Musculoskeletal pain intensity and perceptions during distance learning: A cross-sectional study.
Burak Şevket VuranTurgay AltunalanPublished in: Clinical anatomy (New York, N.Y.) (2024)
Technological developments and the pandemic have popularized the distance learning model at universities. In this educational model, students spend more time in front of screens, and screen-related health conditions have become important. This cross-sectional study of 177 undergraduate students was designed to investigate the effect of block and traditional scheduling in online distance education (ODE) on their musculoskeletal pain and to investigate their perceptions of block scheduling. A two-stage method was used: a quantitative design to compare pain levels, and a qualitative design to determine the students' perceptions of block scheduling using an online survey. Pain intensity was assessed using the Numeric Rating Scale (NRS-11). Data were collected in the university health sciences department. Pain intensity following the block and traditional lessons was analyzed using a paired t-test. Students in the block schedule had significantly more pain, with a large effect size on the whole trunk and upper limbs. Pain levels were also clinically meaningful for the upper (5.73 ± 2.75), lower (5.59 ± 2.87), and neck (4.92 ± 2.60) regions. Students reported positive experiences with block scheduling in ODE such as saving time (43%) and maintaining subject integrity (26%), but also negative experiences such as distraction (56%), fatigue (33%), pain (17%), and boredom (11%). Block scheduling in ODE could cause clinically significant neck and back pain. In distance learning, keeping the course duration short and ensuring student mobility in the classroom are important.
Keyphrases
- chronic pain
- pain management
- neuropathic pain
- healthcare
- mental health
- primary care
- sars cov
- high school
- high resolution
- gene expression
- coronavirus disease
- health information
- physical activity
- risk assessment
- genome wide
- mass spectrometry
- quality improvement
- climate change
- tertiary care
- big data
- lower limb
- postoperative pain
- data analysis
- artificial intelligence
- nursing students