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User-experience of Patients with Telehealth: Complementing a Clinical Trial with Human-Computer Interaction (Preprint)

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Abstract

ABSTRACT Background: The use of telehealth to monitor patients from home is on the rise. A telehealth technology is evaluated in a clinical trial with measures of health outcomes and cost effectiveness. However, what happens between a technology and the patients are not investigated during a clinical trial −the telehealth technology remains as a “black box”. Meanwhile three decades of research in the discipline of Human-Computer Interaction (HCI) presents design, implementation and evaluation of technologies with a primary emphasis on users. HCI research exposed the importance of user-experience (UX) as an essential part of technology development and evaluation. Objective: This research investigates Type 2 Diabetes (T2D) patients’ experiences of a telehealth in-home monitoring technology through HCI approach. How HCI could complement future telehealth clinical trials for patient-centred design and evaluation is also explored. Methods: We adopted an ethnographic philosophy to conduct a contextual inquiry due to time-limitations and semi-structured interviews of nine T2D patients. We defined the method as Clinical User-experience Evaluation (CUE). The patients were enrolled in a telehealth clinical trial of T2D. However, this research is an independent HCI study, conducted by information technologists and health researchers for a patient-centred evaluation of telehealth. Results: Key analytical findings depicted that patients value the benefits of in-home monitoring but the current device did not possess all functionalities that patients want. Results contain patients’ experiences and emotions while using the device, patients’ perceived benefits of the device, and domestication of the device in their homes. Further analysis showed the influence of the device on patients’ awareness, family involvement, and design implications for telehealth T2D. Conclusions: CUE could complement the telehealth clinical trial and uncovered knowledges about T2D patients’ experiences, future design implications and importance of understanding patients in telehealth.
Original Paper
User-experience of Paents with Telehealth: Complemenng a
Clinical Trial with Human-Computer Interacon
Abstract
Background: 



 !
"#$"#%
"#
$&'%

Objective: ()$()%*&'
+&'
"#
Methods: +
,
()+"&-
$"&-%()


Results:.

/*
*
0*
()
Conclusions: "#
()*&'"#
 

Trial Registration:
Keywords: "11(1
111
11
Introducon
()*1()
232(444526(426
7268(426&9):3;
2(<*7268
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72:8
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A
Applied
Ethnography [8]
long term immersive
fieldwork; observation
combined with
participation
Researcher moves
into users’ world
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Research Objecve
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Q1. What happens at the patient’s home during the use of the telehealth device?
Q2. How do patients feel while using the telehealth device?
Q3. Which function/s and designs of the device satisfies /dissatisfies the patients?
Methods
Research Method
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A 
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Participants
pseudonyms
Sex Age Computer use
(hours /week)
Time in Clinical
Trial (months)
Diagnosed
with T2D
(years)
& 0 35 4 6 2(N
O ! 34 34 C 24N
P 0 :C (4 : 3
M ! :: (4 : 24N
J ! :5 5 6 (4
 0 :4 ( 6 (6
9 0 66 2( ; (
D ! 6; ( : 2
 ! 6( :4 : (
Equipment
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=






0(

Data Analysis
#,
,
$!=2%
>M24

Results
A0
*9*

Current Design: Technology-User Fit

+$5%
G$5%
$(%$(%$2%#L
$;%$5%$2%$2%

5D9
E 9 J
 D 

#
9 ( 2  ;
" 2 2
" 2 2 2 2 5
9
! 2  2

/ 5 ( ( 2
),
$9!=%
O*,
$05%G$%
$%
$%

05-,;

Lack of wireless capability:#
*
9&
Apart from when you gotta be home two hours after eating to do it can be a little bit
difficult like..Oh my God I have gotta get home so I mean time wise that’s it if I am not
gonna be at home..$%
+&
9

“I can take this (her own glucometer that she bought) with me, I can't do the blood
pressure, I take this with me and do the blood sugar and then put it down in a book.
$&%
Undesirable experience from sphygmomanometer:-
##
“The blood pressure cuff I have more difficulty with. I put it here where my doctor
would put it. It re pumps and it takes ages to do it. It marks my arm.$P%
P9


