key: cord-0026103-ely1oeun
authors: nan
title: Top Ranked Abstracts from the 2021 Annual Meeting of the Society for Affective Science
date: 2022-01-21
journal: Affect Sci
DOI: 10.1007/s42761-021-00066-6
sha: 519d394f7fe7e1b64df46c5d65634d34e57ff905
doc_id: 26103
cord_uid: ely1oeun

nan

Introduction According to Panksepp's 1978 'hijacking' theory, opiates are so addictive because they fulfil certain biological aspects of acute social needs in the absence of social interactions 3 . Despite converging evidence, e.g that social stressors and poor social support networks increase risk of addiction and relapse in healthy humans 4 , this hypothesis has never been tested in humans. At its core lies the assumption that social support provides stress and discomfort relief through endogenous opioid mechanisms.

Aims Using pharmacological opioid blockade in healthy participants, we will test whether intact opioid signaling is necessary to obtain stress relief from interacting with a friend, as measured by self-reported positive and negative affect, heart rate and cortisol.

Methods This study will recruit 140 pairs of reallife friends and expose them to acute social stress using a novel dyadic version of the Trier Social Stress Task (dTSST) where the pair takes it in turn to perform the task in front of the same panel. Within earshot but out of sight of each other, they are able to witness each other's performance and feedback. In a randomized, double-blind, placebo-controlled study, participant pairs will receive pre-treatment with 50mg of the general opioid antagonist naltrexone or placebo. After the dTSST, half of the pairs in each drug condition will be given 5 minutes to interact freely with their friend (social support condition). The remaining pairs will be kept apart and interact with an experimenter (control condition). Outcome measures are subjective state ratings (VAS scale 0-100), heart rate and salivary cortisol collected throughout the session.

To establish the validity of the dTSST, we tested 21 pairs in a non-pharmacological pilot study. Compared to baseline, dTSST affected both negative (mean change = 21.5, SE=4.37, F1, 80=24.19, p<.001 ) and positive mood (mean change SE=4.08, F1, 80 =16.82, p<.001) . After stress induction, social support (11 pairs) improved recovery of positive mood compared to control interaction (t(40)=-4.2, p<.001) to levels somewhat higher than baseline. While both groups showed reduced negative mood after the social interaction, this recovery was more pronounced after social support SE=4.79, t(40) =1.76, p=.086) . 

Predicted Results We predict that interaction with a friend (compared to control) will yield stress relief, operationalised as recovery to pre-stress mood under placebo, and that opioid blockade will interfere with this support-induced stress relief. While the opioid blockade is not expected to interfere with subjective stress recovery in the control condition 5 , we predict higher salivary cortisol responses to stress with naltrexone in both support conditions 6 . Impact This study enables us to pinpoint the role of endogenous opioid signalling for a key aspect of human sociality, namely the ability to draw on one's social resources to recover after a setback. The use of a dyadic TSST with pairs who are close friends ensures ecological validity whilst maintaining a high degree of experimental rigour.

The prefrontal cortex (PFC) gates the relationship of affective states and bodily sensations (Damasio, 1996) . This is especially relevant during exercise; one framework suggests that interoceptive and cognitive factors interact to determine the influence of exercise on affect (Ekkekakis 2013). Additionally, affective valence responses to exercise have been shown to be associated with PFC hemodynamics (Tempest, Eston, and Parfitt, 2014) . However, few studies have used a multimodal approach to investigate how different bodily responses to exercise work together to influence affect profiles, and no research has examined the role that physical fitness plays in this complex interaction.

Our objective with the present proposal is twofold:

First, we seek to characterize the relationship between a collection of psychophysiological measures (subjective ratings, PFC and muscle hemodynamics, and heart and breathing rates) to exercise at a maximum intensity. Second, we aim to test if these associations change based on individual differences in physical fitness (VO2max).

