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. 2024 Aug 4;14:18038. doi: 10.1038/s41598-024-66931-z

Validation of the athletic mental energy scale for Chinese school-age adolescents

Jiarun Wu 1,2, Frank J H Lu 3, Yishuai Wang 2, Yee Cheng Kueh 4, Garry Kuan 2,✉
PMCID: PMC11298513  PMID: 39098949

Abstract

Mental energy is an important factor in many domains, including athletic performance. The athletic mental energy scale (AMES) is one of the established tools available to measure athletes’ perceived mental energy state. To date, there is no validated questionnaire to assess athletic mental energy for Chinese adolescents. Therefore, purpose of this study was to validate a Chinese version of AMES (C-AMES) among the Chinese adolescents in Lanzhou, Gansu Province, China. We sampled 729 adolescents aged 14 to 18 in five middle schools in Lanzhou City, Gansu Province, China to complete the revised C-AMES. Data were analyzed for factor structure validity by performing CFA. The results showed that the fit index was acceptable (RMSEA = 0.050, CFI = 0.962, TLI = 0.951), and a six-factor model containing 18 C-AMES items had good measurement properties for athletic mental energy. We suggest future study may use C-AMES to examine the relationship between athletes’ mental energy and athletic performance and sporting behavior.

Keywords: Measurement validation, Psychology of sport excellence, Optimal state of mind, Sport psychology

Subject terms: Psychology, Human behaviour

Introduction

Researchers from various fields, including sports psychology, have extensively explored the concept of mental energy. In its early stages, mental energy was referred to as attention ability1–5, reaction time2, memory1,4 language3, visual processing speed1,5, executive function3, or emotional experiences6,7. Due to the lack of a clear definition, researchers in the early stages attempted various measurement methods, such as depression and anxiety scales8, memory tests4, attention tests4, mood scales6,7, visual analog scales4,9, or self-developed questionnaires10,11 to assess what they referred to as "mental energy." As a result, mental energy lacked a solid theoretical framework and specialized measurement tools for a considerable period.

Recognizing the pivotal role of mental energy in human functioning, the North American Branch of the international life science institute (ILSI) convened a workshop during a 2005 world conference to define and conceptualize mental energy. Following in-depth discussions, they ultimately provided a clear definition for mental energy: “the intensity of subjective feeling about one’s capacity to accomplish tasks of daily life-these feelings fluctuate from moment to moment” 12. Additionally, ILSI established a model for mental energy, encompassing five crucial components: motivation, cognition, quality of life, mood, and sleepiness12.

Due to the close positive relationship between mental energy and athletic performance, researchers in sports psychology have shown significant interest in the concept of mental energy. This is rooted in their belief that mental energy enhances key factors such as confidence, motivation, attention control, and emotional management, which collectively improve athletes’ overall performance13. Nideffer (1985) introduced a psychological skill known as “centering”, which he believed could harness energy and induce a state of confidence and focus14. Subsequently, Nideffer (1985) applied this technique in practice, aiding a former male javelin thrower in achieving a world record, capturing the attention of sports psychology researchers14.

Through further exploration, sports psychologists have conceptualized athletes’ performance within a pyramid structure of energy. At the base lies physical energy, followed by emotional energy, mental energy, and at the pinnacle, spiritual energy15. Among these various forms of energy, mental energy is associated with higher-order functions such as cognition, perception, abstract thinking, creativity, and self-awareness/regulation.