Lack of visual data:#


0

D


“I know it does it here (glucometer) but it would be good to see every day’s. But it
doesn´t show you. Like last week I might have been 5.5 and this week I am 7.5 why?
Why am I? Then I would do exactly the same things that I did last week. $J%
MF
MF
M*
M*+GIt would be much better if he could just push a button and see the last
three weeks of his readings.
“Coz he is adjusting his insulin and he needs to know---all the time.
“Probably I would like to see a graph of my results, more often. Like even once a month
would be good to show it on a graph. How my results are going, because you just see
number everyday, but you want to know your ups and downs, and you want to know
using that computer why my diabetes goes higher, I know the reason now why it goes
higher, before I didn´t know the reasons. But now I do. And it’s just the difference the
food that I have eaten and the foods prepared and I have found that because I am
monitoring my blood glucose carefully.$D%
OO
,

“There is nothing like graphs to see trends. They have to display in a sensible way, if
that makes sense. I will be thinking that a progressive graph will do it.$O%
Lack of medication name:P


P

“To see my change of insulin and I couldn’t find on here so I went back through here
with my computer and Internet. My medicine is also here… and insulin is not there but
I looked that up at the computer. Not everyone has that. When I want to see what that
thing do I check it up here. I don’t ever touch the unit because it automatically shuts
down. It’s simple as that, quite easy to use. Bit challenging at the beginning.$P%
O

Mismatch with life due to immobility of the device:
#=

&*9

“I can take this with me, I can't do the blood pressure, I take this with me and do the
blood sugar and then put it down in a book.” (Uma)
Glucometer Discomfort and Pain:+


9
(),
9

,
“Problem I see with this is you have to prick your finger every time you use it. It’s not
that bad but after a while you are bruising your fingertips sore so in that respect I
guess it’s not really something that one looks forwards to going and doing.$%
-=
O


#
Feelings and Percepons
D    
 



“And it’s good that they(nurses), that someone else is keeping an eye on you, back at
office, nurses.” (Vince)

D


I think it’s a great benefit for me, I wish it probably could stay and I would like to keep
it. I don´t know how I am gonna go, I am obviously in the habit of doing it every morning
now, I am gonna have it. It´s a habit now. So next week it’s gonna go and I can still
maintain the regime that I am doing it now, you know.” (Pete)

-9
9
9*

It’s more like a -- there's a regime for everyday 10 minutes
before eating and after eating, she tastes it and morning, afternoon-- it's 10 minutes or 5
minutes—doesn’t affect much. But it improved her overall awareness.” (Serena’s son)
M

It (the device) makes you, wanna do it (the blood glucose reading) $M%
,#?,
*


You know when you haven't done this for a week and oh you should do it. It's like
quitting smoking, you know that you have to ring up somebody every time you have to
ring up. So it's that extra incentive you know. $%

)#M

It´s sort of like a safety net. You know there’s someone in the background always
watching and they will ring you up.” (Vince’s Wife)
0&$35%#&*

9*9*


D

#


D
-
035
&
,=$(6
%&G
&GI don't know what's wrong with it, it suddenly slowed down.
/GDid it slow down today or--?
&GNo, it has been doing this for a few days. I was talking to the lady (Nurse1) on
the phone and-- come on
&come on 

&: I have to go through this every morning. It's--aaah
&

I don't know whether it’s because it's---Aaaahhhhh$&%
=&

 !
=$%


F$0;%#
It’s not really a one-man job.”
0;$%&$%
Discussion
=P
@
-
&'0()
-

Design Implicaons for future telehealth for T2D

+Q
()
Domescaon of the device
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
AM
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In+uence on paents from the use of the technology
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* 
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7(((;8D
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Categorizaon of the paents as users
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7;8
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Limitaons of the Research
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()
,
Comparison with Prior Work
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=()
7;58"&-/
()
Conclusions
#
=


