Hispanic people with HIV who smoke cigarettes experience unique stressors (eg, stigma), which contribute to health disparities. Anxiety sensitivity (AS) may worsen mood management problems, which are a leading barrier to smoking cessation. Interventions targeting AS can improve HIV-specific outcomes and smoking cessation. However, no prior research has culturally tailored an AS reduction program to improve quality of life among Hispanic people with HIV who smoke. The research team previously developed a mobile health (mHealth) intervention addressing AS reduction, smoking cessation, and HIV care management for Black people with HIV who smoke. Building on this work, this study represents a formative, exploratory phase to develop culturally tailored mHealth content for Hispanic people with HIV across 3 distinct regions (Mexico, Central America, and South America), which share many similarities but differ in some cultural and linguistic respects. This work will inform the refinement of materials for these groups and the future development of an integrated mHealth app for smoking, AS, and HIV among this population (ie, VITAL). This study aimed to culturally tailor evidence-based smoking cessation content targeting AS reduction and HIV management among Hispanic adults to inform the development of the VITAL mHealth program. Intervention content was culturally adapted using a theory-informed intervention adaptation framework that integrated a cultural considerations document derived from existing literature on smoking cessation and HIV care among the Hispanic population, along with iterative consultation with a Community Research Advisory Board. This resulted in linguistically tailored content in English and Spanish. The pilot study consisted of Hispanic people with HIV who smoke (N=80), divided into 3 subgroups: Mexican/Mexican American, Central American, and South American. Participants completed self-report assessments and a semistructured interview assessing the treatment videos for content relevance, appropriateness, and ease of understanding. Interviews were conducted online in Spanish or English by trained interviewers. Interview transcripts will be coded by a multidisciplinary qualitative team using a 2-pass approach: initial coding of the interview question followed by higher-level concepts. Themes will be reviewed by another member of the team to assess trustworthiness, saturation, and triangulated with quantitative data, then analyzed by geographic subgroup. Three linguistically tailored versions of the intervention materials were developed. Data collection began August 19, 2024, and finished June 26, 2025. Data cleaning is ongoing, and analyses will begin in April 2026. Content refinement and app integration are anticipated to be completed by September 2026. Upon completion of analysis, data will be used to further refine culturally tailored intervention content for Hispanic adult subgroups. This formative pilot study will inform the cultural adaptation and refinement of an mHealth app, VITAL, which will be tested in a subsequent randomized controlled trial to improve health disparities and assist Hispanic people with HIV in quitting smoking.
Formative evaluation is widely used in implementation science to anticipate barriers and facilitators prior to the deployment of health technologies, typically relying on stakeholders' reported beliefs collected before real-world exposure. This approach has proven informative for many digital health tools; however, its application to immersive and embodied technologies such as extended reality (XR) warrants closer scrutiny. Most XR interventions in health care are delivered through head-mounted displays, which depend on spatial perception and sensorimotor engagement. Several implementation-relevant properties, including comfort, perceived intrusiveness, safety, and workflow disruption, often become apparent only through direct interaction. At the same time, large segments of the health care workforce remain XR-naive, such that preuse judgments are frequently shaped by anticipation rather than experience. Drawing on concepts from implementation science, grounded cognition, and human-computer interaction, this Viewpoint examines a plausible interpretive problem in XR adoption and argues that perception-based formative evaluation, when applied through frameworks developed for screen-based technologies, may misclassify barriers and facilitators. Rather than questioning formative evaluation as a methodological approach, we identify a boundary condition for its interpretability in experience-dependent technologies and propose a pragmatic refinement: incorporating brief experiential familiarization before eliciting stakeholder perceptions to strengthen early-stage assessment and improve alignment with real-world implementation decisions.
As telehealth has become an increasingly common mode of care delivery, older adults may face structural, technological, and interactional barriers that limit their ability to engage with video-based care. Although digital ageism, defined as the presence of age-related stereotypes, lowered expectations, or assumptions about older adults' technology-related competence, has been described in prior literature, less is known about how such dynamics surface during real-time telehealth encounters and how they may shape participation in technology-focused clinical trials. This formative ethnographic study aimed to (1) document real-world barriers encountered by older adults immediately before and during video telehealth visits and (2) inform recruitment and implementation procedures for a subsequent telepharmacy randomized controlled trial. We conducted in-home, real-time ethnographic observation of 20 community-dwelling veterans aged ≥65 years participating in pharmacist-led video visits for medication management. Recruitment occurred over approximately 6 to 10 months using mailed invitation letters (>300 sent), supplemented with outbound telephone calls. Data sources included structured field notes completed independently by an in-house anthropologist and the remote clinical pharmacist, as well as observational documentation of previsit preparation, visit navigation, and postvisit reflections. Data were analyzed using qualitative rapid analysis, with iterative team review and triangulation across data sources. Participants had a mean age of 74 (SD 3.18) years; 19 of 20 (95%) were male, and 18 of 20 (90%) identified as White. All participants completed a video visit with technical support as needed. Structural barriers (eg, broadband access and device availability) and usability challenges (eg, audio-video setup and navigation) were common. Although digital ageism was not a predefined analytical category, age-related assumptions about technology emerged during observation, including participants attributing anticipated or experienced difficulties to age and expressing surprise or pride following successful completion of the visit. These age-related interpretations were analytically distinct from access and usability barriers and were interpreted as manifestations of digital ageism, particularly as internalized age-based expectations. Formative ethnographic observation provided critical insights into how older adults experience telehealth encounters in real-world contexts and informed adaptations to recruitment and implementation procedures for a subsequent randomized controlled trial. Although digital ageism was not an original study aim, age-related assumptions about technology emerged as an important interpretive factor shaping engagement with video-based care. Incorporating ethnographic methods prior to trial implementation may help identify otherwise overlooked barriers and improve the inclusivity and feasibility of technology-focused clinical research involving older adults.