In the process of studying mental energy, sports psychologists have employed various methods to measure it, such as the self-awareness checklist, Multidimensional inventory of sport excellence scale (MUSI)16,17. In their 2015 book, “Foundations of Sport and Exercise Psychology,” Weinberg and Gould (2023) introduced content related to self-awareness and mental energy17. They primarily discussed the importance of enhancing self-awareness and provided various methods and strategies to help athletes improve their self-awareness, thereby increasing their mental energy. Therefore, the self-awareness checklist is not specifically designed to measure mental energy. The mental energy scale, included in the MUSI, is composed of 14 items based on self-assessment of “mental energy” levels. Respondents are required to rate their behaviors on a 5-point Likert scale ranging from strongly disagree (1) to strongly agree (5). Although the scale has demonstrated high internal consistency reliability (Cronbach’s alpha = 0.895), it is considered unidimensional16. This means that all items collectively measure a single psychological construct, “mental energy,” rather than multiple distinct constructs or factors. Consequently, the scale can only provide an overall assessment of the respondent’s mental energy and does not differentiate between different types or aspects of mental energy. This unidimensional scale can be very useful in certain research and application contexts; however, for more detailed and specific assessments of mental energy, it may be necessary to use multidimensional scales or combine it with other assessment tools. Due to the lack of specialized tools and reliable measures for assessing mental energy in sports, researchers have faced challenges in gaining a deeper understanding of the role of mental energy in athletics. Addressing this gap, Lu et al.18 developed a sport-specific mental energy scale called the Athletic Mental Energy Scale (AMES) in response to the absence of suitable measurement tools for mental energy in sports19. This questionnaire comprises 18 items organized into six factors: Vigor, Confidence, Motivation, Tiredness, Concentration, and Calm. Its application has demonstrated high reliability and validity.

Recent studies have shown that athletic mental energy can improve an athlete's competitive courage and attitude, subsequently enhancing their athletic performance and predicting sports outcomes19–21. Additionally, research has indicated significant correlations between the four latent factors of athletic mental energy (vigor, confidence, motivation, and tirelessness) and individual factors related to mindfulness (awareness, non-judgmental attitude, and refocusing), as well as aspects of flow, balance, and absorption in the task22. This suggests that individuals with higher levels of athletic mental energy tend to exhibit stronger focus, making them less susceptible to external distractions. The finding that athletic mental energy can enhance concentration has broad implications, as it is not only crucial for improving athletes’ performance and outcomes but also has significant implications for enhancing academic focus among adolescents. Furthermore, the rapid development of China's sports industry has led to increasing attention on the psychological well-being and performance of adolescent athletes. However, there is currently no validated tool available to assess the athletic mental energy of Chinese adolescents. Therefore, the translation and validation of the Chinese version of AMES (C-AMES) are urgently needed. The validation of C-AMES would provide a powerful tool for Chinese sports psychologists and practitioners, enabling them to better understand and assess the mental energy of adolescent athletes. This, in turn, would facilitate the development of targeted intervention measures to enhance sports performance and overall psychological well-being.

Materials and methods

Participants

The study obtained ethical approval from the Human Research Ethics Committee of Universiti Sains Malaysia (USM) under the reference code USM/JEPeM/22040247. This ethical approval is valid from August 21, 2022, until August 20, 2023. The research employed a cross-sectional design and took place between September and October 2022, involving questionnaire surveys conducted within secondary schools in Lanzhou, Gansu Province, China. Using confirmatory factor analysis (CFA), larger sample sizes generally yield more stable solutions and are more likely to achieve replication in CFA. According to Hair et al. (2014), if the number of factors exceeds six, the required sample size may surpass 500 participants23. In this study, the AMES comprises six factors, necessitating a minimum of 500 participants to complete the survey. Considering an anticipated attrition rate of 30%, at least 715 participants are required. A total of 729 participants aged 14 to 18 were included in the study, with 67.6% being male (n = 493) and 32.4% female (n = 236). The participants' ages ranged from 14 to 18 years, with a mean age of 16.2 years (SD = 1.1), meeting all inclusion and exclusion criteria. Five schools were randomly selected from the list of schools in Lanzhou. Within each selected school, two to three classes were chosen using random sampling. All students from the selected classes were invited to participate in the study. The inclusion criteria comprised students currently attending secondary schools in Lanzhou, aged between 14 and 18, and proficient in reading and communicating in Chinese, and capable of participating in regular school physical activities. Exclusion criteria encompassed students from specialized schools, those with visual, auditory, or other impairments hindering autonomous completion of the questionnaire.

