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Skip search results from other journals and go to results- 158 Journal of Medical Internet Research
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Comments or replies that were coded as not relevant and excluded from further analysis included ones that mentioned the docuseries but not NTPs (eg, “It’s rare to see such a well-structured criticism of Australia’s public policy. Kudos to Netflix.”) and comments or replies that mentioned substances other than NTPs (eg, “When are we going to get a documentary that shows why people should not use marijuana or drink alcohol?”).
JMIR Form Res 2025;9:e76737
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Looking beyond these top 5 features, we can see that several PHQ-9 items, additional GAD-7 and PSS-4 items, family history of anxiety disorder, functional impairment, and diagnosis of disorders (eg, eating and psychotic) also contribute to the prediction. Figure S1 in Multimedia Appendix 1 shows the SHAP summary plot for the GAD-7 model.
This model takes only the first 2 GAD-7 items as input rather than the entire questionnaire.
J Med Internet Res 2025;27:e72669
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Of the 17 new research questions, the steering committee agreed that 4 (24%) matched (see Multimedia Appendix 16 for details). Of these 4 questions, 3 (75%) were considered effectiveness questions and moved on to action 11.
This process started in February 2025 with the clinical experts brainstorming health outcomes for each of the 3 effectiveness questions.
For the first question—“Should inhaled sedatives vs intravenous sedatives be used in difficult to sedate critically ill pediatric patients?”
JMIR Res Protoc 2025;14:e67930
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Practice personnel can interact with the dashboard using additional actions, such as “drill-down views” to view patient-level data on the selected measures or “drill-down exports” to download patient-level data for offline access (see Appendix A in Multimedia Appendix 1).
They can generate performance summary reports for selected quality measures or across multiple measures.
Dashboard audit log files contain records of every session and action performed on the RISE dashboard.
J Med Internet Res 2025;27:e72709
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To increase user engagement, the avatar was also given various gestures and expressions depending on the status of task completion (see Multimedia Appendix 3).
During this phase, we also determined other key components of the chatbot, such as its overall esthetics, its technical specifications, and the frequency of reminders sent to participants. All participants received activity-specific reminders at the beginning of the day (ie, 10 AM) on which the activity was scheduled.
JMIR Form Res 2025;9:e73563
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Large Language Models in Nursing Education: Concept Analysis
Instead, empirical referents or ways in which we see LLMs being used in nursing education will be discussed. This adaptation allows the concept analysis to provide more actionable insights in the field of nursing where practical application is critical [58]. This adjustment aligns with Rodgers’ [23] framework as the method is inherently flexible and encourages adaptation to the concept’s dynamic nature [23,59].
JMIR Nursing 2025;8:e77948
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Of these advertisements, 6 were co-developed with the Public and Patient Involvement (PPI) group, and one was suggested by a study co-investigator (see development of our recruitment and retention strategy for detail on how these advertisements were selected [19]). This set of advertisements was edited during recruitment to reflect the increasing incentive amount being offered.
J Med Internet Res 2025;27:e71611
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This approach allows for a more intuitive understanding of the readability of Chat GPT-generated responses in the context of patient education (see Table 1 for details).
Interpretation of readability scores with estimated educational level: Modified Flesch Reading Ease (FRE) for German and 4th Vienna Formula (WSTF).
a FRE: Modified Flesch Reading Ease.
b WSTF: 4th Vienna Formula.
JMIR Cancer 2025;11:e69783
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See the participant flowchart in Figure 4. On the basis of the screening assessments, 52 (50%) eligible participants were invited to take part in the RCT, and ultimately 45 (NIH: n=33, 73%; HVL: n=5, 11%; NTNU: n=7, 15%) were included and underwent a baseline visit (T1). Following this, they were randomly allocated to 1 of the 2 groups: 24 (53%) to training and 21 (47%) to control.
JMIR Res Protoc 2025;14:e70125
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Many felt that regular check-ins and clearer communication could have improved their engagement and overall experience:
Yeah, I feel like that’s, that’s, that would help the study be so much more successful or everybody's feeling on the same page, just because — I mean, not saying that it's not successful now, but I feel like, you know, if you have people checking me in frequently and letting you know, hey, you know, you had this option, this option, this option, you maybe should try it out, see if this helps
JMIR Hum Factors 2025;12:e73719
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