Real-time force feedback is essential in many surgical specialties. While previous research has focused on force measured at the tool-tissue interface, little work has explored the benefits, limitations, or opportunities of measuring force at the surgeon-tool interface. This study aims to explore scenarios in which surgeons from different medical specialties and experience levels could benefit from receiving feedback on the force exerted at the surgeon-tool (or surgeon-tissue) interface. Exploratory qualitative research was conducted through interviews with medical practitioners (N=15). This study explored perceptions of a conceptual novel force-sensing surgical glove that could provide real-time feedback in terms of usability, utility, value, and limitations. Opportunities and barriers to implement a sensor of this type in clinical practice were also explored. Participants had experience in anesthetics, dental surgery, plastic and dermatological surgery, general surgery, and obstetrics and gynecology, as these surgical fields all require precise feedback on exerted forces. Participants identified two key areas where a force sensor could yield significant benefits: (1) it could enhance surgical training through objective skill assessment and quantifiable feedback, and (2) it could provide valuable insights into the forces applied during practice, particularly in scenarios where other sensory feedback is masked. Participants appreciated that a sensorized glove that can provide real-time force sensing at the surgeon-tool interface would allow for continued feedback irrespective of the instrument, and integrate seamlessly into their current surgical workflow. Furthermore, as surgeons in some specialisms, for example, dental or obstetrics and gynecology, perform manual tasks, having a sensorized glove would provide feedback in instances where they are physically manipulating tissue. However, participants expressed concerns about accurately defining safe force ranges due to the variability in patients' anatomical structures and the potential interference with tactile sensation. Surgeons from various clinical practices agreed that force sensing at the surgeon-tool interface could be valuable and provide them with optimal versatility as to when they would adopt force sensing. A sensorized glove could improve decision-making and surgical outcomes when other sources of information guiding force exertion are masked. Conversely, it could be detrimental when the organic information to guide force exertion is distorted when using the sensor. While the choice between interaction modalities is dependent on the accessibility of different senses during surgery, design suggestions as to where sensors are best placed on a sensorized glove are dependent on the instrument used or the type of manual procedure conducted.
Newborn screening (NBS), a mandated public health intervention, allows the identification of babies with potentially life-threatening disorders and facilitates disease diagnosis and management before the onset of symptoms. While NBS saves lives, the process can be fraught with anxiety and unanswered questions from parents or guardians of newborns, especially as they wait for an appointment with a clinician. This study aimed to describe the development and testing of an educational chatbot (NBSchat) to address the emotional support and information needs of parents of newborns identified with sickle cell trait via NBS. NBSchat, a fully scripted (ie, rule-based) chatbot, was developed by a multidisciplinary team and evaluated through a sequential multiple methods study, including interviews and a survey. To inform chatbot design, we conducted semistructured interviews with 11 adults-5 clinicians who work with parents of infants identified with sickle cell trait through NBS and 6 parents of infants aged 12 months or less-using the critical incident technique and think-aloud tasks while using a prototype of NBSchat. Transcripts underwent thematic analysis. In a survey, 250 parents of infants aged 12 months or less without abnormal NBS results were shown a mock newborn screening result letter and then interacted with NBSchat, after which they self-reported emotional and attitudinal outcomes before and after the simulated exposure. Feedback from interviews confirmed that parents are distressed by trait results and actively seek information and reassurance. Thematic analysis indicated that NBSchat provided reliable, accurate information that parents wanted and had the potential to reduce negative emotions (eg, provide relief and reduce stress). Key strengths included addressing an immediate health concern and offering reassurance. The results of the postintervention survey indicated that, compared to pre-exposure scores, participants reported significantly lower negative emotions (mean 7.0 [SD 3.2] vs 5.8 [SD 3.2] out of 12; mean difference -1.2, 95% CI -1.57 to -0.83; P<.001), improved positive emotions (reflected by a decrease in the reverse-coded positive emotion score; mean 8.6 [SD 4.2] vs 7.8 [SD 4] out of 16; mean difference -0.8, 95% CI -1.27 to -0.37; P<.001), and reduced uncertainty (mean 6.5 [SD 3] vs 5.5 [SD 3.4] out of 12; mean difference -1, 95% CI -1.42 to -0.58; P<.001). Parents noted that NBSchat provided immediate reassurance and was convenient to access. They further reported that the predefined, structured questions in the script helped guide their learning and understanding. Overall, participants who interacted with NBSchat found it to be acceptable, with improved emotional measures after its use. Future research will investigate the outcomes of using the chatbot and its implementation in a pragmatic randomized controlled trial.
