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PubMed2026

Evaluating Patient Satisfaction and Oral Health Impact Profile-14 (OHIP-14): A Multicenter Crossover Study Comparing Selective Pressure Impression Conventional Dentures with Mucostatic Digital Dentures.

PURPOSE: To compare patient satisfaction and oral health impact between individuals receiving complete dentures made by digital methods and those using conventional techniques. MATERIALS AND METHODS: In this randomized crossover clinical trial, 23 patients aged 40 years and older with completely edentulous arches were enrolled at three treatment centers. Each participant received two sets of complete dentures: one set created using conventional methods (selective pressure impression) and the other through digital techniques (mucostatic digital impression). The order of denture placement was randomized, with each set used for 4 weeks. A trained specialist administered treatments alongside research tools, including a general information questionnaire, a denture satisfaction survey, and the OHIP-14 interview tool. Statistical analysis was conducted using Mann-Whitney U test. RESULTS: Participants with digital dentures reported significantly higher satisfaction regarding treatment duration, comfort, confidence, chewing ability, esthetics, and overall satisfaction compared to those with conventional dentures. There were no significant differences in satisfaction concerning speech and pronunciation. Overall, the oral health impact on quality of life was similar between denture types, but participants indicated improved quality of life while using dentures compared to being edentulous. CONCLUSIONS: Patients with digital dentures exhibited greater satisfaction across various domains compared to those with conventional dentures, despite similar satisfaction levels in speech and pronunciation. The impact on quality of life was comparable between both types, as measured by the OHIP-14.

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PubMed2026

Effects of Digital Mental Health Screening Alone and With the Online MINDBODYSTRONG CBT-Based Program on Burnout, Depression, Anxiety, Healthy Behaviors, and Suicidal Ideation in at-Risk Nurses at 3- and 6-Months Post-Intervention: An RCT.

BACKGROUND: Burnout and mental distress among nurses are global public health epidemics that adversely affect nurse well-being and healthcare quality. Evidence-based, scalable mental health interventions are urgently needed. AIMS: To evaluate the 3- and 6-month outcomes of a randomized controlled trial (RCT) comparing a psychologically safe, digital mental health screening and referral program alone versus the same screening and referral program combined with the video-based online MINDBODYSTRONG (MBS) cognitive behavioral therapy (CBT)-based skills-building program among nurses at risk for mental distress. METHODS: 501 nurses were recruited from professional organizations and healthcare systems across the United States by email and randomized to either mental health screening and referral (standard care) or standard care plus the MBS cognitive behavioral skills-building intervention (the intervention). All study activities were conducted remotely. Follow-up surveys administered at 3- and 6-months assessed anxiety, depression, suicidal ideation, burnout, healthy lifestyle beliefs, and healthy lifestyle behaviors using valid and reliable scales. RESULTS: Compared with the screening and referral only group, participants in the intervention group had greater reductions in anxiety and depression and significantly greater increases in healthy lifestyle beliefs and behaviors at 3 and 6 months post-intervention. After controlling baseline risk, the intervention group had a lower risk of suicidal ideation than the screening and referral group at 3 months (relative risk ratio [RRR] = 0.717; 95% CI: 0.320-1.606) and 6 months (RRR = 0.329; 95% CI: 0.101-1.072). The intervention group also had a significantly lower risk of burnout at 6 months (RRR: 0.698, 95% CI: 0.528, 0.929, p = 0.012). Nurses who completed more MBS sessions had less suicidal ideation at 6 months and those who completed more MBS skills-building activities had less burnout at 3 and 6 months. LINKING ACTION TO EVIDENCE: Integrating psychologically safe mental health screening combined with the scalable online CBT-based intervention, MBS, can produce sustained improvements in burnout, mental health symptoms, including suicidality, and healthy lifestyle beliefs and behaviors among nurses experiencing mental distress.

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PubMed2026

Effectiveness of digital health technologies for post-discharge follow-up and management in older adults: a systematic review.