Methods Participants will complete a VO2 max test on a cycle ergometer, preceded by a baseline period and followed immediately by 20 minutes of rest. The entire time, we will record individuals' heart rate (HR), heart rate variability (HRV), respiration rate (RR), and PFC hemodynamic responses (HbO2, Hbb) and muscle oxygenation (MO2) using near infrared spectroscopy (NIRS). Rate of perceived exertion (RPE) and responses on the feeling scale (FS) and felt arousal scale (FAS) will be recorded every minute during and after exercise.

We will use a principal component analysis to extract meaningful shared variance across the three experimental phases of baseline, exercise, and recovery among our 9 measures (FS, FAS, RPE, HR, HRV, RR, HbO2, Hbb, MO2). Using subject to item ratio (5:1) for 9 variables and 3 time points, sample size estimate would be : 27*5 = 135 subjects (Osborne and Costello 2019) . A correlation analysis will then be used to determine the relationship between the weights of the primary components and fitness levels (VO2 max). We predict that affective responses will mirror physiological responses during exercise, and that these measures will be similarly synchronized during the recovery period. Finally, we expect to find the strongest associations among individuals with lower fitness.

The outcome of this proposed work will reveal the measures that are most sensitive to psychophysiological changes surrounding exercise. The results will also help to determine the role of fitness in this interaction.

Introduction Animal work has demonstrated that the presence of offspring changes defensive behavior in female progenitors. For instance, rat dams conditioned to fear an odor will freeze to its presentation when they are alone, but will actively tackle the threat if the pups are present (Rickenbacher et al., 2017) . This suggests that a shift from passive to active avoidance is necessary to allow protection of the pups. Furthermore, it was demonstrated that only pups whose mothers displayed active avoidance learned to freeze to the odor. Interestingly, recent work in humans has also suggested a positive link between high parental anxiety and threat learning in children (Silvers et al., 2020) . Aims Our aims are: 1. To determine how defensive behavior in human parents is modulated by the presence of their children. The working hypothesis is that the presence (vs. absence) of children will promote active relative to passive avoidance strategies in parents; and, 2. To determine whether the type of defensive response predominantly displayed by parents impacts threat learning in children. The working hypothesis is that children whose parents show higher frequency of active avoidance responses will display faster aversive learning rates.

We will use a novel Virtual Reality (VR) paradigm to assess defensive behaviors in parents alone and in presence of their children. Our sample will be 60 dyads of parents and adolescent children (aged 13-17). In VR, participants (parents) will perform a task wherein they will try to avoid a virtual attacker capable of inflicting aversive electrical shocks (Fig.1) . The attack will occur in different stages (pre-encounter, postencounter and circa-strike), to prompt imminencebased defensive behaviors (Fanselow & Lester, 1988) . Participants can decrease the probability of a shock by walking towards the attacker and performing an effortful motor action on a hand-held controller. Passive avoidance (i.e., not moving towards or engaging the at-tacker) will result in a fixed probability of shock. Participants will perform the task by themselves (phase 1), in the presence of an unrelated child from another dyad (phase 2A), or in the presence of their own child (phase 2B). Analysis plan Behavioral measures collected from parents will be: time to initiate active avoidance responses (moving towards attacker and button presses), number/speed of button presses, and time spent in the starting quadrant (i.e., passive avoidance). In addition, we will collect physiological measures (SCR and HR). We will use multilevel modelling to model our behavioral measures as a function of the phase of the experiment (1, 2A and 2B), with random effects by subject. We will also analyze SCR from children. Differential SCR to auditory cues that signal safe or shock attacks will index threat learning, and number of trials until a differential response is observed will index learning rate. We will model these measures as a function of defensive behavior displayed by parents and unrelated adults, allowing us to examine which parental defensive responses predict better learning rates in children, and whether there is an interaction between defensive response and kinship.

Conclusions This study will produce translational knowledge about the interdependence between defense and parental care in human and nonhuman animals. Also, it will foster our understanding of parentchild dynamics in the expression and learning of defensive behavior.

