Related Experiment Video
Updated: Jun 27, 2026
12:18
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Classification of Factors Affecting Manipulation Tendencies Using Decision Trees.
Seçil Ömür Sünbül1, Müzeyyen Soyer1
1Department of Educational Sciences, Faculty of Education, Mersin University, Mersin 33343, Türkiye.
Behavioral Sciences (Basel, Switzerland)
|June 26, 2026
Summary
This study reveals that preoccupied attachment style, low self-esteem, and younger age are key predictors of higher manipulation tendency in adults. These psychological and developmental factors create distinct profiles for manipulation.
Area of Science:
- Psychology
- Social Psychology
- Behavioral Science
Background:
- Manipulation tendency is a complex behavior influenced by various psychological factors.
- Understanding the hierarchical structure of predictors is crucial for accurate classification.
- Previous research has not fully elucidated the interplay of attachment styles, self-esteem, and demographics in predicting manipulation tendency.
Purpose of the Study:
- To identify and rank variables associated with manipulation tendency levels in adults.
- To describe classification patterns of manipulation tendency using a decision tree method.
- To explore the hierarchical and conditional pathways influencing manipulation tendency.
Main Methods:
- A sample of 543 adults (aged 18-45) from Turkey participated.
- Data collected using the Manipulation Scale, Rosenberg Self-Esteem Scale, and Relationship Scales Questionnaire.
- Classification and Regression Tree (C&RT) analysis employed for classification and pattern identification, with data split into training (70%) and test (30%) sets.
Main Results:
- The most influential variables for classifying manipulation tendency were preoccupied attachment style, self-esteem, and age.
- Younger adults with higher preoccupied attachment and lower self-esteem were more likely classified into the high manipulation tendency group.
- Dismissive attachment style, gender (males more frequently in higher tendency groups), secure, and fearful attachment styles also contributed to classification patterns.
Conclusions:
- Manipulation tendency is multifactorial and hierarchical, influenced by attachment styles, self-esteem, age, and gender.
- Decision tree modeling provides an interpretable framework for understanding complex psychological predictor-outcome relationships.
- Findings contribute to a nuanced understanding of how individual psychological characteristics and developmental factors differentiate manipulation tendency profiles.
Related Concept Videos
01:20Decision Making
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Automatic decision-making is fast, intuitive, and relies on gut feelings...
01:14Decision Making: Traditional Method
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
02:01Factorial Design
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
01:19Survival Tree
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a survival tree begins...
Building a Survival Tree
Constructing a survival tree begins...
01:09Decision Making: P-value Method
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
01:37Reason and Intuition
The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the brain can only use...