resilience to adversity Flashcards
1
Q
what is adversity?
A
- Clinical trauma vs sever stressors/adversity
- Traumatic events (DSM5) ‘exposure to actual or threatened death, serious injury or sexual violence’
- -ve & severely stressful major life events that disrupt & impact quality of life e.g. divorce, job loss
- Resilience research has examined a wide diversity of severely stressful events
2
Q
what is resilience
A
- Multiple definitions: all involve a +ve response/adaptation to -ve circumstances
- An outcome pattern characterised by a stable trajectory of healthy functioning after adversity (Bonanno, 2004)
- Ability to ‘bounce back’ & flexibly adapt to changing demands of -ve life situations (Tugade & Fredrickson, 2004)
how you define matters - how you measure it
3
Q
how is resilience measured?
A
- resilience questionnaires
- resilience trajectory
4
Q
resilience questionnaires
A
- measured like a trait
- questions about how you generally react to stressors
5
Q
resilience trajectory
A
- measured after event
- identifies ppl that show a resilient outcome pattern over time
6
Q
reactions to adversity
A
- resilience - never leave mild symptom range (stability)
- recovery - moderate/severe reactions which decreases over time
- delayed - symptoms increase over time
- chronic - stays in severe category
other ppl would say resilience is the ability to bounce back
7
Q
resilience as a new concept
A
- historically viewed as a rare occurence = absent grief
- Bonanno (2004) - bereavement theorists viewed absent grief as a rare & pathological reaction
- BUT research contradicts this assumption
8
Q
bonanno et al. (2002)
resilience prevalence in bereavement
A
- prospective study on spousal loss
- outcome pattern: resilience, common grief, chronic grief
- prevalence: resilient –> common grief –> chronic grief
- no ev of marriage difficulties
- resilient ppl still affected by bereavement: yearning, emotional upset, intrusive thoughts, disturbances in sleep but not at a level impacting too much
9
Q
latent growth micture modelling
LGMM
A
- identifies sub-populations in data
- allows examination of diff outcome trajectories for each sub-group
10
Q
prevalence in spousal loss
A
- subjective well-being as outcome measure (instead of resilience)
- LGMM showed 4-class solution best fit to data
- resilient group - small dip but stay high functioning
- acute recovery group - decrease before loss but increase towards original level
- chronic low group - low functioning, dips and stays low
- improved group - increase at loss and then decreases towards original level
11
Q
prevalence in divorce
LGMM
A
- SWB used
- 3-class solution best fit to data
- resilient - stay high functioning whole time
- moderate increasing - decrease towards divorce & increasing 2-4yrs after divorce
- low increasing - moderate functioning rapidly increasing after divorce
12
Q
is resilience the common trajectory?
norris et al. (2009)
A
- 9/11 and floods in mexico
- PTSD symptoms measured post-disaster
- resilience = adaptability
- resistance = stability
- no diffs in resistance & stability in mexico
- diffs in resistance & stability in US
13
Q
how common is resilience?
infurna & luthar (2016)
A
- LGMM using SEOP data
- 3 models: (A) same as prior studies, (B) variance but show same patterns, (C) ‘bouncing back’ but at diff times
- spousal loss: A resilient most prevalent, B recovery most prevalent, C equal split between resilience & recovery
- divorce: A resilient most prevalent, dropped when model specifications changed (B&C)
14
Q
resilience in longitudinal studies
A
- Operationalisation of resilience is often data-driven in longitudinal designs
- Resilience is not measured directly, but inferred from an adaptive response over time
- Resilience = absence of depression symptoms, reduction in PTSD symptoms, stable pattern of subjective well-being
15
Q
defining resilience: systematic review
cosco et al. (2017)
A
- inclusion criteria: longitudinal data, operationalised & measured resilience, published peer-reviewed research
- measured in 3 ways: psychometric questionnaires, definition-driven methods, data-driven methods
- Most studies defined resilience as the absence of distress/impairment, not maintenance of well-being
- Although stats inform how trajectories are identified, researchers still have to interpret & label the trajectories
- Data driven methods for trajectory identification are based on the characteristics of the sample & may not generalise to other samples