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. 2020 Jul 1;10:10763. doi: 10.1038/s41598-020-67727-7

Table 3.

Within-person associations between adolescents’ use of Instagram and well-being.

Categorical associations
Use versus no use
(N participants = 60; N assessments = 2,112)
Dose–response associations
Duration of use
(N participants = 60; N assessments = 1,075)
Model 3A
Fixed effects
Model 3B
Random effects
Model 4A
Fixed effects
Model 4B
Random effects
B (SE) p β B (SE) p B (SE) p β B (SE) p
Fixed part
Intercept 5.64 (.10)  < .001 7.89 5.64 (.10)  < .001 5.69 (.10)  < .001 7.62 5.69 (.10)  < .001
Assessment (WP) .08 (.04) .031 .09 .08 (.04) .033 .05 (.05) .347 .09 .05 (.05) .276
Passive use (WP) .15 (.07) .027 .14 .15 (.07) .041 .03 (.07) .695 .14 .06 (.07) .440
Active use (WP) .14 (.09) .137 .13 .13 (.09) .164 .05 (.06) .428 .06 .01 (.07) .879
Random part
σ2 residual (WP) 1.18 (.11)  < .001 1.17 (.10)  < .001 1.11 (.12)  < .001 1.07 (.12)  < .001
σ2 between-person (BP) .54 (.08)  < .001 .54 (.08)  < .001 .47 (.08)  < .001 .47 (.08)  < .001
σ2 passive use (BP) .02 (.05) .335 .06 (.04) .068
σ2 active use (BP) .05 (.07) .217 .04 (.04) .142
Model fit
Deviance 6,503.54 6,501.67 3,287.59 3,279.66
AIC 6,515.54 6,517.67 3,299.59 3,295.33
BIC 6,549.48 6,562.91 3,329.47 3,335.17
Chi2 (df) 1.37 (2) .503 19.92 (2)  < .001

For investigating the categorical associations, the passive and active use predictors were dummy coded (passive use: 0 = no passive use of Instagram; 1 = passive use of Instagram; and active use: 0 = no active use of Instagram; 1 = active use of Instagram, respectively). WP = within-person; BP = between-person. All predictors were person-mean centered. Models for the duration of use only include assessments during which participants had used Instagram, either actively or passively. p-values of the fixed part of the model are two-sided, p-values of the random part of the model are one-sided.