Measures

Socio-demographic information

We gathered socio-demographic data from the participants, including age, gender, and class.

Athletic mental energy scale (AMES)

The athletic mental energy scale (AMES) is a questionnaire developed by Lu et al.18 with the specific purpose of assessing mental energy19. The questionnaire comprises 18 interconnected questions. Respondents are required to select the most suitable level (ranging from completely so to totally inconsistent) from the 6 response options based on their own feelings. Each response option corresponds to a score (ranging from 6 to 1). The cumulative score serves as an indicator of participants’ mental energy. This questionnaire has demonstrated strong reliability (Cronbach's α = 0.95) following its utilization in both Taiwan and Malaysia, affirming its effectiveness as a tool for measuring mental energy. Sample question for vigor is “I feel spiritual to do everything in sports”; for confidence is “I feel I can win all competitions in the future”; for motivation is “I feel excited in future competitions”; for concentration is “There’s nothing distracting me in competition”; for tireless is “No matter how long the training lasts I don’t feel tired”; for calm is “When facing to my opponents I am calm”.

Procedure

The athletic mental energy scale (AMES) was translated from the original English version using the following steps:

  1. Forward translation from English to Chinese version was done by two experts who were native speakers in Chinese language. They were invited by email. The two completed the translation work independently. These two forward translations are then reconciled into one consensus translation before back-translation. This was done by the research team. This step is very important to resolve discrepancies between translations. Certain words or phrases in the translated questionnaire require alternate translations.

  2. Two other bilingual experts who had not seen the original English version back-translated the Chinese version into English. The purpose of the back translation process is to ensure that the quality of the Chinese translation is such that when translated back to English, the meaning is the same.

  3. Two Expert in psychology who were competent Chinese and English bilingual speakers reviewed both the English translation from Chinese and Chinese translated version from English before finalising it to Chinese version of AMES (C-AME). It was to detect and deal with any translation discrepancies between the two versions of questionnaire.

The final version of C-AMES was pre-tested on 10 adolescents to ensure its clarity and comprehension for the intended population. The results of the preliminary test and the final Chinese scale are satisfactory, so no modification is required.

During the translation process, the main challenge was how to provide linguistic equivalence in terms of meaning and idiomatic usage between the original and translated versions of the questionnaire. In response to this problem, we made some arrangements in advance, such as inviting two independent translators who are proficient in two languages to perform a forward translation, and another translator will perform a back-translation after the forward translation, to coordinate the final Chinese version of the questionnaire, and administered a questionnaire test in a small group of adolescents.

Following the pilot testing, we proceeded with data collection and continued the Confirmatory Factor Analysis (CFA) study. One week prior to the commencement of the study, researchers visited schools and distributed informed consent forms to parents through the students. One week later, we collected the signed consent forms from these schools. After reviewing the returned forms, we compiled a list of participating students with parental consent. Data collection took place during school hours, specifically during free study periods or physical education classes. While parental consent was obtained, participation in the study was voluntary for the students. Those who agreed to participate were required to sign an informed consent form, indicating their willingness to take part in the research. Participants did not receive any monetary compensation for their involvement. As a token of appreciation for their participation, each individual received a pen, which was provided upon completion of the survey questionnaire.

Statistical analysis

The sociodemographic data of the study subjects were subjected to descriptive statistics using SPSS 27.0 software. First, we use descriptive statistics to examine skewness, kurtosis, outliers, and identifying any missing values. After initial screen of the data, we conducted a Confirmatory Factor Analysis (CFA) by using MPlus version 8.0 software.

