Reliability of Force Production Based on the Sense of Effort at Different Force Levels

Reliability of Force Production Based on the Sense of Effort at Different Force Levels | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Reliability of Force Production Based on the Sense of Effort at Different Force Levels Ryosuke Sugaya, Yoichi Hayashi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8784009/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Accurate force production based on the sense of effort plays a critical role in daily motor control and clinical assessment; however, the reliability of such force production across different force levels remains insufficiently understood. Establishing reliable measurement conditions is essential for interpreting changes in force production based on the sense of effort in both research and applied settings. In this study, we examined the test-retest reliability of grip-force production based on the sense of effort at three force levels: 25%, 50%, and 75% of the maximum voluntary contraction (MVC). A total of 33 young men performed grip-force tests across two sessions, separated by one week, without external feedback. Relative reliability was evaluated using intraclass correlation coefficients (ICCs), and absolute reliability was assessed using standard error of measurement (SEM) and the 95% minimal detectable change. The highest reliability was observed at 25% MVC, with a tendency toward reduced reliability at 50% MVC. These findings suggest that low-force-level production based on the sense of effort is relatively stable, possibly reflecting its frequent use in daily activities and simpler neural control mechanisms. Therefore, it is suggested that lower force levels enable more reliable measurements when evaluating force production based on the sense of effort sense of effort grip force force control test-retest reliability intraclass correlation coefficients standard error of measurement Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The ability to appropriately adjust force production according to situational demands is critically important for both motor efficiency and physical safety. In both daily life and sports, movements seldom require maximum force production; instead, they often demand precise control of submaximal force production. Most daily activities are performed with low-intensity muscle activation, and previous studies have shown that such tasks typically involve only a small fraction of maximum voluntary contraction (MVC) (Kern et al., 2001 ; Tikkanen et al., 2013 ). Similarly, movement intensity rarely reaches maximum levels during training and competition in sports such as soccer and basketball (Caro et al., 2024 ; Irid et al., 2025 ). Moreover, high-intensity movements have been causally linked to musculoskeletal disorders in each joint (van Rijn et al., 2010 ; van der Molen et al., 2017 ), and repeated excessive force production has been identified as a contributing factor to their development (Asadi et al., 2020 ). Accurate estimation of the sense of effort is essential for regulating force production in accordance with task demands. The sense of effort is a subjective feeling associated with voluntary actions and is essential for judging one’s own movements (Preston & Wegner, 2009 ). Previous studies demonstrated that voluntary human movement is regulated by this internal sense (McCloskey et al., 1987 ; Thompson et al., 1990 ). Therefore, the correspondence between the sense of effort and force production has been used as an index of motor control (Jackson et al., 2006 ; Kai et al., 2006 ). Force production and movement accuracy based on the sense of effort have been investigated in various fields, including aging (John et al., 2009 ) and neurological disorders (Lafargue & Franck, 2003). For example, older adults have been shown to exhibit greater errors in estimating the sense of effort compared to younger individuals, which may lead to reduced accuracy and safety in motor performance (John et al., 2009 ). Furthermore, Lafargue & Frank (2003) demonstrated that individuals lacking peripheral sensory feedback were able to produce force with a level of accuracy comparable to that of healthy individuals using their sense of effort. The sense of effort serves as a critical internal cue for force regulation, defined by its central origin in motor commands and its role prior to movement execution. Unlike peripheral afferent sensory feedback, the sense of effort is generated centrally (Smirmaul, 2010). A related internal sensation is the sense of force, which refers to the retrospective perception of the actual amplitude of the force generated and therefore arises only after force production (Jones, 1986 ). In contrast, the sense of effort is believed to originate from central motor commands within the cerebral cortex (Lafargue et al., 2006; Proske & Gandevia, 2012 ), particularly from copies of these commands sent to the sensory regions (Enoka & Stuart, 1992 ). The premotor cortex and supplementary motor area are involved in generating these copies and are associated with decision making and motor preparation (Christensen et al., 2007 ; Haggard & Whitford, 2004 ). These neural mechanisms suggest that the sense of effort is generated prior to actual force production. Supporting this, previous studies have reported that individuals with neurological disorders can regulate force production based on their sense of effort, even when their sense of force is impaired (Teasdale et al., 1993 ). Despite its importance in voluntary movements, no established method for measuring the sense of effort has been developed. Motor control based on the sense of effort has been shown to vary depending on an individual’s current experiences (Rizzato et al., 2024 ). Given this background, the sense of effort is being utilized as a performance indicator in sports (Struzik et al., 2017 ). However, previous studies examining motor control based on the sense of effort have varied considerably in both the type of movement and the method used to indicate force levels. Some studies have employed static tasks (Jackson et al., 2006 ), whereas others have used dynamic movements (Lees et al., 2004 ; Kai et al., 2006 ). Additionally, force levels have been presented using different approaches, such as % MVC (Kumar et al., 1997 ; Pincivero et al., 2001 ) or the Borg scale (John et al., 2009 ; Rewitz et al., 2023), indicating a lack of standardization in measurement procedures. Moreover, because sense-of-effort-based motor control is influenced by factors such as muscle condition and fatigue (Proske et al., 2004 ; Miyamoto et al., 2020 ), measurements may exhibit reproducibility errors, even under identical testing conditions (Seki & Ohtsuki, 1995 ). To determine whether such differences reflect measurement error or true change, reliable assessment methods are required to enhance the consistency of evaluations. The grip force task is frequently used as an experimental paradigm because of its comprehensive utility and broad applicability. Handgrip movements are commonly performed in daily life (Bullock et al., 2013 ; Saudabayev et al., 2018 ). For example, Saudabayev et al. ( 2018 ) recorded daily activities and reported that 3,826 hand grip movements were performed over a 9 h period. Moreover, maximum grip force is also a simple and practical measurement with strong predictive validity. Lower grip force has been associated with increased risk of falls (Sayer et al., 2006 ), exacerbation of disease symptoms (Ikeda et al., 2025 ), higher incidence of disease onset (Tuğral et al., 2025 ; Madjedi et al., 2025 ), and elevated mortality rates (Cooper et al., 2010 ). Given this background, numerous reliable methods for measuring the maximum grip force have been developed, and many studies have reported high reproducibility, indicating that repeated measurements yield consistent values (Bai et al., 2019 ; Gränicher et al., 2024 ; Trajković et al., 2024 ). Because force production based on the sense of effort uses a relative percentage of MVC as the force level, the reliability of the MVC measurement is critical. Therefore, the grip force task is well-suited as a standardized test for studies examining force production based on the sense of effort and has been widely adopted across various studies (Stevens & Cain, 1970 ; Kumar & Simmonds, 1994 ; Adamo et al., 2012 ). Given these considerations, the aim of this study was to examine the test-retest reliability of measuring force production based on the sense of effort in relation to grip force. It is well established that errors tend to increase as the force level increases (Fitts, 1954 ). This phenomenon has been attributed to theories involving random fluctuations in motor unit properties (van Beers et al., 2004 ; Todorov, 2004 ) and the roles of neural control strategies and sensory feedback (Nagamori et al., 2021 ). Moreover, studies focusing on the sense of force have shown that the reliability of grip-force measurements decreases as the force level increases (Li et al., 2020 ; Li et al., 2022 ). Accordingly, this study was conducted on the basis of the hypothesis that the reliability is the highest at low force levels and the lowest at high force levels. Materials and methods Participants A total of 33 healthy young men participated in the study (age: 22.8 ± 2.2 years; weight: 66.2 ± 7.7 kg; height: 172.0 ± 4.6 cm). An a priori power analysis was performed using G*Power software (version 3.1.9.7). Because the study employed a fully within-subject design involving three force levels and two points (i.e., six repeated conditions per participant), the design was approximated as a one-way repeated-measures analysis of variance (ANOVA) with six levels. Assuming a medium effect size (f = 0.25), alpha level of 0.05, and a desired power of 0.95, the estimated required sample size was 28 participants. Furthermore, it has been reported that an insufficient number of participants can affect the outcomes of reliability assessments, and a minimum sample size of 30 participants is recommended for such studies (Koo & Li, 2016 ). Therefore, more than 30 participants were recruited for this study. All participants provided informed consent before participating in the experiment. To avoid potential bias from prior experience, the participants were naive to the experimental task. The study protocol was approved by the Research Ethics Committee of the Graduate School of Sports and Health Studies, Hosei University (approval number: 2024–18). Experimental equipment Maximum grip force and grip force based on the sense of effort were measured using a stationary multipurpose analog amplifier (K800; Biometrics Ltd., UK) and a Jamar-type grip dynamometer (Grip Force Meter G200; Biometrics Ltd., UK). The analog signals from the grip dynamometer were digitized via an A/D converter (PH-670B; Q'sfix, Japan) at a sampling frequency of 1000 Hz and recorded on a computer using TRIAS II software (Q'sfix, Japan). The obtained data were smoothed using a custom Python script (version 3.11.7, Windows). A second-order Butterworth low-pass filter with a cut-off frequency of 10 Hz was applied. Experimental design This study comprised two sessions—a test session and a retest session (Fig. 1 )—conducted by the same experienced examiner. According to previous reports, high reliability in grip force measurements can be achieved by conducting both test and retest sessions using consistent procedures and limb positioning, regardless of the specific posture used for measurement (Watanabe et al., 2005 ). Therefore, identical measurements were performed using the same methods and procedures in both sessions. The interval between the test and retest sessions is critical; intervals that are too short increase the likelihood of memory retention or learning effects, whereas excessively long intervals may include true changes in the measured variable (Calamia et al., 2013 ). Previous methodological studies generally recommend a one-to-two-week interval for research involving physical performance or activity measurements (Polit, 2014 ). In practice, a one-week interval is commonly used in studies assessing the reliability of maximum grip force, jump performance, and knee joint proprioception (Venegas-Carro et al., 2022 ; Heishman et al., 2020 ; Ageberg et al., 2007 ). Based on these considerations, the interval between sessions for the present study was set to one week. Each session included assessments of maximum grip force and grip force based on the sense of effort. Before the test session, the participants' height and weight were recorded, and handedness was assessed. Handedness was evaluated using the Japanese version of the FLANDERS Handedness Questionnaire (Okubo et al., 2014 ), and all grip force measurements were conducted using only the dominant hand. Procedures Maximum grip force Maximum grip force was measured while the participants were seated. The grip dynamometer was placed directly on a table in front of each participant. The elbow was maintained at 90° flexion, and the wrist was positioned at 90° pronation. To prevent the arm from touching the torso or clothing during the measurement, the height and position of the table were individually adjusted. A 5-cm-thick mat was placed under the table, and adjustments were made for each participant to standardize the upper limb posture across the sample. The grip width of the dynamometer was individually adjusted such that the second joint of the index finger formed an approximately right angle while gripping the device. To control the visual input, a fixation point was placed 1 m in front of the participants, and they were instructed to maintain their gaze on it throughout each trial. In this state, each participant performed two trials of MVC. Before each trial, the participants were instructed to generate force as quickly and as strongly as possible to align the peak of the force curve with the force level. A 60-second rest period was provided between trials to minimize the effects of fatigue (Watanabe et al., 2005 ). During these rest periods, the participants were instructed not to release their hand from the dynamometer, as previous studies have suggested that interventions such as static stretching may influence the sense of effort (Macefield et al., 1991 ; Trajano et al., 2014 ). To avoid performance bias, no visual or verbal feedback regarding grip force was provided to the participants during the experiment. According to previous studies, multiple measurements of the maximum grip force are required to ensure adequate reliability (Roberts et al., 2011 ). Therefore, the average of two valid trials was used as the representative value for the maximum grip force. To ensure that grip force production was driven by the sense of effort rather than afferent feedback, the participants performed ballistic gripping contractions. A ballistic contraction was defined as a muscle contraction meeting two criteria: (1) a short contraction duration and (2) a high rate of force development (Desmedt & Godaux, 1978 ). This type of contraction is characterized by the generation of central motor commands (Desmedt & Godaux, 1978 ; Hanneton et al., 1997 ). After each trial, the examiner visually inspected the force-time curve to verify whether the criteria were met. Trials that did not meet the criteria were deemed invalid, and additional trials were conducted until two valid trials were obtained for each participant. Prior to measuring the maximum grip force, the participants performed familiarization trials at self-selected force levels and repetitions. Grip force based on the sense of effort