Nevin Manimala

J Particip Med. 2025 May 26;17:e65046. doi: 10.2196/65046.

ABSTRACT

BACKGROUND: The Pancreatic Cancer Action Network (PanCAN) established its Patient Registry to gather real-world data from patients with pancreatic cancer and their caregivers, related to their diagnosis, symptoms and symptom management, treatments, and more. Results from version 2 of the PanCAN Registry are presented here.

OBJECTIVE: We sought to gather and evaluate patient-reported outcomes data inputted into the PanCAN Patient Registry from December 2020 to January 2024. Statistical analyses were used to identify findings from a relatively small sample size (271 participants, as defined by people who filled out the Basics survey of the PanCAN Registry).

METHODS: Participation in the PanCAN Patient Registry was voluntary, and participants filled out an electronic consent form before joining the registry. Participants were identified through the PanCAN Patient Services Help Line or navigated to the registry directly via the PanCAN website. Data analysis took place via bivariate analysis using the chi-square test for categorical variables. Statistical significance was defined as a P value of <.05, with P values between .05 and .1 considered marginally significant, and P values >.1 considered insignificant.

RESULTS: Pain was reported by 186 out of the 207 (89.9%) PanCAN Patient Registry participants who filled out the pain-related questions in the General Assessment survey. We observed a marginally significant (P=.06) difference between the reporting of pain by patients aged younger than 65 years (86/92, 93.5%) and those aged 65 years or older (66/78, 84.6%). Depression was also a common condition experienced by patients with pancreatic cancer, with 64/103 (62.1%) indicating that they were experiencing or had experienced depression during the course of their illness. A trend suggested that depression was more frequently reported among the subset of patients who also reported pain (53/80, 66.3%) compared with those who did not report pain (5/13, 38.5%; P=.07).

CONCLUSIONS: The use of patient-reported outcomes and real-world data for patients with pancreatic cancer has the potential to have direct impact on clinical practice. Through a relatively small sampling of patients, trends were identified that suggest a higher reporting of pain amongst patients in a younger age group as well as concurrence of pain and depression. These findings underscore the importance of a multidisciplinary team of health care professionals addressing patients’ needs beyond the treatment of their cancer.

PMID:40418805 | DOI:10.2196/65046

JMIR Hum Factors. 2025 May 26;12:e59363. doi: 10.2196/59363.

ABSTRACT

BACKGROUND: Web-based health courses providing lifestyle-related information can potentially increase knowledge, facilitate behavior change, and improve health outcomes for people living with multiple sclerosis (MS). Despite the low engagement with web-based programs by this population, few studies have evaluated factors influencing engagement. This study evaluated engagement with our 6-week lifestyle-related course (Multiple Sclerosis Online Course; MSOC) by participants enrolled in a large, international randomized controlled trial, as well as preliminary outcomes.

OBJECTIVE: This study aimed to quantitatively assess engagement with the MSOC (the intervention course [IC] and standard-care course [SCC]), motivators of and barriers to participants’ course completion, course satisfaction, engagement with the community forum, and intentions to implement lifestyle changes.

METHODS: We collected data via a baseline survey before course commencement and an evaluation survey 1 month after the 6-week course. Course completers were queried on motivators of completion, course satisfaction, previous knowledge, forum participation, and intentions to adopt lifestyle changes. Noncompleters were queried on barriers to course completion. Differences between the 2 study arms were examined using chi-square and 2-tailed t tests. Multivariable linear regression models assessed factors (sociodemographic and course and health related) associated with participants’ intentions to adopt lifestyle changes adjusting for baseline lifestyle factors. Moderation analyses were conducted to test group differences.

RESULTS: Of the 857 participants, 442 (51.6%) completed the MSOC (IC: n=218, 49.3%; SCC: n=224, 50.7%), and 291 (34%) completed the evaluation survey (n=254, 87.3% course completers; n=37, 12.7% noncompleters). Key motivators of course completion included an interest in participating in MS research, optimizing health, course flexibility, and relevant and useful course content. Barriers to course completion included time constraints and technical issues. Most course completers rated the MSOC as “excellent/very good” (IC: 92/126, 73%; SCC: 78/128, 60.9%; P=.17). Engagement with the facilitator-led community forum was higher in the IC than in the SCC (56/126, 44.4% vs 32/128, 25%; P=.003). More IC completers versus SCC completers expressed their intention to adopt dietary changes (89/125, 71.2% vs 74/127, 58.3%; P=.04), increase their sun exposure (82/124, 66.1% vs 62/124, 50%; P=.01), supplement with omega-3 (84/125, 67.2% vs 60/126, 47.6%; P=.004), and practice meditation (85/124, 68.5% vs 66/126, 52.4%; P=.009). Forum engagement, course satisfaction, new course content, and an interest in receiving additional course content were associated with intentions to adopt lifestyle changes across both study arms.

