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Objectives: Effectiveness of psychotherapy depends on patients’ adherence to between-session homework (HW) to practice therapeutic skills. mHealth apps can offer continuing reminders, although frequent reminders overwhelm or burden patients and therefore are ineffective. Predicting likelihood of completing daily HW and sending contextual reminders has the potential to improve HW adherence and therefore improvesymptoms.
Methods: Depressed older participants (N = 51) undergoing psychotherapy provided daily active ratings on mood, anhedonia, stress and pain via an mHealth app. Data on activity, mobilization, sociability and sleep passively were also recorded via device sensors (e.g., microphone, accelerometer, GPS etc.). Using active and passive mHealth data, we developed predictive models of daily home-work completion status using a naïve semi-supervised deep learning algorithm. Prediction accuracy was determined via time-dependent cross-validation.
Results: Study participants had a mean (SD) age of 71.4 (7.76) years, mean (SD) of 14.9 (2.93) years of education, mean (SD) BIS/BAS total of 22.6 (3.36), mean (SD) MADRS total score of20.4 (6.04) and 88.2% were of female gender, 29.4% were single, 83.8% were of non-Hispanic ethnicity, 58.8% belonged to Caucasian race and 38.2% practiced Catholic religion. With 4700 person-days HW completion response, our models show an AUC of 84.7% (sensitivity = 76.2%; specificity = 80%) estimated by cross-validation.
Conclusions: This paper demonstrates the feasibility of predicting adherence to psychotherapy in depressed older adults using actively and passively collected mHealth data. Digital interventions based on such predictive models can potentially increase adherence to psychotherapy and thereby improve its effectiveness without increasing the user notification burden.
Behaviour Change Communication (BCC) intervention programmes often lack documentation of successful processes. This manuscript aims to describe the development of Program Impact Pathway (PIP) using Theory of Change (ToC) approach for a mHealth BCC intervention titled ‘Mobile Solutions Aiding Knowledge for Health Improvement (M-SAKHI)’ aimed at reducing stunting in infants at 18 months of age.
Design:
The PIP was developed using ToC to design the intervention and plan its implementation. Literature review and data from previous pilots helped to identify health service gaps that needed to be addressed by the PIP of this intervention.
Setting:
M-SAKHI was implemented in 244 villages under governance of forty primary health centres of Nagpur and Bhandara districts of eastern Maharashtra in central India.
Participants:
The study investigators and the public health stakeholders participated in developing the PIP. M-SAKHI evaluation study recruited 2501 pregnant women who were followed up through delivery until their infants were 18 months old.
Results:
The PIP was developed, and it identified the following pathways for the final impact: (1) improving maternal and infant nutrition, (2) early recognition of maternal and infant danger signs, (3) improving access and utilisation to healthcare services, (4) improving hygiene, sanitation and immunisation practices, and (5) improving implementation and service delivery of community health workers through their training, monitoring and supervision in real time.
Conclusion:
This paper will illustrate the significance of development of PIP for M-SAKHI. It can aid other community-based programmes to design their PIP for nutrition-based BCC interventions.
Medication non-adherence remains a significant challenge for adolescent heart transplant recipients. Building on the success of a pilot intervention study, herein we describe the protocol for a follow-up randomised control trial using mobile video directly observed therapy, featuring several innovations, to promote medication adherence in a multi-centre sample of adolescent heart transplant patients.
Global mental health services face challenges such as stigma and a shortage of trained professionals, particularly in low- and middle-income countries, which hinder access to high-quality care. Mobile health interventions, commonly referred to as mHealth, have shown to have the capacity to confront and solve most of the challenges within mental health services. This paper conducted a comprehensive investigation in 2024 to identify all review studies published between 2000 and 2024 that investigate the advantages of mHealth in mental health services. The databases searched included PubMed, Scopus, Cochrane and ProQuest. The quality of the final papers was assessed and a thematic analysis was performed to categorize the obtained data. 11 papers were selected as final studies. The final studies were considered to be of good quality. The risk of bias within the final studies was shown to be in a convincing level. The main advantages of mHealth interventions were categorized into four major themes: ‘accessibility, convenience and adaptability’, ‘patient-centeredness’, ‘data insights’ and ‘efficiency and effectiveness’. The findings of the study suggested that mHealth interventions can be a viable and promising option for delivering mental health services to large and diverse populations, particularly in vulnerable groups and low-resource settings.
