Pilot feasibility of an mHealth system for conducting ecological momentary assessment of mood-related symptoms following traumatic brain injury

Characterization of chronic pain, pain interference, and daily pain experiences in adult survivors of childhood cancer: a report from the Childhood Cancer Survivor Study

ABSTRACT

Although survivors of childhood cancer are at an increased risk, little is known about the prevalence of chronic pain, associated interference, and daily pain experiences. Survivors (N = 233; mean age = 40.8 years, range 22-64 years; mean time since diagnosis = 32.7 years) from the Childhood Cancer Survivor Study completed pain and psychosocial measures. Survivors with chronic pain completed 2-week, daily measures assessing pain and psychological symptoms using mHealth-based ecological momentary assessment. Multivariable-modified Poisson and linear regression models estimated prevalence ratio estimates (PR) and mean effects with 95% confidence intervals (CI) for associations of key risk factors with chronic pain and pain interference, respectively. Multilevel mixed models examined outcomes of daily pain and pain interference with prior day symptoms. Ninety-six survivors (41%) reported chronic pain, of whom 23 (24%) had severe interference. Chronic pain was associated with previous intravenous methotrexate treatment (PR = 1.6, 95% CI 1.1-2.3), respiratory (PR = 1.8, 95% CI 1.2-2.5), gastrointestinal (PR = 1.6, 95% CI 11.0-2.3), and neurological (PR = 1.5, 95% CI 1.0-2.1) chronic health conditions, unemployment (PR = 1.4, 95% CI 1.0-1.9) and clinically significant depression and anxiety (PR = 2.9, 95% CI 2.0-4.2), as well as a diagnosis of childhood Ewing sarcoma or osteosarcoma (PR = 1.9, 95% CI 1.0-3.5). Higher pain interference was associated with cardiovascular and neurological conditions, unemployment and clinical levels of depression and/or anxiety, and fear of cancer recurrence. For male, but not female survivors, low sleep quality, elevated anxiety, and elevated depression predicted high pain intensity and interference the next day. A substantial proportion of childhood cancer survivors experience chronic pain and significant associated interference. Chronic pain should be routinely evaluated, and interventions are needed.

Acceptability and Feasibility of Text Message Interface to Assess Parents' Real-time PICU Experiences

INTRODUCTION

Parents of children in the pediatric intensive care unit (PICU) experience substantial stress; a parent's perception of their child's illness severity, more than objective measures, predicts psychological outcomes. No tools exist to assess parents' real-time experiences. This pilot study evaluated the feasibility and acceptability of a text-based tool to measure parental experience.

METHODS

Inclusion criteria included PICU stay >48 h, physician approval, smartphone access, and English-speaking caregiver. Eligible parents received a text-based baseline survey and surveys every other day while hospitalized regarding their mood/experiences and optional open-ended questions regarding stressors. They received post-discharge follow-up surveys at 1 week and 1, 3, and 6 months. Follow-up surveys assessed mood and symptoms of depression, anxiety, and post-traumatic stress. Interviews and surveys about the interface were conducted 1 week and 3 months following discharge. Feasibility was assessed by descriptive statistics (eg, response rates), and acceptability was assessed by descriptive statistics (survey results) and thematic analyses of interviews.

RESULTS

Of 20 enrolled participants, the first 5 were excluded due to technical issues. Of the 15 included, results demonstrated feasibility and acceptability. Most participants (86%) completed all surveys during the PICU stay and continued to complete surveys at a high rate: 79%-94% 3 months post-discharge. All participants agreed that the system was easy to use and were satisfied with the system at discharge, and 91% remained satisfied 3 months post-discharge. Additionally, 76% reported comfort, and 69% reported benefit. From the interviews, participants lauded the system's convenience and applicability of content. Some proposed changes to improve ergonomics. Many suggested this interface could help teams better support families.

CONCLUSIONS

A text-based interface for measuring experience in the PICU is feasible and acceptable to parents. Further research can explore how this could identify parents most at risk of adverse psychological sequelae and lead to earlier supportive interventions.

Clinician experiences with using assistive technology in brain injury rehabilitation: a survey of clinician capability, attitudes, and barriers

BACKGROUND

The rise in assistive technology (AT) solutions to support people with an acquired brain injury (ABI) has warranted clinicians to build capability in assisting clients to select goal-centred AT. The study explored, amongst ABI clinicians, (a) capability, attitudes, and barriers with AT implementation, (b) age-related differences in technology self-efficacy and capability (c) strategies to support AT use in rehabilitation and (d) thematic analysis of AT-related experiences.

METHOD

Mixed methods design. Online survey circulated to ABI clinicians across New South Wales, Australia, comprising purpose-designed items as well as the Modified Computer Self-Efficacy Scale (MCSES; range 0-100).

RESULTS

Clinicians (n = 123) were evenly distributed across decadal age groups. The majority were female (90%, n = 111) and one-third were occupational therapists.Clinicians scored strongly on the MCSES (Mdn = 76, IQR = 19), with younger age groups significantly associated with higher scores (H[3] = 9.667, p = .022). Most clinicians (92%) were knowledgeable of mainstream technology for personal use, but over half (65%) reported insufficient knowledge of suitable AT for clients. Clinicians reported positive attitudes towards AT, however, time to research and develop proficiency with a range of AT was the primary barrier (81%).Thematic analysis suggested that whilst the ideal AT experience is client-motivated requiring multidisciplinary guidance, the clinician role and experience with AT is evolving, influenced by rapid technological advancement and extrinsic opportunities to access AT.

CONCLUSIONS

Whilst clinicians have positive attitudes towards AT, there is a gap in clinician implementation. There is need to support further resources to build clinician capability and access to AT.

Protocol for a remote home-based upper extremity self-training program for community-dwelling individuals after stroke

Background

Half of all stroke survivors experience hemiparesis on the contralateral side, resulting in chronic upper extremity (UE) impairment. Remote rehabilitation is a promising approach to optimize the gains made in the clinic to maximize function and promote UE use at home. This paper describes the study protocol for a remote home-based UE self-training program.

Design

This was a feasibility study that used a convergent mixed methods approach.

Methods

We collected data on 15 community-dwelling individuals with UE hemiparesis after stroke. The study used motivational interviewing (MI) and ecological momentary assessments (EMA) to maximize engagement in a 4-week personalized UE self-training program. The study consisted of three phases: 1) training in MI for the interventionists 2) creating customized treatment plans using shared decision making, and 3) four weeks of UE self-training.

Measures and analysis

To evaluate feasibility, we will summarize recruitment and retention rates, intervention delivery, acceptance, adherence, and safety. Quantitative UE outcomes will measure change in UE status after the intervention (Fugl-Meyer Assessment, Motor Activity Log, Canadian Occupational Performance Measure, and bilateral magnitude ratio). Qualitative data (1:1 semi-structured interviews) will capture participants' perceptions and experience with the intervention. Quantitative and qualitative data will be integrated to gain a deeper understanding of the facilitators and barriers for engagement and adherence to UE self-training.

Conclusion

The results of this study will advance the scientific knowledge for use of MI and EMA as methods for enhancing adherence and engagement in UE self-training in stroke rehabilitation. The ultimate impact of this research will be to improve UE recovery for individuals with stroke transitioning back into community.

Clinical trials registration

NCT05032638.

The Behavioral Assessment Screening Tool for Mobile Health (BASTmHealth): Development and Compliance in 2 Weeks of Daily Reporting in Chronic Traumatic Brain Injury

OBJECTIVES

To develop and evaluate the feasibility of a short form of the Behavioral Assessment Screening Tool (BASTmHealth) for high frequency in situ self-reported assessment of neurobehavioral symptoms using mobile health technology for community-dwelling adults with traumatic brain injury (TBI).

DESIGN

Prospective, repeated-measures study of mHealth assessment of self-reported neurobehavioral symptoms in adults with and without a lifetime history of TBI over a 2-week period.

SETTING

Community.

PARTICIPANTS

Community-dwelling adults with (n=52) and without (n=12) a lifetime TBI history consented to the study (N=64).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

BASTmHealth subscales (2-items each): negative affect, fatigue, executive function, substance abuse, impulsivity; feasibility measured via compliance (assessments assigned/assessments completed) and participant-reported usability.

RESULTS

We developed the 10-item BASTmHealth as a screener for high frequency in situ self-reported assessment of neurobehavioral symptoms leveraging mHealth. Compliance for 2 weeks of BASTmHealth supports its feasibility. Fifty-six of 64 participants (87.5%) who completed baseline assessments completed the 2 weeks of daily assessments; all 8 participants who did not complete ecological momentary assessment had a history of TBI. Overall compliance was 81.4% (496 completed of 609 assigned assessments) among all 52 participants with TBI and 96.7% (494 completed of 511 assigned assessments) among the 44 who completed any daily measures, compared with 91.8% (135 completed of 147 assigned assessments) among those with no TBI history. Participants thought the daily surveys were easy to understand and complete and the number of prompts were reasonable.

CONCLUSIONS

Conducting daily high-frequency in situ self-reported assessment of neurobehavioral symptoms using the BASTmHealth is feasible among individuals with and without a lifetime history of TBI. Developing and evaluating self-reported assessments for community-based assessment is a critical step toward expanding remote clinical monitoring systems to improve post-TBI outcomes.

