Social Reappraisal Studies: Acoustic Analyses
Creators: name: Sahi, Razia S.
name: Silvers, Jennifer
name: Siyan Nussbaum
Publisher: name: OSF Registries
Year: 2022
Subjects: subject: Social and Behavioral Sciences
subject: Psychology
subject: FOS: Psychology

description: This work builds on our previous research (https://osf.io/94ecj/) examining the relationship between reappraising alone and reappraising with help from a close other (i.e. social reappraisal). In that work, we found that social reappraisal was more effective than reappraising alone, and that this effect was not the result of a difference in the quality of the reinterpretations, or due to social buffering (Sahi, Ninova, &amp; Silvers, 2020).

The present work follows up to examine whether features of someone's voice contribute to social reappraisal efficacy. In other words, when a responder helps their friend to reappraise negative stimuli, does how they vocalize the reappraisal (i.e. the acoustic properties of their verbal expression) predict negative affect in the target of support, independently of the content of what they are saying?

We have two existing datasets from the aforementioned research in which we can explore the present question. In these datasets, "helpers" recorded reinterpretations that their friend (the target) heard while viewing negative images. The content of the reinterpretations was the same across dyads such that each negative image was always paired with the same scripted reinterpretation. However, helper participants could vocalize the reinterpretation in whatever way felt natural to them, for example, by using higher or lower pitch. Helpers were given no instructions other than to say the reinterpretation in a way that would be helpful to their friend while viewing the negative images. We measured the target's self-reported negative affect on each trial that they heard their friend's voice. We also measured the target's self reported negative affect as they reappraised stimuli on their own, and as they passively viewed negative and neutral images. Both participants in each dyad completed measures of relationship quality (modified Inventory of Peer Attachment (IPPA)) and personality (e.g. shortened Interpersonal Reactivity Index (IRI), shortened Eysenck Personality Inventory (EPI)). All participants in these studies were female. 

Given that our existing datasets are appropriate for testing the present research questions, we conducted exploratory analyses in the first dataset (N = 40, 18 social reappraisal trials each) that we aim to confirm in the second dataset (N = 40, 12 social reappraisal trials each). Below, we describe the steps we took to analyze dataset 1. Thus, this pre-registration documents our hypotheses prior to analyzing dataset 2. 

Data Cleaning: We used PraatR (Albin, 2014) to extract acoustic features for each audio clip (18 clips per participant, 720 trials total). We used a default pitch range: 75-600 Hz. Data was visually inspected in Praat for every trial and interpolation was performed over spikes. Output was converted to semitones to standardize across participants.

Background &amp; Hypotheses: We focused specifically on one acoustic feature: fundamental frequency (i.e. F0), which is a measure of pitch. Higher pitch has been associated with higher affective arousal (Agrima et al., 2017; Neubauer et al., 2017) and emotions such as interest and relief in the speaker (Kamiloğlu et al., 2020) and greater attention and learning in infant listeners (Fernandez &amp; Knörnschild, 2020). Thus, we wondered whether higher pitch in the helper's voice - as indexed by greater mean F0 - would improve social reappraisal outcomes - as indexed by lower negative affect in the target during social reappraisal. Greater affective arousal in the support giver's voice could serve to increase the salience of their message to the target, or it could communicate the helper's attention and care for the target. Thus, we hypothesized that greater helper mean F0 would predict lower negative affect in the target during social reappraisal. As a more exploratory question, we also tested whether greater F0 standard deviation predicted social reappraisal efficacy, since variability in pitch could potentially also serve to increase the target's attention to the helper's message.

Model: We tested our hypothesis using a multilevel model (trials nested within dyad) with target negative affect on social reappraisal trials as the outcome variable, helper F0 mean on the corresponding trial as the predictor, average target negative affect on solo reappraisal trials as a baseline covariate, and a random intercept. We found that greater mean F0 was associated with lower negative affect during social reappraisal, regardless of whether we included the baseline covariate variable. F0 standard deviation was not associated with negative affect on social reappraisal trials.

Relationship Quality: To follow-up on this result, we wondered whether the helper's vocal patterns was associated with the target's relationship quality in general. In other words, do the emotional benefits of having a friend with greater mean F0 during social support extend outside of the lab to predict greater satisfaction with the quality of support one receives from their friend on a regular basis? Using a simple regression, we found that the helper's mean F0 (averaging across social reappraisal trials) was associated with the target's overall relationship satisfaction, as indexed by the IPPA . When looking at the three subcomponents of the IPPA - trust, communication, and alienation - only the communication subscale (e.g. "When we discuss things, my friends care about my point of view.") was related to the helper's average F0. Interestingly, the helper's F0 was not related to their own relationship satisfaction with the target, nor was the target's relationship satisfaction related to their own negative affect on the social reappraisal trials.

Personality: Finally, we wondered whether the helper's personality traits predicted their vocal patterns. Specifically, we tested whether the helper's empathic tendencies (empathic concern and perspective-taking subscales from the IRI) and extraversion (from EPI) predicted their mean F0 (averaging across trials) using three separate simple regression models. We found no relationship between these personality variables and F0.

We aim to replicate these analyses in dataset 2: (1) Does helper's mean F0 predict target's negative affect on each social reappraisal trial (multilevel model), controlling for target's average negative affect on solo reappraisal task?; (2) Does helper's F0 mean, averaging across social reappraisal trials, predict target's relationship satisfaction (as measured by IPPA - particularly the communication subscale)?; (3) Do the helpers' personality traits predict their mean F0? We hypothesize that our results from dataset 1 will replicate in dataset 2.

We are currently collecting a third dataset (https://osf.io/np67u) in which we can test these same aims, as well as possible gender related effects (i.e. Are there gender differences in mean F0 during social reappraisal? Does gender moderate the effect of helper's mean F0 on target's negative affect during social reappraisal trials?) and memory related effects (i.e. Does greater helper mean F0 during social reappraisal predict greater reduction in negative affect associated with images from lab task to follow-up?). We will continue to assess F0 standard deviation as an exploratory predictor. We will test additional personality variables of interest, such as a measure of compassion (i.e. Dispositional Positive Emotion Scales; Shiota et al., 2006).

We take a Bayesian statistics approach to these questions across studies 1-3 because: (i) we are working with multiple datasets with similar populations, which allows us to establish a meaningful prior in study 1 to use in subsequent studies, and (ii) since we are utilizing existing datasets with no a priori power analyses for these particular research questions, Bayesian statistics allows us to take a graded inference approach to assess whether evidence accumulates in support of the proposed association across datasets.