7:89
C4<7;6;:8&'
"#
*&'()>I+

()D*
()
R
,+"#
*&'
Acknowledgements
!!E
F()/"72B89
()))
Con+icts of Interest
>
Abbreviaons
"&-G"&-
"#G"#
#"G#"
DGD
()G()
!!EG!!E
&'G&-
References
2 ."9.>/KJEMHJ!
GJ!H
(42313$C%G42:(5(
( +9E.""P"99">"
(G=
9/$>D
Q%(42313G2
; H9!=#=!9JA
"()"&-
-$"&-%H(4261;B$;%G2(2
5 J=)"HD"="".J
,GDE9
(4221C$2%G2444;C3
6 .9!&G
&1(42(#9J>GB4;:6;523C
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... Studies in this review employed a range of hardware and software technologies to deliver treatments, 31,33,34,38,39,42,45 manage care 29,30,36,44,46 and to gather feedback from patients. 13,28,30,[34][35][36]40,43,46 Many of these studies used standard hardware which patients already owned including smartphones, tablets and desktop computers. ...
... 13,28,30,34,36,37,46,47 Other studies provided a Fitbit, 34,46 X-Box 46 or treatment-specific technologies such as haptic gloves 27 or continuous glucose monitors (CGM). 31 Sixteen studies (80%) created custom-designed software solutions to deliver one or more patient interactions: four (20%) to deliver online training, 27,34,39,42 eight (40%) to monitor patient progress, 30,31,33,34,36,39,43,46 two (10%) to share patient records 27,29 or seven (35%) to receive patient feedback. 13,28,35,37,40,42,46 These applications were either written for iOS or Android systems or were webbased and accessible through the patient's or clinician's web browser. ...
... 13,28,30,34,36,37,46,47 Other studies provided a Fitbit, 34,46 X-Box 46 or treatment-specific technologies such as haptic gloves 27 or continuous glucose monitors (CGM). 31 Sixteen studies (80%) created custom-designed software solutions to deliver one or more patient interactions: four (20%) to deliver online training, 27,34,39,42 eight (40%) to monitor patient progress, 30,31,33,34,36,39,43,46 two (10%) to share patient records 27,29 or seven (35%) to receive patient feedback. 13,28,35,37,40,42,46 These applications were either written for iOS or Android systems or were webbased and accessible through the patient's or clinician's web browser. ...
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Objective Patient experience significantly impacts healthcare quality, outcomes, resource utilisation and treatment adherence. Digital technologies offer promising approaches for capturing real-time, multi-faceted patient experiences. This scoping review investigated how digital technologies are used to capture patient experience during healthcare encounters and their potential to improve health service delivery and care. Methods A scoping review was conducted to determine associations between patients’ use of digital technology and subsequent outcomes. Four electronic databases were searched using six combination search terms in titles and/or abstracts published between 2016 and 2022. Inclusion criteria focused on studies where patients were primary users of digital technology, reporting on their experience during care. Studies had to report on at least one outcome: health service delivery, quality of care or patient experience. Screening, data extraction and analysis were performed systematically. Results Of the 377 studies retrieved, 20 were included. Most studies incorporated aspects allowing patients to share experiences with digital technologies. Eighty percent (n = 16) of studies reported improvements in patient experiences, 75% (n = 15) enhancements in service delivery aspects and 50% (n = 10) indicated improved quality of care associated with the use of digital technologies. Real-time journaling and narrative methods alongside treatment were linked to improved communication, healthcare efficiencies and patient agency. Technologies facilitating bidirectional communication were particularly associated with positive effects on patients’ sense of agency. Conclusion Digital technologies facilitating documentation of patient experiences demonstrate potential in enhancing care quality through increased patient voice, collaboration and agency. Technologies designed to map and evaluate patients’ healthcare experiences represent a promising approach to improving healthcare outcomes, service delivery and overall patient experience. Further research is needed to establish standardised methodologies and evaluate long-term impacts across diverse populations. Integrating digital narrative medicine principles may offer valuable insights for future interventions aimed at capturing and enhancing patient experiences in healthcare.
... Nevertheless, there is a predominance of texts that address the topic "operation of the telemedicine service" (Figure 11). Moreover, we highlight the articles that seek to promote access to health by telemedicine in remote locations (Bagayoko et al., 2014;Dananjayan;Raj, 2020;Mougiakakou et al., 2011;Nikolaidis;Efthymiadi;Angelidis, 2019;Thobias;Kiwanuka, 2018), in emerging countries (Gebre-Mariam;Bygstad, 2019;Khan et al., 2015;Ncube;, and also to analyze the interoperability of the health service between countries (Domenichiello, 2015;Kautsch;Lichoń;Matuszak, 2017) and the systematization and development of an e-Health system based on user experience (Jalil et al., 2019). ...
