Group Leader and Member Here-and-now Focus and Therapeutic Factors: A Linguistic Inquiry and Word Count Analysis
Bibliographic record
Abstract
OBJECTIVE: Yalom (1985) believed that working in the here-and-now of the group is essential to facilitating the "therapeutic factors" necessary for a successful outcome. Yet, we currently lack research examining whether a here-and-now in-session focus predicts the therapeutic factors, as theorized. METHODS: (LIWC) analysis to assess group member and leader in-session here-and-now focus by analyzing words spoken in a session. RESULTS: The results suggest that when group leaders use more here-and-now words in a speaking turn, group members use more here-and-now words in the subsequent speaking turn. However, contrary to expectation, group leaders and group members "matching" on here-and-now language in a session did not predict more therapeutic factors in between sessions, but rather less social learning. Instead, how consistent or variable group members or leaders were in their here-and-now focus generally predicted more therapeutic factors. CONCLUSION: These results suggest that LIWC may be a promising vehicle to assess here-and-now language in group therapy sessions and that a here-and-now in-session focus has a complex relationship with the therapeutic factors.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".