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| ID | Type | Description | Link |
|---|---|---|---|
| TI2018-098893-BI00 | Other Grant/Funding Number | Ministerio de Ciencia, Innovación y Universidades, Spain |
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The increase in life expectancy, together with the high levels of physical inactivity in the population over 65 years of age, has generated a significant reduction in the quality of life of elderly people, characterized by the increase in functional dependence and risk of falling. In this sense, falls in this population are a serious public health problem, as they can cause fractures that not only exacerbate functional deterioration but can also lead to death. The current literature shows that low muscle strength and poor trunk stability, caused by aging, are associated with low balance levels and consequently with an increased risk of suffering a fall. Thus, there are many studies that have tried to develop trunk muscle conditioning programs as a preventive tool to improve balance, gait and functional mobility in older people. However, these exercise programs have not always shown as positive results as would be expected. One of the main reasons that could explain the heterogeneity of these results is the lack of valid and reliable protocols to objectively measure the intensity of trunk stabilization exercises. This makes trunk training program control and individualization difficult and hinders the proper dose-response characterization of these programs in older people.
Therefore, this project aims to develop new protocols based on low cost and easy to use tools to objectively assess trunk stabilization exercise intensity/difficulty in any sports, geriatric or research facility. This would allow: to perform individualized trunk exercise programs to develop balance, reduce the risk of suffering a fall and improve the quality of life in older people; to increase the replicability of these training programs; and to facilitate, in the future, the establishing of dose/response relationships.
Fifty-seven physically active older adults (22 men and 35 women) participated in the study. All participants were assessed on two occasions prior to the intervention (pre-test 1 and pre-test 2), and two after the intervention (post-test 1 and post-test 2) using the same outcome measures to assess training effects. The testing sessions included: (i) core stability assessment using an unstable sitting test with force platforms; (ii) evaluation of core stabilization exercises-later used in the training program-via smartphone accelerometry; (iii) assessment of postural control and gait under multiple conditions using force platforms and smartphone accelerometry; and (iv) functional mobility testing.
Participants were randomly assigned to one of three groups: two experimental groups (low-intensity and high-intensity core stability training) and a control group. The intervention consisted of a 6-week core stability training program performed twice per week. Each training session included four sets of one variation of four commonly used stabilization exercises targeting the core musculature: frontal bridge, back bridge, lateral bridge, and bird-dog. The two experimental training programs differed in exercise intensity, which was quantified using lumbopelvic accelerations measured via smartphone accelerometers. Participants in the low-intensity group performed exercise variations that elicited oscillation ranges of 0.20-0.30 m/s² for the frontal bridge and 0.15-0.25 m/s² for the lateral bridge, back bridge, and bird-dog exercises during pre-testing. Participants in the high-intensity group performed exercise variations corresponding to oscillation ranges of 0.30-0.40 m/s² for the frontal bridge and 0.25-0.35 m/s² for the lateral bridge, back bridge, and bird-dog exercises. Exercise duration was standardized to 25 seconds for both experimental groups. Training loads were reassessed and adjusted every two weeks throughout the intervention period.
For statistical analysis, means and standard deviations were calculated for all outcomes using both intention-to-treat and per-protocol approaches. Data normality and homogeneity of variance were assessed using the Shapiro-Wilk and Levene's tests, respectively. Two-way mixed-design ANOVAs were conducted with time (pre- vs. post-intervention) as the within-subject factor and group (low intensity, high intensity, control) as the between-subject factor to examine differences in trunk stability, postural control, gait, and functional mobility. Effect sizes were calculated using partial eta squared (η²p). Paired t-tests were performed to examine pre-post changes within each group. All statistical analyses were conducted using JASP software (version 0.18.3; University of Amsterdam, The Netherlands), with statistical significance set at p < 0.05.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Experimental: Low Intensity training group | Experimental | Low Intensity training group will complete a 6 week core stability training program with low intensity/oscillation exercises |
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| Experimental: High Intensity training group | Experimental | High Intensity training group will complete a 6 week core stability training program with high intensity/oscillation exercises |
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| No Intervention: Control group | No Intervention | Control group will have 6 weeks with no intervention before post-test |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Core stability training | Other | This intervention includes an individualized core stability training in older adults |
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| Measure | Description | Time Frame |
|---|---|---|
| Mean radial error of center of pressure in sitting and tandem condition | Postural control in sitting condition over an unstable seat evaluated through the mean radial error of center of pressure displacement | Baseline - 6 weeks |
| Pelvis mean acceleration | Pelvis mean acceleration in different isometric stabilization exercises measured with a smartphone accelerometer | Time Frame: Baseline - every 2 weeks up to 6 weeks |
| Functional mobility | Time in Timed Up and Go Test | Baseline - 6 weeks |
| Balance and gait under different conditions | A smartphone app was used to analyze performance on both outcomes. | Baseline-6 weeks |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Francisco J Vera Garcia, Professor | Universidad Miguel Hernández de Elche | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Biomechanics laboratory of Universidad Miguel Hernandez de Elche | Elche | Alicante | 03202 | Spain |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34744790 | Background | Heredia-Elvar JR, Juan-Recio C, Prat-Luri A, Barbado D, Vera-Garcia FJ. Observational Screening Guidelines and Smartphone Accelerometer Thresholds to Establish the Intensity of Some of the Most Popular Core Stability Exercises. Front Physiol. 2021 Oct 22;12:751569. doi: 10.3389/fphys.2021.751569. eCollection 2021. | |
| 30517171 | Background |
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All Individual Participant Data (IPD) that underlie results in a publication.
Data will be available six months after publication
Data access requests will be reviewed by an external Independent Review Panel. Requestors will be required to sign a Data Access Agreement
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| Barbado D, Irles-Vidal B, Prat-Luri A, Garcia-Vaquero MP, Vera-Garcia FJ. Training intensity quantification of core stability exercises based on a smartphone accelerometer. PLoS One. 2018 Dec 5;13(12):e0208262. doi: 10.1371/journal.pone.0208262. eCollection 2018. |