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Record W3162382551 · doi:10.21203/rs.3.rs-458921/v1

Internet Mentalization Informed Video Feedback (MI-VF) Intervention to Improve Parental Sensitivity in Mother-Infant Dyads with Maternal Depressive Symptoms: Study Protocol for a Randomized Controlled Feasibility Trial

2021· preprint· en· W3162382551 on OpenAlexaff
Marcia Olhaberry, Fanny Leyton, Javier Morán, María José León, Catalina Sieverson, Antonia Muzard, Carolina Honorato, Karin Ensink, Norka Malberg, Patrick Luyten, Stefanella Costa‐Cordella

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversité Laval
FundersAgencia Nacional de Investigación y Desarrollo
KeywordsMentalizationMaternal sensitivityRandomized controlled trialIntervention (counseling)Protocol (science)PsychologyClinical psychologyPsychotherapistMedicineDevelopmental psychologyPsychiatryAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: Depressive symptoms in the postpartum period are a highly prevalent mental health problem. COVID-19 restrictions have increased maternal clinical symptoms during the postpartum period, leading to a high demand for mental health assistance and the need for cost-effective care adjusted to this new context. Video feedback (VF) has been a particularly cost-effective strategy in early interventions focused on maternal sensitivity. However, these interventions usually do not include mentalization as one of the critical elements involved in sensitive and attachment relationships. Also, these interventions are generally carried out in face-to-face settings. This study's main goal is to evaluate the feasibility and acceptability of a brief internet mentalization informed with VF to improve the sensitive response in mother-baby dyads with postpartum depressive symptoms attended in primary health centers.Methods/design: This randomized feasibility trial will include 60 mother-baby dyads. Participants will be randomized and allocated in a 1:1 ratio. A random number sequence will be computer-generated in varying block sizes (2&4) and stratified by center. The intervention aims to improve maternal sensitivity and mentalizing by using a model based on video-feedback methodology in a virtual modality. The intervention consists of four sessions plus one pre-intervention assessment session and psychoeducational cards. Control dyads will receive only psychoeducational cards once a week. Additionally, dyads from both groups will receive the health center’s treatment as usual. A MI-VF manual guides each intervention session, but its application is tailored to each dyad, VF therapists will receive one weekly group supervision session. Data will be collected at baseline, 4 weeks and 3 months follow-up. The main goal of this trial is to assess feasibility outcomes (recruitment rate and data completion) and change in maternal sensibility.Discussion: This study will inform parameters for the future implementation of a large randomized controlled clinical trial, contributing to the current scarce evidence on mentalization informed interventions that use VF as their primary intervention strategy. Also, this study will provide a cost-effective internet-based intervention model, feasible to be implemented in public health settings.Trial registration: NCT04748731

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)0.015
metaresearch head score (Gemma)0.013
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 score0.044
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.013
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0440.006

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.

Opus teacher head0.056
GPT teacher head0.444
Teacher spread0.388 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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