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TRANSCRIPT
For peer review only
Feedback on SMS reminders to encourage adherence among
patients with psychosis: a cross-sectional survey nested
within a randomised trial
Journal: BMJ Open
Manuscript ID: bmjopen-2015-008574
Article Type: Research
Date Submitted by the Author: 22-Apr-2015
Complete List of Authors: Kannisto, Kati; University of Turku, Department of nursing Science; Satakunta Hospital District, Adams, Clive; University of Nottingham, Institute of Mental Health, Division
of Psychiatry Koivunen, Marita; Satakunta Hospital District, Katajisto, Jouko; University of Turku, Department of Mathematics and Statistics Välimäki, Maritta; University of Turku, Department of Nursing Science
<b>Primary Subject Heading</b>:
Mental health
Secondary Subject Heading: Health informatics
Keywords: MENTAL HEALTH, Information technology < BIOTECHNOLOGY & BIOINFORMATICS, Telemedicine < BIOTECHNOLOGY & BIOINFORMATICS
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Feedback on SMS reminders to encourage adherence among patients with psychosis: a cross-
sectional survey nested within a randomised trial
Kati Anneli Kannisto, BNSc, MNSc-student, PhD-student
Department of Nursing Science, University of Turku, Turku, Finland and Satakunta Hospital District
Pori, Finland
Clive E Adams, MD, Institute of Mental Health, Division of Psychiatry, University of Nottingham,
Nottingham, UK United Kingdom
Marita Koivunen, Nursing Director, Adjunct professor, PhD, Satakunta Hospital District Pori,
Finland and Department of Nursing Science, University of Turku, Turku, Finland
Jouko Katajisto, MsSocSc, lecturer, Department of Mathematics and Statistics, University of Turku,
Turku, Finland
Maritta Välimäki, Professor and Nursing Director, RN, PhD, Department of Nursing Science,
University of Turku, Turku, Finland and Turku University Hospital, Turku, Finland and Hong Kong
Polytechnic University, Hong Kong
Corresponding author:
Kati Anneli Kannisto
University of Turku
Department of Nursing Science
Lemminkäisenkatu 1
FI-20014 UNIVERSITY OF TURKU
Finland
Phone: +358 2 333 8401
Fax: +358 2 3338400
Email: [email protected]
KEY WORDS: Psychiatric Services, Text Messaging, Short Message Service, Reminder System,
Descriptive study, Questionnaire
Current: 2606 words (excluding title page, abstract, references, figures and tables)
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ABSTRACT
Objectives
To explore feedback regarding use of tailored SMS reminders in psychiatric outpatient care and
explore factors related to satisfaction.
Design
A cross-sectional survey nested within a nationwide randomized clinical trial ( “Mobile.Net”
ISRCTN: 27704027).
Setting
Psychiatric outpatient care in Finland.
Participants
403 of 558 (response rate 72%) adults with psychosis responded between September 2012 and
December 2013 after 12 months of SMS intervention.
Main outcome measure
Feedback was gathered with a structured questionnaire based on Technology Acceptance Model
(TAM) theory. Data were analysed by Pearson’s Chi-square test, binary logistic regression and
stepwise multiple regression analyses.
Results
Almost all participants (98%) found the SMS reminders easy to use and 87% felt that SMS did not
cause harm. About three quarters (72%) were satisfied with the SMS received, and 61% found it
useful. Divorced people were particularly prone to find SMS reminders useful (χ2=13.17, df=6,
P=0.04) and people seeking employment were more often ‘fully satisfied’ with the SMS compared
with other groups (χ2=10.82, df=4, P=0.029). People who were older at first contact with
psychiatric services were more often ‘fully satisfied’ than younger groups (OR=1.02, 95%
confidence interval 1.01 to 1.04, P=0.007).
Conclusion
Psychotic peoples’ feedback on SMS services in outpatient care encompasses considerable
variation depending on the persons’ socio-demographic factors and illness history. Each persons’
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needs should be taken into consideration but this form of communication is largely inexpensive,
acceptable – including to those of the older age range , malleable, and could be effective.
STRENGTHS AND LIMITATIONS OF THIS STUDY
• To our knowledge, this is the largest study exploring patients’ feedback about SMS
reminders, especially among people with psychosis.
• The questionnaire was based on the Technology Acceptance Model (TAM), which is a
useful theoretical model to understand and explain technology users’ behavior and its
implementation.
• More accurate validity testing is needed to ensure the validity and reliability of use of this
questionnaire for this specific study population.
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INTRODUCTION
Nonadherence is a concern regarding people with psychosis,[1-5]. Lack of adherence to
antipsychotic medication,[6] and poor attendance rates,[7] are both highly prevalent for people
living with schizophrenia. About half do not adhere to medication,[8-10] and 20%–36% miss
scheduled clinical appointments,[11, 12]. Negative attitudes towards antipsychotic medication,
stigma and concern regarding rehospitalization are frequently cited as causes,[13] and promotion
of adherence has been advocated on both health and economic grounds,[6, 13].
Short message service (SMS) text messages as part of mHealth services,[14], have shown potential
to improve adherence to medication,[15-17] and attendance for follow up,[18]. Use of SMS
prompts may improve patients’ self-management of illness,[19], social interactions,[20], subjective
attitude towards medication,[21] and the quality of life,[22]. Text messaging is easy to
undertake,[23], simple to use, inexpensive,[24], acceptable,[25, 26] and potentially useful,[16]. It
has, however, been questioned whether patients with severe mental disorders will interact with
technology because of difficulties with cognitive abilities,[27, 28] or a lack of willingness to engage
in mobile interventions,[29]. In other health care conditions daily SMS reminders did not work –
with no impact on adherence to oral contraceptive pills,[30], nor medication for acne,[31].
Despite doubts, people with serious mental disorders such as schizophrenia are already being
asked to use mobile phones as an aid to self-care. Phones are non-stigmatizing, familiar,[32], and
have acceptable qualities,[32]. Branson et al.,[7] found that people with mental health disorders
perceived SMS reminders as helpful, and no negative experiences were identified. Close to 100%
of people with mental health problems reported familiarity with SMS, easy access and confidence
with mobile phone use,[27]. In this patient group, 73-87% were already using mobile phones daily
with calls and text messaging being the two most common uses of the mobile phones,[34, 35].
Therefore, this group of health service users cannot be ignored while conducting person-centered
information and communication technology (ICT) research,[36].
The feedback of people living with an illness can make an important contribution to improve
healthcare,[37]. Increased emphasis on patients’ feedback reflects extensive investment in
collection and use of peoples’ experience to evaluate providers’ performance in healthcare,[38].
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Although text messaging has shown promise in health services, little research has been conducted
to evaluate service users’ experiences and satisfaction regarding the long-term use of SMS,[39].
Feedback from people living with psychosis is particularly scarce,[7, 21] and this feedback is
needed if there is to be user-driven utilization of mobile technology in daily life,[40]. Structuring
this feedback using Technology Acceptance Model (TAM),[41, 42] produces a frameworks by
which adoption and long-term utilization in the treatment processes can be considered,[43].
The aim of this cross-sectional survey was to explore feedback on tailored SMS reminders to
encourage patients’ adherence to medication and outpatient treatment for patients with
psychosis and to explore the associations related to feedback. For this exploration we used a
subset of data,[44] collected for a randomized controlled trial (“Mobile.Net” ISRCTN: 27704027)
conducted in 24 sites and 45 psychiatric hospital wards in Finland. People in the intervention
group (n=569) received tailored SMS reminders for 12 months (See more detailed Välimäki et
al.,[45]).
METHODS
Participants
569 people in the intervention group of the Mobile.Net trial aged 18–65 years, either sex,
antipsychotic medication on discharge from a psychiatric hospital, having a mobile phone, ability
to use the Finnish language, and given written informed consent. Written informed consent was
guaranteed,[45]. Data of 11 participants were excluded because of refusal after informed consent
(n=5), not fulfilling inclusion criteria (n=3), randomization error (n=1), and death (n=2). The total
remaining was 558 people.