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The aim of this article was to analyze the literature on technological development in telemedicine through bibliometrics, by identifying the state of the art, research gaps, and trends in the literature. The analysis covers a total of 67 articles related to the field of study, published between 2010-2020 in the Springer Link, Science Direct, Wiley Online Library, Web of Science, and Scopus databases. The data was processed using the software StArt, Excel, IBM SPSS Statistics, and Iramuteq. The results presented bibliometric analysis of the articles, classified into the areas of Management (52.2%), IT (25.4%), and Medicine (22.4%), along with a Table of 34 suggestions for future research. Literature trends encompassed six study clusters (health, study, service, technology, patient, and telemedicine), which further subdivided into nine research themes (digital platform, telemedicine service management, telemedicine service operation, end-user perception, business opportunities, healthcare professional perception, covid-19, regulation, and robotics). An observed outcome was a significant increase in the number of publications in the area due to covid-19.
... Social media-based tools are increasingly tailored to specific needs to overcome the challenges posed by limited location-based resources and improve the speed of information sharing in healthcare systems (Redfern et al., 2013;Patel et al., 2015;Jalil et al., 2019;Wang et al., 2021). Recognizing the potential of these tools, the China Food and Drug Administration has emphasized the role of pharmacists in physical medical institutions in providing pharmaceutical care on the Internet. ...
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Background: Time and space constraints have often hindered the provision of optimal pharmaceutical care, limiting medication therapy management. Social media tools have gained significant popularity in the field of pharmaceutical care. This study aimed to develop a WeChat-based intelligent medication manager platform that facilitates online pharmaceutical care and encourages self-management. Methods: We developed a WeChat-based Internet pharmacy service platform called Xiang Medicine Guidance (XMG). Through the analysis of surveys and user access data, we evaluated the demand and utilization of the XMG platform and assessed patients’ satisfaction with its services. Patients’ adherence before and after the XMG platform intervention was also investigated. Results: The XMG platform was launched in November 2022, offering medication guidance, reminders, and consultation services through the WeChat mini-program. By the end of April 2023, the platform had attracted 141.2 thousand users, accumulating 571.0 thousand visits. Moreover, 1,183 clients sought online medication consultations during this period. Six months after the launch of XMG, an impressive 91.02% of users expressed their satisfaction with the platform. The medication reminders and consultations provided by XMG significantly contributed to medication adherence, with 56.02% of users categorized as having good adherence, better than the previous 47.26%. Conclusion: Through its services and features, XMG empowers patients to better manage their medications, seek professional advice, and adhere to their prescribed treatment plans. XMG has the potential to positively impact public health on a broader scale.
... Nielsen refers Think-Aloud method as effective in giving us insights into users' mental models regarding a given task. The study also drew on the procedures of a field study method based on Observation and interviews to understand work practices and behaviors -Contextual inquiry [14,15]. Kim Salazar on Nielsen Norman Group website highlights the value of the contextual inquiry method -to inquiry in context, which results in a collaborative interpretation between researchers and expert users about work practices and behaviors, with a more in-depth understanding of experts' reasoning. ...
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AI technology has the potential to support humans' processes and tasks by augmenting human capabilities and effectiveness. Computer-aided systems have been implemented in healthcare mainly to support clinical decisions. As in other areas, the impact, complexity, and opacity of AI operations have led to the establishment of guidelines for trustworthy AI, which implies being understandable. This study describes the user research work carried out by a multidisciplinary team composed of ML engineers, design researchers, and medical experts, to inform the design of algorithms and user interfaces for two XAI-based clinical decision support tools targeted at Cervical cancer and Glaucoma screening. In particular, we sought to leverage and bridge individual and collective expertise to understand the context, decision-making processes and criteria, and values that frame the respective clinical decisions. The article describes how we operationalised the research activities with expert users and what strategies we followed for subsequent content analysis, ending with the sharing of lessons learned as valuable insights for other research teams interested in designing computer-aided diagnostic systems based on human-centred XAI approaches.