Confirmatory factor analysis (CFA)

A total of 729 participants were included in the CFA study. During the process of model re-specification, any problematic items with factor loadings below 0.4024 were considered for removal, and they were assessed interactively. As per the guidelines proposed by MPlus, modification indices (MI) were examined, and if necessary, residual correlations for specific items were added. All model re-specifications were conducted in consultation with the research team and were based on well-established theoretical support.

The model fit was evaluated using the following indices: Root Mean Square Error of Approximation (RMSEA) with an acceptable level of < 0.08, Weighted Root Mean Square Residual (WRMR) with an acceptable level of < 1.025, Tucker-Lewis Fit Index (TLI) with an acceptable level of > 0.92, and Comparative Fit Index (CFI) with an acceptable level of > 0.9223. The construct reliability (CR) of the CFA measurement model for the C-AMES scale was assessed using Raykov’s method26. A recommended CR value is at least 0.70 or higher. Discriminant validity of factors was established by examining the inter-factor correlations from the final CFA measurement model, and it is considered acceptable if the correlation value is below 0.8527.

Ethics approval

This study obtained approval from the USM Human Research Ethics Committee (USM/JEPeM/22040247) and was conducted in accordance with the guidelines of the International Declaration of Helsinki.

Results

Socio demographic characteristics of the study variables

Referring to Table 1, there were 729 participants with an average age of 16.2 years (SD = 1.1). The majority of participants were male, and all respondents were of Chinese nationality. Given that the average age of participants was 16.2 years and the age of 16 typically represents the middle stage of adolescence, the study categorized participants based on this age. Additionally, 60.5% of the participants were aged 16 years or below, comprising 420 first-year high school students, 124 s-year high school students, and 185 third-year high school students among the total participants.

Table 1.

Demographic characteristics of people with participants (n = 729).

Characteristics Frequencies Percentage (%) Mean (SD)
Gender
 Male 493 67.6
 Female 236 32.4
Age 16.2 (1.1)
Age group
 Age 16 and under 441 60.5
 Over 16 years old 288 39.5
Grade
 1 420 57.6
 2 124 17.0
 3 185 25.4
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Structure validity by confirmatory factor analysis (CFA)

The structure validity of C-AMES was assessed using Confirmatory Factor Analysis (CFA). A CFA was performed on the six-factor model of the 18 items, and the results demonstrated that the fit indices of the model were within acceptable thresholds. All fit indices reached the recommended thresholds (refer to Table 2), and the factor loadings of each item on its respective factor were satisfactory. All item factor loadings were > 0.6. Besides, Table 3 presents the standardized factor loadings of the six-factor model. The CR values for each factor were all > 0.70, indicating acceptable construct reliability.

Table 2.

Goodness of fit indices for athletic mental energy with six factors (standard values and actual value).

Model fitting index χ2 df χ2/df SRMR RMSEA TLI CFI
Standard values  < 5  < 0.08  < 0.08  > 0.90  > 0.90
Actual value 338.532 120 2.821 0.031 0.050 0.951 0.962
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χ2 chi-square, df degrees of freedom, CFI comparative fit index, TLI tucker-lewis index, SRMR standardised root mean square residual, RMSEA root mean square error of approximation.

Table 3.

Composite reliability and average variance extracted for athletic mental energy with six factors.

Estimate S.E Est./S.E P-Value SMC CR AVE
Vig V1 0.778 0.023 34.475 *** 0.605 0.796 0.566
V2 0.778 0.023 34.009 *** 0.605
V3 0.699 0.023 29.986 *** 0.489
Cof V4 0.8 0.021 37.676 *** 0.640 0.816 0.597
V5 0.763 0.022 34.553 *** 0.582
V6 0.755 0.022 33.913 *** 0.570
Mot V7 0.759 0.021 35.556 *** 0.576 0.829 0.618
V8 0.794 0.021 38.67 *** 0.630
V9 0.804 0.02 39.674 *** 0.646
Tir V10 0.729 0.024 30.893 *** 0.531 0.793 0.561
V11 0.703 0.025 28.015 *** 0.494
V12 0.811 0.022 37.551 *** 0.658
Con V13 0.723 0.023 31.578 *** 0.523 0.814 0.593
V14 0.799 0.021 38.987 *** 0.638
V15 0.786 0.021 37.127 *** 0.618
Cal V16 0.709 0.025 28.428 *** 0.503 0.797 0.567
V17 0.761 0.022 34.179 *** 0.579
V18 0.787 0.021 37.165 *** 0.619
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Vig vigour, Cof confidence, Mot motivation, Tir tireless, Con concentration, Cal calm.

