Therapist-Assisted Web-Based Intervention for Prolonged Grief Disorder After Cancer Bereavement: Randomized Controlled Trial
Bibliographic record
Abstract
Background Bereavement due to cancer increases the risk of prolonged grief disorder. However, specialized treatment options for prolonged grief after a loss due to illness are still scarce. Objective The aim of this study is to extend previous findings by evaluating a web-based cognitive behavioral intervention with asynchronous therapist support, consisting of structured writing tasks adapted specifically for prolonged grief after cancer bereavement. Methods The intervention was evaluated in a purely web-based randomized waitlist-controlled trial. Open-access recruitment of participants was conducted on the web. Prolonged grief (Inventory of Complicated Grief), depression, anxiety, posttraumatic stress, posttraumatic growth, somatization, sleep quality, and mental and physical health were assessed on the web via validated self-report measures. Results A total of 87 participants were randomized into the intervention group (IG; 44/87, 51%) or the waitlist control group (43/87, 49%). Of the participants, 7% (6/87) dropped out of the study (5/44, 11%, in the IG). Of the 39 completers in the IG, 37 (95%) completed all intervention tasks. The intervention reduced symptoms of prolonged grief (intention-to-treat: P<.001; η2=0.34; Cohen d=0.80) to a clinically significant extent. It had favorable effects on depression, anxiety, posttraumatic stress, posttraumatic growth, and overall mental health but not on somatization, sleep quality, or physical health. Conclusions The web-based intervention for prolonged grief after cancer bereavement is effective in reducing symptoms of prolonged grief disorder and accompanying syndromes in a timely, easily realizable manner and addresses specific challenges of bereavement to illness. Considering web-based approaches in future mental health care policy and practice can reduce health care gaps for those who are bereaved to cancer. Trial Registration German Clinical Trial Register U1111–1186-6255; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00011001
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".