dr. heleen riper [email protected] innovation centre of mental health & technology sustainable...
TRANSCRIPT
Dr. Heleen [email protected]
Innovation Centre of Mental Health & Technology
Sustainable prevention with e-mental health
INPES April 2010
What would do?
What would do?
1 out of 4 mental health problem in lifetime
1 per 15 YP
1 million suicides per year
0
2
4
6
8
10
12
Disease burden in 2030
Worldwide
% o
f tot
al D
ALY
Source: Mathers & Loncar, 2006
0
2
4
6
8
10
12
High-income countries
Cataracts
HIV/AID
S
Depression
Is. h
eart dise
ase
Road traffi
c
Perinata
l
Cerebrovascu
lair
COPD
chest
infections
Hearing l
oss
Alzheim
er / dementias
Depression
Is. h
eart dise
ase
Alcohol
Diabetes
Cerebrovascu
lair
Hearing l
oss
Lung c
ance
rs / in
fections
Osteart
hritis
COPD
% o
f tot
al D
ALY
more people less money transition chonic diseases
self-managementlife style
health decisions are made by ..
EMH 2000 - 2010co
sts
treatment duration and intensity
effect sizessmall medium
large
mental fitness
prevention
treatment
relapse preventioncare
population health gainlarge medium
small
© Riper 2008
Is it scalable from research into the
Real World?
33%
73%
5%
60%
Developing
Developed
World
% m
obile
sub
s.
90% 25% 17%
5%
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
020406080
100120
Internet Penetration
Study N Target group Comp CYL/WL/ 12 wks* significant
Spek 2008 301 50+ d= 0.55
Warmerdam 2008 268 18+ d= 0.69
De Graaf 2009 303 18+ d= 0.20
Voordouw 2009 6568/1111
18 + d= 1.09 (Pre-post within)
Color Your Life
Drinking Less
*P<0.001
Drinking Less Real World N= 378 ITT
N/ RCT
Target Group Successful drinking at 6 months
Successful drinking at 12 months
261 14/21 SU Alcohol weekly and/or 6/4 per occasion
17,2% DL5,4 % Control(p= .008)
13,6% DL5,5% Control(p<.05)
6 months 12 months
Percentage successful
18,8 %* 17,5 %*2.750 monthly visitors1 out of 16 starts with DLMean 40.9 (25.2 SD) SU WeeklyAUDIT: M 20.27 (sd 6.30)6 months study period: N= 972Response rate 39%Drop out 59% & 56%
Theory: 4 possible outcomes
Modelling cost-effectiveness of eHealth interventions 16
More costsLess effect
Fewer costsLess effect
More costsMore effect
Fewer costsMore effect
Example 1: Self-help in depression
Modelling cost-effectiveness of eHealth interventions 17
-7.500
-5.000
-2.500
0
2.500
5.000
7.500
10.000
-0,40 -0,20 - 0,20 0,40 0,60 0,80
Additional effects
Ad
dit
ion
al c
ost
s
Smit F, Willemse G, Koopmanschap M, Onrust S, Cuijpers P, Beekman A. (2006) Cost-effectiveness of preventing depression in primary care patients: randomised trial. British Journal of Psychiatry 188: 330-336
Example 2: eHealth v waitlist
Modelling cost-effectiveness of eHealth interventions 18
-500
-0.20 - 0.20 0.40
Additional effects
Additio
nal
cost
s
Example 3: eHealth v Group CBT
Modelling cost-effectiveness of eHealth interventions 19
-2,000
500
-0.20 - 0.20 0.40
Additional effects
Additio
nal costs
Key messages
Modelling cost-effectiveness of eHealth interventions 20
low sesetnic cultural minoritiesrecruitment
acceptable interventions
visual screener
Visual Screener
Visual Screener Depression, Anxiety &Alcohol DutchN=86
TurkishN= 82
1. How do you feel? depression 0.39 r 0.21 r2. How did you feel in the past two weeks? depression 0.47 r 0.29 r3. Do you worry a lot? GAD 0.46 r 0.30 r4. Do you sometimes suddenly panic? Panic 15.14 χ2 21.94 χ2
5. Are you afraid of busy places that are difficult to leave?
AGO 0.53 χ2 n.s. 7.28 χ2
6. Is there something that you are very afraid of? Specific Phobia 21.30 χ2 6.53 χ2
7. Are you afraid of being watched by people? Social Fobia 14.22 χ2 1.33 χ2 n.s.
8. Have you ever experienced something horrible?
PTSD 24.39 χ2 12.32 χ2
9. Do you sometimes have unpleasant thoughts that won’t go away?
OCD 5.58 χ2 0.92 χ2 n.s.
10. Do you ever think about your own death? Alcohol 0.70 r 0.22 r11. Do you ever think of killing yourself? Suicide 23.47 χ2 4.29 χ2
Validadion Visual Screener
effective scalable acceptable
planned effortsknowledge
turning point sustainablefilling the gap
health gain
