Trait-based recovery enhances engagement and reduces anxiety and depression symptoms
Abstract The Trait-Based Model of Recovery is a strengths-focused intervention designed to enhance personality traits and reduce mental health symptoms, such as anxiety and depression, among individuals recovering from addiction. This study evaluated the model’s effectiveness using a quasi-experimen...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-06384-0 |
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| Summary: | Abstract The Trait-Based Model of Recovery is a strengths-focused intervention designed to enhance personality traits and reduce mental health symptoms, such as anxiety and depression, among individuals recovering from addiction. This study evaluated the model’s effectiveness using a quasi-experimental pre-post design across diverse settings, including residential and outpatient programs in Kentucky and a pretrial diversion program in Albuquerque, New Mexico, highlighting its broad applicability and generalizability. Participants (N = 139) exhibited substantial reductions in depression (71.5%) and anxiety (58.5%), alongside significant improvements in nine of ten targeted traits, notably resilience and self-awareness. Retention was considerably higher in the intervention group (97.1%) compared to the comparison group’s substantial attrition (15.5% retained). Empathy slightly declined post-intervention, indicating an area for further refinement. The findings support the Trait-Based Model of Recovery as a holistic and strengths-focused framework capable of effectively addressing addiction and co-occurring mental health disorders. By enhancing traits and addressing their potential negative expressions, this approach provides meaningful therapeutic value across diverse recovery contexts. Future research should explore the long-term sustainability of outcomes and identify targeted strategies to enhance traits such as empathy, further optimizing this innovative recovery approach. |
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| ISSN: | 2045-2322 |