Hypertension remains a leading global health challenge, particularly in low- and middle-income countries (LMICs), where limited health care infrastructure and resources restrict effective management. Community health workers (CHWs) are critical in delivering care in these settings, and when equipped with mobile health (mHealth) apps, they can greatly enhance chronic disease management. Involving CHWs in the design and development at all stages is essential for the success of such programs. However, relatively little research discusses CHW feedback on mHealth interventions. This study aims to evaluate CHW feedback on a hypertension program using a novel tablet-based mHealth tool designed for CHW hypertension diagnosis and management in rural Guatemala. We conducted a mixed-methods analysis as part of a pilot study in San Lucas Tolimán, Guatemala, involving 6 CHWs over a 6-month period. Quantitative data were collected using the System Usability Scale and Likert-scale surveys before and after study completion. Qualitative data were gathered through written surveys and focus group interviews conducted in Spanish by bilingual team members. These methods assessed the app's ease of use, workflow integration, and cultural appropriateness. CHWs provided detailed perspectives on technical challenges, training adequacy, and patient engagement, which guided iterative refinements to both the mHealth app and the hypertension management program. The mHealth app was generally well-received. Average System Usability Scale scores exceeded 70, surpassing established usability thresholds. Likert scale data revealed CHWs found the app to be useful and easy to use, but identified training protocols as areas for improvement. Qualitative analysis of focus groups and written surveys revealed 3 dominant themes. First, CHWs identified practical short-term needs, including slower and more comprehensive training sessions, simplified medication dosing regimens to reduce pill burden, and streamlined survey questions to shorten patient visit times. Second, CHWs raised larger structural concerns, including retention challenges related to financial compensation and misalignment between required clinical data collection and the cultural appropriateness of certain app questions. Third, CHWs highlighted program benefits, including improved patient care and hypertension management, empowerment through educational tools, and increased pride and community trust associated with the program. Our findings suggest that iteratively integrating user feedback into the development of mHealth interventions is key to improve usability, cultural appropriateness, and overall effectiveness of chronic disease management in resource-constrained settings. Due to the small number of CHW participants, as well as a reliance on self-reported perceptions, these findings should be interpreted as exploratory and hypothesis-generating rather than generalizable. This study contributes to the growing literature on mHealth apps for noncommunicable diseases in LMICs and provides insights into CHW experiences. Addressing the technical barriers and systemic challenges identified in this study can help improve future implementations of mHealth-enabled chronic disease programs in LMICs.
There are a large number of pediatric emergency patients. Due to the fact that the children cannot describe their own conditions, there is a shortage of nursing staff, it is extremely important to identify the early warning signs of the children's conditions as early as possible. The current targeted care needs to be improved. This study aimed to investigate the application of an artificial intelligence-based pediatric early warning score (PEWS) in the pediatric emergency observation unit, analyze the relationship between PEWS and disease severity , and assess its impact on length of hospital stay and hospitalization costs after admission, so as to provide references for targeted nursing care. We performed a retrospective study. A total of 1,233 pediatric patients admitted via the pediatric emergency department of a tertiary specialty hospital in Guangzhou from September 2023 to March 2024 were included. The patients were divided according to the status of the activation of the early-warning group (PEWS score ≥ 1) vs. not triggered [score 0]) during emergency observation. Length of stay and hospitalization costs were compared between the early warning group and the non-early warning group.The differences between groups were performed with the Mann-Whitney U test. We did the multivariable logistic regression to discuss the association of resource utilization metrics and the status of AI-PEWS, adjusted by age, sex and disease category (respiratory, neurological, hematologic). In 1,233 patients, 597 (48.4%) triggered the AI-PEWS (mean score 2.44 ± 1.41), and 636 (51.6%) did not. In the early warning group, 68 children were transferred to the intensive care unit, with a mean PEWS of 3.32 ± 1.73. Compared with the non-early warning group, the early warning group had a longer hospital stay (z = -5.180, P < 0.001) and higher hospitalization costs (z = -6.500, P < 0.001), and the differences between groups were statistically significant (P < 0.001). Among the top three admission categories-respiratory, neurological, and hematologic diseases-children in the PEWS early warning group had significantly longer hospital stays and higher hospitalization costs, with statistically significant differences between groups (P < 0.01). The β coefficient for length of hospital stay was 0.053 (SE=0.010), Waldχ²=5.533, OR=1.055 (95% CI: 1.035-1.075); while the β coefficient for hospitalization costs was 0.001 (SE=0.000), Waldχ²=6.075, OR=1.001 (95% CI: 1.001-1.001). Compared with the non-early-warning group, the early-warning group had significantly longer hospital stays and higher hospitalization costs; similar patterns were observed within respiratory, neurological, and hematologic disease categories. It shows differences between children who triggered the warning and children who did not, providing a reference for identifying critically ill children and for targeted care.
