Supporting People Who Have Lost a Close Person by Bereavement or Separation: Protocol of a Randomized Controlled Trial Comparing Two French-Language Internet-Based Interventions
Bibliographic record
Abstract
BACKGROUND: Internet-based interventions (IBIs) are as efficient as face-to-face psychotherapy for a variety of mental health disorders, including complicated grief. Most evidence stems from guided IBIs. However, recent research indicates that the benefit of guidance is lower in more interactive IBIs. As such, providing guidance only to people requiring it (guidance on demand) appears a cost-effective solution. This is particularly important to develop given the recent rise in grief symptoms in the context of the COVID-19 pandemic. This paper presents the protocol of a randomized controlled trial comparing the efficacy and adherence rate of 2 IBIs for grief-related symptoms after the loss a close one following death or romantic separation, using a guidance on demand framework. LIVIA 2.0 was developed based on theoretical and empirical findings on grief processes and IBIs, and it will be compared to LIVIA 1 that has already demonstrated its efficacy. OBJECTIVE: Our main hypotheses are that LIVIA 1 (control condition) and LIVIA 2.0 (experimental condition) increase participants' well-being and decrease their distress at posttest and at follow-up, that LIVIA 2.0 is more efficient than LIVIA 1 for all outcomes, and that LIVIA 2.0 has less dropouts than LIVIA 1. METHODS: Outcomes will be assessed at pretest, posttest (12 weeks later), and follow-up (24 weeks later). We will recruit 234 participants through a variety of means, including social media and contacts with the press. Primary outcomes are grief symptoms, depressive symptoms, and eudemonic well-being. Secondary outcomes are anxiety symptoms, grief coping strategies, aspects related to self-identity reorganization, and program satisfaction. LIVIA 2.0 participants will additionally undergo a weekly mood and grief symptom monitoring, allowing us to explore the short-term efficacy of the sessions. RESULTS: The creation and development of the content of LIVIA 2.0 was completed during the first phase of the project. Participant recruitment will begin in May 2022 and will last until January 2023. CONCLUSIONS: This study will emphasize the relevance of the innovations included in LIVIA 2.0 regarding the efficacy and dropout rate of IBIs for grief symptoms and will allow investigations on how these changes impact the demand for guidance. In the current postpandemic times, developing and assessing IBIs targeting grief symptoms are particularly critical given the rise in grief-related symptoms. TRIAL REGISTRATION: clinicaltrials.gov NCT05219760; https://tinyurl.com/3dzztjts. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/39026.
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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 | 0.028 | 0.027 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
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".