Using Machine Learning to Examine Suicidal Ideation After Traumatic Brain Injury: A Traumatic Brain Injury Model Systems National Database Study

OBJECTIVE

The aim of the study was to predict suicidal ideation 1 yr after moderate to severe traumatic brain injury.

DESIGN

This study used a cross-sectional design with data collected through the prospective, longitudinal Traumatic Brain Injury Model Systems network at hospitalization and 1 yr after injury. Participants who completed the Patient Health Questionnaire-9 suicide item at year 1 follow-up ( N = 4328) were included.

RESULTS

A gradient boosting machine algorithm demonstrated the best performance in predicting suicidal ideation 1 yr after traumatic brain injury. Predictors were Patient Health Questionnaire-9 items (except suicidality), Generalized Anxiety Disorder-7 items, and a measure of heavy drinking. Results of the 10-fold cross-validation gradient boosting machine analysis indicated excellent classification performance with an area under the curve of 0.882. Sensitivity was 0.85 and specificity was 0.77. Accuracy was 0.78 (95% confidence interval, 0.77-0.79). Feature importance analyses revealed that depressed mood and guilt were the most important predictors of suicidal ideation, followed by anhedonia, concentration difficulties, and psychomotor disturbance.

CONCLUSIONS

Overall, depression symptoms were most predictive of suicidal ideation. Despite the limited clinical impact of the present findings, machine learning has potential to improve prediction of suicidal behavior, leveraging electronic health record data, to identify individuals at greatest risk, thereby facilitating intervention and optimization of long-term outcomes after traumatic brain injury.

Usability evaluation of a self-management mobile application for individuals with a mild traumatic brain injury

Objective

Mild traumatic brain injuries (mTBIs) are common and may result in persisting symptoms. Mobile health (mHealth) applications enhance treatment access and rehabilitation. However, there is limited evidence to support mHealth applications for individuals with an mTBI. The primary purpose of this study was to evaluate user experiences and perceptions of the Parkwood Pacing and Planning™ application, an mHealth application developed to help individuals manage their symptoms following an mTBI. The secondary purpose of this study was to identify strategies to improve the application. This study was conducted as part of the development process for this application.

Methods

A mixed methods co-design encompassing an interactive focus group and a follow-up survey was conducted with patient and clinician-participants (n = 8, four per group). Each group participated in a focus group consisting of an interactive scenario-based review of the application. Additionally, participants completed the Internet Evaluation and Utility Questionnaire (UQ). Qualitative analysis on the interactive focus group recordings and notes was performed using phenomenological reflection through thematic analyses. Quantitative analysis included descriptive statistics of demographic information and UQ responses.

Results

On average, clinician and patient-participants positively rated the application on the UQ (4.0 ± .3, 3.8 ± .2, respectively). User experiences and recommendations for improving the application were categorized into four themes: simplicity, adaptability, conciseness, and familiarity.

Conclusion

Preliminary analyses indicates patients and clinicians have a positive experience when using the Parkwood Pacing and Planning™ application. However, modifications that improve simplicity, adaptability, conciseness, and familiarity may further improve the user's experience.

Integration of a personalised mobile health (mHealth) application into the care of patients with brain tumours: proof-of-concept study (IDEAL stage 1)

Objectives

Brain tumours lead to significant morbidity including a neurocognitive, physical and psychological burden of disease. The extent to which they impact the multiple domains of health is difficult to capture leading to a significant degree of unmet needs. Mobile health tools such as Vinehealth have the potential to identify and address these needs through real-world data generation and delivery of personalised educational material and therapies. We aimed to establish the feasibility of Vinehealth integration into brain tumour care, its ability to collect real-world and (electronic) patient-recorded outcome (ePRO) data, and subjective improvement in care.

Design

A mixed-methodology IDEAL stage 1 study.

Setting

A single tertiary care centre.

Participants

Six patients consented and four downloaded and engaged with the mHealth application throughout the 12 weeks of the study.

Main outcome measures

Over a 12-week period, we collected real-world and ePRO data via Vinehealth. We assessed qualitative feedback from mixed-methodology surveys and semistructured interviews at recruitment and after 2 weeks.

Results

565 data points were captured including, but not limited to: symptoms, activity, well-being and medication. EORTC QLQ-BN20 and EQ-5D-5L completion rates (54% and 46%) were impacted by technical issues; 100% completion rates were seen when ePROs were received. More brain cancer tumour-specific content was requested. All participants recommended the application and felt it improved care.

Conclusions

Our findings indicate value in an application to holistically support patients living with brain cancer tumours and established the feasibility and safety of further studies to more rigorously assess this.

Remote Follow-Up Technologies in Traumatic Brain Injury: A Scoping Review

Traumatic brain injury (TBI) remains a leading cause of death and disability worldwide. Motivations for outcome data collection in TBI are threefold: to improve patient outcomes, to facilitate research, and to provide the means and methods for wider injury surveillance. Such data play a pivotal role in population health, and ways to increase the reliability of data collection following TBI should be pursued. As a result, technology-aided follow-up of patients with neurotrauma is on the rise; there is, therefore, a need to describe how such technologies have been used. A scoping review was conducted and reported using the PRISMA extension (PRISMA-ScR). Five electronic databases (Embase, MEDLINE, Global Health, PsycInfo, and Scopus) were searched systematically using keywords derived from the concepts of "telemedicine," "TBI," "outcome assessment," and "patient-generated health data." Forty studies described follow-up technologies (FUTs) utilizing telephones (52.5%, n = 21), short message service (SMS; 10%, n = 4), smartphones (22.5%, n = 9), videoconferencing (10%, n = 4), digital assistants (2.5%, n = 1), and custom devices (2.5%, n = 1) among cohorts of patients with TBI of varying injury severity. Where reported, clinical facilitators, remote follow-up timing and intervals between sessions, synchronicity of follow-up instances, proxy involvement, outcome measures utilized, and technology evaluation efforts are described. FUTs can aid more temporally sensitive assessments and capture fluctuating sequelae, a benefit of particular relevance to TBI cohorts. However, the evidence base surrounding FUTs remains in its infancy, particularly with respect to large samples, low- and middle-income patient cohorts, and the validation of outcome measures for deployment via such remote technology.

Gamification for Machine Learning in Surgical Patient Engagement

Patients and their surgeons face a complex and evolving set of choices in the process of shared decision making. The plan of care must be tailored to individual patient risk factors and values, though objective estimates of risk can be elusive, and these risk factors are often modifiable and can alter the plan of care. Machine learning can perform real-time predictions of outcomes, though these technologies are limited by usability and interpretability. Gamification, or the use of game elements in non-game contexts, may be able to incorporate machine learning technology to help patients optimize their pre-operative risks, reduce in-hospital complications, and hasten recovery. This article proposes a theoretical mobile application to help guide decision making and provide evidence-based, tangible goals for patients and surgeons with the goal of achieving the best possible operative outcome that aligns with patient values.

Synthesis of evidence on the use of ecological momentary assessments to monitor health outcomes after traumatic injury: rapid systematic review

BACKGROUND

With the increasing use of mobile technology, ecological momentary assessments (EMAs) may enable routine monitoring of patient health outcomes and patient experiences of care by health agencies. This rapid review aims to synthesise the evidence on the use of EMAs to monitor health outcomes after traumatic unintentional injury.

METHOD

A rapid systematic review of nine databases (MEDLINE, Web of Science, Embase, CINAHL, Academic Search Premier, PsychINFO, Psychology and Behavioural Sciences Collection, Scopus, SportDiscus) for English-language articles from January 2010-September 2021 was conducted. Abstracts and full-text were screened by two reviewers and each article critically appraised. Key information was extracted by population characteristics, age and sample size, follow-up time period(s), type of EMA tools, physical health or pain outcome(s), psychological health outcome(s), general health or social outcome(s), and facilitators or barriers of EMA methods. Narrative synthesis was undertaken to identify key EMA facilitator and barrier themes.

RESULTS

There were 29 articles using data from 25 unique studies. Almost all (84.0%) were prospective cohort studies and 11 (44.0%) were EMA feasibility trials with an injured cohort. Traumatic and acquired brain injuries and concussion (64.0%) were the most common injuries examined. The most common EMA type was interval (40.0%). There were 10 key facilitator themes (e.g. feasibility, ecological validity, compliance) and 10 key barrier themes (e.g. complex technology, response consistency, ability to capture a participant's full experience, compliance decline) identified in studies using EMA to examine health outcomes post-injury.

CONCLUSIONS

This review highlighted the usefulness of EMA to capture ecologically valid participant responses of their experiences post-injury. EMAs have the potential to assist in routine follow-up of the health outcomes of patients post-injury and their use should be further explored.

App-Based Ecological Momentary Assessment to Enhance Clinical Care for Postpartum Depression: Pilot Acceptability Study

Background

Wearable tracking devices and mobile health technology are increasingly used in an effort to enhance clinical care and the delivery of personalized medical treatment. Postpartum depression is the most frequently diagnosed complication of childbirth; however, significant gaps in screening and treatment remain.

Objective

This study aims to investigate the clinical utility, predictive ability, and acceptability of using ecological momentary assessment to collect daily mood, sleep, and activity data through the use of an Apple Watch and mobile app among women with postpartum depression.

