Values Of Variables Research Articles

Algebraic thinking profile of pre-service teachers in solving mathematical problems in relation to their self-efficacy

Algebraic thinking is a person’s ability to understand, analyze, and solve problems using algebraic concepts to simplify statements and find solutions. Currently, many prospective teachers still lack proficiency in applying algebraic thinking skills. Self-efficacy is one of the factors that influences algebraic thinking ability. This study aims to reveal the relationship between self-efficacy and algebraic thinking skills in pre-service mathematics teachers. In the context of solving math problems, especially algebraic ones, algebraic thinking skills are crucial. Using a qualitative method with a descriptive approach, the study employed interview guidelines, questionnaires, and tests as instruments. The results show a clear correlation between the level of self-efficacy and algebraic thinking ability. Pre-service teachers with high self-efficacy can effectively evaluate information, use symbols to represent variables, and solve algebraic equations well. They are also able to determine the values of unknown variables. On the other hand, participants with moderate self-efficacy can interpret and communicate information but are less systematic in selecting problem-solving steps that involve abstraction. Participants with low self-efficacy struggle to interpret information and cannot explain the relationship between the information in the problem and the question asked, leading to incorrect solutions. The conclusion of this study is that the higher the level of self-efficacy, the better one’s algebraic thinking ability. This indicates the importance of enhancing students’ self-efficacy to support more effective algebra learning.

Duration of insomnia and success expectancy predict treatment outcome of iCBT for insomnia

IntroductionIdentifying prognostic factors of treatment outcome may assist in customizing an intervention to a patient's needs. Hence, we conducted a secondary analysis of data from a randomized controlled trial to investigate the effectiveness of an internet-based cognitive behavioral therapy for insomnia (iCBT-I) to find patient characteristics that may predict the change of insomnia severity after treatment.Materials and methodsIn this exploratory analysis involving 94 chronic insomnia patients, we examined the predictive value of several self-reported measures, medical history, and sociodemographic variables to psychological distress with separate linear regression models. The main outcome was the Insomnia Severity Index score improvement from pre- to post-treatmentResultsThe study found that duration of insomnia, b (SE) = −0.02 (0.01), p = 0.01, and attitudes about the expected treatment success, b (SE) = 0.80 (0.27), p = 0.004, were predictors of a better outcome. Moreover, a better outcome was associated with a lower level of the following traits: attention seeking, b (SE) = −1.06 (0.51), p = 0.04; grandiosity, b (SE) = −1.50 (0.57), p = 0.01; distractibility, b (SE) = −1.57 (0.75), p = 0.04; and rigid perfectionism, b (SE) = −1.32 (0.65), p = 0.05.ConclusionOur results suggest that iCBT-I might be particularly beneficial for patients with higher expectations from the therapy and those who have a shorter duration of insomnia. Some pronounced personality traits, such as attention seeking, grandiosity, distractibility, and rigid perfectionism, may predict worse outcomes. However, because this was a post-hoc analysis, our results must be considered exploratory and verified in further studies.Clinical trial registrationhttps://clinicaltrials.gov/study/NCT04300218?cond=NCT04300218&rank=1, Identifier NCT04300218.

Extending the Scope of Instrumental Variable Methods

Abstract Since Philip Wright’s (1928) proposal of the linear instrumental variables (IV) estimator the scope of application of IV models has greatly expanded. There are now nonlinear IV models in use with both additive and nonadditive latent variables, employing both semiparametric and nonparametric specifications. A notable feature of Wright’s linear IV estimator is that it is applicable to incomplete models that leave the genesis of endogenous explanatory variables unspecified. On the other hand, inversion of the linear model enables the value of unobservable heterogeneity to be expressed as a function of observable variables. Only recently has the application of incomplete IV models been extended to cases in which this inversion produces a non-singleton set of values of unobservable variables. This situation arises in many models such as those featuring discrete choice, counts, or censored outcomes, or when there are multiple sources of heterogeneity as in random coefficient models, or when economic considerations result in inequality restrictions on values taken by observed and unobserved variables. This paper provides an introduction to the methods set out for analyzing such generalized instrumental variable (GIV) models in Chesher and Rosen (2017). An illustrative example is provided in which an outcome is determined by a random coefficients linear model with an endogenous explanatory variable and instrumental variable exclusion and independence restrictions.

