Digital Technologies for Women’s Pelvic Floor Muscle Training to Manage Urinary Incontinence Across Their Life Course: Scoping Review
Notice bibliographique
Résumé
BACKGROUND: Women with urinary incontinence (UI) may consider using digital technologies (DTs) to guide pelvic floor muscle training (PFMT) to help manage their symptoms. DTs that deliver PFMT programs are readily available, yet uncertainty exists regarding whether they are scientifically valid, appropriate, and culturally relevant and meet the needs of women at specific life stages. OBJECTIVE: This scoping review aims to provide a narrative synthesis of DTs used for PFMT to manage UI in women across their life course. METHODS: This scoping review was conducted in accordance with the Joanna Briggs Institute methodological framework. A systematic search of 7 electronic databases was conducted, and primary quantitative and qualitative research and gray literature publications were considered. Studies were eligible if they focused on women with or without UI who had engaged with DTs for PFMT, reported on outcomes related to the use of PFMT DTs for managing UI, or explored users' experiences of DTs for PFMT. The identified studies were screened for eligibility. Data on the evidence base for and features of PFMT DTs using the Consensus on Exercise Reporting Template for PFMT, PFMT DT outcomes (eg, UI symptoms, quality of life, adherence, and satisfaction), life stage and culture, and the experiences of women and health care providers (facilitators and barriers) were extracted and synthesized by ≥2 independent reviewers. RESULTS: In total, 89 papers were included (n=45, 51% primary and n=44, 49% supplementary) involving studies from 14 countries. A total of 28 types of DTs were used in 41 primary studies, including mobile apps with or without a portable vaginal biofeedback or accelerometer-based device, a smartphone messaging system, internet-based programs, and videoconferencing. Approximately half (22/41, 54%) of the studies provided evidence for or testing of the DTs, and a similar proportion of PFMT programs were drawn from or adapted from a known evidence base. Although PFMT parameters and program compliance varied, most studies that reported on UI symptoms showed improved outcomes, and women were generally satisfied with this treatment approach. With respect to life stage, pregnancy and the postpartum period were the most common focus, with more evidence needed for women of various age ranges (eg, adolescent and older women), including their cultural context, which is a factor that is rarely considered. Women's perceptions and experiences are often considered in the development of DTs, with qualitative data highlighting factors that are usually both facilitators and barriers. CONCLUSIONS: DTs are a growing mechanism for delivering PFMT, as evidenced by the recent increase in publications. This review highlighted the heterogeneity in types of DTs, PFMT protocols, the lack of cultural adaptations of most of the DTs reviewed, and a paucity in the consideration of the changing needs of women across their life course.
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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 | 0,016 | 0,065 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,005 |
| Bibliométrie | 0,020 | 0,019 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».