Category: Statistics

J Med Internet Res. 2025 Apr 10;27:e68936. doi: 10.2196/68936.

ABSTRACT

BACKGROUND: Diabetes mellitus significantly increases the risk of severe complications from influenza, necessitating targeted vaccination efforts. Despite vaccination being the most effective preventive measure, coverage remains below the World Health Organization’s targets, partly due to limited awareness among patients. This study evaluated a digital health intervention aimed at improving influenza vaccination rates among adults with diabetes.

OBJECTIVE: This study aimed to demonstrate the effectiveness of digital health platforms in increasing vaccination rates among people with diabetes and to emphasize the impact of tailored messaging frequency on patient engagement and health behavior change. We hypothesized that digital tools providing empirical evidence of increased health risk awareness can effectively drive preventive actions.

METHODS: The study leveraged the Dario (Dario Health Corp) digital health platform to retrospectively analyze data from 64,904 users with diabetes assigned by the platform into three groups: (1) Group A received previously studied monthly flu nudge messages; (2) Group B received an adapted intervention with 2-3 monthly messages; (3) Group C served as the control with no intervention. Surveys were conducted at baseline, 3 months, and 6 months to assess vaccination status, awareness of influenza risks, and recollection of educational content. Statistical analyses, including logistic regression, chi-square tests, and t tests, were used to evaluate differences between groups.

RESULTS: Out of 64,904 users, 8431 completed the surveys. Vaccination rates were 71.0% in group A, 71.9% in group B, and 70.5% in group C. Group B showed significantly higher awareness of influenza risks compared with the control group odds ratio (OR; OR 1.35, 95% CI 1.12-1.63; P=.001), while group A did not (OR 1.10, 95% CI 0.92-1.32; P=.27). Recollection of educational content was also higher in groups A (OR 1.29, 95% CI 1.07-1.56; P=.008) and B (OR 1.92, 95% CI 1.59-2.33; P<.001) compared with the control. In addition, a significant correlation between awareness and vaccination rates was found only in group B (χ²(df=1)=6.12, P=.01).

CONCLUSIONS: The adapted digital intervention (group B) effectively increased awareness of influenza risks and recollection of educational content, which correlated with the higher trend in vaccination rates. This study demonstrates the potential of digital health tools to enhance influenza vaccination among people with diabetes by improving risk awareness and education. Further research should focus on optimizing these interventions to achieve significant improvements in vaccination uptake and overall public health outcomes.

TRIAL REGISTRATION: ClinicalTrials.gov NCT06840236; https://clinicaltrials.gov/study/NCT06840236.

PMID:40209214 | DOI:10.2196/68936

JMIR Res Protoc. 2025 Apr 10;14:e64886. doi: 10.2196/64886.

ABSTRACT

BACKGROUND: Every day, approximately 800 women die from pregnancy-related causes, alongside 2.6 million stillbirths and 2.8 million neonatal deaths annually. Inadequate referral by skilled birth attendants hinders timely access to necessary emergency obstetric care, challenging progress toward the maternal health Sustainable Development Goal (SDG) 3. The COVID-19 pandemic further disrupted care in low- and middle-income countries, forcing women to rely on traditional birth attendants, thereby affecting the referral system. It is crucial to understand the experiences of both skilled and traditional birth attendants regarding upward referrals in emergency obstetric care to identify barriers and facilitators within these systems in low- and middle-income countries.

OBJECTIVE: This study aims to map existing evidence on the experiences of skilled and traditional birth attendants regarding upward referral systems in emergency obstetric care within low- and middle-income countries.

METHODS: We will conduct a scoping review guided by the Joanna Briggs Institute’s methodological framework. Studies will be included if they report on experiences with upward referral in obstetrical emergencies. We will consider studies published in English and French from 2016 to July 2024. The literature search will be conducted in databases including PubMed, EBSCOhost (Academic Search Complete and CINAHL with full text), Scopus, Web of Science, and Google Scholar. Identified citations will be managed using EndNote version 21 (Clarivate Analytics) and Rayyan. Two independent reviewers will screen eligible studies and resolve disagreements through discussion with a third reviewer. Data will be extracted using a validated form and analyzed through content analysis, with findings presented narratively. This protocol aligns with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The review will offer a comprehensive narrative of upward referral systems in obstetrical emergencies, focusing on transitions from traditional birth attendants to health care facilities and from lower to higher levels of health care.

