data
Description
This dataset contains four-wave panel survey data collected from Chinese retired older adults (aged ≥60) who have participated in at least one cross-national leisure sports tourism (CLST) experience. The study employed a four-stage cross-lagged design with measurements conducted in June, August, October, and December 2025 (approximately 2-month intervals). A unique anonymous code was used to match responses across waves. After data cleaning and wave matching, the final analytical sample includes 606 valid participants. The dataset supports analyses of a mixed-effects mechanism model examining how CLST influences subjective well-being (SWB) through psychological well-being (PWB), with two mediators (health self-efficacy, HSE; perceived physical function, PPF) and a moderator (cultural identification, CI). All constructs were measured using 7-point Likert-type items (1 = strongly disagree, 7 = strongly agree). Variable structure by wave: • T1: CLST (second-order construct; 16 items; dimensions: affect & meaning, environment & activity, social & interaction) • T2: HSE (8 items) and PPF (second-order construct; 14 items; five dimensions) • T3: PWB (second-order construct; 16 items; four dimensions) and CI (second-order construct; 12 items; three dimensions) • T4: SWB (second-order construct; 22 items; five dimensions) The dataset also includes participant background characteristics (e.g., gender, age, education, household economic level, pre-retirement occupation, participation duration/frequency, future plan). Data are de-identified; no direct personal identifiers are provided. The dataset can be used to replicate confirmatory factor analysis (CFA), structural equation modeling (SEM), bootstrapped mediation/moderation tests, and simple slope analyses reported in the associated manuscript.