Older adults (≥65 years) are a rapidly growing population that are experiencing a higher number of hospitalisation admissions, longer hospital stays, and greater hospitalisation-related costs than younger adults. There is an important gap in post-discharge care for older adults, and digital technologies, such as video visits, mobile health apps, and remote patient monitoring, may support follow-up and management after hospital discharge. This systematic review examined the effectiveness, feasibility, acceptability, and impact (ie, effects on rehospitalisation, quality of life, mental health, adherence, and patient satisfaction) of technology-based interventions used for the follow-up and management of older adults after hospital discharge. MEDLINE (via PubMed), Scopus, and Web of Science were searched from database inception to January, 2026. The search identified 1972 records, of which 46 studies met the inclusion criteria: older adult populations (aged ≥65 years), a technology-based intervention, post-discharge follow-up or management, and empirical data. Overall, digital post-discharge interventions were reported to be feasible, with good engagement, adherence, compliance, and retention; low dropout rates; and positive patient satisfaction. However, mixed findings were reported regarding rehospitalisation rates and mental health outcomes for virtual care compared with those for traditional care. Digital health technologies might represent a promising step towards improving post-discharge health care and continuity of care for older adults.

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PubMed2026

Sex differences in sleep and alcohol consumption outcomes following a digital insomnia intervention.

BACKGROUND: Poor sleep is a well-established risk factor for heavy drinking, and evidence suggests that sleep could serve as a potential treatment target for reducing alcohol consumption. The relationship between poor sleep and problematic drinking appears to be stronger among females, but no studies to date have assessed sex differences in alcohol consumption following insomnia treatment. Here, we combine the samples from two clinical trials to investigate sex differences in the effects of a digital cognitive behavioral therapy for insomnia (Sleep Healthy Using the Internet; SHUTi) on sleep and alcohol outcomes. METHODS: 184 heavy drinking individuals with insomnia (weekly binge episodes: 4/5 + drinks in one sitting for females/males; AUDIT score >7; ISI score >14) were randomly assigned to either the SHUTi program (n = 102) or an active control program (n = 82). Participants completed self-report assessments at baseline, immediately following the 9-week intervention period, and at 3 and 6-months post-intervention. RESULTS: Linear mixed effects models showed that SHUTi effects over time were stronger among females than males for improved sleep outcomes and reduced frequency of total and heavy drinking days (ps ≤ 0.038). Follow-up comparisons of within-group effect sizes revealed consistently larger reductions in alcohol consumption among SHUTi females (Cohen's d range = 0.92-2.23) than SHUTi males (Cohen's d range = 0.65-1.95). CONCLUSIONS: Findings suggest that SHUTi may be more efficacious in improving sleep and reducing drinking among females with insomnia compared to males. These results could have important implications for sex-specific prevention and treatment efforts for heavy drinking individuals with insomnia.

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PubMed2026

From population to individual: advocating personalised digital tools for heat-health early warning in a changing climate.

Escalating heat extremes under climate change are imposing substantial health burdens, with 2023 and 2024 consecutively breaking global temperature records. Mounting evidence suggests that heatwaves elevate the risks of hospitalisation and mortality across multiple disease categories, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and acute kidney injury. Nonetheless, most existing heat-health warning systems remain primarily reliant on population-level predictions, and considering individual differences and disease-specific considerations when defining warning levels would benefit the effectiveness of early prevention for high-risk groups. In this Viewpoint, which is based on the framework of precision public health-delivering the right intervention to the right population at the right time-we propose a framework for personalised digital heat-health early warning tools comprising three dimensions: individualised, risk-stratified prediction models that generate tiered early warnings; personalised health prompts coupled with theory-informed behavioural interventions; and adaptive, equity-oriented alert delivery mechanisms tailored to diverse populations. Such tools have the potential to bridge precision disease prevention and climate adaptation, thereby helping to mitigate heat exposure risks and disease burdens, particularly among high-risk populations. Future implementation research will be essential to address substantial challenges related to feasibility, validation, and equity.

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PubMed2026

Comfort and Usability of Digital Versus Conventional Custom-Fit Mouthguards: A Randomized Clinical Trial.

