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Review
. 2025 Aug 25:16:1553028.
doi: 10.3389/fpsyg.2025.1553028. eCollection 2025.

Psychology's Questionable Research Fundamentals (QRFs): Key problems in quantitative psychology and psychological measurement beyond Questionable Research Practices (QRPs)

Affiliations
Review

Psychology's Questionable Research Fundamentals (QRFs): Key problems in quantitative psychology and psychological measurement beyond Questionable Research Practices (QRPs)

Jana Uher et al. Front Psychol. .

Abstract

Psychology's crises (e.g., replicability, generalisability) are currently believed to derive from Questionable Research Practices (QRPs), thus scientific misconduct. Just improving the same practices, however, cannot tackle the root causes of psychology's problems-the Questionable Research Fundamentals (QRFs) of many of its theories, concepts, approaches and methods (e.g., psychometrics), which are grounded in their insufficiently elaborated underlying philosophies of science. Key problems of psychological measurement are critically explored from independent perspectives involving various fields of expertise and lines of research that are well established but still hardly known in mainstream psychology. This comprehensive multi-perspectival review presents diverse philosophies of science that are used in quantitative psychology and pinpoints four major areas of development. (1) Psychology must advance its general philosophy of science (esp. ontology, epistemology, methodology) and elaborate coherent paradigms. (2) Quantitative psychologists must elaborate the philosophy-of-science fundamentals of specific theories, approaches and methods that are appropriate for enabling quantitative research and for implementing genuine analogues of measurement in psychology, considering its study phenomena's peculiarities (e.g., higher-order complexity, non-ergodicity). (3) Psychologists must heed the epistemic necessity to logically distinguish between the study phenomena (e.g., participants' beliefs) and the means used for their exploration (e.g., descriptions of beliefs in items) to avoid confusing ontological with epistemological concepts-psychologists' cardinal error. This requires an increased awareness of the complexities of human language (e.g., inbuilt semantics) and of the intricacies that these entail for scientific inquiry. (4) Epistemically justified strategies for generalising findings across unique individuals must be established using case-by-case based (not sample-based) nomothetic approaches, implemented through individual-/person-oriented (not variable-oriented) analyses. This is crucial to avoid the mathematical-statistical errors that are inherent to quantitative psychologists' common sample-to-individual inferences (e.g., ergodic fallacy) as well as to enable causal analyses of possibly underlying structures and processes. Concluding, just minimising scientific misconduct, as currently believed, and exploiting language-based algorithms (NLP, LLMs) without considering the intricacies of human language will only perpetuate psychology's crises. Rethinking psychology as a science and advancing its philosophy-of-science theories as necessary fundamentals to integrate its fragmented empirical database and lines of research requires open, honest and self-critical debates that prioritise scientific integrity over expediency.

Keywords: epistemology; language models; measurement; methodology; ontology; psychometrics; quantitative psychology; semantics.

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Conflict of interest statement

PB was employed by Advanced Projects R&D Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

