Impact of Facebook on Glucose Control in Type 1 Diabetes: A Three-Year Cohort Study
Bibliographic record
Abstract
BACKGROUND: As the world is changing, traditional health care services should be adapted for the new era of technology and the Internet. One of the possible ways for communication between health care providers and patients is social media. There are several benefits of social media in health: increased interactions with others; more available and shared information; increased accessibility; social or emotional support. OBJECTIVE: The aim of this study was to evaluate the results of Facebook and CareLink software as a possible Internet tool to improve diabetes control in type 1 diabetes patients using a sensor augmented pump. METHODS: A total of 67 adolescents with type 1 diabetes and in the age range of 14-23 years were randomized in 2 groups: (1) Traditional group and (2) Internet group. In the traditional group, 34 patients were treated using standard medical protocol with regular clinic visits, where data were uploaded at the clinic and interventions (pump settings-basal bolus insulin and education) were delivered to the patient. In the Internet group, 33 patients were treated using Facebook and CareLink software (Medtronic Diabetes) on a monthly basis, where the data were uploaded by the patient at home and interventions (same as traditional group) were delivered via Facebook (written reports and chats). Both the traditional and Internet group had regular visits every 3 months with standard medical protocol. Glycosylated hemoglobin (HbA1c) was obtained before and every 3 months during the study for a 3-year-period. RESULTS: The improvement in glucose control was found in both groups: 7.9% (SD 1.4) [62.8 mmol/mol (SD 12.9)] to 6.9% (SD 1.2) [51.9 mmol/mol (SD 10.8)] in the traditional group, and 7.8% (SD 1.8) [61.7 mmol/mol (SD 17.2)] to 6.7% (SD 1.8) [49.7 mmol/mol (SD 17.3)] in the Internet group). Significant improvement of HbA1c (P<.05) was found in favor of the Internet group. CONCLUSIONS: Social media such as Facebook as a tool can assist in standard medical care to improve glucose control in a long term period in adolescents with type 1 diabetes using insulin pump therapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 0.001 |
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".