La théorie de la noyade émotive virtuelle : une théorisation ancrée sur le processus de recherche d’aide d’adolescents à risque de suicide
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,027 |
| Communication savante | 0,007 | 0,012 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».