A diagram titled “Psychology's Questionable Research Fundamentals (QRFs)” is divided into four sections, each lists 12-25 different QRFs. Section 1 discusses Psychology as a science and its philosophies and theories of science, mentioning as frequent QRFs, for example, scientism, empiricism, naturalism, positivism, pragmatism, reductionist approaches, ignoring higher-order complexity, comparing just results rather than results with theory for replicability, failure to make basic presuppositions explicit. Section 2 covers Specific theories, epistemologies and methodologies of genuine measurement, mentioning as common QRFs, for example, operationalist generation, neglecting the conceptualisation of the real (empirical) study system, confusing incompatible philosophies of science in psychometrics, misconceiving quality and quantity as dichotomy, quantificationism, result-dependent data generation, measurement by decree and arbitrary units. Section 3 focusses on Psychology's means of scientific inquiry, highlighting as frequent QRFs nominalism - believing a method's name justifies assumptions of what it can capture, mistaking semantic for semantic networks, turning descriptions of study phenomena into their explanations, misinterpret judgments of verbal statements for measurements of the phenomena described and relying on the inbuilt semantics of language-based methods. Section 4 outlines QRFs in the common Strategies used for generalising across unique individuals, such as misconceived nomothetic approaches latent variables misinterpreted as 'traits' or 'psychophysical mechanisms', studying sample averages instead of individual configurations, ignoring the non-ergodicity of psychology's study phenomena, using variable-oriented rather than individual-oriented approaches and mistaking operational for theoretical construct definition.
Figure 1
Psychology's Questionable Research Fundamentals (QRFs): Four main areas of development.
A diagram illustrating the real study system and the formal study system used for its exploration and the relations between them. The real study system involves observable features and presumed causes that are abducted or theorised. The formal study system includes raw data, data analysis and data modelling to yield formal models and implications. These two system are connected through four relations: Relation one is within the real study system indicating its presumed internal relations. Relation two is between real and formal system, this is the encoding relation. Relation three is within the formal system, these are formal relations, and relation four is the way back from the formal to the real system, this is the decoding relation. Arrows indicate the cyclic process of passing through these four relations consecutively and iteratively.
Figure 2
Rosen's general process structure of measurement involves a coherent system of four interrelated modelling relations. It conceptualises the real (empirical) study system and the formal (symbolic) system used for studying it as mathematical objects as well as the processes (mappings, relations) each within and back and forth between them, depicted as arrows. © From Uher (2025), Figure 1; adapted from Rosen (1985).
A diagram featuring a network to illustrate the semantic relations between central verbs such as “cause,” “stimulate,” “drive,” “energize,” “interpret,” “lead,” “act,” and “effect”. Connected words extend from each of these central verbs, illustrating various related words and synonyms, forming a complex web of associations that speakers of English have in their minds when using these words.
Figure 3
Semantic networks Natural language terms mutually define each other within chains of semantic relationships. When used in language-based methods, such as in descriptions of the study phenomena in rating items, semantic relationships were shown to reappear as ‘explained variance' in statistical research models.
Venn diagram illustrating the scope and pre-order of properties among managers. The largest circle represents “Helpful”, the second largest within that large one “Benevolent” and the smallest circle within the middle circle represents “trustworthy” managers. Arrows indicate the pre-order flow: “Helpful” precedes the properties “Benevolent” and “Trustworthy”; the property “Trustworthy” succeeds the properties “Helpful” and “Benevolent”; and the property “Benevolent” precedes the property “Trustworthy” but succeeds “Helpful.” A legend explains the graphical indication of these scopes and preorder relations.
Figure 4
Property scopes and property pre-orders associated with subclasses of things (managers). The different scopes of properties enact different pre-orders on these properties. The property “trustworthy” applies to a subclass of all managers who are “benevolent” of all those managers who are “helpful”. That is, the property “benevolent” precedes the property “trustworthy” and succeeds the property “helpful”. Adapted from Weber (2021).
Diagram illustrating the two different kinds of nomothetic approaches in research. The left side shows “Case-by-case based” nomothetic approaches in which the grouping of individuals is based on the first analysis or known differences in the study phenomena. This allows for grouping individuals on the basis of commonalities that some have as compared to some others. This requires individual / person level analyses, such as using Q-factor analysis, cluster analysis, configurational frequency analysis CFA and latent class analysis LCA. It allows for studying individual-level phenomena. The right hand side shows “Sample-based” nomothetic approaches, where the grouping criteria are specified before the analysis of the study phenomena. This allows for analysing only differences between the thus-created groups, thus for studying only sample level phenomena and aggregates of individuals. Here variable-oriented analyses are used, such as R-factor analysis, ANOVA, between-individual latent variable models (LVM) and structural equation models (SEM).
Figure 5
Two different strategies of nomothetic knowledge generation.

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