... Clarke et al. (2013) review 17 papers that identify human-computer interaction (HCI) issues in the use of Electronic Health Records in medical practice, and categorise them into four types: poor display of information, cognitive overload, navigation issues and workflow issues. Jalil et al. (2019) investigate the UX experience of patients managing their type 2 diabetes with an in-home monitoring device. The authors conduct a contextual inquiry followed by semi-structured interviews with 9 patients and report the patients' experiences and emotions while using the device, perceived benefits and limitations. ...
... A discussion of possible human factors that can impact clinical efficacy (e.g., baseline severity; dyadic procedures; personality factors; presence of co-morbidities or medications; or even blinding and placebo effect) are beyond the scope of this article, however these are critical factors that must be considered in provisioning adaptive and personcentered design of such applications. On the other hand, clinicians must also account for variations that arise from interindividual variations in human-computer interactions (HCI) [26]. ...
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The aim of this systematic scoping review was to gain a better understanding of research trends in digital mental health care. We focused on comorbid conditions: depression, anxiety, and pain–which continue to affect an estimated 20% of world population and require complex and continuous social and medical care provisions. We searched all randomized controlled trials on PubMed until May 2021 for any articles that used a form of information and communication technology (ICT) in relation to primary outcomes anxiety, pain, depression, or stress. From 1285 articles that satisfied the inclusion criteria, 890 were randomized trials with nearly 70% satisfactory outcomes. For depression and anxiety, the most frequently reported, were web-based, or mobile apps used for self-monitoring, and guided interventions. For pain, VR-based interventions or games were more prevalent, especially as tools for distraction, or as stimuli for mechanistic studies of pain or anxiety. We discuss gaps in knowledge and challenges that relate to the human factors in digital health applications, and underline the need for a practical and conceptual framework for capturing and reporting such variations.
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Amid the COVID-19 outbreak, healthcare systems have undergone a transformation with telehealth playing a key role. There has been a dramatic shift in the use of telehealth due to its benefits including the convenience it has offered. With the use of telehealth to monitor patients’ health on the rise, it has become more critical to improve the quality of care by identifying and resolving barriers to virtual care delivery systems. In this study, we apply the Systems Engineering Initiative for Patient Safety (SEIPS) 2.0 framework to systematically investigate telemonitoring implementation, as a main category of telehealth services, and identify barriers to high quality of care while monitoring care virtually. We analyze those barriers by capturing them across different work systems of the SEIPS framework, which are: people (patients, healthcare providers, nurses, telemonitoring staff), organization, tools and technology, tasks, internal environment, and external environment. We then, through some research, determine some of those barriers that are more influential and conduct Fault Tree Analysis to identify their root causes. Furthermore, some recommendations are provided to address the identified barriers and their root causes.
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Objective: To understand usage patterns and clinical efficacy of Hello Heart, an mHealth technology application designed to facilitate patient engagement in managing hypertension. Methods: In this single-arm observational study, all subjects with ≥2 blood pressure (BP) recordings were included. The cohort was divided into subgroups by weeks passed since download that patients were still recording measurements. Changes in BP were compared between subgroups. Results: Of 5115 eligible subjects, 3803 (74%) recorded BP for ≥2 weeks. In the 4-week subgroup, 23% achieved BP reduction of ≥10 mmHg versus 24% in the 22-week subgroup (p < 0.001). Among 783 subjects reporting baseline hypertension 57% of the 4-week and 69% of the 22-week subgroups achieved BP normalization (all p < 0.001). Conclusions: We show significant decrease in BP with improved metrics over time. Higher engagement was associated with greater BP reduction and engagement was higher among those with greater clinical need of BP control. Practice implications: Hello Heart represents an operational mHealth technology to improve patient engagement and clinical outcomes.
