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Skip search results from other journals and go to results- 714 Journal of Medical Internet Research
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history and city, Zambia, 2021.
a Previously captured represents people who inject drugs who participated in the biobehavioral survey (capture 3) and reported receiving an object in captures 1 or 2.
b CI: confidence interval.
c P values computed using Kruskal test for difference in medians, and a survey-weighted quasi-binomial general linear model for categorical variables.
d Median network size was 5, 4.5, and 3 in Livingstone, Lusaka, and Ndola, respectively.
e Responses not mutually exclusive.
f Indicates that P
JMIR Public Health Surveill 2025;11:e66551
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In grade 8, 24.6% learned of EVALI from their parents, compared to 9.1% in grade 12 (P
Table 3 shows what students believed caused EVALI. Overall, most who had heard about the condition believed nicotine was the cause (55.0%). More than 1 in 5 (22.1%) said they did not know. Marijuana was chosen by 11.1%, followed by other chemicals (4.7%). Similar percentages thought flavorings (3.5%) or other things (3.6%) were the cause.
J Med Internet Res 2025;27:e69151
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Chi-square statistics and P values were calculated. A Bonferroni correction was applied to account for multiple comparisons, adjusting the significance threshold to .002 (.05/23). P values less than .001 were reported as P
For all domains, the following statistics were generated along with their 95% CI values: overall agreement (or overall accuracy), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Cohen κ.
JMIR Form Res 2025;9:e58097
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Reach-Accept testing in the Chatbot arm was lower than in SMS text messaging (174/1051, 16.6% vs 555/1066, 52.1%; a RR 0.317, 98.33% CI 0.27‐0.38; P
Reach-Accept testing was higher among participants messaged every 10 days vs every 30 days (860/15,717, 5.5% vs 752/15,722, 4.8%; a RR 1.144, 97.5% CI 1.03‐1.28; P=.01; Table 2), and lower if the participants were offered access to PN compared with those in the no PN condition (680/15,718, 4.3% vs 932/15,721, 5.9%; a RR 0.729, 97.5% CI 0.65‐0.81; P
Out of 2117 participants
J Med Internet Res 2025;27:e74145
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Figure 5 and Multimedia Appendix 4 show significant interactions between the algorithm applied and all key sleep metrics across quartiles (P
Boxplots of paired differences between user-centric (TSP) and calendar-relative (is Main Sleep) algorithms for each of the key hypothesized sleep metrics across the quartiles of variation from typical sleep patterns. Box bounds, midline, and whiskers represent the IQR, median, and 1.5 × IQR, respectively.
J Med Internet Res 2025;27:e71718
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Game-Based Social-Emotional Learning for Youth: School-Based Qualitative Analysis of Brain Agents
JMIR Form Res 2025;9:e67550
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