Digital Health: The Critical Value of Mobile Technology for the Health Sector, Different Application Examples from the World and Current Trends
Bibliographic record
Abstract
The internet technology, which began to integrate into our lives rapidly by the end of the 1990s, underwent significant transformations with the advent of mobile technology in the 2000s. Initially accessible through desktop or notebook computers, the internet has evolved to become an integral part of virtually every aspect of our lives as mobile technology advanced throughout the 2000s. The purpose of this study is to examine the role of mobile technologies within current health technologies, investigate the necessary competencies, evaluate mobile technology developments both in Türkiye and globally, and assess the information technology infrastructure, competencies, and skills required by the sector. Our research details various and specific mobile applications from numerous countries. Findings indicate that mobile technology has established itself much more rapidly and effectively in countries with strong internet infrastructure. Mobile health services are perceived as highly valuable by citizens. The real quality and effectiveness of mobile technology depend on its acceptance and swift implementation by users. Gamification is an important tool in the adoption of mobile health applications. These applications can enhance motivation by enabling both doctors to monitor patient care services and patients to track their own health. A good mobile health system should be accepted by both patients and doctors. In countries like Türkiye, where the health system is largely supported by the state, it is seen as necessary for the Ministry of Health to prioritize mobile services to establish a robust mobile health system. Furthermore, to effectively structure mobile services, it is essential to focus on the right problems and identify issues in order of priority. Literature review reveals that various mobile applications have been implemented in fields such as dermatology, orthopedics, ophthalmology, neurosurgery, and clinical pathology. Mobile technologies offer significant cost advantages in the delivery of health services. As the population ages in European Union countries, national governments are seeking ways to reduce healthcare costs. Mobile health is considered a solution to transform the delivery of health services and reduce costs through viable new care models for both industrialized and developing countries. Moreover, it has been observed that mobile applications provide significant benefits for the elderly, particularly in developed countries such as Germany and Sweden. Our study provides a comprehensive assessment of mobile technology in the healthcare sector, highlights prominent applications from Türkiye and around the world, and offers an extensive evaluation for field readers.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".