The Functionality, Evidence, and Privacy Issues Around Smartphone Apps for the Top Neuropsychiatric Conditions

An update on mobile applications collecting data among subjects with or at risk of Alzheimer's disease

Smart mobile phone use is increasing worldwide, as is the ability of mobile devices to monitor daily routines, behaviors, and even cognitive changes. There is a growing opportunity for users to share the data collected with their medical providers which may serve as an accessible cognitive impairment screening tool. Data logged or tracked in an app and analyzed with machine learning (ML) could identify subtle cognitive changes and lead to more timely diagnoses on an individual and population level. This review comments on existing evidence of mobile device applications designed to passively and/or actively collect data on cognition relevant for early detection and diagnosis of Alzheimer's disease (AD). The PubMed database was searched to identify existing literature on apps related to dementia and cognitive health data collection. The initial search deadline was December 1, 2022. Additional literature published in 2023 was accounted for with a follow-up search prior to publication. Criteria for inclusion was limited to articles in English which referenced data collection via mobile app from adults 50+ concerned, at risk of, or diagnosed with AD dementia. We identified relevant literature (n = 25) which fit our criteria. Many publications were excluded because they focused on apps which fail to collect data and simply provide users with cognitive health information. We found that although data collecting cognition-related apps have existed for years, the use of these apps as screening tools remains underdeveloped; however, it may serve as proof of concept and feasibility as there is much supporting evidence on their predictive utility. Concerns about the validity of mobile apps for cognitive screening and privacy issues remain prevalent. Mobile applications and use of ML is widely considered a financially and socially viable method of compiling symptomatic data but currently this large potential dataset, screening tool, and research resource is still largely untapped.

Developments in scalable strategies for detecting early markers of cognitive decline

Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example, biological markers of neuropathology associated with cognitive decline are typically collected via cerebral spinal fluid, cognitive functioning is evaluated from face-to-face assessments by experts and brain measures are obtained using expensive, non-portable equipment. Here, we describe scalable, repeatable, relatively non-invasive and comparatively inexpensive strategies for detecting the earliest markers of cognitive decline. These approaches are characterized by simple data collection protocols conducted in locations outside the laboratory: measurements are collected passively, by the participants themselves or by non-experts. The analysis of these data is, in contrast, often performed in a centralized location using sophisticated techniques. Recent developments allow neuropathology associated with potential cognitive decline to be accurately detected from peripheral blood samples. Advances in smartphone technology facilitate unobtrusive passive measurements of speech, fine motor movement and gait, that can be used to predict cognitive decline. Specific cognitive processes can be assayed using 'gamified' versions of standard laboratory cognitive tasks, which keep users engaged across multiple test sessions. High quality brain data can be regularly obtained, collected at-home by users themselves, using portable electroencephalography. Although these methods have great potential for addressing an important health challenge, there are barriers to be overcome. Technical obstacles include the need for standardization and interoperability across hardware and software. Societal challenges involve ensuring equity in access to new technologies, the cost of implementation and of any follow-up care, plus ethical issues.

Assessment of Smartphone Apps for Common Neurologic Conditions (Headache, Insomnia, and Pain): Cross-sectional Study

BACKGROUND

There are thousands of apps for individuals struggling with headache, insomnia, and pain, but it is difficult to establish which of these apps are best suited for patients' specific needs. If clinicians were to have access to a platform that would allow them to make an informed decision on the efficacy and feasibility of smartphone apps for patient care, they would feel confident in prescribing specific apps.

OBJECTIVE

We sought to evaluate the quality of apps for some of the top common, disabling neurologic conditions (headache, insomnia, and pain) based on principles derived from the American Psychiatric Association's (APA) app evaluation model.

METHODS

We used the Mobile Health Index and Navigation database and expanded upon the database's current supported conditions by adding 177 new app entries. Each app was rated for consistency with the APA's app evaluation model, which includes 105 objective questions based on the following 5 major classes of consideration: (1) accessibility, (2) privacy and security, (3) clinical foundation, (4) engagement style, and (5) interoperability. These characteristics were evaluated to gain a broader understanding of the significant features of each app category in comparison against a control group.

RESULTS

Approximately 90% (187/201) of all apps evaluated were free to download, but only 50% (63/201) of headache- and pain-related apps were truly free. Most (87/106, 81%) sleep apps were not truly free to use. The apps had similar limitations with limited privacy, accessibility, and crisis management resources. For example, only 17% (35/201) of the apps were available in Spanish. The apps offered mostly self-help tools with little tailoring; symptom tracking was the most common feature in headache- (32/48, 67%) and pain-related apps (21/47, 45%), whereas mindfulness was the most common feature in sleep-related apps (73/106, 69%).

