Problematic features of episode-based definitions of depression and a preliminary proposal for their replacement
Bibliographic Data
| ID | 15519374 |
|---|---|
| Authors | Scott B Patten (0000-0001-9871-4041, University of Calgary, corresponding author) |
| Year | 2023 |
| Volume | 14 |
| Pages | 1121524-1121524 |
| Publication date | 2023-03-15 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychiatry (JOURNAL) |
| Journal identifiers | ISSN: 1664-0640 • E-ISSN: 1664-0640 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyt.2023.1121524 |
| PMID | 37009098 |
| OpenAlex | W4324374166 |
| Language | EN |
| References cited | 4 |
Episodes of depression are constructed by imposing temporal and symptom-severity thresholds onto symptom levels that vary over time, resulting in a loss of information. Consequently, it is widely acknowledged that binary categorization of depressive episodes is problematic. Binary classification can make similar symptom levels appear different and different symptom levels appear similar. Furthermore, symptom severity is only one of several thresholds that are applied in the construction of depressive episodes in DSM-5 and ICD-11, others being: a minimum duration of symptoms, the application of a "no significant symptoms" threshold for remission, and time requirements (e.g., 2 months) for remission. Application of each of these thresholds leads to a loss of information. The joint occurrence of these four thresholds creates a complex set of circumstances in which similar patterns of symptoms may be categorized differently and different patterns may be categorized as similar. The ICD-11 definition can be expected to lead to better classification than the DSM-5 approach since it does not require two symptom-free months for remission, eliminating one of four problematic thresholds. A more radical change would be to adopt a truly dimensional perspective which would need to incorporate new elements to reflect time spent at various levels of depression. Such an approach, however, seems feasible both in clinical practice and research
Categorization · Clinical Practice · Cognition · Depression (economics · Depressive symptoms · Perspective (graphical · Physical therapy · Psychiatry · Set (abstract data type · Clinical Psychology · Computer Science · Medicine · Mental Health and Psychiatry · Mental Health Research Topics · Psychology · Treatment of Major Depression · Artificial Intelligence
| Citation velocity | historical |
|---|---|
| Highly cited | No |