Each participant was presented with three force levels of 25%, 50%, and 75% of MVC in random order. As in the maximum grip-force assessment, participants were instructed to produce a grip force as quickly as possible and to match the peak of the force curve to the force level based on their sense of effort. Furthermore, they were instructed not to reproduce the grip force in the previous trial but rather to produce the level of force that they currently perceived to correspond to the specified % MVC. Because three or more trials are recommended when assessing reliability (Koo & Li, 2016 ), three measurements were conducted for each force level in the present study. For each trial, the measured grip force (kg) was converted to a relative value by dividing it by the participant's MVC. The absolute error (AE) was then calculated as the absolute difference between the relative force value and the prescribed force levels (25%, 50%, and 75% of the MVC). AE, expressed as a percentage (Eq. 1 ), served as an index of accuracy for grip force production based on the sense of effort. Except for the force levels and number of trials, all other measurement conditions were identical to those used for the maximum grip force measurement. $$\:AE（％）＝\left|\frac{Measured\:grip\:force}{MVC}\times\:100-force\:level\right|$$ 1 &#x3000;&#x3000;&#x3000;&#x3000;&#x3000;&#x3000;&#x3000;&#x3000; Statistical analysis A two-way repeated-measures ANOVA was conducted with AE as the dependent variable and force level (25%, 50%, and 75% MVC) and session (test and retest) as the within-subject factors. This analysis was conducted to examine whether there were differences in the tendency of AE across force levels and to determine whether any systematic bias (e.g., learning effects or fatigue) existed between sessions. Statistical significance was set at p = 0.05. The results are reported to three decimal places for readability. All analyses were performed using IBM SPSS Statistics (version 29.0; IBM Corp., Armonk, NY). Reliability analysis Bland-Altman plots were initially used to visually assess the agreement between test and retest measurements and to detect potential heteroscedasticity or systematic bias (Atkinson & Nevill, 1998 ). Heteroscedasticity was considered present when the data exhibited a funnel-shaped distribution. In such cases, the coefficient of variation (CV) was adopted as the index of absolute reliability. Conversely, when heteroscedasticity was absent, the standard error of measurement (SEM) was used (Atkinson & Nevill, 1998 ). Reliability was quantified using intraclass correlation coefficients (ICCs), CV or SEM, and the 95% minimal detectable change (95% MDC). ICCs, representing relative reliability, were calculated based on the recommendations of Koo and Li ( 2016 ) using a mean rating (k = 3), absolute agreement, and a two-way mixed-effects model. ICC values were interpreted according to Cicchetti’s classification: poor (ICC < 0.40), fair (0.40 ≤ ICC < 0.60), good (0.60 ≤ ICC < 0.75), and excellent (ICC ≥ 0.75) (Cicchetti, 1994 ). CV, a dimensionless index in which lower values indicate greater precision, was calculated as CV = (SD / Mean) × 100. CV is particularly useful for comparing reliability across different measurement tools (Feltz & Miller, 1996 ) and for evaluating absolute reliability in datasets that exhibit heteroscedasticity (Bland & Altman, 1995 ). SEM, a unit-dependent index, was calculated as SEM = SD × √(1 – ICC). It represents the inherent variability or “noise” within a measurement (Geerinck et al., 2019 ), with lower SEM values indicating greater measurement precision. The 95% MDC, derived from SEM (95% MDC = 1.96 × SEM × √2), represents the smallest statistically meaningful change beyond measurement error (Furlan & Sterr, 2018 ). Results All the participants who provided informed consent completed the experimental procedures without withdrawal. Table 1 and Fig. 2 present the mean and SD of AE for each force level and session. A two-way repeated-measures ANOVA was conducted using AE as the dependent variable and force level (25%, 50%, and 75% MVC) and session (test and retest) as the within-subject factors. Prior to analysis, Mauchly’s test of sphericity was conducted. Because the assumption of sphericity was violated for the force levels, the Greenhouse–Geisser correction was applied. The results indicated no significant main effects of force level ( F (1.419, 45.417) = 3.320, p = 0.061, η p ² = 0.094), session ( F (1, 32) = 0.159, p = 0.692, η p ² = 0.005), and their interaction ( F (2, 64) = 1.546, p = 0.221, η p ² = 0.046). Figures 3 – 5 present the Bland-Altman plots for the three force levels. Prior to evaluating the absolute reliability, heteroscedasticity at each force level was visually inspected using the plots. No evidence of heteroscedasticity was observed; therefore, SEM was adopted as the index of absolute reliability in this study. Table 1 presents AE and the corresponding statistical indices (ICC, SEM, and 95% MDC) for each force level (25%, 50%, and 75% MVC) across the two sessions (test and retest). The highest ICC for AE was observed at 25% MVC, and when considering the 95% confidence interval (95% CI), it was classified as good to excellent according to Cicchetti’s ( 1994 ) criteria. The ICC values for 50% and 75% MVC were comparable and classified as fair to excellent. The SEM and 95% MDC showed the highest reliability at 25% MVC, followed by 75% and 50% MVC. Table 1 Absolute error (AE, %) at each force level and session for grip force based on the sense of effort, together with the corresponding test-retest reliability statistics. Force level Session (test) Session (retest) Mean difference (test − retest) ICC (95% CI) SEM 95% MDC 25% MVC 22.274 ± 14.533 20.526 ± 14.906 1.748 ± 9.356 0.887 (0.631–0.894) 4.948 13.717 50% MVC 19.395 ± 12.307 20.657 ± 12.696 −1.262 ± 11.766 0.720 (0.431–0.862) 6.616 18.338 75% MVC 16.495 ± 10.187 15.233 ± 10.588 1.262 ± 9.808 0.716 (0.426–0.860) 5.537 15.347 Discussion In this study, we evaluated the potential presence of systematic bias in the measurement of force production based on the sense of effort, revealing that no such bias occurred between the test and retest sessions. Based on the shape of the Bland-Altman plots and the results of the main effect of session, no systematic bias—such as learning or fatigue effects—was observed between the test and retest sessions. Systematic changes in force production without structural alterations in muscle are generally attributed to modifications in corticospinal excitability (Lee & Carroll, 2007 ), which typically arise through motor learning processes involving repeated practice (Hortobágyi et al., 2011 ; Leung et al., 2018 ). In the present study, participants did not receive external feedback regarding their results because the task was designed to measure their current level of force production based solely on their sense of effort. Therefore, it is reasonable to assume that no systematic bias in AE occurred between the test and retest sessions. Test-retest reliability Evaluation of the sense of effort at low force levels was found to be highly reliable, with methodological and practical implications. According to Cicchetti’s ( 1994 ) classification and 95% CI, the ICC at 25% MVC was rated as good to excellent. Regarding SEM, the difference between the test and retest sessions was approximately 5%, which was lower than that observed at the other two force levels. Similarly, the 95% MDC indicated that only changes exceeding approximately 13.7% could be interpreted as true changes in force production based on the sense of effort, rather than random error. The observation that the highest reliability occurred at a low force level aligns with previous findings that examined the reliability of the sense of force, such as in grip and pinch force tasks (Li et al., 2020 ; Li et al., 2022 ). This pattern likely reflects behavioral and physiological factors. Many daily activities commonly require only a small fraction of MVC (Kern et al., 2001 ; Tikkanen et al., 2013 ). Therefore, the present findings may reflect both the frequent use of low-force production in everyday life and the relative simplicity of neural control at lower force levels compared with the increased control difficulty and noise at higher force levels (Desmedt & Godaux, 1978 ; Bernardi et al., 1995 ; Harris & Wolpert, 1998 ). These results suggest that the sense of effort during low force control is relatively stable, and such stability is likely essential for maintaining both motor efficiency and physical safety during daily activities. In contrast, the reliability outcomes at 50% and 75% MVC were inconsistent across indices, suggesting increased variability in force levels at or above moderate intensity. These results differed from our initial hypothesis. While ICC values at 50% and 75% were comparable, SEM and 95% MDC indicated the lowest reliability at 50% MVC. According to Cicchetti’s ( 1994 ) classification and the 95% CI, both force levels demonstrated fair to excellent relative reliability. Regarding the SEM at 50% MVC, the difference between the test and retest sessions was approximately 6.5%, which was greater than those observed at the other two force levels. Similarly, the 95% MDC results indicated that only changes exceeding ~ 18.0% could be interpreted as representing a true change in force production based on the sense of effort, rather than random error. Because ICC and SEM reflect different aspects of reliability, it is reasonable that their findings do not always align (Stratford & Goldsmith, 1997 ). However, classical motor control theories suggest that difficulty in neural control increases linearly with force production (Desmedt & Godaux, 1978 ; Bernardi et al., 1995 ), leading to reduced reliability at higher force levels. Furthermore, the general tendency of reliability to decline with increasing force levels is also supported by the signal-dependent noise model (Harris & Wolpert, 1998 ), which posits that neural noise contributes to motor variability scales with the magnitude of the motor command. The lack of a clear force-level-dependent trend in ICC values likely reflects the interplay between within-subject variance (captured by SEM) and between-subject variance. ICC represents the ratio of between-subject variance to total variance (i.e., the sum of between-subject and within-subject variances). Consequently, a greater within-subject variance—reflecting greater variability between test and retest—results in a lower ICC. In this study, SEM indicated that the within-subject variance was the highest at 50% MVC among the three force levels, which should theoretically produce the lowest ICC. However, the ICC values at 50% and 75% MVC were comparable, suggesting that in addition to the increase in within-subject variance, between-subject variance may have been elevated at 50% MVC, thereby offsetting the expected decrease in ICC. The complexity of force production based on the sense of effort is likely heightened at 50% MVC, potentially leading to reduced reliability at this force level. Previous studies highlighted the increased complexity of force production at moderate force levels; at ~ 35–50% MVC, the combined recruitment and firing frequency of motor units reach their most complex state (Slifkin & Newell, 2000 ; Oliveira et al., 2025 ). In the present study, it is plausible that this physiological complexity contributed to an increase in both between-subject and within-subject variances at 50% MVC. This heightened complexity contributes to functional flexibility but critically serves as a primary factor that reduces measurement reliability at moderate force levels. This phenomenon is further supported by mechanisms related to absolute criteria. Previous studies have shown that in tasks requiring the reproduction of the same force level as in a previous trial, the AE varies across different types of movement; however, when normalized to MVC, the magnitude of the error remains consistent regardless of the movement type (Seki & Ohtsuki, 1995 ). Similarly, although different movement tasks (e.g., grasping and pinching) produce distinct AEs, these errors become comparable when normalized to MVC (Mai et al., 1991 ). Based on this theory, the force levels at 25% and 75% MVC in the present study were likely regulated with reference to 0% and 100% of a common scale, respectively. Therefore, it is plausible that referencing these absolute criteria (0% and 100%) contributed to maintaining reliability at these two force levels, whereas 50% MVC lacked such absolute anchors, making force regulation less stable at this intermediate level. Limitations The primary limitations of this study relate to the participant sample, the specificity of the experimental task, and the limited methodological standardization available in this field. These limitations highlight important directions for future research. Because the study included only young adult males, the generalizability of the findings may be limited, as previous research suggests that force production based on the sense of effort exhibits systematic variations depending on sex and age (Jackson et al., 2002 ; John et al., 2009 ). Furthermore, variations in the complexity of force production have been reported between younger and older adults (Fiogbé et al., 2021 ). Therefore, future studies should include populations with diverse demographic characteristics to verify the generalizability of these findings. Additionally, although the experimental conditions were tightly controlled, the applicability of the results to more complex and dynamic movements remains unclear. Performance in such tasks depends not only on the magnitude of individual force production but also on the spatial and temporal coordination of multiple forces, as demonstrated in studies examining vertical jump performance based on the sense of effort (Sadamoto & Ohtsuki, 1977 ). Moreover, it remains unclear whether the present study alone was sufficient to standardize the measurement method for force production based on the sense of effort. Sensory memory related to tactile perception decays rapidly within a few seconds (Bliss et al., 1966 ), and as the interval between the test and retest increases, measurement reliability tends to decrease (Calamia et al., 2013 ). Thus, additional research is needed to determine the optimal interval between test and retest sessions. Furthermore, previous studies on force production based on the sense of effort have adopted a wide range of force levels, with no standardized levels established to date (Kumar et al., 1997 ). Although the present study examined low-to-high force levels, it remains uncertain how the results might differ at untested levels such as 10% or 90% MVC. Conclusion This study investigated the test-retest reliability of measuring force production on the basis of the sense of effort in relation to grip force. The results revealed that relative reliability, as indicated by ICCs, was the highest at 25% MVC, whereas 50% and 75% MVC showed comparable levels of reliability. Overall, the relative reliability was classified as fair to excellent. In contrast, absolute reliability, as assessed through SEM, exhibited a different pattern; SEM was the lowest at 50% MVC and the highest at 25% MVC. Overall, these findings suggest that the present study successfully establishes a measurement procedure for assessing force production based on the sense of effort, and that the highest reliability can be achieved at 25% MVC. These findings underscore the value of low-force assessments for reliably evaluating the sense of effort and provide a foundation for developing standardized measurement protocols, while also highlighting the need for future studies to examine broader populations, additional force levels, and more complex movement contexts. Declarations Compliance with Ethical Standards All procedures performed in studies involving human participants were in accordance with the ethical standards of the institution and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The study was approved by the Research Ethics Committee of the Graduate School of Sports and Health Studies, Hosei University (No. 2024–18). Acknowledgements We wish to thank the participants who graciously agreed to participate in this study. We also thank the professors and colleagues for their valuable and lively discussions. Funding details No funding was received for conducting this study. