标题：Fifty psychological and psychiatric terms to avoid: a list of inaccurate, misleading, misused, ambiguous, and logically confused words and phrases
source：journal.frontiersin.org | by Scott O. Lilienfeld, Katheryn C. Sauvigné, Steven Jay Lynn, Robin L. Cautin, Robert D. Latzman and Irwin D. Waldman
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Oxymorons
(39) Hierarchical stepwise regression. Hierarchical and stepwise multiple regression are entirely separate – and incompatible - procedures. Still, they are readily confused, because in hierarchical regression, variables are entered in sequential steps. Specifically, in hierarchical multiple regression the investigator specifies an a priori order of entry of the variables, ideally on theoretical grounds. In contrast, in stepwise multiple regression, the investigators allows the computer to select the order of entry of the variables (and the final variables in the equation) on empirical grounds, namely, by choosing each successive predictor based on the highest incremental contribution to variability in the outcome variable (Wampold and Freund, 1987; Petrocelli, 2003). Many authors have wisely warned against the routine use of stepwise regression procedures on the grounds that they typically capitalize heavily on chance fluctuations in datasets and rarely yield replicable results (Thompson, 1989).
(40) Mind-body therapies. The term “mind-body therapy” (e.g., Naliboff et al., 2008) refers to a panoply of treatments, such as relaxation, meditation, Reiki, yoga, and biofeedback, that purportedly harness mental functioning to enhance physical health (Wolsko et al., 2004). This term implies erroneously that the “mind” is materially separate from the “body” and thereby endorses a simplistic version of mind-body dualism. Rather than conceptualizing such interventions as making use of the mind to influence the body, we should conceptualize them as making use of one part of the body to influence another.
(41) Observable symptom. This term, which appears in nearly 700 manuscripts according to Google Scholar, conflates signs with symptoms. Signs are observable features of a disorder; symptoms are unobservable features of a disorder that can only be reported by patients (Lilienfeld et al., 2013; Kraft and Keeley, 2015). Symptoms are by definition unobservable.
(42) Personality type. Although typologies have a lengthy history in personality psychology harkening back to the writings of the Roman physician Galen and later, Swiss psychiatrist Carl Jung, the assertion that personality traits fall into distinct categories (e.g., introvert vs. extravert) has received minimal scientific support. Taxometric studies consistently suggest that normal-range personality traits, such as extraversion and impulsivity, are underpinned by dimensions rather than taxa, that is, categories in nature (Haslam et al., 2012). With the possible exception of schizotypal personality disorder (but see Ahmed et al., 2013), the same conclusion holds for personality disorders (Haslam et al., 2012). Hence, if authors elect to use the phrase “personality type,” they should qualify it by noting that the evidence for a genuine typology (i.e., a qualitative difference from normality) is in almost all cases negligible within the personality domain.
(43) Prevalence of trait X. Authors in the psychological and psychiatric literatures frequently refer to “the prevalence” or “base rate” of attributes that are dimensionally distributed in the population, such as personality traits and intelligence. For example, one author team referred to the “greater prevalence of extraversion in American students” (p. 1153) compared with Korean students (Song and Kwon, 2012). Nevertheless, such terms as “prevalence,” “incidence,” “base rate,” “false positive,” and “false negative” are premised on a taxonic model: they presume that the phenomena in question are inherently categorical, that is, either present or absent in nature. For psychological features that are continuously distributed, such terms should be avoided. In the aforementioned phrase, referring to “higher levels of extraversion in American students” would have been more accurate.
(44) Principal components factor analysis. According to Google Scholar, this phrase appears in thousands of articles, including one co-authored by the first author of this manuscript (Reynolds et al., 1988). Nevertheless, this phrase is incoherent, because principal components analysis (which is commonly misspelled as “principle components analysis”) and factor analysis are incompatible approaches to data analysis. Principal components analysis is a data reduction technique that relies on the total variance of the variables in a dataset; its principal goal is to create a smaller set of weighted variables (variates) that approximate the variance of the original variables (Weiss, 1970). In contrast, factor analysis relies only on the shared variance of the variables in a dataset, and it is designed to identify underlying dimensions that best explain the covariation among these variables (Bryant and Yarnold, 1995). In contrast to principal components analysis, whose primary aim is to simplify a dataset by yielding fewer observed variables, the primary aim of exploratory factor analysis is to identify dimensions that ostensibly account for the covariation among the observed variables.
(45) Scientific proof. The concepts of “proof” and “confirmation” are incompatible with science, which by its very nature is provisional and self-correcting (McComas, 1996). Hence, it is understandable why Popper (1959) preferred the term “corroboration” to “confirmation,” as all theories can in principle be overturned by new evidence. Nor is the evidence for scientific theories dichotomous; theories virtually always vary in their degree of corroboration. As a consequence, no theory in science, including psychological science, should be regarded as strictly proven. Proofs should be confined to the pages of mathematics textbooks and journals (Kanazawa, 2008).