This study explores the experiences of participants receiving a mobile-based brief intervention (BI) for hazardous drinking in India, to determine characteristics that influenced engagement and examine perceived reasons for change in alcohol consumption.
Methods
Semi-structured interviews were conducted with 10 adult hazardous drinkers who received a mobile-based BI in the intervention arm of a pilot randomised control trial. Data were coded through an iterative process and analysed using thematic analysis.
Findings
Study participants reported a positive experience, with factors such as customised intervention delivery and personal motivation facilitating their engagement. Participants reported a reduction in quantity and frequency of alcohol use. This was credited to the intervention, particularly, its provision of health-related information, goal-setting content and strategies to manage drinking. Apart from alcohol reduction, participants reported improvements in diet, lifestyle, wellbeing, and familial relations.
Implication
By providing a context to explain the impact of the intervention, the learnings from this study can be used to strengthen the implementation of mobile-based interventions. This study outlines the scope for further research in digital health, such as Internet-based health interventions, and incorporating digital interventions within the ambit of existing health care programmes.
Mental disorders are common among university students. In the face of a large treatment gap, resource constraints and low uptake of traditional in-person psychotherapy services by students, there has been interest in the role that digital mental health solutions could play in meeting students’ mental health needs. This study is a cross-sectional, qualitative inquiry into university students’ experiences of an online group cognitive behavioural therapy (GCBT) intervention. A total of 125 respondents who had participated in an online GCBT intervention completed a qualitative questionnaire, and 12 participated in in-depth interviews. The findings provide insights into how the context in which the intervention took place, students’ need for and expectations about the intervention; and the online format impacted their engagement and perception of its utility. The findings of this study also suggest that, while online GCBT can capitalise on some of the strengths of both digital and in-person approaches to mental health programming, it also suffers from some of the weaknesses of both digital delivery and those associated with in-person therapies.
Health care workers (HCWs) are increasingly faced with the continuous threat of confronting acute disasters, extreme weather-related events, and protracted public health emergencies. One of the major factors that determines emergency-department-based HCWs’ willingness to respond during public health emergencies and disasters is self-efficacy. Despite increased public awareness of the threat of disasters and heightened possibility of future public health emergencies, the emphasis on preparing the health care workforce for such disasters is inadequate in low-and-middle-income countries (LMICs). Interventions for boosting self-efficacy and response willingness in public health emergencies and disasters have yet to be implemented or examined among emergency HCWs in LMICs. Mobile health (mHealth) technology seems to be a promising platform for such interventions, especially in a resource-constrained setting. This paper introduces an mHealth-focused project that demonstrates a model of multi-institutional and multidisciplinary collaboration for research and training to enhance disaster response willingness among emergency department workers in Pakistan.
Technology-based interventions (TBIs) are a useful approach when attempting to provide therapy to more patients with psychosis.
Methods
Randomized controlled trials of outcomes of TBIs v. face-to-face interventions in psychosis were identified in a systematic search conducted in PubMed/Ovid MEDLINE. Data were extracted independently by two researchers, and standardized mean changes were pooled using a three-level model and network meta-analysis.
Results
Fifty-eight studies were included. TBIs complementing treatment as usual (TAU) were generally superior to face-to-face interventions (g = 0.16, p ≤ 0.0001) and to specific outcomes, namely, neurocognition (g = 0.13, p ≤ 0.0001), functioning (g = 0.25, p = 0.006), and social cognition (g = 0.32, p ≤ 0.05). Based on the network meta-analysis, the effect of two TBIs differed significantly from zero; these were the TBIs cognitive training for the neurocognitive outcome [g = 0.16; 95% confidence interval (CI) 0.09–0.23] and cognitive behavioral therapy for quality of life (g = 1.27; 95% CI 0.46–2.08). The variables educational level, type of medication, frequency of the intervention, and contact during the intervention moderated the effectiveness of TBIs over face-to-face interventions in neurocognition and symptomatology.
Conclusions
TBIs are effective for the management of neurocognition, symptomatology, functioning, social cognition, and quality of life outcomes in patients with psychosis. The results of the network meta-analysis showed the efficacy of some TBIs for neurocognition, symptomatology, and quality of life. Therefore, TBIs should be considered a complement to TAU in patients with psychosis.
