M100. LOOSELEAF: DEVELOPING A MOBILE-BASED APPLICATION TO MONITOR DAILY CANNABIS USAGE IN YOUTH AT CLINICAL HIGH-RISK OF PSYCHOSIS: APP DEVELOPMENT AND USABILITY TESTING
Notice bibliographique
Résumé
Abstract Background Youth at clinical high risk for psychosis (CHR) often use cannabis, which can have a negative impact on their attenuated psychotic symptoms (APS). Our overall goal is to develop an app that will monitor cannabis use and its impact on APS. Objectives: (1) To describe the development of a mobile-based application named LooseLeaf (LL) to monitor daily cannabis use of individuals at CHR through participatory design; and (2) To test initial usability, discover and fix technical issues, and ensure correct data transmission of LL. Methods Two two-hour focus groups were run with CHR participants, age 12–30. Opinions of participants on (i) application content, (ii) graphic design, and (iii) user experience of the different features (i.e., home screen, inventory, questions, feedback, and calculator) were gathered from the first focus group. Based on the comments from the first focus group, a usable prototype of the application was created and was shown to the second focus group. The second focus group provided further feedback on the user experience of each feature, and finalized the application’s name and logo. The focus groups were audio recorded and transcribed verbatim for analysis. Following Braun and Clarke’s guidelines, data obtained from the focus groups was qualitatively analyzed with thematic analysis to identify patterns in responses. The application was refined accordingly. Then, six healthy controls and two CHR participants used LL for one week to test its effectiveness in monitoring cannabis use. On days that participants used cannabis they answered LL’ questions about how much cannabis they used, how they used, their subjective emotional experience, and what their social and environmental context was during and after using cannabis. When they did not use cannabis, LL asked questions about their subjective emotional experience and how they felt about not using cannabis. LL included a bug-report feature that participants were encouraged to use when they encountered problems. Qualitative data about LL was gathered through the 23-item Mobile Application Rating Scale (MARS) covering questions about engagement, functionality, aesthetics, information provided, and subjective quality of LL. Descriptive statistics were calculated for the quantitative data from MARS. Results Participants favored a minimal and neutral design, buttons with icons, and color-coding of the emotions. Participants named the application “LooseLeaf” and helped to refine its features. The final design of the application consisted of 11 questions about cannabis consumption and feelings associated with it (i.e., euphoria, anxiety, and psychosis-like experiences). Over the one-week usability testing period, LL had an 85.7% response rate. The bug-report feature was used 13 times by seven participants to flag technical issues and provide suggestions to improve user experience of LL. The App received a good overall score on the MARS. LL’s functionality, aesthetics, information, and safety rated high. Few customization options, lack of willingness to pay for applications in general, and technical issues resulted in lower engagement and subjective quality scores. LL’s perceived impact score was good. Discussion The application’s development process was based on the feedback of CHR youth. This provided important information on the design and content needed to build a user-centric mobile application. LL demonstrated initial usability, an effective bug-report feature, and some technical issues and problems with data transmission. The MARS, interviews, and bug-reports provided effective feedback for refining LL for the next phase of development.
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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,002 |
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 ».