Developing an Internet-Based Support System for Adolescents with Depression
Bibliographic record
Abstract
BACKGROUND: Depression is the most common mental health problem among adolescents. Despite policy guidance and governmental support to develop usable mental health services, there is still a lack of easily accessible and modern interventions available for adolescents in Finland's majority official language. OBJECTIVE: Our objective was to develop a user-friendly and feasible Internet-based support system for adolescents with depression. METHODS: The Internet-based support system for adolescents with depression was developed. To create this new intervention, some examples of existing interventions were studied, the theoretical basis for the intervention was described, and the health needs of adolescents identified. As an outcome of the process, the results were combined and the content and delivery of a new intervention will be described here. RESULTS: Six individual weekly Internet-based support sessions were delivered by a tutor over a 6-week period of time and developed to form an intervention called Depis.Net. This was an Internet-based support system for adolescents with depression tailored to improve self-management skills and increase awareness of their own well-being and mental health. The intervention was accessible via an electronic platform, which was secured and password protected for users. The intervention on the Depis.Net website consisted of elements identifying adolescents' needs, and offering self-monitoring, access to health information and self-reflective written exercises. An educated nurse tutor gave written feedback to each adolescent via the electronic platform. CONCLUSIONS: An Internet-based support system for adolescents with depression was developed using a systematic approach with four steps. This was done to ensure that the intervention had a sound theoretical background and at the same time caters flexibly for the problems that adolescents commonly face in their daily lives. Its potential for adolescents visiting outpatient clinics will be evaluated in the next phase by means of a randomized controlled trial.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".