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The effects of telemedicine strategies on the management of diabetes is not clear. This study aimed to investigate the impact of different telemedicine strategies on glycaemic control management of type 2 diabetes patients. A search was performed in 6 databases from inception until September 2016 for randomized controlled studies that examined the use of telemedicine in adults with type 2 diabetes. Studies were independently extracted and classified according to the following telemedicine strategies: teleeducation, telemonitoring, telecase-management, telementoring and teleconsultation. Traditional and network meta-analysis were performed to estimate the relative treatment effects. A total of 107 studies involving 20,501 participants were included. Over a median of 6 months follow-up, telemedicine reduced haemoglobin A1c (HbA1c) by a mean of 0.43% (95% CI: −0.64% to −0.21%). Network meta-analysis showed that all telemedicine strategies were effective in reducing HbA1c significantly compared to usual care except for telecase-management and telementoring, with mean difference ranging from 0.37% and 0.71%. Ranking indicated that teleconsultation was the most effective telemedicine strategy, followed by telecase-management plus telemonitoring, and finally teleeducation plus telecase-management. The review indicates that most telemedicine strategies can be useful, either as an adjunct or to replace usual care, leading to clinically meaningful reduction in HbA1c.
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Background The use of telehealth steadily increases as it has become a viable modality to patient care. Early adopters attempt to use telehealth to deliver high-quality care. Patient satisfaction is a key indicator of how well the telemedicine modality met patient expectations. Objective The objective of this systematic review and narrative analysis is to explore the association of telehealth and patient satisfaction in regards to effectiveness and efficiency. Methods Boolean expressions between keywords created a complex search string. Variations of this string were used in Cumulative Index of Nursing and Allied Health Literature and MEDLINE. Results 2193 articles were filtered and assessed for suitability (n=44). Factors relating to effectiveness and efficiency were identified using consensus. The factors listed most often were improved outcomes (20%), preferred modality (10%), ease of use (9%), low cost 8%), improved communication (8%) and decreased travel time (7%), which in total accounted for 61% of occurrences. Conclusion This review identified a variety of factors of association between telehealth and patient satisfaction. Knowledge of these factors could help implementers to match interventions as solutions to specific problems.
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Background: Adequate self-management is the cornerstone of type 2 diabetes treatment, as people make the majority of daily treatment measures and health decisions. The increasing prevalence of type 2 diabetes mellitus (T2DM) and the complexity of diabetes self-management demonstrate the need for innovative and effective ways to deliver self-management support. eHealth interventions are promoted worldwide and hold a great potential in future health care for people with chronic diseases such as T2DM. However, many eHealth interventions face high dropout rates. This led to our interest in the experiences of participants who dropped out of an eHealth intervention for adults with T2DM, based on the Guided Self-Determination (GSD) counseling method. Objective: In this study, we aimed to explore experiences with an eHealth intervention based on GSD in general practice from the perspective of those who dropped out and to understand their reasons for dropping out. To the best of our knowledge, no previous qualitative study has focused on participants who withdrew from an eHealth self-management support intervention for adults with T2DM. Methods: A qualitative design based on telephone interviews was used to collect data. The sample comprised 12 adults with type 2 diabetes who dropped out of an eHealth intervention. Data were collected in 2016 and subjected to qualitative content analysis. Results: We identified one overall theme: "Losing motivation for intervention participation." This theme was illustrated by four categories related to the participants' experiences of the eHealth intervention: (1) frustrating technology, (2) perceiving the content as irrelevant and incomprehensible, (3) choosing other activities and perspectives, and (4) lacking face-to-face encounters. Conclusions: Our findings indicate that the eHealth intervention based on GSD without face-to-face encounters with nurses reduced participants' motivation for engagement in the intervention. To maintain motivation, our study points to the importance of combining eHealth with regular face-to-face consultations. Our study also shows that the perceived benefit of the GSD eHealth intervention intertwined with choosing to focus on other matters in complex daily lives are critical aspects in motivation for such interventions. This indicates the importance of giving potential participants tailored information about the aim, the content, and the effort needed to remain engaged in complex interventions so that eligible participants are recruited. Finally, motivation for engagement in the eHealth intervention was influenced by the technology used in this study. It seems important to facilitate more user-friendly but high-security eHealth technology. Our findings have implications for improving the eHealth intervention and to inform researchers and health care providers who are organizing eHealth interventions focusing on self-management support in order to reduce dropout rates.