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ryosuke Sugaya, and Yoichi Hayashi. The first draft of the manuscript was written by Ryosuke Sugaya and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Disclosure statement The authors have no competing interests to declare that are relevant to the content of this article. Data availability The raw data for statistical analysis are available at the following URL: https://osf.io/kmhfy/overview References Adamo DE, Scotland S, Martin BJ (2012) Asymmetry in grasp force matching and sense of effort. Exp Brain Res 217:273–285. https://doi.org/10.1007/s00221-011-2991-6 Ageberg E, Flenhagen J, Ljung J (2007) Test-retest reliability of knee kinesthesia in healthy adults. BMC Musculoskelet Disord 8:57. https://doi.org/10.1186/1471-2474-8-57 Asadi H, Zhou G, Lee JJ, Aggarwal V, Yu D (2020) A computer vision approach for classifying isometric grip force exertion levels. Ergonomics 63:1010–1026. https://doi.org/10.1080/00140139.2020.1745898 Atkinson G, Nevill AM (1998) Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med 26:217–238. https://doi.org/10.2165/00007256-199826040-00002 Bai Z, Shu T, Niu W (2019) Test-retest reliability and measurement errors of grip strength test in patients with traumatic injuries in the upper extremity: a cross-sectional study. BMC Musculoskelet Disord 20:256. https://doi.org/10.1186/s12891-019-2623-z Bernardi M, Solomonow M, Sanchez JH, Baratta RV, Nguyen G (1995) Motor unit recruitment strategy of knee antagonist muscles in a step-wise, increasing isometric contraction. Eur J Appl Physiol Occup Physiol 70:493–501. https://doi.org/10.1007/BF00634378 Bland JM, Altman DG (1995) Comparing two methods of clinical measurement: a personal history. Int J Epidemiol 24(Suppl 1):S7–S14. https://doi.org/10.1093/ije/24.supplement_1.s7 Bliss JC, Crane HD, Mansfield PK, Townsend JT (1966) Information available in brief tactile presentations. Percept Psychophys 1:273–283. https://doi.org/10.3758/BF03207391 Bullock IM, Zheng JZ, De La Rosa S, Guertler C, Dollar AM (2013) Grasp frequency and usage in daily household and machine shop tasks. IEEE Trans Haptics 6:296–308. https://doi.org/10.1109/TOH.2013.6 Caro E, Lapuente-Sagarra M, Caparrós T, Pajón D, Campos-Vázquez MA (2024) Analysis of the submaximal intensity periods during the competitive microcycle in professional football players. Apunts Educ Fís Deporte 158:52–62. https://doi.org/10.5672/apunts.2014-0983.es.(2024/4).158.06 Calamia M, Markon K, Tranel D (2013) The robust reliability of neuropsychological measures: meta-analyses of test-retest correlations. Clin Neuropsychol 27:1077–1105. https://doi.org/10.1080/13854046.2013.809795 Christensen MS, Lundbye-Jensen J, Geertsen SS, Petersen TH, Paulson OB, Nielsen JB (2007) Premotor cortex modulates somatosensory cortex during voluntary movements without proprioceptive feedback. Nat Neurosci 10:417–419. https://doi.org/10.1038/nn1873 Cicchetti DV (1994) Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assess 6:284–290. https://doi.org/10.1037/1040-3590.6.4.284 Cooper R, Kuh D, Hardy R, Mortality Review Group, FALCon and HALCyon Study Teams (2010) Objectively measured physical capability levels and mortality: systematic review and meta-analysis. BMJ 341:c4467. https://doi.org/10.1136/bmj.c4467 Desmedt JE, Godaux E (1978) Ballistic contractions in fast or slow human muscles: discharge patterns of single motor units. J Physiol 285:185–196. https://doi.org/10.1113/jphysiol.1978.sp012566 Enoka RM, Stuart DG (1992) Neurobiology of muscle fatigue. J Appl Physiol 72:1631–1648. https://doi.org/10.1152/jappl.1992.72.5.1631 Feltz CJ, Miller GE (1996) An asymptotic test for the equality of coefficients of variation from k populations. Stat Med 15:647–658. https://doi.org/10.1002/(sici)1097-0258(19960330)15:6%3C647::aid-sim184%3E3.0.co;2-p Fiogbé E, Vassimon-Barroso V, Catai AM, de Melo RC, Quitério RJ, Porta A, Takahashi ACM (2021) Complexity of knee extensor torque: effect of aging and contraction intensity. J Strength Cond Res 35:1050–1057. https://doi.org/10.1519/JSC.0000000000002888 Fitts PM (1954) The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol 47:381–391. https://doi.org/10.1037/h0055392 Furlan L, Sterr A (2018) The applicability of standard error of measurement and minimal detectable change to motor learning research: a behavioral study. Front Hum Neurosci 12:95. https://doi.org/10.3389/fnhum.2018.00095 Geerinck A, Alekna V, Beaudart C, Bautmans I, Cooper C, De Souza Orlandi F, Konstantynowicz J, Montero-Errasquín B, Topinková E, Tsekoura M, Reginster JY, Bruyère O (2019) Standard error of measurement and smallest detectable change of the Sarcopenia Quality of Life (SarQoL) questionnaire: an analysis of subjects from 9 validation studies. PLoS ONE 14:e0216065. https://doi.org/10.1371/journal.pone.0216065 Gränicher P, Maurer Y, Spörri J, Haller B, Swanenburg J, de Bie RA, Lenssen TAF, Scherr J (2024) Accuracy and reliability of grip strength measurements: a comparative device analysis. J Funct Morphol Kinesiol 9:274. https://doi.org/10.3390/jfmk9040274 Haggard P, Whitford B (2004) Supplementary motor area provides an efferent signal for sensory suppression. Cogn Brain Res 19:52–58. https://doi.org/10.1016/j.cogbrainres.2003.10.018 Hanneton S, Berthoz A, Droulez J, Slotine JJE (1997) Does the brain use sliding variables for the control of movements? Biol Cybern 77:381–393. https://doi.org/10.1007/s004220050398 Harris CM, Wolpert DM (1998) Signal-dependent noise determines motor planning. Nature 394:780–784. https://doi.org/10.1038/29528 Heishman AD, Daub BD, Miller RM, Freitas EDS, Frantz BA, Bemben MG (2020) Countermovement jump reliability performed with and without an arm swing in NCAA Division 1 intercollegiate basketball players. J Strength Cond Res 34:546–558. https://doi.org/10.1519/JSC.0000000000002812 Hortobágyi T, Richardson SP, Lomarev M, Shamim E, Meunier S, Russman H, Dang N, Hallett M (2011) Interhemispheric plasticity in humans. Med Sci Sports Exerc 43:1188–1199. https://doi.org/10.1249/MSS.0b013e31820a94b8 Ikeda K, Ikumi A, Onishi S, Ogawa T, Kohyama S, Yoshii Y (2025) Predicting refractoriness in lateral epicondylitis using initial grip strength and QuickDASH: a retrospective cohort study. BMC Musculoskelet Disord 26:645. https://doi.org/10.1186/s12891-025-08902-7 Irid Y, Hutin J, Toussaint J, Sedeaud A (2025) Exploring the most demanding scenarios in elite youth basketball: a comprehensive analysis across playing positions and time windows. Biol Sport 42:37–47. https://doi.org/10.5114/biolsport.2025.148537 Jackson AW, Dishman RK, Martin SB (2002) Perceived leg extension and flexion forces of young adult men and women: comparison to previous findings. Res Q Exerc Sport 73:225–228. https://doi.org/10.1080/02701367.2002.10609013 Jackson AW, Ludtke AW, Martin SB, Koziris LP, Dishman RK (2006) Perceived submaximal force production in young adults. Res Q Exerc Sport 77:50–57. https://doi.org/10.1080/02701367.2006.10599331 John EB, Liu W, Gregory RW (2009) Biomechanics of muscular effort: age-related changes. Med Sci Sports Exerc 41:418–425. https://doi.org/10.1249/MSS.0b013e3181884480 Jones LA (1986) Perception of force and weight: theory and research. Psychol Bull 100:29–42. https://pubmed.ncbi.nlm.nih.gov/2942958/ Kai S, Nakahara M, Watari K, Murakami S, Yoshimoto R (2006) Knee joint angle at the time of adjustment to submaximal jumping in healthy men. J Phys Ther Sci 18:11–13. https://doi.org/10.1589/jpts.18.11 Kern DS, Semmler JG, Enoka RM (2001) Long-term activity in upper- and lower-limb muscles of humans. J Appl Physiol 91:2224–2232. https://doi.org/10.1152/jappl.2001.91.5.2224 Koo TK, Li MY (2016) A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 15:155–163. https://doi.org/10.1016/j.jcm.2016.02.012 Kumar S, Simmonds M (1994) The accuracy of magnitude production of submaximal precision and power grips and gross motor efforts. Ergonomics 37:1345–1353. https://doi.org/10.1080/00140139408964913 Kumar S, Narayan Y, Chouinard K (1997) Effort reproduction accuracy in pinching, gripping, and lifting among industrial males. Int J Ind Ergon 20:109–119. https://doi.org/10.1016/S0169-8141(96)00045-5 Lafargue G, Franck N (2009) Effort awareness and sense of volition in schizophrenia. Conscious Cogn 18:277–289. https://doi.org/10.1016/j.concog.2008.05.004 Lafargue G, Paillard J, Lamarre Y, Sirigu A (2003) Production and perception of grip force without proprioception: is there a sense of effort in deafferented subjects? Eur J Neurosci 17:2741–2749. https://doi.org/10.1046/j.1460-9568.2003.02700.x Lee M, Carroll TJ (2007) Cross education: possible mechanisms for the contralateral effects of unilateral resistance training. Sports Med 37:1–14. https://doi.org/10.2165/00007256-200737010-00001 Lees A, Vanrenterghem J, De Clercq D (2004) The maximal and submaximal vertical jump: implications for strength and conditioning. J Strength Cond Res 18:787–791. https://pubmed.ncbi.nlm.nih.gov/15574084/ Leung M, Rantalainen T, Teo WP, Kidgell D (2018) The ipsilateral corticospinal responses to cross-education are dependent upon the motor-training intervention. Exp Brain Res 236:1331–1346. https://doi.org/10.1007/s00221-018-5224-4 Li L, Li Y, Wu C, Zhang X (2020) Test-retest reliability of tip, key, and palmar pinch force sense in healthy adults. BMC Musculoskelet Disord 21:189. https://doi.org/10.1186/s12891-020-3187-7 Li YX, Li L, Chen X, Zhao Y, Zhao X, Zhang CL (2022) Assessment of grip force sense test-retest reliability in healthy male participants. Ergonomics 65:1621–1630. https://doi.org/10.1080/00140139.2022.2044521 Macefield G, Hagbarth KE, Gorman R, Gandevia SC, Burke D (1991) Decline in spindle support to alpha-motoneurones during sustained voluntary contractions. J Physiol 440:497–512. https://doi.org/10.1113/jphysiol.1991.sp018721 Madjedi KM, Stuart KV, Yin GS, Luben RN, Sun Z, Biradar M, Hu R, Foster PJ, Khaw PT, Bell KC, Crowston JG, Khawaja AP, UK Biobank Eye and Vision Consortium (2025) The association of muscle-related factors with glaucoma and related traits in a large United Kingdom population. Invest Ophthalmol Vis Sci 66:66. https://doi.org/10.1167/iovs.66.6.66 Mai N, Schreiber P, Hermsdörfer J (1991) Changes in perceived finger force produced by muscular contractions under isometric and anisometric conditions. Exp Brain Res 84:453–460. https://doi.org/10.1007/BF00231469 McCloskey DI, Macefield G, Gandevia SC, Burke D (1987) Sensing position and movements of the fingers. News Physiol Sci 2(6):226–230. https://doi.org/10.1152/physiologyonline.1987.2.6.226 Miyamoto T, Kizuka T, Ono S (2020) Influence of preceding muscle activity on perceptually guided force production during superimposed ballistic contraction. Physiol Behav 222:112933. https://doi.org/10.1016/j.physbeh.2020.112933 Nagamori A, Laine CM, Loeb GE, Valero-Cuevas FJ (2021) Force variability is mostly not motor noise: Theoretical implications for motor control. PLoS Comput Biol 17(3):e1008707. https://doi.org/10.1371/journal.pcbi.1008707 Oliveira JH, Gomes JS, Bauer P, Pezarat-Correia P, Vaz JR (2025) Force fluctuations regulation and the role of neurophysiological mechanisms throughout different isometric contraction intensities. Sci Rep 15(1):28442. https://doi.org/10.1038/s41598-025-14543-6 Okubo M, Suzuki H, Nicholls MER (2014) A Japanese version of the FLANDERS handedness questionnaire: Reliability and validity. Jpn J Psychol 85(5):474–481. https://doi.org/10.4992/jjpsy.85.13235 Pincivero DM, Coelho AJ, Campy RM, Salfetnikov Y, Bright A (2001) The effects of voluntary contraction intensity and gender on perceived exertion during isokinetic quadriceps exercise. Eur J Appl Physiol 84(3):221–226. https://doi.org/10.1007/s004210170008 Polit DF (2014) Getting serious about test–retest reliability: A critique of retest research and some recommendations. Qual life research: Int J Qual life aspects Treat care rehabilitation 23(6):1713–1720. https://doi.org/10.1007/s11136-014-0632-9 Preston J, Wegner DM (2009) Elbow grease: When action feels like work. In: Morsella E, Bargh JA, Gollwitzer PM (eds) Oxford handbook of human action: Social cognition and social neuroscience. Oxford University Press, New York, pp 569–586 Proske U, Gregory JE, Morgan DL, Percival P, Weerakkody NS, Canny BJ (2004) Force matching errors following eccentric exercise. Hum Mov Sci 23(3–4):365–378. https://doi.org/10.1016/j.humov.2004.08.012 Proske U, Gandevia SC (2012) The proprioceptive senses: Their roles in signaling body shape, body position and movement, and muscle force. Physiol Rev 92(4):1651–1697. https://doi.org/10.1152/physrev.00048.2011 Rewitz K, Schindler S, Wolff W (2024) Examining the alignment between subjective effort and objective force production. PLoS ONE 19(8):e0307994. https://doi.org/10.1371/journal.pone.0307994 Rizzato A, Cantarella G, Basso E, Paoli A, Rotundo L, Bisiacchi P, Marcolin G (2024) Relationship between intended force and actual force: Comparison between athletes and non-athletes. PeerJ 12:e17156. https://doi.org/10.7717/peerj.17156 Roberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, Sayer AA (2011) A review of the measurement of grip strength in clinical and epidemiological studies: Towards a standardised approach. Age Ageing 40(4):423–429. https://doi.org/10.1093/ageing/afr051 Sadamoto T, Ohtsuki T (1977) Accuracy of output control in jumping: Characteristics in grading and reproduction of distance jumped. Jpn J Phys Educ Health Sport Sci 22(4):215–229. https://doi.org/10.5432/jjpehss.KJ00003392573 Saudabayev A, Rysbek Z, Khassenova R, Varol HA (2018) Human grasping database for activities of daily living with depth, color and kinematic data streams. Sci Data 5:180101. https://doi.org/10.1038/sdata.2018.101 Sayer AA, Syddall HE, Martin HJ, Dennison EM, Anderson FH, Cooper C (2006) Falls, sarcopenia, and growth in early life: Findings from the Hertfordshire cohort study. Am J Epidemiol 164(7):665–671. https://doi.org/10.1093/aje/kwj255 Seki T, Ohtsuki T (1995) Reproducibility of subjectively graded voluntary isometric muscle strength in unilateral and simultaneous bilateral exertion. Ergonomics 38(9):1867–1876. https://doi.org/10.1080/00140139508925234 Slifkin AB, Newell KM (2000) Variability and noise in continuous force production. J Mot Behav 32(2):141–150. https://doi.org/10.1080/00222890009601366 de Smirmaul B P (2012) Sense of effort and other unpleasant sensations during exercise: Clarifying concepts and mechanisms. Br J Sports Med 46(5):308–311. https://doi.org/10.1136/bjsm.2010.071407 Stevens JC, Cain WS (1970) Effort in isometric muscular contractions related to force level and duration. Percept Psychophys 8:240–244. https://doi.org/10.3758/BF03210214 Stratford PW, Goldsmith CH (1997) Use of the standard error as a reliability index of interest: An applied example using