Ecological momentary assessment (EMA) involves repeated collection of real-time self-report data, often multiple times per day, nearly always delivered electronically by smartphone. While EMA has shown promise for researching internal states, behaviors, and experiences in multiple populations, concerns remain regarding its feasibility in samples with cognitive impairments, like those associated with chronic moderate-to-severe traumatic brain injury (TBI).

This study examines adherence to a 7-week high-frequency (5x daily) EMA protocol in individuals with moderate-to-severe TBI, considering changes in response rate over time, as well as individual participant characteristics (memory function, education, injury severity, and age).

In the sample of 39 participants, the average overall response rate was 65% (range: 5%–100%). Linear mixed-effects modeling revealed a small but statistically significant linear decay in response rate over 7 weeks of participation. Individual trajectories were variable, as evidenced by the significant effect of random slope. A better response rate was positively associated with greater educational attainment and better episodic memory function (statistical trend), whereas the effects of age and injury severity were not significant.

These findings shed light on the potential of EMA in TBI studies but underscore the need for tailored strategies to address individual barriers to adherence.

Mobile health has been shown to improve quality, access, and efficiency of health care in select populations. We sought to evaluate the benefits of mobile health monitoring using the KidsHeart app in an infant CHD population.

We reviewed data submitted to KidsHeart from parents of infants discharged following intervention for high-risk CHD lesions including subjects status post stage 1 single ventricle palliation, ductal stent or surgical shunt, pulmonary artery band, or right ventricular outflow tract stent. We report on the benefits of a novel mobile health red flag scoring system, mobile health growth/feed tracking, and longitudinal neurodevelopmental outcomes tracking.

A total of 69 CHD subjects (63% male, 41% non-white, median age 28 days [interquartile range 20, 75 days]) were included with median mobile health follow-up of 137 days (56, 190). During the analytic window, subjects submitted 5700 mobile health red flag notifications including 245 violations (mean [standard deviation] 3 ± 3.96 per participant) with 80% (55/69) of subjects submitting at least one violation. Violations precipitated 116 interventions including hospital admission in 34 (29%) with trans-catheter evaluation in 15 (13%) of those. Growth data (n = 2543 daily weights) were submitted by 63/69 (91%) subjects and precipitated 31 feed changes in 23 participants. Sixty-eight percent of subjects with age >2 months submitted at least one complete neurodevelopment questionnaire.

In our initial experience, mobile health monitoring using the KidsHeart app enhanced interstage monitoring permitting earlier intervention, allowed for remote tracking of growth feeding, and provided a means for tracking longitudinal neurodevelopmental outcomes.

This study aimed to investigate the patient’s perception of the usefulness and limitations of a mobile application as part of the supportive care provided to patients undergoing radiotherapy.

Patients undergoing radiotherapy between February 2023 and March 2023 at a local oncology hospital (n = 150) were invited to complete a questionnaire that assessed the patient’s smartphone knowledge, willingness to use an app during radiotherapy, perceptions of the usefulness of specific app features, and barriers to using such applications. For quantitative analysis, frequencies were obtained for all areas of interest, and the results were correlated with the patient’s demographics.

Of the 39 participants who completed the questionnaire, 82·1% had a smartphone device, 59% could use their smartphones with minimal to no help and 41% had not used their smartphones for medical purposes before. However, 79·5% of patients showed a strong interest in using a mobile app during radiotherapy. Age, gender and level of education had no significant impact on the acceptability of using the mobile application for radiotherapy purposes.

Overall, the findings indicate that most patients have access to mobile technology and are willing to use the mobile app as an additional supportive care tool.

The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey’s Auditory Verbal Learning Test (AVLT).

Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A−T−, n = 195). Analyses were repeated among CU participants only.

The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p’s > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A− vs A+) to large (A−T− vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups.

Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Physical activity (PA) may help maintain brain structure and function in aging. Since the intensity of PA needed to effect cognition and cerebrovascular health remains unknown, we examined associations between PA and cognition, regional white matter hyperintensities (WMH), and regional cerebral blood flow (CBF) in older adults.

Forty-three older adults without cognitive impairment underwent magnetic resonance imaging (MRI) and comprehensive neuropsychological assessment. Waist-worn accelerometers objectively measured PA for approximately one week.

Higher time spent in moderate to vigorous PA (MVPA) was uniquely associated with better memory and executive functioning after adjusting for all light PA. Higher MVPA was also uniquely associated with lower frontal WMH volume although the finding was no longer significant after additionally adjusting for age and accelerometer wear time. MVPA was not associated with CBF. Higher time spent in all light PA was uniquely associated with higher CBF but not with cognitive performance or WMH volume.

Engaging in PA may be beneficial for cerebrovascular health, and MVPA in particular may help preserve memory and executive function in otherwise cognitively healthy older adults. There may be differential effects of engaging in lighter PA and MVPA on MRI markers of cerebrovascular health although this needs to be confirmed in future studies with larger samples. Future randomized controlled trials that increase PA are needed to elucidate cause-effect associations between PA and cerebrovascular health.

