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Record W3046106791 · doi:10.2196/19803

Comparing Web-Based Mindfulness With Loving-Kindness and Compassion Training for Promoting Well-Being in Pregnancy: Protocol for a Three-Arm Pilot Randomized Controlled Trial

2020· article· en· W3046106791 on OpenAlexvenueno aff
Amy Finlay‐Jones, Jacqueline Davis, Amanda O’Donovan, Keerthi Kottampally, Rebecca Ashley, Desiree Silva, Jeneva L. Ohan, Susan L. Prescott, Jenny Downs

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsnot available
Fundersnot available
KeywordsMindfulnessCompassionKindnessRandomized controlled trialProtocol (science)Self-compassionPsychologyMedicineWeb applicationPhysical therapyClinical psychologyPsychotherapistApplied psychologyAlternative medicineComputer scienceWorld Wide WebSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Promoting psychological well-being and preventing distress among pregnant women is an important public health goal. In addition to adversely impacting the mother's health and well-being, psychological distress in pregnancy increases the risk of poor pregnancy outcomes, compromises infant socioemotional development and bonding, and heightens maternal and child vulnerability in the postpartum period. Mindfulness and compassion-based interventions show potential for prevention and early intervention for perinatal distress. As there is an established need for accessible, scalable, flexible, and low-cost interventions, there is increased interest in the delivery of these programs on the web. This project aims to pilot a three-arm randomized controlled trial (RCT) to determine the feasibility of a full-scale RCT comparing 2 web-based interventions (mindfulness vs loving-kindness and compassion) with a web-based active control condition (progressive muscle relaxation). OBJECTIVE: The primary objective of this study is to assess the feasibility of an RCT protocol comparing the 3 conditions delivered on the web as a series of instructional materials and brief daily practices over a course of 8 weeks. The second objective is to explore the experiences of women in the different intervention conditions. The third objective is to estimate SD values for the outcome measures to inform the design of an adequately powered trial to determine the comparative efficacy of the different conditions. METHODS: Pregnant women (n=75) participating in a longitudinal birth cohort study (the ORIGINS project) will be recruited to this study from 18 weeks of gestational age. We will assess the acceptability and feasibility of recruitment and retention strategies and the participants' engagement and adherence to the interventions. We will also assess the experiences of women in each of the 3 intervention conditions by measuring weekly changes in their well-being and engagement with the program and by conducting a qualitative analysis of postprogram interviews. RESULTS: This project was funded in September 2019 and received ethics approval on July 8, 2020. Enrollment to the study will commence in September 2020. Feasibility of a full-scale RCT will be assessed using ADePT (a process for decision making after pilot and feasibility trials) criteria. CONCLUSIONS: If the study is shown to be feasible, results will be used to inform future full-scale RCTs. Evidence for flexible, scalable, and low-cost interventions could inform population health strategies to promote well-being and reduce psychological distress among pregnant women. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry Number 12620000672954p; http://anzctr.org.au/ACTRN12620000672954p.aspx. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/19803.

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)0.042
metaresearch head score (Gemma)0.041
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 score0.062
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.041
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0130.007
Bibliometrics0.0030.004
Science and technology studies0.0040.005
Scholarly communication0.0060.005
Open science0.0040.003
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0620.010

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 head0.237
GPT teacher head0.490
Teacher spread0.253 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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