Data collection
The data were collected between September 2012 and December 2013. One day before the
telephone call for a data collection, the researcher sent a text message to participants allowing
them to prepare for the upcoming call,[46, 47]. To optimize participation the researcher made
contact a maximum of two times in the following days (from 10am to 4pm, not on weekends). In
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the initial call people were told the reason for the call and informed about the study,[48], were
reminded that participation was voluntary and that they are able to stop the interview whenever
they wanted to do so. People who were not reached by telephone, received the questionnaire by
post with written information about the study and a pre-paid postal envelope.
Of 558 possible interviewees, 82 did not answer the call, 58 telephone numbers were
unobtainable (“the dialed number cannot be reached”), and for 48 people the telephone number
was not in use during the data collection. In two calls, another person other than the participant
answered the telephone. Finally 368 people were reached by telephone but eight refused to
participate. The remaining 190 received a blank questionnaire by post. Forty three people
returned these filled. This resulted in a response rate of 72% (403 of a possible 558).
Outcome measures
Data were collected with a five item structured questionnaire developed for the study. Questions
were based on existing literature regarding service users’ experiences and the Technology
Acceptance Model (TAM),[41, 42] exploring patients’ feedback of text-message service. TAM can
be used to link users’ perceived usefulness and perceived ease of use about information
technology to their acceptance of the technology,[42]. Based on our service user consultation,[49],
the instrument was kept short,[50, 51] and simple,[52] to allow it to be undertaken via
telephone,[48]. TAM has already been found to be useful in describing adoption of technology,[43,
53, 54] and explaining users’ behaviour in information technology implementation,[55].
Questions focused on
i. satisfaction regarding the SMS system (1 item) (see Dowshen et al. ,[23]);
ii. perceived usefulness (1 item) (see Branson et al.,[7])
iii. perceived ease of use (2 items) (see Dick et al. ,[56]); and
iv. participants’ intention to use the SMS system in the future (1 item) (see Ben Zeev et
al.,[57]).
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Responses to questions were dichotomous (1 = yes; 2 = no). If answers were uncertain (e.g. ”On
the other hand yes, on the other hand no” or ”yes at the beginning, no at the end”) an additional
option (3 = either yes/either no) was used.
Statistical analysis
Descriptive statistics (frequency, percentage, mean, standard deviation) were used to describe
participants’ characteristics. In addition, four geographical regions,[58] were formed based on the
location of the psychiatric hospital where people were recruited. The following sociodemographic
characteristics were included as predictors in logistic regression models: age, gender (male,
female), marital status (single, married, divorced, widowed), vocational education (none,
vocational training courses, primary vocational skill certificate, secondary vocational skill
certificate, university degree), employment status (employed, retired, homework/ self-employed,
student, job seeker), geographical region (Helsinki-Uusimaa, West Finland, South Finland, and
North and East Finland), and age at first contact in psychiatric services.
Participants’ feedback was calculated in two ways. First, answers to each individual item were
analysed using descriptive statistics. Second, patients were categorized as ‘fully satisfied’ (100%
positive answer to all five questions) and ‘other’ (not fully satisfied).
Differences between feedback between those who were fully satisfied compared with people who
were not for demographic characteristics (gender, marital status, vocational education,
employment status, geographical region) were analysed with Chi-square test. Dependences with
age and age at first contact in psychiatric services were analysed using Spearman correlation
coefficients. Binary logistic regression analysis followed to describe the relationship between
demographic characteristics and a categorical dependent variable (fully vs. not fully satisfied).
Further, stepwise multiple regression analyses were conducted to explore whether satisfaction
with the SMS could be predicted by demographic characteristics. Stepwise forward selection
procedure was used to build the most parsimonious prediction model using SPSS version 21,[59].
Imputation was not used to manage missing values. P-value < 0.05 was interpreted as a
statistically significant difference. The Kuder-Richardson 20 (KR-20) coefficient for dichotomous
variables was used to assess the internal consistency of the questionnaire indicating that the
questionnaire was reliable (KR-20 .68).
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RESULTS
A total of 403 participants (179, 44% male), responded to the questionnaire. Mean age was 39.7
years (SD 12.8, range 18 to 65). About half (47%) were single (30% married, 20% divorced, 3%
widowed) and almost one third (28%) had no vocational education (11% had university degree,
61% had variety of vocational training courses) and 50% were retired. Based on the regional
categorization, about one third of the participants lived in North and East Finland (37%), 29% in
South Finland, 26% were in Helsinki-Uusimaa and 9% in West Finland. Participants’ mean age at
first contact within psychiatric services was 28.2 years (SD 12.1).
Almost all participants (98%) found the SMS reminders easy to use and 87% felt that SMS did not
cause harm (see Table 1). About three quarters (72%) were satisfied with the SMS received, and
61% found it useful although some were ambivalent. Overall two thirds of participants (64%)
stated that they would like to use the SMS system in the future. Almost half of the 403
participants (46%) were fully satisfied with the SMS system (providing 100% positive feedback).
Table 1. Participants’ feedback on SMS
Items Yes (%) No (%) Ambivalent (%)
Satisfaction - "Have you been satisfied with the text messages?" 274 (72) 85 (22) 24 (6)
Usefulness - "Were the text messages useful?" 236 (61) 121 (32) 26 (7)
Easiness - "Were the text messages easy to use?" 392 (98) 8 (2) ––
Harm - "Did the text messages cause any harm to you?" 350 (87) 51 (13) ––
Future use - "Would you use this kind of text message system in the future?" 247 (64) 138 (36) ––
People who were divorced found SMS reminders useful more often than single people (75% vs
60%), married (75% vs 54%) or widowed (75% vs 60%), respectively (χ2=13.17, df=6, P=0.04).
Women perceived the SMS reminders to be harmful more often than men (16 % vs. 9 %, χ2=4.01,
df=1, P=0.045). Of all different background characteristics, job seekers were more often fully
satisfied with the SMS comparing to other groups (Table 2).
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Table 2. Differences between participants in their satisfaction with SMS reminders
Demographic characteristics Fully satisfied
(%)
Not fully satisfied (%) P value
(χ2, df)
Gender
Male
Female
86/179 (48)
100/224 (45)
93/179 (52)
124/224 (55)
0.496
(χ2=0.46, df=1)
Marital status
Single
Married
Divorced
Widowed
86/188 (40)
49/122 (40)
44/81 (54)
5/10 (50)
102/188 (60)
73/122 (60)
37/81 (46)
5/10 (50)
0.262
(χ2=4.00, df=3)
Vocational education
None
Vocational training courses
Primary vocational skill certificate
Secondary vocational skill certificate
University degree
49/110 (44)
38/69 (55)
60/117 (51)
18/58 (31)
19/43 (44)
61/110 (56)
31/69 (45)
57/117 (49)
40/58 (69)
24/43 (56)
0.062
(χ2=8.95, df=4)
Employment status
Employed
Retired
Homework/ self-employed
Student
Job seeker
31/76 (41)
93/196 (47)
2/11 (18)
13/40 (32)
41/72 (57)
45/76 (59)
103/196 (53)
9/11(82)
27/40 (68)
31/72 (43)
0.029*
(χ2=10.82, df=4)
Geographical categorization (NUTS)
West Finland
Helsinki-Uusimaa
South Finland
North and East Finland
23/36 (64)
50/104 (48)
50/115 (43)
63/148 (43)
13/36 (36)
54/104 (52)
65/115 (57)
85/148 (57)
0.121
(χ2=5.80, df=3)
*Statistically significant (P<0.05) by Chi Square test
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Participants recruited in hospitals located in Western Finland were most often fully satisfied with
the SMS system compared to those recruited in other Finnish regions (P=0.048) (Table 3).
