Thai PainPREDICT Validation Study

NCT ID: NCT07195045

Last Updated: 2025-10-03

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

277 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-08-28

Study Completion Date

2027-12-31

Brief Summary

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Painful diabetic neuropathy (PDN) is one of the most common and disabling complications of diabetes mellitus, substantially affecting quality of life, daily functioning, and health system burden. Early identification of PDN is crucial for timely treatment, prevention of complications such as foot ulcers and amputations, and for reducing healthcare costs. However, in Thailand there are limited culturally adapted and validated tools for screening PDN. PainPREDICT is an internationally validated questionnaire designed to characterize neuropathic pain profiles, but its adaptation for Thai patients has not yet been undertaken. In parallel, the use of mobile health technologies (mHealth) has the potential to expand access to screening and monitoring of chronic conditions, particularly in resource-limited settings.

Detailed Description

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This study aims to translate, culturally adapt, and validate the PainPREDICT questionnaire for the Thai population, and to integrate it into a mobile application for use in both clinical and community settings. The study is structured into three phases. Phase 1 involves forward-backward translation of PainPREDICT into Thai, with expert panel review, pilot testing, and psychometric validation. Reliability will be assessed using internal consistency (Cronbach's alpha) and test-retest intraclass correlation coefficients, while validity will be examined through correlations with existing neuropathic pain measures (e.g., DN4) and neurophysiological studies (nerve conduction study, quantitative sensory testing). Phase 2 focuses on the design, development, and usability testing of a mobile application embedding the Thai PainPREDICT questionnaire. Clinicians and patients will test the application, and usability will be assessed with the System Usability Scale and qualitative interviews. Phase 3 evaluates diagnostic accuracy and real-world usability in 200-300 patients with type 1 or type 2 diabetes, including subgroup analysis in resource-limited settings. Diagnostic performance (sensitivity, specificity, positive and negative predictive values, ROC AUC) will be compared with physician diagnosis and objective neurophysiological tests.

Eligible participants are adults (≥18 years) with type 1 or type 2 diabetes who are able to communicate in Thai and provide informed consent. Patients with neuropathy from non-diabetic causes or significant cognitive impairment will be excluded. Recruitment will take place at Chula Neuroscience Center, King Chulalongkorn Memorial Hospital, and affiliated diabetes clinics. The study anticipates enrolling approximately 277 participants, which provides adequate power for psychometric validation and diagnostic accuracy testing. Both PDN patients and diabetic controls without PDN will be included to enable comparative analysis.

The primary outcome is the reliability and validity of the Thai PainPREDICT questionnaire for PDN screening. Secondary outcomes include usability of the mobile application, diagnostic accuracy compared with clinical and neurophysiological standards, and effectiveness in increasing PDN detection in resource-limited settings. The study also seeks to generate evidence on patient and provider satisfaction with the mobile platform. Data will be collected securely, stored in REDCap, and managed in compliance with Thai data protection regulations (PDPA 2019). Ethical approval will be obtained from the Institutional Review Board, Faculty of Medicine, Chulalongkorn University, and written informed consent will be required from all participants.

The expected benefit of this project is the development of a reliable and culturally valid Thai version of PainPREDICT, coupled with an accessible mobile application. This tool is anticipated to facilitate earlier detection of PDN, improve patient management pathways, and reduce disparities in access to care across Thailand. The study will also provide a model for adapting digital health screening tools for other populations with high diabetes burden. Ultimately, the project aims to strengthen evidence-based screening and management of neuropathic pain, improve patient quality of life, and contribute to the broader application of mHealth in chronic disease management.

Conditions

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Painful Diabetic Neuropathy (PDN) Diabetic Neuropathy, Distal Symmetric Polyneuropathy (Manifestation) Type 1 Diabetes Mellitus (T1DM) Type 2 Diabetes Mellitus (T2DM) Neuropathic Pain Diabetes Complications

Study Design

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Allocation Method

NON_RANDOMIZED

Intervention Model

PARALLEL

Participants with type 1 or type 2 diabetes will be divided into two groups: those with painful diabetic neuropathy and those without neuropathy, matched by age, sex, and diabetes type. Both groups will complete the Thai PainPREDICT questionnaire (mobile application and/or paper version). Scores will be compared with clinical diagnosis and neurophysiological testing to assess reliability, validity, and diagnostic accuracy. The model uses parallel assessment rather than crossover or randomized allocation.
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Not applicable. Both patients and investigators are aware of PDN status, and the study does not use blinding. Outcomes are assessed by comparing questionnaire/app results with independent clinical and neurophysiological tests.