In October 2022, the Nutrition Now (NN) e-learning resource was implemented within Maternal and Child Healthcare centers and Early Childhood Education and Care centers of a southern Norwegian municipality. The e-learning resource targets expectant parents, parents of children aged 0-2 years, and Early Childhood Education and Care staff, aiming to promote healthy dietary behaviors during the first 1000 days of life. This study aimed to explore parental perceptions related to the acceptability, appropriateness, feasibility, and reported use of the NN e-learning resource among parents. From October 2022 to May 2023, expecting parents and parents of children aged 0-2 years were recruited from 2 Norwegian municipalities, one intervention group receiving access to the NN e-learning resource, and one control. Participants in the intervention group received a web-based follow-up questionnaire 7 months after gaining access to the NN e-learning resource. Data were analyzed using descriptive statistics. Of the 179 participants in the NN study intervention group, 48 completed the web-based follow-up questionnaire administered 7 months after enrollment. Parents rated the e-learning resource positively on items assessing whether they liked and appreciated the resource, perceived it as an appropriate source of information, and found it doable and easy to use. Most respondents reported visiting the resource (38/48, 79%), although only 21% (10/48) reported frequent visits. Less than half of the participants answering the web-based follow-up questionnaire reported having watched the theme films (20/48, 42%), the recipe films (17/48, 35%), or making food using recipes provided in the e-learning resource (20/48, 42%). Parents rated the NN e-learning resource positively but reported limited use. These findings point to the need for strategies that enhance engagement with self-guided digital interventions among expectant parents and parents of young children. Future efforts should focus on identifying how to maximize potential adoption of the e-learning resource and evaluate its impact to promote healthy dietary behaviors during the first 1000 days of life.
HIV testing is the gateway to the HIV prevention continuum and offers an important opportunity to provide HIV prevention services. TakeMeHome.org is an online program that enables state and local health departments to offer free in-home HIV and sexually transmitted infection self-testing. As few TakeMeHome users have used pre-exposure prophylaxis (PrEP), there is an opportunity to link TakeMeHome users to PrEP information and services. The aim of this study is to develop an implementation strategy to link HIV or sexually transmitted infection self-testers from online orders to PrEP services via direct digital linkage to a novel SMS text messaging navigation program. PrEPmate is an evidence-based bidirectional text-messaging platform that has demonstrated increased PrEP retention and adherence. We developed a novel program to link TakeMeHome testers to mobile SMS text messaging PrEP navigation via PrEPmate. We conducted focus groups among TakeMeHome users to elicit preferences for linkage from TakeMeHome to PrEPmate. Based on these focus groups, we revised the content and functionality of this linkage intervention. In October 2023, we launched a pilot implementation study in 2 US Ending the HIV Epidemic jurisdictions: Sacramento, California, and Tarrant, Texas. Thirteen TakeMeHome users participated in 4 focus groups (mean age 31.5 years; n=4, 31% Latinx, n=2, 15% Black; n=9, 69% never used PrEP). When shown wireframes of the TakeMeHome or PrEPmate linkage, most thought they were easy to navigate and user-friendly. They liked the privacy of connecting with a PrEP navigator using SMS text messaging. Participants recommended providing a clear description of PrEP and PrEPmate services and indicating that PrEP is low or no cost on the TakeMeHome website. On the PrEPmate landing page, they recommended adding language on confidentiality and the partnership with TakeMeHome to show that both services are connected. Once enrolled, they recommended weekly or biweekly check-ins to assist with PrEP navigation. Overall, 92% (12/13) of focus group participants were likely to use PrEPmate to learn more about PrEP and/or link to PrEP services. From October 2023 to May 2024, among 537 individuals who ordered test kits and were not on PrEP, 169 (31%) were linked to the PrEPmate page, and 86 (16%) enrolled in PrEPmate. PrEP navigation was provided via SMS text messaging or phone, with 46 (53%) receiving PrEP education and 26 (30%) in various stages of starting PrEP. In exit interviews, participants found the intervention easy to use and appreciated being connected with an experienced PrEP navigator who helped them access PrEP. Through user-centered design, we successfully developed a program to link TakeMeHome testers to PrEP navigation via PrEPmate, with high feasibility and acceptability of the intervention and a substantial number of clients starting PrEP. The next steps will involve evaluating the effectiveness of this program on a larger scale and, if successful, expanding PrEPmate navigation to all Ending the HIV Epidemic jurisdictions using TakeMeHome.
Patient and public involvement is essential for developing patient-centered and acceptable eHealth interventions, yet little is known about how digital collaboration with patient representatives can best be implemented in psycho-oncological research. This study aimed to identify the benefits and barriers of digital collaboration in the development of an e-mental health application and provide recommendations to optimize digital collaboration with patient representatives in psycho-oncology research. Conducted from July to September 2023, this study involved digital semistructured interviews with 5 patient representatives from the Reduct trial, a multicenter randomized controlled trial to evaluate the efficacy of the web-based psycho-oncological training Make It. The interviews were analyzed using qualitative content analysis. The findings highlighted multiple advantages of digital collaboration. These included significant reductions in travel costs and effort, personal acceptance and preference for digital methods, enhanced flexibility and accessibility, a reduced health burden, increased efficiency, and scalability. Conversely, several challenges were identified: social impacts or impediments due to less face-to-face interaction, technical difficulties, compromised effectiveness and quality of communication, diverse personal preferences and acceptance levels, organizational issues, cognitive demands, socioeconomic barriers, and safety concerns. The following recommendations to optimize digital collaboration were identified: maintaining regular communication and information exchange, valuing and committing to the collaboration, using diverse communication channels, ensuring comprehensible communication, integrating feedback, fostering openness and understanding, diligent documentation and recordkeeping, and providing targeted training and support for patient representatives. These findings confirm and specify previously known opportunities and challenges of digital collaboration, adding crucial insights for its implementation in psycho-oncological research. This research contributes to enhancing patient-centered approaches in psycho-oncology.