The application of mobile health holds promises of achieving greater accessibility in the evolving health care sector. The active engagement of private actors drives its growth, while the challenges that exist between health care privatization and equitable access are a concern. This article selects the private internet hospital in China as a case study. It indicates that a market-oriented regulatory mechanism of private mobile health will contribute little to improving health equity from the perspectives of egalitarians and libertarians. By integrating the capability approach and the right to health, it is claimed that mobile health is a means of accessing health care for everyone, where substantive accessibility should be emphasized. With this view, this article provides policy recommendations that reinforce private sector engagement for mobile health, recognizing liberty, equity, and collective responsibility in the Chinese context.
With their widespread use in the Global South, mobile phones are attracting growing interest from international aid actors and local authorities alike, who are positioning mobile technology as a growth driver and a solution to many social problems. Initiated by giants of the digital industry, these policies are reviving old questions about technological development, the relationship between the market sector and States, and the role of technology in the inequalities between the Global North and Global South. Through a multi-sited ethnography on maternal care in Ghana and India, this Element provides a first-hand look at initiatives that promise to improve poor women's health in the Global South through the use of mobile phones; a field known as Mobile Health or mHealth. Attentive to the way in which these technical objects modify power relations at both international and local levels, this Element also discusses how mHealth transforms care practices and healthcare.
There has been a lack of health technology assessment (HTA) methods for novel digital health technologies (DHTs) such as mHealth, artificial intelligence, and robotics in Finland. The Digi-HTA method has been developed for this purpose. The aim of this study is to determine whether it would be possible to use Digi-HTA recommendations to support healthcare decision-makers. Secondly, from the perspective of companies offering different types of DHT products, this study assesses the suitability of using the Digi-HTA framework to perform HTAs for their products.
Methods
Feedback about Digi-HTA recommendations was collected from healthcare professionals. DHT companies provided input about the Digi-HTA framework. Data were collected via a web-based survey and were analyzed using qualitative methods.
Results
Of the twenty-four healthcare professional respondents, twenty said that the Digi-HTA recommendations contained all the necessary information, and twenty-one found them useful for their work. Respondents hoped that the Digi-HTA recommendations would be better integrated into the decision-making processes and healthcare professionals would be more informed about this new HTA process. The questions of the Digi-HTA framework were applicable for different DHT products based on the responses from DHT companies (n = 8).
Conclusions
According to the study participants, although the Digi-HTA recommendations include clear and beneficial information, their integration into healthcare decision-making processes should be improved. Responses from DHT companies indicate that the Digi-HTA framework would be an appropriate tool for performing assessments for their products. To generalize the findings of this study, more comprehensive studies will be needed.
Mobile Health (mHealth) interventions have received a mix of praise and excitement, as well as caution and even opposition over recent decades. While the rapid adoption of mHealth solutions due to the COVID-19 pandemic has weakened resistance to integrating these digital approaches into practice and generated renewed interest, the increased reliance on mHealth signals a need for optimizing development and implementation. Despite an historically innovation-resistant medical ethos, mHealth is becoming a normalized supplement to clinical practice, highlighting increased demand. Reaching the full potential of mHealth requires new thinking and investment. The current challenge to broaden mHealth adoption and to ensure equity in access may be overcoming a “design purgatory,” where innovation fails to connect to practice. We recommend leveraging the opportunity presented by the COVID-19 pandemic to disrupt routine practice and with a new focus on theory-driven replicability of mHealth tools and strategies aimed at medical education and professional organizations.
This chapter reviews how ubiquitous mobile technology can be used to better understand and improve recovery from alcohol use disorder. Distinct applications of both active and passive technology-assisted data collection (i.e., ecological momentary assessment, ambulatory assessment) to assess alcohol use and broader recovery outcomes are described. Previous studies of and future opportunities to use these methods to examine recovery-related processes and mechanisms of behavior change are highlighted. Promising mobile-based interventions or recovery support services examined to date are described, ranging from classic telehealth approaches to sophisticated interventions relying on both self-reported and sensor-based inputs to tailor the timing and content of intervention (i.e., ecological momentary interventions, Just-In-Time Adaptive Interventions). The chapter concludes with discussion of the potential for these interventions to achieve individualized intervention optimization (i.e., personalized treatment, precision medicine).
Telehealth is now a fundamental health approach to address health-related needs in a way that is consistent with the restrictions imposed by the coronavirus pandemic (COVID-19) globally.