Hybrid evolutionary algorithms (hybrid-GAPSO) based optimization of MIG welding process

MIG welding is a modern part of advanced welding process. In this article, the mathematical modeling by ANN and parametric optimization of MIG welding joining process of cast iron has been propounded using soft computing hybrid-GAPSO. The article also shows the best model using NN basis of fittest with experimental result, computational time, convergence speed and finally RMSE obtained from cross-validation. In this research, the optimal value of the input variables obtained by hybrid-HGAPSO so that output variables hardness (HA) will be maximum & surface roughness (SR) and width of breadth thickness (WOBT) will be minimum, has been illustrated. In this experimental analysis minimized RMSE of 1.15%, 1.433%, and 1.6678% for HA, WOBT and SR are accomplished respectively by HGAPSO-ANN.

On probabilistic and causal reasoning with summation operators

Abstract Ibeling et al. (2023, Annals of Pure and Applied Logic, 103339) axiomatize increasingly expressive languages of causation and probability, and Mossé et al. (2024, The Review of Symbolic Logic, 17, 106–131) show that reasoning (specifically the satisfiability problem) in each causal language is as difficult, from a computational complexity perspective, as reasoning in its merely probabilistic or ‘correlational’ counterpart. Introducing a summation operator to capture common devices that appear in applications—such as the $do$-calculus of Pearl (Causality. Cambridge University Press, 2009) for causal inference, which makes ample use of marginalization—van der Zander et al. (The hardness of reasoning about probabilities and causality. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI-23, E. Elkind, ed., pp. 5730–5738. International Joint Conferences on Artificial Intelligence Organization. Main Track. 2023) extend these earlier complexity results to causal and probabilistic languages with marginalization. We complete this extension, fully characterizing the complexity of probabilistic and causal reasoning with summation, demonstrating that these again remain equally difficult. Surprisingly, allowing free variables for random variable values results in a system that is undecidable, so long as the ranges of these random variables are unrestricted. We finally axiomatize these languages featuring marginalization (or more generally summation), resolving open questions posed by Ibeling et al. (2023, Annals of Pure and Applied Logic, 103339).

The Influence Of Strategic Planning, Strategic Implementation With Stakeholders Support On The Performance Of Regional Drinking Water Companies In Region II

The purpose of this study is to analyze the influence of strategic planning on company performance. To analyze the influence of strategic planning on strategy implementation. To analyze the influence of stakeholder support on strategy implementation. To analyze the influence of strategy implementation on company performance. This research is a quantitative research, with a survey approach. Through the survey, not all individuals are observed but only take samples from the population. The location of this research is PDAM Region II. The sample in this study was 100 respondents using cluster random sampling method. Data analysis method and hypothesis testing with Structural Equation Model (SEM). In testing the model using SEM, there are seven steps that must be taken. Results of the analysis as follows: the value of strategic planning variables on the performance of companies with a p-value less than the lowest average. Variable value of strategic planning to the implementation of the strategy has a p-value less than the lowest average value. The value of the variable support of stakeholders on the implementation of the strategy with p-value less than the lowest average. The value of the variable implementation of the strategy on the performance of companies with a p-value less than the value of the lowest average. From the analysis, it can be concluded strategic planning affect the company's performance, strategic planning affect the implementation of the strategy, the support of influential stakeholders towards the implementation of the strategy and implementation of strategies affect the company's performance.

