BMJ Open · University of Turku, Turku, Finland and Turku University Hospital, Turku, Finland and...

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

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

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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).


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


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


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


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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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


BMJ Open on June 6, 2020 by guest. P

rotected by copyright.http://bm

jopen.bmj.com

/B

MJ O

pen: first published as 10.1136/bmjopen-2015-008574 on 9 N

ovember 2015. D

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1

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


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




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


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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10

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


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


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)


None




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


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)


West Finland

Helsinki-Uusimaa

South 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


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


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


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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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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BMJ Open · University of Turku, Turku, Finland and Turku University Hospital, Turku, Finland and...

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