Exploring the Role of Mental Toughness in Bone Mineral Content: A Preliminary Study

Bone mineral content (BMC), a measure of the mineral content within a person’s bones, is an important parameter in the assessment of bone health. Changes in BMC can be indicative of bone-related conditions. Dual-energy X-ray absorptiometry (DXA) is one of the most widely used and accurate methods for measuring BMC. Sex, age, race, and BMI are known to influence BMC. Physical activity is positively related to BMC levels. Mental toughness (MT) is conceptualized as a state-like psychological resource conducive to goal-oriented pursuits and is positively linked to physical activity outcomes. The relationship between MT and BMC has not been explored. PURPOSE: To investigate the isolated effect of MT on BMC after eliminating the confounding effects of sex, age, race, and BMI. METHODS: A total of 95 individuals participated in the study across two study sites. The sample (Mage = 34.57, SD = 15.87) was predominantly White (64%), normal weight/overweight (MBMI = 25.96, SD = 4.88) males (54%). DXA scans were performed on calibrated scanners using standard procedures. MT was assessed via the Mental Toughness Index (MTI). To reduce measurement error, the MTI was administered twice, separated by a two-week interval. A linear regression model was used to analyze the relationship between BMC and the average of the two MTI scores, while controlling for sex, age, race, and BMI in MATLAB (R2023a). A Cohen’s d for MT and BMC was additionally conducted. RESULTS: The linear regression model was BMC ~ 1 + Sex + Age + Race + BMI + MT. The overall regression was statistically significant (R2 = 0.183, F(94, 88) = 2.78, p = .012). MT was found to significantly predict BMC (β = 0.093, p = .008, d = 2.7). CONCLUSION: The findings underscore the statistical significance of MT as a predictor of BMC, even when accounting for the influence of sex, age, race, and BMI. The effect size points to the practical significance of this relationship, suggesting that individuals with higher MT levels may exhibit greater BMC. Future investigations should consider incorporating demographic covariates to gain deeper insights into these relationships and conduct interventional studies to identify potential underlying mechanisms (e.g., how trainable MT could be linked, to some degree, with an increase in BMC)

The Effects of Different Prolonged Aerobic Exercise Modalities on Physiological Components of Cardiovascular Drift

Cardiovascular Drift (CD) is a physiological phenomenon in which heart rate and VO2 increase in order to maintain cardiac output as the exercise intensity remains the same. Current understanding of CD indicates that CD is caused by a loss of fluids in combination with a reduced ventricular filling time. Different exercise modalities, such as steady state exercise (SSE) and high intensity interval exercise (HIIE) stress the cardiovascular system differently and cause different adaptations. Currently, no research has been conducted observing components (VO2, HR, and RER) of CD in SSE and HIIE. PURPOSE: To determine if HIIE or SSE alters physiological components of CD in healthy aerobically fit individuals. METHODS: Seven aerobically fit individuals (Age 38.14±16.9 yrs.; Ht 172.21 ±10.1 cm.; Wt 72 ± 12.9 kg.; BF% 20.7 ±7.4; VO2 38.79 ± 10.6 ml/kg/min-1) completed a randomized crossover design which consisted of 45 minutes of SSE and HIIE treadmill running to observe differences in VO2, HR, and RER. Participants completed a sing VO2 max ramp protocol treadmill test, which was used to calculate 70%, 90%, and 40% of VO2 reserve (VO2R). The SSE session consisted of 45 minutes of treadmill running at 70% VO2R. The HIIE session consisted of nine 5-minute stages of 3 minutes at 90% VO2R and 2 minutes at 40% VO2R. Data was analyzed via 2 (condition) x 10 (time) repeated measures ANOVA and paired sample t-tests to determine changes in VO2, heart rate (HR), and respiratory exchange ratio (RER). All analyses were performed using SPSS (v.29.01). RESULTS: Significant differences were observed for VO2 between conditions (p=.005), time (p\u3c .001), and condition by time (p \u3c.001). Additionally, HR demonstrated significance between time (p\u3c.001). RER did not have any significant differences between conditions. CONCLUSION: There are significant differences in VO2 values between exercise modalities. Subsequently, as time progressed there were significant differences in VO2 and HR between exercise conditions. Only VO2 had significant differences in time and condition. These differences indicate that different exercise modalities of equal workload elicit varying oxygen utilization, resulting in a drift in oxygen consumption