to-exhaustion multivisit protocol.


    Ten male distance runners completed treadmill and field tests to calculate CS and the maximum distance performed above CS (D'). The field test involved 3 runs on a single visit to an outdoor athletics track over 3600, 2400, and 1200 m. Two field-test protocols were evaluated using either a 30-min recovery or a 60-min recovery between runs. The treadmill test involved runs to exhaustion at 100%, 105%, and 110% of velocity at VO2max, with 24 h recovery between runs.


    There was no difference in CS measured with the treadmill and 30-min- and 60-minrecovery field tests (P < .05). CS from the treadmill test was highly correlated with CS from the 30- and 60-min-recovery field tests (r = .89, r = .82; P < .05). However there was a difference and no correlation in D' between the treadmill test and the 30 and 60-min-recovery field tests (r = .13; r = .33, P > .05). A typical error of the estimate of 0.14 m/s (95% confidence limits 0.09-0.26 m/s) was seen for CS and 88 m (95% confidence limits 60-169 m) for D'. A coefficient of variation of 0.4% (95% confidence limits: 0.3-0.8%) was found for repeat tests of CS and 13% (95% confidence limits 10-27%) for D'.


    The single-visit method provides a useful alternative for assessing CS in the field.
  • Galbraith, A. et al. (2014). A 1-Year Study of Endurance Runners: Training, Laboratory Tests, and Field Tests. International journal of sports physiology and performance [Online] 9:1019-1025. Available at: http://dx.doi.org/10.1123/ijspp.2013-0508.

    To examine the training and concomitant changes in laboratory- and field-test performance of highly trained endurance runners.


    Fourteen highly trained male endurance runners (mean ± SD maximal oxygen uptake [VO2max] 69.8 ± 6.3 mL · kg-1 · min-1) completed this 1-y training study commencing in April. During the study the runners undertook 5 laboratory tests of VO2max, lactate threshold (LT), and running economy and 9 field tests to determine critical speed (CS) and the modeled maximum distance performed above CS (D'). The data for different periods of the year were compared using repeated-measures ANOVA. The influence of training on laboratory- and field-test changes was analyzed by multiple regression.


    Total training distance varied during the year and was lower in May-July (333 ± 206 km, P = .01) and July-August (339 ± 206 km, P = .02) than in the subsequent January-February period (474 ± 188 km). VO2max increased from the April baseline (4.7 ± 0.4 L/min) in October and January periods (5.0 ± 0.4 L/min, P ? .01). Other laboratory measures did not change. Runners' CS was lowest in August (4.90 ± 0.32 m/s) and highest in February (4.99 ± 0.30 m/s, P = .02). Total training distance and the percentage of training time spent above LT velocity explained 33% of the variation in CS.


    Highly trained endurance runners achieve small but significant changes in VO2max and CS in a year. Increases in training distance and time above LT velocity were related to increases in CS.
  • Arkesteijn, M. et al. (2013). The effect of turbo trainer cycling on pedalling technique and cycling efficiency. International journal of sports medicine 34:520-5.
    Cycling can be performed on the road or indoors on stationary ergometers. The purpose of this study was to investigate differences in cycling efficiency, muscle activity and pedal forces during cycling on a stationary turbo trainer compared with a treadmill. 19 male cyclists cycled on a stationary turbo trainer and on a treadmill at 150, 200 and 250 W. Cycling efficiency was determined using the Douglas bags, muscle activity patterns were determined using surface electromyography and pedal forces were recorded with instrumented pedals. Treadmill cycling induced a larger muscular contribution from Gastrocnemius Lateralis, Biceps Femoris and Gluteus Maximus of respectively 14%, 19% and 10% compared with turbo trainer cycling (p<0.05). Conversely, Turbo trainer cycling induced larger muscular contribution from Vastus Lateralis, Rectus Femoris and Tibialis Anterior of respectively 7%, 17% and 14% compared with treadmill cycling (p<0.05). The alterations in muscle activity resulted in a better distribution of power during the pedal revolution, as determined by an increased Dead Centre size (p<0.05). Despite the alterations in muscle activity and pedalling technique, no difference in efficiency between treadmill (18.8±0.7%) and turbo trainer (18.5±0.6%) cycling was observed. These results suggest that cycling technique and type of ergometer can be altered without affecting cycling efficiency.
  • Passfield, L. et al. (2013). Objective time-binning in exposure variation analysis. IMA Journal of Management Mathematics [Online] 24:269-282. Available at: http://dx.doi.org/10.1093/imaman/dps009.
    The development of optimized training regimens requires a comprehensive understanding of training induced adaptations using a combination of laboratory-based and field-based research methods. Field based research often necessitates the use of data-reduction methods, which frequently require sports scientists to make discretization choices. In the present paper, we show how Shannon entropy can be used to reduce the inherent subjectivity of these binning choices when exposure variation analysis is used to quantify variation in power output in training data from competitive cyclists.
  • Hopker, J. and Passfield, L. (2013). Comments on Point:Counterpoint: Skeletal muscle mechanical efficiency does/does not increase with age. Journal of Applied Physiology [Online] 114:1114-1118. Available at: http://dx.doi.org/10.1152/japplphysiol.00185.2013.
  • Arkesteijn, M. et al. (2013). Effect of gradient on cycling gross efficiency and technique. Medicine and Science in Sports and Exercise [Online] 45:920-6. Available at: http://dx.doi.org/10.1249/MSS.0b013e31827d1bdb.

