Myers-Briggs Research Articles

Examining the Relationship between the Integration of Industry and Education and Student Career Mental Health Development: A Case Study of First-year Enterprise Internship at Shanghai Business Accounting School

This study aims to evaluate the effectiveness of industry-education integration on student career development by assessing the vocational personality traits and achievement motivation levels of 994 first-year vocational students from Shanghai Business Accounting School. The MBTI (Myers-Briggs Type Indicator) career personality questionnaire and achievement motivation level questionnaire were employed to measure the outcomes of industry-education integration and provide guidance for career guidance education and enterprise internships for vocational students. The findings indicate that among the four temperament types, the largest proportion is observed among idealists, accounting for 31.3%, while empiricists have the smallest representation at 14.6% among the first-year vocational students. Regarding achievement motivation, the overall achievement motivation score of the first-year vocational students is below zero, indicating a relatively low level of achievement motivation. Specifically, both empiricists and idealists demonstrate a relatively low level of achievement motivation in terms of vocational personality traits. A follow-up assessment of achievement motivation levels was conducted after a short-term enterprise internship, revealing a significant improvement in the achievement motivation levels of the vocational students. This suggests that the dual-subject educational model under industry-education integration can effectively enhance students' vocational skills and activate their internal motivation, thereby improving their achievement motivation and overall competitiveness. By leveraging industry-education integration, the school aims to cultivate high-quality talents and address specific talent shortages in the market, ultimately achieving mutual success between talents and the market.

A Study of the Effects of an Individual's Personality and Characteristics on Job Behavior Using the Myers-Briggs Type Indicator

The Myers-Briggs Type Indicator (MBTI) personality test is becoming increasingly commonly used and acknowledged in many fields as a way to identify personality, and some businesses are starting to implement it in many workplaces to assist businesses increase productivity. This study tries to describe the ways in which MBTI can be used to determine an individual's traits in work behaviours, especially when dealing with other people, tasks, assessments, and friendship prospects. To come to a conclusion about how a person's personality and features affect their behaviour at work, this research uses an integrated method of literature review. For the purpose of understanding and interpreting this integrative literature study, numerous guidelines and case-based examples have been explored. It still has certain drawbacks, and there are just a few prior research. Future research in this area will be required to adapt.

Top-Down Influence? Predicting CEO Personality and Risk Impact from Speech Transcripts

How much does a CEO’s personality impact the performanceof their company? Management theory posits a great influence, but it is difficult to show empirically—there is a lack of publicly available self-reported personality data of top managers. Instead, we propose a text-based personality regressor based on crowd-sourced Myers–Briggs Type Indicator (MBTI) assessments. The ratings have a high internal and external validity and can be predicted with moderate to strong correlations for three out of four dimensions. Providing evidence for the upper echelons theory, we demonstrate that the predicted CEO personalities have explanatory power of financial risk.

Development and Validation of a Short-Form Inventory to Identify Personality Types: The Personality Identity Estimator (PIE)

The use of personality inventories has been limited because of their cost and the length. To overcome these limitations, this study created the Personality Identity Estimator (PIE), an easy-to-use inventory to estimate personality types that can be used at no cost. PIE is a categorical inventory containing 12 items with 3 items for each of the 4 personality-type dimensions in Jungian theory. A sample of 1,104 was used to create PIE. Validity was established through multivariate analyses using data from the administration of the Myers-Briggs Type Indicator to 553 of the sample. Reliability was established by test-retest. Consequently, PIE is a new short-form instrument to estimate personality type following Jung’s concept of personality types. PIE can be completed quickly, is easy to score and interpret, and can be used for self-assessment of personality types. PIE can be used to address individual differences, to increase self-awareness, and as an interactive instructional tool. Thus, PIE is a new valid and reliable tool that can be used in both instructional and research settings confidently and at no charge. Permission is granted to use the Personality Identity Estimator in practice and research. A printable copy of PIE is appended.

Research on the Popularity and Impact of the Myers-Briggs Type Indicator on Young People in China

Self-concept is always an essential part of individuals. A personality test can help people recognize the connections between themselves and the mass society. In recent two years, Myers-Briggs Type Indicator, or MBTI, has become significantly popular among young people in China. Most past research focuses on the theories and implications of MBTI but does not have a clear investigation of how the wide use of MBTI would have an impact on people. This paper will target MBTI as the research subject, discussing its advantages and limitations as well as the possible impacts on young people in disseminating MBTI. A questionnaire will be distributed randomly to young people from different regions of China, combining past research and psychological concept with the result of the questionnaire to help the analysis and conclusion. The research concludes that young people, mostly in urban areas in China, are highly exposed to the MBTI test. The dissemination of MBTI could contribute to interior factors (psychological aspects) and exterior factors (social aspects). From the data analysis, the reliability of MBTI is still under discussion. In general, most people believe their personality types resemble themselves. However, there are pros and cons that result from the popularity of MBTI. For example, most noticeably, judging a person purely based on their personality test results.