Table 3. Associations with participants’ demographic characteristics and feedback
Demographic characteristics OR (95% CI) P value
Age 1.01 (0.99 to 1.04) 0.319
Gender
Male (as reference category)
Female 1.11 (0.71 to 1.72) 0.657
Marital status
Single (as reference category) 0.301
Divorced 0.60 (0.34 to 1.06) 0.077
Married 0.95 (0.50 to 1.79) 0.873
Widowed 0.74 (0.17 to 3.22) 0.686
Vocational education
None (as reference category) 0.126
Vocational training courses 1.11 (0.56 to 2.19) 0.767
Primary vocational skill certificate 1.09 (0.61 to 1.95) 0.778
Secondary vocational skill certificate 0.44 (0.21 to 0.93) 0.033
University degree 1.00 (0.46 to 2.18) 0.996
Employment status
Employed (as reference category) 0.157
Retired 1.18 (0.64 to 2.18) 0.605
Homework/ self-employed 0.46 (0.09 to 2.43) 0.36
Student 0.88 (0.36 to 2.15) 0.775
Job seeker 1.97 (0.97 to 4.01) 0.059
Geographical categorization (NUTS)
West Finland (as reference category) 0.048
Helsinki-Uusimaa 0.49 (0.21 to 1.16) 0.105
South Finland 0.33 (0.14 to 0.76) 0.01
North and East Finland 0.36 (0.16 to 0.83) 0.016
Age at first contact in psychiatric services 1.02 (1.00 to 1.05) 0.08
Participants’ age at first contact in psychiatric services predicted their satisfaction (OR=1.02, 95%
confidence interval 1.01 to 1.04, P=0.007) (Table 4). The older people were at first contact with
psychiatric services, the more often they were fully satisfied with the SMS system. Geographical
categorization,[58] approached conventional levels of statistical significance as a predictor
(P=0.07).
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Table 4. Association with participants’ age at first contact in psychiatric services and feedback
Demographic characteristic OR (95% CI) P value
Age at first contact in psychiatric services 1.02 (1.01 to 1.04) 0.007
DISCUSSION
This study explored patients’ feedback for tailored SMS reminders in psychiatric outpatient care in
Finland. Our study provides deeper insight – and reassurance - for health care personnel and
policymakers regarding what issues should be taken into consideration when individually tailoring
ICT methods to encourage treatment adherence for people with psychosis in order to support self-
management and improving psychiatric outpatient care.
To our knowledge, this is the largest study exploring patients’ feedback about SMS reminders. Our
sampling secured participation from people who received SMS reminders for 12 months. This
group consisted of people living with psychosis, not only schizophrenia, and in this way improves
generalisability to psychiatric outpatient care contexts. In surveys of people with psychotic
disorders low response rates are a major problem,[60]. Using the data from within a trial,
however, considerably increased the usual rates of around or less than 50% to our 72%,[61]. For
this group, telephone survey seems to be usable method to collect data on participant
feedback,[48].
However, although our response rate was high, 28% of those invited to participate declined to do
so. This may have biased our sample. Secondly, the questionnaire was based on the Technology
Acceptance Model (TAM),[41, 42], which is a useful theoretical model to understand and explain
technology users’ behavior and its implementation. More accurate validity testing is needed to
ensure the validity and reliability of use of this questionnaire for this specific study population.
Finally, more men tend to carry the diagnosis of psychosis and be treated with psychosis (53%,
Finnish National Institute of Health and Welfare 2015,[62]). In our data, male patients seem to be
under represented (44%) and selection-bias may have been operating.
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Previous studies have shown that SMS were easy to use,[63], did not cause any harm,[7, 64, 65],
and resulted in high levels of satisfaction,[66]. We concur with these findings. For people with
psychosis SMSs are a feasible and acceptable method of sending reminders. A small minority of
this paranoid group thought thought that SMS caused harm. That the greater proportion of this
group were women (16% vs 9%) is surprising, since women are known to use SMS more than
men,[67], although women tend to prefer to use their mobile phones for making phone calls,[68].
Our study did not confirm the suspicion that people with serious mental health illnesses are not
capable of using technology-based SMS interventions,[28]. Our results are, therefore, promising in
this under-researched area,[7, 21].
People living with mental health problems are often socially isolated and may not have relatives,
friends, or caregivers to remind them to take their medication,[13]. We found that divorced
participants found SMS reminders more useful compared with other marital status groups.
Divorced people may be more lacking in support of their treatment adherence. We also found that
people seeking jobs were more often fully satisfied with the SMS comparing with other groups.
People with severe mental health disorders are 6–7 times more likely to be unemployed than
people without mental health problems,[69]. It could be truly important that an intervention may
have been found which may be particularly acceptable to this group of people. Self-neglect is
common. Men with schizophrenia have a life-expectancy about 20 years shorter than men in the
general population. All acceptable methods to encourage self-care and self-management in this
group are most welcome,[70].
Contrary to previous studies, where young people are referred to as “digital natives” using
information and communication technologies (ICTs) in their daily lives,[71, 72], in our data,
participants whose first contact with psychiatric services was when they were older were most
often fully satisfied with SMS reminders. A simple, one-way SMS reminder system – as used in our
study - could be suitable for an aging population,[73], while younger groups may want to use a
more interactive system,[74], such as games,[75]. However, we are reluctant to take this as an
absolute. Health games or other internet interventions have problems with engagement,[76, 77].
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People under 44 years still use mobile telephones for texting more than for calls,[78] while older
adults report a wide variety of use of technology, including mobile telephones,[73].
Our findings are important in the light of recent international and national guidelines related to
equality in health services. Although patients’ equality has been emphasized globally,[79, 80], and
nationally,[81], there is still high regional variation in medication and involuntary treatment in, for
example, Finland,[82, 83]. In our study satisfaction with SMS reminders also varied according to
geographical region (more often fully satisfied in West Finland). This may, however, reflect
services in general - for example seclusion rates are lower in West Finland than compared with
mean rates in Finland as a whole,[62].
CONCLUSIONS AND IMPLICATIONS
The generally positive feedback and satisfaction with SMS reminders may indicate possibilities for
use of tailored mHealth interventions in psychiatric outpatient care. We think it important to listen
to feedback and that this may affect the acceptance of technology in routine care.
Our results largely endorse that emphasizing the use of simple, already existing technology, such
as mobile phones and SMS,[84], may be an acceptable method in psychiatric outpatient services.
This is in line with our previously published literature review, which showed a wide use of SMS
reminders in different health care services,[85]. The Mobile.Net randomized trial will evaluate the
effects of one particular SMS system, but this feedback study does suggest that this media may
have much to offer in supporting people in an acceptable way, inexpensively, over great distances.
There is, however, a risk that healthcare providers use SMS as a way of shifting their responsibility
to the patient which may promote insufficient follow-up,[64]. This could be a harmful
consequence. Insufficient follow-up can result in non-attendance in vulnerable groups who are
particularly unwell and socially impaired,[86] and at risk of hospitalization,[87]. We need to
understand the possible risks of implementation of SMS interventions,[39], whilst emphasizing the
importance of service users’ participation and feedback,[38].
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FOOTNOTES
Acknowledgments: We thank the patients, staff in participating research organisations and
research assistants who kindly agreed to participate in this study without whom the study would
not have been possible. Thanks also to Kaisa Kauppi, Tella Lantta, Laura Yli-Seppälä and Sanna Suni
for their invaluable help with data collection and data entry. We also thank the Mobile.Net Safety
Committee Group for their input and support throughout this study.
Contributors: KAK carried out the literature review and data collection, wrote the statistical
analysis plan, conducted the descriptive data analyses, drafted and revised the paper. CEA and MK
drafted and revised the paper. JK conducted statistical analyses, assisted to interpret the analysis,
drafted and revised the paper. MV designed the study, wrote the statistical analysis plan, provided
scientific supervision, oversaw the conduct of the study, and drafted and revised the manuscript.
All authors contributed to and have approved the final manuscript.
Funding: This work was supported by The Academy of Finland (132581), Turku University Hospital
(EVO 13893), Satakunta Hospital District (EVO 12/2010, 81096), Foundations’ Professor Pool,
Finnish Cultural Foundation and the University of Turku.
Competing interests: None declared. All authors have completed the ICMJE uniform disclosure
form at www.icmje.org/coi_disclosure.pdf and declare: this work was supported by The Academy
of Finland (132581), Turku University Hospital (EVO 13893), Satakunta Hospital District (EVO
12/2010, 81096), Foundations’ Professor Pool, Finnish Cultural Foundation, and the University of
Turku; no financial relationships with any organisations that might have an interest in the
submitted work in the previous three years; no other relationships or activities that could appear
to have influenced the submitted work.
Ethical approval: Approval for the study (Mobile.Net) was obtained from the Ethics Committee of
the Hospital District of Southwest Finland on 16 December 16 2010 (ref; ETMK 109/180/2010).
