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  1. Article ; Online: Investigation of COVID-19-related symptoms based on factor analysis.

    Luo, Yueming / Wu, Juan / Lu, Jiayan / Xu, Xi / Long, Wen / Yan, Guangjun / Tang, Mengya / Zou, Li / Xu, Dazhi / Zhuo, Ping / Si, Qin / Zheng, Xinping

    Annals of palliative medicine

    2020  Volume 9, Issue 4, Page(s) 1851–1858

    Abstract: ... related to symptoms of COVID-19. Based on the combination of factors, the clinical types of the factors ... of the clinical symptoms of COVID-19, providing a new idea for the comprehensive analysis of clinical symptoms. ... correlation analysis of symptoms was performed.: Results: Factor analysis showed that the clinical symptoms of COVID ...

    Abstract Background: The application of factor analysis in the study of the clinical symptoms of coronavirus disease 2019 (COVID-19) was investigated, to provide a reference for basic research on COVID-19 and its prevention and control.
    Methods: The data of 60 patients with COVID-19 in Jingzhou Hospital of Traditional Chinese Medicine and the Second People's Hospital of Longgang District in Shenzhen were extracted using principal component analysis. Factor analysis was used to investigate the factors related to symptoms of COVID-19. Based on the combination of factors, the clinical types of the factors were defined according to our professional knowledge. Factor loadings were calculated, and pairwise correlation analysis of symptoms was performed.
    Results: Factor analysis showed that the clinical symptoms of COVID-19 cases could be divided into respiratory-digestive, neurological, cough-wheezing, upper respiratory, and digestive symptoms. Pairwise correlation analysis showed that there were a total of eight pairs of symptoms: fever-palpitation, coughexpectoration, expectoration-wheezing, dry mouth-bitter taste in the mouth, poor appetite-fatigue, fatiguedizziness, diarrhea-palpitation, and dizziness-headache.
    Conclusions: The symptoms and syndromes of COVID-19 are complex. Respiratory symptoms dominate, and digestive symptoms are also present. Factor analysis is suitable for studying the characteristics of the clinical symptoms of COVID-19, providing a new idea for the comprehensive analysis of clinical symptoms.
    MeSH term(s) Adult ; Aged ; Aged, 80 and over ; COVID-19 ; Coronavirus Infections/complications ; Coronavirus Infections/therapy ; Digestive System Diseases/etiology ; Factor Analysis, Statistical ; Female ; Humans ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral/complications ; Pneumonia, Viral/therapy ; Respiratory Tract Diseases/etiology ; Young Adult
    Keywords covid19
    Language English
    Publishing date 2020-06-22
    Publishing country China
    Document type Journal Article
    ZDB-ID 2828544-X
    ISSN 2224-5839 ; 2224-5820
    ISSN (online) 2224-5839
    ISSN 2224-5820
    DOI 10.21037/apm-20-1113
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Investigation of COVID-19-related symptoms based on factor analysis

    Luo, Yueming / Wu, Juan / Lu, Jiayan / Xu, Xi / Long, Wen / Yan, Guangjun / Tang, Mengya / Zou, Li / Xu, Dazhi / Zhuo, Ping / Si, Qin / Zheng, Xinping

    Ann Palliat Med

    Abstract: ... principal component analysis. Factor analysis was used to investigate the factors related to symptoms of COVID-19. Based ... Factor analysis showed that the clinical symptoms of COVID-19 cases could be divided into respiratory-digestive ... for studying the characteristics of the clinical symptoms of COVID-19, providing a new idea for the comprehensive analysis ...

    Abstract BACKGROUND: The application of factor analysis in the study of the clinical symptoms of coronavirus disease 2019 (COVID-19) was investigated, to provide a reference for basic research on COVID-19 and its prevention and control. METHODS: The data of 60 patients with COVID-19 in Jingzhou Hospital of Traditional Chinese Medicine and the Second People's Hospital of Longgang District in Shenzhen were extracted using principal component analysis. Factor analysis was used to investigate the factors related to symptoms of COVID-19. Based on the combination of factors, the clinical types of the factors were defined according to our professional knowledge. Factor loadings were calculated, and pairwise correlation analysis of symptoms was performed. RESULTS: Factor analysis showed that the clinical symptoms of COVID-19 cases could be divided into respiratory-digestive, neurological, cough-wheezing, upper respiratory, and digestive symptoms. Pairwise correlation analysis showed that there were a total of eight pairs of symptoms: fever-palpitation, coughexpectoration, expectoration-wheezing, dry mouth-bitter taste in the mouth, poor appetite-fatigue, fatiguedizziness, diarrhea-palpitation, and dizziness-headache. CONCLUSIONS: The symptoms and syndromes of COVID-19 are complex. Respiratory symptoms dominate, and digestive symptoms are also present. Factor analysis is suitable for studying the characteristics of the clinical symptoms of COVID-19, providing a new idea for the comprehensive analysis of clinical symptoms.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #614414
    Database COVID19

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  3. Article ; Online: Predictors of nonresponse and drop-out among children and adolescents receiving TF-CBT: investigation of client-, therapist-, and implementation factors.

    Skar, Ane-Marthe Solheim / Braathu, Nora / Jensen, Tine K / Ormhaug, Silje Mørup

    BMC health services research

    2022  Volume 22, Issue 1, Page(s) 1212

    Abstract: ... post-traumatic stress symptoms (PTSS), therapist (education), and implementation strategy factors (high ... training during the Covid-19 pandemic are associated with nonresponse (above clinical PTSS level ... treatment response and prevent drop-out among children receiving evidence-based treatment. This study ...

