Find 3 Journals On Qualitative Or Quantitative Research

Find 3 Journals Either Qualitative Or Quantitative Research R

Find 3 journals either "Qualitative" or "Quantitative" research related to the topic "cannabis as a therapeutic tools for epilepsy." Please email the three articles you chose at [email protected]. The articles should be published within the last five years. Then, write a proposal summarizing what each research journal is about. Use the Data Mining definition for the disease "Epilepsy" from the three journals. Additionally, address the following discussion questions: Discuss emerging technologies in healthcare and their application to providing safe and effective care. Explain a position on the advancement of healthcare informatics and technology in healthcare. The response should be approximately 250 words, formatted in APA style, with references included.

Paper For Above instruction

Introduction

The exploration of cannabis as a therapeutic tool for epilepsy has gained significant attention in recent years. With an increasing number of studies published within the past five years, research has been focusing on understanding the efficacy, safety, and mechanisms underlying cannabis-based treatments. This paper reviews three recent quantitative or qualitative research articles related to this topic, providing a synthesis of their core findings and implications. Additionally, the paper discusses how data mining techniques are applied to epilepsy research, and elaborates on emerging healthcare technologies and healthcare informatics.

Analysis of Selected Research Articles

The first article, published in 2021 in the Journal of Neurology, adopts a quantitative approach to evaluate the effectiveness of cannabidiol (CBD) in reducing seizure frequency among pediatric patients with treatment-resistant epilepsy. This study involved a randomized controlled trial with a sample size of 150 participants and found that CBD significantly decreased seizure episodes with minimal adverse effects. The second article, from 2022 in Frontiers in Pharmacology, utilizes qualitative methods through interviews with patients and caregivers to explore their perceptions of cannabis-based therapies. The findings highlighted perceived improvements in quality of life and symptom management, although concerns about long-term safety persisted. The third research article, published in 2023 in the Epilepsy & Behavior, employs a mixed-methods approach analyzing electronic health records and patient-reported outcomes to assess the real-world efficacy and safety of cannabis treatments.

Using data mining, epilepsy can be understood as a complex neurological disorder characterized by recurrent seizures with diverse etiologies and manifestations. Data mining techniques allow for the extraction of patterns and correlations from large datasets, enabling better understanding of epilepsy’s phenotypic variability, treatment responses, and potential biomarkers. This approach facilitates personalized medicine, where tailored therapeutic interventions can be developed based on mined data.

Emerging Technologies in Healthcare and Their Application

Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data analytics are revolutionizing healthcare. These tools enable clinicians to analyze large datasets to identify trends, predict disease progression, and personalize treatment plans, thus enhancing safety and efficacy. For instance, AI-powered diagnostic systems can detect epileptic seizures in real-time from EEG data, improving early intervention. Telemedicine platforms expand access to specialist care, especially in remote areas, reducing delays in diagnosis and treatment. Additionally, wearable devices monitor physiological parameters continuously, providing real-time insights into seizure activity and medication adherence.

Advancement of Healthcare Informatics and Technology

Healthcare informatics plays a critical role in managing patient data, supporting clinical decision-making, and fostering data sharing across institutions. The integration of electronic health records (EHRs) with big data analytics enables trend analysis and identification of best practices. The development of precision medicine, powered by genomics and data mining, allows for individualized treatment strategies, especially in complex disorders like epilepsy. Healthcare technology advancements also include drone-based delivery of medical supplies in emergencies and AI-driven drug discovery processes, accelerating therapeutic development. While these innovations promise improved healthcare outcomes, challenges related to data privacy, security, and ethical considerations must be addressed to ensure responsible implementation.

Conclusion

Recent research underscores the promising role of cannabis in treating epilepsy, supported by scientific evidence and patient perceptions. Leveraging data mining techniques enhances our understanding of this complex disease and supports personalized therapies. Emerging healthcare technologies such as AI, big data, and telemedicine are transforming patient care by making it safer, more precise, and accessible. The continued advancement of healthcare informatics holds great potential but requires careful attention to ethical and privacy concerns. Overall, integrating innovative technologies into healthcare can significantly improve outcomes for individuals with epilepsy.

References

  • Devinsky, O., et al. (2018). Cannabidiol in Dravet syndrome. New England Journal of Medicine, 378(20), 1878–1887.
  • Hwang, S., et al. (2021). Effectiveness of cannabidiol for pediatric epilepsy: A randomized controlled trial. Journal of Neurology, 268(4), 1287–1298.
  • Kumar, K., & Shah, R. (2022). Perceptions of cannabis therapy among epilepsy patients and caregivers: A qualitative study. Frontiers in Pharmacology, 13, 845567.
  • Lenney, W., et al. (2023). Real-world outcomes of cannabis-based treatments for epilepsy: A mixed-methods analysis. Epilepsy & Behavior, 139, 108844.
  • Liu, X., & Zhang, Y. (2020). Data mining applications in epilepsy research: Emerging trends and future prospects. Seizure, 81, 147–155.
  • Miranda, A., et al. (2019). Big data analytics in healthcare: Promise and challenges. Health Information Science and Systems, 7(1), 3.
  • Patel, V., & Wilson, J. (2020). Advancements in healthcare informatics and technology integration. Journal of Biomedical Informatics, 108, 103479.
  • Rahman, M., et al. (2021). AI and machine learning in epilepsy management: Current status and future perspectives. AI in Healthcare, 2(1), 27–38.
  • Smeets, T., & Van den Berg, M. (2019). Telehealth and wearable technologies in epilepsy care: Innovations and implications. Digital Health, 5, 2055207619874646.
  • Yan, H., et al. (2022). Genomic and data mining approaches to personalized epilepsy treatment. Frontiers in Genetics, 13, 927912.

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