Permission to conduct the study was guaranteed by each hospital organization. Patients gave their
consent before their recruitment to the Mobile.Net study. Answer to the questionnaire by
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telephone or the return of a completed questionnaire was taken to indicate patients’ consent to
participate in this cross-sectional survey study.
Data sharing: No additional data available. This cross-sectional survey is a part of a randomized
clinical trial (“Mobile.Net” ISRCTN: 27704027).
This is an Open Access article distributed in accordance with the Creative Commons Attribution
Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build
upon this work non-commercially, and license their derivative works on different terms, provided
the original work is properly cited and the use is non-commercial. See:
http://creativecommons.org/licenses/by-nc/4.0/.
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STROBE 2007 (v4) checklist of items to be included in reports of observational studies in epidemiology*
Checklist for cohort, case-control, and cross-sectional studies (combined)
Section/Topic Item # Recommendation Reported on page #
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract Title page, p. 1
(b) Provide in the abstract an informative and balanced summary of what was done and what was found Abstract, p. 2
Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported p. 4-5
Objectives 3 State specific objectives, including any pre-specified hypotheses p. 5
Methods
Study design 4 Present key elements of study design early in the paper p. 5
Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data
collection p. 5-7
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe
methods of follow-up
Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control
selection. Give the rationale for the choice of cases and controls
Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants
p. 6
(b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed
Case-control study—For matched studies, give matching criteria and the number of controls per case
Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic
criteria, if applicable p. 7
Data sources/ measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe
comparability of assessment methods if there is more than one group p. 7
Bias 9 Describe any efforts to address potential sources of bias
Study size 10 Explain how the study size was arrived at p. 6
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen
and why p. 7-8
Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding p. 7-8
(b) Describe any methods used to examine subgroups and interactions p. 7-8
(c) Explain how missing data were addressed p. 8
(d) Cohort study—If applicable, explain how loss to follow-up was addressed
Case-control study—If applicable, explain how matching of cases and controls was addressed
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Kannisto K et al. Feedback on SMS reminders to encourage adherence among patients with psychosis: a cross-sectional survey nested within a randomised trial
Cross-sectional study—If applicable, describe analytical methods taking account of sampling strategy
(e) Describe any sensitivity analyses
Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility,
confirmed eligible, included in the study, completing follow-up, and analysed p. 6, 8
(b) Give reasons for non-participation at each stage p. 6
(c) Consider use of a flow diagram
Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and
potential confounders p. 6
(b) Indicate number of participants with missing data for each variable of interest p. 8-11
(c) Cohort study—Summarise follow-up time (eg, average and total amount)
Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time
Case-control study—Report numbers in each exposure category, or summary measures of exposure
Cross-sectional study—Report numbers of outcome events or summary measures p. 8-11
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95%
confidence interval). Make clear which confounders were adjusted for and why they were included p. 8-11
(b) Report category boundaries when continuous variables were categorized p. 8-11
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses
Discussion
Key results 18 Summarise key results with reference to study objectives p. 12
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction
and magnitude of any potential bias p. 12
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results
from similar studies, and other relevant evidence p. 12-14
Generalisability 21 Discuss the generalisability (external validity) of the study results p. 12
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on
which the present article is based p. 15
*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE
checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.
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Feedback on SMS reminders to encourage adherence among
patients having antipsychotic medication: a cross-sectional
survey nested within a randomised trial
Journal: BMJ Open
Manuscript ID: bmjopen-2015-008574.R1
Article Type: Research
Date Submitted by the Author: 21-Aug-2015
Complete List of Authors: Kannisto, Kati; University of Turku, Department of nursing Science; Satakunta Hospital District, Adams, Clive; University of Nottingham, Institute of Mental Health, Division
of Psychiatry Koivunen, Marita; Satakunta Hospital District, Katajisto, Jouko; University of Turku, Department of Mathematics and Statistics Välimäki, Maritta; University of Turku, Department of Nursing Science
<b>Primary Subject Heading</b>:
Mental health
Secondary Subject Heading: Health informatics
Keywords: MENTAL HEALTH, Information technology < BIOTECHNOLOGY & BIOINFORMATICS, Telemedicine < BIOTECHNOLOGY & BIOINFORMATICS, Psychiatric Services, Text Messaging
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Feedback on SMS reminders to encourage adherence among patients having antipsychotic
medication: a cross-sectional survey nested within a randomised trial
Kati Anneli Kannisto, MNSc, Doctoral Candidate
Department of Nursing Science, University of Turku, Turku, Finland and Satakunta Hospital District
Pori, Finland
Clive E Adams, MD, Institute of Mental Health, Division of Psychiatry, University of Nottingham,
Nottingham, UK United Kingdom
Marita Koivunen, Nursing Director, Adjunct professor, PhD, Satakunta Hospital District Pori,
Finland and Department of Nursing Science, University of Turku, Turku, Finland
Jouko Katajisto, MsSocSc, lecturer, Department of Mathematics and Statistics, University of Turku,
Turku, Finland
Maritta Välimäki, Professor and Nursing Director, RN, PhD, Department of Nursing Science,
University of Turku, Turku, Finland and Turku University Hospital, Turku, Finland and Hong Kong
Polytechnic University, Hong Kong
Corresponding author:
Kati Anneli Kannisto
University of Turku
Department of Nursing Science
Lemminkäisenkatu 1
FI-20014 UNIVERSITY OF TURKU
Finland
Phone: +358 2 333 8401
Fax: +358 2 3338400
Email: [email protected]
KEY WORDS: Psychiatric Services, Text Messaging, Short Message Service, Reminder System,
Descriptive study, Questionnaire
Current: 3712 words (excluding title page, abstract, references, figures and tables)
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ABSTRACT
Objectives
To explore feedback on tailored SMS reminders to encourage medication adherence and
outpatient treatment among patients having antipsychotic medication and associations related to
the feedback.
Design
A cross-sectional survey nested within a nationwide randomized clinical trial (“Mobile.Net”
ISRCTN: 27704027).
Setting
Psychiatric outpatient care in Finland.
Participants
403 of 558 adults with psychosis responded between September 2012 and December 2013 after
12 months of SMS intervention.
Main outcome measure
Feedback was gathered with a structured questionnaire based on Technology Acceptance Model
(TAM) theory. Data were analysed by Pearson’s Chi-square test, binary logistic regression and
stepwise multiple regression analyses.
Results
Almost all participants (98%) found the SMS reminders easy to use and 87% felt that SMS did not
cause harm. About three quarters (72%) were satisfied with the SMS received, and 61% found it
useful. Divorced people were particularly prone to find SMS reminders useful (χ2=13.17, df=6,
P=0.04) and people seeking employment were more often ‘fully satisfied’ with the SMS compared
with other groups (χ2=10.82, df=4, P=0.029). People who were older at first contact with
psychiatric services were more often ‘fully satisfied’ than younger groups (OR=1.02, 95%
confidence interval 1.01 to 1.04, P=0.007).
Conclusion
The feedback of patients having antipsychotic medication on SMS services was generally positive.
Overall, people were quite satisfied despite considerable variation in their socio-demographic
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background and illness history. Our results endorse that the use of simple easy-to-use existing
technology, such as mobile phones and SMS, is acceptable in psychiatric outpatient services.
Moreover, people using psychiatric outpatient services are able to use this technology. This
acceptable and accessible technology can be easily tailored to each patient’s needs and could be
customized to the needs of the isolated or jobless. This is an area in which much careful evaluation
is needed.
STRENGTHS AND LIMITATIONS OF THIS STUDY
• To our knowledge, this is the largest study exploring feedback on SMS reminders among
patients having antipsychotic medication.
• The questionnaire was based on the Technology Acceptance Model (TAM), which is a
useful theoretical model to understand and explain technology users’ behavior and its
implementation.
• More accurate validity testing is needed to ensure the validity and reliability of use of this
questionnaire for this specific study population.
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INTRODUCTION
Medication nonadherence is a common concern regarding people with mental health problems,[1-
5]. Nonadherence to antipsychotic medication,[6] and poor attendance rates at mental health
outpatient clinics,[7] have been found to be highly prevalent for these people,[6, 7], especially for
people living with schizophrenia,[8], which is the severest form of psychosis,[9]. About half do not
adhere to antipsychotic medication, nonadherence rates varying between 47.5–55.8%,[10, 11],
and 20%–36% miss scheduled clinical outpatient appointments,[12, 13]. Negative attitudes
towards antipsychotic medication, stigma and concern regarding rehospitalization are frequently
cited as causes,[14] and promotion of adherence has been advocated on both health and
economic grounds,[6, 15].