Study Groups

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Arm 1: Painful Diabetic Neuropathy (PDN) Group

Adults with type 1 or type 2 diabetes who have painful diabetic neuropathy, confirmed by clinical assessment. Participants will complete the Thai PainPREDICT questionnaire via the mobile application and/or paper version. Results will be compared against clinical diagnosis and neurophysiological tests.

Group Type EXPERIMENTAL

Thai PainPREDICT Questionnaire and Mobile Application

Intervention Type DIAGNOSTIC_TEST

The Thai PainPREDICT Questionnaire is a culturally adapted and validated version of an internationally recognized neuropathic pain assessment tool. In this study, it is administered via both paper form and a secure mobile application designed for Thai patients with diabetes. The app automates scoring, provides real-time feedback, and securely stores data in REDCap in compliance with Thai Personal Data Protection Act (PDPA). The intervention is used to screen for painful diabetic neuropathy and compare results against clinical diagnosis and neurophysiological testing, including DN4, nerve conduction studies, and quantitative sensory testing.

Arm 2: Non-PDN Diabetic Control Group

Adults with type 1 or type 2 diabetes without painful neuropathy, matched by age, sex, and diabetes type. Participants will complete the Thai PainPREDICT questionnaire via the mobile application and/or paper version, with results compared against clinical assessment and neurophysiological testing.

Group Type ACTIVE_COMPARATOR

Thai PainPREDICT Questionnaire and Mobile Application

Intervention Type DIAGNOSTIC_TEST

The Thai PainPREDICT Questionnaire is a culturally adapted and validated version of an internationally recognized neuropathic pain assessment tool. In this study, it is administered via both paper form and a secure mobile application designed for Thai patients with diabetes. The app automates scoring, provides real-time feedback, and securely stores data in REDCap in compliance with Thai Personal Data Protection Act (PDPA). The intervention is used to screen for painful diabetic neuropathy and compare results against clinical diagnosis and neurophysiological testing, including DN4, nerve conduction studies, and quantitative sensory testing.

Interventions

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Thai PainPREDICT Questionnaire and Mobile Application

The Thai PainPREDICT Questionnaire is a culturally adapted and validated version of an internationally recognized neuropathic pain assessment tool. In this study, it is administered via both paper form and a secure mobile application designed for Thai patients with diabetes. The app automates scoring, provides real-time feedback, and securely stores data in REDCap in compliance with Thai Personal Data Protection Act (PDPA). The intervention is used to screen for painful diabetic neuropathy and compare results against clinical diagnosis and neurophysiological testing, including DN4, nerve conduction studies, and quantitative sensory testing.

Intervention Type DIAGNOSTIC_TEST

Other Intervention Names

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PainPREDICT (Thai Version) PainPREDICT App

Eligibility Criteria

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Inclusion Criteria

* Adults aged 18 years or older.
* Diagnosed with type 1 diabetes mellitus or type 2 diabetes mellitus.
* Able to communicate in Thai.
* Willing and able to provide written informed consent.

Exclusion Criteria

* Presence of neuropathy due to other causes (e.g., alcohol, chemotherapy, HIV, other systemic diseases).
* Significant cognitive impairment or neurological conditions that prevent comprehension of the questionnaire.
* Severe psychiatric illness that interferes with study participation.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Chulalongkorn University

OTHER

Sponsor Role lead

Responsible Party

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Jakkrit Amornvit, MD.

Priciple Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Jakkrit Amornvit, MD

Role: PRINCIPAL_INVESTIGATOR

King Chulalongkorn Memorial Hospital

Locations

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King Chulalongkorn Memorial hospital, The Thai Red Cross Society

Pathum Wan, Bangkok, Thailand

Site Status RECRUITING

Countries

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Thailand

Central Contacts

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Jakkrit Amornvit, MD

Role: CONTACT

+66622169338

Tharadon Deepracha, MSc

Role: CONTACT

+66622169338

Facility Contacts

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Jakkrit Amornvit, MD

Role: primary

+66622169338

Other Identifiers

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IRB No. 0296/68

Identifier Type: OTHER

Identifier Source: secondary_id

COA No. 1084/2025

Identifier Type: -

Identifier Source: org_study_id

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