Pengaruh Promosi dan Citra Merek Terhadap Keputusan Pembelian pada Bengkel Mobil Garasi-In

The purpose of the study was to determine the extent to which the promotion and brand image of the car repair shop influence purchasing decisions. The study used a quantitative method by distributing questionnaires to 97 respondents via Google Form. Data includes instrument analysis to assess validity and reliability, classical assumption tests such as normality tests, heteroscedasticity tests, and multicollinearity tests, hypothesis tests such as t-tests and F-tests, multiple linear regression analysis, and calculating the coefficient of determination. This provides results that promotion and brand image have a significant influence on purchasing decisions. Producing a contribution value of promotion variables and brand image variables to purchasing decisions of 68.8% to purchasing decisions..

The Influence of The 7P Marketing Mix Strategy and Digital Marketing on Car Purchasing Decisions at PT. Hadji Kalla Toyota Palopo Branch

Marketing mix helps companies design marketing strategies by paying attention to product, price, distribution, and promotion, while digital marketing uses digital technology to reach consumers directly, both work together to create brand awareness, influence consumer perceptions, and facilitate the purchasing process, influencing purchasing decisions consumers positively. This research aims to determine the influence of 7p marketing mix and digital marketing on car purchasing decisions at Pt. Hadji Kalla Toyota Palopo Branch, either partially or simultaneously. The research approach used in this research is a quantitative approach, namely a direct survey using data collection through questionnaires and observation. The research results show that (1) Marketing mix has no effect on purchasing decisions, with a calculated t value of the marketing mix variable of 1.201 < t table value (1.678) and a sig. 0.312 > 0.05. (2) Digital marketing has a significant positive effect on purchasing decisions, with a calculated t value for the digital marketing variable of 2.553 > t table value of 1.678 and a sig value. 0.014 < 0.05. And (3) Marketing mix and digital marketing simultaneously (together) have a significant effect on purchasing decisions with a calculated F value of 20.233 and a significance of 0.000 < 0.05.

Effect of scapular and shoulder strengthening exercises on prevention of upper limb lymphedema – a pilot study

Background. The most frequent type of cancer among women is breast cancer. According to the report published by Indian Council for Medical Research (ICMR, 2019), there are 1.5 lakh new instances of breast cancer nationwide and around 70,000 people in India die from breast cancer each year. Secondary lymphedema (SL) following breast cancer surgery can occur due to the removal of lymph nodes during breast cancer surgery. Objective. This pilot study was done with the objectives to improve the strength of scapular and shoulder muscles, increase the shoulder range of motion, prevent the development of upper limb lymphedema, to reduce shoulder pain and disability and to improve the quality of life among women who underwent breast cancer surgery. Methodology. Ten patients with a mean age of 49.9 ± 8.6 and mean Body mass index (BMI) of 28.4 ± 3.9 were included according to the inclusion and exclusion criteria. They were randomized into interventional group (Group A n = 5) and conventional group (Group B n = 5). The interventional group performed the routine exercises prescribed along with the scapular and shoulder muscle strengthening exercises, while the conventional group performed only the routine exercises for 12 weeks. Result. The mean change score values of the outcome variables of both the groups were analyzed using Independent ‘t’ test. Discussion. Arm circumference measurement, shoulder pain, disability and quality of life measures showed significant difference between groups at p < 0.05. Shoulder range of motion, muscle strength and arm volumetry did not show much difference between groups indicating the need for long term continuation of the exercises to produce improvement in those parameters. Conclusion. Long term effect of strengthening exercises will have an effect on improvement of shoulder range of motion, arm volume and muscle strength among the women following breast cancer surgery. Strengthening exercises should be recommended as a part of breast cancer rehabilitation protocol to prevent secondary lymphedema and other postsurgical complications.

The Influence of Experience Value, Destination Image, Destination Service Utility on Tourist Loyalty with Tourist Engagement as an Intervening Variable and Heritage Value as a Moderating Variable in Tourist Villages on the Island of Java.

