Feasibility and Acceptability of a Mobile Intervention to Improve Treatment Adherence in Bipolar Disorder

Wenze, Susan J.; Armey, Michael F.; Miller, Ivan W.

doi:10.1177/0145445513518421

Cited by 79 publications

(133 citation statements)

References 50 publications

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“…These patterns mirror those of studies of mobile interventions for other chronic conditions, which included study periods of up to a year in duration [53,55,58]. Despite generally high rates of adherence for this type of intervention, there appears to be considerable variation in usage of the different intervention components within and between studies, such as the self-care advice pages.…”

Section: Findings In the Context Of Other Literaturementioning

confidence: 55%

“…Additionally, very few barriers were reported by patients included in studies in the present review. The finding that few technical problems were experienced is in contrast to previous literature, where many patients have cited technical difficulties as a barrier to use and satisfaction with the intervention [52,54,57,58]. For example, one review of mobile interventions for patients with diabetes reported that 67% of 21 studies reported technical issues [54] and some patients have found these types of issues frustrating and dissatisfying [52].…”

Section: Findings In the Context Of Other Literaturementioning

confidence: 57%

See 1 more Smart Citation

Use of Mobile Devices to Help Cancer Patients Meet Their Information Needs in Non-Inpatient Settings: Systematic Review (Preprint)

Richards¹,

Kinnersley²,

Brain³

et al. 2018

Preprint

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The use of mobile devices to help patients with cancer to meet their information needs in non-inpatient settings: A systematic review IntroductionIt is estimated that one in two people in Great Britain will develop some form of cancer during their lifetime [1]. In 2014, 357,000 new cases of cancer were diagnosed in the UK and the rate of incidence is increasing [2]. However, survival rates have doubled in the UK in the last 40 years and so, for many, cancer is a chronic condition with which they live for many years. Subsequently, there has been a shift from inpatient to outpatient and community cancer care, where patients are required to manage their condition at home, away from regular supervision by clinicians. This change in care requires patients to take a more active role in their treatment and survivorship. Patients are often faced with an uncertain future, unfamiliar tests and procedures, complex decisions about treatment options, treatment-related side-effects and lifestyle changes. In order to take a more active role in their care, and to cope with and manage these changes to daily life, patients require relevant information [3,4]. Research has established that patients have a wide range of information needs throughout their illness. Reviews of these studies suggest that patients generally want information on the extent of the disease, likelihood of cure and prognosis, available treatments, side-effects of treatment, self-care and return to normal life [5][6][7]. Other, less urgent, information needs include the impact of cancer and/or treatment on social activities, family and friends, mental wellbeing and sexual activity, and the risk of family and friends getting cancer [5,6]. There is evidence to suggest that information may help to reduce uncertainty, provide patients with a sense of control over their lives and support informed decision-making about treatment options [8,9]. While many people with cancer want as much information as possible about their condition [10], up to 93% of cancer patients across the US, Europe and the UK report having unmet information needs [11][12][13][14].The introduction of Smart technology has provided a new platform for delivering information-based interventions to patients. Approximately 93% of adults in the UK now personally own or use a mobile phone, of whom 71% specify that they own a Smartphone [15]. Similarly, over two thirds of adults in the UK now own or have access to a tablet computer [15]. Similar statistics of Smart device ownership and use have been reported in cancer patient populations [16,17]. Mobile devices therefore offer the potential for wide reach at the point of need for patients with cancer. Several existing systematic and scoping reviews have explored the general use of mobile devices for patients with cancer [18][19][20][21][22][23]. Findings from these reviews show that mobile interventions have been developed for a range of purposes, including the prevention, detection, and management of cancer; however, most interventions have been designed...