Exploring the Relationship Between Imposter Phenomenon and Myers-Briggs Personality Types in Pharmacy Education

ObjectiveTo investigate the relationship between imposter phenomenon (IP) and Myers-Briggs Type Indicator (MBTI) personality types in pharmacy students. MethodsThis was a retrospective, observational study of doctor of pharmacy students who had previously completed MBTI and Clance Imposter Phenomenon Scale (CIPS) assessments. CIPS scores and categories were compared between the 4 MBTI personality type dichotomies using independent samples t tests and chi-square. ResultsMean CIPS score for included pharmacy students (N = 668) was 62.52 (SD 14.82). Clance Imposter Phenomenon Scale scores were significantly higher in students with MBTI of introversion (mean 64.14, SD 14.27), intuition (mean 63.80, SD 15.78), and perceiving (mean 64.38, SD 15.55) as compared to their dichotomous counterparts. No significant difference in mean CIPS scores was found within the thinking/feeling dichotomy. When analyzing IP risk associated with the various MBTI personality dichotomies, introverts were at a 1.8 times greater risk of high/severe IP than extroverts. Additionally, students with perceiving personality types were at a 1.4 times greater risk of high/severe IP than those with judging personality types. ConclusionOur study suggests that pharmacy students with introversion, intuitive, and perceptive personality types exhibit higher CIPS scores, and those with introversion or perceptive personality types are at risk for high/severe IP. Given the common MBTI types and a high degree of IP in pharmacy students, our findings underlie the need for open, targeted discussions about IP and proactively incorporating strategies and resources within a curriculum to support students in normalizing and easing anxiety.

Personality Detection using Kernel-based Ensemble Model for Leveraging Social Psychology in Online Networks

The Asian social networking market dominates the world landscape with the highest consumer penetration rate. Businesses and investors often look for winning strategies to attract consumers to increase revenues from sales, advertisements, and other services offered on social media platforms. Social media engagement and online relational cohesion have often been defined within the frameworks of social psychology and personality identification is a possible way in which social psychology can inform, engage, and learn from social media. Personality profiling has many real-world applications, including preference-based recommendation systems, relationship building, and career counseling. This research puts forward a novel kernel-based soft-voting ensemble model for personality detection from natural language, KBSVE-P. The KBSVE-P model is built by first evaluating the performance of various Support Vector Machine (SVM) kernels, namely radial basis function (RBF), linear, sigmoidal, and polynomial, to find the best-suited kernel for automatic personality detection in natural language text. Next, an ensemble of SVM kernels is implemented with a variety of voting techniques, such as soft voting, hard voting, and weighted hard voting. The model is evaluated on the publicly available Kaggle_MBTI dataset and a novel South Asian, Indian, low-resource Hindi language_MBTI (pronounced as vishesh charitr, meaning personality in Hindi) dataset for detecting a user's personality across four personality traits, namely introvert/extrovert (IE), thinking/feeling (TF), sensing/intuitive (SI), and judging/perceiving (JP). The proposed kernel-based ensemble with soft voting, KBSVE-P, outperforms the existing models on English Kaggle-MBTI dataset with an average F-score of 85.677 and achieves an accuracy of 66.89 for the Hindi_MBTI dataset.

KLASIFIKASI KEPRIBADIAN MENGGUNAKAN ALGORITMA MACHINE LEARNING

Myers-Briggs Personality Type (MBTI) is a popular personality metric that uses four dichotomies as indicators of personality traits. This study uses a public dataset from Kaggle, namely the Myers-Briggs Personality Type Dataset, the model tested is several machine learning classification models with the help of imlearn under-over sampling techniques for classifying MBTI personality types. This study aims to classify the Myers-Briggs Type Indicator (MBTI) personality type based on text from user posts on the social media platform Reddit. The dataset used in this study consists of around 8,000 posts collected from the MBTI subreddit. Several text processing methods such as tokenization, punctuation removal, and stemming are used to process the raw data before it is entered into the model. The experimental results show that the LSTM model using Adam's optimizer and a learning rate of 0.01 produces good performance with an accuracy of 80.73 compared to other machine learning models. In addition to the LSTM model, XG Boost is also a classification model with the highest accuracy based on 16 personality types producing an accuracy of 60.09 and Logistic Regression with the NS dimension as the best accuracy value of 87.21%.