    Abstract Background: There is a paucity of evidence about effective implementation strategies to increase treatment response and prevent drop-out among children receiving evidence-based treatment. This study examines patient, therapist, and implementation factors and their association to nonresponse and drop-out among youth receiving Trauma-Focused Cognitive Behavioral Therapy (TF-CBT).
    Methods: Youth (n = 1240) aged 6-18 (M = 14.6) received TF-CBT delivered by 382 TF-CBT therapists at 66 clinics. Odds ratio analyses were used to investigate whether pretreatment child (age, gender, number of trauma experiences, post-traumatic stress symptoms (PTSS), therapist (education), and implementation strategy factors (high-low, low-low, low-high intensity therapist and leadership training respectively) or tele-mental health training during the Covid-19 pandemic are associated with nonresponse (above clinical PTSS level post-treatment) and drop-out (therapist-defined early termination). Fidelity checks were conducted to ensure that TF-CBT was used consistently.
    Results: One fourth of the children (24.4%) were nonresponders and 13.3 percent dropped out. Exposure to three or more traumatic experiences were related to nonresponse and drop-out. Higher baseline PTSS was related to a higher probability of nonresponse. There was no effect of therapist education or child gender on nonresponse and drop-out, whereas children over 15 years had a higher likelihood of both. After controlling for baseline PTSS, the effect of age on nonresponse was no longer significant. Drop-out was related to fewer sessions, and most dropped out during the first two phases of TF-CBT. Fidelity was high throughout the different implementation phases. High-intensity therapist training was related to a lower probability of both nonresponse and drop-out, whereas low therapist and leadership training were related to a higher likelihood of both. Multivariate analysis revealed higher child age and higher PTSS baseline scores as significant predictors of nonresponse, and number of trauma experiences (> = 3) at baseline as the only predictor of drop-out.
    Conclusions: High-intensity therapist training seem key to prevent patient nonresponse and drop-out. Leadership training might positively affect both, although not enough to compensate for less intensive therapist training. More complex cases (higher PTSS and exposure to more traumas) predict nonresponse and drop-out respectively, which underscores the importance of symptom assessment to tailor the treatment. The lack of predictive effect of therapist education increases the utilization of TF-CBT.
    Trial registration: Retrospectively registered in ClinicalTrials, ref. nr. NCT05248971.
    MeSH term(s) Adolescent ; Allied Health Personnel ; COVID-19 ; Child ; Cognitive Behavioral Therapy ; Educational Status ; Humans ; Pandemics ; Stress Disorders, Post-Traumatic/prevention & control ; Treatment Outcome
    Language English
    Publishing date 2022-09-29
    Publishing country England
    Document type Journal Article
    ZDB-ID 2050434-2
    ISSN 1472-6963 ; 1472-6963
    ISSN (online) 1472-6963
    ISSN 1472-6963
    DOI 10.1186/s12913-022-08497-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A Follow-Up Investigation of Mental Health Among Discharged COVID-19 Patients in Wuhan, China

    Li Li / Michael Shengtao Wu / Junxiu Tao / Weijun Wang / Jing He / Ru Liu / Juan Guo / Yun Chen / Kejian Li / Shilong Li / Bo Qi / Buxin Han

    Frontiers in Public Health, Vol

    2021  Volume 9

    Abstract: ... to the younger. In addition, the severity of COVID-19 revealed no significant relationship to symptoms of poor ... Questionnaire (PHQ-9) were used to measure the symptoms of insomnia, anxiety, and depression in 782 COVID-19 ... quarantine to home isolation, all the mental symptoms were significantly alleviated. Based on a follow-up ...

    Abstract Objective: To understand the mental health status and its risk factors among discharged COVID-19 patients during the first month of centralized quarantine and the subsequent home isolation.Methods: The scales of the Insomnia Severity Index (ISI), General Anxiety Disorder (GAD-7), and Patient Health Questionnaire (PHQ-9) were used to measure the symptoms of insomnia, anxiety, and depression in 782 COVID-19 patients during the first month of centralized quarantine (March 16 to 26, 2020) and then during home isolation (April 3 to 10, 2020).Results: During the centralized quarantine, the prevalence rates of insomnia, anxiety, and depressive symptoms were 44.37, 31.59, and 27.62%, respectively, and those during the home isolation decreased significantly at 27.11, 17.26, and 16.11%, respectively. In both waves, women showed a higher prevalence of symptoms of poor mental health compared to men, and middle-aged (40–59 years old) and elderly (≥60 years old) showed a higher risk of symptoms of poor mental health compared to the younger. In addition, the severity of COVID-19 revealed no significant relationship to symptoms of poor mental health, whereas, the interaction analysis revealed that those with other underlying diseases showed more symptoms of poor mental health during the centralized quarantine and a greater decrease during the follow-up home isolation.Conclusion: The discharged COVID-19 patients suffered from mental health problems such as, insomnia, depression, and anxiety, and this was especially so for women, the middle-aged and elderly, and those with underlying diseases, but along with the rehabilitation and the environmental change from centralized quarantine to home isolation, all the mental symptoms were significantly alleviated. Based on a follow-up investigation, the current results provide critical evidence for mental health and early rehabilitation upon the discharged COVID-19 patients.
    Keywords COVID-19 ; quarantine ; insomnia ; anxiety ; depression ; Public aspects of medicine ; RA1-1270
    Subject code 150
    Language English
    Publishing date 2021-04-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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