“Watch out!”: Effects of instructed threat and avoidance on human free‐operant approach–avoidance behavior

Abstract

Approach-avoidance paradigms create a competition between appetitive and aversive contingencies and are widely used in nonhuman research on anxiety. Here, we examined how instructions about threat and avoidance impact control by competing contingencies over human approach-avoidance behavior. Additionally, Experiment 1 examined the effects of threat magnitude (money loss amount) and avoidance cost (fixed ratio requirements), whereas Experiment 2 examined the effects of threat information (available, unavailable and inaccurate) on approach-avoidance. During the task, approach responding was modeled by reinforcing responding with money on a FR schedule. By performing an observing response, participants produced an escalating "threat meter". Instructions stated that the threat meter levels displayed the current probability of losing money, when in fact loss only occurred when the level reached the maximum. Instructions also stated pressing an avoidance button lowered the threat level. Overall, instructions produced cycles of approach and avoidance responding with transitions from approach to avoidance when threat was high and transitions back to approach after avoidance reduced threat. Experiment 1 revealed increasing avoidance cost, but not threat magnitude, shifted approach-avoidance transitions to higher threat levels and increased anxiety ratings, but did not influence the frequency of approach-avoidance cycles. Experiment 2 revealed when threat level information was available or absent earnings were high, but earnings decreased when inaccurate threat information was incompatible with contingencies. Our findings build on prior nonhuman and human approach-avoidance research by highlighting how instructed threat and avoidance can impact human AA behavior and self-reported anxiety.

Verbal instructions override the meaning of facial expressions

“…This is particularly evident when information directly refers to the listener or reader 18 – 20 . Accordingly, verbal instructions about imminent aversive events (threat-of-shock) effectively enhance perceptual processing 21 – 23 , defensive activation 4 , 7 , 24 , 25 , and modulate overt behavioral responding (e.g., in decision-making tasks) 26 , 27 . Importantly, this verbal information does not need to be substantiated by first-hand experiences of the anticipated aversive events.…”

Human social defeat and approach–avoidance: Escalating social‐evaluative threat and threat of aggression increases social avoidance

“…First, they indicate the potential value of coupling social defeat and approach–avoidance paradigms for investigating human social avoidance. Two different escalating social threats increased human social avoidance in ways consistent with findings reported in nonhuman social defeat (Beery & Kaufer, 2015; Hammels et al, 2015; Huhman, 2006; Toth & Neumann, 2013), human and nonhuman AP–AV, and threat‐of‐punishment studies (Aupperle, et al, 2015; Bach et al, 2014; Bublatzky et al, 2017; Burgos‐Robles et al, 2017; Capuzzo & Floresco, 2020; Jacobs & Moghaddam, 2020; Pittig & Dehler, 2019; Pittig et al, 2018; Schlund et al, 2016, 2017, 2020; Schwartz et al, 2017; Zorowitz et al, 2019). The use of negative evaluations as a SET to produce avoidance yielded results consistent with those from prior investigations that have used SET to produce anxiety and stress‐related responses (Dickerson & Kemeny, 2004).…”

“…The methods used closely modeled those used in several prior behavioral and neuroscience investigations on avoidance (Schlund et al, 2015, 2016, 2017, 2020). A within‐subject design was used.…”

“…In addition, work in this vein is designed to identify and manipulate variables to reduce avoidance and increase approach. To achieve these goals, many researchers employ approach–avoidance (AP–AV) or threat‐of‐punishment paradigms in which behavior maintained by positive reinforcement is threatened by punishment (Bublatzky et al, 2017; Kirlic et al, 2017; Pittig & Dehler, 2019; Pittig et al, 2018; Schlund et al, 2017, 2020). Emerging neurophysiological research with humans (Aupperle et al, 2015; Bach et al, 2014; Patrick et al, 2019; Schlund et al, 2016; Zorowitz et al, 2019) and nonhumans (Burgos‐Robles et al, 2017; Capuzzo & Floresco, 2020; Jacobs & Moghaddam, 2020; Schwartz et al, 2017) is also examining how neural systems for reward and threat that historically have been studied independently interact to support approach or avoidance.…”

An arbiter model of motivational selection

“…These tendencies vary with experience, deprivation states (e.g., hunger, thirst), reward magnitude, and distance to reward and punishment. For example, increases and decreases in the magnitude of the reward or punisher cause upward or downward shifts of these gradients in humans and other animals (Bach et al, 2014;Schlund et al, 2016;Schlund et al, 2017;Sierra-Mercado et al, 2015). Likewise, alterations in value due to changes in internal states cause shifts in these gradients.…”