RESULTS: The preliminary search was completed in August 2024, and the database search will be conducted within the next 6 months. Findings will be disseminated through medical education conferences and publications.

CONCLUSIONS: This review contributes a comprehensive narrative of upward referral systems in obstetrical emergencies, aiming to enhance understanding and improve transitions from traditional birth attendants to health care facilities and between different health care levels. It could significantly impact maternal and neonatal care by identifying the referral experiences of both skilled and traditional birth attendants. The insights may inform interventions that integrate traditional birth attendants into health care systems, potentially reducing maternal and neonatal mortality. The results will guide future research aimed at developing a model to improve upward referrals for obstetric emergencies in sub-Saharan Africa.

TRIAL REGISTRATION: Open Science Framework 4HAVZ; https://osf.io/4havz.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/64886.

PMID:40209211 | DOI:10.2196/64886

JMIR Mhealth Uhealth. 2025 Apr 10;13:e57018. doi: 10.2196/57018.

ABSTRACT

BACKGROUND: Ecological momentary assessment (EMA) offers an effective method to collect frequent, real-time data on an individual’s well-being. However, challenges exist in response consistency, completeness, and accuracy.

OBJECTIVE: This study examines EMA response patterns and their relationship with sensed behavior for data collected from diverse studies. We hypothesize that EMA response rate (RR) will vary with prompt time of day, number of questions, and behavior context. In addition, we postulate that response quality will decrease over the study duration and that relationships will exist between EMA responses, participant demographics, behavior context, and study purpose.

METHODS: Data from 454 participants in 9 clinical studies were analyzed, comprising 146,753 EMA mobile prompts over study durations ranging from 2 weeks to 16 months. Concurrently, sensor data were collected using smartwatch or smart home sensors. Digital markers, such as activity level, time spent at home, and proximity to activity transitions (change points), were extracted to provide context for the EMA responses. All studies used the same data collection software and EMA interface but varied in participant groups, study length, and the number of EMA questions and tasks. We analyzed RR, completeness, quality, alignment with sensor-observed behavior, impact of study design, and ability to model the series of responses.

RESULTS: The average RR was 79.95%. Of those prompts that received a response, the proportion of fully completed response and task sessions was 88.37%. Participants were most responsive in the evening (82.31%) and on weekdays (80.43%), although results varied by study demographics. While overall RRs were similar for weekday and weekend prompts, older adults were more responsive during the week (an increase of 0.27), whereas younger adults responded less during the week (a decrease of 3.25). RR was negatively correlated with the number of EMA questions (r=-0.433, P<.001). Additional correlations were observed between RR and sensor-detected activity level (r=0.045, P<.001), time spent at home (r=0.174, P<.001), and proximity to change points (r=0.124, P<.001). Response quality showed a decline over time, with careless responses increasing by 0.022 (P<.001) and response variance decreasing by 0.363 (P<.001). The within-study dynamic time warping distance between response sequences averaged 14.141 (SD 11.957), compared with the 33.246 (SD 4.971) between-study average distance. ARIMA (Autoregressive Integrated Moving Average) models fit the aggregated time series with high log-likelihood values, indicating strong model fit with low complexity.

CONCLUSIONS: EMA response patterns are significantly influenced by participant demographics and study parameters. Tailoring EMA prompt strategies to specific participant characteristics can improve RRs and quality. Findings from this analysis suggest that timing EMA prompts close to detected activity transitions and minimizing the duration of EMA interactions may improve RR. Similarly, strategies such as gamification may be introduced to maintain participant engagement and retain response variance.

PMID:40209210 | DOI:10.2196/57018

JMIR Form Res. 2025 Apr 10;9:e63928. doi: 10.2196/63928.

ABSTRACT

BACKGROUND: Gait speed indicates the onset or decline of physical performance in sarcopenia. However, real-time measurements of other gait parameters, such as step length, stride length, step width, and support time, are limited. The advent of wearable technology has facilitated the measurement of these parameters, necessitating further investigation into their potential applications.