BACKGROUND/OBJECTIVES: The use of mouthguards protects teeth and the supporting tissues against impacts. Digital impressions and 3D-printed models can reduce manufacturing steps and minimize discomfort. This study evaluated the fit, comfort, and usability of custom-made mouthguards, obtained by conventional and digital workflow, in amateur athletes. MATERIALS AND METHODS: Amateur athletes were recruited for this randomized, double-blind, crossover clinical study. Each participant received two 4-mm-thick custom-fit mouthguards made of ethylene vinyl acetate (EVA) sheets using two protocols: conventional impression using alginate to produce dental stone cast (CMP) and intraoral digital scanning to produce 3D-printed resin models (DMP). Each mouthguard was worn during all training and matches over 3 months. The order of mouthguard use was randomly assigned. Patient satisfaction with the impression protocol and mouthguard use, model accuracy, and mouthguard fit were assessed. RESULTS: Overall, 46 participants completed the study. The DMP protocol required less execution time (p = 0.023), caused less discomfort (p = 0.018), anxiety (p = 0.008), nausea (p = 0.027), difficulty breathing (p < 0.001), and unpleasant taste (p = 0.006) compared to the CMP protocol. The pain (p = 0.971) perceived by the participants was similar in both impression protocols. The CMP-mouthguards were considered to be better fitting by the majority of participants (p = 0.027). Between-group comparisons revealed that DMP-mouthguard caused less discomfort immediately postadaptation (p = 0.034), with no significant differences observed at 30 or 90 days. CONCLUSIONS: The digital workflow demonstrated to be efficient in the fabrication of mouthguards. Digital impression was more comfortable, requiring less execution time, with more accurate printed models and produced mouthguards with reported comfort and fit levels similar to those manufactured conventionally.

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PubMed2026

Physical reconfiguration of limb electrodes for Precordial Bipolar Lead acquisition: Morphological validation against digital subtraction.

BACKGROUND: The V2 - V1 Precordial Bipolar Lead (PBL) selectively evaluates the right-to-left retrosternal axis and has shown diagnostic value beyond the standard 12‑lead electrocardiogram. However, its use has been limited by the need for raw electrocardiographic data and post-processing software. This study evaluated whether a simple physical reconfiguration of limb electrodes could reproduce the digitally derived V2 - V1 morphology with sufficient accuracy for clinical application. METHODS: Thirty-seven subjects underwent two sequential 10-s 12‑lead recordings using a Cardiovit FT-1 electrocardiograph sampled at 1000 Hz. In the standard recording, the digital PBL was calculated as V2 - V1. In the second recording, the right-arm and left-arm electrodes were repositioned to the V1 and V2 sites so that Lead I directly recorded the retrosternal dipole. Signals were filtered, synchronized, and analyzed using median beats. Morphological agreement was assessed with Pearson correlation on Z-normalized signals, while absolute agreement was evaluated using Lin's concordance correlation coefficient (CCC), intraclass correlation coefficient (ICC (Lewis, 1931; Nehb, 1938 [1,2])), root mean square error (RMSE), and Bland-Altman analysis. RESULTS: Mean Pearson correlation between digital and physical PBL was 0.955 (SD 0.043), with segment-specific correlations of 0.953 (SD 0.054) for QRS and 0.967 (SD 0.052) for ST-T. Lin's CCC and ICC(2,1) were both 0.871 (SD 0.110), and RMSE was 0.091 (SD 0.049) mV. Bland-Altman analysis showed minimal bias (-0.008 mV). CONCLUSIONS: Physical acquisition of the V2 - V1 PBL achieved high agreement with the digitally derived signal, supporting a simplified analog method for broader clinical implementation.

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PubMed2026

Effect of a digitally augmented general health promotion intervention on abstinence from health-risk behaviors among emergency department discharge patients: A randomized controlled trial.

BACKGROUND: Noncommunicable diseases (NCDs) are the leading global cause of death and are driven by modifiable behaviors, such as tobacco use, harmful alcohol consumption, unhealthy diet, and physical inactivity. Recognizing that emergency department (ED) visits represent a unique opportunity to promote behavior change, this trial evaluated a digitally augmented, theory based general health promotion approach, combining a brief telephone-based intervention with mobile instant messaging support, to help discharged ED patients abstain from health risk behaviors. METHODS AND FINDINGS: This assessor-blinded randomized controlled trial was conducted in a major public hospital ED in Hong Kong. Adults (18-65 years) triaged as semi-urgent or non-urgent and with ≥1 health-risk behavior and smartphone access were randomized to receive a digitally augmented, theory‑based general health‑promotion intervention consisting of a brief telephone‑based AWARD‑model intervention (Ask, Warn, Advise, Refer, and Do-it-again) followed by weekly WhatsApp or WeChat messages for 6 months, or to a control group receiving brief telephone advice only. The primary outcome was self-report abstinence from ≥1 health-risk behavior at 6 months; secondary outcomes included the proportion of participants who achieved self-reported abstinence from ≥1 health-risk behavior at 12 months and reduction in the number of behaviors at 6 and 12 months. Of the 2,134 screened patients, 572 were enrolled (286 per group). At 6 months, 30.1% of the intervention participants versus 19.9% of the controls achieved self-reported abstinence (RR = 1.51; 95% CI, 1.13-2.02; P = 0.006). The intervention also significantly increased the likelihood of fewer risky behaviors at 6 (RR = 1.54; P = 0.01) and 12 (RR = 1.48; P = 0.02) months. Physical inactivity showed the greatest improvement at 6 months (31.7% versus 16.2%; P < 0.001). The effects attenuated after cessation of booster messaging. Limitations include reliance on self-reported outcomes, the single-center study design, and loss to follow-up, which may have affected the generalizability of the results. CONCLUSIONS: A digitally augmented, theory-based general health promotion strategy delivered at ED discharge through brief telephone intervention and mobile instant messaging support demonstrated short-term benefits in promoting self-reported abstinence and reducing health-risk behaviors at 6 months. However, the absence of a sustained effect at 12 months suggests that extended support or maintenance strategies may be required to maintain these improvements over time. Multicenter trials with longer follow-up are warranted to evaluate long-term effectiveness. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (Registration No: NCT06077565).

