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ID
Source
Brief title
Health condition
Resilience, Sustainable employability, Occupational health, Physiotherapy, Prevention
Sponsors and support
Intervention
Outcome measures
Primary outcome
No single consented gold standard outcome measure for SE is available. Therefore our outcome variables will be based on best available evidence.
Sustained employability is operationalized as:
workability: Workability index (WAI)
vitality: UWES9 - vitality
stay at work: sickleave
Workability, sickness absence and vitality are assessed at T0 and T1. Changes in these variables are outcome-variables which are used as input for the DST to learn. The changes will be determined based on MCIC’s. The interpretation of the changes will be different for different groups: e.g. when SE of a worker is good at T0, no change or improvement is a good result, but when SE is insufficient at T0, only improvement is a good result.
Secondary outcome
personal: age, education, years employed, working hours/wk
biometry: bloodpressure (syst and diast), HRV (MHRR), cholesterol, glucose, weight and length (BMI), percentage bodyfat.
Questionnaires : QEEW: need for recovery, workpace, experienced physical strain, experienced mental strain (in dutch: VBBA), GHQ-12, UWES-9, Lifestyle questionnaires (Physical Activity, Smoking, Alcohol, Nutrition and Recreation), Experienced general health questionnaire, Coronary heart diseases questionnaire, experienced physical complaints.
Physical capacity: sit&reach test, Harvard step test, handgrip force.
Functional capacity: FCE tests performed are lifting low and working above shoulder hight.
Optional (according to risk at the company): questionnaire vision, hearing, trachea, skin.
Optional (according to advise of occupational doctor): capacity test of vision, hearing and/or lungs.
Background summary
With an aging workforce, the need increases to preserve health and wellbeing as employees work until retirement age. Enhancing sustainable employability (SE) of employees will be of benefit to the individual employees and society. However, with care as usual it proves hard to predict SE on the basis of questionnaires and biometry from a Workers Health Assessment (WHA). This PhD project’s objective is to improve advising by professionals (especially occupational physiotherapists) with regard to the SE of individual employees by
- the application of sensor technology (to measure resilience, a key term of health) to the WHA and
- the application and validation of machine-learning methods: a Decision Support System (on the basis of artificial intelligence) is developed further and evaluated.
The desired result is an efficient (shorter), effective (proven result) and reliable (reproducible) WHS with DSS-SE.
Study design
The outcome measures are measured after 2 years during usual care.
Intervention
Interventions are only usual care and input for the machine learning system.
Workers health assessment (WHA) is performed at workers and an intervention to maintain or improve sustained employability can be advised. After 2 years the WHA is performed again and information about the intervention followed in between is questioned. The primary WHA data, the follow up WHA data and the intervention that was followed are input for the machine learning system that is developed.
M. Six Dijkstra
MH Tromplaan 28
Enschede 7500 KB
The Netherlands
w.m.c.sixdijkstra@saxion.nl
+31 (0)6-12379329
M. Six Dijkstra
MH Tromplaan 28
Enschede 7500 KB
The Netherlands
w.m.c.sixdijkstra@saxion.nl
+31 (0)6-12379329
Inclusion criteria
- workers (18 - 65 years, male and female)
Exclusion criteria
- persons with severe health problems who were currently absent from work.
- persons with a pace maker were excluded from cardiovascular tests
Design
Recruitment
Followed up by the following (possibly more current) registration
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Other (possibly less up-to-date) registrations in this register
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In other registers
| Register | ID |
|---|---|
| NTR-new | NL7337 |
| NTR-old | NTR7553 |
| Other | : 023.011.076 (NWO) |