Co-Developing Content Updates for the Card Sort Task for Self-Harm–Digital (CaTS-D) With People With Lived Self-Harm Experiences: Pilot Study and Thematic Analysis
Notice bibliographique
Résumé
Background: Self-harm is a significant global concern with multiple negative outcomes. Self-harm research tools typically focus on single risk factors, meaning the temporal interplay between factors and their impact on self-harm is unknown. The Card Sort Task for Self-Harm (CaTS) addressed these deficits by using 117 cards to examine multiple self-harm factors. In-person research is time-consuming, costly, and limits participation opportunities. Developing an electronic version of CaTS (Card Sort Task for Self-harm-digital; CaTS-D) is necessary to address these issues, capture large datasets, and provide a stronger evidence base. Since CaTS' inception, understanding of self-harm has evolved, including increasing awareness that lesbian, gay, bisexual, transgender, queer, intersex, asexual, and other minoritized gender and sexual identities (LGBTQIA+) people are at high risk. Updating CaTS is essential to ensure its relevance to both LGBTQIA+ and cisgender-heterosexual self-harm. Objective: We aimed to present results from two studies. Study 1 is a pilot study assessing the feasibility of CaTS-D. Study 2 used qualitative interviews to identify additions or amendments to CaTS to increase its relevance as understanding of self-harm evolves. Methods: Study 1 recruited UK residents (N=13, aged 18-30 y) with lived self-harm experience. Feasibility and acceptability of CaTS-D were assessed using the Systems Usability Scale (SUS) and visual analog scale (VAS). Study 2 recruited UK residents (N=13; LGBTQIA+ n=9 and cisgender-heterosexual n=4; aged 21-29 y) with lived self-harm experience to one-on-one interviews. Results: Study 1 found CaTS-D to be a feasible web application for use in self-harm research. VAS data showed no significant difference between pre- and poststudy mood (t9=1.59; P=.15). In Study 2, thematic analysis resulted in 13 additional cards (eg, "Before 6 mo;" "I don't feel comfortable in my body;" "I was bullied on social media;" and "Self-harm gave me a feeling of control"). Cards were worded clearly, but minor amendments to wording on cards to increase LGBTQIA+inclusivity were identified (ie, changing "boyfriend/girlfriend" to "partner"). While participants felt selective additions were necessary, too many may overwhelm participants. Therefore, future additions should be carefully considered. Conclusions: Pilot-testing shows CaTS-D is a usable, feasible web application to examine self-harm and capture large datasets. Importantly, completing CaTS-D does not negatively impact participants' mood. Updates and key additions were made to CaTS from consultation with people with lived self-harm experiences. These increase the relevance of CaTS and ensure LGBTQIA+ inclusivity.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,031 | 0,056 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».