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PubMed2026

Digital Mindfulness Intervention for Pregnant Women With Affective Disorders and Acute Stress Reactions: Prespecified Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Pregnant women with ICD-10 (International Statistical Classification of Diseases, Tenth Revision) affective or stress-related disorders face an elevated risk of perinatal depression and anxiety, yet evidence on digital nonpharmacologic interventions for this population remains limited. OBJECTIVE: This study evaluated the effectiveness of an 8-week digital mindfulness-based intervention (eMBI) compared with treatment as usual (TAU) among pregnant women with ICD-10 affective or stress-related disorders participating in a randomized controlled trial (RCT). METHODS: This prespecified secondary analysis was conducted within a multicenter RCT in Baden-Württemberg, Germany. Pregnant women aged 18 years and older with elevated depressive symptoms (Edinburgh Postnatal Depression Scale [EPDS]>9) and ICD-10-diagnosed affective or stress-related disorders were randomized 1:1 to eMBI or TAU. The intervention consisted of 8 weekly app-based mindfulness sessions (45 min each) delivered during gestational weeks 29-36, with no direct therapist contact. The primary outcome was continuous depressive symptom severity measured with the EPDS at 4-6 weeks post partum. Secondary outcomes included the EPDS at 6 months post partum, generalized anxiety (State-Trait Anxiety Inventory-State [STAI-S], State-Trait Anxiety Inventory-Trait [STAI-T]), and Pregnancy-Related Anxiety Questionnaire-Revised (PRAQ-R). Analyses followed the intention-to-treat (ITT) principle, using mixed models for repeated measures and multiple imputation. RESULTS: Of the 5299 screened women, 147 met the inclusion criteria for this subgroup analysis (intervention group [IG] had n=73 women and control group had n=74 women). Groups were comparable at baseline. The IG showed significantly greater reductions in EPDS scores at gestational week 34 (Δ=-2.21, P=.01), week 36 (Δ=-3.25, P=.01), and 4-6 weeks post partum (Δ=-4.81, P=.007). Treatment effects remained robust under conservative missing-data assumptions. At 4-6 weeks post partum, a higher proportion of participants in the IG achieved clinically meaningful improvement (31/73, 42.5% vs 21/74, 28.4%; adjusted odds ratio 1.56, 95% CI 1.19-2.05; P=.001). Anxiety outcomes followed a similar pattern, whereas pregnancy-related anxiety did not differ between groups. CONCLUSIONS: In this prespecified subgroup of pregnant women with ICD-10 affective or stress-related disorders, the eMBI was associated with clinically meaningful reductions in depressive symptoms from late pregnancy to 4-6 weeks post partum. Effects at 6 months post partum were attenuated and less stable across missing-data assumptions. These findings support eMBIs as a scalable, nonpharmacological adjunct to perinatal mental health care for women with affective or stress-related disorders, while confirmation in adequately powered trials with strategies to reduce postpartum attrition is warranted.

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PubMed2026

Age at menopause and subjective cognitive symptoms predict digital cognitive outcomes at the gynecological Well-Woman visit.

