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The efficacy and optimal matching of an Internet-based acceptance and commitment therapy intervention for depressive symptoms among university students: A randomized controlled trial in China. | LitMetric

AI Article Synopsis

  • The study evaluated an online Acceptance and Commitment Therapy (iACT) program to see how well it helps college students dealing with depression.
  • Participants were divided into two groups: one received the iACT program, while the other was on a waiting list, with their mental health assessed before and after the program.
  • Results showed significant improvement in depressive symptoms for the iACT group, particularly benefiting students who were more sensitive to relationships and had higher initial levels of depression.

Article Abstract

Objective: The present study tested the efficacy of an unguided internet-based Acceptance and Commitment Therapy (iACT) program for depression, and identified the psychological characteristics of participants who benefitted the most from the program.

Method: Undergraduate students with mild to severe symptoms of depression were randomized to the iACT group (n = 95) or the waiting-list group (WLC group; n = 87). Depressive symptoms and positive mental health were assessed at baseline (T ), at the end of the 6-week program (T ), and at a 3-month follow-up (T ).

Results: Compared with the WLC group, the iACT group showed significantly more improvement in depressive symptoms (d = 1.27) and positive mental health (d = 0.59), both at T and T . Latent Profile Analysis identified three classes of participants: Sensitive-to-Relationship, Low-Reactive-Depression, and Endogenous-Depression group. In general, the treatment was particularly suitable for the Sensitive-to-Relationship class.

Conclusion: The iACT was effective in treating the depressive symptoms of undergraduates, especially suitable for the clients with high baseline depression, high externality, high resistance, and high sensitivity to relationships.

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Source
http://dx.doi.org/10.1002/jclp.23329DOI Listing

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