Effect of Group Logotherapy on Anxiety About Death and Existential Loneliness in Patients With Advanced Cancer
Bibliographic record
Abstract
BACKGROUND: Although logotherapy has been shown to relieve other psychological symptoms of patients with cancer, no studies have specifically investigated the effect of logotherapy on anxiety about death and existential loneliness in these patients. OBJECTIVE: The aim of this study was to determine the effect of group logotherapy on anxiety about death and existential loneliness in patients with advanced cancer. METHODS: Sixty-three patients who were in the advanced stage of cancer were recruited from 2 hospital oncology services and were randomly assigned to either experimental (n = 31) or control group (n = 32). The intervention group received 10 weekly 2-hour group logotherapy. Templer's Death Anxiety Scale and ELQ were completed pre- and posttreatment. RESULTS: A 2 × 2 mixed analysis of variance was used to determine the effect of the treatment on each of the dependent variables. The analyses revealed that patients in the logotherapy group reported a significant decrease in anxiety about death and existential loneliness after (vs before) the treatment. No significant decreases were observed in the waitlist control group. CONCLUSIONS: These results have implications for treating death anxiety and feelings of existential loneliness among patients with advanced cancer. They suggest that group logotherapy is highly effective in reducing these existential concerns. Limitations and avenues for future research are discussed. IMPLICATIONS FOR PRACTICE: The study emphasizes that group logotherapy can be considered in oncology care programs by healthcare professionals and in educational curriculums and is suggested for use among caregivers and patients with advanced cancer.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".