Evidence map›Paper›PMID 39465206›Full record

ArticleFrontiers in sports and active living2024

Training, environmental and nutritional practices in indoor cycling: an explorative cross-sectional questionnaire analysis.

W M Peeters, A H Coussens, I Spears, O Jeffries

Abstract read
In one paragraph

Article in Frontiers in sports and active living, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Physiological Responder Profiles and Fatigue Dynamics in Prolonged Cycling.Journal of functional morphology and kinesiology · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

W M PeetersSchool of Biomedical, Nutrition and Sport Sciences, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
A H CoussensSchool of Biomedical, Nutrition and Sport Sciences, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
I SpearsSchool of Biomedical, Nutrition and Sport Sciences, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
O JeffriesSchool of Biomedical, Nutrition and Sport Sciences, Newcastle University, Newcastle-upon-Tyne, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Indoor cycling at home has grown rapidly in recent years facilitated by advances in technology and gamification. However, there is limited data on individual's training practices when cycling indoors. Methods: Using a single-time point, cross-sectional questionnaire, we gathered information on equipment, environmental considerations, training practices and nutrition during indoor cycling. Results: Following 492 responses, external variables (weather; 88.4%, lack of daylight; 56.3%), time efficiency (81.9%) and general fitness (70.9%) were most frequently cited as reasons to engage in indoor cycling. "Smart" turbo trainers linked to a mixed-reality cycling software were most frequently reported in equipment set-up. 78% of participants attempted to control temperature with 96% of these participants using at least 1 fan to control airflow. The volume of indoor training differed between seasons (winter: 6h10 ± 3 h 30, summer 2h52 ± 2h57, Conclusion: Together we report indoor cycling practices with respect to training equipment, considerations of environmental and nutritional strategies and training habits. Our findings could be used to support the development of future research and indoor training guidelines.

Indexed as

cyclingexercisenutritiontechnologythermoregulation

Identifiers

PMID39465206
PMCPMC11502339

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.