Towards an Ontology of Psychometric Measures
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Authors
Rook, Kelsey
Santos, Henrique
Chorpita, Bruce F.
Sprung, Manuel S.
Pinheiro, Paulo
McGuinness, Deborah L.
Issue Date
2024-05-07
Type
Presentation
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Abstract
The field of psychometrics is a subdomain of psychology concerned with assessment of various social and psychological dimensions of humans. In the areas of mental healthcare and the clinical science that supports it, assessment with psychometric instruments remains a dominant strategy for discovery, understanding, and decision-making. This method predominantly relies on text-based distribution of assessment instruments (usually in the form of questionnaires), and significant limitations in terms of interoperability exist. To bridge this gap, we are developing the Psychometric Ontology of Experiences and Measures (POEM) as a domain ontology tailored to capture the relationships and semantics inherent in psychometric instruments. The central aim of this new ontology is to enable the structured representation of psychometric instruments to facilitate standardized assessment across different dimensions and contexts. Other aims are to support the accessibility and construction of instruments, and making machine-readable formats more readily available. POEM considers the connections of observable questionnaire elements and the complex set of latent (unobservable) variables that are the common targets of psychometric assessment. Further POEM supports the tracking of the provenance of assessments at the questionnaire, scale, and item levels in order to capture how assessments are created, used, reused, and translated.
The present work is the result of a collaboration of semantic engineers and clinical scientists to develop an ontology for psychometric instruments, adopting a bottom-up approach informed by competency questions and use cases generated by the domain experts in the team to ensure sufficient coverage. The developed ontology is designed to address diverse use cases spanning clinical services, research, and development of new psychometric instruments. POEM builds on the foundation of existing taxonomies and ontologies for psychological disorders like SNOMED-CT, the ICD, and the DSM, and integrates them with semantics describing the internal structure of psychometric assessments. While these existing taxonomies and ontologies include a comprehensive representation of psychological disorders and symptoms, POEM includes the semantics necessary to describe assessments, capturing items, scales, and provenance. POEM’s architecture builds upon established ontologies like the Virtual Solar-Terrestrial Observatory (VSTO), which is a semantic data framework that supports formal representations of physical quantities and their underlying representations with an instrument-focused subset (VSTO-I), and the Human-Aware Science Ontology (HAScO), which supports the description of scientific data for acquisition, preparation, and annotation across a variety of domains.
POEM facilitates the integration of observable assessment features, those that describe the architecture of an assessment instrument and its essential parts, with the unobservable semantics of the underlying concepts they represent. The majority of document-level features in POEM align with VSTO-I entities, including questionnaires, questionnaire items, and response options. POEM relates assessments to their underlying concepts on an item-level, relating items to the specific symptoms or constructs they address; more deeply, each response option for an item is shown to estimate a specific experience of the symptom in question. Crucially, POEM also supports the encoding of questionnaire items into scales and subscales, each of which assays a construct (e.g., a clinical syndrome such as depression) that may be present at some level in a human informant, further implying the existence or non-existence of a condition (e.g., a depressive disorder). Our current work focuses on the Revised Children’s Anxiety and Depression Scale (RCADS), which estimates elevations of common psychological disorders and symptoms in children and adolescents, with scales for depression and anxiety, as well as subscales for several specific anxiety disorders [2]. POEM also supports the documentation of the creation and reuse of assessments, scales, and items, including derivation, translation, and related provenance.
We evaluate POEM using our competency questions and use case scenarios with regards to the RCADS, an assessment that is suitable for evaluation due to its multiple nested scales, derived versions of different length and target respondents, many translations, and wide usage. Additionally, POEM’s utility is to be demonstrated by its integration into the Semantic Instrument Repository (SIR), a software infrastructure for managing and distributing knowledge graphs related to data acquisition instruments. SIR will harness POEM’s semantic richness to enable semantic search and retrieval functionalities, and facilitate instrument sharing in various formats, including the rendering of questionnaires into human-readable formats. SIR also supports the tracking of the provenance of assessments and their elements, in order to facilitate the creation and reuse of psychometric instruments.
We maintain a GitHub repository of the POEM ontology as well as related artifacts and documentation, available at the following: https://github.com/tetherless-world/POEM
Description
Full Citation
Rook, K., Santos, H., Chorpita, B.F., Sprung, M.S., Pinheiro, P., McGuinness, D.L. 2024. Towards an Ontology of Psychometric Measures. In The Healthcare and Life Sciences Symposium (HCLS), co-located with The 2024 Knowledge Graph Conference (KGC). New York, NY.
Publisher
The Healthcare and Life Sciences Symposium (HCLS), co-located with The 2024 Knowledge Graph Conference (KGC)