CONCLUSIONS

Although there are many apps for headache, pain, and insomnia, all 3 types of apps have room for improvement around accessibility and privacy. Pain and headache apps share many common features, whereas insomnia apps offer mostly mindfulness-based resources. Given the many available apps to pick from, clinicians and patients should seek apps that offer the highest-quality features, such as complete privacy, remedial features, and the ability to download the app at no cost. These results suggest that there are many opportunities for the improvement of apps centered on headache, insomnia, and pain.

mHealth Solutions for Mental Health Screening and Diagnosis: A Review of App User Perspectives Using Sentiment and Thematic Analysis

Mental health screening and diagnostic apps can provide an opportunity to reduce strain on mental health services, improve patient well-being, and increase access for underrepresented groups. Despite promise of their acceptability, many mental health apps on the market suffer from high dropout due to a multitude of issues. Understanding user opinions of currently available mental health apps beyond star ratings can provide knowledge which can inform the development of future mental health apps. This study aimed to conduct a review of current apps which offer screening and/or aid diagnosis of mental health conditions on the Apple app store (iOS), Google Play app store (Android), and using the m-health Index and Navigation Database (MIND). In addition, the study aimed to evaluate user experiences of the apps, identify common app features and determine which features are associated with app use discontinuation. The Apple app store, Google Play app store, and MIND were searched. User reviews and associated metadata were then extracted to perform a sentiment and thematic analysis. The final sample included 92 apps. 45.65% (n = 42) of these apps only screened for or diagnosed a single mental health condition and the most commonly assessed mental health condition was depression (38.04%, n = 35). 73.91% (n = 68) of the apps offered additional in-app features to the mental health assessment (e.g., mood tracking). The average user rating for the included apps was 3.70 (SD = 1.63) and just under two-thirds had a rating of four stars or above (65.09%, n = 442). Sentiment analysis revealed that 65.24%, n = 441 of the reviews had a positive sentiment. Ten themes were identified in the thematic analysis, with the most frequently occurring being performance (41.32%, n = 231) and functionality (39.18%, n = 219). In reviews which commented on app use discontinuation, functionality and accessibility in combination were the most frequent barriers to sustained app use (25.33%, n = 19). Despite the majority of user reviews demonstrating a positive sentiment, there are several areas of improvement to be addressed. User reviews can reveal ways to increase performance and functionality. App user reviews are a valuable resource for the development and future improvements of apps designed for mental health diagnosis and screening.

A systematic evaluation of primary headache management apps leveraging behavior change techniques

BACKGROUND

Mobile health apps have the potential to promote adherence to headache management through the use of evidence-based behavior change techniques (e.g., self-monitoring). While many headache management apps exist, the extent to which these apps include behavior change techniques remains unknown. Thus, the present study systematically evaluated the content and quality of commercially available headache management apps.

METHODS

Headache apps were identified using a systematic search in the Apple App and Google Play stores. A total of 55 apps were evaluated using the taxonomy of behavior change techniques and app quality using the Mobile App Rating Scale.

RESULTS

Headache management apps included 0-14 behavior change techniques (Mean [M] = 5.89) and 0-8 headache management behavior change techniques (M = 4.29). App quality ranged from 2.84-4.67 (M = 3.73) out of 5.00. Three apps, Migraine Trainer, Easeday: Headache & Migraine, and PainScale, included the highest number of overall and headache management behavior change techniques along with good quality scores.

CONCLUSIONS

While randomized controlled trials are necessary to determine the efficacy of individual headache apps, most existing apps include evidence-based headache management behavior change techniques. Headache apps often focus on either self-monitoring or stress management via relaxation training, suggesting that patients' needs should be used to inform app selection.

Wearables for Neurologic Conditions: Considerations for Our Patients and Research Limitations

Purpose of Review

In 2019, over 50 million Americans were expected to use wearables at least monthly. The technologies have varied capabilities, with many designed to monitor health conditions. We present a narrative review to raise awareness of wearable technologies that may be relevant to the field of neurology. We also discuss the implications of these wearables for our patients and briefly discuss issues related to researching new wearable technologies.

Recent Findings

There are a variety of wearables for neurologic conditions, e.g., stroke (for potential arrhythmia capture), epilepsy, Parkinson disease, and sleep. Research is being performed to capture the risk of neuropsychiatric relapse. However, data are limited and adherence to these wearables is often poorly studied.

Summary

The care of neurology patients may ultimately be improved with the use of wearable technologies. More research needs to examine efficacy and implementation strategies.

Telehealth as a new care delivery model: The headache provider experience

OBJECTIVE

To assess telehealth practice for headache visits in the United States.

BACKGROUND

The rapid roll out of telehealth during the COVID-19 pandemic impacted headache specialists.

METHODS

American Headache Society (AHS) members were emailed an anonymous survey (9/9/20-10/12/20) to complete if they had logged ≥2 months or 50+ headache visits via telehealth.

