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Patient Expectations and Experiences from a Clinical Study in Psychiatric Care Using a Self-Monitoring System

Authors:

Abstract

Preliminary results from a clinical study concerning the feasibility of using a self-monitoring system in psychiatric care are presented. At the end of hospital treatment for depression 32 patients were enrolled in the study. The patients used the self-monitoring system at home during a 4-week period. Data from the case report forms show that a clear majority of the patients find that using the self-monitoring system supported them in getting a better overview of their symptoms. 12 out of 32 patients even found that using the system could help them catch an upcoming depression. A clear majority of the patients found it important that the use of the self-monitoring system was combined with communication and information sharing with their clinicians at face-to-face meetings and/or through telephone contacts.
Patient Expectations and Experiences
from a Clinical Study in Psychiatric
Care Using a Self-Monitoring System
Abstract
Preliminary results from a clinical study concerning the
feasibility of using a self-monitoring system in
psychiatric care are presented. At the end of hospital
treatment for depression 32 patients were enrolled in
the study. The patients used the self-monitoring system
at home during a 4-week period. Data from the case
report forms show that a clear majority of the patients
find that using the self-monitoring system supported
them in getting a better overview of their symptoms.
12 out of 32 patients even found that using the system
could help them catch an upcoming depression. A clear
majority of the patients found it important that the use
of the self-monitoring system was combined with
communication and information sharing with their
clinicians at face-to-face meetings and/or through
telephone contacts.
Author keywords
Depression; self-monitoring; clinical study; feasibility;
user-centered design; e-health; tele-psychiatry; tele-
medicine; e-mental health.
ACM Classification Keywords
J.3: Life and medical sciences: Health, H.5.2 User
interfaces: Evaluation/methodology
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NordiCHI '14, Oct 26
-30 2014, Helsinki, Finland
ACM 978
-1-4503-2542-4/14/10.
http://dx.doi.org/10.1145/2639189.2670258
Lasse Benn Nørregaard &
Philip Kaare Løventoft
Daybuilder Solutions
Fogedmarken 8, 7. th
2200 København N, Denmark
{lbn,
pkl}@daybuilder.dk
Erik Frøkjær
U
niversity of Copenhagen, DIKU
Njalsgade 128, B. 24, 5.
sal
2300 København S, Denmark
erikf@di
.ku.dk
Lise Lauritsen, Emilia Clara
Olsson
, Louise Andersen and
Stine Rauff
Intensive Affective Ambulatorium,
Psychiatric Centre Copenhagen
(University of Copenhagen)
Edel Sauntes Alle 10,
Opg
ang 61B, 3. sal
2100 København Ø, Denmark
Klaus Martiny
Intens
ive Affective Ambulatorium,
Psychiatric Centre Copenhagen
(University of Copenhagen)
Edel Sauntes Alle 10,
Opg
ang 61B, 3. sal
2100 København Ø, Denmark
Klaus.martiny@regionh.dk
Figure
1. Graph of mood (red line), sleep
(blue
area) and exercise (green scatter)
for a patient.
Figure
2.
The field on the website to input
mood.
Introduction
We present preliminary results from 32 patients who
participated in the clinical study “SAFE electronic self-
monitoring in depression” which is still in progress. The
study is conducted at the Intensive Affective
Ambulatorium (IAA), Psychiatric Center of Copenhagen
(PCC), part of the Copenhagen Capital Region
Psychiatry and Rigshospitalet.
The study uses a web application called “Daybuilder”
for self-monitoring. Daybuilder Solutions originally
developed the web application in cooperation with
researchers from IAA for the SAFE study following a
user-centered approach. The experimental design work
and evaluation leading to the development of
Daybuilder was presented at PDC12 [4].
Related works
In recent years, mental e-health has grown as a field of
study [1,3]. Still there are rather few reports on the
use of self-monitoring systems in a clinical psychiatric
context. For instance [2] reports on a smartphone
application used by 10 patients in Austria under the
supervision of a local psychiatric hospital.
Design of the study
The focus of the SAFE study is on the usefulness and
usability of the self-monitoring system. The aims of the
SAFE study are:
To assess if there is a change in patients’ mood and
sleep after they are discharged from
hospitalization.
To assess if this can be measured by self-
monitoring.
To give the patients a tool to monitor themselves
and thereby increase the ability to handle their
illness.
To give the clinicians a more detailed insight into
the patients’ symptoms in the self-monitoring
period.
Participation in the study extends over four weeks for
each patient. This includes two interviews, one at
enrollment and one at the end, daily self-registration of
symptoms and weekly phone contact, reported in Case
Report Forms (CRF) by the clinicians. A CRF is a printed
or digital document recording the data decided by the
research protocol, for each individual patient. The study
was approved by the Danish medical ethics board.
The self-monitoring system
The SAFE study uses a self-monitoring system, which
allows users to register several key variables related to
depression. Users can enter variables either through a
web interface or through the use of ”Short Message
Service” (SMS) messages for mobile phones.
