Back to the Future of Quantitative Psychology and Measurement: Psychometrics in the Twenty-First Century

被引:11
作者
Cipresso, Pietro [1 ,2 ]
Immekus, Jason C. [3 ]
机构
[1] Ist Auxol Italiano, Appl Technol Neuropsychol Lab, Milan, Italy
[2] Univ Cattolica Sacro Cuore, Dept Psychol, Milan, Italy
[3] Univ Louisville, Coll Educ & Human Dev, Dept Educ Leadership Evaluat & Org Dev, Louisville, KY 40292 USA
来源
FRONTIERS IN PSYCHOLOGY | 2017年 / 8卷
关键词
quantitative psychology; measurement; psychometrics; computational psychometrics; mathematical psychology; VIRTUAL-REALITY; CHRONIC STRESS; ENVIRONMENTS; AXIS;
D O I
10.3389/fpsyg.2017.02099
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Measurements in psychology always have been a significant challenge. Research in quantitative psychology has developed several methods and techniques to improve our understanding of humans. Over the last few decades, the rapid advancement of technology had led to more extensive study of human cognition, including both the emotional and behavioral aspects. Psychometric methods have integrated very advanced mathematical and statistical techniques into the analyses, and in our Frontiers Specialty (Quantitative Psychology and Measurement), we have stressed the methodological dimension of the best practice in psychology. The long tradition of using self-reported questionnaires is still of high interest, but it is not enough in the twenty-first century. We stress the use of innovative methods and technologies as psychometric tools. One of the most significant challenges in quantitative psychology and measurement concerns the integration of technologies and computational techniques into current standards. In the following, our aim is to show how data collection can involve human behavior, internal states and the manipulation of experimental settings. In particular, we define typical psychophysiological measures for a deeper understanding of internal states-analyzing the central and peripheral nervous system, hormonal factors in the endocrine system and the fascinating field of gene transcription in human neuroscience. These factors represent the measurement of the "internal" sphere that is becoming so interesting for measurement in all the field of psychology, including social and affective science, not only in the cognitive sciences. The idea to read internal states has always been very clear in clinical and experimental psychology, but now is becoming even more widespread. This is thanks to the improvements in technologies and lower costs. Next, we highlight the measurement of the exhibited behavior patterns representing the "external" sphere of human thinking through expressed behavior. Again, technology is a critical aspect shedding new light on the field. The use of low-cost and high-end technologies for understanding verbal and nonverbal patterns is helping to identify innovative ways to measure the psychological factors leading to a behavior. They can be considered a new challenge of behavioral science, e.g., the use of commercial devices (such as the Kinect) in motor and cognitive neurorehabilitation. Linked to psychophysiology and exhibited behavior patterns, virtual reality is becoming a cutting-edge tool for experimental manipulation, building personalized experimental settings, but found in a laboratory. We define and highlight the use of virtual reality in psychology as an incredible low-cost tool collecting data and creating realistic situations that can be used for clinical, experimental, social settings among others, and so of keen interest in several psychology fields. In conclusion, we present new methods and techniques already used in other fields, but incredibly expanding also in psychology and psychometrics. Computational science, complex networks, and simulations, are highlighted as the promising new methods for the best convergence of psychological science and technologies. These have ability to create innovative tools for better comprehension and a quantitative measurement in psychology. © 2017 Cipresso and Immekus.
引用
收藏
页数:7
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共 62 条
  • [21] A mobile data collection platform for mental health research
    Gaggioli, Andrea
    Pioggia, Giovanni
    Tartarisco, Gennaro
    Baldus, Giovanni
    Corda, Daniele
    Cipresso, Pietro
    Riva, Giuseppe
    [J]. PERSONAL AND UBIQUITOUS COMPUTING, 2013, 17 (02) : 241 - 251
  • [22] Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection
    Giakoumis, Dimitris
    Drosou, Anastasios
    Cipresso, Pietro
    Tzovaras, Dimitrios
    Hassapis, George
    Gaggioli, Andrea
    Riva, Giuseppe
    [J]. PLOS ONE, 2012, 7 (09):
  • [23] Expanding perspectives on cognition in humans, animals, and machines
    Gomez-Marin, Alex
    Mainen, Zachary F.
    [J]. CURRENT OPINION IN NEUROBIOLOGY, 2016, 37 : 85 - 91
  • [24] Big behavioral data: psychology, ethology and the foundations of neuroscience
    Gomez-Marin, Alex
    Paton, Joseph J.
    Kampff, Adam R.
    Costa, Rui M.
    Mainen, Zachary F.
    [J]. NATURE NEUROSCIENCE, 2014, 17 (11) : 1455 - 1462
  • [25] Heim M., 1993, METAPHYSICS VIRTUAL
  • [26] Virtual environments for motor rehabilitation: Review
    Holden, MK
    [J]. CYBERPSYCHOLOGY & BEHAVIOR, 2005, 8 (03): : 187 - 211
  • [27] Commentary: A network theory of mental disorders
    Jones, Payton J.
    Heeren, Alexandre
    McNally, Richard J.
    [J]. FRONTIERS IN PSYCHOLOGY, 2017, 8
  • [28] Kane R. L., 2017, The role of technology in clinical neuropsychology
  • [29] Neuroscience Needs Behavior: Correcting a Reductionist Bias
    Krakauer, John W.
    Ghazanfar, Asif A.
    Gomez-Marin, Alex
    MacIver, Malcolm A.
    Poeppel, David
    [J]. NEURON, 2017, 93 (03) : 480 - 490
  • [30] The psychophysiology of mixed emotional states: Internal and external replicability analysis of a direct replication study
    Kreibig, Sylvia D.
    Samson, Andrea C.
    Gross, James J.
    [J]. PSYCHOPHYSIOLOGY, 2015, 52 (07) : 873 - 886