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Falls in older adults have an annual incidence between 23 and 34% for persons of 65 years and older. The lack of transfer of promising research results on falls prevention to daily practice may have several explanations. One of the first concerns for that matter may be a valid and sensitive selection of the persons at risk who are eligible for fall prevention interventions
Goals of the prospective obeservational study:
Researchers will compare the data of the accuracy of new algorithm with the current Belgian policy.
Participants will participate in a one-time testing moment, where they will be asked some questions about general characteristics and medical history, followed by two questionnaire and seven physical tests . Based on this data, their fall risk will be assessed. In the year that follows, the older person's fall behavior will be monitored with a monthly falls calender. Participant will be asked to fill out these calenders everyday ('Did you fall today?' YES/NO) and send them at the end of each month to the researchers, digitally or postal.
Two questionnaires:
Seven physical tests:
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Multifactorial algorithm to predict fall risk | Diagnostic Test | In this new multifactorial algorithm we will add baseline data (personal characteristics, medical history, and physical and psychological measurements) to predict an older adults risk on falls. The accuracy of this new model will be tested with a 1-year follow up on falls. The new algorithm is inspired by the study of Lusardi et al. (2017): Lusardi MM, Fritz S, Middleton A, Allison L, Wingood M, Phillips E, Criss M, Verma S, Osborne J, Chui KK. Determining Risk of Falls in Community Dwelling Older Adults: A Systematic Review and Meta-analysis Using Posttest Probability. J Geriatr Phys Ther. 2017 Jan/Mar;40(1):1-36. doi: 10.1519/JPT.0000000000000099. PMID: 27537070; PMCID: PMC5158094. |
| Measure | Description | Time Frame |
|---|---|---|
| Conducted analysis of integraded tests | Fall risk calculated with the new multifactorial algorithm based on:
| Baseline |
| Number of falls among Belgian, community dwelling older adults | The number of falls measured with a monthly falls calender | 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Depression | Measured with the Geriatric Depression Scale (GDS-16) | Baseline |
| Fear of falling | Measured with the Falls Efficacy Scale (FES-I) |
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Inclusion Criteria:
Exclusion Criteria:
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Community dwelling, belgian older adults
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Ellis Rommers, PhD | Contact | +32 9 332 46 57 | ellis.rommers@ugent.be |
| Name | Affiliation | Role |
|---|---|---|
| Dirk Cambier, Prof. Dr. | University Ghent | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ghent University | Recruiting | Ghent | Belgium | 9000 | Belgium |
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| Baseline |
| Functional mobility | Measured with the Timed Up and Go (seconds) | Baseline |
| Executive cognitive capacity | Measured with the Timed Up and Go in combination with a cognitive dual task (100-3-3-3-...) (seconds) | Baseline |
| Static Balance | Measured with the Single Leg stance (seconds) | Baseline |
| Strength of the lower limbs | Measured with the 5x Sit to Stand (second) | Baseline |
| Gait speed | Measured with the 4m Gait Speed (m/s) | Baseline |
| Static and dynamic balance | Measured with the Tinetti: Performance-Oriented Mobility Assessment | Baseline |
| Static Balance | Measured with the 4 balance test | Baseline |