ArticlePloS one2017
Who uses running apps and sports watches? Determinants and consumer profiles of event runners' usage of running-related smartphone applications and sports watches.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it, 127 citations in OpenAlex.
- Inequalities in Exclusively Mobile Interventions Targeting Weight-Related Behaviors: Systematic Review of Observational Studies.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Pooled it
- The Effect of Wearable-Based Real-Time Feedback on Running Injuries and Running Performance: A Randomized Controlled Trial.The American journal of sports medicine · 2024Trial
- A Mixed-Methods Analysis of Motivational Dynamics and Strava Use in Active Club Runners.Behavioral sciences (Basel, Switzerland) · 2026Article
- Towards Accurate Reference Values for Heart Rate and Speed Zones by Aerobic Fitness and Sex in Long-Distance Runners.Sports (Basel, Switzerland) · 2026Article
- Exploring training-sleep characteristics and bidirectional lagged relationships in Chinese recreational runners: insights from a year-long wearable monitoring study.Frontiers in physiology · 2026Article
- How much running is too much? Identifying high-risk running sessions in a 5200-person cohort study.British journal of sports medicine · 2025Article
- Utilizing large-scale human mobility data to identify determinants of physical activity.Scientific reports · 2025Article
- Sports and exercise-related smartphone use is antagonistic to hedonic use in regular exercisers: A cross-sectional study examining the roles of exercise frequency and duration.Health science reports · 2024Article
- Exploring the Relationship between Running-Related Technology Use and Running-Related Injuries: A Cross-Sectional Study of Recreational and Elite Long-Distance Runners.Healthcare (Basel, Switzerland) · 2024Article
- A 0.05 m Change in Inertial Measurement Unit Placement Alters Time and Frequency Domain Metrics during Running.Sensors (Basel, Switzerland) · 2024Article
- Comparing Self-Reported Running Distance and Pace With a Commercial Fitness Watch Data: Reliability Study.JMIR formative research · 2024Article
- Predicting Tissue Loads in Running from Inertial Measurement Units.Sensors (Basel, Switzerland) · 2023Article
- Anthropometric profiles and body composition of male runners at different distances.Scientific reports · 2023Article
- Differences in race history by distance of recreational endurance runners from The NURMI Study (Step 2).Scientific reports · 2023Article
- LEAN: Real-Time Analysis of Resistance Training Using Wearable Computing.Sensors (Basel, Switzerland) · 2023Article
- Sensitiveness of Variables Extracted from a Fitness Smartwatch to Detect Changes in Vertical Impact Loading during Outdoors Running.Sensors (Basel, Switzerland) · 2023Article
- Article
- Two of a Kind? Similarities and Differences between Runners and Walkers in Sociodemographic Characteristics, Sports Related Characteristics and Wearable Usage.International journal of environmental research and public health · 2022Article
- Feasibility and usability of GPS data in exploring associations between training load and running-related knee injuries in recreational runners.BMC sports science, medicine & rehabilitation · 2022Article
- Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Individual and unorganized sports with a health-related focus, such as recreational running, have grown extensively in the last decade. Consistent with this development, there has been an exponential increase in the availability and use of electronic monitoring devices such as smartphone applications (apps) and sports watches. These electronic devices could provide support and monitoring for unorganized runners, who have no access to professional trainers and coaches. The purpose of this paper is to gain insight into the characteristics of event runners who use running-related apps and sports watches. This knowledge is useful from research, design, and marketing perspectives to adequately address unorganized runners' needs, and to support them in healthy and sustainable running through personalized technology. Data used in this study are drawn from the standardized online Eindhoven Running Survey 2014 (ERS14). In total, 2,172 participants in the Half Marathon Eindhoven 2014 completed the questionnaire (a response rate of 40.0%). Binary logistic regressions were used to analyze the impact of socio-demographic variables, running-related variables, and psychographic characteristics on the use of running-related apps and sports watches. Next, consumer profiles were identified. The results indicate that the use of monitoring devices is affected by socio-demographics as well as sports-related and psychographic variables, and this relationship depends on the type of monitoring device. Therefore, distinctive consumer profiles have been developed to provide a tool for designers and manufacturers of electronic running-related devices to better target (unorganized) runners' needs through personalized and differentiated approaches. Apps are more likely to be used by younger, less experienced and involved runners. Hence, apps have the potential to target this group of novice, less trained, and unorganized runners. In contrast, sports watches are more likely to be used by a different group of runners, older and more experienced runners with higher involvement. Although apps and sports watches may potentially promote and stimulate sports participation, these electronic devices do require a more differentiated approach to target specific needs of runners. Considerable efforts in terms of personalization and tailoring have to be made to develop the full potential of these electronic devices as drivers for healthy and sustainable sports participation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.