Development of a Web-Based School Support System Within the AVATAR Project for Psychosocial Well-being in Adolescents: Pilot Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Health and well-being promotions are key points of educational programs for adolescents within schools. There are several health education programs mainly based on lifestyle habit changes; however, social and emotional dimensions should be considered within these educational strategies. OBJECTIVE: This study aimed to (1) develop a new web-based school support system to assess and analyze individual, classroom, and scholastic institute data on lifestyle habits, social context, emotional status, and scholastic performance; (2) create a web tool for managing the well-being of adolescents through a dynamic and personalized interface that provides immediate feedback that allows the school to monitor progress; and (3) evaluate, in a pilot study, the feasibility of this web-based school support system in order to build health programs that are specific to the needs of the studied population. METHODS: The AVATAR (a new purpose for the promotion and evaluation of health and well-being among healthy teenagers) method consists of integrating the information coming from different questionnaires. In particular, to allow planning didactic and educational actions based on the results obtained, the AVATAR approach allows subdivision of the results of the different observed variables and the 4 components into the following 3 percentile categories: modify, improve, and maintain. The AVATAR web platform was designed to collect data on lifestyle, emotional status, and social context from junior high schools in terms of the fundamental aspects of adolescent daily life, with free use by the scholastic community (scholars, teachers, and parents). In this pilot/feasibility study, data from 331 students were acquired between 2018 and 2019 at the beginning of the scholastic year (pre) and at the end following the school-based program (post). RESULTS: Preliminary results showed that after school planning and specific program implementation, defined after AVATAR feedback, students reported better well-being perception characterized by higher perception in psychological well-being (P=.001), mood (P=.001), self-perception (P=.006), and autonomy (P=.001), and an increase in the perception of financial resources (P=.001), which helped in developing healthy lifestyle habits (P=.007). In the social context assessment, students reported stronger relationships with family (P=.02) and peers (P=.001), and a lower perception of bullying (P=.001). CONCLUSIONS: The AVATAR web-based platform is a feasible and flexible tool for the health and well-being management of adolescents from epidemiological, preventive, and educational points of view. In particular, it can be used to (1) promote information campaigns aimed at modifying risk behaviors in the student population, (2) sensitize students and put them at the center of their growth path, (3) inform institutions about the health and well-being of the school population, (4) ensure health programs are acceptable and feasible to users before launching on a large scale, and (5) improve the relationship of users (school) and educational agencies with research groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".