JMIR Formative Research

BackgroundPerinatal mood and anxiety disorders are the most common complications of pregnancy. Given the limited mental health resources, there is a need for novel treatment approaches. Though smartphone applications can increase access to evidence-based care, recent research highlights notable limitations, including varying quality and unclear effectiveness. Blended hybrid care models, which integrate synchronous telehealth services with asynchronous modalities (such as mobile apps), have emerged as an alternative. This pilot study evaluates one such model, the Digital Clinic, to determine its potential to bridge this critical treatment gap and compare outcomes to that of non-peripartum patients in the clinic. MethodsPregnant and postpartum women referred for anxiety and depression received 8 weeks of synchronous, virtual, evidence-based CBT from a trained clinician. This treatment was complemented by the asynchronous use of the mindLAMP app, providing digital phenotyping, psychoeducation, and CBT skills, with the support of a Digital Navigator. The efficacy of the intervention was evaluated by comparing GAD-7 and PHQ-9 scores from intake to the end of treatment. ResultsThis secondary analysis included 13 peripartum women from a larger sample of 224 clinic patients. At intake, they reported a mean PHQ-9 score of 9.4 (SD=3.9) and a mean GAD-7 score of 11.69 (SD=6.0). After 8 weeks, participants reported statistically significant decreases of 4.14 points on the GAD-7 (p<.01) and 3.92 points on the PHQ-9 (p<.01). Effect sizes for these reductions were 0.74 (95% CI: 0.20, 1.28) for GAD-7 and 1.10 (95% CI: 0.29, 1.90) for PHQ-9. ConclusionA novel blended hybrid care model, the Digital Clinic, was successful in reducing depression and anxiety among pregnant and postpartum women. This novel approach to maternal mental health shows promise for delivering accessible, effective, evidence-based care to peripartum patients in real-world settings. Future work should further validate its effectiveness with larger, more diverse patient populations with moderate to severe disease.

ObjectivesA majority of patients suffering from acute COVID-19 are expected to recover symptomatically and functionally. However there are reports that some people continue to experience symptoms even beyond the stage of acute infection. This phenomenon has been called longcovid. Study designThis study attempted to analyse symptoms reported by users on twitter self-identifying as longcovid. MethodsThe search was carried out using the twitter public streaming application programming interface using a relevant search term. ResultsWe could identify 89 users with usable data in the tweets posted by them. A majority of users described multiple symptoms the most common of which were fatigue, shortness of breath, pain and brainfog/concentration difficulties. The most common course of symptoms was episodic. ConclusionsGiven the public health importance of this issue, the study suggests that there is a need to better study post acute-COVID symptoms.

BackgroundHealthcare providers can use these virtual platforms for delivering medical advice and prescriptions of medications to patients. This study was aimed to explore the patients experiences and level of satisfaction regarding virtual health care received during the COVID-19 pandemic. This study also assessed the before and during lockdown sleep quality in these participants. Design and MethodsThe current study included 522 participants from Saudi Arabia. Virtual healthcare satisfaction questionnaire was implemented to record the data on patient experience toward the virtual health care during COVID-19 pandemic. ResultsPatients opinions regarding virtual health care received during the COVID-19 pandemic era are summarized using the "five-point Likert scale". The mean score of all the five statements is 4.15, reflecting 83% level of satisfaction of participants towards virtual health care. Among participants, mostly agreed that they were able to communicate adequately with doctors, the picture and sound quality of the virtual appointment were good, their privacy was respected during the consultation, they were comfortable during history taking and exams that were done, and the doctor explained solutions including prescribing medicine and/or providing advice. However, there was no significant association found between the type of specialty attended or patient demographic factors and level of satisfaction. Results of subjective sleep parameters assessed before and during lock down are depicted. Results of t-test showed that the mean scores of all the components namely sleep duration (P<0.001); sleep disturbances (P<0.001), sleep latency (P<0.001), daytime dysfunction (P<0.001), habitual sleep efficiency (P<0.001), and subjective sleep quality (P<0.001) significantly differed between two assessment levels. Mean scores of all the components shifted towards higher values, representing worsening of sleep quality during the COVID-19 pandemic lock down. ConclusionsFindings support and conclude that virtual health care system can be adopted in clinical settings.

