The study, led by Lei Yu of the Third People’s Hospital of Qujing with colleagues including Wenzhi Wu of Beijing Normal University, followed 1,474 adolescents across three annual assessments beginning in October 2021 and ending in October 2023. Participants, whose average age at baseline was about 15.5 years and nearly 60 percent of whom were female, were drawn from 27 classrooms in two public secondary schools in Southwest China. At each wave, the researchers measured three constructs: perceived stress, core self-evaluations, and problematic smartphone use. Perceived stress was assessed with the 10-item Perceived Stress Scale, which captures the appraisal that environmental demands exceed one’s coping resources rather than the mere presence of demands. Core self-evaluations, measured with the 10-item Core Self-Evaluation Scale, represent a higher-order judgment of one’s own worth, competence, sense of control, and emotional stability, integrating self-esteem, generalized self-efficacy, locus of control, and emotional stability into a single psychological resource.

Problematic smartphone use, the third pillar of the study, was measured with a 22-item scale covering withdrawal-like behavior, salience, social comfort, negative effects, and patterns of application use. The construct matters because it is distinct from heavy use. Frequent smartphone use is not inherently maladaptive; the developmental concern arises when use becomes compulsive or poorly controlled and begins to interfere with sleep, learning, emotional functioning, or offline relationships. Reviews have linked problematic smartphone use to poorer mental health and sleep outcomes in young people, but the direction of these associations and the mechanisms behind them have remained unsettled, largely because most studies are cross-sectional snapshots that cannot establish temporal ordering.

The methodological innovation at the heart of the new study is the random-intercept cross-lagged panel model, or RI-CLPM. Conventional cross-lagged panel models, which compare variables across repeated waves, have a well-documented weakness: they can blend stable between-person differences with genuine within-person change. In adolescence this distinction is critical. Some teenagers may be chronically more stressed, lower in self-evaluation, and more prone to problematic phone use because of relatively stable factors such as temperament, family context, academic environment, or peer experiences. Those stable differences are meaningful for identifying risk groups, but they are not the same as dynamic processes unfolding inside an individual. The RI-CLPM solves this by estimating a random intercept for each person on each variable, capturing that adolescent’s typical level, and then asking whether deviations from that own typical level predict later deviations. In other words, it asks whether a teenager who is more stressed than usual this year reports lower self-evaluation next year, and whether that dip forecasts more problematic phone use the year after.

The data showed that the separation was necessary. Intraclass correlations indicated that stable between-person differences accounted for roughly half or more of the total variance in all three constructs, between 52 and 59 percent, with the remainder reflecting within-person fluctuation. At the between-person level, the correlations were strong and unsurprising: adolescents who were generally lower in core self-evaluations tended to report more perceived stress and more problematic smartphone use, and generally more stressed adolescents reported more problematic use. The random intercepts for self-evaluations and stress were correlated at about negative 0.84, an unusually strong trait-level association. But these chronic risk profiles, the researchers emphasize, cannot be treated as evidence of within-person change.

The within-person findings were the study’s core contribution. Core self-evaluations and perceived stress were reciprocally and negatively linked over time. When adolescents reported self-evaluations higher than their own usual level, they subsequently reported lower perceived stress, with a standardized cross-lagged coefficient around negative 0.15. When they reported stress higher than their own usual level, they subsequently reported lower core self-evaluations, with a coefficient around negative 0.12. By the effect-size benchmarks proposed for cross-lagged designs, these associations fall in the large range. The pattern fits appraisal theories of stress, which hold that demands become stressful when coping resources are judged insufficient, and resource-based accounts in which personal resources both protect against stress and are depleted by sustained demands. Higher-than-usual self-belief may buffer the impact of academic competition, peer conflict, and family expectations; repeated experiences of overload, failure, or uncontrollability may in turn erode a teenager’s sense of competence and control.