OBJECTIVE: This study aimed to investigate the relationship between gait parameters measured using wearable sensors and muscle mass, strength, and physical performance in community-dwelling older adults.

METHODS: In a cross-sectional study of 91 participants aged ≥65 years, gait parameters, such as step count, step length, cadence, single and double support times, vertical oscillation, and instantaneous vertical loading rate (IVLR), measured using a wireless earbud device, were analyzed on the basis of the appendicular skeletal muscle mass index (SMI), calf circumference, handgrip strength, 5-time chair stand test, short physical performance battery (SPPB), and the SARC-F (strength, assistance with walking, rise from a chair, climb stairs and fall frequency) questionnaire. This study was conducted from July 10 to November 1, 2023, at an outpatient clinic of a university hospital in Seoul, Korea. Multiple regression analysis was performed to investigate independent associations after adjusting for age, sex, BMI, and comorbidities.

RESULTS: Among 91 participants (45 men and 46 women; mean age 74.1 years for men and 73.6 years for women), gait speed and vertical oscillation showed negative associations with their performance in the 5-time chair stand test (P<.001) and SARC-F and positive associations with their performance in the SPPB (P<.001). Vertical oscillations were also associated with grip strength (P=.003). Single and double support times were associated with performance in the 5-time chair stand test and SPPB (P<.001). In addition, double support time was associated with SARC-F scores (P<.001). Gait speed, support time, vertical oscillation, and IVLR showed independent associations with performance in the 5-time chair stand test and SPPB (P<.001), both related to muscle strength or physical performance. Gait speed, double support time, and vertical oscillation all had significant associations with SARC-F scores.

CONCLUSIONS: This study demonstrated a significant association between gait monitoring using wearable sensors and quantitative assessments of muscle strength and physical performance in older people. Furthermore, this study substantiated the extensive applicability of diverse gait parameters in predicting sarcopenia.

PMID:40209209 | DOI:10.2196/63928

JMIR Hum Factors. 2025 Apr 10;12:e69873. doi: 10.2196/69873.

ABSTRACT

BACKGROUND: Binge drinking, which is linked to various immediate and long-term negative outcomes, is highly prevalent among US college students. Behavioral interventions delivered via mobile phones have a strong potential to help decrease the hazardous effects of binge drinking by promoting safer drinking behaviors.

OBJECTIVE: This study aims to evaluate the preliminary efficacy of bhoos, a novel smartphone app designed to promote safer drinking behaviors among US college students. The app offers on-demand educational content about safer alcohol use, provides dynamic feedback as users log their alcohol consumption, and includes an interactive drink tracker that estimates blood alcohol content in real time.

METHODS: The bhoos app was tested in 2 independent pre-post studies each lasting 4 weeks, among US college students aged 18-35 years. The primary outcome in both trials was students’ self-reported confidence in using protective behavioral strategies related to drinking, with self-reported frequency of alcohol consumption over the past month examined as a secondary outcome.

RESULTS: In study 1, bhoos was associated with increased confidence in using protective behavioral strategies. Students also endorsed the high usability of the app and reported acceptable levels of engagement. Study 2 replicated findings of increased confidence in using protective behavioral strategies, and demonstrated a reduction in the self-reported frequency of alcohol consumption.

CONCLUSIONS: Bhoos is a personalized, accessible, and highly scalable digital intervention with a strong potential to effectively address alcohol-related behaviors on college campuses.

PMID:40209208 | DOI:10.2196/69873

JMIR Med Educ. 2025 Apr 10;11:e67244. doi: 10.2196/67244.

ABSTRACT

BACKGROUND: Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs), have started a new era of innovation across various fields, with medicine at the forefront of this technological revolution. Many studies indicated that at the current level of development, LLMs can pass different board exams. However, the ability to answer specific subject-related questions requires validation.

OBJECTIVE: The objective of this study was to conduct a comprehensive analysis comparing the performance of advanced LLM chatbots-Claude (Anthropic), GPT-4 (OpenAI), Gemini (Google), and Copilot (Microsoft)-against the academic results of medical students in the medical biochemistry course.

