New horizons in group psychotherapy research and practice from third wave positive psychology: a practice-friendly review
Bibliographic record
Abstract
Group psychotherapy has been shown to be equivalent to individual therapy for many disorders, including anxiety, depression, grief, eating disorders, and schizophrenia (Burlingame & Strauss, 2021). In addition to effectiveness in reducing symptoms, group offers members a sense of belonging, purpose, hope, altruism, and meaning throughout treatment (Yalom & Leszcz, 2020). These additional outcomes are especially important considering the COVID-19 pandemic and national/international conflicts, given the trauma, disruptions, and losses people have experienced. Applying recent developments in positive psychology to group therapy can enhance treatment. A practice-friendly review examined recent advances in the positive psychology literature, demonstrating how group therapy offers members unique growth opportunities in addition to reducing symptoms. Key findings from studies applying positive psychological constructs to group therapy outcomes are synthesized. Our review sheds light on the relevance of third wave positive psychology to enrich group therapy (Lomas et al., 2021). Specifically, group therapy can facilitate the development of vitalizing psychological virtues, and these can be used to assess treatment outcome: humanity, wisdom, transcendence, courage, temperance, and justice. Interrelatedly, we present support for including attachment theory and mentalization within a positive psychological group framework. Implications are explored for group therapy research, clinical work, and training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".