A Reflective Thematic Analysis Into the Perceptions of Pregnant Radiographers Regarding the Usefulness of the PregiDose Mobile App to Enhance Fetal Dosimetry and Well-Being: Qualitative Exploration
Notice bibliographique
Résumé
BACKGROUND: Pregnancy apps are widely used by pregnant women, who benefit from self-tracking features to support their health goals. Pregnant radiographers are considered a high-risk group of health workers practicing in ionizing radiation environments. Radiation exposure above threshold limits can cause harmful genetic effects on a fetus. Accordingly, pregnant radiographers are required to wear special fetal dosimeters, which provide real-time readings of radiation dose exposure to the fetus. Pregnant radiographers have the responsibility to self-track their fetal doses to ensure that the threshold limit of 1 mGy is not exceeded. The traditional method used to track doses includes a written log of doses in a notebook. Thus, PregiDose, a unique offering in the context of pregnancy apps, was developed to enhance fetal dose tracking and monitoring using technological methods. OBJECTIVE: This study aims to describe the users' perceptions of the app's usefulness using PregiDose in a natural setting. METHODS: The overarching framework adopted for the study was a design science research (DSR) methodology encompassing five steps, namely (1) problem awareness, (2) suggestion, (3) development, (4) evaluation, and (5) conclusion. This paper presents the evaluation step of DSR. DSR step 4 included a qualitative approach to explore users' perceptions regarding the app. Data were collected using a semistructured interview guide. Open-ended questions were guided by the app's core features, namely dose tracking, education, and wellness. In total, 17 pregnant radiographers in South Africa enrolled to use the app, 9 (53%) engaged with the app, and 4 (24%) agreed to participate in the feedback interviews. The data were collected from October 2023 to March 2024 and analyzed using a reflective thematic data analysis method. RESULTS: Three overarching themes emerged from the data, namely (1) usefulness of PregiDose, (2) barriers to PregiDose adoption and use, and (3) recommendations for the advancement of PregiDose. Users labeled the app's usefulness as positive and perceived it as a modern approach to traditional dose-tracking methods. They perceived the graph output of the dose-tracking feature to be useful for viewing their accumulative doses. They did not fully engage with the journaling feature, indicating that it was a personal preference and not a practice they would usually engage in. Physiological barriers, such as fatigue and "pregnancy brain," were contributors to decreased engagement. Finally, because of the demanding workload and fast-paced nature of the radiography department, users recommended the automation of fetal dosimetry through the Internet of Things. CONCLUSIONS: PregiDose is an occupational health and safety mobile app developed for pregnant radiographers through a DSR approach. The app offers a modern method of dose tracking consistent with technological advancements in the context of self-tracking. However, future implementation would require using Internet of Things to make fetal dose tracking more effective.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,008 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».