Family stress theory states that non-normative stressors can disrupt the equilibrium in family systems (Hill, 1949) . Specifically, external stressors can impact parent-child interaction quality through proximal mechanisms, such as parents' emotions (Crandall, Deater-Deckard, & Riley, 2015) . The COVID-19 pandemic created a unique set of stressors for most families across the globe-ranging from financial strain, lifestyle changes, and health concerns-and their impact on parent-child interactions is not well understood.

This study aims to understand the extent to which COVID-19-related stressors predict parents' interactions with their children across three months when much of the world had issued stay-at-home or shelterin-place orders, and whether parental negative and positive emotions mediate these associations. We hypothesize that experiencing more COVID-19-related stressors (e.g., financial strain, worries about health) will predict less positive and more negative parentchild interactions longitudinally, via increases in parents' negative emotions and decreases in parents' positive emotions. The study hypotheses are pre-registered.

Shortly after COVID-19 was declared an international pandemic (March 11 th , 2020), eligible participants completed online surveys bi-weekly over the course of three months. A subsample of parents with children living at home (n = 287) was selected for this study. At each wave, parents rated the extent to which they experienced (a) perceived threat from the pandemic, (b) worries about theirs' and others' health, (c) financial strain, and (d) inadequate personal space. Parents also rated negative and positive emotions and the extent to which they engaged in positive (e.g., praised their children) or negative (e.g., yelled at their children) interactions with their children. Data collection is complete, and the data are yet to be analyzed.

Random intercept cross-lagged panel models will be used to segregate stable, between-person differences and within-person fluctuations at each wave in the constructs of interest. Autoregressive paths (i.e., stability of all constructs from one wave to the next) will be estimated, along with lagged paths (e.g., COVID-19 stressors at Wave 1 predicting parental emotions at Wave 2; parental emotions at Wave 2 predicting parent-child interaction at Wave 3) for all six waves. Indirect effects will be estimated to examine the mediating effects of parental emotions. Each set of predictors, mediators, and outcomes will be examined in separate models.

Findings from this study will advance our theoretical understanding of how pandemic-specific stressors impact family functioning. Findings can also inform interventions by identifying parents' emotions as a key mechanism to target to strengthen parent-child interactions in the context of stress. Further, we will be able to speak to the generalizability of effects beyond White, educated, industralized, rich, and democratic samples by using a global and diverse sample.

Introduction Age stereotypes (e.g., to be old is to be sick) often translate into negative attitudes toward older adults (Courtney et al., 2000) , leading to suboptimal treatments and inappropriate medical recommendations (Ory et al., 2003) . However, the mechanisms supporting age-based biases in pain assessment and treatment remain unclear to date. Previous studies in the context of gender and racial stereotypes found that stereotypes affect pain perception and perceptual processing (Mende-Siedlecki et al., 2019; Schwarz et al., 2019) , suggesting that age expectations can also bias pain perception.

Aims We plan to characterize whether pain perception in benign medical scenarios are exacerbated in relation to older compared to a younger adults. Furthermore, we will approximate ecological settings by exploring confirmation and violation of perceived age expectations across different medical scenarios. Our findings can help elucidate biases underlying the medical mistreatment of diverse populations.

Methods One-hundred-sixty-nine US citizens successfully completed our pilot study. In each trial, participants saw a brief description portraying a person visiting the doctor and complaining of non-diagnostic pains in one of several places, followed by the face of an old or a young person (obtained from Bainbridge et al., 2013) . Participants rated their subjective assessment of diagnosis severity for that patient (on a scale of 0-20) and how much pain they assess the patient is experiencing (on a scale of 1-7). In our planned study we will control the perceived age of the faces by generating digital age-adapted morphs. We will further vary the described scenario severity. To examine how expectations affect the assessments, the portrayed descriptions will hint at the age of the patient. Trial-specific images will either violate or confirm the expected age. Eighty participants will rate their diagnosis assessments on scales corresponding to those used in the pilot study (sample size calculated using PANGEA v.02 to obtain 0.8 power to detect an effect size of Cohen's d = 0.2 for the interaction between expectation and age).