Short message service (SMS) text messages as part of mHealth services,[15], have shown potential
to improve adherence to antipsychotic medication,[16, 17] and attendance for mental health
outpatient appointments,[13]. Use of SMS prompts may improve patients’ self-management of
illness,[16, 18], social interactions, subjective attitude towards antipsychotic medication, and the
quality of life,[17]. Text messaging is easy to undertake and use,[19, 20], it is inexpensive,[21], and
acceptable,[20, 22]. It has, however, been questioned whether patients having antipsychotic
medication, such as people living with schizophrenia will interact with technology because of
difficulties with cognitive abilities,[23, 24] or a lack of willingness to engage in mobile
interventions,[25]. In other health care conditions daily SMS reminders did not work – with no
impact on adherence to oral contraceptive pills,[26], nor medication for acne,[27].
Despite doubts, people with serious mental disorders such as schizophrenia are already being
asked to use mobile phones as an aid to self-care. Phones are non-stigmatizing, familiar,[28], and
have acceptable qualities,[19]. Ben-Zeev et al.,[20] found that people with serious mental health
disorders perceived SMS reminders as helpful. No negative experiences were identified,[20]. Close
to 100% of people with serious mental health problems reported owning or using a mobile
phone,[29, 30], whereas 59% reported using the Internet,[29]. They also reported familiarity with
SMS, easy access and confidence with mobile phone use,[20]. Over 70% of psychiatric patients
reported their phone to be a smart phone,[30], enabling the use of smart phone interventions,
such as applications for monitoring symptoms of mental health conditions in real time,[30-32] to
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be used in mental health services. Over 50% of psychiatric patients indicated their interest to use
mobile phone applications,[30], whereas 73-87% were already using mobile phones daily with
calls and text messaging being the two most common uses of the mobile phones,[33, 34].
Therefore, this group of health service users cannot be ignored while conducting person-centered
information and communication technology (ICT) research,[35].
The feedback of people living with an illness can make an important contribution to improve
healthcare,[36]. Increased emphasis on patients’ feedback reflects extensive investment in
collection and use of peoples’ experience to evaluate providers’ performance in healthcare,[37].
Although text messaging has shown promises in health services,[13, 16, 17], and proved to be
feasible and acceptable among patients with mental health problems,[19, 20], little research has
been conducted to evaluate service users’ experiences and satisfaction regarding the long-term
use (study periods 12 months or longer) of SMS,[38]. This feedback is needed if there is to be user-
driven utilization of mobile technology in daily life,[39]. Structuring this feedback using Technology
Acceptance Model (TAM),[40, 41] produces a frameworks by which adoption and long-term
utilization in the treatment processes can be considered,[42].
The aim of this cross-sectional survey was to explore feedback on tailored SMS reminders to
encourage medication adherence and outpatient treatment among patients having antipsychotic
medication, and to explore the associations related to the feedback. People in the intervention
group (n=569) received tailored SMS reminders for 12 months (See more detailed Välimäki et al.
2012,[43]).
METHODS
Participants
To explore patients’ feedback we used a subset of data,[44] collected for a multicenter
randomized controlled two-armed trial (“Mobile.Net” ISRCTN: 27704027) conducted in 24 sites
and 45 psychiatric hospital wards in Finland,[43]. 569 people in the intervention group of the
Mobile.Net trial were included in the survey. The inclusion criteria were as follows: age of 18–65
years, either sex, having antipsychotic medication on discharge from a psychiatric hospital, having
a mobile phone, and able to use the Finnish language. Written informed consent was guaranteed.
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Exclusion criteria were as follows: patients who had a planned nonacute treatment period or were
treated in forensic psychiatric services,[43]. During the trial, the participants received tailored SMS
reminders for 12 months,[43]. The most commonly selected messages from the three main topics
(medication, treatment appointment and free time) were as follows: “Have you taken your
medication - feel well”, “It is important to comply with your follow-up appointment, isn't it?” and
“Get up, go out and exercise”. Participants preferred to receive messages 1–6 times per month, at
the beginning of the week (Monday and Tuesday) and in the morning time (6am–12pm) (see more
detailed Kauppi et al. 2015,[45]).
Data collection
The data concerning participants’ feedback on SMS reminders were collected between September
2012 and December 2013. One day before the telephone call for a data collection, the researcher
(i.e. members of the Mobile.Net research group, not including clinical staff) sent a text message to
participants allowing them to prepare for the upcoming call,[46, 47]. To optimize participation the
researcher made contact a maximum of two times in the following days (from 10am to 4pm, not
on weekends). In the initial call people were told the reason for the call and informed about the
study,[48], were reminded that participation was voluntary and that they were able to stop the
interview whenever they wanted to do so. Those who were not reached by telephone, received
the questionnaire by post with written information about the study and a pre-paid postal
envelope.
After detailed data checking, the data of 11 participants (out of 569 participants) were excluded
due to the refusal after informed consent (n=5), not fulfilling inclusion criteria (n=3),
randomization error (n=1), and death (n=2). The total remaining was 558 people. Of 558 possible
interviewees, 82 did not answer the call, 58 telephone numbers were unobtainable for example
due to a switched off mobile phone (“the dialed number cannot be reached”), and for 48 people
the telephone number was not in use during the data collection. In two calls, another person other
than the participant answered the telephone. Finally 368 people were reached by telephone but
eight refused to participate. The remaining 190 received a blank questionnaire by post. Forty three
people returned these filled. This resulted in a response rate of 72% (403 of a possible 558).
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Outcome measures
Data were collected with a five item structured questionnaire developed for the study. Questions
were based on existing literature regarding service users’ experiences and the Technology
Acceptance Model (TAM),[40, 41] exploring patients’ feedback of text-message service. TAM can
be used to link users’ perceived usefulness and perceived ease of use about information
technology to their acceptance of the technology,[41]. Based on our service user consultation,[49],
the instrument was kept short,[50, 51] and simple,[52] to allow it to be undertaken via
telephone,[48]. TAM has already been found to be useful in describing adoption of technology,[42,
53, 54] and explaining users’ behaviour in information technology implementation,[55].
Questions focused on
i. satisfaction regarding the SMS system (1 item) (see Dowshen et al. ,[56]);
ii. perceived usefulness (1 item) (see Branson et al.,[57])
iii. perceived ease of use (2 items) (see Dick et al. ,[58]); and
iv. participants’ intention to use the SMS system in the future (1 item) (see Ben Zeev et
al.,[59]).
Responses to questions were dichotomous (1 = yes; 2 = no). If answers were uncertain (e.g. ”On
the other hand yes, on the other hand no” or ”yes at the beginning, no at the end”) an additional
option (3 = either yes/either no) was used.
Statistical analysis
Descriptive statistics (frequency, percentage, mean, standard deviation) were used to describe
participants’ characteristics. In addition, four geographical regions,[60] were formed based on the
location of the psychiatric hospital where people were recruited. To analyse where any evidence
of selective dropout existed in the data (i.e. difference between participants who could not be
reached by phone), the demographic characteristics between respondents and non-respondents
(i.e. those who answered to the survey questionnaire and those who did not), we used
independent samples t test for continuous variables and Chi Square test (χ2) for categorical
variables. The following sociodemographic characteristics were included as predictors in logistic
regression models: age, gender (male, female), marital status (single, married, divorced,
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widowed), vocational education (none, vocational training courses, primary vocational skill
certificate, secondary vocational skill certificate, university degree), employment status
(employed, retired, homework/ self-employed, student, job seeker), geographical region (Helsinki-
Uusimaa, West Finland, South Finland, and North and East Finland), and age at first contact in
psychiatric services.
Participants’ feedback was calculated in two ways. First, answers to each individual item were
analysed using descriptive statistics. Second, patients were categorized as ‘fully satisfied’ (100%
positive answer to all five questions) and ‘other’ (not fully satisfied).