elbow flexor strength data. Phys Ther 77(7):745–750. https://doi.org/10.1093/ptj/77.7.745 Struzik A, Pietraszewski B, Kawczyński A, Winiarski S, Juras G, Rokita A (2017) Manifestations of proprioception during vertical jumps to specific heights. J Strength Cond Res 31(6):1694–1701. https://doi.org/10.1519/JSC.0000000000001868 Teasdale N, Forget R, Bard C, Paillard J, Fleury M, Lamarre Y (1993) The role of proprioceptive information for the production of isometric forces and for handwriting tasks. Acta Psychol (Amst) 82(1–3):179–191. https://doi.org/10.1016/0001-6918(93)90011-F Thompson S, Gregory JE, Proske U (1990) Errors in force estimation can be explained by tendon organ desensitization. Exp Brain Res 79(2):365–372. https://doi.org/10.1007/BF00608246 Tikkanen O, Haakana P, Pesola AJ, Häkkinen K, Rantalainen T, Havu M, Pullinen T, Finni T (2013) Muscle activity and inactivity periods during normal daily life. PLoS ONE 8(1):e52228. https://doi.org/10.1371/journal.pone.0052228 Todorov E (2004) Optimality principles in sensorimotor control. Nat Neurosci 7(9):907–915. https://doi.org/10.1038/nn1309 Trajano GS, Seitz LB, Nosaka K, Blazevich AJ (2014) Can passive stretch inhibit motoneuron facilitation in the human plantar flexors? J Appl Physiol 117(12):1486–1492. https://doi.org/10.1152/japplphysiol.00809.2014 Trajković N, Rančić D, Ilić T, Herodek R, Korobeynikov G, Pekas D (2024) Measuring handgrip strength in school children: Inter-instrument reliability between Takei and Jamar. Sci Rep 14(1):1074. https://doi.org/10.1038/s41598-024-51368-1 Tuğral A, Bakar Y, Akyol M (2025) Predictors of upper extremity function in breast cancer survivors. Physiother Res Int 30(3):e70082. https://doi.org/10.1002/pri.70082 van Beers RJ, Haggard P, Wolpert DM (2004) The role of execution noise in movement variability. J Neurophysiol 91(2):1050–1063. https://doi.org/10.1152/jn.00652.2003 van der Molen HF, Foresti C, Daams JG, Frings-Dresen MHW, Kuijer PPFM (2017) Work-related risk factors for specific shoulder disorders: A systematic review and meta-analysis. Occup Environ Med 74(10):745–755. https://doi.org/10.1136/oemed-2017-104339 van Rijn RM, Huisstede BMA, Koes BW, Burdorf A (2010) Associations between work-related factors and specific disorders of the shoulder: A systematic review of the literature. Scand J Work Environ Health 36(3):189–201. https://doi.org/10.5271/sjweh.2895 Venegas-Carro M, Kramer A, Moreno-Villanueva M, Gruber M (2022) Test–retest reliability and sensitivity of common strength and power tests over a period of 9 weeks. Sports (Basel) 10(11):171. https://doi.org/10.3390/sports10110171 Watanabe T, Owashi K, Kanauchi Y, Mura N, Takahara M, Ogino T (2005) The short-term reliability of grip strength measurement and the effects of posture and grip span. J Hand Surg Am 30(3):603–609. https://doi.org/10.1016/j.jhsa.2004.12.007 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8784009","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":586567521,"identity":"145210a8-eb8d-46f4-8dd2-2dfc0f256a4a","order_by":0,"name":"Ryosuke Sugaya","email":"data:image/png;base64,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","orcid":"","institution":"Hosei University","correspondingAuthor":true,"prefix":"","firstName":"Ryosuke","middleName":"","lastName":"Sugaya","suffix":""},{"id":586567522,"identity":"2fd7b826-c7e0-47b9-96be-a4800d7484f9","order_by":1,"name":"Yoichi Hayashi","email":"","orcid":"","institution":"Hosei University","correspondingAuthor":false,"prefix":"","firstName":"Yoichi","middleName":"","lastName":"Hayashi","suffix":""}],"badges":[],"createdAt":"2026-02-04 08:55:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8784009/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8784009/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102296993,"identity":"6319a87e-2946-4273-80d2-49a8040bd637","added_by":"auto","created_at":"2026-02-10 10:24:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1820730,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of the experimental design. The presentation order of the 25%, 50%, and 75% MVC force levels was randomized.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8784009/v1/09d9086a7f6524889081bc52.png"},{"id":102229422,"identity":"238bf53f-25d3-49fc-a9da-204968109618","added_by":"auto","created_at":"2026-02-09 15:15:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":972860,"visible":true,"origin":"","legend":"\u003cp\u003eMean and standard deviation (SD) of the absolute error (AE) for each force level and session. A two-way repeated-measures ANOVA showed no significant main effects of force level (\u003cem\u003eF \u003c/em\u003e(1.419, 45.417) = 3.320, \u003cem\u003ep\u003c/em\u003e = 0.061, \u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e² = 0.094), session (\u003cem\u003eF\u003c/em\u003e (1, 32) = 0.159, \u003cem\u003ep\u003c/em\u003e = 0.692, \u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e² = 0.005), and their interaction (\u003cem\u003eF \u003c/em\u003e(2, 64) = 1.546, \u003cem\u003ep\u003c/em\u003e = 0.221, \u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e² = 0.046).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8784009/v1/23e6f6bbfe48e8e7b4b1fafd.png"},{"id":102229425,"identity":"bf7bbdc4-b19a-4dcf-a9fe-4e5176105468","added_by":"auto","created_at":"2026-02-09 15:15:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1243029,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman plot showing the agreement between the absolute error (AE) of tests and retests at 25% MVC. The upper and lower limits of agreement (LOA) indicate the range within which measurement errors are considered acceptable.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8784009/v1/b62097a8aa725b95ac868773.png"},{"id":102229426,"identity":"cccfdade-d888-4460-b1ac-555db2b79aaf","added_by":"auto","created_at":"2026-02-09 15:15:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1245027,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman plot showing the agreement between the absolute error (AE) of tests and retests at 50% MVC. The upper and lower limits of agreement (LOA) indicate the acceptable range of measurement error.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8784009/v1/1ec3c17e715411bc2d1c3b3a.png"},{"id":102229424,"identity":"6d092ba8-d432-49f5-b237-e2178764d46f","added_by":"auto","created_at":"2026-02-09 15:15:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1247730,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman plot showing the agreement between the absolute error (AE) of tests and retests at 75% MVC. The upper and lower limits of agreement (LOA) indicate the acceptable range of measurement error.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8784009/v1/1d1526ae3854dc2b50b2e996.png"},{"id":102397128,"identity":"43daf3c0-d470-4dd3-9a76-aad8ec3b61b6","added_by":"auto","created_at":"2026-02-11 10:01:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7181527,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8784009/v1/cbeaf7a1-d6b2-4147-97db-5261eb7e2d4e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Reliability of Force Production Based on the Sense of Effort at Different Force Levels","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe ability to appropriately adjust force production according to situational demands is critically important for both motor efficiency and physical safety. In both daily life and sports, movements seldom require maximum force production; instead, they often demand precise control of submaximal force production. Most daily activities are performed with low-intensity muscle activation, and previous studies have shown that such tasks typically involve only a small fraction of maximum voluntary contraction (MVC) (Kern et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Tikkanen et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Similarly, movement intensity rarely reaches maximum levels during training and competition in sports such as soccer and basketball (Caro et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Irid et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Moreover, high-intensity movements have been causally linked to musculoskeletal disorders in each joint (van Rijn et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; van der Molen et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and repeated excessive force production has been identified as a contributing factor to their development (Asadi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccurate estimation of the sense of effort is essential for regulating force production in accordance with task demands. The sense of effort is a subjective feeling associated with voluntary actions and is essential for judging one\u0026rsquo;s own movements (Preston \u0026amp; Wegner, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Previous studies demonstrated that voluntary human movement is regulated by this internal sense (McCloskey et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Thompson et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). Therefore, the correspondence between the sense of effort and force production has been used as an index of motor control (Jackson et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Kai et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Force production and movement accuracy based on the sense of effort have been investigated in various fields, including aging (John et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and neurological disorders (Lafargue \u0026amp; Franck, 2003). For example, older adults have been shown to exhibit greater errors in estimating the sense of effort compared to younger individuals, which may lead to reduced accuracy and safety in motor performance (John et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Furthermore, Lafargue \u0026amp; Frank (2003) demonstrated that individuals lacking peripheral sensory feedback were able to produce force with a level of accuracy comparable to that of healthy individuals using their sense of effort.\u003c/p\u003e \u003cp\u003eThe sense of effort serves as a critical internal cue for force regulation, defined by its central origin in motor commands and its role prior to movement execution. Unlike peripheral afferent sensory feedback, the sense of effort is generated centrally (Smirmaul, 2010). A related internal sensation is the sense of force, which refers to the retrospective perception of the actual amplitude of the force generated and therefore arises only after force production (Jones, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). In contrast, the sense of effort is believed to originate from central motor commands within the cerebral cortex (Lafargue et al., 2006; Proske \u0026amp; Gandevia, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), particularly from copies of these commands sent to the sensory regions (Enoka \u0026amp; Stuart, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). The premotor cortex and supplementary motor area are involved in generating these copies and are associated with decision making and motor preparation (Christensen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Haggard \u0026amp; Whitford, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). These neural mechanisms suggest that the sense of effort is generated prior to actual force production. Supporting this, previous studies have reported that individuals with neurological disorders can regulate force production based on their sense of effort, even when their sense of force is impaired (Teasdale et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1993\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite its importance in voluntary movements, no established method for measuring the sense of effort has been developed. Motor control based on the sense of effort has been shown to vary depending on an individual\u0026rsquo;s current experiences (Rizzato et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Given this background, the sense of effort is being utilized as a performance indicator in sports (Struzik et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, previous studies examining motor control based on the sense of effort have varied considerably in both the type of movement and the method used to indicate force levels. Some studies have employed static tasks (Jackson et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), whereas others have used dynamic movements (Lees et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Kai et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Additionally, force levels have been presented using different approaches, such as % MVC (Kumar et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Pincivero et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) or the Borg scale (John et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Rewitz et al., 2023), indicating a lack of standardization in measurement procedures. Moreover, because sense-of-effort-based motor control is influenced by factors such as muscle condition and fatigue (Proske et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Miyamoto et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), measurements may exhibit reproducibility errors, even under identical testing conditions (Seki \u0026amp; Ohtsuki, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). To determine whether such differences reflect measurement error or true change, reliable assessment methods are required to enhance the consistency of evaluations.\u003c/p\u003e \u003cp\u003eThe grip force task is frequently used as an experimental paradigm because of its comprehensive utility and broad applicability. Handgrip movements are commonly performed in daily life (Bullock et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Saudabayev et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). For example, Saudabayev et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) recorded daily activities and reported that 3,826 hand grip movements were performed over a 9 h period. Moreover, maximum grip force is also a simple and practical measurement with strong predictive validity. Lower grip force has been associated with increased risk of falls (Sayer et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), exacerbation of disease symptoms (Ikeda et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), higher incidence of disease onset (Tuğral et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Madjedi et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), and elevated mortality rates (Cooper et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Given this background, numerous reliable methods for measuring the maximum grip force have been developed, and many studies have reported high reproducibility, indicating that repeated measurements yield consistent values (Bai et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Gr\u0026auml;nicher et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Trajković et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Because force production based on the sense of effort uses a relative percentage of MVC as the force level, the reliability of the MVC measurement is critical. Therefore, the grip force task is well-suited as a standardized test for studies examining force production based on the sense of effort and has been widely adopted across various studies (Stevens \u0026amp; Cain, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; Kumar \u0026amp; Simmonds, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Adamo et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven these considerations, the aim of this study was to examine the test-retest reliability of measuring force production based on the sense of effort in relation to grip force. It is well established that errors tend to increase as the force level increases (Fitts, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1954\u003c/span\u003e). This phenomenon has been attributed to theories involving random fluctuations in motor unit properties (van Beers et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Todorov, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and the roles of neural control strategies and sensory feedback (Nagamori et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover, studies focusing on the sense of force have shown that the reliability of grip-force measurements decreases as the force level increases (Li et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Accordingly, this study was conducted on the basis of the hypothesis that the reliability is the highest at low force levels and the lowest at high force levels.