Text message-delivered interventions for chronic disease self-management have potential to reduce health disparities, yet limited research has explored implementing these interventions into clinical care. We partnered with safety net clinics to evaluate a texting intervention for type 2 diabetes called REACH (Rapid Encouragement/Education And Communications for Health) in a randomized controlled trial. Following evaluation, we explored potential implementation determinants and recommended implementation strategies.

We interviewed clinic staff (n = 14) and a subset of intervention participants (n = 36) to ask about REACH’s implementation potential. Using the Consolidated Framework for Implementation Research (CFIR) as an organizing framework, we coded transcripts and used thematic analysis to derive implementation barriers and facilitators. We integrated the CFIR-ERIC (Expert Recommendations for Implementing Change) Matching Tool, interview feedback, and the literature to recommend implementation strategies.

Implementation facilitators included low complexity, strong evidence and quality, available clinic resources, the need for a program to support diabetes self-management, and strong fit between REACH and both the clinics’ existing workflows and patients’ needs and resources. The barriers included REACH only being available in English, a lack of interoperability with electronic health record systems, patients’ concerns about diabetes stigma, limited funding, and high staff turnover. Categories of recommended implementation strategies included training and education, offering flexibility and adaptation, evaluating key processes, and securing funding.

Text message-delivered interventions have strong potential for integration in low-resource settings as a supplement to care. Pursuing implementation can ensure patients benefit from these innovations and help close the research to practice gap.

Smartphones can facilitate patients completing surveys and collecting sensor data to gain insight into their mental health conditions. However, the utility of sensor data is still being explored. Prior studies have reported a wide range of correlations between passive data and survey scores.

To explore correlations in a large data-set collected with the mindLAMP app. Additionally, we explored whether passive data features could be used in models to predict survey results.

Participants were asked to complete daily and weekly mental health surveys. After screening for data quality, our sample included 147 college student participants and 270 weeks of data. We examined correlations between six weekly surveys and 13 metrics derived from passive data features. Finally, we trained logistic regression models to predict survey scores from passive data with and without daily surveys.

Similar to other large studies, our correlations were lower than prior reports from smaller studies. We found that the most useful features came from GPS, call, and sleep duration data. Logistic regression models performed poorly with only passive data, but when daily survey scores were included, performance greatly increased.

Although passive data alone may not provide enough information to predict survey scores, augmenting this data with short daily surveys can improve performance. Therefore, it may be that passive data can be used to refine survey score predictions and clinical utility may be derived from the combination of active and passive data.

While the negative consequences of insomnia are well-documented, a strengths-based understanding of how sleep can increase health promotion is still emerging and much-needed. Correlational evidence has connected sleep and insomnia to resilience; however, this relationship has not yet been experimentally tested. This study examined resilience as a mediator of treatment outcomes in a randomized clinical trial with insomnia patients.

Participants were randomized to either digital cognitive behavioral therapy for insomnia (dCBT-I; n = 358) or sleep education control (n = 300), and assessed at pre-treatment, post-treatment, and 1-year follow-up. A structural equation modeling framework was utilized to test resilience as a mediator of insomnia and depression. Risk for insomnia and depression was also tested in the model, operationalized as a latent factor with sleep reactivity, stress, and rumination as indicators (aligned with the 3-P model). Sensitivity analyses tested the impact of change in resilience on the insomnia relapse and incident depression at 1-year follow-up.

dCBT-I resulted in greater improvements in resilience compared to the sleep education control. Furthermore, improved resilience following dCBT-I lowered latent risk, which was further associated with reduced insomnia and depression at 1-year follow-up. Sensitivity analyses indicated that each point improvement in resilience following treatment reduced the odds of insomnia relapse and incident depression 1 year later by 76% and 65%, respectively.

Improved resilience is likely a contributing mechanism to treatment gains following insomnia therapy, which may then reduce longer-term risk for insomnia relapse and depression.

Despite a large number of mobile apps in the field of mental health, it is difficult to find a useful and reliable one, mainly due to the fact that the effectiveness of many apps has not been assessed scientifically. The present study aimed to assess the effects of mental health apps on managing the symptoms of stress, anxiety, and depression.

A comprehensive literature search was conducted in PubMed, Scopus, EMBASE, Cochrane, and Web of Science databases for the papers published from 2000 to 2019. Studies were included if they reviewed articles or mobile apps for their effectiveness in stress, anxiety, and depression. The reviews that had considered mobile apps or web-based mobile applications as an intervention or part of intervention were included, as well.

A total of 4,999 peer-reviewed articles were identified, out of which nine systematic reviews met the inclusion criteria. Seven systematic reviews measured depression outcomes, three measured stress, and five systematic reviews measured anxiety symptoms. The applications that used behavior change strategies, such as Cognitive Behavioral Therapy, Acceptance and Commitment Therapy, and Behavioral Activation, reported significant effects on depression, anxiety, and stress.

