Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in Mountains
<i>Background and Objectives</i>: Accurate hiking time estimate is crucial for outdoor activity planning, especially in mountainous terrains. Traditional mountain signage and online platforms provide generalized hiking time recommendations, often lacking personalization. This study aims...
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MDPI AG
2025-01-01
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| Online Access: | https://www.mdpi.com/1648-9144/61/1/115 |
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| author | Marco Vecchiato Nicola Borasio Emiliano Scettri Vanessa Franzoi Federica Duregon Sandro Savino Andrea Ermolao Daniel Neunhaeuserer |
| author_facet | Marco Vecchiato Nicola Borasio Emiliano Scettri Vanessa Franzoi Federica Duregon Sandro Savino Andrea Ermolao Daniel Neunhaeuserer |
| author_sort | Marco Vecchiato |
| collection | DOAJ |
| description | <i>Background and Objectives</i>: Accurate hiking time estimate is crucial for outdoor activity planning, especially in mountainous terrains. Traditional mountain signage and online platforms provide generalized hiking time recommendations, often lacking personalization. This study aims to evaluate the variability in hiking time estimates from different methods and assess the potential of a novel algorithm, MOVE, to enhance accuracy and safety. <i>Materials and Methods</i>: A cross-sectional analysis was conducted using data from 25 Italian loop trails selected via the Wikiloc platform, considering user-uploaded GPS data from at least 20 users per trail. Real-world hiking times were compared with estimations from Komoot, Outdooractive, mountain signage, and the MOVE algorithm, which incorporates individualized biological and trail characteristics. <i>Results</i>: Significant discrepancies were observed between actual hiking times and estimates from Komoot (ΔWK: −48.92 ± 57.16 min), Outdooractive (ΔWO: −69.13 ± 58.23 min), and mountain signage (ΔWS: −29.59 ± 59.90 min; all <i>p</i> < 0.001). In contrast, MOVE showed no statistically significant difference (ΔWM: −0.27 ± 65.72 min; <i>p</i> = 0.278), providing the most accurate predictions. <i>Conclusions</i>: Current hiking time estimation methods show substantial variability and inaccuracy, which may pose safety risks. MOVE demonstrated superior accuracy, offering personalized hiking time predictions based on user-specific data and trail characteristics. Integrating such advanced tools into outdoor activity planning could enhance safety and accessibility, particularly for individuals with chronic conditions. Further studies should explore integrating real-time health data to refine these tools. |
| format | Article |
| id | doaj-art-502f3e46244d4ff5b9861e856f469b5e |
| institution | Kabale University |
| issn | 1010-660X 1648-9144 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Medicina |
| spelling | doaj-art-502f3e46244d4ff5b9861e856f469b5e2025-01-24T13:40:40ZengMDPI AGMedicina1010-660X1648-91442025-01-0161111510.3390/medicina61010115Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in MountainsMarco Vecchiato0Nicola Borasio1Emiliano Scettri2Vanessa Franzoi3Federica Duregon4Sandro Savino5Andrea Ermolao6Daniel Neunhaeuserer7Sports and Exercise Medicine Division, Department of Medicine, University of Padova, Via Giustiniani 2, 35128 Padova, ItalySports and Exercise Medicine Division, Department of Medicine, University of Padova, Via Giustiniani 2, 35128 Padova, ItalySports and Exercise Medicine Division, Department of Medicine, University of Padova, Via Giustiniani 2, 35128 Padova, ItalySports and Exercise Medicine Division, Department of Medicine, University of Padova, Via Giustiniani 2, 35128 Padova, ItalySports and Exercise Medicine Division, Department of Medicine, University of Padova, Via Giustiniani 2, 35128 Padova, ItalyDepartment of Medicine, University of Padova, Via Giustiniani 2, 35128 Padova, ItalySports and Exercise Medicine Division, Department of Medicine, University of Padova, Via Giustiniani 2, 35128 Padova, ItalySports and Exercise Medicine Division, Department of Medicine, University of Padova, Via Giustiniani 2, 35128 Padova, Italy<i>Background and Objectives</i>: Accurate hiking time estimate is crucial for outdoor activity planning, especially in mountainous terrains. Traditional mountain signage and online platforms provide generalized hiking time recommendations, often lacking personalization. This study aims to evaluate the variability in hiking time estimates from different methods and assess the potential of a novel algorithm, MOVE, to enhance accuracy and safety. <i>Materials and Methods</i>: A cross-sectional analysis was conducted using data from 25 Italian loop trails selected via the Wikiloc platform, considering user-uploaded GPS data from at least 20 users per trail. Real-world hiking times were compared with estimations from Komoot, Outdooractive, mountain signage, and the MOVE algorithm, which incorporates individualized biological and trail characteristics. <i>Results</i>: Significant discrepancies were observed between actual hiking times and estimates from Komoot (ΔWK: −48.92 ± 57.16 min), Outdooractive (ΔWO: −69.13 ± 58.23 min), and mountain signage (ΔWS: −29.59 ± 59.90 min; all <i>p</i> < 0.001). In contrast, MOVE showed no statistically significant difference (ΔWM: −0.27 ± 65.72 min; <i>p</i> = 0.278), providing the most accurate predictions. <i>Conclusions</i>: Current hiking time estimation methods show substantial variability and inaccuracy, which may pose safety risks. MOVE demonstrated superior accuracy, offering personalized hiking time predictions based on user-specific data and trail characteristics. Integrating such advanced tools into outdoor activity planning could enhance safety and accessibility, particularly for individuals with chronic conditions. Further studies should explore integrating real-time health data to refine these tools.https://www.mdpi.com/1648-9144/61/1/115GPShikingmountainoutdoorphysical activitysafety |
| spellingShingle | Marco Vecchiato Nicola Borasio Emiliano Scettri Vanessa Franzoi Federica Duregon Sandro Savino Andrea Ermolao Daniel Neunhaeuserer Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in Mountains Medicina GPS hiking mountain outdoor physical activity safety |
| title | Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in Mountains |
| title_full | Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in Mountains |
| title_fullStr | Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in Mountains |
| title_full_unstemmed | Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in Mountains |
| title_short | Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in Mountains |
| title_sort | are suggested hiking times accurate a validation of hiking time estimations for preventive measures in mountains |
| topic | GPS hiking mountain outdoor physical activity safety |
| url | https://www.mdpi.com/1648-9144/61/1/115 |
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