The pathway to the phone ran through this resource, not around it. Higher-than-usual core self-evaluations predicted lower subsequent problematic smartphone use, a significant prospective association with a coefficient around negative 0.13. Perceived stress, by contrast, showed no direct predictive path to later problematic use once stable differences and self-evaluations were modeled. Yet a longitudinal indirect association from stress to problematic smartphone use through core self-evaluations was statistically different from zero, estimated with 5,000 bootstrap samples and bias-corrected confidence intervals. The reverse sequence, in which problematic use would erode self-evaluations and later raise stress, was not supported. This asymmetry gives the model a sharper developmental interpretation: at the annual time scale examined here, the road from stress to the smartphone passes through the self. The finding is consistent with compensatory internet-use theory and the I-PACE model, both of which frame problematic digital behavior as emerging from interactions among affective states, person-level vulnerabilities, cognitive appraisals, and executive control, rather than from stress alone.

The authors are careful about what the design can and cannot claim. Because the study is observational, the temporally ordered indirect associations cannot be read as causal mediation, and the hypotheses and analytic plan were not preregistered. The researchers also stress-tested their conclusions. The results held under 200 multiple imputations of missing data, under classroom-cluster-robust standard errors accounting for nesting within 27 classrooms, and under partial scalar measurement-invariance specifications. The within-person pathways did not differ significantly between boys and girls, though the authors caution that this invariance concerns the path coefficients only, not mean levels, stress exposure, or patterns of use. One measurement caveat deserves attention: the Perceived Stress Scale showed only modest internal consistency in this sample, with reliability coefficients between roughly 0.66 and 0.72, which may have attenuated associations involving stress and warrants replication with alternative measures.

The practical implications are framed as hypotheses for future work rather than prescriptions. The prospective association between core self-evaluations and later problematic smartphone use suggests that self-evaluative resources may be worth examining as a candidate mechanism in experimental and intervention research, for example by testing whether programs that strengthen perceived competence, control, coping confidence, or emotion regulation produce subsequent changes in smartphone behavior. But until such evidence exists, core self-evaluations should be viewed as a potentially relevant psychological process, not an established intervention target. The authors also note limitations of scale and scope: all constructs were self-reported, the one-year lag may not match the faster rhythms at which stress and phone use interact day to day, and the sample came from only two public secondary schools in Southwest China, limiting generalizability across regions and school types. Future studies combining self-reports with device-recorded behavior, sleep indicators, and daily diary or ecological momentary assessment could capture shorter-term dynamics that annual waves cannot.

What the study ultimately offers is a more conditional account of why some adolescents lose control of their smartphone habits. Stressful periods appear most relevant to problematic use when they are accompanied by declines in self-evaluative resources; a generalized stress-to-phone link was not supported. Core self-evaluations, often treated as a fixed background trait, emerge instead as a dynamic resource that fluctuates meaningfully around each adolescent’s typical level and carries developmental information across years. For a generation growing up with smartphones woven into school coordination, peer contact, and family communication, the message from this three-year dataset is subtle but consequential: the psychological resource that matters may not be how much stress a teenager faces, but how capable, in control, and emotionally stable that teenager feels while facing it.

Subject of Research: Within-person longitudinal relations among perceived stress, core self-evaluations, and problematic smartphone use in Chinese adolescents

Article Title: Within-person reciprocal relations among perceived stress, core self-evaluations, and problematic smartphone use in Chinese adolescents

Article References: Yu, L., Wu, W., Jia, Y., Chang, L., & Ji, J. (2026). Within-person reciprocal relations among perceived stress, core self-evaluations, and problematic smartphone use in Chinese adolescents. Current Psychology, 45(20), Article 1587. https://doi.org/10.1007/s12144-026-10123-7

Image Credits: AI Generated

DOI: 10.1007/s12144-026-10123-7

Keywords: adolescents, perceived stress, core self-evaluations, problematic smartphone use, random-intercept cross-lagged panel model, longitudinal study, self-esteem, compensatory internet-use theory, I-PACE model, China, mental health, self-regulation