Despite significant advancements in healthcare technology, digital health solutions – especially those for serious mental illnesses – continue to fall short of their potential across both clinical practice and efficacy. The utility and impact of medicine, including digital medicine, hinges on relationships, trust, and engagement, particularly in the field of mental health. This paper details results from Phase 1 of a two-part study that seeks to engage people with schizophrenia, their family members, and clinicians in co-designing a digital mental health platform for use across different cultures and contexts in the United States and India.
Methods
Each site interviewed a mix of clinicians, patients, and their family members in focus groups (n = 20) of two to six participants. Open-ended questions and discussions inquired about their own smartphone use and, after a demonstration of the mindLAMP platform, specific feedback on the app's utility, design, and functionality.
Results
Our results based on thematic analysis indicate three common themes: increased use and interest in technology during coronavirus disease 2019 (COVID-19), concerns over how data are used and shared, and a desire for concurrent human interaction to support app engagement.
Conclusion
People with schizophrenia, their family members, and clinicians are open to integrating technology into treatment to better understand their condition and help inform treatment. However, app engagement is dependent on technology that is complementary – not substitutive – of therapeutic care from a clinician.
Medication non-adherence causes poor outcomes in paediatric organ transplantation. COVID-19 pandemic has led to an exponential use of mobile health approaches for patient care. Herein, we describe a pilot intervention study using mobile video directly observed therapy building on emerging trends in research and clinical practice pertaining to medication adherence in paediatric organ transplantation.
Public health measures to curb SARS-CoV-2 transmission rates may have negative psychosocial consequences in youth. Digital interventions may help to mitigate these effects. We investigated the associations between social isolation, COVID-19-related cognitive preoccupation, worries, and anxiety, objective social risk indicators, and psychological distress, as well as use of, and attitude toward, mobile health (mHealth) interventions in youth.
Methods
Data were collected as part of the “Mental Health And Innovation During COVID-19 Survey”—a cross-sectional panel study including a representative sample of individuals aged 16–25 years (N = 666; Mage = 21.3; assessment period: May 5, 2020 to May 16, 2020).
Results
Overall, 38% of youth met criteria for moderate or severe psychological distress. Social isolation worries and anxiety, and objective risk indicators were associated with psychological distress, with evidence of dose–response relationships for some of these associations. For instance, psychological distress was progressively more likely to occur as levels of social isolation increased (reporting “never” as reference group: “occasionally”: adjusted odds ratio [aOR] 9.1, 95% confidence interval [CI] 4.3–19.1, p < 0.001; “often”: aOR 22.2, CI 9.8–50.2, p < 0.001; “very often”: aOR 42.3, CI 14.1–126.8, p < 0.001). There was evidence that psychological distress, worries, and anxiety were associated with a positive attitude toward using mHealth interventions, whereas psychological distress, worries, and anxiety were associated with actual use.
Conclusions
Public health measures during pandemics may be associated with poor mental health outcomes in youth. Evidence-based digital interventions may help mitigate the negative psychosocial impact without risk of viral infection given there is an objective need and subjective demand.
Sleep disruption is a common precursor to deterioration and relapse in people living with psychotic disorders. Understanding the temporal relationship between sleep and psychopathology is important for identifying and developing interventions which target key variables that contribute to relapse.
Methods
We used a purpose-built digital platform to sample self-reported sleep and psychopathology variables over 1 year, in 36 individuals with schizophrenia. Once-daily measures of sleep duration and sleep quality, and fluctuations in psychopathology (positive and negative affect, cognition and psychotic symptoms) were captured. We examined the temporal relationship between these variables using the Differential Time-Varying Effect (DTVEM) hybrid exploratory-confirmatory model.
Results
Poorer sleep quality and shorter sleep duration maximally predicted deterioration in psychosis symptoms over the subsequent 1–8 and 1–12 days, respectively. These relationships were also mediated by negative affect and cognitive symptoms. Psychopathology variables also predicted sleep quality, but not sleep duration, and the effect sizes were smaller and of shorter lag duration.
Conclusions
Reduced sleep duration and poorer sleep quality anticipate the exacerbation of psychotic symptoms by approximately 1–2 weeks, and negative affect and cognitive symptoms mediate this relationship. We also observed a reciprocal relationship that was of shorter duration and smaller magnitude. Sleep disturbance may play a causal role in symptom exacerbation and relapse, and represents an important and tractable target for intervention. It warrants greater attention as an early warning sign of deterioration, and low-burden, user-friendly digital tools may play a role in its early detection.