Psychological Distress Among Healthcare Providers During the COVID-19 Pandemic in Gaza Strip: A Cross-sectional Study

The aim of this study was to determine healthcare providers’ knowledge and practices about dysphagia. A descriptive cross-sectional study was carried out based on a self-administered and anonymous questionnaire addressed to healthcare providers in Spain. A total of 396 healthcare providers participated in the study. Of these, 62.3% knew the definition of dysphagia as a swallowing disorder. In addition, up to 39.2% of the participants reported that they did not know whether the EatingAssessmentTool (EAT-10) dysphagia screening test was usedin their own clinical settings. Similarly, up to 49.1% of them did not know the ClinicalExaminationVolume-Viscosity (MECV-V) method. Nearly all participants (98.8%) reported that thickeners must be used forall liquids administered to patients. A higher percentage of respondents based the choice of texture on patient’s tolerance (78.2%) rather than on the MECV-V result (17.3%). In addition,76.4% of the professionals had witnessed a bronchoaspiration; after it, 44.4% (n = 175) of them reported the appearance of pneumonia, and 14.5% (n = 57) the death of the patient (p = 0.005). The participants revealeda moderate/low knowledge ofthe definition, diagnosis, and clinical management of liquid dysphagia, which indicates some room for improvements.

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Comparison of predicted psychological distress among workers between artificial intelligence and psychiatrists: a cross-sectional study in Tsukuba Science City, Japan

BMJ Open ◽

10.1136/bmjopen-2020-046265 ◽

2021 ◽

Vol 11 (6) ◽

pp. e046265

Author(s):

Shotaro Doki ◽

Shinichiro Sasahara ◽

Daisuke Hori ◽

Yuichi Oi ◽

Tsukasa Takahashi ◽

...

Keyword(s):

Neural Network ◽

Artificial Intelligence ◽

Psychological Distress ◽

Cross Sectional Study ◽

Sectional Study ◽

Cross Sectional ◽

Explanatory Variables ◽

The Neural Network ◽

Significant Difference ◽

Total Data

ObjectivesPsychological distress is a worldwide problem and a serious problem that needs to be addressed in the field of occupational health. This study aimed to use artificial intelligence (AI) to predict psychological distress among workers using sociodemographic, lifestyle and sleep factors, not subjective information such as mood and emotion, and to examine the performance of the AI models through a comparison with psychiatrists.DesignCross-sectional study.SettingWe conducted a survey on psychological distress and living conditions among workers. An AI model for predicting psychological distress was created and then the results were compared in terms of accuracy with predictions made by psychiatrists.ParticipantsAn AI model of the neural network and six psychiatrists.Primary outcomeThe accuracies of the AI model and psychiatrists for predicting psychological distress.MethodsIn total, data from 7251 workers were analysed to predict moderate and severe psychological distress. An AI model of the neural network was created and accuracy, sensitivity and specificity were calculated. Six psychiatrists used the same data as the AI model to predict psychological distress and conduct a comparison with the AI model.ResultsThe accuracies of the AI model and psychiatrists for predicting moderate psychological distress were 65.2% and 64.4%, respectively, showing no significant difference. The accuracies of the AI model and psychiatrists for predicting severe psychological distress were 89.9% and 85.5%, respectively, indicating that the AI model had significantly higher accuracy.ConclusionsA machine learning model was successfully developed to screen workers with depressed mood. The explanatory variables used for the predictions did not directly ask about mood. Therefore, this newly developed model appears to be able to predict psychological distress among workers easily, regardless of their subjective views.

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A cross‐sectional study of infection control measures against COVID‐19 and psychological distress among Japanese workers

Journal of Occupational Health ◽

10.1002/1348-9585.12259 ◽

2021 ◽

Vol 63 (1) ◽

Author(s):

Yoshino Yasuda ◽

Tomohiro Ishimaru ◽

Masako Nagata ◽

Seiichiro Tateishi ◽

Hisashi Eguchi ◽

...

Keyword(s):

Psychological Distress ◽

Infection Control ◽

Cross Sectional Study ◽

Control Measures ◽

Sectional Study ◽

Cross Sectional ◽

Infection Control Measures ◽

Japanese Workers

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Perspectives of Healthcare Professionals Regarding Factors Associated with Antimicrobial Resistance (AMR) and Their Consequences: A Cross Sectional Study in Eastern Province of Saudi Arabia

Antibiotics ◽

10.3390/antibiotics10070878 ◽

2021 ◽

Vol 10 (7) ◽

pp. 878

Author(s):

Mohamed A. Baraka ◽

Amany Alboghdadly ◽

Samar Alshawwa ◽

Asim Ahmed Elnour ◽

Hassan Alsultan ◽

...