This research is expected to contribute to a deeper understanding of the dynamics of tourist loyalty in the context of tourist villages in Java, by considering various factors that influence it, such as Experience Value, Destination Image, Destination Service Utility, Tourist Loyalty, Tourist Engagement, and Heritage Value as Variable Intervening. This research model was analyzed using SmartPLS. Data were collected by distributing surveys to 230 tourists visiting tourist villages in Java Island. The data collection technique used a sample non- probability. The results of the study indicate that most of the hypotheses proposed are accepted, it is proven that there are eight hypotheses that are proven to have a significant direct relationship between variables, and three hypotheses do not have a significant relationship. The research model tested only shows the influence of variables that support sustainable growth, with these eight variables. Further research is expected to develop with other variables such as tourism village management, tourism village improvement strategies, tourism village development. This study proves that tourism villages can use research results to identify opportunities and threats that may arise from factors Destination Service Utility, in improving tourism development.

RETRACTION: Association of biochemical markers with the severity of pre-eclampsia.

A. M. Maged, G. Aid, N. Bassiouny, D. S. Eldin, S. Dahab, and N K. Ghamry, "Association of Biochemical Markers With the Severity of Pre-Eclampsia," International Journal of Gynecology & Obstetrics 136, no. 2 (2017): 138-144, https://doi.org/10.1002/ijgo.12029. The above article, published online on 16 November 2016 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor-in-Chief, Michael Geary; the International Federation of Gynecology and Obstetrics; and John Wiley & Sons Ltd. The retraction has been agreed upon following an investigation into concerns raised by a third party regarding improbable values of free categorical variables in Table1; the statistical significance in Table1, 2, 3 and 5, where the P-values could not be reproduced using the information presented in the article; and inconsistent information on the number of stillbirth and stillborn neonates in Table5. The authors were informed about the concerns, but they did not wish to cooperate with the investigation and were not able to provide the raw data as the study was conducted more than 5 years ago and the original data was no longer retained according to institutional policies. The authors' institute was also contacted, but they remained unresponsive. In the absence of a satisfactory explanation or supporting raw data, the editors have determined that the data for this study cannot be considered reliable and decided to retract the article.

Research on Predicting the Winning Rate of Momentum Tennis Athletes

In tennis, "momentum" usually refers to the momentum or trend formed by a series of events (such as consecutive scoring) in a game, which can have a significant impact on the outcome of the game. After gaining motivation, players or teams often exhibit higher morale and confidence, and are more likely to win consecutive points or games. Specifically, momentum may be reflected in indicators such as continuous scores and break points. In a game, the server is usually more likely to win points, so evaluating momentum requires considering the influence of various factors. The paper believe that athletes are primarily influenced by the psychological impact of momentum, but psychological factors are also an abstract concept. Therefore, the paper have turned our attention to the various behaviors of athletes on the field. Therefore, the paper used five indicators to quantify the momentum score of athletes. To address the coach's concerns, the paper use random testing and correlation analysis to verify the statistical significance of attempting to score and win games, rather than random events. This article uses learning algorithms such as decision tree models to predict the value of target variables at turning points based on feature data. Analyze the contribution of each feature to advantage transformation and ultimately identify the relevant factors that affect advantage transformation.

Methodological considerations in calculating the minimal clinically important change score for the core outcome measures index (COMI): insights from a large single-centre spine surgery registry.

