Table 3.
Hierarchical regression analysis predicting loneliness
Variables | Model 1 | Model 2 | Model 3 | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
B | SE | β | t | B | SE | β | t | B | SE | β | t | ΔR2 | R2Adj | |
Block 1 – Socio-demographics (F(4,999) = 14.00; p < 0.001) | 0.05 | 0.05 | ||||||||||||
Gendera | 0.36 | 0.11 | 0.10 | 3.17** | 0.33 | 0.11 | 0.09 | 3.02** | 0.28 | 0.10 | 0.08 | 2.83** | ||
Marital statusb | −0.06 | 0.10 | −0.02 | − 0.66 | − 0.02 | 0.09 | − 0.01 | − 0.21 | − 0.13 | 0.08 | − 0.04 | −1.57 | ||
Chronic health conditionsc | − 0.55 | 0.15 | − 0.12 | −3.73*** | − 0.66 | 0.15 | − 0.14 | −4.48*** | − 0.24 | 0.14 | − 0.05 | −1.77 | ||
Self-reported health statusd | 0.62 | 0.12 | 0.17 | 5.36*** | 0.22 | 0.13 | 0.06 | 1.72 | 0.04 | 0.12 | 0.01 | 0.33 | ||
Block 2 – Lifestyle factors (F(9,994) = 17.57; p < 0.001) | 0.08 | 0.13 | ||||||||||||
Physical exercisec | 0.52 | 0.11 | 0.14 | 4.70*** | 0.40 | 0.10 | 0.11 | 3.96*** | ||||||
Internet browsing hoursd | 0.27 | 0.07 | 0.15 | 4.04*** | 0.15 | 0.06 | 0.08 | 2.51* | ||||||
Social media usee | 0.15 | 0.06 | 0.09 | 2.42* | 0.15 | 0.06 | 0.09 | 2.64** | ||||||
Alcohol consumptionc | −0.75 | 0.21 | −0.11 | −3.49** | −0.65 | 0.19 | −0.09 | −3.32** | ||||||
Self-reported quality of lifef | 0.59 | 0.13 | 0.15 | 4.46*** | 0.44 | 0.12 | 0.12 | 3.70*** | ||||||
Block 3 – Psychiatric symptoms (F(13,990) = 33.36; p < 0.001) | 0.17 | 0.30 | ||||||||||||
Fear of COVID-19 | −0.01 | 0.01 | −0.04 | −1.32 | ||||||||||
Anxiety | 0.10 | 0.01 | 0.25 | 6.96*** | ||||||||||
Depression | 0.03 | 0.01 | 0.09 | 2.60* | ||||||||||
Insomnia | 0.06 | 0.01 | 0.21 | 6.97*** |
B Unstandardized regression coefficient, SE Standard error, β Standardized regression coefficient; a1 = Male, 2 = Female; b1 = Unmarried, 2 = Married, 3 = In a relationship; c1 = Yes, 2 = No; d1 = < 2 hours, 2 = 2–4 hours, 3 = 4–6 hours, 4 = > 6 hours; e1 = Not at all, 2 = Rarely, 3 = Sometime, 4 = Often, 5 = Always; f1 = Good, 2 = Poor. *p < 0.05, **p < 0.01, ***p < 0.001