Smartphones are now commonly used, for virtual outpatient consultations, to help reduce disease transmission during the COVID-19 pandemic. Nosocomial spread of COVID 19 and hospital acquired infections are usually from staff or students to patients. Reducing non- essential staff numbers on ward rounds may reduce the risk. We describe the novel use of smartphones, with Microsoft Teams, to live stream inpatient interactions, radiological images, pathology results, charts and patient review between an office-based and ward team (virtual ward round) and for teaching medical students in secondary care. After Research and Ethics, Digital services and Information Governance approval we compared a smartphone and head-worn device (Realwear HMT-1). Data collection was by participant questionnaire. Statistical analysis was performed using the Mann - Whitney test. There was no statistically significant difference in audio and video feed quality between the smart phone (p value = 0.3) and Realwear device (p value = 0.41). However the smartphone was preferred during ward rounds and was 85% cheaper than the Realwear device. Urology medical staff numbers on the ward were reduced by 50%. Ward round efficiency improved as administrative tasks could be performed by the office team during the virtual ward round. Virtual ward rounds using smartphones can facilitate remote communication between staff, students and patients. Staff in isolation or shielding can also assist front line colleagues from home. Smarter use of the smart phone may help reduce staff numbers on wards and reduce the number COVID-19 and nosocomial infections, potentially reducing morbidity and mortality locally and globally.

BackgroundNowadays, social media video-sharing website YouTube is globally accessible and used for sharing news and information. It also serves as a tool for migraine sufferers seeking guidance about Daith piercing as a potential migraine treatment; however, shared and disseminated video content is rarely regulated and does not follow evidence-based medicine. ObjectiveTo investigate the content, quality, and reliability of YouTube videos on Daith piercing for the treatment of migraine. MethodsYouTube videos were systematically searched from the video portal inception until 17th January 2024. "Daith piercing" AND "migraine" were the applied search terms. All video blogs reporting on Daith piercing for the treatment of migraine were included. The primary outcome of interest was assessing the Global Quality Scale and DISCERN implementing the five-point Likert scale ("very poor" to "excellent") to evaluate each video blogs quality, flow, and reliability. Secondary outcomes included the relapse time of migraine after Daith piercing, and further outcomes related to Daith piercing. This systematic video analysis was preregistered in PROSPERO (https://www.crd.york.ac.uk/prospero/ CRD42024510089). ResultsOut of 496 initially screened video recordings, 246 videos were included in the final analysis (N=69 categorized as Personal Experience; N=176 as Others, defined as videos from bloogers, piercers or other persons not affected by migraine; and N=1 as Healthcare Professionals). Overall, these videos collectively gathered 67783 likes and received 4.68 million views. The Global Quality Scale rating in the category Personal Experience revealed that the quality of 50.7% of videos was very poor; 29.0% poor; 11.6% moderate and 8.7% good. In the category Others, Global Quality Scale rating showed that the quality of 60.8% of videos was very poor; 25.6% poor; 11.9% moderate and 1.7% good (P<0.05 compared to the proportion of good quality videos in the category Personal Experience quality). The one video in the category Healthcare Professionals was rated "poor quality". Ratings applying the DISCERN tool were comparable. Overall, 111 (45.1%) videos recommended and 14 (5.7%) discouraged Daith piercing for migraine relief. ConclusionBased on the Global Quality Scale and DISCERN scores, the information, usefulness, and accuracy of most YouTube content on Daith Piercing for migraine treatment are generally of poor quality and reliability. The lack of high-quality and reliable videos might expose users to potentially misleading information and the dissemination of unproven medical interventions. Plain Language SummaryThis systematic video analysis evaluated the quality and reliability of 246 YouTube videos on Daith piercing as a migraine treatment, accessing the DISCERN instrument and the Global Quality Scale tool. The analysis revealed that most videos were anecdotal, lacked input from healthcare professionals, and demonstrated poor quality and reliability. These findings highlight that YouTube is not a reliable source for medical information on Daith piercing for migraine treatment, underscoring the importance of consulting physicians and referencing peer-reviewed research for well-informed decision-making.

