Text message conversations between peer supporters and women to deliver infant feeding support using behaviour change techniques: A qualitative analysis
Bibliographic record
Abstract
OBJECTIVE: To analyse text message conversations between peer supporters (called Infant Feeding Helpers - IFHs) and new mothers using qualitative methods to understand how peer support can influence and support women's feeding experiences. DESIGN: Qualitative analysis of text messages conversations using both inductive thematic and deductive content approaches to coding. Thematic analysis of the text message transcripts and deductive content analysis was used to code if Behaviour Change Techniques (BCTs) were employed by IFHs in their interactions with women. BCTs coded in text messages were then compared with those tabulated from antenatal meeting recordings and documented in interview transcripts. PARTICIPANTS AND SETTING: 18 primiparous women and 7 Infant Feeding Helpers from one community site in South-West England. FINDINGS: Three key themes were identified in the18 text message conversations (1679 texts): 'breastfeeding challenges', 'mother-centred conversations', and 'emotional and practical support'. The core BCTs of 'social support' and 'changing the social environment' were found at least once in 17 (94 %) and 18 (100 %) text message conversations respectively. Meanwhile, 'instruction to perform the behaviour' was used at least once in over 50 % of conversations. Generally, the use of BCTs was greatest between birth and two weeks during a period of daily texts when women reported many feeding challenges. The number and range of BCTs used in text messages were similar to those documented in audio-recorded meetings and interview accounts. CONCLUSION AND IMPLICATIONS: Infant Feeding Helpers were able to provide engaging and successful breastfeeding peer support through text messages. Messaging was shown to be an appropriate and accessible method of delivering BCTs focussing on 'social support' and 'changing the social environment'. Peer supporters delivering BCTs via text messages is acceptable and appropriate to use if in-person support is limited due to unforeseen circumstances such as the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".