Nearly all youth use the internet daily, with many maintaining several social media accounts. As increasing numbers of young people engage online and the ways we communicate fundamentally change, it is increasingly important to ask: how do these shifts influence youth mental health? To better understand how social media may affect mental health, researchers require validated tools that capture young people's heterogeneous experiences with social media. However, few available measures evaluate the full range of positive and negative behaviors associated with its use, limiting our ability to meaningfully advance interventions promoting online hygiene. This study aims to develop and validate the Comprehensive Assessment of Social Media Use (CASM). The CASM is a self-report survey measure that moves beyond simple duration or frequency of use and captures how young people engage with social media. Importantly, the CASM assesses both the positive and negative dimensions of social media engagement. Two studies are outlined in this paper. Study 1 outlines the process of item generation and exploratory factor analysis. Study 2 outlines confirmatory factor analysis and validity testing. Both studies were conducted online and enrolled a convenience sample of college-aged young adults. Study 1 enrolled 260 participants (mean age 19.73, SD 2.91; n=172, 66.2% female; n=164, 63.1% White; n=38, 14.6% lesbian, gay, bisexual, transgender/transsexual, and queer [LGBTQ]). Study 2 enrolled 508 participants (mean age 18.99, SD 1.17; n=323, 63.6% female; n=272, 53.5% White; n=58, 11.4% LGBTQ). Exploratory and confirmatory factor analysis resulted in a 29-item CASM scale that assesses 7 distinct aspects of young adult social media use: self-branding, compulsive use, disruptive use, impulsive sharing, social engagement, induce negative emotions, and induce positive emotions. This model accounted for 61% of the variance in responses. The chi-squared test of model fit was significant (χ²356=941, P<.001; root mean square error of approximation=0.064; comparative fit index=0.855; Tucker-Lewis index=0.848; standardized root mean squared residual=0.060). Factor internal consistency reliability ranged from 0.699 to 0.817. Validity testing suggested moderate discriminant, convergent, and criterion validity. The CASM measures a broad range of social media behaviors, enabling researchers to more effectively examine associations between online engagement and mental health outcomes. We hope the CASM will help researchers better understand how young people interact with social media, and that this knowledge will inform the development of more targeted interventions promoting healthy online habits.
Text generation approaches in health care communication have evolved along 2 major paths. The first path involves generative adversarial networks, progressing from basic architectures to specialized variants like Text-to-Text Generative Adversarial Network (TT-GAN) and Time and Frequency Domain-Based Generative Adversarial Network (TF-GAN), which address challenges in discrete text generation through techniques such as Gumbel-Softmax and reinforcement learning. The second path emerges from transformer-based architectures, particularly Generative Pretrained Transformer-2 (GPT-2), which uses extensive pretraining and self-attention mechanisms to generate contextually appropriate text. GPT-2's transformer architecture enhances persuasive health communication by generating personalized messages using various strategies like task support, dialogue support, and social support for effective health interventions. This study aimed to use GPT-2 as a generative method to construct persuasive text in a dataset and compare the performance of sentiment analysis and emotion detection analysis. We combined sentiment analysis tools (VADER [Valence Aware Dictionary and Sentiment Reasoner] and TextBlob) with emotion detection methods (Text2Emotion and NRCLex [National Research Council Lexicon]) to analyze health coaching messages across different persuasive types: reminder, reward, suggestion, and praise. TextBlob and VADER achieved accuracies of 57% and 69%, respectively, while RoBERTa (robustly optimized BERT approach)-sentiment outperformed them with an accuracy of 88%. Emotion detection showed a high prevalence of "joy" and "happy" labels (93.69% positive skew). While transformers excel in accuracy, lexicon-based models like VADER offer a better performance-efficiency balance for real-time health communication systems. For emotion detection, all categories showed perfect accuracy (1.0), while trust showed mixed results, with precision, recall, and F1-score values ranging from 0.81 to 0.96. The emotion detection analysis revealed varying success rates across different emotions, with some categories, such as anger and neutral, showing reasonable performance and others, such as trust, showing mixed performance. This research contributes to understanding the emotional dynamics of persuasive health communication and highlights both the capabilities and limitations of current natural language processing tools in analyzing health-related persuasive messaging. This proof-of-concept study using synthetically generated data establishes a methodological framework for multimodal sentiment and emotion analysis. The findings require validation with real-world health coaching messages before clinical deployment.