Differences between feedback between those who were fully satisfied compared with people who
were not for demographic characteristics (gender, marital status, vocational education,
employment status, diagnosis (ICD 10,[61]), geographical region) were analysed with Chi-square
test. Dependences with age and age at first contact in psychiatric services were analysed using
Spearman correlation coefficients. Binary logistic regression analysis followed to describe the
relationship between demographic characteristics and a categorical dependent variable (fully vs.
not fully satisfied). Further, stepwise multiple regression analyses were conducted to explore
whether satisfaction with the SMS could be predicted by demographic characteristics. Stepwise
forward selection procedure was used to build the most parsimonious prediction model using
SPSS version 21,[62]. Imputation was not used to manage missing values. P-value < 0.05 was
interpreted as a statistically significant difference. The Kuder-Richardson 20 (KR-20) coefficient for
dichotomous variables was used to assess the internal consistency of the questionnaire indicating
that the questionnaire was reliable (KR-20 .68).
RESULTS
A total of 403 participants (179, 44% male), responded to the questionnaire. Mean age was 39.7
years (SD 12.8, range 18 to 65). About half (47%) were single (30% married, 20% divorced, 3%
widowed) and almost one third (28%) had no vocational education (11% had a university degree,
61% had a variety of vocational training courses) and 50% were retired. The most common
psychiatric diagnoses (ICD 10,[61]) were F20-F29: schizophrenia, schizotypal and delusional
disorders (38%) and F30-F39: mood [affective] disorders (29%), other 33% were minor (more
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detailed description in Table 1). Based on the regional categorization, about one third of the
participants lived in North and East Finland (37%), 29% in South Finland, 26% were in Helsinki-
Uusimaa and 9% in West Finland. Participants’ mean age at first contact within psychiatric services
was 28.2 years (SD 12.1). Less than half of the participants (43%) had a neuroleptic medication,
following neuroleptic and antidepressant medication together (36%), antidepressant medication
(6%) and other psychiatric medication (5%). Medication information was missing for 10% of the
participants.
Participants who did not answer to the survey questionnaire (n=155, 28%) were younger
(P<0.001), most often male (P=0.014, χ2=6.16, df=1), had no vocational education (P=0.027,
χ2=10.96, df=4), and came younger to their first contact in psychiatric services (P=0.003) when
compared to participants, who answered to the survey questionnaire (n = 403) (Table 1).
Table 1. Comparison of demographic characteristic of the respondents (N = 403) and
nonrespondents (N = 155)
Demographic characteristics n (%) Respondent
n=403
Nonrespondent
n=155
P value
(χ2, df)
Age, mean (SD)
Range
39,7 (12,8)
18-65
35,4 (12,0)
18-64
<0.001
Gender, n (%)
Male
Female
179 (44)
224 (56)
87 (56)
68 (44)
0.014*
(χ2=6.16, df=1)
Marital status, n (%)
Single
Married
Divorced
Widowed
188 (47)
122 (30)
81 (20)
10 (3)
85 (55)
28 (18)
36 (23)
4 (3)
0.039*
(χ2=8.29, df=3)
Vocational education, n (%)
None
Vocational training courses
Primary vocational skill certificate
Secondary vocational skill certificate
University degree
Missing information
110 (27)
59 (17)
117 (29)
58 (14)
43 (11)
6 (2)
63 (40)
20 (13)
41 (27)
20 (13)
9 (6)
2 (1)
0.027*
(χ2=10.96, df=4)
Employment status, n (%)
Employed
Retired
Homework/ self-employed
Student
Job seeker
Missing information
76 (19)
196 (49)
11 (3)
40 (10)
72 18)
8 (2)
29 (19)
67 (43)
4 (3)
19 (12)
35 (23)
1 (<1)
0.639
(χ2=2.54, df=4)
Diagnose (ICD-10), n (%) 0.134
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F00-F091
F10-F192
F20-F293
F30-F394
F40-F495
F50-F596
F60-F697
F70-F798
F80-F899
F90-F9810
Diagnose missing
1 (<1)
13 (3)
154 (38)
115 (29)
35 (9)
1 (<1)
48 (12)
3 (<1)
2 (<1)
1 (<1)
30 (7)
–
16 (10)
56 (36)
40 (26)
11 (7)
–
22 (14)
1 (<1)
1 (<1)
–
8 (5)
(χ2=13.1, df=9)
Geographical categorization (NUTS), n (%)
West Finland
Helsinki-Uusimaa
South Finland
North and East Finland
36 (9)
104 (26)
115 (28)
148 (37)
16 (10)
44 (28)
52 (34)
43 (28)
0.252
(χ2=4.09, df=3)
Age at first contact in psychiatric services, mean (SD)
Range
28,2 (12,1)
3-64
25,2 (10,1)
3-52
0.003
*Statistically significant (P<0.05) by Chi Square test and T-test 1 Organic, including symptomatic, mental disorders
2 Mental and behavioral disorders due to psychoactive substance use
3 Schizophrenia, schizotypal and delusional disorders
4 Mood [affective] disorders
5 Neurotic, stress-related and somatoform disorders
6 Behavioral syndromes associated with physiological disturbances and physical factors
7 Disorders of adult personality and behavior
8 Mental retardation
9 Disorders of psychological development
10 Behavioural and emotional disorders with onset usually occurring in childhood and adolescence
Almost all participants (98%) found the SMS reminders easy to use and 87% felt that SMS did not
cause harm (see Table 2). About three quarters (72%) were satisfied with the SMS received, and
61% found it useful although some were ambivalent. Overall two thirds of participants (64%)
stated that they would like to use the SMS system in the future. Almost half of the 403
participants (46%) were fully satisfied with the SMS system (providing 100% positive feedback).
Table 2. Participants’ feedback on SMS (n=403)
Items Yes (%) No (%) Ambivalent (%)
Satisfaction - "Have you been satisfied with the text messages?" 274 (72) 85 (22) 24 (6)
Usefulness - "Were the text messages useful?" 236 (61) 121 (32) 26 (7)
Easiness - "Were the text messages easy to use?" 392 (98) 8 (2) ––
Harm - "Did the text messages cause any harm to you?" 51 (13) 350 (87) ––
Future use - "Would you use this kind of text message system in the future?" 247 (64) 138 (36) ––
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Out of the total sample (N=558) 70% found the SMS reminders easy to use, and 63% felt that SMS
did not cause any harm. Almost half of the participants (49%) were satisfied with the SMS
received, and 42% found it useful. Slightly less than half of the participants (44%) were interested
to use the SMS intervention in the future. One third of the participants (33%) were fully satisfied
with the SMS system.
Participants selected a mean number of 10 messages per month (range 2–25),[45]. There were no
statistically significant differences (P>0.05) related to the amount of selected text messages and
participants’ feedback on SMS reminders. Further, there were no statistically significant
differences (P>0.05) when comparing participants’ feedback on SMS reminders between
participants with schizophrenia (F20-F29) and participants with other psychiatric diagnoses (other
than F20-F29).
Out of 403, a total amount of 51 (13%) participants were in opinion that text messages caused
‘harm’ e.g. the messages woke the participant in the morning, irritated them or disturbed their
work. Those who pointed out more often negative issues in SMS were females (69%), aged about
40 years (mean 39,5; range 19 to 62), single (47%; 33% married, 16% divorced, 4% widowed) and
retired (55%; 22% had no vocational education, 12% university degree, 66% a variety of vocational
training courses). Further, in this group of 51 patients, the most common psychiatric diagnoses
were F20-F29: schizophrenia, schizotypal and delusional disorders (35%) and F30-F39: mood
[affective] disorders (26%), other 39% were minor.
On the contrary, people who were divorced found SMS reminders useful more often than single
people (75% vs 60%), married (75% vs 54%) or widowed (75% vs 60%), respectively (χ2=13.17,
df=6, P=0.04). Women perceived the SMS reminders to be harmful more often than men (16 % vs.
9 %, χ2=4.01, df=1, P=0.045). Of all different background characteristics, job seekers were more
often fully satisfied with the SMS comparing to other groups (Table 3).