The Minimal Clinically Important Change (MCIC) is used in conjunction with Patient-Reported Outcome Measures (PROMs) to determine the clinical relevance of changes in health status. MCIC measures a change within the same person or group over time. This study aims to evaluate the variability in computing MCIC for the Core Outcome Measure Index (COMI) using different methods. Data from a spine centre in Switzerland were used to evaluate variations in MCIC for the COMI score. Distribution-based and anchor-based methods (predictive and nonpredictive) were applied. Bayesian bootstrap estimated confidence intervals. From 27,003 cases, 9821 met the inclusion criteria. Distribution-based methods yielded MCIC values from 0.4 to 1.4. Anchor-based methods showed more variability, with MCIC values from 1.5 to 4.9. Predictive anchor-based methods also provided variable MCIC values for improvement (0.3-2.4), with high sensitivity and specificity. MCIC calculation methods produce varying values, emphasizing careful method selection. Distribution-based methods likely measure minimal detectable change, while non-predictive anchor-based methods can yield high MCIC values due to group averaging. Predictive anchor-based methods offer more stable and clinically relevant MCIC values for improvement but are affected by prevalence and reliability corrections.

Neighborhood environment and falls: a longitudinal Japan gerontological evaluation study

Abstract Background Older adults who experience falls are at a high risk of injury and death and require long-term care. Notably, the risk of falls varies among different neighborhood environments. No prior longitudinal studies have examined the association between falls and neighborhood environment at the community level. Identifying such associations will help prevent people falling by improving their neighborhood environment. Herein, we aimed to identify neighborhood environmental factors associated with falls among older adults in Japan. Methods We analyzed the data of 27,346 older adults living in 416 communities who participated in the 2010, 2013, and 2016 Japan Gerontological Evaluation Study surveys. The dependent variable was the occurrence of falls in 2016, and the explanatory variables were the mean scores of each of eight community-level neighborhood environment variables, categorized into tertiles (high, middle, and low groups) in 2013. Our model was adjusted for covariates (e.g., sex, age, and socioeconomic status) using the variables from 2010. A multilevel Poisson regression analysis was performed to obtain the relative risk (RR) and 95% confidence interval (CI) between the neighborhood environment and falls. Missing variable values were supplemented by multiple imputations. Results Older adults living in neighborhood environments with more parks or foot paths suitable for exercise or walking had a lower risk of falling after 3 years compared to those living in neighborhood environments with fewer parks or foot paths (RR: 0.89; CI: 0.80-0.99). For the variable ‘locations difficult for walking, such as hills or steps’, older adults in the middle group had a lower risk of falling than those in the low group (RR: 0.94; CI: 0.88-0.99). Conclusions Parks or foot paths are important environmental improvements that may prevent falls. Having hills or steps in the neighborhood could be beneficial when properly integrated into the environment. Key messages • Older adults with access to parks, footpaths, and challenging terrains suitable for exercise and walking, had a lower risk of falling. • These findings could be applied in urban designs to prevent falls among older adults.

Evaluation of the Effect of Antibacterial Toothpastes Containing Chlorhexidine and Amine Fluoride on Oral Flora in Patients Undergoing Orthodontic Treatment-A Randomised Controlled Trial.

To compare the efficacy of chlorhexidine (CHX) and amine fluoride (AF) toothpastes on oral flora in fixed orthodontic treatment patients. Thirteen patients were given toothpaste containing AF, and 12 patients were given toothpaste containing CHX. Microbial and periodontal records were taken before, 1 week, and 5 weeks after the bonding procedure. Gingival index (GI), plaque index (PI), and bleeding on probing (BOP) values were recorded by the same expert calibrated before the study. Biofilm samples were taken, and then colony counts of the samples were evaluated. Whether the variable values obtained in the groups at the time of measurement were different was examined by Nonparametric Analysis of Longitudinal Data in Factorial Experiments-Nonparametric Tests for the F1_LD_F1 design for longitudinal data. Gender distribution was similar in the study groups (χ2 = 1.944; p = 0.163). The mean age of the patients did not differ in the groups (t = 0.502; p = 0.620). In general, the variable values analysed within the scope of the study did not show significant differences between groups and time (p > 0.05). When the pairwise interactions were analysed, it was found that there was a significant difference only for PI values (F = 3.411; p = 0.035). While there were no significant differences observed in BOP, GI, and S. mutans levels and changes in IgA and IgE values between toothpastes containing CHX and AF, the PI index of CHX-containing toothpastes exhibited a notably lower level. Both AF- and CHX-containing toothpastes can be used for managing biofilm, controlling bacteria, and minimising gingivitis in subjects undergoing fixed orthodontic treatment.