Screenshots from the self-monitoring system can be
seen in Figures 1 and 2. A trial version is available on
www.daybuilder.com.
Preliminary results from the case report
forms
We present the answers to the questions selected from
the CRFs (see Figures 3 and 4 for the questions).
The frequencies for different answers can be seen in
Tables 1A and 1B, where Table 1A are questions about
expectations asked at patient enrollment and Table 1B
are the questions asked at the end of the study about
the patients’ actual experiences.
Questions at enrollment
QA1: Do you think that
recording your mood will
influence your mood? If yes,
then how?
QA2: Do you think that this
program will have an overall
influence on your illness? If
yes, in which way?
QA3: Do you think that this
program can cover your need
for recording your
symptoms?
QA4: Do you think that this
program would be able to
help you gain more control of
your condition and everyday
life?
QA5: Do you think that the
self-monitoring system can
help you catch an upcoming
depression?
QA6: How important is the
follow-up on your recordings
to you?
Figure 3. Questions selected from
the Case Report Forms
concerning patient expectations
at enrollment.
Pos.
Neg.
Pos. And
Neg.
Neutral
N/A
5
3
9
12
3
12
0
0
16
4
Yes
No
Not Sure
-
N/A
19
6
3
-
4
15
4
10
-
3
21
0
7
-
4
Impor-
tant
Not
imp.
-
Neutral
N/A
19
4
-
3
5
Table 1A: Answers from the patients to the questions from
Figure 3, concerning their expectations with the self-monitoring
system. “N/A” covers patients with either no answer or non-
interpretable answers.
A research assistant coded the answers according to a
guide into one of the following three nominal scales,
depending on the nature of the question: (Positive,
Negative, Positive and negative, Neutral); (Yes, No, Not
sure); (Important, Not important, Neutral).
The majority of the patients experienced the use of the
software to be rather neutral in relation to their mood
(QB1), see Table 1B, more or less in line with what was
expected by the patient (QA1), see Table 1A.
Sometimes it influenced mood positively, sometimes
negatively.
For instance, as one patient notes “[The self-monitoring
system] can both affect mood positively and negatively
depending on the mood score. Good tool to help me
feel how I really feel”.
Regarding the overall influence of using the self-
monitoring system (QB2), 11 out of 32 patients did
experience an influence, while 13 patients did not. 19
out of 32 patients reported that they gained a better
overview of their symptoms (QB4). The answers
concerning QB6 show that 18 patients found it
important to have follow-up sessions with their
clinician, either face-to-face or by telephone. Only one
patient did not find such follow-up important. Six
patients were not sure about the importance of follow-
up sessions, and 7 patients did not answer.
Expectations and experiences
We conducted Fisher’s exact test for association in
order to clarify to what degree patients’ expectations
differed from what they actually experienced during the
study. For that purpose the questions with similar
themes were paired (QAn - QBn), see Figures 3 and 4.
Fisher’s exact test shows that there is no statistically
significant differences (p<.05) between the answers to
questions at enrollment and at the end of the study.
This points to patients’ expectations in general being
met.
Questions at the end
QB1: Did the recording of
your mood influence your
mood? If so, how?
QB2: Do you think that using
this self-monitoring system
has had an overall influence
on your symptoms during the
last 4 weeks? If yes, in what
way?
QB3: Did the self-monitoring
system cover your needs for
recording your symptoms?
QB4: Did the self-monitoring
system give you a better
overview of your symptoms?
QB5: Did you experience that
the self-monitoring system
could help you catch an
upcoming depression?
QB6: How important is the
follow-up on your recordings
to you?
Figure 4. Questions selected from
the Case Report Forms
concerning patient experiences at
the end of the study.
Pos.
Neg.
Pos. And
Neg.
Neutral
N/A
5
2
3
14
8
11
0
1
13
7
Yes
No
Not Sure
-
N/A
14
10
1
-
7
19
5
1
-
7
12
7
5
-
8
Impor-
tant
Not
imp.
-
Neutral
N/A
18
1
-
6
7
Table 1B: Answers from the patients to the questions from
Figure 4, concerning their experiences with the self-monitoring
system. “N/A” covers patients with either no answer or non-
interpretable answers.
Discussion
We saw in the results that there was no significant
influence on mood with only 2/32 (6%) reporting that
their mood was influenced negatively by using the
software and 5/32 (16%) reporting that mood was
influenced positively. At the same time 11/32 (34%)
reported that they felt that using the self-monitoring
system influenced their illness positively overall.
While expectations and experiences were not
statistically significantly different, there was a tendency
to expectations not being met completely. However the
actual results are encouraging in that there was quite a
large proportion (12/32, 38%) who answered a definite
yes to whether the program had helped them catch an
upcoming depression (QB5).
Therapist follow-up is, in line with the literature [1],
essential as can be seen from the answers to QB6, both
at enrollment and end, where respectively 19/32 (59%)
and 18/32(57%) answer a definite yes.
To support the reader’s interpretation of the
quantitative data we include a few quotes from the
CRFs in Figure 5.
