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Consumer-Grade Neurofeedback With Mindfulness Meditation: Meta-Analysis
We conducted 2 different approaches, trim-and-fill, which corrects for publication bias in small samples, and 3-parameter selection models which explicitly model the proportion of studies below a p-threshold. We considered applying p-curve approaches, but they require at least 3 significant findings which was not the case for multiple models.
A PRISMA flow diagram is shown in Figure 2 (PRISMA checklist provided in Multimedia Appendix 2).
J Med Internet Res 2025;27:e68204
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The statistical analysis showed a significant but low Pearson correlation between NPRS and pain surface index (r=0.14; 95% CI 0.06-0.21; P
Study patient characteristics.
a PSPS-T2: persistent spinal pain syndrome type 2.
b CRPS: complex regional pain syndrome.
Pain intensity (NPRSa), pain surface, and pain typology.
a NPRS: Numeric Pain Rating Scale.
J Med Internet Res 2025;27:e62786
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Based on this medium effect size, at least 98 participants are needed to detect a significant group × time interaction effect (P
Based on prior trials of Tuned In, we expect a high retention rate among youth [6]. However, some attrition may occur among adolescents [25]. Even with that attrition rate, we anticipate retaining at least 30 adolescents at the postintervention stage, providing sufficient data from this pilot study to inform future large-scale trials.
JMIR Res Protoc 2025;14:e67764
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Background characteristics of nursing home residents in both the experimental and control groups who completed the semistructured interviews after the 4-week intervention.
a Significance level set at P
b Chi-square test with Yates continuity correction.
c Not applicable.
d GDS: Global Deterioration Scale.
JMIR Form Res 2025;9:e56586
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A recent systematic review and meta-analysis of randomized controlled trials reported that using mobile app-assisted self-care interventions was associated with significant reductions in both systolic (standardized mean difference −0.17, P=.02) and diastolic (standardized mean difference −0.17, P=.02) blood pressure (BP) [4].
J Med Internet Res 2025;27:e59275
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Next, we concatenated the extracted elements (ie, the answers to the aforementioned 4 questions [A]) with the following prompt (P)—“Let’s integrate the above information and summarize this patient comment:”—along with the patient comment (C) to prompt the LLM for patient comment summary generation. The input to the LLMs was [A; P; C], and the output was the final summary.
The advanced prompting techniques used in this study were applied in combination with each instruction-based model.
JMIR Med Inform 2025;13:e62909
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