National implementation of a digital Parkinson's disease screening programme in Thailand: reach, adoption, and real-world performance of the CheckPD app.
Parkinson's disease (PD) remains underdiagnosed in Thailand, and its rising prevalence presents a growing challenge for the healthcare system. The previously validated CheckPD digital population screening platform has been implemented nationally in collaboration with the Thai Red Cross Society (TRCS) and the National Health Security Office (NHSO), enabling integration of digital PD risk screening into preventive health frameworks.
To evaluate the early phase of a national rollout of the CheckPD platform, focusing on population reach, adoption, predictive performance, exploratory usability, and implementation factors influencing scalability across diverse real-world settings.
This RE-AIM-guided implementation study in 10 Thai provinces assessed reach, adoption, completion, system performance and positive predictive value among neurologist-evaluated screen-positive participants. Preliminary usability was assessed in 30 post-screening completers using the SUS and UEQ-S. Supplementary implementation feedback was collected from Village Health Volunteers and public health officers.
Between January 2024 and October 2025, 13,381 out of 18,520 users completed screening across 10 provinces (completion rate: 72.3%). The mean SUS score was 83, with a 92% first-time task completion rate. Programme reach was achieved through multiple channels, including Village Health Volunteers (6,742 participants), community field campaigns (5,207), facilitated online training initiatives (3,448), and self-initiated app downloads (3,123). When compared with neurologists' diagnoses among 730 screen-positive participants who underwent evaluation, the screening demonstrated a positive predictive value of 81.23% (593/730; 95% CI 78.39%-84.07%). Key facilitators of implementation included TRCS endorsement and network support, community volunteer engagement, and user-centred app design. Exploratory multivariable logistic regression analysis identified educational attainment and geographic context as significant predictors of screening completion, with higher educational attainment and residence outside Bangkok associated with a higher likelihood of completing the screening workflow.
The CheckPD programme demonstrates that national-scale digital screening for neurological disorders is feasible in a low-to-middle-income country when embedded within trusted institutions, supported by community networks, and aligned with data protection standards. Thailand's experience provides an early, promising, and potentially scalable model for implementing population-level improvements in brain health by enabling earlier detection and assessment of individuals at risk, in alignment with the World Health Organization's Brain Health framework.
To evaluate the early phase of a national rollout of the CheckPD platform, focusing on population reach, adoption, predictive performance, exploratory usability, and implementation factors influencing scalability across diverse real-world settings.
This RE-AIM-guided implementation study in 10 Thai provinces assessed reach, adoption, completion, system performance and positive predictive value among neurologist-evaluated screen-positive participants. Preliminary usability was assessed in 30 post-screening completers using the SUS and UEQ-S. Supplementary implementation feedback was collected from Village Health Volunteers and public health officers.
Between January 2024 and October 2025, 13,381 out of 18,520 users completed screening across 10 provinces (completion rate: 72.3%). The mean SUS score was 83, with a 92% first-time task completion rate. Programme reach was achieved through multiple channels, including Village Health Volunteers (6,742 participants), community field campaigns (5,207), facilitated online training initiatives (3,448), and self-initiated app downloads (3,123). When compared with neurologists' diagnoses among 730 screen-positive participants who underwent evaluation, the screening demonstrated a positive predictive value of 81.23% (593/730; 95% CI 78.39%-84.07%). Key facilitators of implementation included TRCS endorsement and network support, community volunteer engagement, and user-centred app design. Exploratory multivariable logistic regression analysis identified educational attainment and geographic context as significant predictors of screening completion, with higher educational attainment and residence outside Bangkok associated with a higher likelihood of completing the screening workflow.
The CheckPD programme demonstrates that national-scale digital screening for neurological disorders is feasible in a low-to-middle-income country when embedded within trusted institutions, supported by community networks, and aligned with data protection standards. Thailand's experience provides an early, promising, and potentially scalable model for implementing population-level improvements in brain health by enabling earlier detection and assessment of individuals at risk, in alignment with the World Health Organization's Brain Health framework.
Authors
Bhidayasiri Bhidayasiri, Phumphid Phumphid, Sringean Sringean, Anan Anan, Laosombut Laosombut, Meesri Meesri, Wekhinhiran Wekhinhiran, Leabthong Leabthong, Phokaewvarangkul Phokaewvarangkul, Surangsrirat Surangsrirat, Vateekul Vateekul, Win Win, Jeh-Voh Jeh-Voh, Panyakaew Panyakaew, Phuenpathom Phuenpathom, Maytharakcheep Maytharakcheep, Jagota Jagota, Ratanasirisawad Ratanasirisawad, Khongprasert Khongprasert, Rattanachaisit Rattanachaisit, Prasertpan Prasertpan, Udomsirithamrong Udomsirithamrong, Phoumindr Phoumindr, Likhitwitayawuid Likhitwitayawuid, Saengmanee Saengmanee, Rattanajun Rattanajun, Horaruengdecha Horaruengdecha, Sukmueng Sukmueng, Dornbunlon Dornbunlon, Sittitrai Sittitrai, Vorachetbancha Vorachetbancha, Chanchalong Chanchalong, Phonsrithong Phonsrithong, Kullavanijaya Kullavanijaya, Sricholwattana Sricholwattana, Chirapravati Chirapravati, Chariyavilaskul Chariyavilaskul, Sukpisan Sukpisan, Thammatacharee Thammatacharee, Limpanyalers Limpanyalers, Juthasong Juthasong, Rattanamornsakul Rattanamornsakul, Bunnag Bunnag, Boonrach Boonrach
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