Constructing a model of the axis form in a S-shaped riser of a cultivator paw

When cultivating the soil, a force of resistance to the movement of cultivator paw acts on it. It has a variable value and causes a moment of force applied to the riser of the paw. Under the action of the moment, the elastic axis of the riser changes its shape. This affects the position of the paw in the soil. The form of an S-shaped riser whose elastic axis consists of two circle arcs has been considered in this study. During cultivator operation, one part of the riser bends, increasing the curvature of the elastic axis, and the other, on the contrary, unbends, that is, its curvature decreases. The modeling of the shape of the elastic axis of the paw riser is based on the theory of resistance of materials, according to which the curvature of the elastic axis of the cantilevered band is directly proportional to the applied moment and inversely proportional to its stiffness. If the shape of the cross-section of the riser along its entire length is unchanged and the properties of the metal are also the same, then the stiffness is constant. In the case of small deflections of the band, the linear theory of bending is used, but the deflections in the riser are significant, so the nonlinear theory has been used for this case. At the same time, it is taken into account that the elastic axis of the riser already has an initial curvature, the sign of which changes after passing through the point of connection of the component arcs. To model the shape of the elastic axis of the S-shaped paw riser, the deformation of the arcs of the circles that form this paw was calculated separately. Numerical integration methods were used to find the shape of the deformed elastic axes of both parts of the riser. They were connected into a whole and a deformed elastic axis of the S-shaped riser was obtained. Two variants of the riser with different lengths of their elastic axis, but the same height and the same angle of entry into the soil, were considered. The combination of the component arcs of the riser shows that, under the action of the same force, the deviation from the specified movement depth for one riser is 2 cm, and for the other – 4 cm.

Asymmetric intrinsic charm in the nucleon and its implications for the D0 production in the LHCb p+Ne20 fixed-target experiment

Recent results indicate that charm quarks are intrinsic components of the proton wave function, and that the charm and anticharm distributions for a given value of the Bjorken-x variable can be different. In this paper, we will investigate the impact of this asymmetric intrinsic charm on the production of D0 and D¯0 mesons for fixed target p+Ne20 collisions at the LHCb. In our calculations, we include the contribution of the gluon-gluon fusion, gluon-charm and recombination processes and assume distinct models for the treatment of the intrinsic charm component. We demonstrate that the presence of an intrinsic charm improves the description of the current data for the rapidity and transverse momentum distributions of D mesons. However, such models are not able to describe the LHCb data for the D0−D¯0 asymmetry at large transverse momentum, which point out that the description of the intrinsic charm needs to be improved and/or new effects should be taken into account in the production of heavy mesons at forward rapidities in fixed-target collisions. Published by the American Physical Society 2024

Pengaruh Waktu Aerasi terhadap Peningkatan Efisiensi Penghilangan Amonia di Air Lindi pada Sistem Ammonia Stripper

Talang Gulo Final Disposal Site (FDS) has a Leachate Treatment Plant (LTP) equipped with denitrification and nitrification facilities which function to reduce the concentration of ammonia (NH3) in leachate according to predetermined environmental quality standards. Research samples were taken in the form of leachate using the grab sampling method in accordance with SNI 6989.59:2008. The results of the research showed that the aeration time for the ammonia stripper of 3 hours, 6 hours and 12 hours both gave the highest value for the ammonia stripper efficiency percentage variable. The highest ammonia removal efficiency is aeration time of 12 hours. However, if we look at the operating efficiency of the ammonia stripper, the removal of ammonia by using an aeration time of 12 hours does not provide a significant improvement when compared to a treatment with an aeration time of 6 hours. This means that the operating time is 6 hours faster, the 6 hour variation can provide an ammonia removal efficiency of more than 90%

Applying survey weights to ordinal regression models for improved inference in outcome-dependent samples with ordinal outcomes.

