1. Service user involvement and
study success
An analysis of the MHRN portfolio
database
Liam Ennis and Professor Til Wykes
2. Background
Many funders now require service
user involvement (or justification why
not)
MHRN directive = assisting
involvement
3. Involvement – what
“When we talk about service user
involvement, we mean the active involvement of
service users, not their passive involvement as
recipients of services or information. Involving is
often described as doing
things with or by people, rather
than for or to them.
‘Involvement’ covers a range of activities, from
consulting service users abut their views or
wishes, through to working in partnership with them
to develop projects or services, right up to service
users leading projects, services or organisations”
(Taken from TwoCan Associates)
4. Involvement – why
Ensuring that research questions are
those that are valued by service users
Enhancing translational value of
research
Improving quality and feasibility
5. Involvement – where
e.g.
Setting research priorities (Rose et
al, 2008; Thornicroft et al, 2002)
Choosing/generating outcomes
(Crawford et al, 2011; Evans et al, 2012)
Alternative methodologies (Rose et
al, 2011)
BUT no studies investigate whether
there are benefits to the study itself
6. The present study
Aims to establish whether:
1) Service user involvement has increased
over time
2) Particular factors are associated with
involvement
3) Service user involvement is associated
with recruitment success
7. Data source
MHRN portfolio database
Contains all adopted studies since
2004
N = 374
8. Measures
Level of service user involvement:
1. Consultation
2. Researcher-initiated collaboration
3. Jointly/service-user initiated
collaboration, or user-controlled
studies
9. Measures
Study complexity
Primary CSG
Funding body
◦ NIHR/MRC/Charity/International/Government
Study characteristics
◦ Randomised/Intervention/Follow up
Adoption order
10. Outcomes
Levels of servicer user involvement
Successful recruitment (>90% -
nationally set target by NIHR)
11. Statistical analysis
Change in service user involvement over
time was assessed by correlating adoption
order with level of service user involvement
using Pearson’s product moment
Predictors of levels of service user
involvement were explored using
multinomial logistic regression
Associations with participant recruitment
were explored using binary logistic regression
(N = 135)
12. Results
Service user involvement was
modestly correlated with adoption
order, r = ·12, p <· 05 showing that
involvement has increased over time.
13. Predictor Wald's chi-square p odds ratio
CSG
Psychotic disorders 0·66 ·42 0·68
Mood disorders 1·69 ·19 0·46
Other common mental disorders 3·46 ·06 0·29
Developmental disorders 6·31 ·012* 0·06
Personality disorders 5·82 ·016* 0·17
Social interventions 5·14 ·023* 0·14
Funder
NIHR 5·97 ·015* 4·45
MRC 0·18 ·67 0·72
Government 0·001 ·97 1·03
Charities/not for profit 1·64 ·20 3·03
14. Consultation
Researcher
70 Initiated
60 Jointly/Patient-
initiated/Patient
controlled
50
% 40
30
Mean
20 proportion
in highest
10 category
0
NIHR MRC Government Charities/not International
Funder for profit
15. Predictor Wald’s chi-square p odds ratio
Results
Non-follow up 5·94 ·015* 0·23
Complexity 6·55 ·010* 0·83
Involvement
Researcher initiated 1·41 ·236 1·63
Jointly initiated or higher 4·58 ·032* 4·12
16. Interpretation: context
Important to emphasise associations,
not causality
Therefore only provides directions for
future research
Need more variables to delineate this
relationship
17. Why might the association
exist?
Language in information sheets etc
Least-burdensome design of research
Intrinsic appeal of service user
involvement
18. Limitations
Unmeasured factors, e.g. researcher
commitment
Detail of categories of involvement
Are researchers involving users as
they set out to?
19. Future directions
More research…
MHRN adoption forms could help
delineate the relationship by
requesting more detail & being more
specific about the information required