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Problematic smartphone use and disengagement in first-year college students: A daily diary study of between- and within-person differences.

PAPER pubmed Addictive behaviors 2026 Cohort study Effect: harm Evidence: Moderate

Abstract

Existing evidence suggests that problematic smartphone use (PSU) and disengagement may form part of a spiraling process. This investigation explores this process among first-year undergraduates, distinguishing within-person fluctuations from between-person rank order stability. Over 30 consecutive days, 104 first-year undergraduates in China (M = 18.62, SD = 0.96, 55.1% female) completed daily surveys that assessed PSU and disengagement. Dynamic structural equation modeling indicated a bidirectional lagged association whereby higher-than-usual PSU on a given day was prospectively associated with higher-than-usual disengagement the next day, and higher-than-usual disengagement on a given day was prospectively associated with higher-than-usual PSU the next day. Individuals with higher PSU than their peers tended to report greater disengagement, with PSU consistently amplifying its impact on disengagement. Neither family socioeconomic status nor gender significantly influenced the model. The findings highlight a harmful cycle of daily reinforcement at the within-person level, coupled with consistent associations at the between-person level. Given the importance of the first year of university, the findings underscore the need for targeted interventions that address both PSU and disengagement and aim to attenuate their bidirectional association.

AI evidence extraction

At a glance
Study type
Cohort study
Effect direction
harm
Population
First-year undergraduate students in China
Sample size
104
Exposure
smartphone · 30 consecutive days
Evidence strength
Moderate
Confidence: 74% · Peer-reviewed: yes

Main findings

Across 30 daily surveys, dynamic structural equation modeling found bidirectional lagged associations: higher-than-usual PSU on a given day predicted higher-than-usual disengagement the next day, and higher-than-usual disengagement predicted higher-than-usual PSU the next day. Between persons, students with higher PSU than peers reported greater disengagement; family socioeconomic status and gender did not significantly influence the model.

Outcomes measured

  • Problematic smartphone use (PSU)
  • Disengagement

Limitations

  • Exposure is problematic smartphone use (behavioral measure), not quantified EMF/RF exposure (no frequency or SAR reported).
  • Observational daily-diary design; causal inference is limited.
  • Outcomes and exposure assessed via self-report surveys.
View raw extracted JSON
{
    "study_type": "cohort",
    "exposure": {
        "band": null,
        "source": "smartphone",
        "frequency_mhz": null,
        "sar_wkg": null,
        "duration": "30 consecutive days"
    },
    "population": "First-year undergraduate students in China",
    "sample_size": 104,
    "outcomes": [
        "Problematic smartphone use (PSU)",
        "Disengagement"
    ],
    "main_findings": "Across 30 daily surveys, dynamic structural equation modeling found bidirectional lagged associations: higher-than-usual PSU on a given day predicted higher-than-usual disengagement the next day, and higher-than-usual disengagement predicted higher-than-usual PSU the next day. Between persons, students with higher PSU than peers reported greater disengagement; family socioeconomic status and gender did not significantly influence the model.",
    "effect_direction": "harm",
    "limitations": [
        "Exposure is problematic smartphone use (behavioral measure), not quantified EMF/RF exposure (no frequency or SAR reported).",
        "Observational daily-diary design; causal inference is limited.",
        "Outcomes and exposure assessed via self-report surveys."
    ],
    "evidence_strength": "moderate",
    "confidence": 0.7399999999999999911182158029987476766109466552734375,
    "peer_reviewed_likely": "yes",
    "keywords": [
        "problematic smartphone use",
        "smartphone",
        "disengagement",
        "daily diary",
        "dynamic structural equation modeling",
        "undergraduates",
        "China",
        "bidirectional association"
    ],
    "suggested_hubs": []
}

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AI-extracted fields are generated from the abstract/metadata and may be incomplete or incorrect. This content is for informational purposes only and is not medical advice.

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