Tuberculosis (TB) is a significant public health concern. Globally, TB is among the top 10 and the leading cause of death due to a single infectious agent. Providing standard anti-TB therapy for at least 6 months is recommended as one of the crucial strategies to control the TB epidemic. However, the long duration of TB treatment raised the issue of non-adherence. Non-adherence to TB therapy could negatively affect clinical and public health outcomes. Thus, directly observed therapy (DOT) has been introduced as a standard strategy to improve anti-TB medication adherence. Nonetheless, the DOT approach has been criticized due to inconvenience, stigma, reduced economic productivity, and reduced quality of life, which ultimately could complicate adherence issues. Apart from that, its effectiveness in improving anti-TB adherence is debatable. Therefore, digital technology could be an essential tool to enhance the implementation of DOT. Incorporating the health belief model (HBM) into digital technology can further increase its effectiveness in changing behavior and improving medication adherence. This article aimed to review the latest evidence regarding TB medication non-adherence, its associated factors, DOT’s efficacy and its alternatives, and the use of digital technology and HBM in improving medication adherence. This paper used the narrative review methodology to analyze related articles to address the study objectives. Conventional DOT has several disadvantages in TB management. Integrating HBM in digital technology development is potentially effective in improving medication adherence. Digital technology provides an opportunity to improve medication adherence to overcome various issues related to DOT implementation.

Musculoskeletal disorder (MSD) is a major health problem, which can lead to an enormous burden to the institution as well as chronic disability to the individual. Teachers are at risk of developing MSD due to the exposure to various ergonomic risk factors. Teachers of special education, for example, are expected to perform extra duty such as lifting and moving students, feeding food, changing diapers, and helping them in ambulation. Although there is an adequate amount of scientific research on MSD’s prevalence and its risk factors among regular teachers, only few studies have focused on special education teachers. This review aimed to address these gaps by describing the evidence from various papers on the prevalence of MSD among regular and special education teachers and the related risk factors. The papers have been gathered using electronic databases, including PubMed, Science Direct, Google Scholar, and Springer. The prevalence of MSD among regular teachers ranges from 48.7% to 73.7%, while the prevalence ranges from 38.7% to 94% in special education teachers. Risk factors, such as individual (age, duration of teaching, working hours, and work burden), physical (teaching activities, affected body areas), and psychological factors (stress, anxiety, fear), were identified. From the review, it is recommended to implement ergonomically designed workplaces, comprehensive ergonomic training, psychological approaches, and functional training among teachers at risk.

Special education teachers encounter considerable occupational challenges, yet there is limited information concerning musculoskeletal disorders (MSD) within this group. Therefore, this study aimed to address this gap by determining the prevalence of MSD, investigating associated factors of MSD, and identifying predictors of MSD among special education teachers. A cross-sectional study was conducted among special education teachers in Kota Kinabalu and Penampang, Sabah. Data were collected through self-administered questionnaires and musculoskeletal fitness assessments. Chi-square tests and independent t-tests were utilized to determine factors associated with MSD, while multiple logistic regression was performed to develop a comprehensive predictive model for MSD, which was then validated and tested for model fitness. A total of 122 individuals participated in the study, yielding a response rate of 95 %. The findings revealed a high prevalence of MSD (77.9 %) among special education teachers, with the lower back, shoulder, neck, knee, upper back, and foot being the most affected regions. The multivariable regression model identified several predictors of MSD, including marital status (adjusted odds ratio [aOR] = 4.78, 95 % confidence interval [CI] = 1.49–15.40), body fat percentage (aOR = 1.06, 95 % CI = 1.00–1.12), teaching in prolonged standing for few days a week (aOR = 3.20, 95 % CI = 0.99–10.29) or every day (aOR = 6.20, 95 % CI = 1.44–26.70), mindfulness (aOR = 0.47, 95 % CI = 0.22–0.98), and back extensor strength (aOR = 5.86, 95 % CI = 1.92–17.92). This study highlights the necessity of implementing interventions focusing on the ergonomic, psychological, and musculoskeletal fitness components to mitigate the prevalence of MSD and improve the overall well-being of special education teachers.

SARS-CoV-2 virus created a huge health impact due to isolation, quarantine, or lockdown. University students also affected with the closure of institute and switch in teaching methods. The objective of this study is to explore the health-related lifestyle changes among university students during the implementation of movement control order. Secondly, we aimed to convoke suggestions and recommendations to promote healthy living amidst university students. This study implemented qualitative method via using a semi-structured interview. Three focus group discussions were conducted consisting of 12 participants recruited from snowball sampling method. Utilizing verbatim transcription approach, an inductive thematic point was sketch for data analysis. Seven male and five female students with a mean age of 20 ± 1.3 years (range 19-23) were recruited into this study. Four themes identified from the interview. Physical health influence by administrative roles to physically inactive and less sport activity. Secondly, mental health concern towards mixed emotions, coping strategy, psychological adjustment, and mental health issues. Variation and self-prepare food, food supply, dietary habit and dietary pattern contribute to changes in food intake. Student lifestyles modulate to sleep hygiene, alcohol consumption, online classes problem, individual factors, and other unhealthy activities. Some students experience no difference in the surrounding transformation. During the pandemic, students experienced health related-behavioural changes involving physical health, mental health, dietary and lifestyle. Even though some informants perceived no changes in certain aspect, they still experience health-related behavioural changes in other aspect linked to health.