Methods

This was a pilot study consisting of 3 in-person research visits over the course of a 6-week enrollment period. Questionnaires to assess depression, anxiety, and maternal functioning were periodically collected, along with daily self-reported symptoms and passively collected physiological data via an Apple Watch. Feedback was collected from study participants and the study clinician to determine the utility and acceptability of daily tracking. Logistic regression was used to determine whether mood scores in the 2 weeks before a visit predicted scores at follow-up. Compliance with daily assessments was also measured.

Results

Of the 26 women enrolled, 23 (88%) completed the 6-week study period. On average, the participants completed 67% (34.4/51.5 days) of all active daily assessments and 74% (38/51.5 days) of all passive measures. Furthermore, all 23 participants completed the 3 required visits with the research team. Predictive correlations were found between self-reported mood and Edinburgh Postnatal Depression Scale score at follow-up, self-reported anxiety and EDPS, and sleep quality and Edinburgh Postnatal Depression Scale.

Conclusions

Using ecological momentary assessment to track daily symptoms of postpartum depression using a wearable device was largely endorsed as acceptable and clinically useful by participants and the study clinician and could be an innovative solution to increase care access during the COVID-19 pandemic.

Feasibility and Pilot Testing of Mobile Health Apps to Supplement 2 Healthy Lifestyle Interventions in Chronic Traumatic Brain Injury

OBJECTIVES

To determine the feasibility of mobile health (mHealth) apps for enhancing participation of people with chronic traumatic brain injury (TBI) in the Group Lifestyle Balance (GLB-TBI) weight loss intervention and Brain Health Group (BHG-TBI) active control intervention.

SETTING

Community.

PARTICIPANTS

n = 56 overweight/obese adults with moderate-severe TBI.

DESIGN

The GLB-TBI is a 12-month group- and community-based program to promote healthy eating and physical activity. The BHG-TBI is a 12-month group- and community-based program to promote general brain health, designed as an active control condition matched on time, structure, and perceived benefit to the GLB-TBI. In a randomized controlled trial testing the efficacy of the GLB-TBI for weight loss, participants used a group-specific mHealth app providing daily tips customized according to their intervention allocation.

MAIN MEASURES

Compliance (percentage of daily prompts read and completed) and participant-reported satisfaction and usability.

RESULTS

In conjunction with relevant stakeholders, we developed the content and structure of the GLB-TBI and BHG-TBI apps based on core curriculum components. We incorporated cognitive strategies (app notifications) to address potential cognitive impairment common after TBI. Both apps delivered brief daily educational and motivational "tips" derived directly from their respective curricula. Daily use of the apps varied greatly across participants, with most participants who used the apps completing 10% to 50% of daily content. Participants found the apps to be easy to use, but only some found them helpful. App use was substantially different for those who participated in the intervention during (2020) versus before (2019) the COVID-19 pandemic.

CONCLUSIONS

Although enhancing an intensive lifestyle intervention with mHealth technology may be helpful, further refinement is needed to optimize the frequency and delivery methods of mHealth content. Although one might expect remote app use to have been higher during the pandemic, we observed the opposite, potentially due to less hands-on training and ongoing support to use the app and/or general technology fatigue with social distancing.

A systematic review on integrated care for traumatic brain injury, mental health, and substance use

Traumatic brain injuries (TBI) and mental health or substance use disorders (MHSU) are global public health concerns due to their prevalence and impact on individuals and societies. However, care for individuals with TBI and MHSU remains fragmented with a lack of appropriate services and supports across the continuum of healthcare. This systematic review provided an evidence-based foundation to inform opportunities to mobilize and adapt existing resources to integrate care for individuals with TBI and MHSU by comprehensively summarizing existing integrated activities and reported barriers and facilitators to care integration. MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Central Register of Controlled Trials, Sociological Abstracts, and Dissertations & Theses Global were independently reviewed by two reviewers based on pre-determined eligibility criteria. Data on the integration activity, level and type of integration, reported barriers and facilitators, and the strategies aligning with the World Health Organization’s (WHO) Framework on Integrated Person-Centred Care were extracted to form the basis for a narrative synthesis. Fifty-nine peer-reviewed articles were included, describing treatments (N = 49), programs (N = 4), or screening activities (N = 7). Studies discussing clinical integration at the micro- (N = 38) and meso- (N = 10) levels, service integration at the micro- (N = 6) and meso- (N = 5) levels, and functional integration at the meso-level (N = 1) were identified. A minority of articles reported on facilitators (e.g., cognitive accommodations in treatment plans; N = 7), barriers (e.g., lack of education on cognitive challenges associated with TBI; N = 2), or both (N = 6), related to integrating care. This review demonstrated that integrated TBI and MHSU care already exists across a range of levels and types. Given the finite and competing demands for healthcare resources, cognitive accommodations across treatment plans to facilitate integrated TBI and MHSU care should be considered. Multidisciplinary teams should also be explored to provide opportunities for education among health professionals so they can be familiar with TBI and MHSU.

Trial registration: Prospero Registration: CRD42018108343.

Treatment of Psychiatric Problems After Traumatic Brain Injury

Psychiatric sequelae of traumatic brain injury (TBI) can cause significant and often chronic impairment in functioning and quality of life; however, their phenomenological and mechanistic complexities continue to present significant treatment challenges. The clinical presentation is often an amalgam of syndromes and co-occurring symptoms that require a highly nuanced and systematic approach to treatment. Although few randomized controlled trials have tested treatments for psychiatric problems after TBI and the synthesis of results continues to be compromised by the heterogeneity of study populations, small samples, and differing inclusion criteria and outcome measures, an increasing body of literature supports evidence-based treatment strategies. We provide a narrative review of pharmacological, psychoeducational/behavioral, and neuromodulation treatments for psychiatric conditions in adults with TBI and discuss known or postulated mechanisms of action for these treatment approaches. Where data are available, we focus on randomized controlled trials and large case series in which a psychiatric condition provides both a selection criterion and a primary or secondary outcome. We conclude by proposing directions for future research, particularly the need for novel neuropharmacological, behavioral, and neurophysiological studies and pragmatic trials of multicomponent and adaptive models that will increase understanding of the mechanisms underlying post-TBI psychiatric disorders and accelerate dissemination and implementation of effective person-centered care.

Feasibility of an Interactive Coaching App to Enhance Post-concussion Outpatient Care

Objectives: To determine the feasibility of patients to use a web-based health app for management of post-concussion (mTBI) symptoms in an out-patient setting.

Participants: Seven (7) patients who were referred to an outpatient specialist clinic (physiatry) with persisting symptoms following a concussion. Participants had to be 18 years of age or older and more than 3 months post injury.

Design: This was a prospective cohort study using a web-based platform for chronic disease management to guide patients in managing symptoms based on individual clinical recommendations. Each patient received weekly Symptom Management Plans created by a health coach and a physician specialist, designed to reinforce positive progress with clinical recommendations.

Main Measures: Adherence to tracking daily recommendations and symptoms (data collected through the web-interface), The Rivermead Post-Concussion Questionnaire (self report) and a Satisfaction Questionnaire (self report).

Results: Adherence to assigned clinical recommendations was close to 100%. Pre-post results on the patient reported outcome measure (Rivermead Post Concussion Tool) showed improvement for most patients in their experience of symptoms. The Satisfaction Questionnaire showed high rates of satisfaction with the App and the intervention in general.

Conclusions: Use of a web-based health app with a health coach is feasible in this patient population from both the patient and clinician perspective based on high adherence. There is also some evidence of improvement of symptoms with this intervention over time. Further exploration of the use of this type of intervention with post-concussion patients could potentially impact long-term outcomes.

Test-Retest Reliability of Home-Based Fitness Assessments Using a Mobile App (R Plus Health) in Healthy Adults: Prospective Quantitative Study

BACKGROUND

Poor physical fitness has a negative impact on overall health status. An increasing number of health-related mobile apps have emerged to reduce the burden of medical care and the inconvenience of long-distance travel. However, few studies have been conducted on home-based fitness tests using apps. Insufficient monitoring of physiological signals during fitness assessments have been noted. Therefore, we developed R Plus Health, a digital health app that incorporates all the components of a fitness assessment with concomitant physiological signal monitoring.

OBJECTIVE

The aim of this study is to investigate the test-retest reliability of home-based fitness assessments using the R Plus Health app in healthy adults.

METHODS

A total of 31 healthy young adults self-executed 2 fitness assessments using the R Plus Health app, with a 2- to 3-day interval between assessments. The fitness assessments included cardiorespiratory endurance, strength, flexibility, mobility, and balance tests. The intraclass correlation coefficient was computed as a measure of the relative reliability of the fitness assessments and determined their consistency. The SE of measurement, smallest real difference at a 90% CI, and Bland-Altman analyses were used to assess agreement, sensitivity to real change, and systematic bias detection, respectively.

RESULTS

The relative reliability of the fitness assessments using R Plus Health was moderate to good (intraclass correlation coefficient 0.8-0.99 for raw scores, 0.69-0.99 for converted scores). The SE of measurement and smallest real difference at a 90% CI were 1.44-6.91 and 3.36-16.11, respectively, in all fitness assessments. The 95% CI of the mean difference indicated no significant systematic error between the assessments for the strength and balance tests. The Bland-Altman analyses revealed no significant systematic bias between the assessments for all tests, with a few outliers. The Bland-Altman plots illustrated narrow limits of agreement for upper extremity strength, abdominal strength, and right leg stance tests, indicating good agreement between the 2 assessments.