CONCLUSIONS: The web-based lifestyle IC provided new and satisfactory content and facilitated intentions to adopt lifestyle changes. Positive associations between engagement with the community forum and intentions to implement lifestyle changes and identifying barriers to completion such as time constraints provide important insights to inform the design of future digital health interventions for people living with MS and possibly other chronic conditions.

TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12621001605886; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382778&isReview=true.

PMID:40418803 | DOI:10.2196/59363

JMIR Hum Factors. 2025 May 26;12:e72867. doi: 10.2196/72867.

ABSTRACT

BACKGROUND: Generative artificial intelligence (AI)-particularly large language models (LLMs)-has generated unprecedented interest in applications ranging from everyday questions and answers to health-related inquiries. However, little is known about how everyday users decide whether to trust and adopt these technologies in high-stakes contexts such as personal health.

OBJECTIVES: This study examines how ease of use, perceived usefulness, and risk perception interact to shape user trust in and intentions to adopt DeepSeek, an emerging LLM-based platform, for health care purposes.

METHODS: We adapted survey items from validated technology acceptance scales to assess user perception of DeepSeek. A 12-item Likert scale questionnaire was developed and pilot-tested (n=20). It was then distributed on the web to users in India, the United Kingdom, and the United States who had used DeepSeek within the past 2 weeks. Data analysis involved descriptive frequency assessments and Partial Least Squares Structural Equation Modeling. The model assessed direct and indirect effects, including potential quadratic relationships.

RESULTS: A total of 556 complete responses were collected, with respondents almost evenly split across India (n=184), the United Kingdom (n=185), and the United States (n=187). Regarding AI in health care, when asked whether they were comfortable with their health care provider using AI tools, 59.3% (n=330) were fine with AI use provided their doctor verified its output, and 31.5% (n=175) were enthusiastic about its use without conditions. DeepSeek was used primarily for academic and educational purposes, 50.7% (n=282) used DeepSeek as a search engine, and 47.7% (n=265) used it for health-related queries. When asked about their intent to adopt DeepSeek over other LLMs such as ChatGPT, 52.1% (n=290) were likely to switch, and 28.9% (n=161) were very likely to do so. The study revealed that trust plays a pivotal mediating role; ease of use exerts a significant indirect impact on usage intentions through trust. At the same time, perceived usefulness contributes to trust development and direct adoption. By contrast, risk perception negatively affects usage intent, emphasizing the importance of robust data governance and transparency. Significant nonlinear paths were observed for ease of use and risk, indicating threshold or plateau effects.

CONCLUSIONS: Users are receptive to DeepSeek when it is easy to use, useful, and trustworthy. The model highlights trust as a mediator and shows nonlinear dynamics shaping AI-driven health care tool adoption. Expanding the model with mediators such as privacy and cultural differences could provide deeper insights. Longitudinal experimental designs could establish causality. Further investigation into threshold and plateau phenomena could refine our understanding of user perceptions as they become more familiar with AI-driven health care tools.

PMID:40418796 | DOI:10.2196/72867

JMIR Med Educ. 2025 May 26;11:e65220. doi: 10.2196/65220.

ABSTRACT

BACKGROUND: Artificial intelligence (AI) systems are becoming increasingly relevant in everyday clinical practice, with Food and Drug Administration-approved AI solutions now available in many specialties. This development has far-reaching implications for doctors and the future medical profession, highlighting the need for both practicing physicians and medical students to acquire the knowledge, skills, and attitudes necessary to effectively use and evaluate these technologies. Currently, however, there is limited experience with AI-focused curricular training and continuing education.

OBJECTIVE: This paper first introduces a novel blended learning curriculum including one module on AI for medical students in Germany. Second, this paper presents findings from a qualitative postcourse evaluation of students’ knowledge and attitudes toward AI and their overall perception of the course.