It seems that mental health apps can be promising media for reducing depressive symptoms. This field is an emerging area of mobile health, and further research should be done in future in order to reach conclusive evidence.

The aim of this study was to develop a module which could be used to facilitate the assessment of mobile medical applications (MMA) for regulatory and reimbursement purposes.

In-depth interviews were conducted with policymakers, healthcare practitioners, and application developers to determine possible pathways and impediments to MMA reimbursement. These findings were integrated with our previous research on MMA reimbursement and regulation to create a module that could be used with existing health technology assessment (HTA) methodological frameworks to guide the evaluation of MMAs.

Stakeholders indicated that they trust how traditional medical devices are currently appraised for reimbursement. They were concerned that there was a lack of clarity regarding which entity in the health system was responsible for determining app quality. They were also concerned about the digital health literacy of medical practitioners and patients. Concepts emerging from our previous research were reinforced by the interview findings, including that the connectivity and cybersecurity of apps need to be considered, along with an assessment of software reliability. It is also critical that the credibility of the information presented in apps is assessed as it could potentially mislead patients and clinicians.

An MMA evaluation module was created that would enable an existing HTA process to be adapted for the assessment of MMA technology. These adaptations include making provisions for an assessment of app cybersecurity, the impact on MMA clinical utility of software updates, and compatibility issues. Items to address concerns around practitioner responsibility and app misinformation were also incorporated into the module.

Le suicide et les conduites auto-agressives sont fréquents dans la population adulte. De précédentes études ont prouvé que le fait de maintenir le lien avec le sujet suicidant, par lettres ou cartes postales, après la prise en charge en aigu, réduit le risque de récidive. De plus, les études de faisabilité ont montré que l’intervention par SMS est acceptable pour les patients. L‘objectif principal de cette étude est de démontrer l’efficacité du dispositif de veille par SMS sur la réduction de la récidive suicidaire à 6 mois. Nous présenterons dans un premier temps l’étude de faisabilité puis l’étude multicentrique démarrée dans 8 CHU.

Il s’agira d’un essai de supériorité, contrôlé, randomisé, multicentrique, d’une durée de 2 ans, et piloté par le CHRU de Brest. Les sujets seront des adultes ayant survécu à un passage à l’acte suicidaire, inclus après une prise en charge aux urgences ou une courte hospitalisation. Le recrutement s’étalera sur une période de 9 mois. Les SMS seront envoyés à j2, j7, j15, puis mensuellement. Ces messages se soucieront du bien-être du patient, et lui rappelleront les coordonnées d’urgence dont il dispose en cas de besoin. Les patients seront évalués à j0, puis à 6 et 13 mois. Le critère de jugement principal sera le nombre de patients récidivant à 6 mois, dans le groupe recevant les SMS et dans le groupe témoin (qui bénéficie de la prise en charge de référence). Les critères de jugement secondaires seront le nombre de patients récidivant à 13 mois, le nombre de tentatives de suicide à 6 et 13 mois, le nombre de décès par suicide à 6 et 13 mois, dans les deux groupes. Les idées suicidaires seront évaluées dans chaque groupe, à j0, à 6 mois, et à 13 mois. Enfin, les coûts médicaux et la satisfaction seront évalués à 13 mois.

La fréquence de récidive attendue à 6 mois dans le groupe témoin est de l’ordre de 18 %. Nous espérons la réduire à 9 % grâce au contact par SMS. Afin d’y parvenir, le nombre de sujets nécessaires a été évalué à 530, soit 265 dans chaque bras.

Ce dispositif de veille par SMS s’appuie sur de précédentes interventions, aux résultats significatifs dans le domaine, et est facilement reproductible. Nous proposons d’évaluer son efficacité dans la réduction du risque de récidive suicidaire au sein d’une population d’adultes ayant fait un passage à l’acte.

Mobile health (mHealth) due to its popularity and accessibility can be widely applied in different health areas such as the management of chronic diseases. However, its success depends on the acceptance of their users. Therefore, the aim of this study was to survey the attitudes of patients with chronic disease toward mHealth technology and their willingness to use it.

This study was conducted within a 2-year period (2016–2018) to determine and compare the attitude and willingness of patients with asthma, diabetes, and multiple sclerosis (MS) toward using mHealth technology in a province in Iran.

In total, 222 patients participated in this study. More than 93 percent of the patients with diabetes and MS, and 65 percent of the asthmatic patients preferred using mHealth services rather than consulting a physician (p < .0001). About 98, 94, and 49 percent of the MS, diabetic, and asthmatic patients, respectively felt comfortable if their health conditions checked by physicians through mHealth technology (p < .0001).

Our results showed that the majority of the patients felt comfortable and preferred using mHealth technology rather than consulting the physicians. The attitudes of diabetic and MS patients toward mHealth technology were rather more positive compared to asthmatic patient attitude. These results may be helpful for the developers of mHealth technology, and researchers who design mHelath interventions for patients with chronic disease.