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA total of 33 healthy young men participated in the study (age: 22.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 years; weight: 66.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7 kg; height: 172.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6 cm). An a priori power analysis was performed using G*Power software (version 3.1.9.7). Because the study employed a fully within-subject design involving three force levels and two points (i.e., six repeated conditions per participant), the design was approximated as a one-way repeated-measures analysis of variance (ANOVA) with six levels. Assuming a medium effect size (f\u0026thinsp;=\u0026thinsp;0.25), alpha level of 0.05, and a desired power of 0.95, the estimated required sample size was 28 participants. Furthermore, it has been reported that an insufficient number of participants can affect the outcomes of reliability assessments, and a minimum sample size of 30 participants is recommended for such studies (Koo \u0026amp; Li, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, more than 30 participants were recruited for this study. All participants provided informed consent before participating in the experiment. To avoid potential bias from prior experience, the participants were naive to the experimental task. The study protocol was approved by the Research Ethics Committee of the Graduate School of Sports and Health Studies, Hosei University (approval number: 2024\u0026ndash;18).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental equipment\u003c/h3\u003e\n\u003cp\u003eMaximum grip force and grip force based on the sense of effort were measured using a stationary multipurpose analog amplifier (K800; Biometrics Ltd., UK) and a Jamar-type grip dynamometer (Grip Force Meter G200; Biometrics Ltd., UK). The analog signals from the grip dynamometer were digitized via an A/D converter (PH-670B; Q'sfix, Japan) at a sampling frequency of 1000 Hz and recorded on a computer using TRIAS II software (Q'sfix, Japan). The obtained data were smoothed using a custom Python script (version 3.11.7, Windows). A second-order Butterworth low-pass filter with a cut-off frequency of 10 Hz was applied.\u003c/p\u003e\n\u003ch3\u003eExperimental design\u003c/h3\u003e\n\u003cp\u003eThis study comprised two sessions\u0026mdash;a test session and a retest session (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u0026mdash;conducted by the same experienced examiner. According to previous reports, high reliability in grip force measurements can be achieved by conducting both test and retest sessions using consistent procedures and limb positioning, regardless of the specific posture used for measurement (Watanabe et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Therefore, identical measurements were performed using the same methods and procedures in both sessions. The interval between the test and retest sessions is critical; intervals that are too short increase the likelihood of memory retention or learning effects, whereas excessively long intervals may include true changes in the measured variable (Calamia et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Previous methodological studies generally recommend a one-to-two-week interval for research involving physical performance or activity measurements (Polit, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In practice, a one-week interval is commonly used in studies assessing the reliability of maximum grip force, jump performance, and knee joint proprioception (Venegas-Carro et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Heishman et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ageberg et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Based on these considerations, the interval between sessions for the present study was set to one week. Each session included assessments of maximum grip force and grip force based on the sense of effort. Before the test session, the participants' height and weight were recorded, and handedness was assessed. Handedness was evaluated using the Japanese version of the FLANDERS Handedness Questionnaire (Okubo et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and all grip force measurements were conducted using only the dominant hand.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eProcedures\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMaximum grip force\u003c/h2\u003e \u003cp\u003eMaximum grip force was measured while the participants were seated. The grip dynamometer was placed directly on a table in front of each participant. The elbow was maintained at 90\u0026deg; flexion, and the wrist was positioned at 90\u0026deg; pronation. To prevent the arm from touching the torso or clothing during the measurement, the height and position of the table were individually adjusted. A 5-cm-thick mat was placed under the table, and adjustments were made for each participant to standardize the upper limb posture across the sample. The grip width of the dynamometer was individually adjusted such that the second joint of the index finger formed an approximately right angle while gripping the device. To control the visual input, a fixation point was placed 1 m in front of the participants, and they were instructed to maintain their gaze on it throughout each trial. In this state, each participant performed two trials of MVC. Before each trial, the participants were instructed to generate force as quickly and as strongly as possible to align the peak of the force curve with the force level. A 60-second rest period was provided between trials to minimize the effects of fatigue (Watanabe et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). During these rest periods, the participants were instructed not to release their hand from the dynamometer, as previous studies have suggested that interventions such as static stretching may influence the sense of effort (Macefield et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Trajano et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). To avoid performance bias, no visual or verbal feedback regarding grip force was provided to the participants during the experiment. According to previous studies, multiple measurements of the maximum grip force are required to ensure adequate reliability (Roberts et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Therefore, the average of two valid trials was used as the representative value for the maximum grip force. To ensure that grip force production was driven by the sense of effort rather than afferent feedback, the participants performed ballistic gripping contractions. A ballistic contraction was defined as a muscle contraction meeting two criteria: (1) a short contraction duration and (2) a high rate of force development (Desmedt \u0026amp; Godaux, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1978\u003c/span\u003e). This type of contraction is characterized by the generation of central motor commands (Desmedt \u0026amp; Godaux, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1978\u003c/span\u003e; Hanneton et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). After each trial, the examiner visually inspected the force-time curve to verify whether the criteria were met. Trials that did not meet the criteria were deemed invalid, and additional trials were conducted until two valid trials were obtained for each participant. Prior to measuring the maximum grip force, the participants performed familiarization trials at self-selected force levels and repetitions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGrip force based on the sense of effort\u003c/h2\u003e \u003cp\u003eEach participant was presented with three force levels of 25%, 50%, and 75% of MVC in random order. As in the maximum grip-force assessment, participants were instructed to produce a grip force as quickly as possible and to match the peak of the force curve to the force level based on their sense of effort. Furthermore, they were instructed not to reproduce the grip force in the previous trial but rather to produce the level of force that they currently perceived to correspond to the specified % MVC. Because three or more trials are recommended when assessing reliability (Koo \u0026amp; Li, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), three measurements were conducted for each force level in the present study. For each trial, the measured grip force (kg) was converted to a relative value by dividing it by the participant's MVC. The absolute error (AE) was then calculated as the absolute difference between the relative force value and the prescribed force levels (25%, 50%, and 75% of the MVC). AE, expressed as a percentage (Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), served as an index of accuracy for grip force production based on the sense of effort. Except for the force levels and number of trials, all other measurement conditions were identical to those used for the maximum grip force measurement.\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:AE（％）＝\\left|\\frac{Measured\\:grip\\:force}{MVC}\\times\\:100-force\\:level\\right|$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u0026amp;amp;#x3000;\u0026amp;amp;#x3000;\u0026amp;amp;#x3000;\u0026amp;amp;#x3000;\u0026amp;amp;#x3000;\u0026amp;amp;#x3000;\u0026amp;amp;#x3000;\u0026amp;amp;#x3000;\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eA two-way repeated-measures ANOVA was conducted with AE as the dependent variable and force level (25%, 50%, and 75% MVC) and session (test and retest) as the within-subject factors. This analysis was conducted to examine whether there were differences in the tendency of AE across force levels and to determine whether any systematic bias (e.g., learning effects or fatigue) existed between sessions. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05. The results are reported to three decimal places for readability. All analyses were performed using IBM SPSS Statistics (version 29.0; IBM Corp., Armonk, NY).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eReliability analysis\u003c/h3\u003e\n\u003cp\u003eBland-Altman plots were initially used to visually assess the agreement between test and retest measurements and to detect potential heteroscedasticity or systematic bias (Atkinson \u0026amp; Nevill, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Heteroscedasticity was considered present when the data exhibited a funnel-shaped distribution. In such cases, the coefficient of variation (CV) was adopted as the index of absolute reliability. Conversely, when heteroscedasticity was absent, the standard error of measurement (SEM) was used (Atkinson \u0026amp; Nevill, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Reliability was quantified using intraclass correlation coefficients (ICCs), CV or SEM, and the 95% minimal detectable change (95% MDC). ICCs, representing relative reliability, were calculated based on the recommendations of Koo and Li (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) using a mean rating (k\u0026thinsp;=\u0026thinsp;3), absolute agreement, and a two-way mixed-effects model. ICC values were interpreted according to Cicchetti\u0026rsquo;s classification: poor (ICC\u0026thinsp;\u0026lt;\u0026thinsp;0.40), fair (0.40\u0026thinsp;\u0026le;\u0026thinsp;ICC\u0026thinsp;\u0026lt;\u0026thinsp;0.60), good (0.60\u0026thinsp;\u0026le;\u0026thinsp;ICC\u0026thinsp;\u0026lt;\u0026thinsp;0.75), and excellent (ICC\u0026thinsp;\u0026ge;\u0026thinsp;0.75) (Cicchetti, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1994\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCV, a dimensionless index in which lower values indicate greater precision, was calculated as CV = (SD / Mean) \u0026times; 100. CV is particularly useful for comparing reliability across different measurement tools (Feltz \u0026amp; Miller, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) and for evaluating absolute reliability in datasets that exhibit heteroscedasticity (Bland \u0026amp; Altman, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). SEM, a unit-dependent index, was calculated as SEM\u0026thinsp;=\u0026thinsp;SD \u0026times; \u0026radic;(1 \u0026ndash; ICC). It represents the inherent variability or \u0026ldquo;noise\u0026rdquo; within a measurement (Geerinck et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), with lower SEM values indicating greater measurement precision. The 95% MDC, derived from SEM (95% MDC\u0026thinsp;=\u0026thinsp;1.96 \u0026times; SEM \u0026times; \u0026radic;2), represents the smallest statistically meaningful change beyond measurement error (Furlan \u0026amp; Sterr, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e All the participants who provided informed consent completed the experimental procedures without withdrawal. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e present the mean and SD of AE for each force level and session. A two-way repeated-measures ANOVA was conducted using AE as the dependent variable and force level (25%, 50%, and 75% MVC) and session (test and retest) as the within-subject factors. Prior to analysis, Mauchly\u0026rsquo;s test of sphericity was conducted. Because the assumption of sphericity was violated for the force levels, the Greenhouse\u0026ndash;Geisser correction was applied. The results indicated no significant main effects of force level (\u003cem\u003eF\u003c/em\u003e (1.419, 45.417)\u0026thinsp;=\u0026thinsp;3.320, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.061, \u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e\u0026sup2; = 0.094), session (\u003cem\u003eF\u003c/em\u003e (1, 32)\u0026thinsp;=\u0026thinsp;0.159, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.692, \u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e\u0026sup2; = 0.005), and their interaction (\u003cem\u003eF\u003c/em\u003e (2, 64)\u0026thinsp;=\u0026thinsp;1.546, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.221, \u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e\u0026sup2; = 0.046).\u003c/p\u003e \u003cp\u003eFigures \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e present the Bland-Altman plots for the three force levels. Prior to evaluating the absolute reliability, heteroscedasticity at each force level was visually inspected using the plots. No evidence of heteroscedasticity was observed; therefore, SEM was adopted as the index of absolute reliability in this study. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents AE and the corresponding statistical indices (ICC, SEM, and 95% MDC) for each force level (25%, 50%, and 75% MVC) across the two sessions (test and retest). The highest ICC for AE was observed at 25% MVC, and when considering the 95% confidence interval (95% CI), it was classified as good to excellent according to Cicchetti\u0026rsquo;s (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) criteria. The ICC values for 50% and 75% MVC were comparable and classified as fair to excellent. The SEM and 95% MDC showed the highest reliability at 25% MVC, followed by 75% and 50% MVC.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAbsolute error (AE, %) at each force level and session for grip force based on the sense of effort, together with the corresponding test-retest reliability statistics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eForce level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSession (test)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSession (retest)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean difference (test\u0026thinsp;\u0026minus;\u0026thinsp;retest)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eICC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% MDC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25% MVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.274\u0026thinsp;\u0026plusmn;\u0026thinsp;14.533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.526\u0026thinsp;\u0026plusmn;\u0026thinsp;14.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.748\u0026thinsp;\u0026plusmn;\u0026thinsp;9.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.887 (0.631\u0026ndash;0.894)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.717\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50% MVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e19.395\u0026thinsp;\u0026plusmn;\u0026thinsp;12.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.657\u0026thinsp;\u0026plusmn;\u0026thinsp;12.696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1.262\u0026thinsp;\u0026plusmn;\u0026thinsp;11.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.720 (0.431\u0026ndash;0.862)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e18.338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75% MVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e16.495\u0026thinsp;\u0026plusmn;\u0026thinsp;10.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.233\u0026thinsp;\u0026plusmn;\u0026thinsp;10.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.262\u0026thinsp;\u0026plusmn;\u0026thinsp;9.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.716 (0.426\u0026ndash;0.860)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15.347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we evaluated the potential presence of systematic bias in the measurement of force production based on the sense of effort, revealing that no such bias occurred between the test and retest sessions. Based on the shape of the Bland-Altman plots and the results of the main effect of session, no systematic bias\u0026mdash;such as learning or fatigue effects\u0026mdash;was observed between the test and retest sessions. Systematic changes in force production without structural alterations in muscle are generally attributed to modifications in corticospinal excitability (Lee \u0026amp; Carroll, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), which typically arise through motor learning processes involving repeated practice (Hortob\u0026aacute;gyi et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Leung et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In the present study, participants did not receive external feedback regarding their results because the task was designed to measure their current level of force production based solely on their sense of effort. Therefore, it is reasonable to assume that no systematic bias in AE occurred between the test and retest sessions.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eTest-retest reliability\u003c/h2\u003e \u003cp\u003eEvaluation of the sense of effort at low force levels was found to be highly reliable, with methodological and practical implications. According to Cicchetti\u0026rsquo;s (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) classification and 95% CI, the ICC at 25% MVC was rated as good to excellent. Regarding SEM, the difference between the test and retest sessions was approximately 5%, which was lower than that observed at the other two force levels. Similarly, the 95% MDC indicated that only changes exceeding approximately 13.7% could be interpreted as true changes in force production based on the sense of effort, rather than random error. The observation that the highest reliability occurred at a low force level aligns with previous findings that examined the reliability of the sense of force, such as in grip and pinch force tasks (Li et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This pattern likely reflects behavioral and physiological factors. Many daily activities commonly require only a small fraction of MVC (Kern et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Tikkanen et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Therefore, the present findings may reflect both the frequent use of low-force production in everyday life and the relative simplicity of neural control at lower force levels compared with the increased control difficulty and noise at higher force levels (Desmedt \u0026amp; Godaux, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1978\u003c/span\u003e; Bernardi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Harris \u0026amp; Wolpert, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). These results suggest that the sense of effort during low force control is relatively stable, and such stability is likely essential for maintaining both motor efficiency and physical safety during daily activities.\u003c/p\u003e \u003cp\u003eIn contrast, the reliability outcomes at 50% and 75% MVC were inconsistent across indices, suggesting increased variability in force levels at or above moderate intensity. These results differed from our initial hypothesis. While ICC values at 50% and 75% were comparable, SEM and 95% MDC indicated the lowest reliability at 50% MVC. According to Cicchetti\u0026rsquo;s (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) classification and the 95% CI, both force levels demonstrated fair to excellent relative reliability. Regarding the SEM at 50% MVC, the difference between the test and retest sessions was approximately 6.5%, which was greater than those observed at the other two force levels. Similarly, the 95% MDC results indicated that only changes exceeding\u0026thinsp;~\u0026thinsp;18.0% could be interpreted as representing a true change in force production based on the sense of effort, rather than random error. Because ICC and SEM reflect different aspects of reliability, it is reasonable that their findings do not always align (Stratford \u0026amp; Goldsmith, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). However, classical motor control theories suggest that difficulty in neural control increases linearly with force production (Desmedt \u0026amp; Godaux, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1978\u003c/span\u003e; Bernardi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), leading to reduced reliability at higher force levels. Furthermore, the general tendency of reliability to decline with increasing force levels is also supported by the signal-dependent noise model (Harris \u0026amp; Wolpert, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), which posits that neural noise contributes to motor variability scales with the magnitude of the motor command.\u003c/p\u003e \u003cp\u003eThe lack of a clear force-level-dependent trend in ICC values likely reflects the interplay between within-subject variance (captured by SEM) and between-subject variance. ICC represents the ratio of between-subject variance to total variance (i.e., the sum of between-subject and within-subject variances). Consequently, a greater within-subject variance\u0026mdash;reflecting greater variability between test and retest\u0026mdash;results in a lower ICC. In this study, SEM indicated that the within-subject variance was the highest at 50% MVC among the three force levels, which should theoretically produce the lowest ICC. However, the ICC values at 50% and 75% MVC were comparable, suggesting that in addition to the increase in within-subject variance, between-subject variance may have been elevated at 50% MVC, thereby offsetting the expected decrease in ICC.\u003c/p\u003e \u003cp\u003eThe complexity of force production based on the sense of effort is likely heightened at 50% MVC, potentially leading to reduced reliability at this force level. Previous studies highlighted the increased complexity of force production at moderate force levels; at ~\u0026thinsp;35\u0026ndash;50% MVC, the combined recruitment and firing frequency of motor units reach their most complex state (Slifkin \u0026amp; Newell, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Oliveira et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In the present study, it is plausible that this physiological complexity contributed to an increase in both between-subject and within-subject variances at 50% MVC. This heightened complexity contributes to functional flexibility but critically serves as a primary factor that reduces measurement reliability at moderate force levels. This phenomenon is further supported by mechanisms related to absolute criteria. Previous studies have shown that in tasks requiring the reproduction of the same force level as in a previous trial, the AE varies across different types of movement; however, when normalized to MVC, the magnitude of the error remains consistent regardless of the movement type (Seki \u0026amp; Ohtsuki, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Similarly, although different movement tasks (e.g., grasping and pinching) produce distinct AEs, these errors become comparable when normalized to MVC (Mai et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Based on this theory, the force levels at 25% and 75% MVC in the present study were likely regulated with reference to 0% and 100% of a common scale, respectively. Therefore, it is plausible that referencing these absolute criteria (0% and 100%) contributed to maintaining reliability at these two force levels, whereas 50% MVC lacked such absolute anchors, making force regulation less stable at this intermediate level.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe primary limitations of this study relate to the participant sample, the specificity of the experimental task, and the limited methodological standardization available in this field. These limitations highlight important directions for future research. Because the study included only young adult males, the generalizability of the findings may be limited, as previous research suggests that force production based on the sense of effort exhibits systematic variations depending on sex and age (Jackson et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; John et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Furthermore, variations in the complexity of force production have been reported between younger and older adults (Fiogb\u0026eacute; et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, future studies should include populations with diverse demographic characteristics to verify the generalizability of these findings. Additionally, although the experimental conditions were tightly controlled, the applicability of the results to more complex and dynamic movements remains unclear. Performance in such tasks depends not only on the magnitude of individual force production but also on the spatial and temporal coordination of multiple forces, as demonstrated in studies examining vertical jump performance based on the sense of effort (Sadamoto \u0026amp; Ohtsuki, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). Moreover, it remains unclear whether the present study alone was sufficient to standardize the measurement method for force production based on the sense of effort. Sensory memory related to tactile perception decays rapidly within a few seconds (Bliss et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1966\u003c/span\u003e), and as the interval between the test and retest increases, measurement reliability tends to decrease (Calamia et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Thus, additional research is needed to determine the optimal interval between test and retest sessions. Furthermore, previous studies on force production based on the sense of effort have adopted a wide range of force levels, with no standardized levels established to date (Kumar et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Although the present study examined low-to-high force levels, it remains uncertain how the results might differ at untested levels such as 10% or 90% MVC.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study investigated the test-retest reliability of measuring force production on the basis of the sense of effort in relation to grip force. The results revealed that relative reliability, as indicated by ICCs, was the highest at 25% MVC, whereas 50% and 75% MVC showed comparable levels of reliability. Overall, the relative reliability was classified as fair to excellent. In contrast, absolute reliability, as assessed through SEM, exhibited a different pattern; SEM was the lowest at 50% MVC and the highest at 25% MVC. Overall, these findings suggest that the present study successfully establishes a measurement procedure for assessing force production based on the sense of effort, and that the highest reliability can be achieved at 25% MVC. These findings underscore the value of low-force assessments for reliably evaluating the sense of effort and provide a foundation for developing standardized measurement protocols, while also highlighting the need for future studies to examine broader populations, additional force levels, and more complex movement contexts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institution and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The study was approved by the Research Ethics Committee of the Graduate School of Sports and Health Studies, Hosei University (No. 2024\u0026ndash;18).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe wish to thank the participants who graciously agreed to participate in this study. We also thank the professors and colleagues for their valuable and lively discussions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for conducting this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ryosuke Sugaya, and Yoichi Hayashi. The first draft of the manuscript was written by Ryosuke Sugaya and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data for statistical analysis are available at the following URL: https://osf.io/kmhfy/overview\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdamo DE, Scotland S, Martin BJ (2012) Asymmetry in grasp force matching and sense of effort. Exp Brain Res 217:273\u0026ndash;285. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00221-011-2991-6\u003c/span\u003e\u003cspan address=\"10.1007/s00221-011-2991-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgeberg E, Flenhagen J, Ljung J (2007) Test-retest reliability of knee kinesthesia in healthy adults. BMC Musculoskelet Disord 8:57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2474-8-57\u003c/span\u003e\u003cspan address=\"10.1186/1471-2474-8-57\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsadi H, Zhou G, Lee JJ, Aggarwal V, Yu D (2020) A computer vision approach for classifying isometric grip force exertion levels. Ergonomics 63:1010\u0026ndash;1026. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00140139.2020.1745898\u003c/span\u003e\u003cspan address=\"10.1080/00140139.2020.1745898\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAtkinson G, Nevill AM (1998) Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med 26:217\u0026ndash;238. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2165/00007256-199826040-00002\u003c/span\u003e\u003cspan address=\"10.2165/00007256-199826040-00002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBai Z, Shu T, Niu W (2019) Test-retest reliability and measurement errors of grip strength test in patients with traumatic injuries in the upper extremity: a cross-sectional study. BMC Musculoskelet Disord 20:256. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12891-019-2623-z\u003c/span\u003e\u003cspan address=\"10.1186/s12891-019-2623-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBernardi M, Solomonow M, Sanchez JH, Baratta RV, Nguyen G (1995) Motor unit recruitment strategy of knee antagonist muscles in a step-wise, increasing isometric contraction. Eur J Appl Physiol Occup Physiol 70:493\u0026ndash;501. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF00634378\u003c/span\u003e\u003cspan address=\"10.1007/BF00634378\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBland JM, Altman DG (1995) Comparing two methods of clinical measurement: a personal history. Int J Epidemiol 24(Suppl 1):S7\u0026ndash;S14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ije/24.supplement_1.s7\u003c/span\u003e\u003cspan address=\"10.1093/ije/24.supplement_1.s7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBliss JC, Crane HD, Mansfield PK, Townsend JT (1966) Information available in brief tactile presentations. Percept Psychophys 1:273\u0026ndash;283. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3758/BF03207391\u003c/span\u003e\u003cspan address=\"10.3758/BF03207391\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBullock IM, Zheng JZ, De La Rosa S, Guertler C, Dollar AM (2013) Grasp frequency and usage in daily household and machine shop tasks. IEEE Trans Haptics 6:296\u0026ndash;308. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1109/TOH.2013.6\u003c/span\u003e\u003cspan address=\"10.1109/TOH.2013.6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaro E, Lapuente-Sagarra M, Caparr\u0026oacute;s T, Paj\u0026oacute;n D, Campos-V\u0026aacute;zquez MA (2024) Analysis of the submaximal intensity periods during the competitive microcycle in professional football players. Apunts Educ F\u0026iacute;s Deporte 158:52\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5672/apunts.2014-0983.es.(2024/4).158.06\u003c/span\u003e\u003cspan address=\"10.5672/apunts.2014-0983.es.(2024/4).158.06\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalamia M, Markon K, Tranel D (2013) The robust reliability of neuropsychological measures: meta-analyses of test-retest correlations. Clin Neuropsychol 27:1077\u0026ndash;1105. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/13854046.2013.809795\u003c/span\u003e\u003cspan address=\"10.1080/13854046.2013.809795\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChristensen MS, Lundbye-Jensen J, Geertsen SS, Petersen TH, Paulson OB, Nielsen JB (2007) Premotor cortex modulates somatosensory cortex during voluntary movements without proprioceptive feedback. Nat Neurosci 10:417\u0026ndash;419. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nn1873\u003c/span\u003e\u003cspan address=\"10.1038/nn1873\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCicchetti DV (1994) Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assess 6:284\u0026ndash;290. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/1040-3590.6.4.284\u003c/span\u003e\u003cspan address=\"10.1037/1040-3590.6.4.284\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCooper R, Kuh D, Hardy R, Mortality Review Group, FALCon and HALCyon Study Teams (2010) Objectively measured physical capability levels and mortality: systematic review and meta-analysis. BMJ 341:c4467. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmj.c4467\u003c/span\u003e\u003cspan address=\"10.1136/bmj.c4467\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDesmedt JE, Godaux E (1978) Ballistic contractions in fast or slow human muscles: discharge patterns of single motor units. J Physiol 285:185\u0026ndash;196. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1113/jphysiol.1978.sp012566\u003c/span\u003e\u003cspan address=\"10.1113/jphysiol.1978.sp012566\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEnoka RM, Stuart DG (1992) Neurobiology of muscle fatigue. J Appl Physiol 72:1631\u0026ndash;1648. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1152/jappl.1992.72.5.1631\u003c/span\u003e\u003cspan address=\"10.1152/jappl.1992.72.5.1631\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeltz CJ, Miller GE (1996) An asymptotic test for the equality of coefficients of variation from k populations. Stat Med 15:647\u0026ndash;658. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/(sici)1097-0258(19960330)15:6%3C647::aid-sim184%3E3.0.co;2-p\u003c/span\u003e\u003cspan address=\"10.1002/(sici)1097-0258(19960330)15:6%3C647::aid-sim184%3E3.0.co;2-p\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFiogb\u0026eacute; E, Vassimon-Barroso V, Catai AM, de Melo RC, Quit\u0026eacute;rio RJ, Porta A, Takahashi ACM (2021) Complexity of knee extensor torque: effect of aging and contraction intensity. J Strength Cond Res 35:1050\u0026ndash;1057. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1519/JSC.0000000000002888\u003c/span\u003e\u003cspan address=\"10.1519/JSC.0000000000002888\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFitts PM (1954) The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol 47:381\u0026ndash;391. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/h0055392\u003c/span\u003e\u003cspan address=\"10.1037/h0055392\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFurlan L, Sterr A (2018) The applicability of standard error of measurement and minimal detectable change to motor learning research: a behavioral study. Front Hum Neurosci 12:95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fnhum.2018.00095\u003c/span\u003e\u003cspan address=\"10.3389/fnhum.2018.00095\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeerinck A, Alekna V, Beaudart C, Bautmans I, Cooper C, De Souza Orlandi F, Konstantynowicz J, Montero-Errasqu\u0026iacute;n B, Topinkov\u0026aacute; E, Tsekoura M, Reginster JY, Bruy\u0026egrave;re O (2019) Standard error of measurement and smallest detectable change of the Sarcopenia Quality of Life (SarQoL) questionnaire: an analysis of subjects from 9 validation studies. PLoS ONE 14:e0216065. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0216065\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0216065\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGr\u0026auml;nicher P, Maurer Y, Sp\u0026ouml;rri J, Haller B, Swanenburg J, de Bie RA, Lenssen TAF, Scherr J (2024) Accuracy and reliability of grip strength measurements: a comparative device analysis. J Funct Morphol Kinesiol 9:274. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/jfmk9040274\u003c/span\u003e\u003cspan address=\"10.3390/jfmk9040274\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaggard P, Whitford B (2004) Supplementary motor area provides an efferent signal for sensory suppression. Cogn Brain Res 19:52\u0026ndash;58. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cogbrainres.2003.10.018\u003c/span\u003e\u003cspan address=\"10.1016/j.cogbrainres.2003.10.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHanneton S, Berthoz A, Droulez J, Slotine JJE (1997) Does the brain use sliding variables for the control of movements? Biol Cybern 77:381\u0026ndash;393. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s004220050398\u003c/span\u003e\u003cspan address=\"10.1007/s004220050398\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarris CM, Wolpert DM (1998) Signal-dependent noise determines motor planning. Nature 394:780\u0026ndash;784. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/29528\u003c/span\u003e\u003cspan address=\"10.1038/29528\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeishman AD, Daub BD, Miller RM, Freitas EDS, Frantz BA, Bemben MG (2020) Countermovement jump reliability performed with and without an arm swing in NCAA Division 1 intercollegiate basketball players. J Strength Cond Res 34:546\u0026ndash;558. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1519/JSC.0000000000002812\u003c/span\u003e\u003cspan address=\"10.1519/JSC.0000000000002812\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHortob\u0026aacute;gyi T, Richardson SP, Lomarev M, Shamim E, Meunier S, Russman H, Dang N, Hallett M (2011) Interhemispheric plasticity in humans. Med Sci Sports Exerc 43:1188\u0026ndash;1199. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1249/MSS.0b013e31820a94b8\u003c/span\u003e\u003cspan address=\"10.1249/MSS.0b013e31820a94b8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIkeda K, Ikumi A, Onishi S, Ogawa T, Kohyama S, Yoshii Y (2025) Predicting refractoriness in lateral epicondylitis using initial grip strength and QuickDASH: a retrospective cohort study. BMC Musculoskelet Disord 26:645. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12891-025-08902-7\u003c/span\u003e\u003cspan address=\"10.1186/s12891-025-08902-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrid Y, Hutin J, Toussaint J, Sedeaud A (2025) Exploring the most demanding scenarios in elite youth basketball: a comprehensive analysis across playing positions and time windows. Biol Sport 42:37\u0026ndash;47. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5114/biolsport.2025.148537\u003c/span\u003e\u003cspan address=\"10.5114/biolsport.2025.148537\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJackson AW, Dishman RK, Martin SB (2002) Perceived leg extension and flexion forces of young adult men and women: comparison to previous findings. Res Q Exerc Sport 73:225\u0026ndash;228. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/02701367.2002.10609013\u003c/span\u003e\u003cspan address=\"10.1080/02701367.2002.10609013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJackson AW, Ludtke AW, Martin SB, Koziris LP, Dishman RK (2006) Perceived submaximal force production in young adults. Res Q Exerc Sport 77:50\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/02701367.2006.10599331\u003c/span\u003e\u003cspan address=\"10.1080/02701367.2006.10599331\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohn EB, Liu W, Gregory RW (2009) Biomechanics of muscular effort: age-related changes. Med Sci Sports Exerc 41:418\u0026ndash;425. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1249/MSS.0b013e3181884480\u003c/span\u003e\u003cspan address=\"10.1249/MSS.0b013e3181884480\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones LA (1986) Perception of force and weight: theory and research. Psychol Bull 100:29\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/2942958/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/2942958/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKai S, Nakahara M, Watari K, Murakami S, Yoshimoto R (2006) Knee joint angle at the time of adjustment to submaximal jumping in healthy men. J Phys Ther Sci 18:11\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1589/jpts.18.11\u003c/span\u003e\u003cspan address=\"10.1589/jpts.18.11\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKern DS, Semmler JG, Enoka RM (2001) Long-term activity in upper- and lower-limb muscles of humans. J Appl Physiol 91:2224\u0026ndash;2232. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1152/jappl.2001.91.5.2224\u003c/span\u003e\u003cspan address=\"10.1152/jappl.2001.91.5.2224\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoo TK, Li MY (2016) A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 15:155\u0026ndash;163. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jcm.2016.02.012\u003c/span\u003e\u003cspan address=\"10.1016/j.jcm.2016.02.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar S, Simmonds M (1994) The accuracy of magnitude production of submaximal precision and power grips and gross motor efforts. Ergonomics 37:1345\u0026ndash;1353. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00140139408964913\u003c/span\u003e\u003cspan address=\"10.1080/00140139408964913\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar S, Narayan Y, Chouinard K (1997) Effort reproduction accuracy in pinching, gripping, and lifting among industrial males. Int J Ind Ergon 20:109\u0026ndash;119. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0169-8141(96)00045-5\u003c/span\u003e\u003cspan address=\"10.1016/S0169-8141(96)00045-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLafargue G, Franck N (2009) Effort awareness and sense of volition in schizophrenia. Conscious Cogn 18:277\u0026ndash;289. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.concog.2008.05.004\u003c/span\u003e\u003cspan address=\"10.1016/j.concog.2008.05.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLafargue G, Paillard J, Lamarre Y, Sirigu A (2003) Production and perception of grip force without proprioception: is there a sense of effort in deafferented subjects? Eur J Neurosci 17:2741\u0026ndash;2749. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1046/j.1460-9568.2003.02700.x\u003c/span\u003e\u003cspan address=\"10.1046/j.1460-9568.2003.02700.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee M, Carroll TJ (2007) Cross education: possible mechanisms for the contralateral effects of unilateral resistance training. Sports Med 37:1\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2165/00007256-200737010-00001\u003c/span\u003e\u003cspan address=\"10.2165/00007256-200737010-00001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLees A, Vanrenterghem J, De Clercq D (2004) The maximal and submaximal vertical jump: implications for strength and conditioning. J Strength Cond Res 18:787\u0026ndash;791. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/15574084/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/15574084/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeung M, Rantalainen T, Teo WP, Kidgell D (2018) The ipsilateral corticospinal responses to cross-education are dependent upon the motor-training intervention. Exp Brain Res 236:1331\u0026ndash;1346. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00221-018-5224-4\u003c/span\u003e\u003cspan address=\"10.1007/s00221-018-5224-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi L, Li Y, Wu C, Zhang X (2020) Test-retest reliability of tip, key, and palmar pinch force sense in healthy adults. BMC Musculoskelet Disord 21:189. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12891-020-3187-7\u003c/span\u003e\u003cspan address=\"10.1186/s12891-020-3187-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi YX, Li L, Chen X, Zhao Y, Zhao X, Zhang CL (2022) Assessment of grip force sense test-retest reliability in healthy male participants. Ergonomics 65:1621\u0026ndash;1630. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00140139.2022.2044521\u003c/span\u003e\u003cspan address=\"10.1080/00140139.2022.2044521\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMacefield G, Hagbarth KE, Gorman R, Gandevia SC, Burke D (1991) Decline in spindle support to alpha-motoneurones during sustained voluntary contractions. J Physiol 440:497\u0026ndash;512. