Introduction: Depression and demoralization are highly prevalent among individuals with physical illnesses but their relationship is still unclear. Objective: To examine the relationship between clinical features of depression and demoralization with the network approach to psychopathology. Methods: Participants were recruited from the medical wards of a University Hospital in Italy. The Demoralization Scale (DS) was used to assess demoralization, while the Patient Health Questionnaire-9 (PHQ-9) to assess depressive symptoms. The structure of the depression-demoralization symptom network was examined and complemented by the analysis of topological overlap and Exploratory Graph Analysis (EGA) to identify the most relevant groupings (communities) of symptoms and their connections. The stability of network models was estimated with bootstrap procedures and results were compared with factor analysis. Results: Life feeling pointless, low mood/discouragement, hopelessness and feeling trapped were among the most central features of the network. EGA identified four communities: (1) Neurovegetative Depression, (2) Loss of purpose, (3) Frustrated Isolation and (4) Low mood and morale. Loss of purpose and low mood/morale were largely connected with other communities through anhedonia, hopelessness and items related to isolation and lack of emotional control. Results from EGA displayed good stability and were comparable to those from factor analysis. Limitations: Cross-sectional design; sample heterogeneity Conclusions: Among general hospital inpatients, features of depression and demoralization are independent, with the exception of low mood and self-reproach. The identification of symptom groupings around entrapment and helplessness may provide a basis for a dimensional characterization of depressed/demoralized patients, with possible implications for treatment.

The relationship between demoralization and depressive symptoms among patients from the general hospital: network and exploratory graph analysis

Belvederi Murri M.
Primo
;
Caruso R.
Secondo
;
Ounalli H.;Zerbinati L.;Berretti E.;Costa S.;Recla E.;Folesani F.;Nanni M. G.
Penultimo
;
Grassi L.
Ultimo
2020

Abstract

Introduction: Depression and demoralization are highly prevalent among individuals with physical illnesses but their relationship is still unclear. Objective: To examine the relationship between clinical features of depression and demoralization with the network approach to psychopathology. Methods: Participants were recruited from the medical wards of a University Hospital in Italy. The Demoralization Scale (DS) was used to assess demoralization, while the Patient Health Questionnaire-9 (PHQ-9) to assess depressive symptoms. The structure of the depression-demoralization symptom network was examined and complemented by the analysis of topological overlap and Exploratory Graph Analysis (EGA) to identify the most relevant groupings (communities) of symptoms and their connections. The stability of network models was estimated with bootstrap procedures and results were compared with factor analysis. Results: Life feeling pointless, low mood/discouragement, hopelessness and feeling trapped were among the most central features of the network. EGA identified four communities: (1) Neurovegetative Depression, (2) Loss of purpose, (3) Frustrated Isolation and (4) Low mood and morale. Loss of purpose and low mood/morale were largely connected with other communities through anhedonia, hopelessness and items related to isolation and lack of emotional control. Results from EGA displayed good stability and were comparable to those from factor analysis. Limitations: Cross-sectional design; sample heterogeneity Conclusions: Among general hospital inpatients, features of depression and demoralization are independent, with the exception of low mood and self-reproach. The identification of symptom groupings around entrapment and helplessness may provide a basis for a dimensional characterization of depressed/demoralized patients, with possible implications for treatment.
2020
Belvederi Murri, M.; Caruso, R.; Ounalli, H.; Zerbinati, L.; Berretti, E.; Costa, S.; Recla, E.; Folesani, F.; Kissane, D.; Nanni, M. G.; Grassi, L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2475927
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