The Journey of Engaging With Web-Based Self-Harm and Suicide Content: Longitudinal Qualitative Study
Notice bibliographique
Résumé
BACKGROUND: Self-harm and suicide are major public health concerns worldwide, with attention focused on the web environment as a helpful or harmful influence. Longitudinal research on self-harm and suicide-related internet use is limited, highlighting a paucity of evidence on long-term patterns and effects of engaging with such content. OBJECTIVE: This study explores the experiences of people engaging with self-harm or suicide content over a 6-month period. METHODS: This study used qualitative and digital ethnographic methods longitudinally, including one-to-one interviews at 3 time points to explore individual narratives. A trajectory analysis approach involving 4 steps was used to interpret the data. RESULTS: The findings from 14 participants established the web-based journey of people who engage with self-harm or suicide content. In total, 5 themes were identified: initial interactions with self-harm or suicide content, changes in what self-harm or suicide content people engage with and where, changes in experiences of self-harm or suicide behaviors associated with web-based self-harm or suicide content engagement, the disengagement-reengagement cycle, and future perspectives on web-based self-harm or suicide content engagement. Initial engagements were driven by participants seeking help, often when offline support had been unavailable. Some participants' exposure to self-harm and suicide content led to their own self-harm and suicide behaviors, with varying patterns of change over time. Notably, disengagement from web-based self-harm and suicide spaces served as a protective measure for all participants, but the pull of familiar content resulted in only brief periods of disconnection. Participants also expressed future intentions to continue returning to these self-harm and suicide web-based spaces, acknowledging the nonlinear nature of their own recovery journey and aiming to support others in the community. Within the themes identified in this study, narratives revealed that participants' behavior was shaped by cognitive flexibility and rigidity, metacognitive abilities, and digital expertise. Opportunities for behavior change arose during periods of cognitive flexibility prompted by life events, stressors, and shifts in mental health. Participants sought diverse and potentially harmful content during challenging times but moved toward recovery-oriented engagements in positive circumstances. Metacognitive and digital efficacy skills also played a pivotal role in participants' control of web-based interactions, enabling more effective management of content or platforms or sites that posed potential harms. CONCLUSIONS: This study demonstrated the complexity of web-based interactions, with beneficial and harmful content intertwined. Participants who demonstrated metacognition and digital efficacy had better control over web-based engagements. Some attributed these skills to study processes, including taking part in reflective diaries, showing the potential of upskilling users. This study also highlighted how participants remained vulnerable by engaging with familiar web-based spaces, emphasizing the responsibility of web-based industry leaders to develop tools that empower users to enhance their web-based safety.
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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 | 0,009 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,004 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,001 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».