Relationship between depression, smartphone addiction, and sleep among Chinese engineering students during the COVID-19 pandemic

Table 3 Multiple linear regression of depression (n = 685)

Variables	Model 1	Model 2	Model 3
Sleep quality	-	-	0.158
Sleep latency	-	-	0.587a
Sleep duration	-	-	0.471b
Habitual sleep efficiency	-	-	0.185
Sleep disturbances	-	-	1.817a
Sleep medication	-	-	1.436a
Daytime dysfunction	-	-	1.304a
Smartphone addiction	-	0.141a	0.082a
Age	-0.130	-0.113	-0.066
Gender	0.526	0.602	0.112
Nationality	-0.524	-0.570	-0.292
Political status	0.435	-0.035	-0.102
Only child	-0.279	-0.047	0.092
Home location	-0.557	-0.668	-0.392
Family socioeconomic status	-0.170	-0.153	-0.181
Father’ education	-0.115	-0.152	0.228
Observations	685	685	685
Adjusted R2	0.011	0.116	0.352

^aP < 0.01.

^bP < 0.05.

^cP < 0.10.

Bold represents statistically significant. Gender: 0 = male, 1 = female. Nationality: 0 = minority nationality, 1 = Han nationality. Political status: 0 = nonparty member, 1 = Communist Party member; only child: 0 = having siblings; 1 = only child. Home location: 0 = rural, 1 = town. Family socioeconomic status: 1 = lower, 2 = lower middle, 3 = middle, 4 = upper middle, 5 = upper. Father’s educational level: 0 = never receiving higher education, 1 = completing higher education.