Human Personality Prediction by Text Analysis Using CNN

In recent years, predicting an individual's MBTI type using multiple data sources has become a major research subject. In this paper, we explore the use of machine learning algorithms for MBTI prediction based on text data. Recently, many firms have begun shortlisting individuals based on their personality, as this increases job efficiency because the person would be able to work on what he is good at rather than what he is compelled to do.The personality model used in this model is Myers-Briggs Personality Type Indicator. The Myers-Briggs Type Indicator (MBTI) is a popular personality evaluation tool which separates people into 16 personality types based on their preferences in four domains. Recent study has revealed that machine learning algorithms can be used to identify an individual's MBTI type based on writing samples.In this paper, we propose a methodology to predict an individual's MBTI type using machine learning algorithms such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Text Analysis. We also link an individual's MBTI type to job roles to aid in the recruitment process.

Examination of the Possible Relationship of MBTI Personality Types among Cardiac Rehabilitation Patients– A Cross-Sectional Study

INTRODUCTION: The relationship between personality type and medical problems has been discussed widely in the literature, but empirical data on the relationship between heart diseases and personality types is lacking. In the current study, we aim to look at the connections (if there are ones) between Myer-Briggs Type Indicator (MBTI) personality types and Cardiac Rehabilitation Patients (CRPs) profiles. 
 
 MATERIALS & METHODS: The current cross-sectional study was conducted from October 2017 to February 2019. The study included five hundred fifty-two (male: 336, female: 216) CRPs referred to Tehran Heart Center via a convenient sampling. After acquiring a written consent form and obtaining demographic data (age, educational status, blood type, antigen type, BMI, risk factors) from the medical history database, we asked participants to answer to Persian version of the MBTI questionnaire. Finally, we assessed any existing (if there) relationship between MBTI subtypes and the abovementioned variables among CRPs.
 
 RESULTS: According to the current study, among 16 MBTI personality types, only four types were identified in cardiac rehabilitation patients. Accordingly, INTJ maintained the highest frequency of CRPs, followed by ISTJ, ESTJ and ISFJ, respectively. The current study demonstrated a significant difference between PCI and CABG interventions among four MBTI dichotomies. The study also shows no significant association between risk factors and MBTI personality types (P<0.05).
 
 CONCLUSION: The result of the study has a salient clinical implication, as it can be adopted in the screening and intervention phases of the clinical process. During the screening, a clinician can tailor the therapeutic procedures according to the specific needs of the patient's personality traits. Furthermore, clinicians may elevate patients' adherence to treatment by considering specific personality preferences.

MBTI Personality Prediction Using Machine Learning and SMOTE for Balancing Data Based on Statement Sentences

The rise of social media as a platform for self-expression and self-understanding has led to increased interest in using the Myers–Briggs Type Indicator (MBTI) to explore human personalities. Despite this, there needs to be more research on how other word-embedding techniques, machine learning algorithms, and imbalanced data-handling techniques can improve the results of MBTI personality-type predictions. Our research aimed to investigate the efficacy of these techniques by utilizing the Word2Vec model to obtain a vector representation of words in the corpus data. We implemented several machine learning approaches, including logistic regression, linear support vector classification, stochastic gradient descent, random forest, the extreme gradient boosting classifier, and the cat boosting classifier. In addition, we used the synthetic minority oversampling technique (SMOTE) to address the issue of imbalanced data. The results showed that our approach could achieve a relatively high F1 score (between 0.7383 and 0.8282), depending on the chosen model for predicting and classifying MBTI personality. Furthermore, we found that using SMOTE could improve the selected models’ performance (F1 score between 0.7553 and 0.8337), proving that the machine learning approach integrated with Word2Vec and SMOTE could predict and classify MBTI personality well, thus enhancing the understanding of MBTI.

