Detalhes bibliográficos
| Ano de defesa: |
2018 |
| Autor(a) principal: |
Del Rosso, Sebastián
 |
| Orientador(a): |
Boullosa, Daniel A.
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| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Católica de Brasília
|
| Programa de Pós-Graduação: |
Programa Stricto Sensu em Educação Física
|
| Departamento: |
Escola de Saúde e Medicina
|
| País: |
Brasil
|
| Palavras-chave em Português: |
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| Área do conhecimento CNPq: |
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| Resumo em Inglês: |
The main goal of the present study was to identify the main determinants influencing and thus explaining pacing and performance during self-paced 10 km running time trial and develop prediction equations including metabolic/respiratory and neuromuscular variables. Twenty-seven well-trained runners (age = 26,4 ± 6,5 years, training experience = 7,4 ± 5,9 years, training volume = 89,1 ± 39,1 km·week-1, VO2max = 62,3 ± 4,5 mL·kg-1·min-1) completed three testing sessions: During the first session, body composition and mechanical variables (concentric peak velocity, PV; time to peak velocity, TPV; peak force, PF; and peak power, PP) in the half-squat (AG) and loaded squat jump (SSC) were measured. The second testing session was dedicated to assessing metabolic variables [VO2max, ventilatory thresholds (VT1 and VT2), cost of running (CR) and maximal speed (SMAX)] and vertical jump (CMJ) potentiation; while during the third session a 10 km self-paced time trial was carried out. Also, before and after (0, 3, 6, and 9 min) the 10 km, athletes completed 2 CMJ for measuring mechanical variables [eccentric displacement (DE), mean eccentric and concentric velocity (VME, VMC), eccentric and concentric peak velocity (PVE, PVC)]. Pacing was defined as the time (T10km) or speed (S10km) every 1000 m, and analysis of those factors influencing the 10 km performance was carried by means of hierarchic multiple regression, whit the inclusion of all available variables. In addition, regression analyses were performed to develop prediction equation for T10km. Cluster analyses were carried out to evaluate the effects of performance levels [high performance group, GAD; low performance group (GBD)] and jumping potentiation (potentiation group, GP; non-potentiation group, GNP). For the whole sample, the final model including SMAX, CR, o a AGVP, Δ3-Pre CMJPVE (m·s-1), HRmax (bpm) and SSCPF (N) was statistically significant; r2 = 0,91, F(6-26) = 35,64, P < 0,001, EES = 0,76, r2ADJUSTED = 0,89; while the prediction model included the following variables: SMAX, CR and AGVP [r2 = 0,75; F(3-26) = 22,52; P < 0,001; EES = 1,23]. For the performance groups, there were significant main simple effects for time [F(2-52) = 12,20, P<0,001), η2 = 0,32] and group [F(1-25) = 49,91; P<0,001, η2 = 0,66] and also differences in the explaining variables for T10km: GAD [SMAX; SSCPF, HRMEAN, CV10km e Post-0min CMJPVE, F(5-9) = 266,06; P <0,001; SSE = 0,09 min; r2ADJUSTED = 0,99]; GBD [VT2-%VO2max, Δ6-Pre CMJEPV, CR; F(4-18) = 33,16; P <0,001, EES = 0,045 min; r2ADJUSTED = 0,88]. Furthermore, different prediction equations were found for each group: GAD – [T10km (min) = 68,65 – (1,084 × SMAX) – (0,008 × SSCPF) + (0,083 × AGCARGA); r2 = 0,98]; GBD - T10km (min) = 44,75 – (1,05× SMAX) + (0,17×VT2-%VO2max) + (1,89 × CMJVME) – (0,061 × Age); r2 = 0,89]. For jump potentiation groups there were significant differences only in the last 400 m and RPE (GNP = 8,36 ± 1,6 vs. GP = 6,8 ± 1,7; P = 0,03). Also, jump potentiation correlated with the final 400 m time in the whole sample (r = -0.42; P = 0,031) and with RPE for the GAD group (r = -0,75; P = 0,032). In conclusion, the results of the present study suggest that mechanical factors are significant for endurance runners given that explain part of the variance in the T10km while allowed for performance prediction. Moreover, performance level appears to be related to neuromuscular differences influencing pacing whereas jump potentiation likely affects effort perception. |
