Evidence map›Paper›PMID 39944543›Full record

ArticleFrontiers in neurology2025

Evaluation of compliance and accuracy in Parkinson's disease motor symptom tracking: a comparative study of digital and traditional paper diaries using a smartphone application (MyParkinson's).

Nazli Durmaz Celik, Asli Yaman Kula, Naci Murat, Müge Kuzu Kumcu, Aydan Topal, Serhat Özkan

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Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nazli Durmaz CelikDepartment of Neurology, Eskişehir Osmangazi University, Faculty of Medicine, Eskişehir, Türkiye.
Asli Yaman KulaDepartment of Neurology, Bezmialem Vakif University Hospital, Istanbul, Türkiye.
Naci MuratDepartment of Industrial Engineering, Ondokuz Mayıs University, Samsun, Türkiye.
Müge Kuzu KumcuDepartment of Neurology, Lokman Hekim University, Ankara, Türkiye.
Aydan TopalDepartment of Neurology, Samsun Training and Research Hospital, Samsun, Türkiye.
Serhat ÖzkanDepartment of Neurology, Faculty of Medicine, Eskişehir Osmangazi University, Eskişehir, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/objectives: This study aimed to evaluate compliance and accuracy in comparison with traditional PD diaries for tracking motor symptoms using a new smartphone application (MyParkinson's) and paper diary strategies. Parkinson's disease (PD) is a neurodegenerative disorder with progressive motor symptoms. Treatment becomes more challenging as PD progresses, motor complications in the form of wearing-off phenomenon and levodopa-induced dyskinesia develop. Traditional paper diaries and clinical scales used to evaluate patients may be inadequate in assessing whether the patient is "on" or "off," resulting in less-than-ideal treatment changes. Methods: A randomized crossover design was utilized to examine 22 advanced PD patients who underwent symptomatic assessment with both diaries during two separate 24-h periods seven days apart. The compliance and accuracy of data were assessed by comparing diary entries with the clinical examination notes and WhatsApp queries. LaOerly, patients' diary preferences were also evaluated. Results: The digital diary had significantly beOer compliance and accuracy than the paper diaries, with substantial/almost perfect levels of agreement ( Conclusion: Digital diaries are helpful in the clinical management of PD patients as they minimize recall bias and reduce data errors in appropriately selected patients. Our study suggests a broader adoption of digital health technologies in PD management. Still, additional research is necessary to improve the tools and assess long-term patient outcomes.

Indexed as

mobile applicationsmotor symptom diaryParkinson’s diseaseParkinson’s disease digital diarysmartphone application

Identifiers

PMID39944543
PMCPMC11814194

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.