Negative Mood States Increase Movement Path Deviations And Rate Of Exertion During Multiple Runs

Mood states may influence running biomechanics and exercise recovery, suggesting sustainable training requires both mental and physical support. PURPOSE: To determine if: 1) between-run differences (Δ) in Total Mood Disturbance (TMD) correlate with Δ in gait deviations (DEV) and Δ in perceived exertion (RPE) during prolonged runs and 2) correlations differ between running on consecutive days vs. every-other-day. METHODS: 19 experienced runners (10 M/9F; 30.1 ± 18.2 km/week) completed two run protocols at their first ventilatory threshold speed until RPE = 17: 3 consecutive days of running and 3 runs with 24-hour rest between runs. TDM was determined with the “today” version of the Profile of Mood States prior to each run. 3D ankle eversion (EVE), tibial internal rotation (TIR), knee abduction-adduction (ABD), and RPE were recorded every 5-min of each run. DEV in EVE, TIR, and ABD were calculated as described in Sumner et al., (2024). Change in RPE and DEV between first and last 5-min within each run were normalized by run duration (RPE/min, DEV/min). ΔTMD, ΔRPE/min, and ΔDEV/min were calculated as run 3 - run 1. High and low ΔTMD groups were created using a median split. Pearson correlations assess relationships between ΔTMD vs. ΔRPE/min and ΔTMD vs. ΔDEV/min. Two-sample t-tests compared ΔDEV/min and ΔRPE/min between high and low ΔTMD groups. RESULTS: Correlations between ΔTMD and ΔRPE/min for each protocol are reported in Figure 1. The high ΔTMD group had greater ΔRPE/min (p < 0.01) and greater TIR ΔDEV/min (p = 0.04) than the low ΔTMD group (mean ± 1SD: High = 0.003 ± 0.008 ΔRPE/min, 0.16 ± 0.61% ΔDEV/min; Low = -0.011 ± 0.008 ΔRPE/min, -0.75 ± 1.14% ΔDEV/min). ΔTMD was weakly correlated with EVE (r = 0.34) and ABD (r = -0.22) ΔDEV/min. Correlations with ΔTMD were lower for the rest protocol (ΔRPE/min: r = 0.44; all ΔDEV/min: r = -0.08 - +0.08). CONCLUSION: The relationships suggest that mood state monitoring may be useful in regulating running during intense running training. Supported by: Brooks Sports, Inc.

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Journal
Medicine & Science in Sports & Exercise
Published
2025-09-16
DOI
https://doi.org/10.1249/01.mss.0001160104.43200.f7
Primary Topic
Children's Physical and Motor Development
Type
article
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article

Negative Mood States Increase Movement Path Deviations And Rate Of Exertion During Multiple Runs

Allison H. Gruber, John S. Raglin, Marni G. Wasserman, Jennifer Sumner et al.
Medicine & Science in Sports & Exercise
Children's Physical and Motor Development
article

Negative Mood States Increase Movement Path Deviations And Rate Of Exertion During Multiple Runs

Allison H. Gruber, John S. Raglin, Marni G. Wasserman, Jennifer Sumner, Christian Ertel, James McDonnell
article en

Abstract

Mood states may influence running biomechanics and exercise recovery, suggesting sustainable training requires both mental and physical support. PURPOSE: To determine if: 1) between-run differences (Δ) in Total Mood Disturbance (TMD) correlate with Δ in gait deviations (DEV) and Δ in perceived exertion (RPE) during prolonged runs and 2) correlations differ between running on consecutive days vs. every-other-day. METHODS: 19 experienced runners (10 M/9F; 30.1 ± 18.2 km/week) completed two run protocols at their first ventilatory threshold speed until RPE = 17: 3 consecutive days of running and 3 runs with 24-hour rest between runs. TDM was determined with the “today” version of the Profile of Mood States prior to each run. 3D ankle eversion (EVE), tibial internal rotation (TIR), knee abduction-adduction (ABD), and RPE were recorded every 5-min of each run. DEV in EVE, TIR, and ABD were calculated as described in Sumner et al., (2024). Change in RPE and DEV between first and last 5-min within each run were normalized by run duration (RPE/min, DEV/min). ΔTMD, ΔRPE/min, and ΔDEV/min were calculated as run 3 - run 1. High and low ΔTMD groups were created using a median split. Pearson correlations assess relationships between ΔTMD vs. ΔRPE/min and ΔTMD vs. ΔDEV/min. Two-sample t-tests compared ΔDEV/min and ΔRPE/min between high and low ΔTMD groups. RESULTS: Correlations between ΔTMD and ΔRPE/min for each protocol are reported in Figure 1. The high ΔTMD group had greater ΔRPE/min (p < 0.01) and greater TIR ΔDEV/min (p = 0.04) than the low ΔTMD group (mean ± 1SD: High = 0.003 ± 0.008 ΔRPE/min, 0.16 ± 0.61% ΔDEV/min; Low = -0.011 ± 0.008 ΔRPE/min, -0.75 ± 1.14% ΔDEV/min). ΔTMD was weakly correlated with EVE (r = 0.34) and ABD (r = -0.22) ΔDEV/min. Correlations with ΔTMD were lower for the rest protocol (ΔRPE/min: r = 0.44; all ΔDEV/min: r = -0.08 - +0.08). CONCLUSION: The relationships suggest that mood state monitoring may be useful in regulating running during intense running training. Supported by: Brooks Sports, Inc.

Medicine & Science in Sports & ExerciseVol. 57(10S)
Minnesota Orthopedic Sports Medicine Institute (US), Indiana University Bloomington (US)
Openalex Percentile: Top 73%
Children's Physical and Motor Development
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