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Record W4310388175 · doi:10.2196/37827

A Web-Based Self-help Intervention for Coping With the Loss of a Partner: Protocol for Randomized Controlled Trials in 3 Countries

2022· article· en· W4310388175 on OpenAlexvenueno aff
Jeannette Brodbeck, Sofia Jacinto, Afonso Gouveia, Nuno Mendonça, Sarah Madörin, Lena Brandl, Lotte Schokking, Ana Maria Rodrigues, Judite Gonçalves, Bettina Mooser, Marta M. Marques, Joana Isaac, Vasco Nogueira, Lex van Velsen

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsnot available
FundersInnosuisse - Schweizerische Agentur für InnovationsförderungZonMwActive and Assisted Living programmeEuropean Commission
KeywordsLonelinessGriefRandomized controlled trialCoping (psychology)PopulationPsychological interventionSelf-efficacyMedicinePsychologyFocus groupClinical psychologyPsychotherapistPsychiatry

Abstract

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BACKGROUND: The death of a partner is a critical life event in later life, which requires grief work as well as the development of a new perspective for the future. Cognitive behavioral web-based self-help interventions for coping with prolonged grief have established their efficacy in decreasing symptoms of grief, depression, and loneliness. However, no study has tested the efficacy for reducing grief after losses occurring less than 6 months ago and the role of self-tailoring of the content. OBJECTIVE: This study aims to evaluate the clinical efficacy and acceptance of a web-based self-help intervention to support the grief process of older adults who have lost their partner. It will compare the outcomes, adherence, and working alliance in a standardized format with those in a self-tailored delivery format and investigate the effects of age, time since loss, and severity of grief at baseline as predictors. Focus groups to understand user experience and a cost-effectiveness analysis will complement the study. METHODS: The study includes 3 different randomized control trials. The trial in Switzerland comprises a waitlist control group and 2 active arms consisting of 2 delivery formats, standardized and self-tailored. In the Netherlands and in Portugal, the trials follow a 2-arm design that will be, respectively, complemented with focus groups on technology acceptance and cost-effectiveness analysis. The main target group will consist of adults aged >60 years from the general population in Switzerland (n≥85), the Netherlands (n≥40), and Portugal (n≥80) who lost their partner and seek help for coping with grief symptoms, psychological distress, and adaptation problems in daily life. The trials will test the intervention's clinical efficacy for reducing grief (primary outcome) and depression symptoms and loneliness (secondary outcomes) after the intervention. Measurements will take place at baseline (week 0), after the intervention (week 10), and at follow-up (week 20). RESULTS: The trials started in March 2022 and are expected to end in December 2022 or when the needed sample size is achieved. The first results are expected by January 2023. CONCLUSIONS: The trials will provide insights into the efficacy and acceptance of a web-based self-help intervention among older adults who have recently lost a partner. Results will extend the knowledge on the role of self-tailoring, working alliance, and satisfaction in the effects of the intervention. Finally, the study will suggest adaptations to improve the acceptance of web-based self-help interventions for older mourners and explore the cost-effectiveness of this intervention. Limitations include a self-selective sample and the lack of cross-cultural comparisons. TRIAL REGISTRATION: Switzerland: ClinicalTrials.gov NCT05280041; https://clinicaltrials.gov/ct2/show/NCT05280041; Portugal: ClinicalTrials.gov NCT05156346; https://clinicaltrials.gov/ct2/show/NCT05156346. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37827.

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 imitation

Not 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.

metaresearch head score (Codex)0.049
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.071
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.042
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0160.009
Bibliometrics0.0040.005
Science and technology studies0.0040.004
Scholarly communication0.0050.004
Open science0.0030.003
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0710.011

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.

Opus teacher head0.225
GPT teacher head0.586
Teacher spread0.361 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

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".

Quick stats

Citations11
Published2022
Admission routes1
Has abstractyes

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