| Link de acesso: |
https://bdtd.ucb.br:8443/jspui/handle/tede/2441
|
Resumo: |
The main goal of the present study was to identify the main determinants influencing and thus explaining pacing and performance during self-paced 10 km running time trial and develop prediction equations including metabolic/respiratory and neuromuscular variables. Twenty-seven well-trained runners (age = 26,4 ± 6,5 years, training experience = 7,4 ± 5,9 years, training volume = 89,1 ± 39,1 km·week-1, VO2max = 62,3 ± 4,5 mL·kg-1·min-1) completed three testing sessions: During the first session, body composition and mechanical variables (concentric peak velocity, PV; time to peak velocity, TPV; peak force, PF; and peak power, PP) in the half-squat (AG) and loaded squat jump (SSC) were measured. The second testing session was dedicated to assessing metabolic variables [VO2max, ventilatory thresholds (VT1 and VT2), cost of running (CR) and maximal speed (SMAX)] and vertical jump (CMJ) potentiation; while during the third session a 10 km self-paced time trial was carried out. Also, before and after (0, 3, 6, and 9 min) the 10 km, athletes completed 2 CMJ for measuring mechanical variables [eccentric displacement (DE), mean eccentric and concentric velocity (VME, VMC), eccentric and concentric peak velocity (PVE, PVC)]. Pacing was defined as the time (T10km) or speed (S10km) every 1000 m, and analysis of those factors influencing the 10 km performance was carried by means of hierarchic multiple regression, whit the inclusion of all available variables. In addition, regression analyses were performed to develop prediction equation for T10km. Cluster analyses were carried out to evaluate the effects of performance levels [high performance group, GAD; low performance group (GBD)] and jumping potentiation (potentiation group, GP; non-potentiation group, GNP). For the whole sample, the final model including SMAX, CR, o a AGVP, Δ3-Pre CMJPVE (m·s-1), HRmax (bpm) and SSCPF (N) was statistically significant; r2 = 0,91, F(6-26) = 35,64, P < 0,001, EES = 0,76, r2ADJUSTED = 0,89; while the prediction model included the following variables: SMAX, CR and AGVP [r2 = 0,75; F(3-26) = 22,52; P < 0,001; EES = 1,23]. For the performance groups, there were significant main simple effects for time [F(2-52) = 12,20, P<0,001), η2 = 0,32] and group [F(1-25) = 49,91; P<0,001, η2 = 0,66] and also differences in the explaining variables for T10km: GAD [SMAX; SSCPF, HRMEAN, CV10km e Post-0min CMJPVE, F(5-9) = 266,06; P <0,001; SSE = 0,09 min; r2ADJUSTED = 0,99]; GBD [VT2-%VO2max, Δ6-Pre CMJEPV, CR; F(4-18) = 33,16; P <0,001, EES = 0,045 min; r2ADJUSTED = 0,88]. Furthermore, different prediction equations were found for each group: GAD – [T10km (min) = 68,65 – (1,084 × SMAX) – (0,008 × SSCPF) + (0,083 × AGCARGA); r2 = 0,98]; GBD - T10km (min) = 44,75 – (1,05× SMAX) + (0,17×VT2-%VO2max) + (1,89 × CMJVME) – (0,061 × Age); r2 = 0,89]. For jump potentiation groups there were significant differences only in the last 400 m and RPE (GNP = 8,36 ± 1,6 vs. GP = 6,8 ± 1,7; P = 0,03). Also, jump potentiation correlated with the final 400 m time in the whole sample (r = -0.42; P = 0,031) and with RPE for the GAD group (r = -0,75; P = 0,032). In conclusion, the results of the present study suggest that mechanical factors are significant for endurance runners given that explain part of the variance in the T10km while allowed for performance prediction. Moreover, performance level appears to be related to neuromuscular differences influencing pacing whereas jump potentiation likely affects effort perception. |