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Section: Findings In the Context Of Other Literaturementioning

confidence: 55%

Section: Findings In the Context Of Other Literaturementioning

confidence: 57%

Use of Mobile Devices to Help Cancer Patients Meet Their Information Needs in Non-Inpatient Settings: Systematic Review (Preprint)

Richards¹,

Kinnersley²,

Brain³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Our study app was simple in its design: users can log, review, and visualize their mood. This simplicity ensures study results will generalize to the wealth of mobile and wearable technology developed for BP [12][13][14][15][16][17][18][19], translating into better technology for individuals with BP to monitoring symptoms.…”

Section: Discussionmentioning

confidence: 99%

“…Increasingly, BP symptoms are being monitored passively through sensors on smartphones and wearable devices [12][13][14][15][16][17]. Smart-phone platforms MONARCA (MONitoring, treAtment and pRediCtion of bipolAr Disorder Episodes) [18] and PRIORI (Predicting Individual Outcomes for Rapid Intervention) [19] predict mood from patterns of speech and behavior from recorded calls, number of phone calls, and phone call duration.…”

Section: Introductionmentioning

confidence: 99%

Engagement Strategies for Self-Monitoring Symptoms of Bipolar Disorder With Mobile and Wearable Technology: Protocol for a Randomized Controlled Trial (Preprint)

Cochran¹,

Belman-Wells²,

McInnis³

2018

Preprint

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“…Interest in applying digital technologies to psychiatric practice has been increasing since the early 2000s, and recommendations for future research in this area were issued in 2013 by a technical expert panel convened by the Agency for Healthcare Research and Quality and the National Institute of Mental Health [10][11][12]. Examples of interventions that have used DHTs in patients with SMI include ecological momentary assessment and treatment interventions [13], computerized psychotherapies [14], cognitive remediation [15,16], family psychoeducation interventions [17], and interventions specifically targeting medication adherence [18].…”

Section: The Potential Of Digital Health Tools For Psychiatric Practicementioning

confidence: 99%

Expert Consensus Survey on Digital Health Tools for Patients With Serious Mental Illness: Optimizing for User Characteristics and User Support (Preprint)

Hatch¹,

Hoffman²,

Ross³

et al. 2018

Preprint

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Background: Digital technology is increasingly being used to enhance healthcare in various areas of medicine. In the area of serious mental illness (SMI), it is important to understand the special characteristics of target users that may influence motivation and competence to use digital health tools (DHTs), as well as the resources and training necessary for these patients to facilitate the use of this technology. Objective: To conduct a quantitative expert consensus survey to identify key characteristics of target users (patients and healthcare professionals [HCPs]), barriers and facilitators for appropriate use, and resources needed to optimize the use of DHTs in patients with SMI. Methods: A panel of 40 experts in digital behavioral health who met the participation criteria completed a 19-question survey rating predefined responses on a 9-point Likert scale. Consensus was determined using a chi-square test of score distributions across 3 ranges (1-3, 4-6, 7-9). Categorical ratings of first, second, or third line were designated based on the lowest category into which the confidence interval of the mean ratings fell, with a boundary >6.5 for first line. Here, we report experts' responses to 9 questions (265 options) that focused on (1) user characteristics that would promote or hinder the use of DHTs, (2) potential benefits/motivators and barriers/unintended consequences of DHT use, and (3) support and training for patients and HCPs. Results: Among patient characteristics most likely to promote use of DHTs, experts endorsed interest in using state-of-the-art technology, availability of necessary resources, good occupational functioning, and perception of the tool as beneficial. Certain diseaseassociated signs and symptoms (eg, more severe symptoms, substance abuse problems, a chaotic living situation) were considered likely to make it difficult for patients to use DHTs. Enthusiasm among HCPs for DHTs and availability of staff and equipment to support their use were identified as variables to enable HCPs to successfully incorporate DHTs into their practices. The experts identified a number of potential benefits of and barriers to use of DHTs by patients and HCPs. Most experts agreed that both HCPs and patients would need to be trained in the use of these new technologies. Conclusions: These results provide guidance to the mental health field on how to optimize the development and deployment of DHTs for patients with SMI.

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Feasibility and Acceptability of a Mobile Intervention to Improve Treatment Adherence in Bipolar Disorder

Cited by 79 publications

References 50 publications

Use of Mobile Devices to Help Cancer Patients Meet Their Information Needs in Non-Inpatient Settings: Systematic Review (Preprint)

Use of Mobile Devices to Help Cancer Patients Meet Their Information Needs in Non-Inpatient Settings: Systematic Review (Preprint)

Engagement Strategies for Self-Monitoring Symptoms of Bipolar Disorder With Mobile and Wearable Technology: Protocol for a Randomized Controlled Trial (Preprint)

Expert Consensus Survey on Digital Health Tools for Patients With Serious Mental Illness: Optimizing for User Characteristics and User Support (Preprint)

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