Text messaging to improve connection between adolescents and their health care providers
Bibliographic record
Abstract
Objective Adolescence marks a time of transition where teenagers are learning to advocate for themselves. In those with underlying chronic conditions such as adolescent dysautonomia, improving communication between clinic visits may improve connection with their health care provider which may aide management. Our aims were as follows: (1) to implement a text message platform to increase communication between adolescent patients and health care provider (HCP); (2) to evaluate its effect on quality of life (QoL), symptom burden, and patient engagement; and (3) to determine patient satisfaction with the platform. Methods Participants (age 12–18) with access to a personal mobile phone were recruited from a pediatric dysautonomia clinic. A weekly automated text message asking “How are you?” was sent to participants (WelTel Inc.). Responses were triaged to HCP and responded to within 48 hours. Results Twenty-six participants with median (interquartile range) age of 16.8 (15.7–17.4) years completed the study. Duration of the text messaging intervention was 33 (26.8–37.3) weeks. A total of 896 automated weekly messages were sent, which resulted in 206 (23%) care conversations. Participants found texting useful (96%) and produced feelings of connection to their HCP (92%). There was no change in overall QoL or symptom burden ( p > 0.05). Conclusion A text message platform was successfully implemented in adolescents seen in our Dysautonomia Clinic. Patients were engaged, satisfied with the platform, and felt connected to their HCP despite no changes in QoL or symptom burden.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".