Tenn, Hong-Ui (2022) Causal Complexity and Causal Ontology of Health-Related Quality of Life Model. In: UNSPECIFIED.
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Abstract
Patient-centered care (PCC) promotes the kind of healthcare that values patients’ rights, perspectives, and autonomy. Clinical practitioners usually employ health-related quality of life (HRQL) measurement tools to help them assess how well they implement PCC. HRQL is a construct that consists of different dimensions of patients’ health conditions, such as biomedical factors, functional status, general health perception, and overall quality of life (McClimans, 2019; Wilson and Cleary, 1995). HRQL measurement tools aim to develop ways of measuring HRQL. Developing an HRQL measurement tool needs a theoretical model. Wilson and Cleary (1995) developed the most widely-used theoretical model that informed the design or development of HRQL measurement tools (Bakas et al., 2012).
In this paper, I will point out that Wilson and Cleary’s model implicitly instills a causal bias into the current HRQL measuring practice, even though they do not explicitly endorse any causal ontology in their model (1995, p. 60). Based on my literature analysis, most of the HRQL research guided by Wilson and Cleary’s model has the same type of causal hypotheses, i.e., from biomedical factors to non-biomedical factors. Causal hypotheses regarding how non-biomedical factors cause biomedical factors are rarely investigated. This causal bias is an obstacle for implementing PCC because it implicitly directs researchers’ attention away from how patients’ values, preferences, and overall quality of life can causally affect their HRQL.
To rectify this implicit causal bias that impedes PCC implementation, I will propose a way to strengthen the causal ontology of Wilson and Cleary’s model. I will employ Rocca and Anjum’s (2020) notion of causal complexity to modify Wilson and Cleary’s model. According to Rocca and Anjum, causal complexity means that variables from different dimensions of a patient can cause each other or co-cause an illness. I propose to change how Wilson and Cleary present causal connections in their diagram to represent their theoretical model. My proposed changes will provide clear guidance and motivation for clinical researchers to investigate how patients’ values, preferences, and overall quality of life can causally affect their HRQL.
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| Item Type: | Conference or Workshop Item (UNSPECIFIED) | ||||||
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| Keywords: | causal complexity, health-related quality of life, patient-centered care, causal ontology, quality of life | ||||||
| Subjects: | General Issues > Causation Specific Sciences > Medicine > Health and Disease General Issues > Reductionism/Holism |
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| Depositing User: | Mr. Hong-Ui Tenn | ||||||
| Date Deposited: | 06 May 2022 15:52 | ||||||
| Last Modified: | 06 May 2022 15:52 | ||||||
| Item ID: | 20543 | ||||||
| Subjects: | General Issues > Causation Specific Sciences > Medicine > Health and Disease General Issues > Reductionism/Holism |
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| Date: | 2022 | ||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/20543 |
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