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1113/jphysiol.1991.sp018721\u003c/span\u003e\u003cspan address=\"10.1113/jphysiol.1991.sp018721\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMadjedi KM, Stuart KV, Yin GS, Luben RN, Sun Z, Biradar M, Hu R, Foster PJ, Khaw PT, Bell KC, Crowston JG, Khawaja AP, UK Biobank Eye and Vision Consortium (2025) The association of muscle-related factors with glaucoma and related traits in a large United Kingdom population. Invest Ophthalmol Vis Sci 66:66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1167/iovs.66.6.66\u003c/span\u003e\u003cspan address=\"10.1167/iovs.66.6.66\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMai N, Schreiber P, Hermsd\u0026ouml;rfer J (1991) Changes in perceived finger force produced by muscular contractions under isometric and anisometric conditions. Exp Brain Res 84:453\u0026ndash;460. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF00231469\u003c/span\u003e\u003cspan address=\"10.1007/BF00231469\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCloskey DI, Macefield G, Gandevia SC, Burke D (1987) Sensing position and movements of the fingers. News Physiol Sci 2(6):226\u0026ndash;230. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1152/physiologyonline.1987.2.6.226\u003c/span\u003e\u003cspan address=\"10.1152/physiologyonline.1987.2.6.226\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiyamoto T, Kizuka T, Ono S (2020) Influence of preceding muscle activity on perceptually guided force production during superimposed ballistic contraction. Physiol Behav 222:112933. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.physbeh.2020.112933\u003c/span\u003e\u003cspan address=\"10.1016/j.physbeh.2020.112933\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagamori A, Laine CM, Loeb GE, Valero-Cuevas FJ (2021) Force variability is mostly not motor noise: Theoretical implications for motor control. PLoS Comput Biol 17(3):e1008707. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pcbi.1008707\u003c/span\u003e\u003cspan address=\"10.1371/journal.pcbi.1008707\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOliveira JH, Gomes JS, Bauer P, Pezarat-Correia P, Vaz JR (2025) Force fluctuations regulation and the role of neurophysiological mechanisms throughout different isometric contraction intensities. Sci Rep 15(1):28442. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-025-14543-6\u003c/span\u003e\u003cspan address=\"10.1038/s41598-025-14543-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkubo M, Suzuki H, Nicholls MER (2014) A Japanese version of the FLANDERS handedness questionnaire: Reliability and validity. Jpn J Psychol 85(5):474\u0026ndash;481. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4992/jjpsy.85.13235\u003c/span\u003e\u003cspan address=\"10.4992/jjpsy.85.13235\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePincivero DM, Coelho AJ, Campy RM, Salfetnikov Y, Bright A (2001) The effects of voluntary contraction intensity and gender on perceived exertion during isokinetic quadriceps exercise. Eur J Appl Physiol 84(3):221\u0026ndash;226. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s004210170008\u003c/span\u003e\u003cspan address=\"10.1007/s004210170008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolit DF (2014) Getting serious about test\u0026ndash;retest reliability: A critique of retest research and some recommendations. Qual life research: Int J Qual life aspects Treat care rehabilitation 23(6):1713\u0026ndash;1720. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11136-014-0632-9\u003c/span\u003e\u003cspan address=\"10.1007/s11136-014-0632-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePreston J, Wegner DM (2009) Elbow grease: When action feels like work. In: Morsella E, Bargh JA, Gollwitzer PM (eds) Oxford handbook of human action: Social cognition and social neuroscience. Oxford University Press, New York, pp 569\u0026ndash;586\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProske U, Gregory JE, Morgan DL, Percival P, Weerakkody NS, Canny BJ (2004) Force matching errors following eccentric exercise. Hum Mov Sci 23(3\u0026ndash;4):365\u0026ndash;378. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.humov.2004.08.012\u003c/span\u003e\u003cspan address=\"10.1016/j.humov.2004.08.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProske U, Gandevia SC (2012) The proprioceptive senses: Their roles in signaling body shape, body position and movement, and muscle force. Physiol Rev 92(4):1651\u0026ndash;1697. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1152/physrev.00048.2011\u003c/span\u003e\u003cspan address=\"10.1152/physrev.00048.2011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRewitz K, Schindler S, Wolff W (2024) Examining the alignment between subjective effort and objective force production. PLoS ONE 19(8):e0307994. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0307994\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0307994\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRizzato A, Cantarella G, Basso E, Paoli A, Rotundo L, Bisiacchi P, Marcolin G (2024) Relationship between intended force and actual force: Comparison between athletes and non-athletes. PeerJ 12:e17156. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7717/peerj.17156\u003c/span\u003e\u003cspan address=\"10.7717/peerj.17156\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, Sayer AA (2011) A review of the measurement of grip strength in clinical and epidemiological studies: Towards a standardised approach. Age Ageing 40(4):423\u0026ndash;429. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ageing/afr051\u003c/span\u003e\u003cspan address=\"10.1093/ageing/afr051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSadamoto T, Ohtsuki T (1977) Accuracy of output control in jumping: Characteristics in grading and reproduction of distance jumped. Jpn J Phys Educ Health Sport Sci 22(4):215\u0026ndash;229. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5432/jjpehss.KJ00003392573\u003c/span\u003e\u003cspan address=\"10.5432/jjpehss.KJ00003392573\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaudabayev A, Rysbek Z, Khassenova R, Varol HA (2018) Human grasping database for activities of daily living with depth, color and kinematic data streams. Sci Data 5:180101. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/sdata.2018.101\u003c/span\u003e\u003cspan address=\"10.1038/sdata.2018.101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSayer AA, Syddall HE, Martin HJ, Dennison EM, Anderson FH, Cooper C (2006) Falls, sarcopenia, and growth in early life: Findings from the Hertfordshire cohort study. Am J Epidemiol 164(7):665\u0026ndash;671. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/aje/kwj255\u003c/span\u003e\u003cspan address=\"10.1093/aje/kwj255\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeki T, Ohtsuki T (1995) Reproducibility of subjectively graded voluntary isometric muscle strength in unilateral and simultaneous bilateral exertion. Ergonomics 38(9):1867\u0026ndash;1876. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00140139508925234\u003c/span\u003e\u003cspan address=\"10.1080/00140139508925234\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSlifkin AB, Newell KM (2000) Variability and noise in continuous force production. J Mot Behav 32(2):141\u0026ndash;150. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00222890009601366\u003c/span\u003e\u003cspan address=\"10.1080/00222890009601366\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Smirmaul B P (2012) Sense of effort and other unpleasant sensations during exercise: Clarifying concepts and mechanisms. Br J Sports Med 46(5):308\u0026ndash;311. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bjsm.2010.071407\u003c/span\u003e\u003cspan address=\"10.1136/bjsm.2010.071407\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStevens JC, Cain WS (1970) Effort in isometric muscular contractions related to force level and duration. Percept Psychophys 8:240\u0026ndash;244. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3758/BF03210214\u003c/span\u003e\u003cspan address=\"10.3758/BF03210214\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStratford PW, Goldsmith CH (1997) Use of the standard error as a reliability index of interest: An applied example using elbow flexor strength data. Phys Ther 77(7):745\u0026ndash;750. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ptj/77.7.745\u003c/span\u003e\u003cspan address=\"10.1093/ptj/77.7.745\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStruzik A, Pietraszewski B, Kawczyński A, Winiarski S, Juras G, Rokita A (2017) Manifestations of proprioception during vertical jumps to specific heights. J Strength Cond Res 31(6):1694\u0026ndash;1701. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1519/JSC.0000000000001868\u003c/span\u003e\u003cspan address=\"10.1519/JSC.0000000000001868\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeasdale N, Forget R, Bard C, Paillard J, Fleury M, Lamarre Y (1993) The role of proprioceptive information for the production of isometric forces and for handwriting tasks. Acta Psychol (Amst) 82(1\u0026ndash;3):179\u0026ndash;191. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0001-6918(93)90011-F\u003c/span\u003e\u003cspan address=\"10.1016/0001-6918(93)90011-F\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThompson S, Gregory JE, Proske U (1990) Errors in force estimation can be explained by tendon organ desensitization. Exp Brain Res 79(2):365\u0026ndash;372. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF00608246\u003c/span\u003e\u003cspan address=\"10.1007/BF00608246\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTikkanen O, Haakana P, Pesola AJ, H\u0026auml;kkinen K, Rantalainen T, Havu M, Pullinen T, Finni T (2013) Muscle activity and inactivity periods during normal daily life. PLoS ONE 8(1):e52228. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0052228\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0052228\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTodorov E (2004) Optimality principles in sensorimotor control. Nat Neurosci 7(9):907\u0026ndash;915. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nn1309\u003c/span\u003e\u003cspan address=\"10.1038/nn1309\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrajano GS, Seitz LB, Nosaka K, Blazevich AJ (2014) Can passive stretch inhibit motoneuron facilitation in the human plantar flexors? J Appl Physiol 117(12):1486\u0026ndash;1492. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1152/japplphysiol.00809.2014\u003c/span\u003e\u003cspan address=\"10.1152/japplphysiol.00809.2014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrajković N, Rančić D, Ilić T, Herodek R, Korobeynikov G, Pekas D (2024) Measuring handgrip strength in school children: Inter-instrument reliability between Takei and Jamar. Sci Rep 14(1):1074. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-024-51368-1\u003c/span\u003e\u003cspan address=\"10.1038/s41598-024-51368-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTuğral A, Bakar Y, Akyol M (2025) Predictors of upper extremity function in breast cancer survivors. Physiother Res Int 30(3):e70082. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/pri.70082\u003c/span\u003e\u003cspan address=\"10.1002/pri.70082\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Beers RJ, Haggard P, Wolpert DM (2004) The role of execution noise in movement variability. J Neurophysiol 91(2):1050\u0026ndash;1063. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1152/jn.00652.2003\u003c/span\u003e\u003cspan address=\"10.1152/jn.00652.2003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan der Molen HF, Foresti C, Daams JG, Frings-Dresen MHW, Kuijer PPFM (2017) Work-related risk factors for specific shoulder disorders: A systematic review and meta-analysis. Occup Environ Med 74(10):745\u0026ndash;755. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/oemed-2017-104339\u003c/span\u003e\u003cspan address=\"10.1136/oemed-2017-104339\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Rijn RM, Huisstede BMA, Koes BW, Burdorf A (2010) Associations between work-related factors and specific disorders of the shoulder: A systematic review of the literature. Scand J Work Environ Health 36(3):189\u0026ndash;201. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5271/sjweh.2895\u003c/span\u003e\u003cspan address=\"10.5271/sjweh.2895\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVenegas-Carro M, Kramer A, Moreno-Villanueva M, Gruber M (2022) Test\u0026ndash;retest reliability and sensitivity of common strength and power tests over a period of 9 weeks. Sports (Basel) 10(11):171. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/sports10110171\u003c/span\u003e\u003cspan address=\"10.3390/sports10110171\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWatanabe T, Owashi K, Kanauchi Y, Mura N, Takahara M, Ogino T (2005) The short-term reliability of grip strength measurement and the effects of posture and grip span. J Hand Surg Am 30(3):603\u0026ndash;609. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jhsa.2004.12.007\u003c/span\u003e\u003cspan address=\"10.1016/j.jhsa.2004.12.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sense of effort, grip force, force control, test-retest reliability, intraclass correlation coefficients, standard error of measurement","lastPublishedDoi":"10.21203/rs.3.rs-8784009/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8784009/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAccurate force production based on the sense of effort plays a critical role in daily motor control and clinical assessment; however, the reliability of such force production across different force levels remains insufficiently understood. Establishing reliable measurement conditions is essential for interpreting changes in force production based on the sense of effort in both research and applied settings. In this study, we examined the test-retest reliability of grip-force production based on the sense of effort at three force levels: 25%, 50%, and 75% of the maximum voluntary contraction (MVC). A total of 33 young men performed grip-force tests across two sessions, separated by one week, without external feedback. Relative reliability was evaluated using intraclass correlation coefficients (ICCs), and absolute reliability was assessed using standard error of measurement (SEM) and the 95% minimal detectable change. The highest reliability was observed at 25% MVC, with a tendency toward reduced reliability at 50% MVC. These findings suggest that low-force-level production based on the sense of effort is relatively stable, possibly reflecting its frequent use in daily activities and simpler neural control mechanisms. Therefore, it is suggested that lower force levels enable more reliable measurements when evaluating force production based on the sense of effort\u003c/p\u003e","manuscriptTitle":"Reliability of Force Production Based on the Sense of Effort at Different Force Levels","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 15:15:40","doi":"10.21203/rs.3.rs-8784009/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"26a39d68-6c78-4630-bb72-2debae7e4a29","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T03:23:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 15:15:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8784009","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8784009","identity":"rs-8784009","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}