Predicted Results Pilot data were analyzed using R 4.0.3. Using mixed models with participants as random intercepts, participants provided higher ratings for older compared to younger adults on both the pain ratings (ƅ=.01 p<.001) and the severity assessments (ƅ=.02 p<.001; see figure 1 ). In our planned study, we predict an interaction between the perceived age and the expectations outcome (confirm/violate). Specifically, we expect that, for older targets, confirmation will lead to a more adverse diagnosis, whereas rejection will attenuate it. The pain and severity assessment are expected to vary by the severity of the scenarios. 

The share of older adults in the population is rising at an increasing rate. Here we plan to identify how perceived age and pain expectations bias the processes involved in medical decisions. By understanding the roots of the phenomenon, we can begin to conceptualize effective interventions to successfully influence the detrimental effects of ageism in field settings.

Introduction Classical neurocircuitry models of posttraumatic stress disorder (PTSD) emphasize alterations in activity of the limbic regions, including the hippocampus and the amygdala, and the medial prefrontal cortex as significant contributors to the clinical presentation of PTSD (Ross & Cisler 2020) . However, a growing body of evidence suggests that neural deficits in PTSD are likely more complex than region-specific dysfunction. Instead, an emerging literature posits that PTSD may be associated with dysfunction in large-scale neural networks rather than simply individual regions or bivariate circuits. The application of network neuroscience to investigations of neural dysfunction in PTSD thus far is promising, yet is impeded by limitations in network community detection such as the resolution of the size of networks that can be defined. A new community detection approach relying on a quality function termed Asymptotical Surprise (Traag et al. 2015) and the Partitioning Cost Optimization (PACO) algorithm (Nicolini, Bordier & Bifone 2016) provides a promising framework for resolution-limit-free community detection that has yet to be applied to investigations of PTSD.

The primary aim of this investigation is to define resting-state neural network dysfunction and alterations of sub-network topological organization in a large sample of adult women with PTSD. Ultimately, the goal of this project is to produce strong tests of hypotheses pertaining to network specialization in PTSD using robust, reliable, and resolution-limit-free community detection.

without PTSD underwent a full psychological assessment and a 7.5-minute resting state scan at two different sites. PTSD participants were included based on interpersonal violence exposure and current diagnosis of PTSD; control participants were included based on absence of trauma history and current mental health disorders. During the resting-state scan, participants were instructed to fixate on the cross on the screen while remaining awake and allowing their minds to wander naturally. Image preprocessing followed standard steps.

atlas will be used to define individual and group-level modular brain organization. For each participant, we will calculate the mean timecourse of voxels within each ROI, excluding voxels within ROIs that were outside of the brain for a given individual, resulting in connectivity matrix for each participant. These matrices will be concatenated across participants, correlated, and r-to-z transformed, and all diagonals and negative values will be set to zero within the matrix. Global modular brain organization in each group will be assessed through the use of the community detection quality function Asymptotical Surprise through the PACO algorithm (Traag et al. 2015 , Nicolini, Bordier, & Bifone 2016 . Linear regression models will be used to examine the relationships between modular brain organization (i.e. within-module strength and global participation coefficient), group membership (PTSD or control), and trauma and symptom measures, controlling for participant age, scanner site, and head motion.