Personality Types and Traits—Examining and Leveraging the Relationship between Different Personality Models for Mutual Prediction

The popularity of social media services has led to an increase of personality-relevant data in online spaces. While the majority of people who use these services tend to express their personality through measures offered by the Myers–Briggs Type Indicator (MBTI), another personality model known as the Big Five has been a dominant paradigm in academic works that deal with personality research. In this paper, we seek to bridge the gap between the MBTI, Big Five and another personality model known as the Enneagram of Personality, with the goal of increasing the amount of resources for the Big Five model. We further explore the relationship that was previously reported between the MBTI types and certain Big Five traits as well as test for the presence of a similar relationship between Enneagram and Big Five measures. We propose a new method relying on psycholingusitc features selected based on their relationship with the MBTI model. This approach showed the best performance through our experiments and led to an increase of up to 3% in automatic personality recognition for Big Five traits on the per-trait level. Our detailed experimentation offers further insight into the nature of personality and into how well it translates between different personality models.

Myers-Briggs Type Indicator analysis using decision-tree-related methods

Myers-Briggs Type Indicator (MBTI) is currently one of the most widely used personality testing tools. MBTI has important value in the field of psychology and career planning. In this essay, a system that can predict people's MBTI features based on their social media posts is proposed. The dataset used in this paper is derived from the online posts of peo-ple with different MBTI personality types. After these posts are preprocessed, they will be analyzed using methods related to decision trees such as random forest and XGBoost. The results from these methods will be compared to other common methods, such as neural networks. The essay measures the ability of the different methods by using the classifying accuracy in the four different dimensions of MBTI. The decision-tree-related methods achieved generally higher accuracy in the task than other types of methods such as neural networks. Methods such as random forest achieved accuracy over 85% on the second la-bel (N/S), and at least 60% accuracy on other labels.

Identifying 16 Personalities Based on Daily Writing by Random Forest and Logistic Regression

The Myers-Briggs Type Indicator (MBTI) is a self-reported personality test based on psychological theory proposed by Carl Gustav Jung, elaborated and developed by Katharine Cook Briggs and Isabel Briggs Myers. It separates human’s personality into 4 dimensions: mind, energy, nature and tactics, 2 directions are provided in each dimension, and it results 16 distinct personalities. Through the exquisite figures design of each personality and extensive advertisement, the test has immediately attracted a huge amount of participants among the youth. Finally, the MBTI test gradually creates a new trend of labeling and judging people according to their personality. Current studies have predicted the personality through linear SVM, Neural network, and K-means. This study devotes to utilize Logistic Regression model and Random forest model to predict based on the daily conversation. As a result, the accuracy that the author gets is relatively high comparing with similar works, and the best accuracy of 4 dimensions (Mind, Energy, Nature, Tactics) in author’s model reaches 78.67%, 85.82%, 58.73% and 63.0%.. The purpose of this study is examining the practicability of implementing machine learning in the psychological field, meanwhile, extends the methods of predict one’s personality. Studies in this field can be further used to help analyze a people, and assist the doctors to treat psychological problems.

BERPIKIR KRITIS SISWA BERKEPRIBADIAN SENSING, INTUITION, THINKING DAN FEELING DALAM MENYELESAIKAN MASALAH DENGAN INFORMASI KONTRADIKSI

Critical thinking skill is necessary to be learned by every students, because by thinking critically students are able to understand other mathematical skills. One of the problems that can improve critical thinking skills is Problem With Contradiction Information (PWCI), which means problem that contains wrong information. Every student has their own characteristics, it also influences their critical thinking. One of the ways to identify a type of personality people is by using the Myers Briggs Type Indicator (MBTI), which classifies humans based on several perspectives, such as how to understanding and receiving information (Sennsing-Intuition), also how to make a conclusion and decision (Thinking-Feeling). The purpose of this study is to describe the critical thinking skills of students with sensing, intuition, thinking and feeling personalities. This research is a descriptive study with a qualitative approach. This research was based on SMAN Arjasa, and the subject was 8 students consisting of 2 students each with sensing, intuition, thinking and feeling personality. Data collection methods used are test and interview. The analysis technique used is the analysis of test results, interviews and triangulation. The results of this research revealed that students with sensing, intuition, thinking and feeling personality types have their own characteristics when solving the problem. The results of the critical thinking test found that there were no students who were able to fulfill critical thinking skills but there were students who were able to find contradictory information in the question

Assessment of High Performing Teachers: The Role of Personality Traits

The majority of the successful organizations of the world are using personality assessment tests like Myers Briggs Type Indicator (MBTI) for recruitment and selection (R&S), and to better understand the strengths and weaknesses of their high performing employees. MBTI research divides humans into 16 categories and also proposes that those having specific personality traits can adopt the teaching profession, as it suits their personality. Employers in Pakistan hardly use any personality assessment tools for recruitment and selection, and still rely on more conservative methods like ‘interviews’.

