Two commonly used subjective assessment scores are the Pittsburgh Sleep Quality Index (PSQI) to assess sleep quality and the Epworth Sleepiness Scale (ESS) to assess excessive daytime sleepiness. The pattern observed is delayed onset of sleep, frequent awakening episodes, insomnia, sleep apnoea, excessive daytime sleepiness, restless leg syndrome, abnormal limb movements, pain in limbs, confusion, and nightmares. Higher rates of primary sleep disorders, demographic characteristics, metabolic abnormalities, and the efficacy of treatment place HDP at higher risk. Sleep disturbances are common in patients with end-stage kidney disease on hemodialysis (hemodialysis population: HDP). Therefore, it is revealed in this work that the correct use of artificial intelligence technology in the education of labour concept has extremely important value for the intelligent development of education methods. Comparing the data of group A and group B suggests that the labour view expressed in group A is more biased in the cognition of labour purpose, and students in group A is more negative and lazier in labour attitude and labour habits, which shows that wireless network mobile devices have a great negative impact on the overall labour view of college students. In the question “What would you do when you find that the public area is dirty and poor, but it’s not your turn to be on duty?”, only about 50% of college students are willing to clean actively. ![]() ![]() Meanwhile, about 50%–60% of college students think that “housework has nothing to do with me, and it’s all the work of adults”. According to the statistical survey results, about 20% of college students agree that “if they have enough money to live, they do not have to work” while less than 50% agree that “they cannot be admitted to civil servants and senior managers in the company and are willing to engage in ordinary labour in the future”. Secondly, the impact of wireless network mobile devices on college students' labour education is obtained by comparing group A (using artificial intelligence APPs for wireless network devices to learn about labour concepts) and group B (using traditional classroom teaching methods for to learn about labour concepts). Firstly, a questionnaire survey is used to investigate the labour concept of 400 college students. ![]() To cultivate correct labour values and good labour quality of college students and effectively promote the development of their labour concept education, this work explores the impact of wireless network mobile devices on college students’ labour concept education under the environment of artificial intelligence.
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