*p < 0.05 **p < 0.01 ***p < 0.001.

Discriminant validity

Figure 1 illustrates the model of Athletic Mental Energy with six factors. The standardized inter-factor correlations are relatively low, all being below 0.85. These results provide support for the discriminant validity of the dimensions within the C-AMES scale.

Figure 1.

Figure 1

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Model of athletic mental energy with six factors.

The test-retest reliability of the C-AMES

To assess the reliability of the questionnaire data, we selected a sample of 72 participants. These individuals were chosen from 12 selected classes, with the first six students from each class, in order, completing the questionnaire. After an interval of 14 days, the participants completed the C-AMES questionnaire again for validation purposes. The intraclass correlation coefficient (ICC) was used to analyze the correlation between the scores of the two questionnaires. This analysis provided insights into the consistency and stability of the questionnaire data over time, serving as a measure of its reliability. The comparison revealed a significant positive correlation between the scores from the two administrations, with an ICC of 0.908, indicating high reliability of the questionnaire.

Discussion

In the context of Chinese adolescents, the concept and investigation of AME traits remain relatively novel. As far as the authors are aware, this study represents the first comprehensive exploration of the AME factor structure within the Chinese adolescent population. Therefore, the validation of the Chinese version of AMES (C-AMES) stands as a crucial cornerstone for further understanding the prevalence of AME traits among adolescent individuals in China. The development of C-AMES marks a significant step towards characterizing the mental energy of the Chinese population in the domain of sports and physical activity. In this study, we conducted a confirmatory examination of the factor structure of C-AMES. Building on prior research, the original version of AMES has been widely acknowledged for its reliability, validity, and stability19. Thus, we translated the English version of AMES into the Chinese version (C-AMES) to cater to the native Chinese-speaking population for adolescents in China.

The present study, following the confirmatory factor analysis of C-AMES, has revealed that when measuring the athletic mental energy of middle school students in Lanzhou, the Chinese version of AMES (C-AMES) demonstrates favorable performance in terms of both factor loadings and model fit. As a result, all the original questionnaire items were retained without any deletions. Considering that the age group of participants in this study is comparable to that of the original AMES participants and due to the robust model fit, high construct reliability, and discriminant validity observed in C-AMES, it can be inferred that C-AMES is well-suited for application among Chinese students.

This study employed a confirmatory approach to examine and validate the factor structure of C-AMES. One of the advantages of using Confirmatory Factor Analysis (CFA) is that it allows for the assessment of the validity of a measurement model based on the proposed theoretical framework. C-AMES consists of six factors, each comprised of three items. CFA provides a valuable method to assess the coherence between the theoretical construct and the observed variables, thus verifying the underlying structure of C-AMES.

Once the factor structure of C-AMES has been validated, it is essential to assess its structural validity. Structural validity refers to the extent to which a set of measurement items accurately reflects the underlying theoretical structure, essentially gauging the accuracy of measurement23. The structural validity of C-AMES primarily encompasses convergent validity and discriminant validity. Convergent validity examines the degree to which different items within the same factor are consistently related, while discriminant validity assesses the distinctiveness of each factor from others within the measurement model.