Keyword(s):

Antimicrobial Resistance ◽

Inappropriate Prescribing ◽

Healthcare Providers ◽

Cross Sectional Study ◽

Sectional Study ◽

Key Factors ◽

Eastern Province ◽

Cross Sectional ◽

Factors Associated ◽

Factors Influencing

Factors reported in the literature associated with inappropriate prescribing of antimicrobials include physicians with less experience, uncertain diagnosis, and patient caregiver influences on physicians’ decisions. Monitoring antimicrobial resistance is critical for identifying emerging resistance patterns, developing, and assessing the effectiveness of mitigation strategies. Improvement in prescribing antimicrobials would minimize the risk of resistance and, consequently, improve patients’ clinical and health outcomes. The purpose of the study is to delineate factors associated with antimicrobial resistance, describe the factors influencing prescriber’s choice during prescribing of antimicrobial, and examine factors related to consequences of inappropriate prescribing of antimicrobial. A cross-sectional study was conducted among healthcare providers (190) in six tertiary hospitals in the Eastern province of Saudi Arabia. The research panel has developed, validated, and piloted survey specific with closed-ended questions. A value of p < 0.05 was considered to be statistically significant. All data analysis was performed using the Statistical Package for Social Sciences (IBM SPSS version 23.0). 72.7% of the respondents have agreed that poor skills and knowledge are key factors that contribute to the inappropriate prescribing of antimicrobials. All of the respondents acknowledged effectiveness, previous experience with the antimicrobial, and reading scientific materials (such as books, articles, and the internet) as being key factors influencing physicians’ choice during antimicrobial prescribing. The current study has identified comprehensive education and training needs for healthcare providers about antimicrobial resistance. Using antimicrobials unnecessarily, insufficient duration of antimicrobial use, and using broad spectrum antimicrobials were reported to be common practices. Furthermore, poor skills and knowledge were a key factor that contributed to the inappropriate use and overuse of antimicrobials, and the use of antimicrobials without a physician’s prescription (i.e., self-medication) represent key factors which contribute to AMR from participants’ perspectives. Furthermore, internal policy and guidelines are needed to ensure that the antimicrobials are prescribed in accordance with standard protocols and clinical guidelines.

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Prevalence and Associated Factors of Psychological Distress Among Secondary School Students in Mekelle City, Tigray Region, Ethiopia: Cross-Sectional Study

Psychology Research and Behavior Management ◽

10.2147/prbm.s252779 ◽

2020 ◽

Vol Volume 13 ◽

pp. 473-480

Author(s):

Haftom Gebremedhin ◽

Berhanu Bifftu ◽

Mikiyas Tulu Lebessa ◽

Aemro Weldeyes ◽

Tesfay Tsegay Gebru ◽

...

Keyword(s):

Psychological Distress ◽

Secondary School ◽

Associated Factors ◽

Secondary School Students ◽

Cross Sectional Study ◽

Sectional Study ◽

School Students ◽

Cross Sectional ◽

Tigray Region ◽

Mekelle City

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Healthcare Provider Attitudes toward the Newly Developed COVID-19 Vaccine: Cross-Sectional Study

Nursing Reports ◽

10.3390/nursrep11010018 ◽

2021 ◽

Vol 11 (1) ◽

pp. 187-194

Author(s):

Gasmelseed Ahmed ◽

Zainab Almoosa ◽

Dalia Mohamed ◽

Janepple Rapal ◽

Ofelia Minguez ◽

...

Keyword(s):

Private Hospital ◽

Univariate Analysis ◽

Healthcare Providers ◽

Cross Sectional Study ◽

Chronic Illnesses ◽

Sectional Study ◽

Provider Attitudes ◽

Cross Sectional ◽

Electronic Survey ◽

Consistency Results

Background: During the long wait and the global anxiety for a vaccine against COVID-19, impressively high-safety and effective vaccines were invented by multiple pharmaceutical companies. Aim: We aimed to assess the attitudes of healthcare providers and evaluate their intention to advocate for the vaccine. Methods: This was a cross-sectional study conducted in a tertiary private hospital where an electronic survey was distributed among healthcare providers (HCPs). The survey contained two sections: socio-demographic characteristics and Likert-scale perception, with 72% internal consistency. Results: The response rate to the email survey was 37% (n = 236). In addition, 169 (71.6%) of respondents were women, with more than half (134, 56.8%) aged ≤35 years. A total of 110 (46.6%) had over 10 years of experience, and most of them were nurses (146, 62%). Univariate analysis revealed that older participants significantly accepted and advocated for the new vaccine more than the younger ones. In the multivariate analysis, men were significantly more likely than women to accept and advocate for the new vaccine, as were those with chronic illnesses. Participants with allergy were significantly less likely to accept the vaccine than others. odds ratio (OR) and p-values were 2.5, 0.003; 2.3, 0.04; and 0.4, 0.01, respectively. Conclusion: The acceptance rate for the newly-developed COVID-19 vaccines was average among HCPs. Sex, age, presence of chronic illnesses, and allergy were significant predictors of accepting the vaccine.

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