Corrigendum: Together Apart: The Mitigating Role of Digital Communication Technologies on Negative Affect During the COVID-19 Outbreak in Italy

Due to a clerical error, the values for the amount of technology use for business/school motives before the lockdown were reported incorrectly in Table 2 and Table 3. The amended Table 2 and Table 3 appears below.

Table 2.

Descriptive statistics and correlations among variables.

		α	M	SD	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
1	Age	–	31.26	13.19
2	Gender	–	–	–	−0.163**
3	Days of isolation	–	14.15	7.18	−0.206**	0.075
4	Number of exits	–	2.36	1.63	0.358**	−0.089	−0.550**
5	Number of persons living with	–	2.96	1.30	−0.283**	0.027	0.075	−0.118*
6	House sqm	–	123.09	77.09	−0.106*	0.002	0.085	−0.055	0.357**
7	Past technology use	–	1.75	0.55	0.168**	−0.149**	−0.013	0.012	−0.074	−0.030
8	Amount of technology use	–	2.42	0.70	−0.196**	−0.021	0.037	−0.147**	−0.075	0.002	0.474**
9	Past tech use for business/school	–	1.92	1.18	0.353**	−0.165**	−0.194**	0.233**	−0.158**	−0.113*	0.183**	0.056
10	Frequency tech use for business/school	–	2.40	1.35	0.181**	−0.100*	−0.027	0.096*	−0.049	−0.002	0.116*	0.099*	0.562**
11	Social support	0.89	5.53	0.96	0.115*	0.077	−0.039	−0.003	0.013	0.022	0.177**	0.162**	0.038	−0.014
12	Loneliness	0.93	2.80	1.08	−0.249**	0.052	0.025	−0.085	0.034	0.006	−0.164**	−0.003	−0.078	−0.022	−0.507**
13	State boredom	0.95	3.79	1.16	−0.367**	0.198**	0.114*	−0.145**	0.037	−0.011	−0.136**	0.078	−0.145**	−0.110*	−0.245**	0.617**
14	State irritability	0.90	3.50	1.31	−0.399**	0.242**	0.117*	−0.140**	0.164**	0.030	−0.129**	0.089	−0.168**	−0.059	−0.250**	0.503**	0.685**
15	State anger	0.90	2.65	1.23	−0.330**	0.196**	0.094*	−0.078	0.074	0.030	−0.072	0.091*	−0.102*	−0.059	−0.248**	0.502**	0.657**	0.733**
16	State anxiety	0.84	4.48	1.23	−0.195**	0.301**	−0.024	−0.032	0.075	−0.023	−0.114*	0.041	−0.090	−0.063	−0.080	0.349**	0.571**	0.567**	0.565**
17	Belongingness	0.80	4.53	1.01	0.187**	0.128**	−0.003	0.004	0.019	0.015	0.091	0.125**	0.056	0.029	0.428**	−0.311**	−0.230**	−0.223**	−0.213**	-0.039

Gender was coded 1 = males and 2 = females. N = 463;

^*p < 0.05;

^**p < 0.01.

Table 3.

Significant results of simple and multiple linear regressions.

Predictor	Dependent variable	Model statistics	B	SE B	β	95%CI		p
						LL	UL
Age	Social support	R2 = 0.062, F(9, 453) = 3.31, p < 0.001	0.010	0.004	0.135	0.002	0.017	=0.011
Gender			0.267	0.103	0.121	0.064	0.469	=0.010
Past technology use			0.310	0.082	0.179	0.150	0.471	<0.001
Age	Loneliness	R2 = 0.081, F(9, 453) = 4.44, p < 0.001	−0.020	0.004	−0.246	−0.029	−0.012	<0.001
Past technology use			−0.257	0.091	−0.131	−0.437	−0.078	=0.005
Age	Boredom	R2 = 0.166, F(9, 453) = 10.04, p < 0.001	−0.031	0.004	−0.352	−0.040	−0.022	<0.001
Gender			0.349	0.118	0.131	0.108	0.581	=0.003
Age	Anger/irritability	R2 = 0.179, F(9, 453) = 10.99, p < 0.001	−0.033	0.004	−0.365	−0.041	−0.024	<0.001
Gender			0.470	0.118	0.174	0.238	0.702	<0.001
Age	Anxiety	R2 = 0.124, F(9, 453) = 7.11, p < 0.001	−0.014	0.005	−0.155	−0.024	−0.005	=0.003
Gender			0.777	0.128	0.275	0.525	1.028	<0.001
Age	Belongingness	R2 = 0.077, F(9, 453) = 4.203, p < 0.001	0.019	0.004	0.243	0.011	0.027	<0.001
Gender			0.406	0.108	0.174	0.193	0.619	<0.001

N = 463; Predictors: (Constant), Age, Gender, Days of isolation, Number of exits, Number of persons living with, House sqm, Past technology use, Past tech use for business/school, Frequency tech use for business/school. LL, lower limit; UL, upper limit.

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.