    The purpose of this study was to determine the effect of gradient on cycling gross efficiency and pedaling technique.


    Eighteen trained cyclists were tested for efficiency, index of pedal force effectiveness (IFE), distribution of power production during the pedal revolution (dead center size [DC]), and timing and level of muscle activity of eight leg muscles. Cycling was performed on a treadmill at gradients of 0% (level), 4%, and 8%, each at three different cadences (60, 75, and 90 rev·min).


    Efficiency was significantly decreased at a gradient of 8% compared with both 0% and 4% (P < 0.05). The relationship between cadence and efficiency was not changed by gradient (P > 0.05). At a gradient of 8%, there was a larger IFE between 45° and 225° and larger DC, compared with 0% and 4% (P < 0.05). The onset of muscle activity for vastus lateralis, vastus medialis, gastrocnemius lateralis, and gastrocnemius medialis occurred earlier with increasing gradient (all P < 0.05), whereas none of the muscles showed a change in offset (P > 0.05). Uphill cycling increased the overall muscle activity level (P < 0.05), mainly induced by increased calf muscle activity.


    These results suggest that uphill cycling decreases cycling gross efficiency and is associated with changes in pedaling technique.
  • Hopker, J. and Passfield, L. (2013). The measurement of exercise efficiency. Journal of Applied Physiology [Online] 114:1114-1114. Available at: http://dx.doi.org/10.1152/japplphysiol.00185.2013.
    Comments to the editor
  • Jobson, S. et al. (2013). Inter- and intra-session reliability of muscle activity patterns during cycling. Journal of Electromyography and Kinesiology [Online] 23:230-7. Available at: http://dx.doi.org/10.1016/j.jelekin.2012.08.013.
    The aim of this study was to determine the inter- and intra-session reliability of the temporal and magnitude components of activity in eight muscles considered important for the leg cycling action. On three separate occasions, 13 male non-cyclists and 11 male cyclists completed 6 min of cycling at 135, 150, and 165 W. Cyclists completed two additional 6-min bouts at 215 and 265 W. Surface electromyography was used to record the electrical activity of tibialis anterior, soleus, gastrocnemius medialis, gastrocnemius lateralis, vastus medialis, vastus lateralis, rectus femoris, and gluteus maximus. There were no differences (P > 0.05) in the muscle activity onset and offset or in the iEMG of any muscles between visits. There were also no differences (P > 0.05) between cyclists and non-cyclists in the variability of these parameters. Overall, standard error of measurement (SEM) and intra-class correlation analyses suggested similar reliability of both inter- and intra-session muscle activity onset and offset. The SEM of activity onset in tibialis anterior and activity offset in soleus, gastrocnemius lateralis and rectus femoris was markedly higher than in the other muscles. Intra-session iEMG was reliable (coefficient of variation (CV) = 5.3-13.5%, across all muscles), though a CV range of 15.8-43.1% identified low inter-session iEMG reliability. During submaximal cycling, the temporal components of muscle activity exhibit similar intra- and inter-session reliability. The magnitude component of muscle activity is reliable on an intra-session basis, but not on an inter-session basis.
  • Layec, G. et al. (2013). Comments on point:counterpoint: skeletal muscle mechanical efficiency does/does not increase with age. Journal of Applied Physiology [Online] 114:1114-1118. Available at: http://dx.doi.org/10.1152/japplphysiol.00185.2013.
  • Galbraith, A., Hopker, J. and Passfield, L. (2013). Changes in laboratory and field based measurements in highly trained runners across a training year. British Journal of Sports Medicine [Online] 47:e4. Available at: http://dx.doi.org/10.1136/bjsports-2013-093073.4.
    We examined the effects of one year's endurance training on laboratory and field-based fitness measures in highly trained distance runners. Fourteen distance runners (mean±SD: age 28±8?y, body mass 67.0±6.3?kg, VO2max 69.8±6.3?mL.kg?1.min?1) with at least 2 years competitive experience completed 5 laboratory and 9 field tests across a 12 month period, during which time training volume and intensity were monitored. The laboratory tests measured VO2max, lactate threshold (LT) and running economy, whilst the field tests measured critical speed (CS) and the maximum distance that can be performed above CS (D’). The data were analyzed using repeated measures ANOVA, correlation coefficients and multiple regression. VO2max (L.min?1) changed during the year, being higher in October (5.0?L.min?1, P<0.01) and January (5.0?L.min?1, P=0.01), than in April (4.7?L.min?1). There were no changes in the other laboratory measures during the study. Total distance covered in training changed during the year, being higher in January-February (474?km) than May-July (333?km; P=0.01) and July-August (339?km; P=0.02). Total distance covered in the training period preceding the laboratory test correlated with LT and running economy (r=0.55, P<0.01; r=-0.33, P=0.01). CS changed during the year (P=0.02), being at its lowest in August (4.90?m.s?1) and reaching a peak in February (4.99?m.s?1). There were no differences in D’ across the study (P=0.11). Total training distance and percentage of training time spent above threshold velocity explained 33% of the variation in CS. Increasing training distance and the percentage of training time above threshold velocity was shown to increase CS.
  • Hopker, J., Coleman, D. and Passfield, L. (2013). Reply to Boning and Pries. Journal of applied physiology [Online] 115:1863-1863. Available at: http://dx.doi.org/10.1152/japplphysiol.01061.2013.