CONCLUSIONS

Home-based fitness assessments using the R Plus Health app were reliable and feasible in young, healthy adults. The results of the fitness assessments can offer a comprehensive understanding of general health status and help prescribe safe and suitable exercise training regimens. In future work, the app will be tested in different populations (eg, patients with chronic diseases or users with poor fitness), and the results will be compared with clinical test results.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2000030905; http://www.chictr.org.cn/showproj.aspx?proj=50229.

Relations among Suicidal Ideation, Depressive Symptoms, and Functional Independence during the Ten Years after Traumatic Brain Injury: A Model Systems Study

OBJECTIVE

To investigate relative causality in relations among suicidal ideation (SI), depressive symptoms, and functional independence over the first 10 years after traumatic brain injury (TBI).

DESIGN

Prospective longitudinal design with data collected through the TBI Model Systems (TBIMS) network at acute rehabilitation hospitalization, as well as 1, 2, 5, and 10 years after injury.

SETTING

United States Level I/II trauma centers and inpatient rehabilitation centers with telephone follow-up.

PARTICIPANTS

Individuals enrolled into the TBIMS National Database (N=9539) with at least one SI score at any follow-up data collection (72.1% male, mean age = 39.39 years).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURE

Patient Health Questionnaire-9 and Functional Independence Measure at years 1, 2, 5, and 10 post-injury.

RESULTS

A cross-lagged panel structural equation model (SEM), which is meant to indirectly infer causality through longitudinal correlational data, suggested that SI, depressive symptoms, and functional independence each significantly predicted themselves over time. Within the model, bivariate correlations among variables were all significant within each time point. Between years 1 and 2 and between years 2 and 5, depressive symptoms had a larger effect on SI than SI had on depressive symptoms. Between years 5 and 10, there was reciprocal causality between the two variables. Functional independence more strongly predicted depressive symptoms than the reverse between years 1 and 2 as well as years 2 and 5, but its unique effects on SI over time were extremely marginal or absent after controlling for depressive symptoms.

CONCLUSIONS

A primary goal for rehabilitation and mental health providers should be to monitor and address elevated symptoms of depression as quickly as possible before they translate into SI, particularly for individuals with TBI who have reduced functional independence. Doing so may be a key to breaking the connection between low functional independence and SI.

Development of a Mobile App for Ecological Momentary Assessment of Circadian Data: Design Considerations and Usability Testing

BACKGROUND

Collecting data on daily habits across a population of individuals is challenging. Mobile-based circadian ecological momentary assessment (cEMA) is a powerful frame for observing the impact of daily living on long-term health.

OBJECTIVE

In this paper, we (1) describe the design, testing, and rationale for specifications of a mobile-based cEMA app to collect timing of eating and sleeping data and (2) compare cEMA and survey data collected as part of a 6-month observational cohort study. The ultimate goal of this paper is to summarize our experience and lessons learned with the Daily24 mobile app and to highlight the pros and cons of this data collection modality.

METHODS

Design specifications for the Daily24 app were drafted by the study team based on the research questions and target audience for the cohort study. The associated backend was optimized to provide real-time data to the study team for participant monitoring and engagement. An external 8-member advisory board was consulted throughout the development process, and additional test users recruited as part of a qualitative study provided feedback through in-depth interviews.

RESULTS

After ≥4 days of at-home use, 37 qualitative study participants provided feedback on the app. The app generally received positive feedback from test users for being fast and easy to use. Test users identified several bugs and areas where modifications were necessary to in-app text and instructions and also provided feedback on the engagement strategy. Data collected through the mobile app captured more variability in eating windows than data collected through a one-time survey, though at a significant cost.

CONCLUSIONS

Researchers should consider the potential uses of a mobile app beyond the initial data collection when deciding whether the time and monetary expenditure are advisable for their situation and goals.

Development and Application of Medicine-Engineering Integration in the Rehabilitation of Traumatic Brain Injury

The rapid progress of the combination of medicine and engineering provides better chances for the clinical treatment and healthcare engineering. Traumatic brain injury (TBI) and its related symptoms have become a major global health problem. At present, these techniques has been widely used in the rehabilitation of TBI. In this review article, we summarizes the progress of the combination of medicine and industry in the rehabilitation of traumatic brain injury in recent years, mainly from the following aspects: artificial intelligence (AI), brain-computer interfaces (BCI), noninvasive brain stimulation (NIBS), and wearable-assisted devices. We believe the summary of this article can improve insight into the combination of medicine and industry in the rehabilitation of traumatic brain injury.

Perceived Recovery and Self-Reported Functioning in Adolescents with Mild Traumatic Brain Injury: The Role of Sleep, Mood, and Physical Symptoms

Purpose: To determine the contributions of anxiety, depressive, and concussion symptoms and sleep quality to self-perceived recovery in adolescents with concussion.Method: Adolescents aged 12-20 (n = 298) completed anxiety, depression, concussion symptoms, and sleep measures at an initial concussion clinic visit and three-month follow-up. At follow-up, they reported self-perceived recovery as percent back to normal.Results: Injury-related factors alone did not predict self-perceived recovery (R²_Adj =.017, p =.074). More concurrent physical, mental health, and sleep symptoms explained 18.8% additional variance in poorer self-perceived recovery (R²_Adj Change =.188, p <.05). Physical symptoms (B_stand = -.292) and anxiety (B_stand = -.260) accounted for the most variance in self-perceived recovery.Conclusion: Post-concussive symptoms, in particular anxiety and self-reported physical symptoms, seem to characterize protracted recovery. Self-perceived recovery as an outcome measure may provide a more holistic understanding of adolescents' experiences after concussion.

Compliance With Mobile Ecological Momentary Assessment of Self-Reported Health-Related Behaviors and Psychological Constructs in Adults: Systematic Review and Meta-analysis

Background

Mobile ecological momentary assessment (mEMA) permits real-time capture of self-reported participant behaviors and perceptual experiences. Reporting of mEMA protocols and compliance has been identified as problematic within systematic reviews of children, youth, and specific clinical populations of adults.

Objective

This study aimed to describe the use of mEMA for self-reported behaviors and psychological constructs, mEMA protocol and compliance reporting, and associations between key components of mEMA protocols and compliance in studies of nonclinical and clinical samples of adults.

Methods

In total, 9 electronic databases were searched (2006-2016) for observational studies reporting compliance to mEMA for health-related data from adults (>18 years) in nonclinical and clinical settings. Screening and data extraction were undertaken by independent reviewers, with discrepancies resolved by consensus. Narrative synthesis described participants, mEMA target, protocol, and compliance. Random effects meta-analysis explored factors associated with cohort compliance (monitoring duration, daily prompt frequency or schedule, device type, training, incentives, and burden score). Random effects analysis of variance (P≤.05) assessed differences between nonclinical and clinical data sets.

Results

Of the 168 eligible studies, 97/105 (57.7%) reported compliance in unique data sets (nonclinical=64/105 [61%], clinical=41/105 [39%]). The most common self-reported mEMA target was affect (primary target: 31/105, 29.5% data sets; secondary target: 50/105, 47.6% data sets). The median duration of the mEMA protocol was 7 days (nonclinical=7, clinical=12). Most protocols used a single time-based (random or interval) prompt type (69/105, 65.7%); median prompt frequency was 5 per day. The median number of items per prompt was similar for nonclinical (8) and clinical data sets (10). More than half of the data sets reported mEMA training (84/105, 80%) and provision of participant incentives (66/105, 62.9%). Less than half of the data sets reported number of prompts delivered (22/105, 21%), answered (43/105, 41%), criterion for valid mEMA data (37/105, 35.2%), or response latency (38/105, 36.2%). Meta-analysis (nonclinical=41, clinical=27) estimated an overall compliance of 81.9% (95% CI 79.1-84.4), with no significant difference between nonclinical and clinical data sets or estimates before or after data exclusions. Compliance was associated with prompts per day and items per prompt for nonclinical data sets. Although widespread heterogeneity existed across analysis (I²>90%), no compelling relationship was identified between key features of mEMA protocols representing burden and mEMA compliance.

Conclusions

In this 10-year sample of studies using the mEMA of self-reported health-related behaviors and psychological constructs in adult nonclinical and clinical populations, mEMA was applied across contexts and health conditions and to collect a range of health-related data. There was inconsistent reporting of compliance and key features within protocols, which limited the ability to confidently identify components of mEMA schedules likely to have a specific impact on compliance.

Use of mHealth Technology for Patient-Reported Outcomes in Community-Dwelling Adults with Acquired Brain Injuries: A Scoping Review

The purpose of our scoping review was to describe the current use of mHealth technology for long-term assessment of patient-reported outcomes in community-dwelling individuals with acquired brain injury (ABI). Following PRISMA guidelines, we conducted a scoping review of literature meeting these criteria: (1) civilians or military veterans, all ages; (2) self-reported or caregiver-reported outcomes assessed via mobile device in the community (not exclusively clinic/hospital); (3) published in English; (4) published in 2015-2019. We searched Ovid MEDLINE(R) < 1946 to 16 August 2019, MEDLINE InProcess, EPub, Embase, and PsycINFO databases for articles. Thirteen manuscripts representing 12 distinct studies were organized by type of ABI [traumatic brain injury (TBI) and stroke] to extract outcomes, mHealth technology used, design, and inclusion of ecological momentary assessment (EMA). Outcomes included post-concussive, depressive, and affective symptoms, fatigue, daily activities, stroke risk factors, and cognitive exertion. Overall, collecting patient-reported outcomes via mHealth was feasible and acceptable in the chronic ABI population. Studies consistently showed advantage for using EMA despite variability in EMA timing/schedules. To ensure best clinical measurement, research on post-ABI outcomes should consider EMA designs (versus single time-point assessments) that provide the best timing schedules for their respective aims and outcomes and that leverage mHealth for data collection.

Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study

BACKGROUND

Smartphone-based symptom monitoring has gained increased attention in psychiatric research as a cost-efficient tool for prospective and ecologically valid assessments based on participants' self-reports. However, a meaningful interpretation of smartphone-based assessments requires knowledge about their psychometric properties, especially their validity.

OBJECTIVE

The goal of this study is to systematically investigate the validity of smartphone-administered assessments of self-reported affective symptoms using the Remote Monitoring Application in Psychiatry (ReMAP).

METHODS

The ReMAP app was distributed to 173 adult participants of ongoing, longitudinal psychiatric phenotyping studies, including healthy control participants, as well as patients with affective disorders and anxiety disorders; the mean age of the sample was 30.14 years (SD 11.92). The Beck Depression Inventory (BDI) and single-item mood and sleep information were assessed via the ReMAP app and validated with non-smartphone-based BDI scores and clinician-rated depression severity using the Hamilton Depression Rating Scale (HDRS).

RESULTS

We found overall high comparability between smartphone-based and non-smartphone-based BDI scores (intraclass correlation coefficient=0.921; P<.001). Smartphone-based BDI scores further correlated with non-smartphone-based HDRS ratings of depression severity in a subsample (r=0.783; P<.001; n=51). Higher agreement between smartphone-based and non-smartphone-based assessments was found among affective disorder patients as compared to healthy controls and anxiety disorder patients. Highly comparable agreement between delivery formats was found across age and gender groups. Similarly, smartphone-based single-item self-ratings of mood correlated with BDI sum scores (r=-0.538; P<.001; n=168), while smartphone-based single-item sleep duration correlated with the sleep item of the BDI (r=-0.310; P<.001; n=166).

CONCLUSIONS

These findings demonstrate that smartphone-based monitoring of depressive symptoms via the ReMAP app provides valid assessments of depressive symptomatology and, therefore, represents a useful tool for prospective digital phenotyping in affective disorder patients in clinical and research applications.

Evaluating the Cross-Sectional and Longitudinal Relationships Predicting Suicidal Ideation Following Traumatic Brain Injury

OBJECTIVE

Characterize relationships among substance misuse, depression, employment, and suicidal ideation (SI) following moderate to severe traumatic brain injury (TBI).

DESIGN

Prospective cohort study.

SETTING

Inpatient rehabilitation centers with telephone follow-up; level I/II trauma centers in the United States.

PARTICIPANTS

Individuals with moderate to severe TBI with data in both the National Trauma Data Bank and the Traumatic Brain Injury Model Systems National Database, aged 18 to 59 years, with SI data at year 1 or year 2 postinjury (N = 1377).

MAIN OUTCOME MEASURE

Primary outcome of SI, with secondary employment, substance misuse, and depression outcomes at years 1 and 2 postinjury.

RESULTS

Cross-lagged structural equation modeling analysis showed that year 1 unemployment and substance misuse were associated with a higher prevalence of year 1 depression. Depression was associated with concurrent SI at years 1 and 2. Older adults and women had a greater likelihood of year 1 depression. More severe overall injury (injury severity score) was associated with a greater likelihood of year 1 SI, and year 1 SI was associated with a greater likelihood of year 2 SI.

CONCLUSIONS

Substance misuse, unemployment, depression, and greater extracranial injury burden independently contributed to year 1 SI; in turn, year 1 SI and year 2 depression contributed to year 2 SI. Older age and female sex were associated with year 1 depression. Understanding and mitigating these risk factors are crucial for effectively managing post-TBI SI to prevent postinjury suicide.

Real-time measurement of post-stroke fatigue in daily life and its relationship with the retrospective Fatigue Severity Scale

Improving our understanding of post-stroke fatigue is crucial to develop more effective interventions. This effort may be hampered by the methods used to assess fatigue, which usually rely on retrospective memory reports. However, such reports are prone to memory bias and may not capture variability in fatigue in daily life; thereby failing to adequately represent symptom experience. This study aimed to assess the strength of the relationship between real-time experience of post-stroke fatigue and the commonly used retrospective Fatigue Severity Scale (FSS). Thirty individuals with stroke completed 10 daily questionnaires about momentary (here-and-now) fatigue for six consecutive days using the mHealth application PsyMate^TM (Experience Sampling Method). From these real-time fatigue ratings (N = 1012), we calculated three indices: total average, peak fatigue, and fatigue on the final day. Afterwards, participants rated their fatigue retrospectively with the FSS. Results showed weak to moderate and strong correlations (range: .334, .667), with retrospective reports capturing up to 44% of the variance in the indices of momentary fatigue. Exploratory analyses also revealed that even individuals with similar total FSS scores demonstrated highly different day-to-day fatigue patterns. We conclude that retrospective measures may provide an incomplete view of post-stroke fatigue and diurnal variation therein.

Smartphone-Based Experience Sampling in People With Mild Cognitive Impairment: Feasibility and Usability Study

BACKGROUND

Daily functioning of people with cognitive disorders such as mild cognitive impairment (MCI) is usually depicted by retrospective questionnaires, which can be memory-biased and neglect fluctuations over time or contexts.

OBJECTIVE

This study examines the feasibility and usability of applying the experience sampling method (ESM) in people with MCI to provide a detailed and dynamic picture of behavioral, emotional, and cognitive patterns in everyday life.

METHODS

For 6 consecutive days, 21 people with MCI used an ESM app on their smartphones. At 8 semi-random timepoints per day, participants filled in momentary questionnaires on mood, activities, social context, and subjective cognitive complaints. Feasibility was determined through self-reports and observable human-technology interactions. Usability was demonstrated on an individual and group level.

RESULTS

Of the 21 participants, 3 dropped out due to forgetting to carry their smartphones or forgetting the study instructions. In the remaining 18 individuals, the compliance rate was high, at 78.7%. Participants reported that momentary questions reflected their daily experiences well. Of the 18 participants, 13 (72%) experienced the increase in awareness of their own memory functions as pleasant or neutral.

CONCLUSIONS

Support was found for the general feasibility of smartphone-based experience sampling in people with MCI. However, many older adults with MCI are currently not in possession of smartphones, and study adherence seems challenging for a minority of individuals. Momentary data can increase the insights into daily patterns and may guide the person-tailored development of self-management strategies in clinical settings.

Acceptance of Rehabilitation Technology in Adults With Moderate to Severe Traumatic Brain Injury, Their Caregivers, and Healthcare Professionals: A Systematic Review

BACKGROUND

Moderate to severe traumatic brain injuries (TBIs) commonly result in persistent physical, cognitive, and/or emotional deficits that require long-term rehabilitation. Technology-enabled rehabilitation provides an innovative alternative to traditional intervention models. End-user acceptance of these interventions, however, is a critical factor in determining the effective implementation and acceptance of these technologies.

OBJECTIVE

To systematically review the literature to identify methods and measures used to evaluate user acceptance relating to rehabilitation technologies for adults with moderate to severe TBI, their caregivers, and healthcare professionals.

METHODS

Six key databases including Medline, Embase, CINAHL, Cochrane, Scopus, and Web of Science were searched using the relevant search terms.

RESULTS

From a yield of 2059 studies, 13 studies met the eligibility criteria. The review revealed limited research that formally evaluated user acceptance in relation to rehabilitation technologies designed for adults with TBI. Furthermore, where such evaluations were conducted, comprehensive research designs incorporating theoretical frameworks of technology acceptance were sparse. Importantly, a range of technologies and recommendations that positively influenced user acceptance were identified. Future directions for research in this area include the use of theory-driven research designs to enhance our understanding of technology acceptance, to support the development of rehabilitation technologies that maximize functional outcomes for individuals with TBI.

Enhancement of Neurocognitive Assessments Using Smartphone Capabilities: Systematic Review

BACKGROUND

Comprehensive exams such as the Dean-Woodcock Neuropsychological Assessment System, the Global Deterioration Scale, and the Boston Diagnostic Aphasia Examination are the gold standard for doctors and clinicians in the preliminary assessment and monitoring of neurocognitive function in conditions such as neurodegenerative diseases and acquired brain injuries (ABIs). In recent years, there has been an increased focus on implementing these exams on mobile devices to benefit from their configurable built-in sensors, in addition to scoring, interpretation, and storage capabilities. As smartphones become more accepted in health care among both users and clinicians, the ability to use device information (eg, device position, screen interactions, and app usage) for subject monitoring also increases. Sensor-based assessments (eg, functional gait using a mobile device's accelerometer and/or gyroscope or collection of speech samples using recordings from the device's microphone) include the potential for enhanced information for diagnoses of neurological conditions; mapping the development of these conditions over time; and monitoring efficient, evidence-based rehabilitation programs.

OBJECTIVE

This paper provides an overview of neurocognitive conditions and relevant functions of interest, analysis of recent results using smartphone and/or tablet built-in sensor information for the assessment of these different neurocognitive conditions, and how human-device interactions and the assessment and monitoring of these neurocognitive functions can be enhanced for both the patient and health care provider.