METHODS: Clinical-year medical students can attend a 5-day elective course called “Medicine in the Digital Age,” which includes one dedicated AI module alongside 4 others on digital doctor-patient communication; digital health applications and smart devices; telemedicine; and virtual/augmented reality and robotics. After course completion, participants were interviewed in semistructured small group interviews. The interview guide was developed deductively from existing evidence and research questions compiled by our group. A subset of interview questions focused on students’ knowledge, skills, and attitudes regarding medical AI, and their overall course assessment. Responses were analyzed using Mayring’s qualitative content analysis. This paper reports on the subset of students’ statements about their perception and attitudes toward AI and the elective’s general evaluation.

RESULTS: We conducted a total of 18 group interviews, in which all 35 (100%) participants (female=11, male=24) from 3 consecutive course runs participated. This produced a total of 214 statements on AI, which were assigned to the 3 main categories “Areas of Application,” “Future Work,” and “Critical Reflection.” The findings indicate that students have a nuanced and differentiated understanding of AI. Additionally, 610 statements concerned the elective’s overall assessment, demonstrating great learning benefits and high levels of acceptance of the teaching concept. All 35 students would recommend the elective to peers.

CONCLUSIONS: The evaluation demonstrated that the AI module effectively generates competences regarding AI technology, fosters a critical perspective, and prepares medical students to engage with the technology in a differentiated manner. The curriculum is feasible, beneficial, and highly accepted among students, suggesting it could serve as a teaching model for other medical institutions. Given the growing number and impact of medical AI applications, there is a pressing need for more AI-focused curricula and further research on their educational impact.

PMID:40418795 | DOI:10.2196/65220

J Med Internet Res. 2025 May 26;27:e64581. doi: 10.2196/64581.

ABSTRACT

BACKGROUND: Mental health issues have emerged as a global challenge, particularly affecting middle-aged and older adults. Research has shown that internet use can potentially promote mental health. Substantial research investigated the relationship between mental health and internet usage time or purposes. However, few studies have examined the association between internet usage time trajectories and mental health.

OBJECTIVE: The objective of this study was to identify distinct trajectories of internet usage time over a span of 11 years and assess their relationship with depressive scores among middle-aged and older adults.

METHODS: Using longitudinal data from the China Family Panel Studies spanning from 2010 to 2020 and consisting of 5 waves. Participants older than 45 years with internet usage data available for at least 3 waves, including wave 5, were included in the analysis. Internet usage time was operationalized as the number of hours spent on the internet per week, while depressive scores were assessed using the 8-item Center for Epidemiologic Studies Depression Scale (CES-D 8). A latent class mixed model was used to identify distinct trajectories of internet usage time over the course of this period. Mixed-effect models were used to test the relationship between distinct trajectories of internet usage time and depressive scores.

RESULTS: Among 9163 middle-aged and older adults were included in the analysis. The trajectory analysis identified 3 clusters: “Never use,” “Slow increase,” and “Rapid increase.” The “Never use” cluster indicated no internet use for one decade. In the slow increase cluster, internet use rose slowly with an average of 7.69 hours per week in 2020. In contrast, the “Rapid increase” cluster exhibited a sharp increase, reaching 15.13 hours per week in 2020. Compared to the “Never use” cluster, the “Slow increase” cluster was significantly negatively associated with depressive scores among middle-aged and older adults (coefficient -0.20, 95% CI -0.34 to -0.06), while the “Rapid increase” cluster showed no significant association. The benefits of internet use were more pronounced among females and older adults with chronic diseases than among their male and older adult counterparts without chronic diseases. The sensitive analysis confirmed the robustness of the results.

CONCLUSIONS: This study identified 3 trajectory clusters of internet usage time among middle-aged and older adults in China from 2010 to 2020. Compared to the older adults who never used the internet, those whose internet usage increases gradually over time exhibited slightly lower depressive scores. Notably, the “Slow increase” cluster exhibited a negative association with depressive scores, with this association being statistically significant in females and older adults with chronic diseases, but not in males or those without chronic diseases. Future initiatives should aim to establish an older adult-friendly internet environment to facilitate internet access for older adults and promote moderate internet use.

PMID:40418794 | DOI:10.2196/64581

JMIR Mhealth Uhealth. 2025 May 26;13:e57474. doi: 10.2196/57474.