The average variance extracted (AVE) represents the mean of the squared factor loadings associated with each factor. Within this study, the AVE values range from 0.561 to 0.618 for different constructs. Furthermore, the composite reliability (CR) spans from 0.793 to 0.829 in this study, surpassing the recommended threshold of 0.60 proposed by28. This provides evidence for the robust convergent validity of the model29,30. This study also furnishes compelling evidence of discriminant validity, as the inter-factor correlations are below the recommended threshold of 0.85. The results of discriminant validity indicate that each factor within C-AMES maintains distinctiveness, avoiding substantial overlap with other factors. Moreover, each factor captures phenomena that are not captured by the other factors.

Additionally, in a recent study conducted in Thailand, researchers also validated the Thai version of the AMES (AMES-Thai)31. The results showed that, similar to the original AMES, no items were removed from the AMES-Thai. The measurement model indicated that the 6-factor, 18-item scale was satisfactory (χ2/DF = 149.76, CFI = 0.99, GFI = 0.97, RMSEA = 0.004, SRMR = 0.003). The CR for each subscale ranged from 0.57 to 0.80, and the AVE ranged from 0.48 to 0.6631. These findings are consistent with our study's results, suggesting that AMES has good structural validity and reliability across different cultural contexts, reliably measuring adolescents’ mental energy. The conclusions of the Thai study also indirectly support the reliability of our findings.

Nevertheless, it is important to acknowledge several limitations in this study. Firstly, the data collection was confined to Lanzhou, Gansu Province, China, which raises questions about the generalizability of C-AMES to middle school students in other regions of China. This limitation might restrict the broader applicability of the study findings beyond the specific region. Secondly, the entirety of the survey responses relied on participants' self-reports, lacking additional forms of corroborative evidence. Self-report data can be susceptible to self-report biases, potentially affecting the accuracy of the data. Lastly, participants might have been influenced by social desirability, leading them to provide answers that align with societal expectations32. As a countermeasure, we made efforts to encourage participants to provide truthful responses to mitigate this potential impact.

In this study, C-AMES has demonstrated excellent structural validity, confirming the six-factor structure consistent with previous AMES research. However, it remains crucial to further investigate the replicability of C-AMES among populations in different regions. Future researchers should also focus on validating the stability of C-AMES and AMES over time through longitudinal studies. Longitudinal measurement offers several advantages, including the ability to provide more comprehensive information than cross-sectional studies, enabling researchers to explore processes of change and variability, assess the degree of measurement invariance, and examine potential causal relationships33.

Conclusion

The C-AMES is a valuable tool for evaluating athletic mental energy among adolescents. Its six dimensions offer a nuanced perspective on various aspects of athletic mental energy in this context. Looking ahead, there are practical implications to explore. Future research could investigate its concurrent validity with established measures relevant to adolescent sports performance. Also, conducting invariance studies across demographics like age and types of sports involvement would enhance its usefulness. Given its relevance in adolescent sports psychology, the C-AMES is beneficial for both researchers and practitioners. Its multidimensional approach helps understand adolescents' athletic mental states, aiding in tailored interventions for performance and well-being. Hence, future studies focusing on adolescent sports, particularly in Chinese-speaking populations, could benefit from using the C-AMES for comprehensive insights and targeted interventions.

Supplementary Information

Supplementary Information. (242.3KB, pdf)

Author contributions

JW designed the study, interpreted the results, drafted and edited the manuscript, coordinated the study activities. GK and YCK designed the study, prepared the material, analyzed the data, interpreted the results, drafted and edited the manuscript. GK, YKC critically revised the draft of the manuscript. All authors reviewed and approved the manuscript.

Funding

The present study is free from any disputes regarding attribution and intellectual property rights. This research is funded by the Social Sciences and Humanities Research Grant, University of Guizhou (2024RW280) with the main title: “Research on the impact mechanism and intervention strategies of minors’ mental health”.

Data availability

The dataset used during the current study is available on reasonable request from the corresponding author.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-66931-z.

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Supplementary Materials

Supplementary Information. (242.3KB, pdf)

Data Availability Statement

The dataset used during the current study is available on reasonable request from the corresponding author.

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