METHODS

This survey presents a review of current mobile technological capabilities to enhance the assessment of various neurocognitive conditions, including both neurodegenerative diseases and ABIs. It explores how device features can be configured for assessments as well as the enhanced capability and data monitoring that will arise due to the addition of these features. It also recognizes the challenges that will be apparent with the transfer of these current assessments to mobile devices.

RESULTS

Built-in sensor information on mobile devices is found to provide information that can enhance neurocognitive assessment and monitoring across all functional categories. Configurations of positional sensors (eg, accelerometer, gyroscope, and GPS), media sensors (eg, microphone and camera), inherent sensors (eg, device timer), and participatory user-device interactions (eg, screen interactions, metadata input, app usage, and device lock and unlock) are all helpful for assessing these functions for the purposes of training, monitoring, diagnosis, or rehabilitation.

CONCLUSIONS

This survey discusses some of the many opportunities and challenges of implementing configured built-in sensors on mobile devices to enhance assessments and monitoring of neurocognitive functions as well as disease progression across neurodegenerative and acquired neurological conditions.

A Review of Smartphone Applications for Persons With Traumatic Brain Injury: What Is Available and What Is the Evidence?

OBJECTIVES

To map the number and type of smartphone applications available for persons with traumatic brain injury (TBI), evaluate validity of app content, and investigate evidence for any claims made.

METHODS

We searched iTunes and Google Play and also completed a web search. The purpose of each app and any claims were extracted, and a search for best available evidence was performed.

RESULTS

Seventy apps met our inclusion criteria (35 related to assessment, 11 to education, 9 to treatment/management, 8 to impact sensors, and 7 to symptom tracking). To the best of our knowledge, no empirical research has been published to demonstrate that the use of any particular TBI-related app leads to clinically meaningful benefits compared with not using the app. Other problems include potential biases in self-report leading to possible app misuse, lack of references for app content, and inappropriate marketing to laypersons not trained to interpret the findings of tools validated for use by healthcare professionals.

CONCLUSIONS

The current evidence for benefit from using TBI-related apps is minimal. More collaborative research is needed among clinicians, scientists, and app developers to determine whether, and how, apps may be helpful to individuals at risk for or following TBI.

Ecological Momentary Assessment in Patients With an Acquired Brain Injury: A Pilot Study on Compliance and Fluctuations

Ecological Momentary Assessment (EMA) promises to be a suitable method for capturing the dynamics in self-assessments through repeated measurements in naturalistic environments using common mobile devices. Therefore, EMA could increase the power of neuropsychological assessment by obtaining a more fine-grained picture of symptoms, limitations, and strengths in patients with an acquired brain injury (ABI) in real-life situations. The present study examined 15 patients with an ABI with cognitive and motor impairments. Following a semirandomized high-frequency sampling plan to assess EMA's feasibility and applicability, data were collected across 7 days. At eight prompts per day, patients were asked about their current activities, the social context they were in, their current mood, performance judgments of their own functional status, and the frequency of self-reflections. The average compliance rate was 71.6%. The fluctuations in patients' responses were measured in terms of variance distributions within simple (intercept only) three-level models and root mean square of successive difference values. They were sufficient, as shown, for example, by the mean within-person variability of 44.9% across all of the items studied. There were no significant correlations between patients' age, severity of depressive symptoms, or their level of functioning and their compliance with study participation or the variability of their responses. The results support the feasibility and applicability of EMA as an assessment technique in patients with an ABI. There are, however, limitations that should be considered when planning an assessment of brain-injured patients using EMA.

Establishment of a Patient-Centered Outcomes Research Network for Individuals with TBI and Neuropsychiatric Symptoms

Aims: The overarching goal of this project was to establish a group comprised of a variety of TBI stakeholders for the purpose of: (1) determining facilitators and barriers in management of neuropsychiatric symptoms after TBI; (2) identifying strategies for maintaining a TBI PCOR network; (3) enumerating research topics related to TBI neuropsychiatry; and (4) highlighting policy changes related to TBI neuropsychiatry.Methods: Twenty-nine TBI stakeholders participated in focus group discussions. Qualitative analyses were conducted both manually and using Dedoose software.Results: Participant-identified barriers included stigma associated with experiencing neuropsychiatric symptoms and poor insurance coverage. Facilitators included treatment focused on education of neuropsychiatric symptoms after TBI and having a comprehensive caregiver plan. Best strategies for maintaining TBI PCOR network included having a well-defined project, continued regular meetings, and on-going education of network members. Pertinent research topics included TBI and aging, factors influencing outcomes after TBI, substance use disorders related to TBI, and effectiveness of telemental health services. Needed policy changes included making TBI neuropsychiatry education accessible to stakeholders and improving accessibility of TBI neuropsychiatric care.Conclusion: TBI stakeholders identified several facilitators of care for neuropsychiatric symptoms after TBI and suggested research topics and best practices for conducting PCOR in this area.

Usability Evaluations of Mobile Mental Health Technologies: Systematic Review

Background

Many mobile health (mHealth) apps for mental health have been made available in recent years. Although there is reason to be optimistic about their effect on improving health and increasing access to care, there is a call for more knowledge concerning how mHealth apps are used in practice.

Objective

This study aimed to review the literature on how usability is being addressed and measured in mHealth interventions for mental health problems.

Methods

We conducted a systematic literature review through a search for peer-reviewed studies published between 2001 and 2018 in the following electronic databases: EMBASE, CINAHL, PsycINFO, PubMed, and Web of Science. Two reviewers independently assessed all abstracts against the inclusion and exclusion criteria, following the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines.

Results

A total of 299 studies were initially identified based on the inclusion keywords. Following a review of the title, abstract, and full text, 42 studies were found that fulfilled the criteria, most of which evaluated usability with patients (n=29) and health care providers (n=11) as opposed to healthy users (n=8) and were directed at a wide variety of mental health problems (n=24). Half of the studies set out to evaluate usability (n=21), and the remainder focused on feasibility (n=10) or acceptability (n=10). Regarding the maturity of the evaluated systems, most were either prototypes or previously tested versions of the technology, and the studies included few accounts of sketching and participatory design processes. The most common reason referred to for developing mobile mental health apps was the availability of mobile devices to users, their popularity, and how people in general became accustomed to using them for various purposes.

Conclusions

This study provides a detailed account of how evidence of usability of mHealth apps is gathered in the form of usability evaluations from the perspective of computer science and human-computer interaction, including how users feature in the evaluation, how the study objectives and outcomes are stated, which research methods and techniques are used, and what the notion of mobility features is for mHealth apps. Most studies described their methods as trials, gathered data from a small sample size, and carried out a summative evaluation using a single questionnaire, which indicates that usability evaluation was not the main focus. As many studies described using an adapted version of a standard usability questionnaire, there may be a need for developing a standardized mHealth usability questionnaire.

Feasibility Study of Problem-Solving Training for Care Partners of Adults With Traumatic Brain Injury, Spinal Cord Injury, Burn Injury, or Stroke During the Inpatient Hospital Stay

OBJECTIVE

To determine the feasibility of delivering an evidence-based self-management intervention, problem-solving training (PST), to care partners of individuals with traumatic brain injury (TBI), spinal cord injury (SCI), burn injury, or stroke during the inpatient hospital stay.

DESIGN

In this single group pre-post intervention pilot feasibility study.

SETTING

Inpatient rehabilitation or acute care and community.

PARTICIPANTS

Care partners (spouse or partner, family member, friend who is in any way responsible for the health or well-being of the care recipient) of individuals with TBI, SCI, burn injury, or stroke (N=39).

INTERVENTION

PST is a metacognitive self-management intervention that teaches individuals a global strategy for addressing self-selected problems. Participants received up to 6 sessions of PST in person or via telephone during their care recipient's inpatient stay.

MAIN OUTCOME MEASURES

We measured feasibility of recruitment, intervention delivery, and postintervention use of a smartphone app (Care Partner Problem Solving [CaPPS]) and participant satisfaction (Client Satisfaction Questionnaire [CSQ]) and engagement (Pittsburgh Rehabilitation Participation Scale [PRPS]) with the intervention.

RESULTS

Of 39 care partners approached, n=10 (25.6%) were ineligible. Of n=29 (74.4%) who were eligible, n=17 (58.6%) refused, and n=12 (41.4%) consented, of whom n=8 (66.7%) completed ≥3 PST sessions. Not perceiving any benefit was the most common reason for refusal, followed by no interest in research. Participants were very satisfied with PST (CSQ mean=3.35, SD=0.60), reported strong working alliance (Working Alliance Inventory mean=6.8, SD=3.1), and demonstrated very good engagement (PRPS mean=4.75, SD=1.41). CaPPS was downloaded and used by only n=3 participants.

CONCLUSIONS

Delivering a self-management intervention to care partners during the care recipient's acute hospital stay is feasible for a subset of potential participants. Short lengths of stay, language fluency, and perceiving no potential benefit were noted barriers. Boosters via smartphone app have potential, but several barriers must first be overcome.

Mood Monitoring Over One Year for People With Chronic Obstructive Pulmonary Disease Using a Mobile Health System: Retrospective Analysis of a Randomized Controlled Trial

Background

Comorbid anxiety and depression can add to the complexity of managing treatment for people living with chronic obstructive pulmonary disease (COPD). Monitoring mood has the potential to identify individuals who might benefit from additional support and treatment.