METHODS: We used 200 USMLE (United States Medical Licensing Examination)-style multiple-choice questions (MCQs) selected from the course exam database. They encompassed various complexity levels and were distributed across 23 distinctive topics. The questions with tables and images were not included in the study. The results of 5 successive attempts by Claude 3.5 Sonnet, GPT-4-1106, Gemini 1.5 Flash, and Copilot to answer this questionnaire set were evaluated based on accuracy in August 2024. Statistica 13.5.0.17 (TIBCO Software Inc) was used to analyze the data’s basic statistics. Considering the binary nature of the data, the chi-square test was used to compare results among the different chatbots, with a statistical significance level of P<.05.

RESULTS: On average, the selected chatbots correctly answered 81.1% (SD 12.8%) of the questions, surpassing the students’ performance by 8.3% (P=.02). In this study, Claude showed the best performance in biochemistry MCQs, correctly answering 92.5% (185/200) of questions, followed by GPT-4 (170/200, 85%), Gemini (157/200, 78.5%), and Copilot (128/200, 64%). The chatbots demonstrated the best results in the following 4 topics: eicosanoids (mean 100%, SD 0%), bioenergetics and electron transport chain (mean 96.4%, SD 7.2%), hexose monophosphate pathway (mean 91.7%, SD 16.7%), and ketone bodies (mean 93.8%, SD 12.5%). The Pearson chi-square test indicated a statistically significant association between the answers of all 4 chatbots (P<.001 to P<.04).

CONCLUSIONS: Our study suggests that different AI models may have unique strengths in specific medical fields, which could be leveraged for targeted support in biochemistry courses. This performance highlights the potential of AI in medical education and assessment.

PMID:40209205 | DOI:10.2196/67244

JMIR Public Health Surveill. 2025 Apr 10;11:e68724. doi: 10.2196/68724.

ABSTRACT

BACKGROUND: Effective dissemination of federal risk communication by news media during multijurisdictional enteric illness outbreaks can increase message reach to rapidly contain outbreaks, limit adverse outcomes, and promote informed decision-making by the public. However, dissemination of risk communication from the federal government by mass media has not been evaluated.

OBJECTIVE: This study aimed to describe and assess the dissemination of federal risk communication by news media outlets during multijurisdictional enteric illness outbreaks in Canada.

METHODS: A comprehensive systematic search of 2 databases, Canadian Newsstream and Canadian Business & Current Affairs, was run using search terms related to the source of enteric illnesses, general outbreak characteristics, and relevant enteric pathogen names to retrieve news media articles issued between 2014 and 2023, corresponding to 46 public health notices (PHNs) communicating information about multijurisdictional enteric illness outbreaks during the same period. A codebook comprised of 3 sections-general characteristics of the article, consistency and accuracy of information presented between PHNs and news media articles, and presence of health belief model constructs-was developed and applied to the dataset. Data were tabulated and visualized using RStudio (Posit).

RESULTS: News media communicated about almost all PHNs (44/46, 96%). News media commonly developed their own articles (320/528, 60.6%) to notify the public about an outbreak and its associated product recall (121/320, 37.8%), but rarely communicated about the conclusion of an outbreak (12/320, 3.8%). News media communicated most outbreak characteristics, such as the number of cases (237/319, 74.3%), but the number of deaths was communicated less than half the time (114/260, 43.8%). Benefit and barrier constructs of the health belief model were infrequently present (50/243, 20.6% and 15/243, 6.2%, respectively).

CONCLUSIONS: Canadian news media disseminated information about most multijurisdictional enteric illness outbreaks. However, differences in coverage of multijurisdictional enteric illness outbreaks by news media were evident. Federal organizations can improve future risk communication of multijurisdictional enteric illness outbreaks by news media by maintaining and strengthening interorganizational connections and ensuring the information quality of PHNs as a key information source for news media.

PMID:40209203 | DOI:10.2196/68724

N Z Med J. 2025 Apr 11;138(1613):87-95. doi: 10.26635/6965.6842.