Mobile health (mHealth), and specifically smartphone apps, have grown exponentially in both functionality and accessibility and are becoming an important component of health care. Research exploring the use of mHealth for managing or treating chronic diseases, such as cancer, has shown promising effects. Yet, comparatively little work has examined how such technologies can enhance exercise interventions for young people with cancer. To optimize the effectiveness of mHealth in these contexts, it is essential to build a stronger evidence base on user experience. This study aimed to investigate how healthy children and young people engaged with an augmented reality (AR) app developed specifically for children and young people undergoing cancer treatment, and to identify design features that may support engagement and behavior change in the intended clinical population. School and university students, aged 8-21 years, were eligible to participate in the study. Practical workshops allowed participants to engage with the AR exercise app before taking part in focus groups to explore user experiences. Data were analyzed using qualitative content analysis, which also involved a critical friend approach using 2 researchers (HM and KS). Suggested improvements were mapped against the motivational affordances' taxonomy. A total of 39 participants aged 8-21 years took part in the focus group study. Participants found the demonstrations and varied exercises useful but expressed some concerns regarding data safety and functionality of the novel AR avatar. It was proposed that additional educational components, challenges, and rewards, as well as a customizable avatar, social support features, and audio instructions for a more inclusive design would be desirable and could enhance user experience. When mapped against the motivational affordances taxonomy, the suggested improvements aligned primarily with mechanisms of user education, challenges, feedback, cooperation, and comparison. This study provides an understanding of how apps that prescribe exercise can be optimized to enhance motivation and user experience. By assessing feedback and suggestions for improvements, the findings highlight key design features that may support engagement. While this initial work focused on healthy, age-matched participants, further evidence specifically in children and young people with a childhood cancer diagnosis is needed.
The digital mental health (DMH) industry has grown drastically over the last decade; yet, many DMH products have failed to demonstrate meaningful clinical outcomes, in large part due to lack of scientific evidence. This viewpoint paper highlights an example of how early-stage DMH companies can prioritize science as a strategic advantage. We discuss Moment for Parents, an artificial intelligence-driven maternal mental health app built entirely with support from the National Institutes of Health (NIH) Small Business Innovation Research (SBIR) program. We illustrate the advantages and challenges of building a science-backed product with federal funding. Benefits include credible evidence generation, independence in product development, and enhanced market differentiation. We also discuss the challenges of navigating the SBIR ecosystem, including grant writing and administrative demands, and aligning business objectives with federal research priorities. By showcasing both the promise and complexity of SBIR funding, this viewpoint paper offers actionable insights for founders and chief executive officers who aim to prioritize science in the DMH space.
Greater homework adherence in cognitive behavioral therapy (CBT) is associated with positive treatment outcomes. However, the problems emerging from CBT homework use are common and affect adherence. In recent years, gamification has been explored to increase intervention adherence, but not yet in relation specifically to homework assignments. In this study, the aim was to gain a better understanding of obstacles to CBT homework and the use of gamification to overcome these. Concept mapping, a method to organize related information visually, was used in this study. For the 1-day face-to-face concept mapping session, 7 therapists (32 to 55 y, 6 females) participated and generated items based on 2 focal questions of interest. The generated items were grouped on perceived similarity, and each individual item was rated on (1) severity and difficulty (focal question 1) and (2) importance, acceptance by therapist, and acceptance by patient (focal question 2). The item groups on perceived similarity were inserted into computer software. Based on multidimensional scaling and hierarchical cluster analyses, item clusters were generated by the computer software and were presented to the therapists. The therapists were asked for their preference for the number of items a cluster should contain. Through brainstorming, the therapists collectively generated a list of 29 possible reasons for not doing homework by patients. In the same manner, a list of 38 game design elements that could help patients make CBT homework was generated. External factors (eg, no time due to crisis situations) and lack of motivation (eg, not aspiring to a therapy goal) were perceived as the most important reasons for patients not to do homework. External and symptoms-unrelated internal factors were considered by therapists as the most difficult for patients to change for improved homework adherence. The game design elements, facilitation, and rewards were rated as most important to help patients do homework. These elements were also seen as most accepted by therapists. Facilitation of doing homework and rewards seem to have the potential to tackle some of the external factors and lack of motivation to make CBT homework that patients could have. Conclusions were limited by the small number of participating therapists. Future research is needed on the effects of specific game design elements, the number of these elements, their combinations, and patients' preferences.
The Sustainable Development Goals (SDGs) aim to eradicate poverty and inequality while ensuring that all individuals enjoy good health. Among these, target 3.1 seeks to reduce the global maternal mortality ratio to less than 70 per 100,000 live births. However, progress toward this target has been limited, particularly in low- and middle-income countries (LMICs), where health care delivery remains constrained by limited resources. While digital innovations have increasingly been adopted to improve health care access and service delivery, a significant proportion of populations in LMICs continues to experience inadequate access to essential maternal health services. This gap underscores the need for affordable, sustainable, and contextually appropriate strategies that are cost-effective in improving maternal health outcomes in underserved communities. This study leverages the principles of frugal innovation and information and communication technologies for development (ICT4D) to propose a frugal-oriented ICT4D framework to deliver low-cost digital maternal health solutions in LMIC settings. The framework seeks to optimize the use of available resources, foster equitable access to maternal health care, and contribute toward achieving SDG 3, particularly target 3.1. The study was conducted in both rural and urban-poor settings in Kenya using a 2-phased quantitative approach. In phase 1, eight theoretical themes relevant to maternal health uptake were explored. These themes were represented on color-coded sorting cards, which participants ranked according to perceived importance. Phase 2 involved administering structured survey questionnaires to collect empirical data. The study included a total of 32 participants, whose insights provided a foundation for analyzing the significance of contextual factors influencing maternal health service utilization. The weighted scores for 3 of the 8 predetermined theoretical themes-such as resources, information services, and social support programs-emerged as the most influential factors shaping maternal health promotion (N=32). Resources ranked highest (n=6, 18.81%), followed by information services (n=6, 17.99%), while social support programs accounted for 9.64% (n=3) of the overall influence. These findings highlight critical enablers and barriers within the maternal health care landscape and provide a nuanced understanding of contextual dynamics that affect the uptake of maternal health services. The results informed the design of a frugal-oriented ICT4D framework that prioritizes low-cost digital interventions tailored to resource-limited settings. Despite increasing recognition of digital innovations as tools for health care transformation in LMICs, adoption of existing capital-intensive solutions remains low due to financial and infrastructural constraints. This study emphasizes the importance of adopting frugal innovation and ICT4D principles in designing low-cost, scalable digital health interventions to improve access to maternal health care. Implementing such approaches can address resource limitations, enhance maternal health outcomes, and support progress toward SDG 3, particularly target 3.1. The proposed framework provides a foundation for future research and practical interventions aimed at sustainable, equitable maternal health service delivery in LMIC contexts.
