Evaluation of Satisfaction With a Secure, Connected Mobile App for Women in Assisted Reproductive Technology Programs: Prospective Observational Study
Notice bibliographique
Résumé
BACKGROUND: Telemedicine has emerged rapidly as a novel and secure tool to deliver medical information and prescriptions. A secure, connected health care app (WiStim) has been developed in order to facilitate dialogue between patients and the medical team during an ovarian stimulation cycle for medically assisted reproduction (MAR). OBJECTIVE: This study aimed to evaluate the patients' and midwives' levels of satisfaction with the connected mobile app. METHODS: We conducted a prospective, observational, single-center study at Lille University Hospital, France. From May 1 to July 31, 2021, all women undergoing ovarian stimulation started to receive their treatment advice through the mobile app. A total of 184 women were included and they filled out the 30-item Usefulness Satisfaction and Ease-of-Use (USE) questionnaire, which examines the users' opinions in 4 dimensions: usefulness, ease of use, ease of learning, and satisfaction. The women also answered a series of closed and open questions. The 5 midwives in our assisted reproductive technology center filled out the French version of the 10-item System Usability Scale (SUS) when the app was implemented and then after 3 and 6 months of use. We also performed semistructured interviews with the midwives. RESULTS: Overall, 183 women using the app completed the questionnaire. None refused to use the app, and 1 withdrew from the study. The mean scores for the four USE dimensions were all significantly greater than 4, that is, the middle of the response scale. The women liked the app's ease of use, the access to tutorial videos, and the reminders about appointments and treatments. In particular, the women liked to be able to (re)read the information; this reassured them, might have reduced the number of missed appointments and treatments, and made them more independent during the day, especially when they were working. Some of the women regretted the loss of direct contact with the midwife. The mean SUS score was 76 (SD 13.54) at the start of the study, 75 (SD 17.16) after 3 months, and 84 (11.21) after 6 months. According to the adjective rating scale, these scores corresponded to good usability for the app. After the requisite training and a familiarization period, the midwives reported that using the app saved them 2 hours a day. The mobile app enabled better transmission of information and thus probably helped to decrease treatment errors. CONCLUSIONS: The WiStim connected mobile app is one of the first reliable, secure apps in the field of MAR. The app reassured the patients during the ovarian stimulation. Women and the medical team considered that the app was easy and intuitive to use. Given the growth in demand for MAR programs and the medical team's workload, the time savings provided by the app constitute a nonnegligible advantage.
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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 | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».