Conclusions Upon completion of these analyses, we aim to contribute a new, neurophysiologically plausible and highly predictive, model of functional connectivity alterations that characterize PTSD. We expect that this new model will provide enhanced explanatory power as a biomarker for functional neuroimaging differences in trauma-related psychiatric disorders. Summary In aversive contexts, anxiety has previously been associated with an increased probability of fear relapse. It remains unclear whether this is due to faster learning or context-specific learning. We investigated whether high trait anxious (TA) individuals learn gradually or switch between multiple environmental states (i.e. contexts) in a probabilistic aversive learning task. Across three experiments, participants' behaviour indicated a positive relationship between switch steepness and TA. We followed this behavioural finding by developing a novel state inference model which fit the data of high TA individuals better than gradual learning models (Rescorla-Wagner, Pearce-Hall). These results provide behavioural and computational evidence that high TA individuals have a tendency to represent the environment as multiple states which serves as novel explanation for higher relapse rates in anxiety. Keywords · trait anxiety · state inference · extinction · reinforcement learning · computational modelling Ondrej Zika: zika@mpib-berlin.mpg.de Introduction Predicting the likelihood of outcomes in changing environments can be achieved by two strategies: 1) Gradually updating one's beliefs or 2) identifying latent states and switching between them. While discovering latent states of an environment is often beneficial, Gershman et al. (2013) showed that this can hinder necessary unlearning, and that so called gradual extinction can prevent the return of fear. In line with this, we previously observed that high TA individuals are better at approximating the true shock contingencies after reversal, especially in extinction (Zika, Bogacz, & Wiech, 2019) .

In this study we test whether TA is associated with a higher propensity to represent multiple states during learning.

Methods Data were pooled from three studies that used the same probabilistic learning task (study 1: n=27; study 2: n=17, study 3: n=33; total n=77). In the task, participants were presented with one cue per trial and had to estimate the probability of receiving a shock given the shown cue. Unbeknown to the participants, the true probability of shock changed between 25% and 75% every 20 -35 trials. In study 3, two additional conditions were included in which contingencies changed between 40% and 60%, and 10% and 90%. Based on participants' ratings, we calculated the steepness of each switch. To capture whether participants mentally inferred separate states (e.g. high vs low shock probability states), we developed a new computational model. Our model formalizes the expectation of shock as a beta distribution. Importantly, it has the ability to create a new state if evidence violates the current state or to switch to an existing non-current state. The model was validated using parameter and model recovery procedures. 

We provide behavioural and computational evidence suggesting that high trait anxious individuals have a propensity to represent aversive environment as multiple states rather than learn gradually. While improved state inference minimizes experienced irreducible (risk) uncertainty, it also increases the chance of fear relapse. Our finding therefore provides new potential explanation for higher relapse rates in high trait anxiety.

Introduction Similar to previous global outbreaks, the COVID-19 pandemic has been shown to predict psychological stress, depression, and anxiety in addition to substantial morbidity and mortality (Rajkumar, 2020) . It is crucial to identify which emotion regulation strategies are most effective in reducing the psychological impact of stressors related to COVID-19. Emotion regulation can be implemented via one or more strategies involving situation selection, situation modification, attention redeployment, cognitive change (e.g., cognitive reappraisal), or response modulation (Gross, 1998) . Prior work has shown that cognitive reappraisal is highly adaptive and associated with reduced negative affect as well as enhanced physical and psychological health compared to other strategies (John & Gross, 2004) . Two tactics of reappraisal are psychological distancing (e.g., appraising a situation objectively and impartially) and reinterpretation (e.g., imagining a better outcome for a situation) (Denny & Ochsner, 2014) . In contrast to reinterpretation training, distancing training has shown to predict reduced perceived stress over time (Denny & Ochsner, 2014) . Thus, psychological distancing is a promising emotion regulation strategy to probe in the context of stress related to COVID-19.

Aims The purpose of our study was to examine associations between the frequency of using particular emotion regulation strategies and stress related to COVID-19. Additionally, we were interested to model trait-level individual differences in emotion dysregulation as well as person-level factors. We predicted that engagement of psychological distancing would be associated with lower pandemic-related stress, whereas other emotion regulation strategies were expected to be either unrelated or positively related to pandemic-related stress.

We conducted an online study via a webbased recruitment platform (i.e., Prolific) designed to recruit nationally-representative survey samples. Of the 298 original participants, one was excluded due to missing data (total N = 297). We collected demographic information, perceived socioeconomic status (SES), and trait-related emotion dysregulation via the DERS-SF. We used robust regression using M-M estimation via lmrob in R. In our a priori model, predictors were the extent of engagement of emotion regulation strategies derived from the Gross process model of emotion regulation (Gross, 1998) , and covariates were age, gender, community SES, race/ethnicity, and traitrelated emotion dysregulation. The dependent variable was overall perceived stress related to COVID-19.