Researchers often use outcome-dependent sampling to study the exposure-outcome association. The case-control study is a widely used example of outcome-dependent sampling when the outcome is binary. When the outcome is ordinal, standard ordinal regression models generally produce biased coefficients when the sampling fractions depend on the values of the outcome variable. To address this problem, we studied the performance of survey-weighted ordinal regression models with weights inversely proportional to the sampling fractions. Through an extensive simulation study, we compared the performance of four ordinal regression models (SM: stereotype model; AC: adjacent-category logit model; CR: continuation-ratio logit model; and CM: cumulative logit model), with and without sampling weights under outcome-dependent sampling. We observed that when using weights, all four models produced estimates with negligible bias of all regression coefficients. Without weights, only stereotype model and adjacent-category logit model produced estimates with negligible to low bias for all coefficients except for the intercepts in all scenarios. In one scenario, the unweighted continuation-ratio logit model also produced estimates with low bias. The weighted stereotype model and adjacent-category logit model also produced estimates with lower relative root mean square errors compared to the unweighted models in most scenarios. In some of the scenarios with unevenly distributed categories, the weighted continuation-ratio logit model and cumulative logit model produced estimates with lower relative root mean square errors compared to the respective unweighted models. We used a study of knee osteoarthritis as an example.

Fine Tuning ECG Interpretation for Young Athletes: ECG Screening Using Z-score-based Analysis

BackgroundElectrocardiograms (ECGs) in athletes commonly reveal findings related to physiologic adaptations to exercise, that may be difficult to discern from true underlying cardiovascular abnormalities. North American and European societies have published consensus statements for normal, borderline, and abnormal ECG findings for athletes, but these criteria are not based on established correlation with disease states. Additionally, data comparing ECG findings in athletes to non-athlete control subjects are lacking. Our objective was to compare the ECGs of collegiate athletes and non-athlete controls using Z-scores for digital ECG variables to better identify significant differences between the groups and to evaluate the ECG variables in athletes falling outside the normal range.MethodsValues for 102 digital ECG variables on 7206 subjects aged 17–22 years, including 672 athletes, from Hawaii Pacific Health, University of Hawaii, and Rady Children’s Hospital San Diego were obtained through retrospective review. Age and sex-specific Z-scores for ECG variables were derived from normal subjects and used to assess the range of values for specific ECG variables in young athletes. Athletes with abnormal ECGs were referred to cardiology consultation and/or echocardiogram.ResultsAthletes had slower heart rate, longer PR interval, more rightward QRS axis, longer QRS duration but shorter QTc duration, larger amplitude and area of T waves, prevalent R’ waves in V1, and higher values of variables traditionally associated with left ventricular hypertrophy (LVH): amplitudes of S waves (leads V1-V2), Q waves (V6, III) and R waves (II, V5, V6). Z-scores of these ECG variables in 558 (83%) of the athletes fell within − 2.5 and 2.5 range derived from the normal population dataset, and 60 (8.9%) athletes had a Z-score outside the − 3 to 3 range. While 191 (28.4%) athletes met traditional voltage criteria for diagnosis of LVH on ECG, only 53 athletes (7.9%) had Z-scores outside the range of -2.5 to 2.5 for both S amplitude in leads V1-V2 and R amplitude in leads V5-6. Only one athlete was diagnosed with hypertrophic cardiomyopathy with a Z-score of R wave in V6 of 2.34 and T wave in V6 of -5.94.ConclusionThe use of Z-scores derived from a normal population may provide more precise screening to define cardiac abnormalities in young athletes and reduce unnecessary secondary testing, restrictions and concern.