Alzheimer disease (AD) affects cognition, treatment adherence, family connections, and health care resource allocation. Most patients with AD have low adherence to medication therapy due to the limitations associated with cognitive impairment. Therefore, increasing the involvement of patients and their family members in medication management is important to improve treatment outcomes and reduce the burden of care. This study explores the potential application of artificial intelligence (AI) in medication management for Chinese patients with early- to mid-stage AD focusing on enhancing medication adherence. The study first predicts and evaluates key factors through an online Delphi study, which provides a basis for their subsequent incorporation into the AI model as input variables to enable prediction of medication-taking behaviors. Since AI research in medication management for this population is still undeveloped, this paper further explores the multiple potentials of AI from a theoretical view, including drug dosage optimization, multidrug interaction detection, and family education support. It will provide a preliminary direction and theoretical basis for the development of an intelligent medication management system in the future. The exploratory online Delphi study with no modification predicted the key factors influencing medication adherence. Based on the results, the study confirmed the potential of AI to improve adherence. Participation by 12 experts in 3 rounds systematically assessed the core elements influencing patients' adherence to their medication. Family care, social support, environmental factors, emotional support, and patient behaviors were identified as the primary factors influencing medication adherence among Chinese patients with AD. These factors were validated and ranked through iterative Delphi rounds, with family care and social support receiving the highest importance scores. The Wilcoxon signed-rank test indicated no significant difference between rounds (P=.06), supporting the stability of the consensus. These findings establish a foundational set of variables for AI systems that predict and enhance medication adherence. This study highlights the critical factors affecting medication adherence by Chinese patients with AD. It was designed as an exploratory online Delphi study to identify and prioritize key influencing factors, rather than to validate a specific AI-based system, and the findings provide a theoretical foundation for future AI-informed interventions. The results also indicate theoretical potential roles for AI in supporting medication management, such as optimizing drug dosage, detecting multidrug interactions, and enhancing family education.
Speech sound disorders are common in children and are associated with an increased risk of academic reading difficulties. The COVID-19 pandemic further highlighted the need for remote and digitalized assessment tools. In South Korea, standardized instruments such as the Urimal Test of Articulation and Phonation and Assessment of Phonology and Articulation for children are widely used but have limitations, including reliance on face-to-face evaluation, and the absence of automated scoring. This study aimed to develop and establish the content validity of an articulation assessment tool that can overcome these limitations and be integrated into digital therapeutics (DTx). A 3-round modified Delphi survey was conducted between July and September 2025 with 92% (23/25) of the invited experts, including 52.2% (12/23) physiatrists and 47.8% (11/23) speech-language pathologists, with a mean professional experience of 10.69 (SD 5.09) years. All participants (23/23, 100%) completed all rounds. Panelists evaluated the appropriateness of word lists, phonological environments, and scoring criteria. Quantitative analyses, including calculations of content validity ratio (CVR), content validity index (CVI), and median and IQR, were performed. Consensus thresholds were set at a CVR of ≥0.39, a CVI of ≥0.78, a median of ≥3.5, and an IQR of ≤1.0. Items were retained only when all 4 criteria were satisfied. While formal qualitative analysis was not performed, the research team internally reviewed and synthesized core keywords and themes from the experts' open-ended responses to guide the refinement of items. These findings were summarized into four key areas: (1) modernization of word stimuli, (2) expansion of phonological coverage, (3) refinement of scoring criteria to reduce ambiguity, and (4) enhancement of result interpretability through visualization. In round 2, a revised 35-word list was evaluated across 25 items, of which 20 (80%) met all consensus criteria. In total, 20% (5/25) of the items failed to meet at least one threshold, including phonological environment adequacy (CVR=0.48; CVI=0.74), scoring redundancy (CVR=0.13; CVI=0.57), usefulness of proportion of whole-word correctness or percentage of word proximity (CVR=0.39; CVI=0.70), contribution of mean phonological length (CVR=0.22; CVI=0.61), and usefulness of feature-based indexes (CVR=0.30; CVI=0.65; IQR 2). Items that reached consensus showed CVR values of 0.57 to 0.91, CVI values of 0.78 to 0.96, a median score of 4, and IQR values of 0 to 1. In round 3, all remaining items achieved consensus. This Delphi study developed a novel articulation assessment tool with robust content validity. This tool includes updated word stimuli, diverse analysis indexes, and visualization features, thereby enhancing its clinical utility and suitability for integration into artificial intelligence-based DTx. By standardizing and digitalizing articulation assessments, this tool has the potential to support personalized and accessible interventions for children with speech sound disorders.