In our a priori regression model (R 2 = .25;

Adjusted R 2 = .22), greater use of psychological distancing was unique among all emotion regulation strategies, and unique among all regression variables overall, in predicting lower overall COVID-19-related stress (β = -.14, p = 0.04, 95% CI [-0.28, 0.00]). Motivated by these results, we examined an additional multiple regression model incorporating the original regressors as well as separate interaction terms between distancing usage and each covariate (i.e., age, gender, SES, race/ethnicity, and trait-related emotion dysregulation) in predicting overall COVID-19-related stress. No interactions between distancing usage and any of the covariates above were significant (all p > 0.26).

These results suggest the broad applicability and utility of psychological distancing during the COVID-19 pandemic as part of an adaptive emotion regulation toolkit and motivate the investigation of interventions involving distancing in this context.

Correlation analysis revealed that perceptions of PTG were negatively correlated to defeat and suicide ideation with medium effect sizes while it was correlated with entrapment, anxiety and depression with small effect sizes. Using Hayes' PROCESS macro for SPSS, two separate moderation analyses were performed to test the moderating effects of PTG. PTG had a significant direct effect on suicidal ideation; however, it did not moderate either defeat-entrapment (above part of the Table 1 ) or entrapment-suicidal ideation relationship (below part of the Table 1 ). 

in the pathogenesis of many medical and psychiatric conditions, and inflammatory dysfunction in epithelial tissue (e.g., skin, gut) may play a causal role in systemic inflammation (Scrivo, et al., 2011; Uluçkan, et al., 2017) . Emerging evidence suggests activation of positive valence systems (e.g., reward response) may regulate inflammation; however, little is known about these processes within the epithelium.

Aims To investigate the role of different positive valence domains in regulating inflammation in the epithelium, the current study used self-report and behavioral measures of reward responsivity as predictors of erythema (inflammation in the skin). To induce and measure individual differences in erythema, we used a recently developed method, PI-MED testing (Richey, et al., 2019) . We hypothesized that both self-report and behavioral reward responsivity would predict residualized change in erythema response.

Methods Participants (n = 43) were drawn from a larger study of stressed adults. Erythema was measured at two timepoints (baseline and ~9 weeks later), and self-report and behavioral reward responsivity measures were collected at three timepoints within the same period. Precision Implementation of Minimal Erythema Dose (PI-MED) testing (Richey, et al., 2019) was used to induce erythema, via exposure to a UV-light, and to measure individual differences in erythema response. The Snaith-Hamilton Pleasure Scale (SHAPS; Snaith, et al., 1995) was used as a measure of self-reported reward responsivity. Reward responsivity was also measured behaviorally using a signal detection task (Pizzagalli, et al., 2005) , with reward measures derived from signal detection theory (response bias) and from computational modelling (reward sensitivity and learning rate). Slopes and intercepts were computed across the three timepoints for all reward responsivity measures and were entered into hierarchical regressions as predictors of erythema response at time 2, controlling for baseline erythema.

Hierarchical regressions demonstrated that only the slope of SHAPS anhedonia (but not behavioral predictors) significantly predicted erythema response at time 2, controlling for baseline erythema response. Baseline erythema response was a positive predictor (pr=.71, p<.001) of erythema response ~9 weeks later. Further, increasing self-report SHAPS anhedonia across the study period was also a positive predictor (pr=.33, p=.04) of erythema response at time 2 (controlling for baseline erythema), and explained almost half as much variance in the time 2 erythema response as did the baseline erythema measure. Conclusions As the present results suggest that reward responsivity may regulate erythema, future work might explore reward response as a potential intervention target for attenuating inflammatory response in skin, which is known to precipitate broader inflammatory dysfunction.