Conference or workshop item

  • Hopker, J. and Passfield, L. (2016). Modelling of Cycling Power Output Data and its applicability for anti-doping. in: Science & Cycling 2016.
  • De Coninck, K. et al. (2015). Inter-observer agreement of thoracolumbar fascia morphology: An exploratory analysis of ultrasound images. in: pp. 668-669.
  • De Coninck, K. et al. (2015). Inter-observer agreement of thoracolumbar fascia morphology: an exploratory analysis of ultrasound images. in: Fourth International Fascia Research Congress. Elsevier, pp. 668-669. Available at: https://doi.org/10.1016/j.jbmt.2015.07.005.
    BACKGROUND: Ultrasound imaging (USI) has been shown to be a valid method to investigate the morphology of the thoracolumbar fascia (TLF) [1]. A USI-based study has demonstrated that the TLF of subjects with chronic lower back pain (LBP) is on average 25% thicker and more disorganised compared to a control group [1]. The aim of this study is to explore inter-observer agreement between a range of clinicians on (dis)organisation of TLF in ultrasound images. There are currently no validated methods for the evaluation of USI of TLF.
    METHODS: Design: an exploratory analysis using a fully crossed design of inter-observer agreement. This study was approved by the University of Kent’s School of Sport and Exercise Sciences Research and Ethics Committee (Prop. 163 – 2013). Participants: Thirty observers consisting of 21 (70%) Medical Doctors, 7 (23%) physiotherapists and 2 (6%) radiologists, with a combined total average of 13 years of clinical experience (± SD 9.4). 57% had no experience in USI, 36% had experience ranging from monthly to daily evaluations of USI, no observers had experience in evaluating USI of TLF. Protocol: A sub-set of thirty ultrasound scans of TLF were randomly selected from a data set of 308 scans of subjects with and without LBP (from a larger study conducted by the first author). All scans were anonymised and displayed on a desktop computer, or projected on a screen. All observers viewed and rated each of the 30 scans independently on a Likert-type scale from 1(very disorganised) to 10 (very organised). Inter-observer agreement was assessed using a two-way mixed, consistency, average measures intra-class correlation (ICC), the Cronbach’s Alpha, to assess consistency among observers. The Krippendorff’s Alpha (Kalpha) [2] reliability estimate was used to assess agreement.
    RESULTS: The resulting ICC was in the excellent range, ICC = 0.98, indicating that observers had a high degree of consistency, suggesting that (dis)organisation was rated similarly across observers. Observers without USI experience scored an ICC = 0.96, observers with USI experience scored an ICC = 0.95, again both in the excellent range. In this small cohort, experience in USI does not appear to impact on consistency. The Krippendorff’s ordinal alpha ? was .621, indicating a modest degree of agreement.
    CONCLUSIONS: The high ICC and modest Kalpha suggest that a minimal amount of measurement error was introduced by the independent observers, and therefore statistical power for subsequent analyses is not substantially reduced. This will allow for further analysis of USI images of TLF in terms of morphology and classification. This could ultimately, lead to a meaningful evaluation of treatments of TLF.
  • Hopker, J. et al. (2013). The Influence of ageing and training status on exercise efficiency and cycling performance. in: European College of Sports Sciences.
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