How good is the Myers-Briggs Type Indicator for predicting leadership-related behaviors?

The Myers-Briggs Type Indicator (MBTI) is a popular tool used by psychologists working as managers' coaches in organizational contexts. Despite its popularity, few studies provide empirical evidence on the role of the MBTI as a predictor of managers' leadership-related behaviors. This article is written based on research that answers the question of how good the MBTI is to prove leadership behavior. It does so by comparing goodness-of-fit indexes of two confirmatory factor analysis models and two structural models on the personality-leadership relationship, following standards of reproducible research principles. We sampled 529 participants who were graduate and undergraduate students enrolled in business administration programs from Colombian universities. Results show conclusive evidence of the psychometric measurement of both MBTI and leadership practices, even though the relationship between MBTI and the leadership practices inventory proved to be weak.

Personality Analysis by Tweet Mining

Social Media addiction is becoming a Commonplace. A user gets deeply involve with an application or website that he share it thoughts , ideas and viewpoints on these platforms more comfortably then communicating with an people face to face . By text mining these viewpoint and thoughts from social Media psychological profiling can b done to improve user experience & personality assessment .The aim is to exhibits the construct validation framework for Personality Analysis using machine learning approaches like Term Frequency-Inverse Document Frequency (TF-IDF) SVM. We put forward the methodology by which user’s personality can be analyzed using publicly available information on user’s personal Twitter account using the Myers_Briggs Type Indicator (MBTI). This study will contribute & help in many ways such as customization of Content displayed and product list , Recruitment and Information Retrieval.

Concepts and experiments on psychoanalysis driven computing

This research investigates the effective incorporation of the human factor and user perception in text-based interactive media. In such contexts, the reliability of user texts is often compromised by behavioural and emotional dimensions. To this end, several attempts have been made in the state of the art, to introduce psychological approaches in such systems, including computational psycholinguistics, personality traits and cognitive psychology methods.In contrast, our method is fundamentally different since we employ a psychoanalysis-based approach; in particular, we use the notion of Lacanian discourse types, to capture and deeply understand real (possibly elusive) characteristics, qualities and contents of texts, and evaluate their reliability. As far as we know, this is the first time computational methods are systematically combined with psychoanalysis. We believe such psychoanalytic framework is fundamentally more effective than standard methods, since it addresses deeper, quite primitive elements of human personality, behaviour and expression which usually escape methods functioning at “higher”, conscious layers. In fact, this research is a first attempt to form a new paradigm of psychoanalysis-driven interactive technologies, with broader impact and diverse applications.To exemplify this generic approach, we apply it to the case-study of fake news detection; we first demonstrate certain limitations of the well-known Myers–Briggs Type Indicator (MBTI) personality type method, and then propose and evaluate our new method of analysing user texts and detecting fake news based on the Lacanian discourses psychoanalytic approach.

Stress levels among pre-clinical Medical students and their coping strategies

BACKGROUND & OBJECTIVE: Stress is no doubt prevalent among medical students. Insight into how different personality types cope with this challenge might give the opportunity to healthcare authorities to devise a more standardized guideline for conducting a psychological aptitude test at the time of intake into medical school. Our objective is to look at the stress and anxiety among medical students and how different personality types cope with stress.
 METHODOLOGY: A Cross-sectional descriptive study was carried out at CMH Kharian Medical College from November 2020 to May 2021. Agha Khan University, Anxiety and Depression Scale was employed to assess stress and anxiety levels among medical students. Myers–Briggs Type Indicator (MBTI) was used to identify personality traits, and the “Brief COPE Inventory Scale” was employed to investigate stress coping styles(approach or avoidant) among students. SPSS was used to analyze the results.
 RESULTS: Out of 158 participants, 108(68.4%) were females, and 50(31.6%) were males. More than half of the preclinical medical students, 93(58.86%) were having stress [females 73(67.59%), males 20(40%)]. Personality types showed that 100(63.3%) students belonged to the introvert group, while 58(36.7%) students belonged to the extrovert group. Most participants, 144(91%) students, adopted approach coping styles rather than avoidant ones (14 (8.86%). Stress was significantly associated with personality types (p=0.021), coping style (p=0.007), and gender (female) (p=0.001). However, we did not find any association between personality types & coping styles (p=0.936).
 CONCLUSION: High level of stress and anxiety (58.86%) was found among students and was more prevalent among females and extroverted medical students. Both personality types (extroverts and introverts) used approach coping styles rather than avoidant trends.