Background: The concept of force-velocity (FV) profiling is inspired by the fundamental properties of skeletal muscles, where there is an inverse relationship between force and velocity. The measurement of force and the corresponding velocity during varying loads have been conducted since the start of the 20th century. Due to rapid advances in technology, devices that can measure forces and velocities in a variety of movements have increased rapidly in recent years. As a result, FV profiling has gained popularity among coaches, athletes, and scientists as a tool for performance assessment and individualized training prescriptions. Purpose: The purpose of this Ph.D. thesis was to investigate the use of force- velocity profiling as a tool for performance assessment and individualized training prescriptions in athletes. To achieve this aim, three experimental studies were conducted, each addressing a specific research question. Study I aimed to assess the reliability and agreement of commonly used measurement equipment for evaluating force-velocity profiles in well-trained and elite athletes. Study II investigated the effectiveness of an individualized training approach based on FV-profiling on jumping performance in well-trained athletes. Lastly, Study III aimed to investigate whether a placebo effect is present when participants are told they are receiving "optimal training" compared to "control training." The hypothesis was that FV-variables obtained from different measurement equipment would not be consistent, and the reliability would depend on the equipment and procedures used. The thesis also hypothesized that individualized training based on FV-profiling would lead to greater improvements in jump height compared to traditional power training. Additionally, a placebo effect was anticipated when participants were informed, they were receiving "optimal training." Methods: In total, 216 participants were initially included for testing across all three studies. Study I: Involved 100 participants (male and female) ranging from world-class Olympic medalists to club-level athletes. The study design involved physical testing of participants four times, with the first two testing timepoints separated by approximately one week, followed by a training period of two to six months, and the last two timepoints separated by approximately one week. The data was collected from various Olympic training and testing facilities. The XII testing protocol consisted of a series of squat jumps (SJ), countermovement jumps (CMJ), and a leg press test with incremental loads. The FV-relationship was derived from a force plate, a linear position transducer encoder, and a flight- time calculation method. To determine the FV-variables, the average force and velocity measurements for each test were fitted with linear regression, resulting in theoretical maximal force (F0), velocity (V0), power (PMAX), and the slope of the FV profile (SFV). Study II: A 10-week training intervention was carried out on 46 national-level team sport athletes (20 ± 4 years, 83 ± 13 kg) from ice-hockey, handball, and soccer. To develop a theoretical optimal squat jump (SJ)-FV- profile, SJ with five different loads (0, 20, 40, 60, and 80 kg) was performed. Based on the participants' initial FV-profile, athletes were randomly assigned to train toward, away, or independently (balanced training) of their initial theoretical optimal FV-profile, utilizing training material that was the same across groups in terms of sets x repetitions but changed in relative loading to target different parts of the FV-profile. The athletes were assessed in 10 and 30 m sprints, SJ, and CMJ, one repetition maximum (1RM) squat, and a leg-press power test before and after the intervention. Study III: 70 male and female Athletes were recruited for a 10-week training intervention. Participants were informed that they were either in the individualized training program based on their force-velocity profile (Placebo) or the control group (Control). Despite the different allocations, both groups followed the same workout routines on average. The testing protocol included CMJs with progressively heavier weights, 20-meter sprints, 1RM back squats, and leg-press tests. Ultrasound measurements were taken using a brightness mode (B-mode) ultrasonography apparatus to measure the resting muscle thickness of the m. rectus femoris. The SETS scale (Stanford Expectations of Treatment Scale) was used to evaluate positive and negative treatment expectations toward the intervention. Results: In Study I, although individual FV-profiles displayed strong linearity (R2>0.95), yet the SFV was unreliable for all measurement methods during vertical jumping (coefficient of variation (CV): 14-30%, interclass correlation coefficient (ICC): 0.36-0.79). Further, only the leg press exercise displayed acceptable reliability for all four FV-variables (F0, V0, PMAX, SFV) (CV: 3.7-8.3%, ICC: 0.82-0.98). While F0 and PMAX demonstrated a relative agreement across measurement methods (Pearson r: 0.56-0.95, Standard Error of Estimate [SEE] %: 5.8-18.8), V0 and SFV showed lower to no agreement across methods (r: - XIII 0.39-0.78, SEE%: 12.2-37.2). In Study II, the results indicated no significant group differences in any of the performance measures. Changes toward the optimal SJ-FV-profile had a negative correlation with changes in SJ height (r = - 0.49, p < 0.001). Changes in SJ-power had a positive correlation with changes in SJ-height (r = 0.88, p < 0.001) and CMJ-height (r = 0.32, p = 0.044), but no significant correlation with changes in 10 m (r = -0.02, p = 0.921) and 30 m sprint time (r = -0.01, p = 0.974). Small to trivial changes in 1RM squat (2.9%, 4.6%, and 6.5%), 10 m sprint time (1.0%, -0.9%, and -1.7%), 30 m sprint time (0.9%, -0.6%, and -0.4%), CMJ height (4.3%, 3.1%, and 5.7%), SJ height (4.8%, 3.7%, and 5.7%), and leg-press power (6.7%, 4.2%, and 2.9%) were observed in the groups training toward, away, or irrespective of their initial theoretical optimal FV-profile, respectively. In Study III, the Placebo group demonstrated a significant increase in 1RM squat compared to Control (5.7 ± 6.4% vs. 0.9 ± 6.9%, [0.26 vs 0.02 Effect Size], Bayes Factor: 5.1 [BF 10], p = 0.025). Additionally, the Placebo group showed slightly higher adherence to the training program compared to Control (82 ± 18% vs. 72 ± 13%, BF10: 2.0, p = 0.08). After controlling for adherence, the difference in 1RM squat between the groups remained significant (p = 0.013), while no significant differences were observed in the other measurements. Conclusions: Study I, Test-retest reliability of the FV-profile can be affected by various factors, including biological, technical, and methodological variation. However, what sets it apart from other performance assessments is the distance/degree of extrapolation to the FV-intercepts, which also plays a crucial role in its reliability. Our data shows that when there is a 5-10% variation in individual jumps, V0 and SFV cannot be accurately measured, regardless of the measurement method used. It is important to be aware of these limitations when assessing FV-profiles, especially in jumping tasks. For improved accuracy of FV- profile assessments, efforts should be made to reduce variation in jumping performance and/or assess loads closer to the FV-intercepts. Study II challenges the notion that training toward an optimal SJ-FV-profile is beneficial for improving athletic performance. Results showed no significant differences in SJ height, CMJ height, 10 and 30 m sprint time, 1RM strength, or leg-press power between participants who trained toward, away from, or balanced irrespective of their initial FV-profile. These results call into question the use of FV-profiles for guiding individualized training prescriptions in athletes. Instead, the focus should XIV be on improving power across the entire FV continuum rather than solely attempting to correct a theoretical FV imbalance. Study III provides novel evidence that believing to receive optimal training instead of a generic training program may induce a placebo effect in sports and exercise training interventions. These findings imply that the placebo effect could play a significant role in the outcome variances of training interventions that lack a placebo-controlled design. The findings of this dissertation emphasize the importance of carefully selecting measurement equipment, exercises, and procedures when using force-velocity profiling for performance assessment. Additionally, the thesis highlights that individualized training based on force- velocity profiling may not always result in significant improvements in performance outcomes. Therefore, coaches and athletes should be cautious when using FV profiling as the sole determinant for individualized training programs. Finally, the presence of a placebo effect in training interventions indicates the need for placebo-controlled designs in future res
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