The Impact of a Text Messaging Service (Tonsil-Text-To-Me) on Pediatric Perioperative Tonsillectomy Outcomes: Cohort Study With a Historical Control Group
Bibliographic record
Abstract
BACKGROUND Tonsillectomy is one of the most common pediatric surgical procedures performed in North America. Caregivers experience complex challenges in preparing their child for surgery and coordinating postoperative care at home. Uncertainty and confusion can arise across the perioperative pathway, leading to poorer health outcomes for children and an increase in health service utilization. Effectiveness studies on text-message interventions for caregivers during perioperative pediatric tonsillectomy are scarce. Earlier feasibility results of the ‘Tonsil-Text-To-Me’ intervention were promising with high levels of satisfaction and engagement. OBJECTIVE The aim of this study was to pilot test Tonsil-Text-To-Me to determine if and how it might improve perioperative experiences for caregivers and patient outcomes. METHODS Caregivers of children aged 3-14 years undergoing tonsillectomy were included. Data from a historical control group and intervention group (during COVID-19) were compared. Data were collected on the day before surgery, 3 days post-surgery, and 14 days post-surgery. The intervention consisted of 15 text messages sent starting 2 weeks before surgery up to the eighth day after surgery. Texts focused on activity reminders, links to nutrition and hydration tips, pain management strategies, and guidance on monitoring for complications. Measures included the Parenting Self-Agency Measure, General Health Questionnaire-12, Parents’ Postoperative Pain Measure, Client Satisfaction Questionnaire-8, engagement analytics (i.e., frequency of link clicks), as well as analgesic consumption, pain, child activity, and multiple health service utilization questions. Descriptive and inferential statistics were performed to summarize and compare results. RESULTS Fifty-one caregivers participated (32 control; 19 intervention). Ninety-eight percent (50/51) reported being daily users of text-messaging prior to the study. Intervention group caregivers had a statistically significant positive difference in Parenting Self-Agency Measure scores (p=0.001). Positive but nonsignificant trends for the texting intervention compared to usual care were observed for Parents' Postoperative Pain Measure, highest level of pain, child’s return to normal activity levels, and a range of health service utilization measures. Pain levels for both control and intervention groups met the clinically significant threshold. Participants rated the intervention as highly satisfactory across all eight Client Satisfaction Questionnaire dimensions (Mean= 29.4 out of 32.0). Engagement with the service was high and the most frequently engaged texts related to the virtual tour of the day surgery unit and the checklist of what to bring to the hospital. CONCLUSIONS Preliminary results from this cohort study with historical control group comparator found that Tonsil-Text-To-Me had a positive impact on caregivers’ perioperative care experience. The small sample size and unclear impacts of COVID-19 on study design should be considered when interpreting results. Controlled trials with larger sample sizes for evaluating text-message interventions aimed to support caregivers of children undergoing tonsillectomy surgery are warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".