Amos version 26

The analysis of the data commenced with descriptive and correlational examinations. To test the research hypothesis, Structural Equation Modeling (SEM) was conducted using Amos version 26, while the SPSS (Ver. 25) was utilized for the other analyses. Following the recommendation of Anderson and Gerbing (1988) (link), the measurement model was first fitted to the data, after which the underlying structural model was examined. In evaluating the overall fitness of the hypothesized model, multiple fit indices were considered. These included: (a) the ratio of χ² to the degrees of freedom, (b) the Goodness of Fit Index (GFI), (c) the Comparative Fit Index (CFI), (d) the Root-Mean-Square Error of Approximation (RMSEA), and (e) the Standardized Root-Mean-Square Residual (SRMR). According to Kline (2023) , a good fit is indicated by a small χ² to the degrees of freedom value with p > 0.05. Additionally, GFI and CFI values equal to or higher than 0.90 (Hu and Bentler, 1999 (link)) suggest a good fit, while RMSEA values should not exceed 0.08, and SRMR values should not surpass 0.10 (Bowen and Guo, 2011 ).

SPSS software, version 22.0 (IBM, Armonk, NY, United States) and AMOS version 26.0 software were used for the statistical analysis. The count data was described by frequency and constituent ratio, and the measurement data were described by mean ± standard deviation. The normal distribution samples were tested by using the t-test, and the non-normal distribution was tested by using nonparametric test. Spearman correlation analysis was used to analyze the scores of SIS, AODS and OAI-20. The significance level was set at 0.05. To evaluate the fitness of the hypothetical model, the chi-square/degrees of freedom ratio (x²/df ), goodness-of-fit index (GFI), root mean square error of approximation (RMSEA), adjusted goodness-of-it index (AGFI), the incremental fit index (IFI), normed fit index (NFI), comparative fit index (CFI) and Tucke-Lewis index (TLI) were used. The following threshold values were recommended as criteria for an adequate model: x²/df < 3.00, GFI > 0.80, RMSEA <0.08, AGFI >0.80, IFI > 0.90, NFI > 0.90, CFI > 0.90 and TLI > 0.90 (Wu, 2013 ).

We used SPSS version 23.0 (IBM Corporation, Armonk, NY, USA) for initial data input, collation, and preliminary analyses. The normality of the data distribution was assessed using Q–Q plots [69 (link)], where the scatter points closely aligned with the diagonal, confirming the assumption of data normality. We employed Harman’s single-factor test to address the potential common method bias issue. Variable scores were computed, and relations among key variables, such as parental phubbing, parent–child conflict, emotion regulation, and electronic media use, were explored using Pearson’s correlation method. Following these preliminary analyses, we constructed and validated structural equation models using AMOS version 26.0 (IBM Corporation). This advanced analytical phase sought to elucidate the relation between parental phubbing and young children’s electronic media use, accounting for the mediating role of parent–child conflict and the moderating role of emotion regulation.

Correlations with the variables were processed using Pearson’s correlation coefficient, to test for multicollinearity. The correlation coefficient ranged from 0 to 1, with values of 0.80 or less [46 (link)], and the variance inflation factor (VIF) values were less than 10 [47 ].
Structural relationships between variables were identified by analyzing indirect effects using the model. The sizes of the direct effect, indirect effect, and total effect were calculated by bootstrapping, to confirm the significance of the mediating effect. The collected data were analyzed using IBM SPSS for Windows, version 26.0 (IBM corp., Armonk, NY, USA) and AMOS, version 26.0 (IBM Corp., Armonk, NY, USA).

Statistical analyses and the exploratory factorial analysis were performed using SPSS version 28 (IBM Inc., Armonk, NY, USA). Univariant and bivariant analyses were conducted. The statistical software AMOS version 26.0.0 (IBM Inc., Armonk, NY, USA) was used for confirmatory factor analysis. The study was conducted in accordance with the Declaration of Helsinki. Informed consent was shown at the beginning of the questionnaire. Personal data were not collected. The confidentiality of the participants was absolute as no personal data were collected or stored, and the researchers only could access completely anonymous questionnaires. Although the responses were anonymous and, therefore, participants could not be identified, the questionnaires were stored in encrypted servers of the Andalusian Health Service. This study was approved by the Research and Ethics Committee of Nursing, Physiotherapy, and Medicine Department of the University of Almeria (Spain), with approval number EFM 205/2022.