Running
Conditions
Keywords
Plyometric Exercise, Running, Athletic Performance, Sports Injuries, Workload, Sleep Quality
Brief summary
Background. Plyometric training is an effective strategy to improve power and performance in sprint-based sports; however, evidence regarding its actual effects in athletes during the winter season and its potential influence on the occurrence of health problems remains limited. Objective. To analyse the association between participation in a plyometric exercise programme during the winter pre-season and competitive performance, as well as the occurrence of lower-limb health problems in sprinters. Methods. This will be a prospective observational cohort study with fully online data collection. Federated sprinters or athletes affiliated with athletics clubs will be included. The main exposure will be participation in a plyometric exercise programme (≥2 sessions per week in January). Outcomes will be winter competitive performance (best official time) and lower-limb health problems assessed using the OSTRC-H2 questionnaire. Control variables will include sleep quality (PSQI), internal training load (session-RPE), injury history, and competitive level. Statistical analyses will include linear and logistic regression models adjusted for potential confounders. Expected results. A positive association is expected between engagement in plyometric training and competitive performance, along with a lower frequency of lower-limb health problems, particularly among athletes with adequate sleep quality and a well-balanced training load.
Interventions
OTHERPlyometric training
Participation in a structured plyometric exercise programme during the winter pre-season (≥2 sessions per week)
OTHERTraining without plyometric exercises
Winter pre-season training programme without plyometric exercises
Sponsors
Universidad Católica San Antonio de Murcia
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
16 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Age ≥16 years * Regular participation in sprint events (60-400 m) * Planned participation in winter competitions * Membership of an athletics club * Provision of digital informed consent
Exclusion criteria
* Recent acute lower-limb injury preventing training * Medical contraindication to plyometric training * Inability to complete follow-up * Low questionnaire completion rate (\<70%).
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Assessment of changes in winter competitive performance at baseline, after the winter pre-season, and after the competitive season | Baseline, through study completion, an average of 1 month | Winter competitive performance will be measured using the best official time recorded by each athlete in their main event (60, 100, 200, or 400 metres) during the winter season. The value will be expressed in seconds and will be obtained via self-report in the final questionnaire, together with the competition in which it was achieved. This continuous variable will represent the primary performance outcome. |
| Assessment of changes in the occurrence of lower-limb health problems at baseline, after the winter pre-season, and after the competitive season | Baseline, through study completion, an average of 1 month | The occurrence of lower-limb health problems will be assessed using the Oslo Sports Trauma Research Center Overuse Injury Questionnaire (OSTRC-O), Spanish validated version. Based on the weekly reports, two indicators will be derived: the presence of at least one substantial lower-limb health problem (dichotomous variable: yes/no) and the total number of weeks with any health problem in this location (discrete variable). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Assessment of changes in sleep quality at baseline, after the winter pre-season, and after the competitive season | Baseline, through study completion, an average of 1 month | Sleep quality will be assessed using the Spanish version of the Pittsburgh Sleep Quality Index (PSQI). This scale yields a global score ranging from 0 to 21, with higher scores indicating poorer sleep quality. It will be administered at baseline and at the end of the season |
| Assessment of changes in the internal training load at baseline, after the winter pre-season, and after the competitive season | Baseline, through study completion, an average of 1 month | Internal training load will be calculated using the session-RPE method (14). This assessment is based on weekly training duration in minutes multiplied by the global perceived exertion rated on the Borg CR10 scale. From the weekly records, the mean weekly training load will be derived as a continuous variable. |
| Assessment of the previous performance at baseline | Baseline | Previous performance will be defined as the best official time recorded during the previous season, expressed in seconds, and will be used as a covariate to adjust for baseline performance level. |
| Assessment of lower-limb injury history at baseline | Baseline | Lower-limb injury history over the previous 12 months will be recorded as a dichotomous variable (yes/no), with documentation of the primary injury location. |
Countries
Spain
Contacts
PRINCIPAL_INVESTIGATORRubén Cuesta-Barriuso, PhD
Universidad de Oviedo
Outcome results
None listed