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Big Data Supporting Public Health Hearing Policies (EVOTION)

University College London (UCL) logo

University College London (UCL)

Status

Completed

Conditions

Hearing Loss

Treatments

Device: Mobile phone
Device: Hearing aid
Device: Sensor

Study type

Interventional

Funder types

Other

Identifiers

NCT03316287
17/0064

Details and patient eligibility

About

Hearing Loss (HL) affects over 5% of the world's population (WHO 2014) and is the 5th leading cause of Years Lived with Disability. HL is currently managed with Hearing Aids (HAs), i.e. programmable sound amplification devices that are worn by the hearing impaired subjects to address their hearing difficulties. HA use however is often problematic, costly and with poor overall benefits. The holistic management of HL requires appropriate public health policies for HL prevention, early diagnosis, long-term treatment and rehabilitation; detection and prevention of cognitive decline; and socioeconomic inclusion of HL patients. Currently the evidential basis for forming such policies is limited.

The EVOTION project proposes to address this by collecting and analysing a big set of heterogeneous data, including HA usage, audiological, physiological, cognitive, clinical and medication, personal, behavioural, life style, occupational and environmental data.

This will be done by:

i. accessing big datasets of existing HA user data from the EVOTION clinical partners (UCL/UCLH and GST in the UK; OTICON in Denmark) ii. collection of prospective HA user data who will be recruited to the prospective EVOTION study and who will undergo some additional assessments iii. collection of real time dynamic data of the human participant HA users who will be given a smart phone with different apps (auditory tests; auditory training), sensors (recording of heart rate, blood pressure, respiratory rate etc.) and smart HAs (recording environmental factors such as noise levels, type of noise etc.) so that real life contextual factors that affect HA usage and outcome can be identified.

These data will be analysed with big data analysis/data mining techniques in order to identify relationships between these in order to use this information to derive and support public health decisions.

Enrollment

1,080 patients

Sex

All

Ages

18+ years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • Age >18 years
  • Basic understanding of oral and written English
  • Unilateral and/or bilateral mild to severe sensorineural hearing loss
  • Willing to use smart hearing aids for at least 2 hours daily on average
  • Willing/capable to use a mobile phone

Exclusion criteria

  • Dementia (MoCA<22 )
  • Not agreeing or able to attend for f/u appointments
  • Not agreeing or able to use HA >2 hours daily (average)
  • Not sufficient vision to use smartphone ap

Trial design

Primary purpose

Other

Allocation

Non-Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

1,080 participants in 2 patient groups

Hearing aid + mobile phone
Experimental group
Treatment:
Device: Mobile phone
Device: Hearing aid
Hearing aid + mobile phone + biosensor
Experimental group
Treatment:
Device: Sensor
Device: Mobile phone
Device: Hearing aid

Trial contacts and locations

1

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Data sourced from clinicaltrials.gov

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