1. From Loss to Loneliness: The Relationship Between Bereavement and Depressive Symptoms
Eiko Fried
KU Leuven

2. Current research practices
Depression understood as a latent variable
We can measure this latent variable by assessing its observable indicators
We assess symptoms such as sad mood, fatigue, and insomnia to indicate the presence of the underlying disorder
We can so because depression is the common cause for its symptoms
Symptom sum-scores used to provide information about people's position on the latent variable
Cutoffs on sum-scores used to distinguish between healthy and depressed
Introduction

3. Current research practices
Consequences:
Depression is studied as homogeneous, discrete diagnostic category ("genes for depression", "risk factors for depression")
Symptoms modeled as passive and interchangeable indicators
Reciprocal interactions among symptoms (emotion dynamics) are considered irrelevant
These results encouraged us to study bereavement on the level of symptoms
Introduction

4. Current research practices
Consequences:
Depression is studied as homogeneous, discrete diagnostic category ("genes for depression", "risk factors for depression")
Symptoms modeled as passive and interchangeable indicators
Reciprocal interactions among symptoms (emotion dynamics) are considered irrelevant
This contrasts with evidence:
1,030 unique depression symptom profiles identified in 3,703 depressed patients
These results encouraged us to study bereavement on the level of symptoms
Introduction

5. Current research practices
Consequences:
Depression is studied as homogeneous, discrete diagnostic category ("genes for depression", "risk factors for depression")
Symptoms modeled as passive and interchangeable indicators
Reciprocal interactions among symptoms (emotion dynamics) are considered irrelevant
This contrasts with evidence:
1,030 unique depression symptom profiles identified in 3,703 depressed patients
MD symptoms differ in their risk factors, impact on impairment of functioning, and biological markers
These results encouraged us to study bereavement on the level of symptoms
Introduction

6. Current research practices
Consequences:
Depression is studied as homogeneous, discrete diagnostic category ("genes for depression", "risk factors for depression")
Symptoms modeled as passive and interchangeable indicators
Reciprocal interactions among symptoms (emotion dynamics) are considered irrelevant
This contrasts with evidence:
1,030 unique depression symptom profiles identified in 3,703 depressed patients
MD symptoms differ in their risk factors, impact on impairment of functioning, and biological markers
MD symptoms organized in dynamic networks of causal influences
These results encouraged us to study bereavement on the level of symptoms
Introduction

7. From Loss to Loneliness: The Relationship Between Bereavement and Depressive Symptoms
 Fried, E. I., Bockting, C., Arjadi, R., Borsboom, D., Tuerlinckx, F., Cramer, A., Epskamp, S., Amshoff, M., Carr, D., & Stroebe, M. (2015). From Loss to Loneliness: The Relationship Between Bereavement and Depressive Symptoms. Journal of Abnormal Psychology, 1–10. doi: /abn

8. From Loss to Loneliness
Research question
Does the stressful life event spousal loss affect all or only some depression symptoms? (Keller & Nesse 2005, 2006; Keller et al. 2007)
From Loss to Loneliness

9. From Loss to Loneliness
Research question
Does the stressful life event spousal loss affect all or only some depression symptoms? (Keller & Nesse 2005, 2006; Keller et al. 2007)
Can the effect be better explained by …
H1: the common cause framework, indirect effect of partner loss on depressive symptoms that goes through a latent variable s1 s2 D B s3 s4 s5
From Loss to Loneliness

10. From Loss to Loneliness
Research question
Does the stressful life event spousal loss affect all or only some depression symptoms? (Keller & Nesse 2005, 2006; Keller et al. 2007)
Can the effect be better explained by …
H2: a network, direct effect of loss on symptoms s2 B s1 s3 s4
From Loss to Loneliness

11. From Loss to Loneliness
Methods
Lives of Older Couples (CLOC) study
Baseline: married couples enrolled (60+ years)
Bereaved: N=241
Controls: N=274 (still-married)
CES-D11, dichotomized
Baseline
Death
Follow-up
… 6 months … t
From Loss to Loneliness

12. From Loss to Loneliness
Demographics
N=515
85.4% female
Mean age during enrollment: 73.3
Bereaved participants experienced spousal loss on average 31 months after enrollment
Most frequent causes of death:
heart attacks (29.5%)
cancer (25.3%)
arteriosclerosis and related conditions (12.4%)
strokes (8.7%)
From Loss to Loneliness

13. From Loss to Loneliness
Results
Lives of Older Couples (CLOC) study
Baseline: married couples, 65 years or older
Bereaved: N=241
Controls: N=274 (still-married)
Baseline: no differences between bereaved and control participants (age, sex, depressive symptoms)
Baseline
Death
Follow-up
… 31 months …
… 6 months … t
From Loss to Loneliness

14. From Loss to Loneliness
Results
Lives of Older Couples (CLOC) study
Baseline: married couples, 65 years or older
Bereaved: N=241
Controls: N=274 (still-married)
Baseline: no differences between bereaved and control participants (age, sex, depressive symptoms)
Death
Follow-up
… 31 months …
… 6 months … t
From Loss to Loneliness

15. From Loss to Loneliness
Results I
are specific symptoms increased in the context of bereavement?
From Loss to Loneliness

16. Results II: common cause model
Model fit:
²= 288.7, df = 54, p < .001 RMSEA = .09, CFI = .90
From Loss to Loneliness

17. Results II: alternative model
From Loss to Loneliness

18. Results II: alternative model
Model fit:
²= 171.4, df = 58, p < .001 RMSEA = .07, CFI = .95
Model comparison:
²diff = , dfdiff = 6, p < .001
From Loss to Loneliness

19. Results III: Network model
Ising Model (binary data)
"Partial correlations"
Conservative estimation of edges due to penalization (lasso based on EBIC)
Fruchterman-Reingold algorithm for visualization
The symptom network is cross-sectional, so we have to be careful with a causal interpretation; however, the main finding can likeyl be interpreted causally: loss triggers loneliness, and not the other way around; from there, sypmtom activatoin spreads through the NW.
From Loss to Loneliness

20. Results III: Network model
Ising Model (binary data)
"Partial correlations"
Conservative estimation of edges due to penalization (lasso based on EBIC)
Fruchterman-Reingold algorithm for visualization
From Loss to Loneliness

21. From Loss to Loneliness
Conclusion
Bereavement differentially impacts on depression symptoms; common cause explanation problematic
In line with other research documenting "situation-symptom-congruence"
Sum-scores obfuscate important (dynamic) insights
Loneliness as a gateway symptom; implications for intervention and prevention
DSM-3 and DSM-4 bereavement exclusion criterion
From Loss to Loneliness

22. Thank you