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Background: Poor diabetes self-care can have a negative impact on psychological well-being and quality of life. Given the scarcity of traditional psychological support and the barriers to uptake of and attendance at face-to-face education programs, Web-based interventions are becoming a popular approach to provide an additional platform for psychological support in long-term conditions. However, there is limited evidence to assess the effect of Web-based psychological support in people with type 2 diabetes. Objective: This systematic review is the first review to critically appraise and quantify the evidence on the effect of Web-based interventions that aim to improve well-being in people with type 2 diabetes. Methods: Searches were carried out in the following electronic databases: MEDLINE, EMBASE, CINAHL, PsycINFO, and Cochrane Library. Reference lists were hand-searched. A meta-analysis was conducted for depression and distress outcomes. Results: A total of 16 randomized controlled studies met the inclusion criteria for the systematic review and 9 were included in the meta-analyses. Theories were applied to the majority of the interventions. The most common behavior change techniques were "General information" and "Tracking/monitoring." Interventions with a duration of 2-6 months providing professional-led support with asynchronous and synchronous communication appeared to be associated with significant well-being outcomes. The pooled mean (95% confidence interval) difference between the intervention and control arms at follow-up on depression score was -0.31 (-0.73 to 0.11). The pooled mean difference on distress scores at follow-up was -0.11 (-0.38 to 0.16). No significant improvements in depression (P=.15) or distress (P=.43) were found following meta-analyses. Conclusions: While the meta-analyses demonstrated nonsignificant results for depression and distress scores, this review has shown that there is a potential for Web-based interventions to improve well-being outcomes in type 2 diabetes. Further research is required to confirm the findings of this review.
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Background: Brief automated messages have the potential to support self-management in people with type 2 diabetes, but their effect compared with usual care is unclear. Objective: To examine the effectiveness of interventions to change lifestyle behavior delivered via automated brief messaging in patients with type 2 diabetes. Methods: A systematic literature review of controlled trials examined the impact of interventions, delivered by brief messaging, and intended to promote lifestyle change in people with type 2 diabetes, on behavioral and clinical outcomes. Bibliographic databases searched included Medline, Embase, CINAHL, PsycINFO, and ISI WoK. Two reviewers independently screened citations. We extracted information on study risk of bias, setting (high versus low- and middle-income countries) and intervention characteristics (including use of theory and behavior-change techniques). Outcome measures included acceptability of the interventions and their impact on 1) determinants of lifestyle behavior (knowledge about diabetes, self-efficacy, attitudes towards self-management), 2) lifestyle behavior (diet, physical activity), and 3) clinical and patient-reported outcomes. Where possible, we pooled data using random-effects meta-analyses to obtain estimates of effect size of intervention compared to usual care. Results: We identified 15 trials (15 interventions) meeting our inclusion criteria. Most interventions were delivered via short message service text messaging (n=12) and simultaneously targeted diet and physical activity (n=11). Nine interventions consisted of unidirectional messages, whereas six consisted of bidirectional messages, with patients receiving automated tailored feedback based on self-reported data. The acceptability of the interventions, and their impact on lifestyle behavior and its determinants, were examined in a low proportion of trials, with heterogeneous results being observed. In 13 trials (1155 patients) where data were available, there was a difference in glycated hemoglobin of -0.53% (95% CI -0.59% to -0.47%) between intervention groups compared to usual care. In five trials (406 patients) there was a non-significant difference in body mass index of -0.25 kg/m2 (95% CI -1.02 to 0.52). Interventions based on unidirectional messages produced similar effects in the outcomes examined, compared to those based on bidirectional messages. Interventions conducted in low- and middle-income countries showed a greater impact than those conducted in high-income countries. In general, trials were not free of bias and did not use explicit theory. Conclusions: Automated brief messages strategies can improve health outcomes in people with type 2 diabetes. Larger, methodologically robust trials are needed to confirm these positive results.