Objective

We used data from the sElf-management anD support proGrammE (EDGE) trial to examine: (1) the extent to which the mood-monitoring components of a mobile health system for patients with COPD were used by participants; (2) the levels of anxiety and depression symptoms among study participants; (3) the extent to which videos providing advice about coping with low mood were viewed; and (4) the characteristics of participants with differing levels of mood and utilization of mood monitoring.

Methods

A total of 107 men and women with a clinical diagnosis of COPD, aged ≥40 years old, were recruited to the intervention arm of the EDGE trial. Participants were invited to complete the Patient Health Questionnaire-8 and the Generalized Anxiety Disorder-7 test every four weeks using a tablet computer. Mood disturbance based on these measures was defined as a score ≥5 on either scale. Participants reporting a mood disturbance were automatically directed (signposted) to a stress or mood management video. Study outcomes included measures of health status, respiratory quality of life, and symptoms of anxiety and depression.

Results

Overall, 94 (87.9%) participants completed the 12-month study. A total of 80 participants entered at least one response each month for at least ten months. On average, 16 participants (range 8-38 participants) entered ≥2 responses each month. Of all the participants, 47 (50%) gave responses indicating a mood disturbance. Participants with a mood disturbance score for both scales (n=47) compared with those without (n=20) had lower health status (P=.008), lower quality of life (P=.009), and greater anxiety (P<.001) and increased depression symptoms (P<.001). Videos were viewed by 64 (68%) people over 12 months. Of the 220 viewing visualizations, 70 (34.7%) began after being signposted. Participants signposted to the stress management video (100%; IQR 23.3-100%) watched a greater proportion of it compared to those not signposted (38.4%; IQR 16.0-68.1%; P=.03), whereas duration of viewing was not significantly different for the mood management video.

Conclusions

Monitoring of anxiety and depression symptoms for people with COPD is feasible. More than half of trial participants reported scores indicating a mood disturbance during the study. Signposting participants to an advisory video when reporting increased symptoms of a mood disturbance resulted in a longer view-time for the stress management video. The opportunity to elicit measures of mood regularly as part of a health monitoring system could contribute to better care for people with COPD.

Behavioral Activation Augmented With Mobile Technology for Depression and Anxiety in Chronic Moderate-Severe Traumatic Brain Injury: Protocol for a Randomized Controlled Trial

Objective

To describe and provide the rationale for a randomized controlled trial for depression or anxiety after moderate to severe traumatic brain injury (TBI), which will test 2 treatments based on behavioral activation (BA), a promising model to promote both positive mood and increased activity in this population.

Design

Randomized controlled trial with masked outcome assessment.

Setting

Outpatient catchment area of 1 TBI treatment center.

Participants

Community-dwelling persons (N=60) with moderate-severe TBI at least 6 months prior to enrollment and greater than mild depression or anxiety.

Interventions

Participants will be randomized 2:1 into an 8-session treatment, behavioral activation with technology, consisting of 6 face-to-face sessions and 2 via phone, with mood and activity monitoring conducted via ecological momentary assessment on a smartphone; or a single session incorporating BA principles followed by 8 weeks of activity reminders in the form of implementation intentions, delivered as text messages.

Main Outcome Measures

Brief Symptom Inventory-18 (primary outcome); Environmental Reward Observation Scale, Behavioral Activation for Depression Scale, Participation Assessment with Recombined Tools-Objective, Diener Satisfaction With Life Scale, Quality of Life after Brain Injury scale, Patient Global Impression of Change. Outcomes are measured midway through intervention, after treatment cessation (primary outcome), and at 2-month follow-up. A treatment enactment interview is administered after the follow-up to ascertain to what extent participants continue to engage in activities and use strategies promoted during trial participation.

Results

N/A.

Conclusions

N/A.

Mobile Health for Traumatic Brain Injury: A Systematic Review of the Literature and Mobile Application Market

Traumatic Brain Injury (TBI) is a growing public health issue with an increasing burden of disease globally. TBI can lead to significant motor, cognitive and emotional deficits. Mobile health (mHealth) is a promising technology to help diagnose and manage patients with TBI. The aim of this study was to systematically examine and classify available TBI mobile applications (apps) and critically appraise the literature underpinning mHealth for the management of TBI. Two major app markets (Apple and Google Play) were systematically searched. Included apps were classified and had data extracted. Coupled to this, a systematic search of the literature (MEDLINE, Web of Science, Scopus, PsycINFO) was performed examining the effectiveness of mHealth interventions in helping patients manage their symptoms after TBI (registered with PROSPERO: CRD42018107386). From 1296 apps, 53 met our inclusion criteria. The top three functions were TBI screening, education and biomechanics monitoring. Twenty-six apps (49.1%) focused on sports-related concussion. Eight apps (15.1%) were gamified and 12 apps (22.6%) connected to an external device. From the literature, a total of eight articles were included of which four (50%) were case series, two (25%) were feasibility/pilot studies, one (12.5%) was a case report, and one (12.5%) was a randomised controlled trial. The median number of patients was seven (1 - 43). There is a small number of mobile apps for TBI, mostly focusing on sports-related concussion. At present, the uptake and application of these apps as a management aid is limited and the evidence for their usefulness in TBI remains low.

Iterative processes: a review of semi-supervised machine learning in rehabilitation science

Purpose: To define semi-supervised machine learning (SSML) and explore current and potential applications of this analytic strategy in rehabilitation research.Method: We conducted a scoping review using PubMed, GoogleScholar and Medline. Studies were included if they: (1) described a semi-supervised approach to apply machine learning algorithms during data analysis and (2) examined constructs encompassed by the International Classification of Functioning, Disability and Health (ICF). The first two authors reviewed identified articles and recorded study and participant characteristics. The ICF domain used in each study was also identified.Results: After combining information from the eight studies, we established that SSML was a feasible approach for analysis of complex data in rehabilitation research. We also determined that semi-supervised approaches may be more accurate than supervised machine learning approaches.Conclusions: A semi-supervised approach to machine learning has potential to enhance our understanding of complex data sets in rehabilitation science. SSML mirrors the iterative process of rehabilitation, making this approach ideal for calibrating devices, classifying activities or identifying just-in-time interventions. Rehabilitation scientists who are interested in conducting SSML should collaborate with data scientists to advance the application of this approach within our field.Implications for rehabilitationSemi-supervised machine learning applications may be a feasible approach for analyses of complex data sets in rehabilitation research.Semi-supervised machine learning approaches uses a combination of labelled and unlabelled data to produce accurate predictive models, thereby requiring less user-input data than other machine learning approaches (i.e., supervised, unsupervised), reducing resource cost and user-burden.Semi-supervised machine learning is an iterative process that, when applied to rehabilitation assessment and outcomes, could produce accurate personalized models for treatment.Rehabilitation researchers and data scientists should collaborate to implement semi-supervised machine learning approaches in rehabilitation research, optimizing the power of large datasets that are becoming more readily available within the field (e.g., EEG signals, sensors, smarthomes).

A randomized controlled trial protocol for people with traumatic brain injury enrolled in a healthy lifestyle program (GLB-TBI)

Weight gain is prevalent among people with traumatic brain injury (TBI) and may be attributable to environmental or injury-specific factors such as mobility impairment, endocrine dysfunction, behavioral and emotional disorders, and sensory loss. Few weight management programs exist to meet the unique needs of this population. Researchers modified a nationally recognized, evidence-based weight-loss program, Group Lifestyle Balance™ (GLB), to address the needs of over-weight and obese people post TBI (GLB-TBI). This current randomized controlled trial (RCT) examines the efficacy of the GLB-TBI on weight and secondary outcomes compared to an attention control educational support group. Furthermore, researchers have developed a mobile technology app to further engage participants in the program. This RCT will enroll and randomize 66 participants over a two-year period. It is anticipated that findings from this current RCT will contribute to the knowledge and evidence for an effective weight-loss intervention among this underserved population, with a goal of achieving full recognition by the Centers for Disease Control and Prevention-National Diabetes Prevention Program and subsequent Center for Medicare and Medicaid Services reimbursement for participation.

Remote supervision of rehabilitation interventions for survivors of moderate or severe traumatic brain injury: A scoping review

INTRODUCTION

Individuals with moderate or severe traumatic brain injury (TBI) often have persistent impairments upon discharge home. In rural communities, specialized rehabilitation services to address impairments can be difficult to access. The purpose of this scoping review is to examine how remote supervision is currently being used in TBI rehabilitation to identify gaps in knowledge that need to be addressed to facilitate access to and implementation of these services.

METHODS

The main objective for this review is to identify the methods being used to deliver remote supervision for rehabilitation in a moderate or severe TBI population. The aim of this review was to document the implementation characteristics of remote supervision used including: (1) type of supervision such as synchronous, asynchronous supervision or mixed; (2) frequency and intensity of remote supervision; and (3) outcomes used to measure intervention delivery as well as effectiveness within this population. This scoping review follows EQUATOR Network recommendations for screening and extracting data.

RESULTS

Twenty-six studies using a variety of remote supervision technology and outcome measures were included. Supervision frequency and intensity are poorly reported with no standardization. One hundred and six outcome measures were reported in this review showing large diversity in the areas being explored.