BackgroundFibromyalgia (FM) is a complex, chronic condition characterized by widespread musculoskeletal pain, cognitive dysfunction, fatigue, and emotional comorbidities such as anxiety and depression. These symptoms severely impact daily functioning and quality of life. Although non-pharmacological strategies--such as therapeutic exercise and patient education--are recommended as first-line treatments, their implementation outside the clinical setting remains a challenge due to low adherence and lack of continuity. ObjectiveTo evaluate the effectiveness of a digital health intervention--BEI app--as a complement to usual care in improving clinical and functional outcomes among patients with fibromyalgia. MethodsThis is a randomized controlled trial (RCT) with two parallel arms (1:1 allocation). A total of 70 adult participants with fibromyalgia (diagnosed per ACR 2016 criteria) will be recruited through a patient association in Madrid, Spain. The control group will receive 12 weeks of standard, in-person treatment consisting of group-based education and physical activity. The experimental group will receive the same in- person program plus daily access to the BEI mobile application, which includes educational modules, physical and cognitive training, symptom tracking, and personalized feedback. Outcomes will be assessed at baseline, week 6 (mid- intervention), week 12 (post-intervention), and week 24 (follow-up). Primary outcomes include pain intensity (VAS) and functional impact (FIQR). Secondary outcomes include catastrophizing, self-efficacy, cognitive function, physical activity, anxiety, depression, quality of life, app engagement, and satisfaction. Expected resultsThe results of this trial will provide evidence regarding the potential of mHealth tools to enhance adherence, self-efficacy, and functional outcomes in individuals with fibromyalgia. Trial registrationNCT07090434 (ClinicalTrials.gov)

BackgroundSmartphones and their increasing capabilities have helped humans to communicate and perform many tasks and it leads to a form of dependency, and it may have negative effects on everyone, especially students. ObjectivesTo assess smartphone addiction and its relationship to academic performance among medical students at King Saud University, Kingdom of Saudi Arabia. MethodsAn observational cross-sectional study was conducted from July to September 2022 including students of the College of Medicine at King Saud University, Kingdom of Saudi Arabia. The data collection tool was structured and utilized an electronic survey. ResultsA total of 330 participants answered the study questionnaire. The most common age range of study participants was 18-28 years with 64.2% of the study sample. Male participants represented 63%. The study income is less than 5000 riyals 54.5% per month. Majority of ftudents (65%) believe that using smartphones them to study more efficiently. Analysis of the study results shows that there is a statistically significant correlation between phone addiction and a decrease in the academic performance of college students. ConclusionOur study found that there is a significant correlation between phone addiction and a drop in academic performance. Despite its attractiveness, smartphone addiction is a time waster for students that might disrupts their sleep and causes stress. It is, therefore, necessary to create a comprehensive plan that directs the students towards balanced use.

There is a growing interest to investigate the feasibility of using voice user interfaces as a platform for digital therapeutics in chronic disease management. While mostly deployed as smartphone applications, some demographics struggle when using touch screens and often cannot complete tasks independently. This research aimed to evaluate how heart failure patients interacted with a voice app version of an already existing digital therapeutic, Medly, using a mixed-methods concurrent triangulation approach. The objective was to determine the acceptability and feasibility of the voice app by better understanding who this platform is be best suited for. Quantitative data included engagement levels and accuracy rates. Participants (n=20) used the voice app over a four week period and completed questionnaires and semi-structured interviews relating to acceptability, ease of use, and workload. The average engagement level was 73%, with a 14% decline between week one and four. The difference in engagement levels between the oldest and youngest demographic was the most significant, 84% and 43% respectively. The Medly voice app had an overall accuracy rate of 97.8% and was successful in sending data to the clinic. Users were accepting of the technology (ranking it in the 80th percentile) and felt it did not require a lot of work (2.1 on a 7-point Likert scale). However, 13% of users were less inclined to use the voice app at the end of the study. The following themes and subthemes emerged: (1) feasibility of clinical integration: user adaptation to voice apps conversational style, device unreliability, and (2) voice app acceptability: good device integration within household, users blamed themselves for voice app problems, and voice app missing desirable user features. The voice app proved to be most beneficial to those who: are older, have flexible schedules, are confident with using technology, and are experiencing other medical conditions.

