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Record W4224270401 · doi:10.2196/36821

Participants’ Perceptions of Essential Coaching for Every Mother—a Canadian Text Message–Based Postpartum Program: Process Evaluation of a Randomized Controlled Trial

2022· article· en· W4224270401 on OpenAlexaffvenueabout
Justine Dol, Megan Aston, Douglas McMillan, Gail Tomblin Murphy, Marsha Campbell‐Yeo

Bibliographic record

VenueJMIR Formative Research · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsNova Scotia Health AuthorityDalhousie UniversitySt. Michael's Hospital
Fundersnot available
KeywordsCoachingRandomized controlled trialMedicinePsychological interventionIntervention (counseling)Family medicineThematic analysisNursingPsychologyQualitative research

Abstract

fetched live from OpenAlex

BACKGROUND: "Essential Coaching for Every Mother" is a Canadian text message-based program that sends daily messages to mothers for 6 weeks after they give birth. There is a need to explore the program's effectiveness in terms of the participants' experience to guide refinement and modification. OBJECTIVE: This study aimed to describe the process evaluation of the Essential Coaching for Every Mother randomized controlled trial through an evaluation of the research implementation extent and quality. METHODS: Participants were recruited from Nova Scotia, Canada, between January 5 and August 1, 2021. Enrolled participants were randomized into the intervention or control group. Participants randomized to the intervention group received standard care along with the Essential Coaching for Every Mother program's text messages related to newborn and maternal care for the first 6 weeks after giving birth, while the control group received standard care. Usage data were collected from the SMS text message program used, and participants completed web-based questionnaires at 6 weeks after birth. Quantitative data and qualitative responses to open-ended questions were used to triangulate findings. Quantitative data were summarized using means, SDs, and percentages, as appropriate, while qualitative data were analyzed using thematic analysis. RESULTS: Of the 295 unique initial contacts, 150 mothers were eligible and completed the baseline survey to be enrolled in the study (intervention, n=78; control, n=72). Of those randomized into the intervention group, 75 (96%) completed the 6-week follow-up survey to provide feedback on the program. In total, 48 (62%) intervention participants received all messages as designed in the Essential Coaching for Every Mother program, with participants who enrolled late missing on average 4.7 (range 1-12) messages. Intervention participants reported an 89% satisfaction rate with the program, and 100% of participants would recommend the program to other new mothers. Participants liked how the program made them feel, the format, appropriate timing of messages, and content while disliking the frequency of messages and gaps in content. Participants also provided suggestions for future improvement. CONCLUSIONS: Our process evaluation has provided a comprehensive understanding of interest in the program as well as identified preference for program components. The findings of this study will be used to update future iterations of the Essential Coaching for Every Mother program. TRIAL REGISTRATION: ClincalTrials.gov NCT04730570; https://clinicaltrials.gov/ct2/show/NCT04730570.

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)0.070
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.368

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0700.074
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.142
GPT teacher head0.559
Teacher spread0.417 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2022
Admission routes3
Has abstractyes

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