Self-management supported by assistive, rehabilitation and telecare technologies

Not Applicable

Completed

• Conditions: Topic: Generic Health Relevance and Cross Cutting Themes, Primary Care Research Network for England; Subtopic: Not Assigned, Generic Health Relevance (all Subtopics); Disease: All Diseases, Other; Not Applicable; Rehabilitation

• Registration Number: ISRCTN31254396
• Lead Sponsor: niversity of Sheffield (UK)

Brief Summary

Not available

Detailed Description

Not available

Study Timeline

• Study Start: 2010-06-18
• Last Update Posted: 5 June 2017

Recruitment & Eligibility

• Status: Completed
• Sex: All
• Target Recruitment: 150

Inclusion Criteria

User participants with one of the following conditions:
1. Stroke, congestive heart failure (CHF) and chronic pain
2. People with stroke - up to 2 years post stroke
3. People diagnosed with chronic heart failure (CHF) (New York Heart Association [NYHA]) 2, 3 or 4
4. Living in the community
5. Access to a telephone line
6. Sufficient English language skills in order to understand and express themselves verbally

Carer participants:
7. Co-resident with patient participant or in very frequent contact with them

Clinician participants:
8. Currently involved in delivery of services to people with one of the three conditions

Exclusion Criteria

User participants:
1. Co-morbid cognitive or physical impairment to the extent that it will hinder participants from giving informed consent and/or talking in a group setting
2. In-patient in a hospital or other residential setting

Carer participants:
3. Not having a large amount of contact with a patient who has agreed to participate in the study

Study & Design

• Study Type: Interventional
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
To investigate how technology can be used to construct tailored plans of interventions to be undertaken

Secondary Outcome Measures

Name	Time	Method
1. To examine the extent to which behaviour change is promoted through personalised feedback<br>2. To identify how information on signs, symptoms and lifestyle consequences can be fed back to users in a usable way<br>3. To identify how relevant signs, symptoms and lifestyle consequences of long-term conditions can be effectively monitored and modelled