La théorie de la noyade émotive virtuelle : une théorisation ancrée sur le processus de recherche d’aide d’adolescents à risque de suicide
Bibliographic record
Abstract
The use of Information and Communication Technologies (ICT) for help-seeking is becoming more and more common for adolescents at risk of suicide. Objectives The aim of this current study was to better understand the help-seeking process of adolescents at risk for suicide. Methods A grounded theory methodology was used to describe the experience of adolescents at risk of suicide and gain a deeper understanding of their ICT help-seeking process. Data was collected through semi-structured interviews, an ICT help-seeking questionnaire and live observations of ICT help-seeking strategies by the adolescents of this study. Theoretical saturation was reached with a total of 15 adolescents, aged 13 to 17, at risk of suicide. Results The grounded theory that emerged gravitated towards the fact that adolescents chose to virtually deal with emotional drowning. A specific context allowed this central category to emerge and included the adolescents' state, their personal triggers, their social environment as well as their desire to use ICT. The ICT strategies used by the adolescents to deal with their emotional drowning were to distract themselves, to get informed, to reveal themselves or to help others. Adolescents in this study used different ways to distract themselves with ICT. This included reading texts, watching online videos, listening to music and playing games. They also increased their literacy by informing themselves on suicide and mental health problems. However, many adolescents also searched for ways to help them commit suicide. Although most of the results were suicide prevention related, the keywords used by the adolescents remain preoccupying. Revealing their thoughts and their feelings about their emotional state seemed to be easier through ICT. They sometimes chose to reveal themselves anonymously but most of the time, they revealed themselves to use ICT to friends they already had in real life. Also, helping friends through ICT seemed to be very rewarding and helpful to the adolescents of our study even when they were in a state of emotional drowning. These different strategies to virtually deal with their emotional drowning hindered many different consequences which were to grow emotionally, to get help, to get temporary relief, to stay indifferent, to worsen their suicidal thoughts or to attempt suicide. Conclusion Although some negative consequences of ICT emerge from this study, a great deal of the consequences was positive and helpful for these adolescents. Overall, this study shows that ICT offer great opportunities for adolescent suicide prevention. Implications for practice, training and research are further discussed.
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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 | 0.017 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".