Effectiveness of Telemedicine in Managing Health-Related Issues in the Pediatric Population: A Systematic Review
Bibliographic record
Abstract
Healthcare delivery is made more convenient and effective via telemedicine, which enables physicians to conduct virtual consultations and evaluations with pediatric patients. The purpose of this systematic review was to evaluate the efficacy of telemedicine as compared to physical appointments in the pediatric population. We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to search for the available literature using pre-specified inclusion and exclusion criteria. These databases provided 968 relevant research articles, which Endnote software screened for duplicates. Fourteen studies were considered relevant for full-text evaluation. After complete text evaluation, only 11 of these articles were found to be relevant. The Newcastle-Ottawa Scale (NOS) was used for the risk of bias assessment of all included studies. Eleven articles in all satisfied the requirements for inclusion and were added to the review. Every study was classified as either a cluster randomized trial (27%) or a randomized controlled trial (RCT) (73%). There were between 22 and 400 participants in each trial. Medical conditions evaluated included obesity (27%), mental health disorders (9%), asthma (18%), otitis media (9%), skin disorders (9%), type 1 diabetes (9%), attention deficit hyperactivity disorder (ADHD) (9%), and pancreatic insufficiency associated with cystic fibrosis (1/11). Telemedicine strategies employed included telemedicine-based screening visits (9%), smartphone-based therapies (27%), phone counseling (18%), and videoconferencing visits between patients and doctors (45%). The outcomes of the telemedicine procedures in every included study were on par with or superior to those of the control groups. Medication adherence, appointment completion rates, life satisfaction, symptom management, and disease progression were all outcomes associated with these findings. Although more research is needed, the evidence from this review suggests that telemedicine services for the general public and pediatric care are comparable to or better than in-person services. Patients, healthcare professionals, and caregivers may benefit from using both telemedicine services and traditional in-person healthcare services. To maximize the potential of telemedicine, future research should focus on improving patients' access to care, increasing the cost-effectiveness of telemedicine services, and eliminating barriers to telemedicine use.
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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 | 0.011 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".