A Group-Based Telehealth Intervention for Birth Trauma: Protocol for a Pilot Feasibility and Waitlist Control Trial
Notice bibliographique
Résumé
BACKGROUND: Traumatic childbirth experiences affect almost half of Australian women giving birth and can lead to significant mental health impacts, including postpartum depression, anxiety. and posttraumatic stress disorder (PTSD). Despite evidence supporting psychological interventions for birth trauma, there are prominent gaps in the accessibility of these treatments, particularly for postpartum women in regional or rural areas, who face long waitlists, geographical isolation, and high financial costs. Although narrative approaches hold promise for addressing birth-related trauma, no research study to date has specifically trialed a narrative-informed, group-based telehealth intervention in this space. OBJECTIVE: This study aims to assess the acceptability and feasibility of a narrative-informed, group-based telehealth intervention for postpartum women in reducing the mental health impacts of having experienced a traumatic childbirth. METHODS: This pilot feasibility trial with a waitlist control design evaluated a six-session narrative-informed, group-based intervention delivered weekly via telehealth to postpartum women who experienced a traumatic childbirth within the past 6 months. The intervention incorporated narrative therapy techniques, such as externalization, double-listening, and outsider witnessing. Participants from a specific catchment area of predominantly rural towns in New South Wales in Australia were randomly assigned to either an intervention group (IG) or a waitlist control group (WCG). Quantitative measures assessing mental health symptoms of postpartum depression (Edinburgh Postnatal Depression Scale [EPDS]), anxiety (Perinatal Anxiety Screening Scale [PASS]) and posttraumatic stress (City Birth Trauma Scale [City BiTS]) were administered prior to, in between, and at the end of treatment, and measures of client satisfaction (Client Satisfaction Questionnaire [CSQ-8]) and group cohesion (Group Cohesiveness Scale [GCS]) were administered on completion of the intervention. RESULTS: The project was funded in March 2024. Recruitment was completed between July and August 2024. Eleven pretreatment sessions were held in August 2024. Of the 33 expressions of interest (EOIs) received by August 2024, 9 participants were recruited and randomized to the IG (n=4, 44.4%) and the WCG (n=5, 55.6%). The IG completed the six-session program between September and October 2024, with data collection finalized for pre-, mid-, and postintervention timepoints. The WCG began receiving the intervention mid-October 2024, with the final data collection in December 2024. Key feasibility and acceptability metrics include attendance rates, participant retention, and group cohesion scores. Data analysis is ongoing, with manuscript preparation planned for mid-late 2025. CONCLUSIONS: This study addresses a critical gap in evaluating scalable, accessible mental health interventions for birth trauma recovery. By using narrative approaches in a telehealth group format, this intervention directly responds to the barriers around accessibility and affordability highlighted in recent policy recommendations. Thus, findings from this pilot study could provide important directions in reducing the burden on perinatal mental health services in regional and rural Australia. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ANZCTR12624000460505p; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12624000460505p. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/69051.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,020 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,007 | 0,004 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,006 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,074 | 0,011 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».