Opportunities of measuring hierarchical models of psychopathology
Abstract All psychiatric phenomena are positively associated, and several different models can account for this observation. These include the correlated factors, network, general psychopathology as outcome, and hierarchical models. Advantages of hierarchical models, which consist of one general and...
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| Format: | Article |
| Language: | English |
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Wiley
2023-12-01
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| Series: | JCPP Advances |
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| Online Access: | https://doi.org/10.1002/jcv2.12187 |
| _version_ | 1797405160049213440 |
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| author | Erik Pettersson |
| author_facet | Erik Pettersson |
| author_sort | Erik Pettersson |
| collection | DOAJ |
| description | Abstract All psychiatric phenomena are positively associated, and several different models can account for this observation. These include the correlated factors, network, general psychopathology as outcome, and hierarchical models. Advantages of hierarchical models, which consist of one general and several (general factor‐residualized) specific factors, is that the general factor provides an opportunity to reliably measure global distress and impairment, while the specific factors might improve the ability to discriminate between individuals with different kinds of problems. Nevertheless, other models also have their respective advantages, and it remains challenging to empirically determine which model best accounts for the positive manifold in psychiatry. Instead, I present two non‐empirical arguments in favor of hierarchical models. First, by measuring the general factor in isolation, the specific factors tend to include both favorable and unfavorable correlates, which might reduce stigma compared to psychiatric diagnoses that by and large are associated with only unfavorable outcomes. Second, the general psychopathology factor displays an unusual psychometric property in that it includes symptoms of opposite meaning if they have similar valence (e.g., self‐reported symptoms such as gullible and paranoid, lazy and workaholic, and terrified and apathetic load in the same direction), which one might want to measure in isolation from variance capturing the content of symptoms. I conclude by speculating that tests designed based on hierarchical models might help clinical assessment. |
| first_indexed | 2024-03-09T03:05:45Z |
| format | Article |
| id | doaj.art-28c07d09273942b2acc9f9e57ecf46c9 |
| institution | Directory Open Access Journal |
| issn | 2692-9384 |
| language | English |
| last_indexed | 2024-03-09T03:05:45Z |
| publishDate | 2023-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | JCPP Advances |
| spelling | doaj.art-28c07d09273942b2acc9f9e57ecf46c92023-12-04T07:30:04ZengWileyJCPP Advances2692-93842023-12-0134n/an/a10.1002/jcv2.12187Opportunities of measuring hierarchical models of psychopathologyErik Pettersson0Department of Medical Epidemiology and Biostatistics Karolinska Institutet Stockholm SwedenAbstract All psychiatric phenomena are positively associated, and several different models can account for this observation. These include the correlated factors, network, general psychopathology as outcome, and hierarchical models. Advantages of hierarchical models, which consist of one general and several (general factor‐residualized) specific factors, is that the general factor provides an opportunity to reliably measure global distress and impairment, while the specific factors might improve the ability to discriminate between individuals with different kinds of problems. Nevertheless, other models also have their respective advantages, and it remains challenging to empirically determine which model best accounts for the positive manifold in psychiatry. Instead, I present two non‐empirical arguments in favor of hierarchical models. First, by measuring the general factor in isolation, the specific factors tend to include both favorable and unfavorable correlates, which might reduce stigma compared to psychiatric diagnoses that by and large are associated with only unfavorable outcomes. Second, the general psychopathology factor displays an unusual psychometric property in that it includes symptoms of opposite meaning if they have similar valence (e.g., self‐reported symptoms such as gullible and paranoid, lazy and workaholic, and terrified and apathetic load in the same direction), which one might want to measure in isolation from variance capturing the content of symptoms. I conclude by speculating that tests designed based on hierarchical models might help clinical assessment.https://doi.org/10.1002/jcv2.12187comorbiditygeneral psychopathologyhierarchical factor modelsP factor |
| spellingShingle | Erik Pettersson Opportunities of measuring hierarchical models of psychopathology JCPP Advances comorbidity general psychopathology hierarchical factor models P factor |
| title | Opportunities of measuring hierarchical models of psychopathology |
| title_full | Opportunities of measuring hierarchical models of psychopathology |
| title_fullStr | Opportunities of measuring hierarchical models of psychopathology |
| title_full_unstemmed | Opportunities of measuring hierarchical models of psychopathology |
| title_short | Opportunities of measuring hierarchical models of psychopathology |
| title_sort | opportunities of measuring hierarchical models of psychopathology |
| topic | comorbidity general psychopathology hierarchical factor models P factor |
| url | https://doi.org/10.1002/jcv2.12187 |
| work_keys_str_mv | AT erikpettersson opportunitiesofmeasuringhierarchicalmodelsofpsychopathology |