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Background: Adoptions of health behaviors are crucial for maintaining good health after type 2 diabetes mellitus (T2DM) diagnoses. However, adherence to glucoregulating behaviors like regular exercise and balanced diet can be challenging, especially for people living in lower-socioeconomic status (SES) communities. Providing cost-effective interventions that improve self-management is important for improving quality of life and the sustainability of health care systems. Objective: To evaluate a health coach intervention with and without the use of mobile phones to support health behavior change in patients with type 2 diabetes. Methods: In this noninferiority, pragmatic randomized controlled trial (RCT), patients from two primary care health centers in Toronto, Canada, with type 2 diabetes and a glycated hemoglobin/hemoglobin A1c (HbA1c) level of ≥7.3% (56.3 mmol/mol) were randomized to receive 6 months of health coaching with or without mobile phone monitoring support. We hypothesized that both approaches would result in significant HbA1c reductions, although health coaching with mobile phone monitoring would result in significantly larger effects. Participants were evaluated at baseline, 3 months, and 6 months. The primary outcome was the change in HbA1c from baseline to 6 months (difference between and within groups). Other outcomes included weight, waist circumference, body mass index (BMI), satisfaction with life, depression and anxiety (Hospital Anxiety and Depression Scale [HADS]), positive and negative affect (Positive and Negative Affect Schedule [PANAS]), and quality of life (Short Form Health Survey-12 [SF-12]). Results: A total of 138 patients were randomized and 7 were excluded for a substudy; of the remaining 131, 67 were allocated to the intervention group and 64 to the control group. Primary outcome data were available for 97 participants (74.0%). While both groups reduced their HbA1c levels, there were no significant between-group differences in change of HbA1c at 6 months using intention-to-treat (last observation carried forward [LOCF]) (P=.48) or per-protocol (P=.83) principles. However, the intervention group did achieve an accelerated HbA1c reduction, leading to a significant between-group difference at 3 months (P=.03). This difference was reduced at the 6-month follow-up as the control group continued to improve, achieving a reduction of 0.81% (8.9 mmol/mol) (P=.001) compared with a reduction of 0.84% (9.2 mmol/mol)(P=.001) in the intervention group. Intervention group participants also had significant decreases in weight (P=.006) and waist circumference (P=.01) while controls did not. Both groups reported improvements in mood, satisfaction with life, and quality of life. Conclusions: Health coaching with and without access to mobile technology appeared to improve glucoregulation and mental health in a lower-SES, T2DM population. The accelerated improvement in the mobile phone group suggests the connectivity provided may more quickly improve adoption and adherence to health behaviors within a clinical diabetes management program. Overall, health coaching in primary care appears to lead to significant benefits for patients from lower-SES communities with poorly controlled type 2 diabetes. Trial registration: ClinicalTrials.gov NCT02036892; http://clinicaltrials.gov/ct2/show/NCT02036892 (Archived by WebCite at http://www.webcitation.org/6b3cJYJOD).
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Adherence to chronic disease management is critical to achieving improved health outcomes, quality of life, and cost-effective health care. As the burden of chronic diseases continues to grow globally, so does the impact of non-adherence. Mobile technologies are increasingly being used in health care and public health practice (mHealth) for patient communication, monitoring, and education, and to facilitate adherence to chronic diseases management. We conducted a systematic review of the literature to evaluate the effectiveness of mHealth in supporting the adherence of patients to chronic diseases management ("mAdherence"), and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among patients and health care providers. We searched PubMed, Embase, and EBSCO databases for studies that assessed the role of mAdherence in chronic disease management of diabetes mellitus, cardiovascular disease, and chronic lung diseases from 1980 through May 2014. Outcomes of interest included effect of mHealth on patient adherence to chronic diseases management, disease-specific clinical outcomes after intervention, and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among target end-users. In all, 107 articles met all inclusion criteria. Short message service was the most commonly used mAdherence tool in 40.2% (43/107) of studies. Usability, feasibility, and acceptability or patient preferences for mAdherence interventions were assessed in 57.9% (62/107) of studies and found to be generally high. A total of 27 studies employed randomized controlled trial (RCT) methods to assess impact on adherence behaviors, and significant improvements were observed in 15 of those studies (56%). Of the 41 RCTs that measured effects on disease-specific clinical outcomes, significant improvements between groups were reported in 16 studies (39%). There is potential for mHealth tools to better facilitate adherence to chronic disease management, but the evidence supporting its current effectiveness is mixed. Further research should focus on understanding and improving how mHealth tools can overcome specific barriers to adherence.