Resilience & Adversity Flashcards
How does Bonanno (2004) define resilience?
An outcome pattern characterised by a stable trajectory of healthy functioning after adversity
Use longitudinal studies for research
Who defines resilience as ‘the ability to bounce back and flexibly adapt to changing demands to negative life situations’?
Tugade and Fredrickson 2004
Trait approach, questionnaires
How can resilience be measured?
Depression
Subjective life well-being
What are the four patterns following a traumatic event?
Recovery – high levels of distress after event which gradually drops off
Resilience – mild levels of distress after event which stays mostly stable – never becomes clinically severe
Delayed – high levels of distress not until a significant time (1 year) after event
Chronic – clinical/high levels of distress straight after event which are maintained after time
What are resilience questionnaires?
Measured like a trait
Questions about how you generally react to stressors
Resilience trajectories
Measured after event for several years
Defined as outcome pattern unfolding over time
How was resilience historically viewed?
Rare ccourrence
‘Viewed absent grief as rare and a pathological reaction’ - Bonanno 2004
Research contradicts this assumption
Bonanno, Wortman, et al. 2002
Bereavement study
205 participants from existing longitudinal study
Depression measured pre-loss, 6 months after and 18 months after
46% resilient - movement no more than 1 S.D.
11% common grief
15% chronic grief
No significant differences in attachment or satisfaction pre-loss to explain resilience patterns
How resilient are people after spousal loss or divorce? - Mancini, Bonanno, & Clark 2011
Methods
16,795 participants from German Socioeconomic Panel Study (GSEOP) from 1984-2003
Face to face interviews each year
Used new stats technique - Latent Growth Mixture Modelling (LGMM)
- Identifies sub-populations in the data
- Allows examination of different outcome trajectories for each sub-group
- Exploratory and data-driven technique
Prevalence of resilience: Spousal loss - Mancini, Bonanno, & Clark 2011
Study using GSEOP data - 464 people experienced spousal loss
Subjective well-being used as outcome measure - level of life satisfaction
LGMM revealed 4 class solution as best fit of data:
- Resilient – most dominant (slight dip but mostly stable) – 59%
- Acute Recovery – dip in well-being which then increases over time – 21%
- Improved – well-being increases before loss and then drops off after – 5% - don’t know circumstances behind loss
- Chronic – low well-being before and after – 15% - outcome pattern stable but not considered resilient because not high well-being
Prevalence of resilience: Divorce - Mancini, Bonanno, & Clark 2011
629 experienced divorce from GSEOP data
Subjective well-being used as outcome measure
LGMM revealed a 3 class solution was best fit
Resilient – 72%
Moderate-decreasing – 19%
Low-increasing – 9%
Prevalence of Resilience: Lifetime Adversity - Seery 2011
National survey - 2000 people
Longitudinal, multiple assessments over 2 years:
- Cumulative lifetime adversity
- Global distress
- Functional impairment
- Life satisfaction
- PTSD
Data best fits quadratic model
Best functioning and highest life satisfaction with some level of adversity
Some adversity needed to develop skills for resilience
Is resilience the common trajectory? - Infurna & Luthar 2016
Replication of resilience research
Re-examined outcome trajectories with LGMM after spousal loss divorce and unemployment from GSEOP data
Life satisfaction used as outcome measure
For each event, ran three different statistical models
1. Same model specifications as in prior studies (Bonanno – people within sub-group are allowed to differ from each other)
2. Variance of outcome trajectories were allowed to differ within subgroups (those who are resilient are going to be fairly similar to average)
3. Means and variances of outcome trajectories allowed to differ between subgroups and within each subgroup
When statistical constraints are loosed, resilient % drastically decreases
Due to data manipulaton - no a priori hypotheses
What is the significance of resilience/adversity research?
Will all suffer traumatic/upsetting events
Strategid decisions have to be made regarding allocation of health care resources
Research used to inform policy makers
Mechanisms promoting resilience - Bauer & Bonanno 2001
69 participants suffered spousal loss
Structured clinical interviews with psychologist to measure grief at 6, 14 and 25 months after loss
Optimal ratio of positive:negative self-evaluations (5:1) associated with lower grief over time
Greater focus on ‘doing’ self-evaluations associated with lower grief over time
Linking’ doing’ and ‘being’ evaluations together - lower grief over time