Program Retention Prediction

Program Retention Prediction is the use of data and analytical models to estimate whether people will continue participating in a program over time, helping organizations understand and improve sustained engagement. The process examines behavioral indicators such as attendance, participation frequency, completed activities, and changes in engagement, then applies statistical or machine-learning methods to identify patterns associated with continued participation or withdrawal. In behavioral research and program management, these predictions can support early identification of participants who may disengage, guide targeted communication or support, and inform program design. Reliable predictions also help evaluate retention strategies and improve the allocation of outreach resources.

Program Retention Prediction - Related Videos

Research

JoVE EoE - Neuropathology

Determination of the Calcium Retention Capacity of Isolated Mitochondria

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2025

This video demonstrates the procedure to assess mitochondrial calcium retention capacity by monitoring real-time changes in fluorescence as mitochondria uptake calcium. This assay is useful for studying mitochondrial function and calcium-related processes, including apoptosis and neurodegenerative diseases.

Programmed Electrical Stimulation in Mice

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Cited by 48 •

2010

Programmed electrical stimulation provides the ability to determine conduction properties of the heart, and the possibility to induce and terminate cardiac arrhythmias using various pacing protocols. Using a transvenous catheter, intracardiac electrogram recordings can be obtained in mice following programmed electrical stimulation protocols to identify arrhythmogenic substrates.

Research

JoVE Journal - Biology
Free Sample

A Protocol for Computer-Based Protein Structure and Function Prediction

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Cited by 79 •

2011

Guidelines for computer based structural and functional characterization of protein using the I-TASSER pipeline is described. Starting from query protein sequence, 3D models are generated using multiple threading alignments and iterative structural assembly simulations. Functional inferences are thereafter drawn based on matches to proteins with known structure and functions.

RNA Secondary Structure Prediction Using High-throughput SHAPE

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Cited by 16 •

2013

High-throughput selective 2' hydroxyl acylation analyzed by primer extension (SHAPE) utilizes a novel chemical probing technology, reverse transcription, capillary electrophoresis and secondary structure prediction software to determine the structures of RNAs from several hundred to several thousand nucleotides at single nucleotide resolution.

Soil Core Sample Collection for Water Retention Property Analysis

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2026

Source:Alessia J. Marchesan1, Guillermo Hernandez Ramirez11Renewable Resources, University of Alberta. This video demonstrates the technique for collecting a soil sample for hydraulic property analysis. The sampling area is cleared, and the top crust is evacuated. The sampling ring is then placed into the soil to collect the sample. The ring with the sample is then cleaned, labeled, packed, and transferred undisturbed for analysis.

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