DISCUSSION

Different types of remote supervision have been used with this population; however, there are no clear guidelines on clinical implementation. Future studies must better define implementation parameters of remote supervision. Benefit on physical activity, balance and mobility outcomes also need to be further explored.

Methodological Strategies for Ecological Momentary Assessment to Evaluate Mood and Stress in Adult Patients Using Mobile Phones: Systematic Review

Background

Ecological momentary assessment (EMA) has utility for measuring psychological properties in daily life. EMA has also allowed researchers to collect data on diverse experiences and symptoms from various subjects.

Objective

The aim of this study was to review methodological strategies and useful related information for EMA using mobile phones to capture changes of mood and stress in adult patients seeking health care.

Methods

We searched PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, the Cochrane Library, PsycINFO, and Web of Science. This review included studies published in peer-reviewed journals in English between January 2008 and November 2017 that used basic- or advanced-feature mobile phones to measure momentary mood or stress in adult patients seeking health care in outpatient departments. We excluded studies of smoking and substance addictions and studies of mental disorder patients who had been diagnosed by physicians.

Results

We reviewed 12 selected articles that used EMA via mobile phones to measure momentary mood and stress and other related variables from various patients with chronic fatigue syndrome, breast cancer, migraine, HIV, tinnitus, temporomandibular disorder, end-stage kidney disease, and traumatic brain injury. Most of the selected studies (11/12, 92%) used signal contingency and in 8 of the 12 studies (67%) alarms were sent at random or semirandom intervals to prompt the momentary measurement. Out of 12 studies, 7 (58%) used specific apps directly installed on mobile phones, 3 (25%) used mobile phones to link to Web-based survey programs, and 2 (17%) used an interactive voice-response system.

Conclusions

This study provides researchers with useful information regarding methodological details for utilizing EMA to measure mood and stress in adult patients. This review shows that EMA methods could be effective and reasonable for measuring momentary mood and stress, given that basic- and advanced-feature mobile phones are ubiquitous, familiar, and easy to approach. Therefore, researchers could adopt and utilize EMA methods using mobile phones to measure psychological health outcomes, such as mood and stress, in adult patients.

Apps and Mobile Health Technology in Rehabilitation: The Good, the Bad, and the Unknown

Although there is disparity in access to mobile health (mHealth) services among people with disabilities, several smartphone and tablet-based mHealth applications are available that may affect the care of patients in rehabilitation medicine. This article reviews the current evidence for and breadth of application-based mHealth interventions in rehabilitation medicine, including comprehensive self-management mHealth services; weight management mHealth services; diagnosis-specific mHealth services for individuals with brain, spinal cord, musculoskeletal, or other injury types; and nonmedical services to improve community and social integration.

Variability in daily self-reported emotional symptoms and fatigue measured over eight weeks in community dwelling individuals with traumatic brain injury

OBJECTIVE

To investigate within-person variability in daily self-reported emotional and fatigue symptoms and factors associated with high within-person variability among individuals with chronic traumatic brain injury (TBI).

DESIGN

This was a prospective descriptive pilot study of n = 18 adults with chronic TBI (2-27 years post-injury) who owned and could independently use an Apple or Android device.

METHODS

Participants completed daily assessments for 8 weeks via smartphone. Outcome measures included the Positive and Negative Affect Schedule, Patient Health Questionnaire-2, Generalized Anxiety Disorder-2, and a 7-point fatigue rating. We examined within-person variability over time using individual Multilevel Linear Models. We categorized within-person variability as High or Low based on individual standard deviations in relationship to sample standard deviation.

RESULTS

Significant temporal within-person variability occurred for all measures. High variability was associated with more symptom reporting versus Low variability, and variability was associated with sex (High variability: 88% women; Low variability 90% men).

CONCLUSIONS

Symptom measurement at a single time point among adults with chronic TBI may not capture day-to-day symptom fluctuation and may misidentify individuals in need of intervention. Assessing symptom profiles over time to capture temporal and individual variability may provide a more ecologically valid measure for managing long-term symptoms after TBI.

Barriers to and Facilitators of Engagement With Remote Measurement Technology for Managing Health: Systematic Review and Content Analysis of Findings

BACKGROUND

Remote measurement technology refers to the use of mobile health technology to track and measure change in health status in real time as part of a person's everyday life. With accurate measurement, remote measurement technology offers the opportunity to augment health care by providing personalized, precise, and preemptive interventions that support insight into patterns of health-related behavior and self-management. However, for successful implementation, users need to be engaged in its use.

OBJECTIVE

Our objective was to systematically review the literature to update and extend the understanding of the key barriers to and facilitators of engagement with and use of remote measurement technology, to guide the development of future remote measurement technology resources.

METHODS

We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines involving original studies dating back to the last systematic review published in 2014. We included studies if they met the following entry criteria: population (people using remote measurement technology approaches to aid management of health), intervention (remote measurement technology system), comparison group (no comparison group specified), outcomes (qualitative or quantitative evaluation of the barriers to and facilitators of engagement with this system), and study design (randomized controlled trials, feasibility studies, and observational studies). We searched 5 databases (MEDLINE, IEEE Xplore, EMBASE, Web of Science, and the Cochrane Library) for articles published from January 2014 to May 2017. Articles were independently screened by 2 researchers. We extracted study characteristics and conducted a content analysis to define emerging themes to synthesize findings. Formal quality assessments were performed to address risk of bias.

RESULTS

A total of 33 studies met inclusion criteria, employing quantitative, qualitative, or mixed-methods designs. Studies were conducted in 10 countries, included male and female participants, with ages ranging from 8 to 95 years, and included both active and passive remote monitoring systems for a diverse range of physical and mental health conditions. However, they were relatively short and had small sample sizes, and reporting of usage statistics was inconsistent. Acceptability of remote measurement technology according to the average percentage of time used (64%-86.5%) and dropout rates (0%-44%) was variable. The barriers and facilitators from the content analysis related to health status, perceived utility and value, motivation, convenience and accessibility, and usability.

CONCLUSIONS

The results of this review highlight gaps in the design of studies trialing remote measurement technology, including the use of quantitative assessment of usage and acceptability. Several processes that could facilitate engagement with this technology have been identified and may drive the development of more person-focused remote measurement technology. However, these factors need further testing through carefully designed experimental studies.

TRIAL REGISTRATION

International Prospective Register of Systematic Reviews (PROSPERO) CRD42017060644; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=60644 (Archived by WebCite at http://www.webcitation.org/70K4mThTr).

Development of a Just-in-Time Adaptive mHealth Intervention for Insomnia: Usability Study

Background

Healthy sleep is a fundamental component of physical and brain health. Insomnia, however, is a prevalent sleep disorder that compromises functioning, productivity, and health. Therefore, developing efficient treatment delivery methods for insomnia can have significant societal and personal health impacts. Cognitive behavioral therapy for insomnia (CBTI) is the recommended first-line treatment of insomnia but access is currently limited for patients, since treatment must occur in specialty sleep clinics, which suffer from an insufficient number of trained clinicians. Smartphone-based interventions offer a promising means for improving the delivery of CBTI. Furthermore, novel features such as real-time monitoring and assessment, personalization, dynamic adaptations of the intervention, and context awareness can enhance treatment personalization and effectiveness, and reduce associated costs. Ultimately, this “Just in Time Adaptive Intervention” for insomnia—an intervention approach that is acceptable to patients and clinicians, and is based on mobile health (mHealth) platform and tools—can significantly improve patient access and clinician delivery of evidence-based insomnia treatments.

Objective

This study aims to develop and assess the usability of a Just in Time Adaptive Intervention application platform called iREST (“interactive Resilience Enhancing Sleep Tactics”) for use in behavioral insomnia interventions. iREST can be used by both patients and clinicians.

Methods

The development of iREST was based on the Iterative and Incremental Development software development model. Requirement analysis was based on the case study’s description, workflow and needs, clinician inputs, and a previously conducted BBTI military study/implementation of the Just in Time Adaptive Intervention architecture. To evaluate the usability of the iREST mHealth tool, a pilot usability study was conducted. Additionally, this study explores the feasibility of using an off-the-shelf wearable device to supplement the subjective assessment of patient sleep patterns.

Results

The iREST app was developed from the mobile logical architecture of Just in Time Adaptive Intervention. It consists of a cross-platform smartphone app, a clinician portal, and secure 2-way communications platform between the app and the portal. The usability study comprised 19 Active Duty Service Members and Veterans between the ages of 18 and 60. Descriptive statistics based on in-app questionnaires indicate that on average, 12 (mean 12.23, SD 8.96) unique devices accessed the clinician portal per day for more than two years, while the app was rated as “highly usable”, achieving a mean System Usability Score score of 85.74 (SD 12.37), which translates to an adjective rating of “Excellent”. The participants also gave high scores on “ease of use and learnability” with an average score of 4.33 (SD 0.65) on a scale of 1 to 5.

Conclusions

iREST provides a feasible platform for the implementation of Just in Time Adaptive Intervention in mHealth-based and remote intervention settings. The system was rated highly usable and its cross-platformness made it readily implemented within the heavily segregated smartphone market. The use of wearables to track sleep is promising; yet the accuracy of this technology needs further improvement. Ultimately, iREST demonstrates that mHealth-based Just in Time Adaptive Intervention is not only feasible, but also works effectively.