RESULTS

Out of 1348 members, 225 (16.7%) responded. Most were female (59.8%; 113/189). Median age was 47 (interquartile range [IQR] 37-57) (N = 154). The majority were MD/DOs (83.7%; 159/190) or NP/PAs (14.7%; 28/190), and most (65.1%; 123/189) were in academia. Years in practice were 0-3: 28; 4-10: 58; 11-20: 42; 20+: 61. Median number of telehealth visits was 120 (IQR 77.5-250) in the prior 3 months. Respondents were "comfortable/very comfortable" treating via telehealth (a) new patient with a chief complaint of headache (median, IQR 4 [3-5]); (b) follow-up for migraine (median, IQR 5 [5-5]); (c) follow-up for secondary headache (median, IQR 4 [3-4]). About half (51.1%; 97/190) offer urgent telehealth. Beyond being unable to perform procedures, top barriers were conducting parts of the neurologic exam (157/189), absence of vital signs (117/189), and socioeconomic/technologic barriers (91/189). Top positive attributes were patient convenience (185/190), reducing patient travel stress (172/190), patient cost reduction (151/190), flexibility with personal matters (128/190), patient comfort at home (114/190), and patient medications nearby (103/190). Only 21.3% (33/155) of providers said telehealth visit length differed from in-person visits, and 55.3% (105/190) believe that the no-show rate improved. On a 1-5 Likert scale, providers were "interested"/"very interested" in digitally prescribing headache apps (median 4, IQR 3-5) and "interested"/"very interested" in remotely monitoring patient symptoms (median 4, IQR 3-5).

CONCLUSIONS

Respondents were comfortable treating patients with migraine via telehealth. They note positive attributes for patients and how access may be improved. Technology innovations (remote vital signs, digitally prescribing headache apps) and remote symptom monitoring are areas of interest and warrant future research.

Survey on Acceptance of Passive Technology Monitoring for Early Detection of Cognitive Impairment

Introduction

Digital biomarkers may act as a tool for early detection of changes in cognition. It is important to understand public perception of technologies focused on monitoring cognition to better guide the design of these tools and inform patients appropriately about the associated risks and benefits. Health care systems may also play a role in the clinical, legal, and financial implications of such technologies.

Objective

To evaluate public opinion on the use of passive technology for monitoring cognition.

Methods

This was a one-time, Internet-based survey conducted in English and Spanish.

Results

Within the English survey distributed in the USA (n = 173), 58.1% of respondents would be highly likely to agree to passive monitoring of cognition via a smartphone application. Thirty-eight percent of those with a higher degree of experience with technology were likely to agree to monitoring versus 20% of those with less experience with technology (p = 0.003). Sixty-two percent of non-health-care professionals were likely to agree to monitoring versus 45% of health-care workers (p = 0.012). There were significant concerns regarding privacy (p < 0.01). We compared the surveys answered in Spanish in Costa Rica via logistic regression (n = 43, total n = 216), adjusting for age, education level, health-care profession, owning a smartphone, experience with technology, and perception of cognitive decline. Costa Rican/Spanish-speaking respondents were 7 times more likely to select a high probability of agreeing to such a technology (p < 0.01). English-speaking respondents from the USA were 5 times more likely to be concerned about the impact on health insurance (p = 0.001) and life insurance (p = 0.01).

Conclusions

Understanding public perception and ethical implications should guide the design of digital biomarkers for cognition. Privacy and the health-care system in which the participants take part are 2 major factors to be considered. It is the responsibility of researchers to convey the ethical and legal implications of cognition monitoring.

Physiotherapists' and occupational therapists' perspectives on information and communication technology in stroke rehabilitation

Aim

The aim of this study was to explore the current and potential use of information and communication technology (ICT) to enhance coherent person-centred rehabilitation after stroke, from the perspectives of physiotherapists and occupational therapists.

Method

Five occupational therapists and four physiotherapists from different phases of the Danish stroke rehabilitation process were included and two focus group interviews were carried out. A grounded theory approach was used throughout the study and a constant comparative method was used in the analysis.

Results

Three subcategories were identified from the analysis of interviews with participants: 1) ICT and apps as meaningful and supportive in the rehabilitation process, 2) ICT as a tool in communication and documentation and 3) Barriers to the integration of ICT and apps in the rehabilitation process. From these categories one core category emerged: The potential of a personalized app solution to facilitate coherent person-centred rehabilitation.

Conclusion

ICT was perceived as important to integrate in stroke rehabilitation both for assessment, training and to compensate for remaining deficits. The development of a personalized app solution could accommodate stroke survivors’ and significant others’ need for insight into and overview over the rehabilitation process as well as access to relevant information, which would thereby empower them. Furthermore, a personalized app solution could also facilitate follow-up after discharge and was perceived to ease the communication and documentation within and between sectors, as well as communication with both stroke survivors and significant others.