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一种整合迈尔斯-布里格斯类型指标(MBTI)和支配性、影响性、稳定性及尽责性(DISC)的个性化健康训练综合剖析系统:相关性分析与可用性评估

A Comprehensive Profiling System Integrating Myers-Briggs Type Indicator (MBTI) and Dominance, Influence, Steadiness, and Conscientiousness (DISC) for Personalized Health Training: Correlational Analysis and Usability Evaluation.

作者信息

Kim Donghyun, Lee Dong Hun, Hwang Mi Kyung

机构信息

Department of Industrial and Systems Engineering, Dongguk University, Seoul, Republic of Korea.

KOI Healthcare Co., Ltd., Seoul, Republic of Korea.

出版信息

JMIR Hum Factors. 2025 Jul 18;12:e73397. doi: 10.2196/73397.

DOI:10.2196/73397
PMID:40686278
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12319163/
Abstract

BACKGROUND

This study proposes an integrated approach to developing personalized health behavior change programs by combining personality traits and behavior types. Existing tools, such as Myers-Briggs Type Indicator (MBTI) and Dominance, Influence, Steadiness, and Conscientiousness (DISC), have limitations: MBTI reflects internal tendencies but lacks behavioral insights, while DISC highlights behavior but overlooks deeper personality aspects. To address these gaps, the study integrates MBTI and DISC to create a comprehensive profiling system.

OBJECTIVE

The goal of this research is to design a novel profiling system that merges MBTI and DISC for personalized health management. This system aims to link personality traits with behavior patterns to enhance the effectiveness of tailored health behavior change programs.

METHODS

The study involved 3 phases: administering MBTI and DISC tests to 130 participants to analyze correlations, developing an integrated survey for health behavior analysis, and testing its usability with 20 experts for validation.

RESULTS

Significant correlations were observed between MBTI and DISC indicators, including a notable negative correlation between Thinking-Feeling (T/F) and Dominance (D), suggesting an inverse relationship between decision-making preferences and assertiveness. Usability testing results indicated high participant satisfaction, with an average SUS (System Usability Scale) score of 86.0. The SUS is a widely used questionnaire for measuring subjective assessments of usability. This score exceeded industry benchmarks for system usability. Expert evaluations further reinforced the system's practical applicability, highlighting its potential to enhance user engagement through personalized behavioral insights.

CONCLUSIONS

This study presents a combined MBTI and DISC profiling system, offering both theoretical insights and practical tools for health behavior change programs. Future research should validate its effectiveness with larger samples and explore broader applications in various health domains.

摘要

背景

本研究提出了一种通过结合人格特质和行为类型来制定个性化健康行为改变计划的综合方法。现有工具,如迈尔斯-布里格斯类型指标(MBTI)和支配性、影响性、稳定性和尽责性(DISC),存在局限性:MBTI反映内部倾向但缺乏行为洞察力,而DISC突出行为但忽略了更深层次的人格方面。为了弥补这些差距,该研究将MBTI和DISC整合,创建了一个全面的剖析系统。

目的

本研究的目标是设计一种新颖的剖析系统,将MBTI和DISC合并用于个性化健康管理。该系统旨在将人格特质与行为模式联系起来,以提高量身定制的健康行为改变计划的有效性。

方法

该研究包括三个阶段:对130名参与者进行MBTI和DISC测试以分析相关性,开发用于健康行为分析的综合调查问卷,并与20名专家进行可用性测试以进行验证。

结果

在MBTI和DISC指标之间观察到显著相关性,包括思维-情感(T/F)和支配性(D)之间显著的负相关,表明决策偏好和 assertiveness 之间存在反比关系。可用性测试结果表明参与者满意度很高,系统可用性量表(SUS)的平均得分为86.0。SUS是一种广泛用于测量可用性主观评估的问卷。该分数超过了系统可用性的行业基准。专家评估进一步加强了该系统的实际适用性,突出了其通过个性化行为洞察力提高用户参与度的潜力。

结论

本研究提出了一种结合MBTI和DISC的剖析系统,为健康行为改变计划提供了理论见解和实用工具。未来的研究应该用更大的样本验证其有效性,并探索在各个健康领域更广泛的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/13e8bebd1481/humanfactors-v12-e73397-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/dc465b20d324/humanfactors-v12-e73397-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/689531b18abe/humanfactors-v12-e73397-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/d5e54f324859/humanfactors-v12-e73397-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/bb4984e68ee1/humanfactors-v12-e73397-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/5adec032f772/humanfactors-v12-e73397-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/13e8bebd1481/humanfactors-v12-e73397-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/dc465b20d324/humanfactors-v12-e73397-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/689531b18abe/humanfactors-v12-e73397-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/d5e54f324859/humanfactors-v12-e73397-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/bb4984e68ee1/humanfactors-v12-e73397-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/5adec032f772/humanfactors-v12-e73397-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc3/12319163/13e8bebd1481/humanfactors-v12-e73397-g006.jpg

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