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      Visualizing Research Trends and Identifying Hotspots of Traditional Chinese Medicine (TCM) Nursing Technology for Insomnia: A 18-Years Bibliometric Analysis of Web of Science Core Collection

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          Abstract

          Objective

          To explore the research hotspot and frontier direction of TCM nursing of insomnia and provide reference for the follow-up study of the optimal scheme of TCM nursing of insomnia.

          Background

          Insomnia is a common sleep-wake disorder, affects 6–10% of adults and was associated with independent higher risks of cardiovascular disease and diabetes. TCM Nursing Techniques of insomnia has a long history and has shown a definite impact. However, it's still lack of analysis in the field of the most commonly used and effective techniques, as well as the co-morbidities associated with insomnia. Therefore, the database was searched and analyzed to find effective TCM Nursing Techniques for insomnia and related diseases related to insomnia.

          Method

          Randomized controlled trials on the intervention of TCM Nursing Techniques in insomnia were retrieved from Web of Science Core Collection and imported into CiteSpace 5.6.R5 visualization software. The works of literature were co-cited by keywords authors and institutions for visual analysis, and the co-morbidities associated with insomnia of TCM Nursing Techniques in literature was extracted manually. The symptoms of co-morbidities associated with insomnia were imported into Cytoscape 3.9.0 software and clustered by CytoHubba.

          Result

          As of October 20, 2021, the literature published in the last 20 years from Web of Science Core Collection was screened, and the publication period of the included literature was from 2004 to 2021. From 2016 to now, the total number of articles has been increasing. A total of 146 articles were included, and the highest production year was 2020. There is little cooperation between states, institutions, and authors. China (including Hong Kong and Taiwan) and Hong Kong Polytech University are leading countries and institutions in this area. MYUNGHAENG HUR is the most cited author, and J ALTERN COMPLEM MED is the most cited journal. According to cluster analysis and keyword frequency, auricular therapy, aromatherapy, and acupressure are the three most commonly used techniques. While the top five co-morbidities are fatigue, anxiety, depression, pain and hemodialysis. The three frontier topics and the main research directions are sleep quality, comorbid insomnia and clinical trial design.

          Conclusion

          We found that acupressure, aromatherapy, and auricular acupoint therapy are the most commonly used nursing methods of TCM to intervene in insomnia. However, these studies have limitations such as small sample size, lack of objectivity in evaluating sleep quality, and high heterogeneity of intervention measures, which are not conducive to forming TCM clinical nursing guidelines. Therefore, it is necessary to adopt objectified sleep quality evaluation methods, select suitable acupoints according to TCM theories, and design multi-center large-sample clinical trials based on the safety principle of randomized blind control. This study provides an in-depth perspective for insomnia research on TCM Nursing Techniques and includes information for follow-up research on TCM Nursing Techniques of insomnia.

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          Most cited references76

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          The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research

          Despite the prevalence of sleep complaints among psychiatric patients, few questionnaires have been specifically designed to measure sleep quality in clinical populations. The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire which assesses sleep quality and disturbances over a 1-month time interval. Nineteen individual items generate seven "component" scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for these seven components yields one global score. Clinical and clinimetric properties of the PSQI were assessed over an 18-month period with "good" sleepers (healthy subjects, n = 52) and "poor" sleepers (depressed patients, n = 54; sleep-disorder patients, n = 62). Acceptable measures of internal homogeneity, consistency (test-retest reliability), and validity were obtained. A global PSQI score greater than 5 yielded a diagnostic sensitivity of 89.6% and specificity of 86.5% (kappa = 0.75, p less than 0.001) in distinguishing good and poor sleepers. The clinimetric and clinical properties of the PSQI suggest its utility both in psychiatric clinical practice and research activities.
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            CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature

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              European guideline for the diagnosis and treatment of insomnia

              This European guideline for the diagnosis and treatment of insomnia was developed by a task force of the European Sleep Research Society, with the aim of providing clinical recommendations for the management of adult patients with insomnia. The guideline is based on a systematic review of relevant meta-analyses published till June 2016. The target audience for this guideline includes all clinicians involved in the management of insomnia, and the target patient population includes adults with chronic insomnia disorder. The GRADE (Grading of Recommendations Assessment, Development and Evaluation) system was used to grade the evidence and guide recommendations. The diagnostic procedure for insomnia, and its co-morbidities, should include a clinical interview consisting of a sleep history (sleep habits, sleep environment, work schedules, circadian factors), the use of sleep questionnaires and sleep diaries, questions about somatic and mental health, a physical examination and additional measures if indicated (i.e. blood tests, electrocardiogram, electroencephalogram; strong recommendation, moderate- to high-quality evidence). Polysomnography can be used to evaluate other sleep disorders if suspected (i.e. periodic limb movement disorder, sleep-related breathing disorders), in treatment-resistant insomnia, for professional at-risk populations and when substantial sleep state misperception is suspected (strong recommendation, high-quality evidence). Cognitive behavioural therapy for insomnia is recommended as the first-line treatment for chronic insomnia in adults of any age (strong recommendation, high-quality evidence). A pharmacological intervention can be offered if cognitive behavioural therapy for insomnia is not sufficiently effective or not available. Benzodiazepines, benzodiazepine receptor agonists and some antidepressants are effective in the short-term treatment of insomnia (≤4 weeks; weak recommendation, moderate-quality evidence). Antihistamines, antipsychotics, melatonin and phytotherapeutics are not recommended for insomnia treatment (strong to weak recommendations, low- to very-low-quality evidence). Light therapy and exercise need to be further evaluated to judge their usefulness in the treatment of insomnia (weak recommendation, low-quality evidence). Complementary and alternative treatments (e.g. homeopathy, acupuncture) are not recommended for insomnia treatment (weak recommendation, very-low-quality evidence).
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                Author and article information

                Contributors
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                31 March 2022
                2022
                : 13
                : 816031
                Affiliations
                [1] 1School of Nursing, Beijing University of Chinese Medicine , Beijing, China
                [2] 2School of Traditional Chinese Medicine, Beijing University of Chinese Medicine , Beijing, China
                [3] 3School of Management, Beijing University of Chinese Medicine , Beijing, China
                Author notes

                Edited by: Kittisak Sawanyawisuth, Khon Kaen University, Thailand

                Reviewed by: David Neubauer, Johns Hopkins Medicine, United States; Hantong Hu, Zhejiang Chinese Medical University, China; Yonggang Zhang, Sichuan University, China; Aicheng Yang, The First Affiliated Hospital of Jinan University, China; Sonia Sonia, Guru Angad Dev Veterinary and Animal Sciences University, India

                *Correspondence: Xiangdi Liu 13810693238@ 123456126.com

                This article was submitted to Sleep Disorders, a section of the journal Frontiers in Neurology

                †These authors share first authorship

                Article
                10.3389/fneur.2022.816031
                9009417
                35432182
                f53cbd6e-8a9b-4361-83e2-8fd4d0b3966d
                Copyright © 2022 Wang, Chen, Zhai, Chu, Liu and Ma.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 24 November 2021
                : 04 February 2022
                Page count
                Figures: 8, Tables: 7, Equations: 0, References: 77, Pages: 16, Words: 9773
                Categories
                Neurology
                Original Research

                Neurology
                insomnia,tcm,nursing,technique,visualization analysis,bibliometric
                Neurology
                insomnia, tcm, nursing, technique, visualization analysis, bibliometric

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