INTRODUCTION: Women are at increased risk for Alzheimer's Disease (AD). Growing evidence suggests that the menopausal transition may represent a vulnerable window for development of AD-related pathology. Yet, women are diagnosed with AD later than men. Conducting routine cognitive screenings and integrating information about both cognitive symptoms and age at menopause may help address sex-based disparities in detection and prevention. This study investigated whether subjective cognitive symptoms, in combination with age at menopause, were associated with performance on a digital cognitive task in postmenopausal women. METHODS: 183 postmenopausal women (mean age = 63.8, range = 45-85) were recruited after their Well-Woman visit. Participants completed the Screener for Cognitive Problems in Everyday Life (SCoPE) to assess subjective cognitive symptoms, followed by a sensitive measure of objective cognition: the Linus Health Digital Clock and Recall (DCR™). Information was also collected on age at menopause. We examined associations of subjective cognitive symptoms and age at menopause with digital cognitive performance, adjusting for age, education and depression. Model fit was evaluated using adjusted R2, AIC, and BIC. RESULTS: 48.1% of women reported one or more cognitive symptoms on the SCoPE. On objective testing, 73.2% scored in the normal range, 20.8% in the borderline range, and 6.0% in the impaired range. SCoPE total score was negatively associated with objective cognitive performance in adjusted models (B = -.12, p = .03). Age at menopause showed a significant quadratic association with cognitive performance (B = -0.006, p<.001). SCoPE total was not associated with DCR subtests, while age at menopause predicted both Delayed Recall and Clock Drawing. CONCLUSION: Subjective cognitive symptoms and age at menopause were associated with lower performance on a sensitive, objective cognitive test. Findings support routine cognitive screening and suggest that subjective cognitive symptoms as well as age at menopause are associated with cognitive function.

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PubMed2026

Assessment of atypical glandular cell interpretation in Pap tests using the Hologic Genius Digital Diagnostics System.

Atypical glandular cells (AGC) are a diagnostic challenge. The aim of this study was to evaluate the efficacy and diagnostic performance of AGC detection on the Hologic Genius Digital Diagnostics System (HGDDS). A retrospective analysis of 451 ThinPrep Pap cases was conducted, including 207 cases of AGC, 27 cases of high-grade squamous intraepithelial lesion (HSIL), 25 cases of low-grade squamous intraepithelial lesion (LSIL), and 192 benign cases. All AGC cases had follow-up histologic diagnoses, with 66 cases subsequently diagnosed as adenocarcinoma. The slides were randomized, scanned, and analyzed by the HGDDS. Patient age and HPV test results were provided to reviewers, an experienced cytologist, who screened the cases, followed by two cytopathologists who independently examined the cases on the HGDDS. Diagnostic concordance between the two cytopathologists indicated strong agreement (κ = 0.829). Sensitivity of AGC on Papanicolaou (Pap) tests for adenocarcinoma detection on HGDDS was 98.5% and 95.5%, respectively, comparable to the original ThinPrep interpretation (OTPI). Specificity for adenocarcinoma detection was significantly higher (84.6% and 85.6%) with the HGDDS than 27.7% with OTPI. Overall, the diagnostic performance for AGC/HSIL interpretation to detect CIN2/3/adenocarcinoma appeared to have improved with HGDDS compared with OTPI, particularly for specificity and positive predictive value (PPV). This is the first study evaluating AGC diagnosis using the HGDDS. The findings demonstrate that the sensitivity of adenocarcinoma detection as AGC on HGDDS is comparable to the ThinPrep Imaging System, but the specificity and PPV are improved. This suggests the potential of artificial intelligence to augment the performance of cervical cancer screening.

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PubMed2026

A pragmatic randomized controlled trial of self-directed online writing interventions for posttraumatic stress symptoms in a real-world digital setting.

