The Impact of a Text Messaging Service (Tonsil-Text-To-Me) on Pediatric Perioperative Tonsillectomy Outcomes: Cohort Study With a Historical Control Group
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».