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
Prospective Study of Role of Positive Emotion in Crisis - Fredrickson, Tugade, Waugh, & Larkin 2003
133 participants surveyed prior to 9/11 terrorist attacks, 47 participants completed follow-up survey 2 weeks later
Significant positive relation between positive emotions and resilience
Negative relation between positive emotions and depression
Direct relation between resilience and depression but not significant when added positive emotions to model
Didn’t find relation when used positive emotions instead of negative emotions or when switched emotions with resilience - Suggest causal relationship: resilience – positive emotions
Use of positive emotion accounts for link between resilience and increase in psychological resources e.g. optimism, tranquility
Why do positive emotions in times of crisis promote resilience? - Tugade & Fredrickson 2004
Negative emotions narrow attention and thought-action repertoires – select from a few strategies, helpful in fear arousing scenarios
Positive emotions broaden attention and repertoire of actions – widening problem-solving strategies
Study 1: Do resilient people show faster cardiovascular recovery from a stressful experience?
57 UG participants - measured trait resilience
Negative mood induction - prepare speech to be recorded
Measured emotions felt during task, cognitive appraisals and cardiovascular activity
Resilient participants were less threatened by task, showed quicker recovery through use of positive emtions and cognitive appraisals
Positivity ratio - Fredrickson & Losada 2005
3 to 1 positive to negative emotions facilitate human flourishing
Brown, Sokal, & Friedman 2013
Called into question positivity ratio
No theoretical or empirical basis to support the application of equations from fluid dynamics to human emotions
Demonstrated mathematical errors in application of equations
Led to partial retraction of Fredrickson and Losada 2005 paper
Extraversion and resilience
High E - feel positively about selves, feel confident, enjoy social gatherings - experience positive feelings of enthusiasm and energy
Neuroticism and resilience
Experience fear of physical dangers, anxiety in response to life stresses
Campbell-Stills et al. 2006
Trait resilience positively correlated with E and C and negatively correlated with N
Sarubin et al. 2015
High E and low N explain relationship between positive experiences and resilience
Problems with Campbell-Stills et al. 2006 and Sarubin et al. 2006
Correlational design not longitudinal
Measure resilience aas a trait - some argue can’t define resilience this way
Cognitive reappraisal and resilience
Individual differences in the use of cognitive reappraisal linked to resilience
Cognitive reappraisal = emotional regulation strategy where a person reinterprets the situation to change the meaning and emotional impact of the event
Can be used to down regulate negative emotion triggered by stressful events
Zahniser and Conley 2018
Longitudinal study - 1000 new uni students 3 surveys (T1=before, T2=2 weeks in, T3=end of year 1) Resilience – inferred as fewer internalising symptoms e.g. anxiety/depression Students whose perceptions of stress increased from T1 to T3 reported fewer internalising symptoms when they were frequent reappraisers More able to cognitively reappraise and down-regulate negative emotions – experience fewer symptoms of depression/anxiety
Flexibility in resilience
Alternative definition of resilience is about flexibly adapting to changing demands
Resilience requires effective regulation of negative emotions triggered by a stressful event
Key to resilience is use of context sensitive coping mechanisms - flexibly adapt coping mechanisms
Coifman & Bonanno 2010 - Does ability to shift emotional responses depending on contextual demands predict greater adjustment after bereavement?
48 participants, spousal or parental loss
T1: 4 months after - clinical interview assessing depression and narrative interview assessing emotional expression for other events and relationship with deceased
T2: 18 months after - clinical interview
Significant findings only for those high in depression at T1
Benefits to showing context relevant emotions - negative emotions at T1 led to lower depression at T2
Positive emotional expression beneficial in all contexts
Participants able to shift emotions to match context experiences lower depression at T2 - were more positive when talking about positive events
Model of Regulatory Flexibility - Bonanno & Burton 2013
Theory
No categorically good or bad coping strategies
Effective coping strategies = fit between the coping strategy and ongoing situation
Effective coping is characterised by ‘flexible responding to situational demands’ - Individual differences in how effectively people can do this
Individual differences in monitoring of success of coping strategy and how able we are to change unsuccessful strategies
Model of Regulatory Flexibility - Bonanno & Burton 2013
Model
Stressor
Evaluate demands and opportunities - context sensitivity
Select regulatory strategy - repertoire
Monitor and modify as needed - feedback