ABSTRACT

AIM: To update prescribers about the revised Land Transport (Drug Driving) Amendment Act 2022 (LTAA) and implications for prescribing.

METHODS: We reviewed the legislation of the LTAA and the specific drugs identified in it, mainly benzodiazepines and opioids. We also briefly reviewed published evidence on the impact of benzodiazepines and opioids on driving.

RESULTS: Both opioids and benzodiazepines are associated with increased accidents in observational (non-controlled) studies, though the odds ratios are small (at most 1.65 for benzodiazepines and around 2.0 for opioids), and accident events are rare. Prescribers are not advised to do blood levels or bedside testing to assess driving fitness. They should consult a peer group or mental health pharmacist when advising patients taking multiple psychoactive medications if they are safe to drive.

CONCLUSION: There are no current jurisprudence or guidelines for prescribers on how to interact with the LTAA. Nor is it clear if or how investigations or complaints relating to the LTAA would be handled by the Health and Disability Commissioner (HDC), the Medical Council of New Zealand and/or the Coroner. Until more detailed instructions are published, this article should provide some guidance for professionals who prescribe benzodiazepines or opioids.

PMID:40209198 | DOI:10.26635/6965.6842

N Z Med J. 2025 Apr 11;138(1613):79-86. doi: 10.26635/6965.6809.

ABSTRACT

BACKGROUND: Delayed ovarian torsion management can lead to unnecessary oophorectomy and halving of a woman’s fertility potential.

AIMS: To improve recognition and efficiency of ovarian torsion management at Waitematā by examining common presenting symptoms/signs and identifying areas of treatment delay.

METHODS: An audit of all ovarian torsion cases at Waitematā over 24 months (01/05/2022-30/04/2024).

RESULTS: Forty-five women had ovarian torsion, and 42 were premenopausal. Common presenting features included abdominal pain (100%), ovarian cysts (97.8%), nausea (82%) and vomiting (51%). Peritonism was rare (13.3%). Oophorectomy was performed in 26 cases (57.8%). Rates of oophorectomy increased with increasing time from symptom onset until presentation. The time from presentation until surgery (average of 28 hours) was longer than other tertiary centres, with delays largely arising from triage to ultrasound, and then while awaiting access to theatre.

CONCLUSIONS: Improving torsion recognition and expediting both imaging and surgery should reduce oophorectomy rates. Women presenting with symptomatic ovarian cysts without torsion should be adequately counselled on the risk of future torsion events and encouraged to seek acute medical attention for changes in symptoms. Additionally, more study is needed to determine if relying on computed tomography (CT) findings alone (e.g., presence of ovarian cysts more than 5cm) in the presence of symptoms suggestive of ovarian torsion can reduce time to diagnosis and improve surgical outcomes, compared to the commonly used CT followed by ultrasound.

PMID:40209197 | DOI:10.26635/6965.6809

N Z Med J. 2025 Apr 11;138(1613):50-66. doi: 10.26635/6965.6806.

ABSTRACT

AIM: The New Zealand population defined as “Pacific” is ethnically diverse, but this diversity is seldom examined in health research. This paper applies novel methods for describing health outcomes for specific Pacific populations in New Zealand using all-cancer and gastric cancer incidence and mortality as examples. Effects of loss to follow-up from leaving the country are also assessed.

METHOD: The New Zealand Cancer Registry was linked to administrative datasets and analysed within Stats NZ’s Integrated Data Infrastructure (IDI). All-cancer and gastric cancer incidence was examined over the 1995-2022 period, as well as 1-5-year mortality among 1998-2017 diagnoses.

RESULTS: There was variability in age-standardised all-cancer incidence and gastric cancer incidence for different Pacific groups. Less variation in mortality was identified between groups, and these rates increased only modestly when adjusting for those who left the country. Lower all-cancer mortality was observed in 2008-2017 compared with 1998-2007.

CONCLUSION: Variation in health outcomes among specific Pacific ethnicities is masked when examining Pacific peoples as an aggregated ethnic group. However, small counts among small ethnicities create challenges for producing detailed, reliable data when using the IDI.

PMID:40209195 | DOI:10.26635/6965.6806