IntroductionThe capacity to deliver essential health services has been negatively impacted by the COVID-19 pandemic particularly due to lockdown restrictions. Telemedicine provides a safe, efficient, and effective solution that addresses the needs of patients and the health system. However, there remain implementation challenges and barriers to patient adoption in resource-limited settings as in the Philippines. This study thus aimed to describe patient perspectives and experiences with telemedicine services, and explore the factors that influence telemedicine use and satisfaction. MethodsThis study used a mixed-methods design through online surveys and in-depth interviews. An online survey using Consumer Assessment of Healthcare Providers and Systems (CAHPS) Clinician & Group Adult Visit Survey 4.0 (beta) and Telehealth Usability Questionnaire (TUQ) was accomplished by 200 participants aged 18 to 65 years. A subsample of 16 participants was interviewed to provide insights to the quantitative data. We used descriptive statistics to analyze survey data and grounded theory to analyze data from interviews. ResultsParticipants were generally satisfied with telemedicine services, with most reporting that this was an efficient and convenient alternative to face-to-face consultations. However, only 2 in 5 perceived telemedicine as affordable. Our quantitative findings suggest that participants preferred telemedicine services rather than in-person consultations, especially in cases where they feel that their condition is not urgent and does not need extensive physical examination. Safety against COVID-19, and the availability of multiple communication platforms contributed to patient satisfaction with telemedicine. Negative perceptions of patients on their telemedicine provider, perceived higher costs, poor connectivity and other technological issues were found to be barriers to patient satisfaction. DiscussionTelemedicine is viewed as a safe and efficient alternative to receiving care. Continued adoption of telemedicine will require improvements in technology and better patient communication related to their telemedicine provider and the associated costs.

BackgroundIn recent years, Instagram has become the most popular tool among professional doctors in Azerbaijan for educating their patients. The use of the Instagram application aims to raise patients awareness of the importance of taking care of their health and to increase their knowledge about their health conditions using modern services. In this article, the authors examine the quality of Instagram content for health education among the population. MethodsWe conducted a survey to collect anonymous data from more than 205 respondents and summarized the following points. Results65% of the respondents were already obtaining health information from Instagram before to participating in the study. 15.1 % of them frequently visit Instagram for health information while 5% had found the health information accessed there harmful. 71% of respondents think accessing health information in this way is beneficial but that the quality and usefulness of the content is average. 95% of respondents reported that the health information they obtained from the identical platform was not causing them any harm ConclusionThe medical information shared on Instagram is generally considered useful and beneficial by the population, but it is desirable to improve the quality of the content.

IntroductionEmojis have surpassed facial expressions and they are now widely used to deliver complex concepts by representing graphical expressions in the digital platform. In this study, we endeavored to develop medical emojis for clinical signs and symptoms to be used as tools for text-based counselling. MethodsThe present study was conducted using the Delphi method with medical studnets and general practitioners, drawing and discussing in several repeated rounds. For this purpose, about 100 clinical signs/symptoms were considered using the ICD-10 website. ResultsIn the present study, from one hundred signs and symptoms we reached to 85 signs/symptoms that after first round of sessions were illustrated. Out of these 85 eligible emojis, 4 cases were removed due to the lack of consensus. The rest of the emojis were finalized and prepared by the graphic designer. These emojis then were published online to collect online votes. ConclusionIn this study, we could design up to 81 medical emojis presenting clinical sign and symptoms with acceptable consensus between the participants. These emojis were reasonably acceptable by our panelists in presenting the established clinical concepts.

Post Covid-19 condition (PCC), long COVID-19 syndrome and post-acute sequelae of SARS-CoV-2 (PASC) all refer to a constellation of symptoms that are unresolved long after the acute phase of the viral infection. The severity of symptoms can vary from mild and tolerable to severe and debilitating.1,2 Due to the evolving nature of the SARS-CoV-2 pandemic, treatment protocols for the illness are in a constant state of evolution. The early stage of long COVID-19 syndrome contributes to a dearth of treatment protocols based on empirical evidence, while the absence of a conclusive pathophysiological understanding further complicates the development of such protocols. Current treatment regimens include homeopathic medicine, specialist system focused treatments, infusion therapies, hyperbaric oxygenation, and polypharmacy. The physiological, psychological, and societal impact of long COVID-19 cannot be approached casually and must govern the intensity with which the healthcare community approaches treatment of long COVID-19 syndrome. In this 41-patient cohort study from a chronic pain management practice, the use of either unilateral or bilateral stellate ganglion block (SGB) was explored to manage symptoms associated with long COVID-19 syndrome. Results indicated that a substantial proportion of patients (86%) experienced a reduction of their symptoms following SGB treatment.