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Table 3. Differences between participants in their satisfaction with SMS reminders (n=403)
Demographic characteristics Fully satisfied
n/N (%)
Not fully satisfied
n/N (%)
P value
(χ2, df)
Gender
Male
Female
86/179 (48)
100/224 (45)
93/179 (52)
124/224 (55)
0.496
(χ2=0.46, df=1)
Marital status
Single
Married
Divorced
Widowed
86/188 (40)
49/122 (40)
44/81 (54)
5/10 (50)
102/188 (60)
73/122 (60)
37/81 (46)
5/10 (50)
0.262
(χ2=4.00, df=3)
Vocational education
None
Vocational training courses
Primary vocational skill certificate
Secondary vocational skill certificate
University degree
49/110 (44)
38/69 (55)
60/117 (51)
18/58 (31)
19/43 (44)
61/110 (56)
31/69 (45)
57/117 (49)
40/58 (69)
24/43 (56)
0.062
(χ2=8.95, df=4)
Employment status
Employed
Retired
Homework/ self-employed
Student
Job seeker
31/76 (41)
93/196 (47)
2/11 (18)
13/40 (32)
41/72 (57)
45/76 (59)
103/196 (53)
9/11(82)
27/40 (68)
31/72 (43)
0.029*
(χ2=10.82, df=4)
Diagnose (ICD-10)
F00-F09
F10-F19
F20-F29
F30-F39
F40-F49
F50-F59
F60-F69
F70-F79
F80-F89
F90-F98
0/1 (0)
6/13 (46)
73/154 (47)
63/115 (55)
14/35 (40)
0/1 (0)
17/48 (35)
1/3 (33)
1/2 (50)
0/1 (0)
1/1 (0)
7/13 (54)
81/154 (53)
52/115 (45)
21/35 (60)
1/1 (100)
31/48 (65)
2/3 (67)
1/2 (50)
1/1 (100)
0.439
(χ2=8.98, df=9)
Geographical categorization (NUTS)
West Finland
Helsinki-Uusimaa
South Finland
North and East Finland
23/36 (64)
50/104 (48)
50/115 (43)
63/148 (43)
13/36 (36)
54/104 (52)
65/115 (57)
85/148 (57)
0.121
(χ2=5.80, df=3)
*Statistically significant (P<0.05) by Chi Square test
Participants recruited in hospitals located in Western Finland were most often fully satisfied with
the SMS system compared to those recruited in other Finnish regions (P=0.048) (Table 4).
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Table 4. Associations with participants’ demographic characteristics and feedback (n=403)
Demographic characteristics OR (95% CI) P value
Age 1.01 (0.99 to 1.04) 0.319
Gender
Male (as reference category)
Female 1.11 (0.71 to 1.72) 0.657
Marital status
Single (as reference category) 0.301
Divorced 0.60 (0.34 to 1.06) 0.077
Married 0.95 (0.50 to 1.79) 0.873
Widowed 0.74 (0.17 to 3.22) 0.686
Vocational education
None (as reference category) 0.126
Vocational training courses 1.11 (0.56 to 2.19) 0.767
Primary vocational skill certificate 1.09 (0.61 to 1.95) 0.778
Secondary vocational skill certificate 0.44 (0.21 to 0.93) 0.033
University degree 1.00 (0.46 to 2.18) 0.996
Employment status
Employed (as reference category) 0.157
Retired 1.18 (0.64 to 2.18) 0.605
Homework/ self-employed 0.46 (0.09 to 2.43) 0.36
Student 0.88 (0.36 to 2.15) 0.775
Job seeker 1.97 (0.97 to 4.01) 0.059
Geographical categorization (NUTS)
West Finland (as reference category) 0.048
Helsinki-Uusimaa 0.49 (0.21 to 1.16) 0.105
South Finland 0.33 (0.14 to 0.76) 0.01
North and East Finland 0.36 (0.16 to 0.83) 0.016
Age at first contact in psychiatric services 1.02 (1.00 to 1.05) 0.08
Participants’ age at first contact in psychiatric services predicted their satisfaction (OR=1.02, 95%
confidence interval 1.01 to 1.04, P=0.007). The older people were at first contact with psychiatric
services, the more often they were fully satisfied with the SMS system. Geographical
categorization,[58] approached conventional levels of statistical significance as a predictor
(P=0.07).
DISCUSSION
This study explored patients’ feedback on tailored SMS reminders in psychiatric outpatient care in
Finland. Our study provides deeper insight – and reassurance - for health care personnel and
policymakers regarding what issues should be taken into consideration when individually tailoring
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ICT methods to encourage treatment adherence for people with antipsychotic medication in order
to support self-management and improving psychiatric outpatient care.
To our knowledge, this is the largest study exploring patients’ feedback on SMS reminders for
people having antipsychotic medication. Our sampling secured participation from people who
received SMS reminders for 12 months. This group consisted of people having antipsychotic
medication, not only schizophrenia, and in this way improves generalisability to psychiatric
outpatient care contexts. In studies concerning people with mental health problems low survey
response rates have been a major methodological problem,[63]. Our survey response rate was
72%, which is quite satisfactory comparing to other studies where response rate may vary
between 63% and 99%,[64-67].
Our study has also limitations. First, we do not have data about how many people actually used
the intervention. It is therefore possible that those 72% participants who answered to the survey
questionnaire are active technology users and expressed their satisfaction with the SMS
intervention offered. Comparison of the background characteristics also showed that our data is
biased toward older participants, females, those who were married, and had vocational education.
Second, the survey questionnaire was based on the Technology Acceptance Model (TAM),[40, 41],
which is a useful theoretical model to understand and explain technology users’ behavior and its
implementation. Validity testing is needed in the future to ensure the validity and reliability of use
of this questionnaire for this specific study population and to compare the results with other
studies. Third, the instrument was kept short,[50, 51] and simple,[52], to be carried out in
telephone,[48]. On the other hand, the forced-choice binary yes/no response options may have
limited to capture the nuance of patients’ feedback on SMS reminders. Fourth, one of our
inclusion criteria was that the participants will own a mobile phone. About 97% of the Finnish
citizens have mobile phones,[68] and therefore using SMS in health services seems to be a real
opportunity in the future. However, to use the intervention globally, more information is needed
about the use of mobile technology in other countries, such as in Africa where the mobile phone
penetration is about 63%,[69]. This has to be taken into consideration when implementing SMS
reminders into other contexts. Finally, more men tend to carry the diagnosis of psychosis and be
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treated with psychosis in Finland (53%, Finnish National Institute of Health and Welfare 2015,[70]).
In our data, male participants seem to be underrepresented (44%). We also missed those who are
single, have no vocational education, and job seekers who are often more ill than average and use
health services less than others, even though they have particular need for those services,[71] or
may have problems with treatment adherence in mental health services,[72]. Special effort should
therefore put on those persons who are difficult to capture in mental health services.
Previous studies have shown that SMS were easy to use,[19, 20], did not cause any harm,[57], and
resulted in high levels of satisfaction,[20, 22, 64]. We concur with these findings. In our study, 98%
of participants responded that SMS were easy to use, whereas some references have had doubts
that patients with mental health problems will not interact with technology because of difficulties
with cognitive abilities,[23, 24]. Our study findings are instead promising so that SMS intended for
people with mental health problems is a feasible and acceptable method of sending reminders. A
small minority of this patient group thought that SMS caused harm such as irritation or
disturbance. Only a few previous studies reported SMS causing similar kind of harm,[64, 73]. That
the greater proportion of this group were women (16% vs 9%) is surprising, since women are
known to use SMS more than men,[74], although women tend to prefer to use their mobile
phones for making phone calls,[75].
Our study did not confirm the suspicion that people with serious mental health illnesses are not
capable of using technology-based SMS interventions,[24]. Cognitive inability is common with
people with schizophrenia for example in domains of working memory, speed of processing and
verbal learning [28], which may promote challenges in interacting with technology [24]. Ben-Zeev
et al. [20] found that given opportunity and with the help of appropriate training many people
with schizophrenia are able and willing to use mobile technologies successfully [25], learn quickly
and remember how to use mobile interventions [20]. Therefore, mental illness itself is not a
barrier for technology use to encourage patient self-management.
