Related Experiment Video
Updated: Jan 11, 2026
07:31
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
7.5K
Methods for Analytical Validation of Novel Digital Clinical Measures: Implementation Feasibility Evaluation Using
Simon Turner1, Lysbeth Floden2, Leif Simmatis3
1Digital Medicine Society, Boston, MA, United States.
Journal of Medical Internet Research
|November 17, 2025
Summary
Sensor-based digital health technologies (sDHTs) generate digital measures (DMs) for drug development. Confirmatory factor analysis (CFA) effectively validates novel DMs against reference measures, guiding study design for reliable results.
Area of Science:
- Biostatistics
- Digital Health Technologies
- Drug Development
Background:
- Sensor-based digital health technologies (sDHTs) generate digital measures (DMs) crucial for scientific and clinical decisions.
- DMs can accelerate drug development, reduce trial costs, and improve care access.
- Analytical validation (AV) of novel DMs is challenging due to the lack of established reference measures (RMs).
Purpose of the Study:
- To assess the feasibility of implementing statistical methods for analytical validation (AV) using real-world data.
- To examine how study design factors impact the estimation of relationships between DMs and RMs.
- To provide guidance on standardizing AV for novel DMs.
Main Methods:
- Utilized four real-world datasets (Urban Poor, STAGES, mPower, Brighten) to simulate AV studies.
- Assessed study design properties: temporal coherence, construct coherence, and data completeness.
- Compared statistical methods: Pearson correlation coefficient (PCC), simple linear regression (SLR), multiple linear regression (MLR), and confirmatory factor analysis (CFA).
Main Results:
- Confirmatory factor analysis (CFA) models generally showed acceptable fit and estimated factor correlations.
- CFA-derived factor correlations were consistently stronger than Pearson correlation coefficients (PCC).
- Strongest correlations were observed in hypothetical studies with high temporal and construct coherence.
Conclusions:
- The evaluated statistical methods are feasible for real-world data in AV of DMs.
- Confirmatory factor analysis (CFA) is recommended for assessing novel DM-RM relationships.
- Findings offer practical recommendations for AV study design, promoting standardized validation of sDHTs.
Related Concept Videos
01:03Data Validation
6.3K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Nursing assessment guides are generally based on holistic models rather than medical...
6.3K
01:15Data Validation
557
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
Key parameters for method validation include:
557
01:20Measurement of Bioavailability: Pharmacodynamic Methods
221
Pharmacodynamic methods provide insights into a drug's effects on physiological processes over time and play a crucial role in understanding bioavailability and therapeutic efficacy. These methods can be broadly classified into acute pharmacological and therapeutic response approaches, each with distinct mechanisms and applications.The acute pharmacological response method directly correlates a drug's physiological effects, such as ECG or pupil diameter changes, to its time course in the body.
221
01:16Clinical Trials
10.1K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
There are four phases in a clinical trial. A phase one...
10.1K
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
387
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
387
01:29Clinically Relevant Drug Product Specifications: Methods of Establishment
189
Product specifications define the acceptable quality of a pharmaceutical product by ensuring identity, purity, potency, and strength. These specifications serve as benchmarks during development, manufacturing, and post-approval quality control. Clinically relevant specifications are particularly important because they directly relate to a drug's safety and efficacy in clinical use.Dissolution studies are critical biopharmaceutic tools that link in vitro behavior to in vivo performance. They...
189