Background: Public health and other large-scale crises, such as the COVID-19 pandemic, have intensified the global mental health burden, creating unprecedented demand for accessible interventions for posttraumatic stress symptoms (PTSS).Objective: We evaluated the feasibility and effectiveness of two self-directed online writing interventions embedded within China's WeChat ecosystem during the COVID-19 pandemic through a pragmatic randomised controlled trial.Methods: Between December 2021 and August 2022, 1,526 adults were screened for PTSS via a Tencent Medinfo Mini-Program. Eligible participants (n = 211) were randomised to Guided Narrative Technique-Writing (GNT-W, n = 100) or Expressive Writing (EW, n = 111). Both interventions comprised three self-directed daily writing sessions delivered entirely online without human support. Primary outcome was PTSD symptom severity (PTSD Checklist-Short), assessed at baseline, post-intervention, 2-week, and 1-month follow-ups.Results: While initial engagement followed typical digital health patterns (64.5% overall attrition), participants who initiated treatment showed strong adherence (77% completion). Both interventions were associated with significant within-group reductions in PTSS severity (GNT-W: b = -0.43, p = .023, d = -0.43; EW: b = -0.60, p = .001, d = -0.58), with no significant between-group difference (group × time: b = 0.18, p = .48). GNT-W did not confer additional benefit over EW protocol on PTSS severity.Conclusions: Both self-directed writing interventions were associated with within-group reductions in PTSS; without an inactive control condition, however, these changes cannot be firmly attributed to the interventions. GNT-W showed no advantage over the simpler EW protocol. These findings offer preliminary support for embedding scalable, low-barrier writing interventions in widely used digital platforms.Chinese Clinical Trial Registry: ChiCTR2000034836.

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PubMed2026

The Impact of Chatbot Type and Normative Messaging on Chatbot Usage Intention Based on the Health Technology Acceptance Model: Randomized Controlled Trial.

BACKGROUND: Digital health tools, such as health chatbots, may improve access to scalable health support, but adoption remains inconsistent. Existing models do not fully integrate technology acceptance factors with health motivation factors relevant to digital health use. OBJECTIVE: This study proposed and tested the health technology acceptance model and examined whether normative message framing and chatbot type were associated with health motivation, technology acceptance, and intention to use a health chatbot. METHODS: In October 2025, we conducted a 4 × 2 between-participants online experiment with 1000 US adults recruited from a nationally representative YouGov panel. Participants were randomized to 1 of 8 conditions varying norm message type (self-oriented, peer-oriented, expert-oriented, or family-oriented) and chatbot type (AI-powered or rule-based) in a cancer prevention and genetic risk information scenario. Outcomes included descriptive norms, injunctive norms, perceived susceptibility, perceived severity, perceived benefits, self-efficacy, perceived ease of use, trust, privacy concerns, and usage intention. Data were analyzed using a multivariate ANOVA with Bonferroni-adjusted post hoc tests and multiple linear regression. RESULTS: Peer-oriented and family-oriented messages produced higher usage intention than expert-oriented messages, and peer-oriented messages also increased descriptive norms, injunctive norms, self-efficacy, and trust. AI-powered chatbots were associated with higher usage intention (P=.02) and greater trust (P=.008) than rule-based chatbots. In regression analyses, the model explained 50.8% of the variance in usage intention. Usage intention was positively associated with descriptive norms (β=0.087; P=.003), injunctive norms (β=0.078; P=.009), perceived susceptibility (β=0.051; P=.03), perceived benefits (β=0.253; P<.001), and trust (β=0.33; P<.001), and negatively associated with perceived severity (β=-0.047; P=.049) and privacy concerns (β=-0.11; P<.001). Perceived ease of use and self-efficacy were not significant predictors. CONCLUSIONS: The health technology acceptance model was a useful framework for explaining the intention to use a health chatbot by combining technology acceptance and health motivation constructs. Both social design features and chatbot design features shaped adoption-related beliefs, with peer-oriented and family-oriented framing and AI-powered chatbots showing particular promise. Trust and privacy concerns remained central determinants of intended use.

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PubMed2026

The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures: A Systematic Review and Meta-analysis.

BACKGROUND: Current endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopic-based diagnostic sampling for indeterminant biliary strictures remain suboptimal. Artificial intelligence (AI)-based algorithms by means of computer vision in machine learning have been applied to cholangioscopy in an effort to improve diagnostic yield. The aim of this study was to perform a systematic review and meta-analysis to evaluate the diagnostic performance of AI-based diagnostic performance of AI-associated cholangioscopic diagnosis of indeterminant or malignant biliary strictures. METHODS: Individualized searches were developed in accordance with PRISMA and MOOSE guidelines, and meta-analysis according to Cochrane Diagnostic Test Accuracy working group methodology. A bivariate model was used to compute pooled sensitivity and specificity, likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristics curve (SROC). RESULTS: Five studies (n=675 lesions; a total of 2,685,674 cholangioscopic images) were included. All but one study analyzed a deep learning AI-based system using a convoluted neural network (CNN) with an average image processing speed of 30 to 60 frames per second. The pooled sensitivity and specificity were 95% (95% CI: 85-98) and 88% (95% CI: 76-94), with a diagnostic accuracy (SROC) of 97% (95% CI: 95-98). Sensitivity analysis of CNN studies (4 studies, 538 patients) demonstrated a pooled sensitivity, specificity, and accuracy (SROC) of 95% (95% CI: 82-99), 88% (95% CI: 72-95), and 97% (95% CI: 95-98), respectively. CONCLUSIONS: Artificial intelligence-based machine learning of cholangioscopy images appears to be a promising modality for the diagnosis of indeterminant and malignant biliary strictures.

