(43) RECHARGING THE BATTERY: MONITORING DAILY RECOVERY AND READINESS PERCEPTIONS FOLLOWING A MULTI-MONTH WILDERNESS BACKPACKING TREK: A CASE STUDY

Purpose: Evaluate factors best suited to capture daily recovery and readiness fluctuations after a multi-month, self-supported backpacking wilderness trek.

Methods: An experienced backpacker (30.1yrs; 78.3kg; 179.1cm; 20.5% BF) completed a wilderness-based backpacking trek known as the Appalachian National Scenic Trail northbound thru-hike. The participant hiked 3,531km with an accumulated elevation gain of 99,643m over 139 days. Markers of acute recovery and readiness were recorded daily on-trail and throughout a 4-week post-trek recovery period using a research validated mobile application. To furnish specific time point comparisons, 3-d averages surrounding baseline (BASE), trek end (END), and 4-weeks post-trek (4-WK-POST) time points were calculated. Using the mobile application, ratings of perceived sleep quality (SQ), fatigue (FR), and mental energy (MER) were recorded daily upon waking using a visual analog scale along with self-reported sleep duration (SD). Heart rate variability (HRV) and resting heart rate (RHR) were also measured daily upon waking via photoplethysmography (PPG) employing the phone camera and the mobile application. Data trends were analyzed via percent change from BASE, while Pearson correlations, and cross correlation time series analyses assessed variable relationships.

Results: At END, MER dropped from BASE (BASE: 50.00; END: 26.00, Δ-48.00%), while FR increased (BASE: 60.00; END: 70.00, Δ16.67%). Both MER and FR improved over the post-trek period, yet remained below BASE at 4-WK-POST (MER: 32.67, Δ-34.67%; FR: 67.67, Δ12.78%). At END, HRV dropped (BASE: 119.33; END: 65.67, Δ-44.97%) and RHR increased (BASE: 55.87; END: 62.40, Δ11.69%) compared to BASE. HRV and RHR continued to worsen through 4-WK-POST (HRV: 57.67, Δ-51.68%; RHR: 64.10, Δ14.74%). SD was substantially shorter at END versus BASE (BASE: 10.15; END: 6.01, Δ-40.84%) and dropped further by 4-WK-POST (5.25, Δ-48.26%). SQ paralleled SD over the trek (BASE: 43.00; END: 28.00, Δ-34.88) but improved over BASE by 4-WK-POST (55.67, Δ29.46%). Over the 4-week post-trek period, SQ was positively correlated with MER (R=0.61; p< 0.01) and negatively correlated with FR (R=-0.64; p< 0.01). Cross correlation time series analysis revealed that both relationships were strongest on the day of rating. SD was not significantly correlated with MER (p=0.59) nor FR (p=0.049). Neither physiological outcome measure, HRV nor RHR, were significantly correlated with MER (HRV: p=0.66, RHR: p=0.72) nor FR (HRV: p=0.68, RHR: p=0.97).

Conclusion: Unsurprisingly, at trek END, autonomic and perceived markers of daily recovery and readiness all worsened from BASE. Post trek, improved SQ facilitated enhanced perceptions of recovery, despite continued deterioration of physiological outcome measures. Though markers of autonomic function may be better suited for monitoring long-term physiological stress, they fail to capture acute patterns of perceived recovery and readiness upon return from long-term expeditions. As a result, SQ may be better suited to capture daily fluctuations in acute recovery and readiness status than markers of autonomic function. PRACTICAL APPLICATIONS: Ratings of sleep quality may be used to monitor acute perceived recovery following extended duration events. To expedite perceived recovery and readiness, ultra-endurance participants should establish a consistent sleep routine that prioritizes quality upon reintegration to modern activities and lifestyle. 

Acknowledgements: None