We found that people seeking jobs were more often fully satisfied with the SMS comparing with
other groups. People with severe mental health disorders are 6 to 7 times more likely to be
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unemployed than people without mental health problems,[76]. The use of ICT (information and
communication technology) has increased among people aged 55 or over,[77], and is essential for
people seeking jobs,[78]. This may indicate that job seekers are active mobile phone and ICT users,
and therefore satisfied with the SMS reminder system. Our study results are encouraging, because
it can be truly important that an intervention to be used is acceptable to this group of people. All
acceptable methods to encourage self-care and self-management in this group are most
welcome,[79]. Overall, patients’ satisfaction with psychiatric services and care varies from
satisfaction level little over 50%,[80], to “good” (scale from “very poor” to “very good”,[81]. As
opposite to previous satisfaction studies, our study result with 72% of the participants indicating
their satisfaction concerning the SMS reminders was considerably higher. Therefore, our study
result is encouraging.
Contrary to previous studies, where young people are referred to as “digital natives” using
information and communication technologies (ICTs) in their daily lives,[82, 83], in our data,
participants whose first contact with psychiatric services was when they were older were most
often fully satisfied with SMS reminders. A simple, one-way SMS reminder system – as used in our
study - could be suitable for an aging population,[84], while younger groups may want to use a
more interactive system,[85], such as games,[86] (e.g. serious games to tackle social anxiety and
self-stigmatization with people with psychosis,[87]), or smart phone interventions (e.g.
applications for monitoring symptoms of mental health conditions in real time,[30-32]). Over 80%
(mainly male and younger participants) of participants with first-episode psychosis reported to use
consoles,[88]. However, we are reluctant to take this as an absolute. Health games or other
internet interventions have problems with engagement,[89, 90]. People under 44 years still use
mobile telephones for texting more than for calls,[91] while older adults report a wide variety of
use of technology, including mobile telephones,[84].
CONCLUSIONS AND IMPLICATIONS
The generally positive feedback and satisfaction with SMS reminders may indicate possibilities for
use of tailored mHealth interventions in psychiatric outpatient care. We think it is important to
listen to feedback and that this may affect the acceptance of technology in routine care. Our study
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results confirm previous studies concerning feasibility and acceptability of the use of SMS in
psychiatric care, but are unique in terms of large study population (n=558) and long-term (study
period 12 month) use of the intervention.
Our results largely endorse that emphasizing the use of simple, already existing technology, such
as mobile phones and SMS,[92], may be an acceptable method in psychiatric outpatient services.
This is in line with our previously published literature review, which showed a wide use of SMS
reminders in different health care services,[93]. The Mobile.Net randomized trial will evaluate the
effects of one particular SMS system, but this feedback study does suggest that this media may
have much to offer in supporting people in an acceptable way, inexpensively, over great distances.
There is, however, a risk that healthcare providers use SMS as a way of shifting their responsibility
to the patient which may promote insufficient follow-up,[94]. This could be a harmful
consequence. Insufficient follow-up can result in non-attendance in vulnerable groups who are
particularly unwell and socially impaired,[95] and at risk of hospitalization,[96]. We need to
understand the possible risks of implementation of SMS interventions,[38], whilst emphasizing the
importance of service users’ participation and feedback,[37].
FOOTNOTES
Acknowledgments: We thank the patients, staff in participating research organisations and
research assistants who kindly agreed to participate in this study without whom the study would
not have been possible. Thanks also to Kaisa Kauppi, Tella Lantta, Laura Yli-Seppälä and Sanna Suni
for their invaluable help with data collection and data entry. We also thank the Mobile.Net Safety
Committee Group for their input and support throughout this study.
Contributors: KAK carried out the literature review and data collection, wrote the statistical
analysis plan, conducted the descriptive data analyses, drafted and revised the paper. CEA and MK
drafted and revised the paper. JK conducted statistical analyses, assisted to interpret the analysis,
drafted and revised the paper. MV designed the study, wrote the statistical analysis plan, provided
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scientific supervision, oversaw the conduct of the study, and drafted and revised the manuscript.
All authors contributed to and have approved the final manuscript.
Funding: This work was supported by The Academy of Finland (132581), Turku University Hospital
(EVO 13893), Satakunta Hospital District (EVO 12/2010, 81096), Foundations’ Professor Pool,
Finnish Cultural Foundation and the University of Turku.
Competing interests: MNSc. Kannisto reports grants from Satakunta Hospital District, during the
conduct of the study; Dr. Adams has nothing to disclose; MsSocSc. Katajisto has nothing to
disclose; PhD. Koivunen has nothing to disclose; Professor Välimäki reports grants from The
Academy of Finland, Turku University Hospital, Satakunta Hospital District, Foundations Professor
Pool, Finnish Cultural Foundation, and non-financial support from University of Turku, during the
conduct of the study. All authors have completed the ICMJE uniform disclosure form at
www.icmje.org/coi_disclosure.pdf and declare: this work was supported by The Academy of
Finland (132581), Turku University Hospital (EVO 13893), Satakunta Hospital District (EVO
12/2010, 81096), Foundations’ Professor Pool, Finnish Cultural Foundation, and the University of
Turku; no financial relationships with any organisations that might have an interest in the
submitted work in the previous three years; no other relationships or activities that could appear
to have influenced the submitted work.
Ethical approval: Approval for the study (Mobile.Net) was obtained from the Ethics Committee of
the Hospital District of Southwest Finland on 16 December 16 2010 (ref; ETMK 109/180/2010).
Permission to conduct the study was guaranteed by each hospital organization. Patients gave their
consent before their recruitment to the Mobile.Net study. Answer to the questionnaire by
telephone or the return of a completed questionnaire was taken to indicate patients’ consent to
participate in this cross-sectional survey study.
Data sharing: No additional data available. This cross-sectional survey is a part of a randomized
clinical trial (“Mobile.Net” ISRCTN: 27704027).
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This is an Open Access article distributed in accordance with the Creative Commons Attribution
Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build
upon this work non-commercially, and license their derivative works on different terms, provided
the original work is properly cited and the use is non-commercial. See:
http://creativecommons.org/licenses/by-nc/4.0/.
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STROBE 2007 (v4) checklist of items to be included in reports of observational studies in epidemiology*
Checklist for cohort, case-control, and cross-sectional studies (combined)
Section/Topic Item # Recommendation Reported on page #
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract Title page, p. 1
(b) Provide in the abstract an informative and balanced summary of what was done and what was found Abstract, p. 2
Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported p. 4-5
Objectives 3 State specific objectives, including any pre-specified hypotheses p. 5
Methods
Study design 4 Present key elements of study design early in the paper p. 5
Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data
collection p. 5-7
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe
methods of follow-up
Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control
selection. Give the rationale for the choice of cases and controls
Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants
p. 5-6
(b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed
Case-control study—For matched studies, give matching criteria and the number of controls per case
Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic
criteria, if applicable p. 7
Data sources/ measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe
comparability of assessment methods if there is more than one group p. 7
Bias 9 Describe any efforts to address potential sources of bias
Study size 10 Explain how the study size was arrived at p. 6
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen
and why p. 7-8
Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding p. 7-8
(b) Describe any methods used to examine subgroups and interactions p. 7-8
(c) Explain how missing data were addressed p. 8
(d) Cohort study—If applicable, explain how loss to follow-up was addressed
Case-control study—If applicable, explain how matching of cases and controls was addressed
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Kannisto K et al. Feedback on SMS reminders to encourage adherence among patients with psychosis: a cross-sectional survey nested within a randomised trial
Cross-sectional study—If applicable, describe analytical methods taking account of sampling strategy
(e) Describe any sensitivity analyses
Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility,
confirmed eligible, included in the study, completing follow-up, and analysed p. 6, 8
(b) Give reasons for non-participation at each stage p. 6
(c) Consider use of a flow diagram
Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and
potential confounders p. 6
(b) Indicate number of participants with missing data for each variable of interest p. 8-11
(c) Cohort study—Summarise follow-up time (eg, average and total amount)
Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time
Case-control study—Report numbers in each exposure category, or summary measures of exposure
Cross-sectional study—Report numbers of outcome events or summary measures p. 8-13
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95%
confidence interval). Make clear which confounders were adjusted for and why they were included p. 8-13
(b) Report category boundaries when continuous variables were categorized p. 8-13
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses
Discussion
Key results 18 Summarise key results with reference to study objectives p. 13
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction
and magnitude of any potential bias p. 14-15
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results
from similar studies, and other relevant evidence p. 13-16
Generalisability 21 Discuss the generalisability (external validity) of the study results p. 14
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on
which the present article is based p. 18
*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE
checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.
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