ABSTRACT

BACKGROUND: The adoption of high-quality health apps has been slow, despite the myriad benefits associated with their use. This is partly due to concerns regarding the effectiveness, safety, and data privacy of such apps. Quality assessments with robust and transparent criteria can address these concerns and, thereby, encourage the use of high-quality apps. However, a major challenge for such assessments is reaching a scale at which a substantial proportion of the more than 350,000 available health apps can be evaluated.

OBJECTIVE: To support the scaling of health app quality assessments, this study aimed to examine the preferences and willingness to pay for assessments with different value propositions among potential customers.

METHODS: We conducted 2 discrete choice experiments: one with 41 health app developers and another with 46 health system representatives (from health care institutions, authorities, and insurers) from across Europe. Mixed logit models were applied to examine the impact of assessment attributes on participants’ choices as well as to calculate marginal willingness to pay and predicted assessment uptake.

RESULTS: Among health app developers, the attributes with the largest impact on assessment choices were the associated clinical care uptake (integration into clinical guidelines and reimbursement or procurement) and cost (purchase price). Increased willingness to use assessed apps and app store integration of assessment results had a moderate impact on choices, while required developer time investment and time until assessment results become available made the smallest contribution. Among health system representatives, increased willingness of clinicians and patients to use evaluated apps had the greatest impact on assessment choices, followed by cost. Time until assessment result availability and the percentage of peers recommending the assessment made a moderate contribution, while reassessment frequency had the smallest impact on choices. On average, health app developers were willing to pay an additional €9020 (95% CI €4968-€13,072) if an assessment facilitates guideline integration and procurement or reimbursement (at the time of data collection, €1=US $1.11), while health system representatives were, on average, willing to pay €7037 (95% CI €4267-€9806) more if an assessment results in a large, rather than a small, increase in willingness to use the evaluated app. The predicted uptake of assessments that offer the preferred values for all attributes was 88.6% among app developers and 91.1% among health system representatives.

CONCLUSIONS: These findings indicate that, to maximize uptake and willingness to pay among health app developers, it is advisable for assessments to facilitate or enable clinical guideline integration and reimbursement or procurement for high-scoring apps. Assessment scaling thus requires close collaboration with health authorities, health care institutions, and insurers. Furthermore, if health system organizations are targeted as customers, it is essential to provide evidence for the assessment’s impact on patients’ and clinicians’ willingness to use health apps.

PMID:40418790 | DOI:10.2196/57474

Int J Biostat. 2025 May 22. doi: 10.1515/ijb-2023-0138. Online ahead of print.

ABSTRACT

Bayesian hierarchical models with a spatially smooth conditional autoregressive prior distribution are commonly used to estimate the spatio-temporal pattern in disease risk from areal unit data. However, most of the modeling approaches do not take possible boundaries of step changes in disease risk between geographically neighbouring areas into consideration, which may lead to oversmoothing of the risk surfaces, prevent the detection of high-risk areas and yield biased estimation of disease risk. In this paper, we propose a two-stage method to jointly estimate the disease risk in small areas over time and detect the locations of boundaries that separate pairs of neighbouring areas exhibiting vastly different risks. In the first stage, we use a graph-based optimisation algorithm to construct a set of candidate neighbourhood matrices that represent a range of possible boundary structures for the disease data. In the second stage, a Bayesian hierarchical spatio-temporal model that takes the boundaries into account is fitted to the data. The performance of the methodology is evidenced by simulation, before being applied to a study of respiratory disease risk in Greater Glasgow, Scotland.

PMID:40418785 | DOI:10.1515/ijb-2023-0138

Int J Cancer. 2025 May 26. doi: 10.1002/ijc.35478. Online ahead of print.