Youth experiencing early psychosis in West Africa often face delays in accessing evidence-based treatment. Digital mental health interventions may offer an acceptable and scalable approach to improve access to early psychosis care in West Africa; however, few data exist on the experiences and perspectives of patients with early psychosis and their caregivers to inform digital intervention development. This study aims to explore current experiences of early psychosis care, identify barriers and facilitators to in-person early psychosis care within health facilities, and identify opportunities for digital interventions to support patients with early psychosis and caregivers in Ghana. We conducted qualitative focus group discussions among patients with early psychosis, their caregivers, and their mental health care providers recruited at Accra Psychiatric Hospital in Accra, Ghana. Trained qualitative researchers facilitated discussions using a structured qualitative interview guide, exploring current care practices for early psychosis in Ghana, barriers and facilitators to facility-based care, and perceptions of digital mental health interventions. Transcripts were translated, transcribed, and analyzed thematically using a hybrid inductive and deductive approach grounded in the theoretical framework of acceptability. Overall, we conducted 4 focus group discussions (N=31) among 7 patients with early psychosis (median age 28, IQR 21-41 years), 6 caregivers (median age 58, IQR 29-34 years), and 18 clinicians (median age 30, IQR 29-34 years). Participants described current early psychosis care practices in Ghana, including seeking spiritual and traditional healing, the dearth of information and resources about psychosis, and the integral role of caregivers in facilitating treatment engagement and continuation (often at the cost of caregiver mental distress and burnout). Common barriers to facility-based mental health care included stigma associated with mental illness, lack of prior knowledge about early psychosis and treatment options, and practical constraints (eg, financial, logistical, and health care system limitations). Motivating factors for facility-based care included success stories from community members and strong rapport and trust in mental health clinicians. Technology (eg, mobile phones, laptops, radio, and television) was commonly used among participants in typical daily tasks, health information seeking, and stress reduction. Participants expressed support for digital tools that could deliver psychoeducation about early psychosis, support treatment adherence, and extend patient-provider communication between clinic visits. Digital mental health interventions have the potential to complement facility-based early psychosis services in Ghana by addressing misinformation, reducing access barriers, and supporting caregiver roles. These qualitative findings inform potential integration points, content, attributes, and strengths of digital modalities that could be leveraged to support patients with early psychosis and their caregivers in Ghana.
Stress, sleep deprivation, and burnout are significant safety risks for acute care surgeons, negatively impacting performance, well-being, and clinical outcomes. This pilot randomized controlled trial aimed to measure neurophysiological effects of prescribed music (PM) and self-selected music (SSM) on surgeon stress, burnout, and neurophysiological responses using a multimodal protocol that integrated functional magnetic resonance imaging (fMRI), wearable biosensor monitoring, and psychological self-assessments. Full-time attending surgeons at a quaternary care hospital were invited to participate in a 3-armed trial (1:1:1 block allocation). Intervention groups were instructed to listen to 30 minutes (minimum 15 minutes) of either PM or SSM daily at bedtime for 6 weeks, reflecting real-world conditions. PM comprised original compositions based on elements promoting perceived relaxation from a prior study. The control arm avoided music in the 30 minutes before bed. Allocation was concealed from the recruiting investigator; the fMRI technicians, the statistician, and lead investigators were blinded until analyses were completed. Functional connectivity patterns were measured using fMRI at baseline and 6 weeks while participants listened to simulated intensive care unit noise, PM, and SSM. Secondary outcomes included continuous actigraphy for sleep quality and self-reported anxiety, sleep quality, and burnout using validated scales (State-Trait Anxiety Inventory, Pittsburgh Sleep Quality Index, and Maslach Burnout Inventory). A total of 22 surgeons were assessed; demands of fMRI and data collection schedule led 3 to decline and 2 (allocated to PM) not to finish baseline measures; 6 PM, 5 SSM, and 6 controls received allocated intervention; 2 PM participants were withdrawn for nonadherence and missing follow-up data and 1 control missed follow-up collection due to scheduling (final analysis set after missing data: PM: n=4, SSM: n=5, control: n=5). One control participant experienced transient vertigo in fMRI. Trends in fMRI data indicated that both intervention groups experienced less negative emotional arousal and anxiety, with physical tension reduced in the PM group. The PM group exhibited reduced stress response in the frontal lobes when exposed to intensive care unit alarms, suggesting diminished attentional response to the high-stress auditory environment, compared to control. However, lack of statistical significance and baseline variability entail cautious interpretation. Observations of sleep quality were mixed, and no statistically significant differences in stress surveys were observed. Both music interventions trended toward positive changes in neurophysiological responses, suggesting potential benefits in reducing surgeon stress. However, due to the small sample, mixed or nonsignificant results, and the exploratory nature of this study, findings should be considered preliminary. Further research with larger, diverse cohorts is required to confirm trends, refine both the intervention approach and recruitment strategies, and determine whether objective compositional elements or personally selected music drive the mechanisms of potential positive effects. ClinicalTrials.gov NCT05980429; https://clinicaltrials.gov/study/NCT05980429.