Predicting Vaccine Hesitancy Using Machine Learning

N/AActive Not RecruitingNCT06988969

University of Yalova600 enrolled

Overview

In recent years, emerging technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and Virtual Reality (VR) have rapidly become integrated into daily life. The widespread use of these applications has led to the accumulation of vast amounts of data, giving rise to what is commonly referred to as "Big Data." Due to the sheer volume, manual processing and analysis of these large datasets are not feasible. Therefore, software tools and libraries-such as Python and R libraries-have been developed to perform these analyses efficiently and to generate predictions for the future by leveraging historical data through Machine Learning (ML) algorithms. The primary goal of machine learning algorithms is to discover patterns within existing data and use these patterns to make accurate predictions on new data. The use of machine learning in the field of healthcare has gained significant momentum in recent years. However, a review of the literature reveals that research specifically addressing childhood vaccine hesitancy remains limited. This study aims to identify the factors contributing to vaccine hesitancy among parents of children aged 0-48 months and to develop a predictive model using machine learning techniques based on these factors. Such a model could help anticipate the likelihood of vaccine refusal among parents and thereby support the development of targeted public health strategies for at-risk populations.

Study Type

OBSERVATIONAL

Enrollment

600

Conditions

Vaccine Refusal Vaccine Hesitancy Machine Learning Children

Eligibility

Sex: ALLMin age: 18 YearsMax age: 65 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: Parents who meet the following criteria will be included in the study: * Have proficiency in understanding and reading the Turkish language, * Are able to use technological devices such as mobile phones or computers to access social media platforms (Participants used social media platforms such as Instagram and WhatsApp to communicate) via the internet, * Are 18 years of age or older, * Have children aged 0-4 years, * Consent to participate in the study, * Have children without any absolute contraindications to vaccination. Exclusion Criteria: * Parents of high-risk infants (such as those with a history of systemic illness, preterm labor, anomalies, etc.), * Parents who are unwilling to participate in the study will be excluded.

Outcomes

Primary Outcomes

Parental Vaccine Hesitancy Status

The Vaccine Hesitancy Scale is a measurement tool designed to assess individuals' vaccine hesitancy or opposition. It consists of 21 items across 4 subscales and uses a 5-point Likert scale format. The four subscales of the scale are: Vaccine Benefit and Protective Value, Vaccine Opposition, Solutions for Avoiding Vaccination, and Justification of Vaccine Hesitancy. Higher scores on the scale indicate greater levels of vaccine hesitancy or opposition.

Time frame: Day 1 (Parents will be sent the questionnaire and asked to respond promptly.)