Tecnologias para a promoção da saúde de estudantes universitários: revisão de escopo
Bibliographic record
Abstract
The impact of the new reality and the obligations of students in higher education can trigger a series of problems. Thus, university spaces are strategic environments for the development of health promotion actions for these students. For this, the use of tools is important to facilitate approximation, interest and collaboration, especially among young people. Thus, the objective of the present study was to analyze the technologies and their contributions to the promotion of the health of university students in the health area. The study developed a Scoping Review based on the JBI. The following research questions were adopted: “What are the technologies for promoting the health of university students in the health area present in the literature? What are the advantages and characteristics of using these technologies?” The sources selected for the study were: Medline/Pubmed, Cumulative Index to Nursing and Allied Health Literature, Web of Science, Latin American and Caribbean Literature in Health Science, Nursing Databases, Scopus, Cochrane, SciElo, Education Resources Information Center, Catalog of Theses and Dissertations by the Coordination for the Improvement of Higher Education Personnel, The National Library of Australia's, Academic Archive Online, Digital Access to Research Theses, Europe E-Theses Portal, Electronic Theses Online Service, Repositorio Científico de Acesso Aberto de Portugal, National ETD Portal, Theses Canada and Google Scholar. A total of 42,294 studies were found and 71 articles were selected for this research. The studies were mostly published in the United States of America, with the main methodology being experimental studies. Among the target audience, there was a predominance of nursing and medicine students, aged between 17 and 54 years. Regarding technologies, the most predominant was light technologies, 34 studies (47.9%), the use of health education, group training and mindfulness/mindfulness were the most used, followed by light/hard technologies 25 studies (35.2%) and technology lasts 12 articles (16.9%). The main focus was on students' mental health in addition to their physical health. The most frequent time of application of the technology was up to eight weeks, being applied mostly in spaces of the university itself, such as classrooms, on the web and outdoors and gymnasiums. Due to the variety of technologies, the materials used were also diverse. Most of the studies did not consider the previous assessment of the health of the students, being only applied to technology. The use of these technologies has shown positive effects in promoting the health of students in the health area, with an improvement in depressive symptoms, anxiety, stress, as well as an increase in the practice of physical activities and also an improvement in the ability to deal with academic stressors. Academic stress experienced by healthcare students can impair health and performance. Thus, these technologies are important strategies to be adopted by educational institutions to ensure the health of their students.
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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 | 0.044 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.035 | 0.042 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".