Background <p>Mental health among college students represents a significant and growing public health concern. Negative bias in prospection is closely related to depression and anxiety. Prospection bias (PB) encompasses increased negativity, reduced positivity and overgeneralization, which exhibit intricate co-occurrence patterns and exert a complex influence on mental health. However, the presence of distinct patterns of PB and their impact on mental health remain unknown.</p> Methods <p>We recruited 1,030 Chinese college students to complete assessments of PB, depression, anxiety, stress and resilience. Latent profile analysis (LPA) was used to identify distinct PB profiles. Linear regression was then applied to examine their effects on mental health outcomes.</p> Results <p>The results suggested six profiles: (1) high levels of increased negativity and overgeneralization but a low level of reduced positivity (contradictory overgeneralizers), (2) low PB, (3) moderate low PB, (4) a high level of increased negativity but low levels of reduced positivity and overgeneralization (simple contradictory), (5) high PB, and (6) moderate high PB. Regression analyses demonstrated that high prospection bias predicted more severe stress, depressive and anxious symptoms, as well as lower resilience. Additionally, the results implied that handling increased negativity and reduced positivity of prospection might be potential ways to improve mental health.</p> Conclusions <p>These findings may facilitate the early detection of mental health issues among college students and contribute to the refinement of future interventions.</p>

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Patterns of prospection bias predict mental health among Chinese college students: a latent profile analysis

  • Lei Xia,
  • Xianglin Bai,
  • Zhengzhi Feng,
  • Jinglu Yan,
  • Zhuoya Yang

摘要

Background

Mental health among college students represents a significant and growing public health concern. Negative bias in prospection is closely related to depression and anxiety. Prospection bias (PB) encompasses increased negativity, reduced positivity and overgeneralization, which exhibit intricate co-occurrence patterns and exert a complex influence on mental health. However, the presence of distinct patterns of PB and their impact on mental health remain unknown.

Methods

We recruited 1,030 Chinese college students to complete assessments of PB, depression, anxiety, stress and resilience. Latent profile analysis (LPA) was used to identify distinct PB profiles. Linear regression was then applied to examine their effects on mental health outcomes.

Results

The results suggested six profiles: (1) high levels of increased negativity and overgeneralization but a low level of reduced positivity (contradictory overgeneralizers), (2) low PB, (3) moderate low PB, (4) a high level of increased negativity but low levels of reduced positivity and overgeneralization (simple contradictory), (5) high PB, and (6) moderate high PB. Regression analyses demonstrated that high prospection bias predicted more severe stress, depressive and anxious symptoms, as well as lower resilience. Additionally, the results implied that handling increased negativity and reduced positivity of prospection might be potential ways to improve mental health.

Conclusions

These findings may facilitate the early detection of mental health issues among college students and contribute to the refinement of future interventions.