This study represents a practical advancement in the application of vocal biomarkers for mental health tracking in real-world settings. Through a prospective cohort study involving 104 participants from an outpatient psychiatric population, we introduced a novel "Mental Fitness Vocal Biomarker" (MFVB) score, derived from eight preselected vocal features supported by literature review. Our findings demonstrate the MFVBs efficacy in objectively stratifying individuals based on risk for elevated mental health symptom severity using the M3 Checklist for transdiagnostic assessment (depression, anxiety, post-traumatic stress disorder, and bipolar) as reference standard. Continuous observation over time significantly improves efficacy, yielding a risk ratio of 1.53 (1.09-2.14, p=0.0138) for single 30-second voice samples to 2.00 (1.21-3.30, p=0.0068) for 2-week aggregations, depending on MFVB score. Notably, in the highly engaged subgroup (5-6 MFVB uses per week, 38% of participants), a risk ratio of 8.50 (2.31-31.25, p=0.0013) was observed, underscoring the utility of frequent and continuous observation. Participant feedback confirmed the user-friendliness of the application and perceived benefits, highlighting the MFVBs potential as a cost-effective, scalable, and privacy-preserving adjunct to traditional psychiatric assessments. These results establish that vocal biomarkers are a promising tool for objective mental health tracking in real-world conditions, offering personalized insights into users mental well-being as they engage with clinical therapy or other beneficial activities that are associated with improved mental health risks and outcomes.

BackgroundApproximately 19% of adults in Europe are affected by chronic pain, which reduces quality of life. Pain management apps (mHealth) offer a promising solution for self-management, but users engagement and adherence can be a limitation to their clinical impact. User experience design and studies play an important role in optimizing usability and long-term adoption of digital health interventions. ObjectiveThis study aims to evaluate the user experience of Dolodoc, a mobile application for chronic pain self-management, using a mixed-methods approach that evaluates acceptability through a content quality survey and examines usability by analyzing overall usage patterns. MethodsA cross-sectional acceptability study was conducted among chronic pain patients recruited from the Geneva University Hospitals pain center and through snowball sampling. Participants rated 84 evidence-based self-management strategies using a five-point Likert scale based on 5 acceptability criterias: understandability, motivation, feasibility, relevance, and alignment with the related quality-of-life dimension. Usability was assessed through usage metrics that were collected over six months using Piwik PRO analytics to observe the usage behaviors of real-world Dolodoc users. ResultsIn the acceptability study, a total of 33 participants rated the self-management strategies positively across all dimensions. On a scale from -2 to 2, the strategies were well understood (mean = 1,47), motivational (1.12), feasible(1.01), relevant (0.99), and aligned with the dimensions (1.33). The usability study demonstrated that 60% of patients used Dolodoc only once, indicating that long-term adherence remains a challenge. Within Dolodoc, pain tracking, useful links and medication logging were the most actively used features. DiscussionThis study highlights the gap between acceptability and long-term adherence to mHealth solutions. Improving personalization and accessibility could increase user engagement and long-term adherence. Future iterations of the app should incorporate tailored interventions and real-time feedback mechanisms. In addition, taking advantage of a digital navigation follow-up could facilitate user adoption and sustained engagement.

