The Vietnamese Version of the Brief Illness Perception Questionnaire and the Beliefs about Medicines Questionnaire:Translation and Cross-cultural Adaptation

OBJECTIVE: To translate and cross-culturally adapt the Brief Illness Perception Questionnaire (BIPQ) and the Beliefs about Medicines Questionnaire (BMQ) into Vietnamese. METHODS: We followed the guideline by Beaton et al. (2000 & 2007). Stage I: two translators (informed and uninformed) translated the questionnaires. Stage II: the translations were synthesized. Stage III: back translation was performed by two translators fluent in both Vietnamese and English but naïve to the outcome measurement. Stage IV: seven experts reached consensus on the pre-final Vietnamese version (BIPQ-V and BMQ-V). Stage V: field test of the questionnaires on 16 twelve-year-old students and 31 Vietnamese patients. In addition, we determined the internal consistency and test-retest reliability of the questionnaires in 34 Vietnamese patients with acute coronary syndrome. RESULTS: All experts agreed that there was semantic, idiomatic, experiential, and conceptual equivalence between the original and pre-final Vietnamese versions of the BIPQ and BMQ. Cronbach's alpha coefficients of the internal consistency were acceptable for the BMQ-V Specific-Necessity (0.64), BMQ-V Specific-Concerns (0.62), and BMQ-V General-Harm (0.60), with the exception of BMQ-V General-Overuse (0.27). Intra-class correlation coefficients of the test-retest reliability was acceptable for the subscales of BMQ-V (range: 0.77-0.86), and BIPQ-V items (range: 0.62-0.85) with the exception of BIPQ-V 1 (0.44, 95% CI -014-0.72) and BIPQ-V 4 (0.57, 95% CI 0.22-0.81). CONCLUSIONS: The Vietnamese version of BIPQ and BMQ are reliable tools to assess illness perceptions and beliefs about medicines of patients with acute coronary syndrome. Psychometric properties of these questionnaires should be tested in different patient populations

Prevalence and Determinants of Medication Adherence among Patients with HIV/AIDS in Southern Vietnam

This study was conducted to determine the prevalence and determinants of medication adherence among patients with HIV/AIDS in southern Vietnam. METHODS: A cross-sectional study was conducted in a hospital in southern Vietnam from June to December 2019 on patients who began antiretroviral therapy (ART) for at least 6 months. Using a designed questionnaire, patients were considered adherent if they took correct medicines with right doses, on time and properly with food and beverage and had follow-up visits as scheduled. Multivariable logistic regression was used to identify determinants of adherence. KEY FINDINGS: A total of 350 patients (from 861 medical records) were eligible for the study. The majority of patients were male (62.9%), and the dominant age group (≥35 years old) accounted for 53.7% of patients. Sexual intercourse was the primary route of transmission of HIV (95.1%). The proportions of participants who took the correct medicine and at a proper dose were 98.3% and 86.3%, respectively. In total, 94.9% of participants took medicine appropriately in combination with food and beverage, and 75.7% of participants were strictly adherent to ART. The factors marital status (odds ratio (OR) = 2.54; 95%CI = 1.51-4.28), being away from home (OR = 1.7; 95%CI = 1.03-2.78), substance abuse (OR = 2.7; 95%CI = 1.44-5.05), general knowledge about ART (OR = 2.75; 95%CI = 1.67-4.53), stopping medication after improvement (OR = 4.16; 95%CI = 2.29-7.56) and self-assessment of therapy adherence (OR = 9.83; 95%CI = 5.44-17.77) were significantly associated with patients' adherence. CONCLUSIONS: Three-quarters of patients were adherent to ART. Researchers should consider these determinants of adherence in developing interventions in further studies

Knowledge of Antiretroviral Treatment and Associated Factors in HIV-Infected Patients

This study aimed to assess the knowledge of antiretroviral (ARV) treatment and the associated factors in HIV-infected patients in Vietnam. We conducted a cross-sectional descriptive study of 350 human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) patients being treated with ARV at outpatient clinics at Soc Trang, Vietnam, from June 2019 to December 2019. Using an interview questionnaire, patients who answered at least eight out of nine questions correctly, including some required questions, were considered to have a general knowledge of ARV treatment. Using multivariate logistic regression to identify factors associated with knowledge of ARV treatment, we found that 62% of HIV-infected patients had a general knowledge of ARV treatment, with a mean score of 8.2 (SD 1.4) out of 9 correct. A higher education level (p < 0.001); working away from home (p = 0.013); getting HIV transmitted by injecting drugs or from mother-to-child contact (p = 0.023); the presence of tension, anxiety, or stress (p = 0.005); self-reminding to take medication (p = 0.024); and a high self-evaluated adherence (p < 0.001) were found to be significantly associated with an adequate knowledge of ARV treatment. In conclusion, education programs for patients, as well as the quality of medical services and support, should be strengthened

Pneumonia: Drug-Related Problems and Hospital Readmissions

Pneumonia is one of the most common infectious diseases and the fourth leading cause of death globally. According to US statistics in 2019, pneumonia is the most common cause of sepsis and septic shock. In the US, inpatient pneumonia hospitalizations account for the top 10 highest medical costs, totaling $9.5 billion for 960,000 hospital stays. The emergence of antibiotic resistance in the treatment of infectious diseases, including the treatment of pneumonia, is a globally alarming problem. Antibiotic resistance increases the risk of death and re-hospitalization, prolongs hospital stays, and increases treatment costs, and is one of the greatest threats in modern medicine. Drug-related problems (DRPs) in pneumonia - such as suboptimal antibiotic indications, prolonged treatment duration, and drug interactions - increase the rate of antibiotic resistance and adverse effects, thereby leading to an increased burden in treatment. In a context in which novel and effective antibiotics are scarce, mitigating DRPs in order to reduce antibiotic resistance is currently a prime concern. A variety of interventions proven useful in reducing DRPs are antibiotic stewardship programs, the use of biomarkers, computerized physician order entries and clinical decision support systems, and community-acquired pneumonia scores

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In Part I, an extensive background of social distancing is provided, and enabling wireless technologies are thoroughly surveyed. In this Part II, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we discuss open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in their standard architectures/designs

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect- in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect- in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In Part I, an extensive background of social distancing is provided, and enabling wireless technologies are thoroughly surveyed. In this Part II, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we discuss open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in their standard architectures/designs