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Observational Study to Investigate the Recognition Gap between Patients and Physicians In Neurological Diseases (Parkinson's disease, multiple sclerosis, epilepsy) and Development of a Predictive Model Using AI (GAP-AI) (GAP-AI)

Patients-Physicians Gap Survey (GAP-AI)

198

Of the patients, 119 were women (60.0%) and 104 were at least 60 years of age (52.8%). The most common diagnosis was Parkinson's disease (69.5%), followed by multiple sclerosis (20.3%) and epilepsy (10.2%), with an overall mean disease duration of 7.4 years.

In total, 198 patients were enrolled and 197 patients were included in the FAS (one patient withdrew their consent).

No reports of adverse events

Slight gaps in perceptions between patients and physicians were identified regarding the primary endpoints of patient satisfaction, shared decision-making, activities of daily living, and quality of life.

This study identified perception gaps between patients with neurological diseases and their physicians and the factors that influence them. Multiple machine learning algorithms were used to develop predictive models based on study data. Insights from this study underscore the importance of recognizing such discrepancies for enhancing clinical practice through a better understanding between patients and their physicians.

No

We provide access to the de-identified individual participant data (IPD) for eligible studies to aid qualified researchers in addressing legitimate scientific objectives. These IPDs will be provided in a secure research environment following approval of a data sharing request, and under the terms of a data sharing agreement.

https://jrct.mhlw.go.jp/latest-detail/jRCT1030220258

Oyama Genko

Juntendo University Hospital

3-1-1 Hongo,Bunkyo-ku, Tokyo

g_oyama@juntendo.ac.jp

Oyama Genko

Juntendo University Hospital

3-1-1 Hongo,Bunkyo-ku, Tokyo

+81-3-3813-3111

g_oyama@juntendo.ac.jp

Complete

Sept. 01, 2022

Observational

1. Diagnosis of target disease: Parkinson's disease, multiple sclerosis, epilepsy (Juvenile myoclonic epilepsy, juvenile absence-like epilepsy, grand mal epilepsy in wakefulness)
2. Patients who have been visiting the Department of Neurology at Juntendo University Hospital for at least 3 months and have visited the hospital at least once within the past 3 months
3. Persons who have received sufficient explanation for participation in this research and have obtained written consent of the subject's own free will after sufficient understanding

1. Patients aged < 18 years at the time of informed consent
2. People who cannot answer by themselves due to cognitive dysfunction, etc.
3. Other persons who are judged to be inappropriate as research subjects by the research manager

Both

Parkinson's disease, Multiple sclerosis, Epilepsy

The primary endpoint will be the results of the following questionnaire, which will be assessed by both patients and physicians in pairs, in order to clarify the actual situation of the three gaps in the level of understanding of the patient's condition, the level of satisfaction, and the SDM between patients with neurological diseases (Particularly outpatients with Parkinson's disease, multiple sclerosis, or epilepsy) and physicians.
1. PSQ-18 PSQ-18(Visit 2)
2. ADL Barthel Index(Visit 2)
3. SF-36 Subdomain (Visit 1)
4. SDM-Q-9(Visit 2)
5. SDM-Q-Doc(Visit 2)
6. Unique Questionnaires (Pairwise Variables for Both Patients and Physicians) (Visit 2)

As a secondary objective, in order to clarify the factors affecting the gap in the level of understanding of the patient's condition, the level of satisfaction, and SDM between patients with neurological diseases (Particularly outpatients with Parkinson's disease, multiple sclerosis, or epilepsy) and attending physicians, which was revealed in the primary endpoint, the results of the questionnaire to be answered by only the following patients, physician's attribute information, and necessary items in EMRs will be tabulated and analyzed as secondary endpoints.
1. PDQ-39(Visit 2)
2. MSQOL-54(Visit 2)
3. QOLIE-31P(Visit 1)
4. SF-36(Visit 1)
5. Original questionnaire (Visit 2)
6. Physician Attribute Information
7. Medical record information

+81-3-3818-3111

July. 08, 2022

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