Differential Longitudinal Effects of Emotional Abuse and Neglect on Adolescent Anxiety and Problematic Smartphone Use: The Mediating Role of Prospective Positive Imagery dataset

This study adopts a three-wave longitudinal follow-up design. Data collection is carried out at three distinct time points, namely T1, T2 and T3. A complete dataset dedicated to longitudinal research is finally integrated with comprehensive data levels and standardized processing procedures, which can be directly applied to subsequent statistical analyses such as longitudinal correlation analysis, cross-lagged analysis, mediation and moderation analysis, as well as inter-group comparison.The dataset consists of three major sections with complete content and clear classification, including basic raw data, screened and calibrated data, and deeply processed data.First, raw collected data. It fully incorporates the original response data of all participants to each scale item at the three measurement time points of T1, T2 and T3, and retains the unmodified original scores of all items. This part preserves first-hand research information to the greatest extent, and can support retrospective researches such as re-examination of scale reliability and validity, item screening, and item analysis.Second, screened valid longitudinal sample data. In accordance with the requirements of three-wave longitudinal research, the original samples are matched and screened. The data of valid participants who completed all three rounds of measurements from T1 to T3 are independently sorted out. Participants with sample loss, mid-term dropout and invalid responses are excluded, so as to ensure the sample consistency and research rigor of longitudinal follow-up analysis, and meet the analytical needs of various longitudinal tracking models.Third, secondarily processed standardized data. On the basis of valid longitudinal samples, systematic data preprocessing is completed. On the one hand, the scores of each scale item are standardized to eliminate dimensional differences and meet the prerequisites for multivariate statistics, model fitting and other subsequent analyses. On the other hand, sub-dimension scores and total scores of each dimension and the overall scale are accurately calculated, which avoids secondary manual calculation and greatly simplifies the data analysis process.Overall, the dataset features complete original materials, strict sample screening and standardized data processing. All processing procedures are traceable. It not only maintains the research expandability of raw data, but also provides refined analytical data after data cleaning, standardization and summarization. This dataset can effectively support the implementation of the current research and further extended longitudinal psychological studies.