The impact of the COVID-19 pandemic on the education of medical, dental and non-medical healthcare professionals in Bangladesh : findings and connotation

Lockdown measures in response to the COVID-19 pandemic had an appreciable impact on the education of all medical, dental, and non-medical healthcare professional (HCP) students. These included the closure of universities necessitating a rapid move to e-learning and new approaches to practical’s. However initially, there was a lack of knowledge and expertise regarding e-learning approaches and the affordability of internet bundles and equipment. We initially con-ducted two pilot studies to assess such current challenges, replaced by a two-stage approach including a full investigation involving 32 private and public universities during the early stages of the pandemic followed by a later study assessing the current environment brought about by the forced changes. Top challenges at the start of the pandemic included a lack of familiarity with e-learning approaches, cost of the internet, lack of IT equipment and the quality of the classes. Universities offered support to staff and students to a varying degree to address identified challenges. Since then, e-learning approaches have widened the possibilities for teaching and learning at convenient times. However, challenges remain. In conclusion, there were considerable challenges at the start of them pandemic. Several key issues have been addressed with hybrid learning here to stay. Remaining challenges include a lack of ICT equipment. However, new innovations will continue

Post-discharge quality of life of COVID-19 patients at 1-month follow-up: A cross-sectional study in the largest tertiary care hospital of Bangladesh.

There is increasing evidence of the post-COVID-19 suffering and decreased quality of life in the COVID-19 patients. This study aimed to assess the quality of life and associated factors of COVID-19 patients at one month after discharge from the hospital. This was a cross-sectional study that was conducted at the post-covid clinic of Dhaka Medical College Hospital (DMCH) where RT-PCR-confirmed adult COVID-19 recovered patients were enrolled one month after discharge from the same hospital. They were consecutively selected from January 01 to May 30. A pretested semi-structured questionnaire was used for the data collection for clinical variables. The generic multi-attributable utility instrument EQ-5D-5L was used for assessing health-related quality of life (HRQoL). A total of 563 patients were enrolled in the study. The patients had a mean age with standard deviation (±SD) of 51.18 (±13.49) years and 55.95% were male. The mean (SD) EQ-5D-5L index score and EQ-VAS scores were 0.78 (±0.19) and 70.26 (±11.13), respectively. Overall, 45.77%, 50.99%, 52.79%, 55.14% and 62.16% had problems (slight to extreme) in the mobility, self-care, usual activities, pain/discomfort and anxiety/depression dimensions, respectively. Patients aged ≥60 years had significant problem in mobility (odds ratio [OR] 3.24, 95% confidence interval [CI]: 1.07-9.77). Female participants were 5.50 times (95% CI: 2.22-13.62) more likely to have problems in their usual activities. In comparison to urban area, living in a peri-urban setting was significantly associated with problems in mobility (OR 1.89, 95% CI: 1.13-3.20), pain/discomfort (OR 1.82, 95% CI: 1.04-3.12) and anxiety/depression (OR 2.16, 95% CI: 1.22-3.84). Comorbid patients were 1.75 times (95% CI: 1.07-2.85) more likely to report problems in the pain/discomfort dimension. Presence of symptom(s) was associated with problems in self-care (OR 3.27, 95%CI: 1.31-8.18), usual-activity (OR 3.08, 95%CI: 1.21-7.87), pain/discomfort dimensions (OR 2.75, 95%CI: 1.09-6.96) and anxiety/depression (OR 3.35, 95%CI: 1.35-8.30). Specific management strategies should be planned to address the factors associated with low health-related quality of life in post-acute care of COVID-19 patients

Supplementary tables.

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Dataset.

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Characteristics of respondents and EQ-5D index and visual analogue (EQ VAS) score.

Characteristics of respondents and EQ-5D index and visual analogue (EQ VAS) score.</p

Multivariable logistic regression analysis to determine factors associated with slight to extreme responses in the five dimensions of the EQ-5D.

Multivariable logistic regression analysis to determine factors associated with slight to extreme responses in the five dimensions of the EQ-5D.</p

Proportion of participants reporting problems in five dimensions of EQ-5D-5L.

Proportion of participants reporting problems in five dimensions of EQ-5D-5L.</p