Willingness to Be Contacted via a Patient Portal for Health Screening, Research Recruitment, and at-Home Self-Test Kits for Health Monitoring: Pilot Quantitative Survey
Notice bibliographique
Résumé
Background: Patient portals are being increasingly used by health systems in the United States. Although some patients use portals for clinical use, patient perspectives on using portals for research-related activities, to complete health screenings, and to request at-home self-test kits are unclear. Objective: We aimed to understand patient perspectives on using electronic health portals for research; health-related screenings; and patient-initiated, home-based self-testing. Methods: Patients (N=105) from the Patient Engaged Research Center at a large, urban, midwestern health system completed a 23-item web-based survey on patient portal (MyChart) use and willingness to use the patient portal for research, risk assessments, and self-test kits. Frequencies and percentages were generated. Results: Almost all participants (102/105, 97.1%) had accessed MyChart at least once, with most (44/102, 43.1%) indicating they logged in at least once per month. Participants indicated logging into MyChart to check laboratory results or other health data (89/105, 84.8%), because they received a message to log in (85/105, 81%), and to message their health care professional (83/105, 79%). Fewer participants logged in to see what medications they had been prescribed (16/105, 15.2%) and to learn more about their health conditions (29/105, 27.6%). Most participants indicated logging into MyChart on a computer via a website (70/105, 66.7%) or on a smartphone via an app (54/105, 51.4%). When asked about how likely they would be to participate in different types of research if contacted via MyChart, most (90/105, 85.7%) said they would be likely to answer a survey, fill out a health assessment (87/105, 82.9%), or watch a video (86/105, 81.9%). Finally, participants would be willing to answer risk assessment questions on MyChart regarding sleep (74/101, 73.3%), stress (65/105, 61.9%), diabetes (60/105, 57.1%), anxiety (59/105, 56.2%), and depression (54/105, 51.4%) and would be interested in receiving an at-home self-test kit for COVID-19 (66/105, 62.9%), cholesterol (63/105, 60%), colon cancer (62/105, 59%), and allergies (56/105, 53.3%). There were no significant demographic differences for any results (all P values were >.05). Conclusions: Patient portals may be used for research recruitment; sending research-related information; and engaging patients to answer risk assessments, read about health information, and complete other clinical tasks. The lack of significant findings based on race and gender suggests that patient portals may be acceptable tools for recruiting research participants and conducting research. Allowing patients to request self-test kits and complete risk assessments in portals may help patients to take agency over their health care. Future research should examine if patient portal recruitment may help address persistent biases in clinical trial recruitment to increase enrollment of women and racial minority groups.
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 | 0,008 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| 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) | 0,004 | 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 ».