The Somatic Marker Hypothesis and the Possible Functions of the Prefrontal Cortex

Sample Size and Subject to Item Ratio in Principal Components Analysis

A functional behavioristic approach to aversively motivated behavior: Predatory imminence as a determinant of the topography of defensive behavior

Freezing suppression by oxytocin in central amygdala allows alternate defensive behaviours and mother-pup interactions. ELife, 6, e24080

An exploration of amygdala-prefrontal mechanisms in the intergenerational transmission of learned fear

Maternal emotion and cognitive control capacities and parenting: A conceptual framework

Families under stress: Adjustment to the crisis of war separation and reunion

Acute care nurses' attitudes toward older patients: A literature review

Perceptual contributions to racial bias in pain recognition

Challenging Aging Stereotypes Strategies for Creating a More Active Society

How Stereotypes Affect Pain

Altered large-scale functional brain organization in posttraumatic stress disorder: A comprehensive review of univariate and network-level neurocircuitry models of PTSD

Detecting communities using asymptotical surprise

Community detection in weighted brain connectivity networks beyond the resolution limit

Computational and neural mechanisms of human aversive learning

Antecedent-and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology

Healthy and Unhealthy Emotion Regulation: Personality Processes, Individual Differences, and Life Span Development

PTG (PTG Inventory -SF), depression and anxiety (Hospital Depression and Anxiety Scale) measures. There was no inclusion criterion based on the presence of current suicidal thoughts in order to capture the dynamics of proposed relationships in a broader community sample

Post-traumatic growth as protection against suicidal ideation after deployment and combat exposure. Military medicine

Toward an objective characterization of an anhedonic phenotype: A signal-detection approach

Precision implementation of minimal erythema dose (MED) testing to assess individual variation in human inflammatory response

Inflammation as "common soil" of the multifactorial diseases

A scale for the assessment of hedonic tone the Snaith-Hamilton Pleasure Scale

Chronic systemic inflammation originating from epithelial tissues

We would like to thank the study participants and research assistants who assisted with data collection.

We would like to thank Charlotte Hirsch for assistance with data collection and Fred Oswald for consultation regarding data analysis.

Meryem Betul Yasdiman * , Ellen Townsend * , and Laura Blackie School of Psychology, University of Nottingham * Self-harm Research Group Summary The current study explored the interaction between post-traumatic growth (PTG) and key risk factors for developing suicidal thoughts (e.g., defeat, entrapment) according to the Integrated Motivational-Volitional Model of Suicidal Behaviour (O'Connor & Kirtley, 2018) . Contrary to our expectations, we did not uncover a moderating effect of perceived PTG on the relationships between 1) defeat and entrapment and 2) entrapment and suicidal ideation.Keywords · post-traumatic growth · Integrated Motivational-Volitional (IMV) Model of suicidal behaviour · suicide · cross-sectional · moderating effects Meryem Betul Yasdiman: meryem.yasdiman@nottingham.ac.uk Introduction Perceptions of post-traumatic growth (PTG) measure the extent to which an individual reports positive changes in their identity, relationships, worldviews after a stressful event (Tedeschi & Calhoun, 1996) . Recent evidence has found that perceiving PTG from a past stressful life event is associated with lower reports of suicidal ideation (Bush et al., 2011) indicating its potential protective function. However, little is known about how perceptions of PTG interact with feelings of defeat and entrapment to predict suicidal ideation. The current study examined this question through the Integrated Motivational-Volitional (IMV) Model of Suicidal Behaviour.Aims This study aims to investigate the functional value of perceptions of PTG through the IMV Model of suicidal behaviour. We predict that PTG would serve as a moderator in the IMV model and disrupt the transition from defeat to entrapment (main hypothesis) and from entrapment to suicidal ideation (secondary hypothesis).

Holly Sullivan-Toole 1* , Shengchuang Feng 2 , Corinne N. Carlton 1 , Thomas M. Olino 3 , Irving C. Allen 4 , John A. Richey