The Role of Digital Tools in Meeting the Needs of Adults With Tourette Syndrome: A Human-Centered Design Approach
Notice bibliographique
Résumé
Background: Individuals with tic disorders (TDs) have access to a small but growing number of digital tools (such as apps and websites) for tic management and support. While prior work has shown promise for these tools, they have traditionally been designed by researchers first and evaluated by members of the TD community after tool development is complete. A human-centered design process targeting this domain has the potential to reveal new insights relevant to the development of future tools. We seek to establish a preliminary understanding of how the TD community uses and perceives current resources for tic management and support as well as their overall concerns and needs in this area. Objective: This study aimed to explore the design potential of future digital tools for helping adults manage their tics by gathering an initial set of needs and requirements from adult members of the TD community in the United States. Methods: An online survey was distributed via TD community groups and also via TD clinicians and researchers in the United States. The survey contained a combination of dichotomous, multiple-choice, and open-ended questions, with opportunities for participants to specify how they currently receive support, rank their preferred features and requirements, and express their needs and concerns relevant to future work. Qualitative responses were analyzed with inductive thematic analysis. Results: Most respondents typically sought answers from digital platforms first (124/158, 78.5%) when confronting a question about their tics. Even so, only 18.4% (29/158) reported having previously used a digital tool to help with their tics or any other aspect of their health. Simultaneously, 88.9% (136/153) indicated that they would be very (81/153, 52.9%) or somewhat (55/153, 35.9%) likely to use a digital tool designed for adults with tics. Of those listing concerns (42/158, 26.6%), common reported concerns included the tool being too time-consuming, difficult to use, or generally not meeting accessibility standards. When asked to rank the one feature of a digital tool that they believed to be most important, tic monitoring (66/154, 42.9%) and trigger monitoring (54/154, 35.1%) were among the most popular requested features as opposed to other options, such as information gathering, reminders to practice a therapeutic skill or take medicine, social support, or opportunities to share their story. While screen navigation was most preferred, results indicated that a multimodal design overall would support the most users. Conclusions: Our study participants reported a lack of useful technology for tic management and indicated a need for accessible tools to assist in tic and trigger monitoring in particular. Other concerns included that new tools would be difficult to use or learn due to tics. Findings suggest a cautious excitement for future digital tools in this area.
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 | 0,052 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,006 |
| Communication savante | 0,007 | 0,004 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».