Future work
A new study is planned, to investigate how self-
monitoring systems can be used to guide clinicians’
feedback regarding sleep hygiene upon release from
inpatient care. More research is needed as to what
effect self-monitoring systems have on longer term
outcomes. Our results point to a mechanism where
mood itself is not directly influenced by the self-
monitoring system, but patients and clinicians have
better options for preventing recurrence.
Conclusion
These preliminary results show that mood is not
significantly influenced by using a self-monitoring
system. Patients’ expectations were mostly met.
Overview over symptoms is improved while at the
same time providing the opportunity to catch a
recurring depression earlier.
Acknowledgements
The SAFE study was funded by Trygfonden and
supported by the PCC and University of Copenhagen.
We wish to thank our research assistant Maria Green
Schønfeldt for her thorough work with coding the CRFs.
References
[1] Christensen, H., Griffiths, K.M., and Farrer, L.
Adherence in internet interventions for anxiety and
depression. Journal of medical Internet research
11, 2 (2009), e13.
[2] Grünerbl, A., Oleksy, P., Bahle, G., Haring, C.,
Weppner, J., and Lukowicz, P. Towards smart
phone based monitoring of bipolar disorder.
Proceedings of the Second ACM Workshop on
Mobile Systems, Applications, and Services for
HealthCare - mHealthSys ’12, (2012), 1.
[3] Lederman, R., Wadley, G., Gleeson, J., Bendall, S.,
and Álvarez-Jiménez, M. Moderated online social
therapy. ACM Transactions on Computer-Human
Interaction 21, 1 (2014), 1–26.
[4] Løventoft, P.K., Nørregaard, L.B., and Frøkjær, E.
Designing daybuilder. Proceedings of the 12th
Participatory Design Conference on Exploratory
Papers Workshop Descriptions Industry Cases -
Volume 2 - PDC ’12, ACM Press (2012), 1.
Quotes from CRFs:
QB1: Positive, [it] provides an
opportunity to speak with others
about it in a better way. [I] could
see it relatively from regis-
trations, so a single bad period is
not taking up so much space”
QB2: “Frees time to speak with
my closest about other things.
There is control of symptoms.”
QB3: “I did not really gain
anything from using the program,
as twice daily was too demanding
on a computer. [I] miss more
notes under the parameters. An
app, with reminders if missing
medicine or registration.”
QB4: “Gives structure, a model
to explain condition, helps
memory, gives heightened
awareness”; “The program has
given a better overview, yes. But
negatively as the patient thinks it
is hard to see that mood is not
going up. “
QB5: “Aware of symptoms
(appetite, anxiety, mood) and
behavior + contact IAA. Good
idea with surveillance and contact
from clinician.
QB6: “Follow-ups have been
decisive for gain, as the phone
conversations have motivated me
to look at the graphs. Phone +
meetings, both when it is good
and bad feeling of safety from
knowing that others watch.”
Figure 5. Selected CRF quotes.
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Daybuilder is an experimental smartphone app intended to support people with depression. It was designed in collaboration with six participants who had all received antidepressant medication within the last two years. The Daybuilder prototype was field tested with the same six participants for three to four weeks. All participants were interested in using an application like Daybuilder, immediately or in the future if they were to suffer from depression again. The study has shown it possible to design a smartphone app that people with depression find interesting and potentially supportive in their daily lives and in their clinical treatment. In this project we chose to work directly with the depressive people, without involving clinicians, in an effort to get as close as possible to the participants' needs and concerns. This approach caused certain difficulties in recruitment, required adaptation of design activities, and consideration of certain ethical issues. The seriousness and prevalence of depression in society make it urgent as a next step to do a comprehensive study to clarify possible clinical effects of using smartphone apps for this special user group.
Article
Open access websites which deliver cognitive and behavioral interventions for anxiety and depression are characterised by poor adherence. We need to understand more about adherence in order to maximize the impact of Internet-based interventions on the disease burden associated with common mental disorders. The aims of this paper are to review briefly the adherence literature with respect to Internet interventions and to investigate the rates of dropout and compliance in randomized controlled trials of anxiety and depression Web studies. A systematic review of randomized controlled trials using Internet interventions for anxiety and depression was conducted, and data was collected on dropout and adherence, predictors of adherence, and reasons for dropout. Relative to reported rates of dropout from open access sites, the present study found that the rates of attrition in randomized controlled trials were lower, ranging from approximately 1 - 50%. Predictors of adherence included disease severity, treatment length, and chronicity. Very few studies formally examined reasons for dropout, and most studies failed to use appropriate statistical techniques to analyze missing data. Dropout rates from randomized controlled trials of Web interventions are low relative to dropout from open access websites. The development of theoretical models of adherence is as important in the area of Internet intervention research as it is in the behavioral health literature. Disease-based factors in anxiety and depression need further investigation.
Moderated online social therapy
  • R Lederman
  • G Wadley
  • J Gleeson
  • S Bendall
  • M Álvarez-Jiménez