Therapy Online: A Web-Based Video Support Group for Family Caregivers of Survivors With Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVE: This innovative descriptive study explores the benefits of a traumatic brain injury (TBI) caregiver support group intervention provided using videoconferencing within a password protected Web-based platform. METHODS: Ten caregivers of family members with TBI were registered to a password-protected Web site (Caring for Others) that provided information about caring for a person with TBI and access to a videoconferencing support group intervention program. Where needed, caregivers were provided with computer equipment, Internet access, and training to negotiate the Web site links. Two groups of 5 caregivers of survivors of TBI participated (average age of survivor-20 years, average time since injury-4.6 years) and met online with a trained clinician weekly for 10 sessions. Using directed content analysis, transcripts of each session were coded with NVivo software. RESULTS: The content analysis reported group process themes, therapeutic interventions used, caregiver outcomes, and the challenges for clinicians delivering a therapeutic intervention online. CONCLUSIONS: Traumatic brain injury caregivers shared similar concerns and problem-solving strategies for managing caregiving tasks. Overall, participants found the sessions helpful for managing the emotional impact of caring for a family member with TBI.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".