ObjectiveChatGPT is the first large language model (LLM) to reach a large, mainstream audience. Its rapid adoption and exploration by the population at large has sparked a wide range of discussions regarding its acceptable and optimal integration in different areas. In a hybrid (virtual and in-person) panel discussion event, we examined various perspectives regarding the use of ChatGPT in education, research, and healthcare. Materials and MethodsWe surveyed in-person and online attendees using an audience interaction platform (Slido). We quantitatively analyzed received responses on questions about the use of ChatGPT in various contexts. We compared pairwise categorical groups with Fishers Exact. Furthermore, we used qualitative methods to analyze and code discussions. ResultsWe received 420 responses from an estimated 844 participants (response rate 49.7%). Only 40% of the audience had tried ChatGPT. More trainees had tried ChatGPT compared with faculty. Those who had used ChatGPT were more interested in using it in a wider range of contexts going forwards. Of the three discussed contexts, the greatest uncertainty was shown about using ChatGPT in education. Pros and cons were raised during discussion for the use of this technology in education, research, and healthcare. DiscussionThere was a range of perspectives around the uses of ChatGPT in education, research, and healthcare, with still much uncertainty around its acceptability and optimal uses. There were different perspectives from respondents of different roles (trainee vs faculty vs staff). More discussion is needed to explore perceptions around the use of LLMs such as ChatGPT in vital sectors such as education, healthcare and research. Given involved risks and unforeseen challenges, taking a thoughtful and measured approach in adoption would reduce the likelihood of harm.

BackgroundNomophobia, characterised by the dread or anxiety of being without access to a mobile phone, has become an increasing behavioural issue among young adults, especially university students. Excessive reliance on smartphones has been linked to psychological suffering, impaired everyday functioning, and negative academic results. Nonetheless, information about the prevalence and determinants of nomophobia among university students in Bangladesh is scarce. This study aimed to evaluate the prevalence of nomophobia and investigate its associated sociodemographic traits and smartphone-related behaviors among medical and university students in Bangladesh. Materials and MethodsA cross-sectional study was performed with 476 undergraduate medical and non-medical students from eight districts of Bangladesh from September 2023 to July 2025, using an online structured questionnaire. Nomophobia was evaluated via the validated Nomophobia Questionnaire (NMP-Q). The questionnaire was pilot-tested (n=60) and showed good reliability (Cronbachs =0.82). Information on socio-demographics, mobile phone usage trends, and application preferences was collected. Data was processed using STATA version 16. Descriptive statistics, t-tests, ANOVA, Pearson correlation, and multiple linear regression analyses were used to ascertain factors related to nomophobia. ResultsThe average age of participants was 20.70 {+/-} 1.52 years. 46.79% of students exhibited moderate nomophobia, whereas 25.69% had severe nomophobia. Elevated nomophobia scores were strongly correlated with female gender, moderate household income, usage of social media and communication applications, prolonged daily mobile phone usage (>7 hours), frequent phone checking, and instant phone checking upon awakening. Multiple linear regression indicated that extended phone usage, engagement with social communication applications, middle-income position, and early-morning phone checking are independent predictors of elevated nomophobia scores. ConclusionNomophobia is significantly common among university students in Bangladesh. Behavioural patterns such as prolonged daily smartphone use, frequent phone checking, immediate phone use upon waking, and extensive engagement with social communication and media applications are associated with excessive smartphone usage and development of nomophobia. These findings underscore the necessity for awareness initiatives, early detection, and focused interventions to alleviate the adverse psychological and behavioural effects of nomophobia in students.

Maternal mental health remains a critical yet underrecognized public health concern in Nigeria, with postpartum depression (PPD) and maternal suicide emerging as significant challenges due to limited access to mental healthcare services, stigma, and systemic barriers. This study explores the potential of digital health solutions such as mobile applications, teletherapy, AI-driven mental health chatbots, and SMS-based interventions in addressing postpartum mental health disorders among Nigerian mothers. Using a quantitative survey of 200 postpartum women, the research examines the effectiveness, accessibility, and challenges associated with digital mental health interventions.