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PubMed2026

One Year After a Cyberattack: Lessons Learned and Dosimetric Analysis of Contingency Radiotherapy Plans.

PURPOSE: Cyberattacks on health care institutions pose significant risks to patient care, particularly in radiotherapy departments, which are heavily reliant on digital systems. This study examines the impact of a ransomware attack on our hospital and evaluates the effectiveness of the contingency measures implemented to resume radiotherapy treatments. METHODS AND MATERIALS: Following the cyberattack, our radiotherapy department faced a complete shutdown. After an initial estimate considering a shutdown of several weeks, a contingency plan was executed, including manual patient data retrieval and collaboration with a backup hospital. Contingency plans were prepared and delivered within hours, despite a partial lack of information. These plans allowed some patients to restart treatment 3 days after the attack. A dosimetric analysis was performed for the contingency plans, including various pathologies, mainly glioblastoma, head and neck cancers, and lung cancer. We compared the original and contingency plans in terms of dose coverage to the clinical target volume, biological effective dose, and their clinical impact as assessed at the 1‑year follow‑up after the cyberattack. RESULTS: Treatments resumed within 12 days at our hospital. Patients with glioblastoma showed good target coverage because of generous margins, resulting in favorable outcomes. In head and neck cases, the lack of detailed imaging led to significant target volume misses, suggesting that more conservative initial treatments could have been beneficial. Lung cases demonstrated accurate peripheral lesion targeting but faced challenges in central lesions because of the absence of positron emission tomography information. In most cases, the approach of using a contingency plan, even with limited information, led to a higher biological effective dose than would have been achieved if treatment had been stopped until full recovery at our hospital. CONCLUSIONS: The study highlights the critical importance of robust contingency planning in radiotherapy departments, emphasizing the need for backup systems and tailored approaches based on tumor location and available diagnostic information. These lessons emphasize that preparedness for digital disruptions should not focus exclusively on information and technology infrastructure.

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PubMed2026

Unanticipated Effects of Parental Social Media Use: Guidance for Clinicians.

"Sharenting," the practice of parents posting photographs, videos, and information about their children on social media, has an ever-growing presence in modern society. However, researchers and the public are now recognizing the potential consequences of sharing, including creation of permanent digital footprints, strained familial relationships, and threats to children's safety. Despite this emerging evidence, no U.S. clinical or legal guidelines exist for parents on safe sharing. Visits with behavioral health providers and family physicians can serve as key points for intervention. This column aims to provide clinicians with a better understanding of sharenting and its potential effects on patients and families, guidance on discussing safe online sharing, and a tool for parents and other caregivers to use when deciding whether to post.

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PubMed2024

Promoters and Barriers of Vaccine Hesitancy.

This systematic review explores the psychological antecedents of Vaccine Hesitancy, a significant determinant of vaccination behavior. Following PRISMA guidelines, an extensive search was conducted starting from 1673 papers and resulting in 48 publications from various databases. The review identifies psychological factors, specifically cognitive, personality, experiential, and social factors contributing to hesitancy. Cognitive factors include health literacy, conspiracy beliefs, trust, and perceived risk. Personality traits such as extraversion, openness, and psychological capital impact hesitancy, while psychopathy increases it. Personal experiences, like perceived stress and racial discrimination, indirectly affect hesitancy. Social factors, including social relationships and norms, play a significant role in reducing hesitancy. Tailored interventions addressing these factors can enhance vaccine acceptance.

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PubMed2026

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS: In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74·1 months (IQR 68·3-75·4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS: Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0·84 [95% CI 0·79-0·88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11·6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0·41-0·93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0·36-0·48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (≥70·0%; mean absolute improvement 12·1 percentage points [SD 2·8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0·010). INTERPRETATION: Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING: None.

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