ABSTRACT

Cancer inequalities are wide and enduring, within countries between socio-demographic groups and between countries. These are generated and sustained throughout the key phases of the cancer pathway, from investigation, clinical assessment, decision and access to treatment, and follow-up care. We aimed to describe the characteristics of implemented interventions, evaluated in published controlled experiments in the medical literature, specifically designed to target reductions in inequalities along the cancer pathway. We searched the Ovid Medline and Embase databases from January 2005 to April 2024 for controlled experiments reporting on interventions tackling inequalities. We extracted information on the publication, the aim and type of intervention, its setting, the characteristics of the sample and of the interventions, and summarised their results and limitations. We identified 56 articles reporting on 57 interventions. Of these, 51 (89.5%) focused on access to screening; 56 (98.2%) focused on colorectal, breast, and cervical cancers; 37 (64.9%) concentrated on ethnic inequalities and 48 (84.2%) were based in the USA. In addition, the majority of interventions sought to change individual knowledge, beliefs, and behaviour rather than issues at the system-level. The importance of addressing how healthcare is delivered equitably to all individuals is widely recognised, and there is evidence that individual factors account for only a small part of cancer pathway inequalities. Yet, this scoping review reports a lack of diversity in the implementation of interventions addressing cancer inequalities, and a minority of them target health system issues.

PMID:40418769 | DOI:10.1002/ijc.35478

J Pediatr Endocrinol Metab. 2025 May 22. doi: 10.1515/jpem-2024-0600. Online ahead of print.

ABSTRACT

OBJECTIVES: A prospective study was conducted examining the association between blood lipid levels and bone mineral density in preschool-aged children.

METHODS: Healthy preschool-aged children (n=411) were included in this 12-month cohort study. The bone mineral density and bone mineral content of the non-dominant forearm and calcaneus were measured using dual-energy X-ray absorptiometry (DXA). Additionally, the children’s fasting blood was drawn at baseline to measure blood lipids.

RESULTS: The sample comprised 411 healthy preschool-aged children, 208 girls and 203 boys, with a mean age of 4.80±0.70 years. After one year of observation, the bone mineral density of the non-dominant calcaneus in preschool children increased by 30.37 mg/cm², bone mineral content increased by 29.85 mg, and triglyceride levels increased by 0.05 mmol/L. A significant inverse assocation was observed between serum triglyceride levels within the normal physiological range and the changes in bone mineral density (BMD) at the non-dominant calcaneus in preschool children, whereas no such association was detected with BMD changes in the non-dominant forearm. A 1 mmol/L increase in triglycerides within the physiological normal range was associated with a 6.73 mg/cm² decrease in bone mineral density (95 % CI: -12.90, -0.56) and a 5.98 mg decrease in bone mineral content (95 % CI: -11.77, -0.19). There was no significant relationship between other lipids and bone mineral density.

CONCLUSIONS: Serum triglyceride concentrations within the physiological normal range showed a significant negative correlation with the 12-month increment of calcaneal bone mineral density in preschool children (p<0.05).

PMID:40418764 | DOI:10.1515/jpem-2024-0600

Womens Health (Lond). 2025 Jan-Dec;21:17455057251338424. doi: 10.1177/17455057251338424. Epub 2025 May 26.

ABSTRACT

BACKGROUND: Women with disabilities have a similar desire for pregnancy as their non-disabled peers but experience more ambivalence and doubt about their intention to have a child. While many have healthy pregnancies, they face higher risks and trade-offs in health, function, and independence.

OBJECTIVES: To review the literature on pregnancy in women with physical disabilities to guide interventions and clinical care guidelines.

ELIGIBILITY CRITERIA: Abstracts were reviewed if they were original research on pregnancy involving adult women with physical disabilities. Both qualitative and quantitative studies were included, with no restrictions on language or publication year.

SOURCES OF EVIDENCE: PubMed, Scopus, and CINAHL Complete and reference lists of eligible articles.

CHARTING METHODS: Abstracts were eligible for full-text review if they were (1) original research, (2) in humans, (3) about pregnancy, and (4) involved adult women with physical disabilities. Data were extracted by independent reviewers using Covidence software and assessed with a customized critical appraisal guide.

RESULTS: Five major topics characterized 171 reviewed articles: (1) rates of pregnancy, fertility, and termination or loss; (2) pregnancy complications and infant outcomes; (3) effects of pregnancy on physical function disease activity; (4) maternal care; and (5) social and interpersonal dimensions of pregnancy. Most studies were conducted in the Americas and Europe, and high-income countries used a quantitative design and were assessed to have a moderate risk of bias.

CONCLUSIONS: This review highlights the need for future research to (1) build a stronger evidence base for tailored maternal care, (2) examine disability discrimination’s impact on pregnancy outcomes, (3) develop interventions to reduce disability-related inequities, and (4) improve disability competence among maternal care providers.

PMID:40418752 | DOI:10.1177/17455057251338424