BackgroundMobile health (mHealth) is reshaping healthcare delivery, especially in HIV management. The World Health Organization advocates for mHealth to provide healthcare workers (HCWs) with real-time data, enhancing patient care. However, in Malawis Lighthouse Trust antiretroviral therapy (ART) clinic, the nurse-led community-based ART (NCAP) program faces hurdles with data management due to lack of access to electronic medical records systems (EMRS) in the community setting. EMRS is not typically available in differentiated service delivery settings where reliable power and internet are often unavailable. We used human-centered design (HCD) processes to create a mobile EMRS prototype, the Community-based ART Retention and Suppression (CARES) app. We explore progress to simplify workflow for HCWs and improve client care. MethodsTo evaluate the CARES apps feasibility and acceptability among NCAP HCWs, we conducted in-depth interviews among 15 NCAP HCWs. We used a rapid qualitative analysis approach guided by the extended Technology Acceptance Model. The study complied with the Consolidated Criteria for Reporting Qualitative Research (COREQ). ResultsAs a likely result of HCD, HCWs demonstrated high expectations for the CARES app to improve healthcare delivery and data management. However, challenges such as app performance, data integration, and system navigation were significant barriers to acceptance or feasibility. Despite challenges, HCWs remained optimistic about the potential for CARES to enhance NCAP clinical decision-making and data flow. HCWs emphasized the need for continuous training and stakeholder engagement, improved infrastructure, data security protections, and establishing the CARES app and EMRS integration to facilitate CARES long-term success at scale. ConclusionThe studys findings underscore the importance of HCD for mHealth buy-in. As HCWs were invested in CARES success, they remained optimistic that the app could enhance NCAP services if user experience and app performance improved. Incorporation of HCW feedback would help deliver beyond the promise of CARES.

BackgroundHealthcare provider burnout is a critical issue with significant implications for individual well-being, patient care, and healthcare system efficiency. Addressing burnout is essential for improving both provider well-being and the quality of patient care. Ambient artificial intelligence (AI) offers a novel approach to mitigating burnout by reducing the documentation burden through advanced speech recognition and natural language processing technologies that summarize the patient encounter into a clinical note to be reviewed by clinicians. ObjectiveTo assess provider burnout and professional fulfilment associated with Ambient AI technology during a pilot study, assessed using the Stanford Professional Fulfillment Index (PFI). MethodsA pre-post observational study was conducted at University of Iowa Health Care with 38 volunteer physicians and advanced practice providers. Participants used a commercial ambient AI tool, over a 5-week trial in ambulatory environments. The AI tool transcribed patient-clinician conversations and generated preliminary clinical notes for review and entry into the electronic medical record. Burnout and professional fulfillment were assessed using the Stanford PFI at baseline and post-intervention. ResultsPre-test and post-test surveys were completed by 35/38 participants (92% survey completion rate). Results showed a significant reduction in burnout scores, with the median burnout score improving from 4.16 to 3.16 (p=0.005), with validated Stanford PFI cutoff for overall burnout 3.33. Burnout rates decreased from 69% to 43%. There was a notable improvement in interpersonal disengagement scores (3.6 vs. 2.5, p<0.001), although work exhaustion scores did not significantly change. Professional fulfillment showed a modest, non-significant increase (6.1 vs. 6.5, p=0.10). ConclusionsAmbient AI significantly reduces healthcare provider burnout and modestly enhances professional fulfillment. By alleviating documentation burdens, ambient AI improves operational efficiency and provider well-being. These findings suggest that broader implementation of ambient AI could be a strategic intervention to combat burnout in healthcare settings.

BackgroundThe demand on mental health services is rapidly increasing, outpacing the capacity of traditional treatment systems like the NHS. Digital interventions offer a scalable means of addressing this gap, but real-world evidence of their impact on service utilisation is limited. AimsThis study examines whether use of the Mindstep platform, a digital mental health tool offering assessments and video-based self-guided support, is associated with reduced intended use of clinical services and user-perceived usefulness. MethodsA retrospective observational study was conducted using user survey data (N = 254) from individuals with at least 30 days of Mindstep exposure. Participants reported past-year healthcare use, rated the perceived usefulness of Mindstep, and estimated their future clinical service use both with and without Mindstep access. The primary outcome was changes in intended use of public and private clinical services; the secondary outcome was perceived usefulness. ResultsMindstep use was associated with a 58.1% average reduction in intended clinical service use across all categories, with the largest reductions for private consultants and GPs. Users with low prior healthcare engagement reported the greatest reductions, while those with high prior usage rated Mindstep as most useful (mean usefulness score = 0.40 on a 0-1 scale). ConclusionsEngagement with the Mindstep platform was associated with substantial reductions in intended clinical service use and moderate perceived usefulness, particularly among underserved and high-need user groups. While intention may not directly translate to behaviour, these findings suggest that digital mental health platforms may play an important role in alleviating demand on healthcare systems and improving access to early support.