Abstract

Recent developments in cognitive interpreting studies have begun to focus on the role of interpreters’ experience of emotions (Korpal and Jasielska 2019; Rojo and Foulquié Rubio 2025). This shift has broadened our view of interpreters’ cognition beyond information processing to incorporate the interpreters’ subjective experience into the description of interpreters’ cognition. However, because it is a recent expansion in our field, little is known about how interpreters regulate their affective states and how this relates to their self-regulation during interpreting. This article reports the findings of a qualitative study aimed at exploring the affective states that interpreters experience during interpreting and the self-regulation strategies they put in place to attain their goals. A stimulated-recall technique was applied to identify through interpreters’ retrospective comments both their affective states and the self-regulatory mechanisms they applied during an interpreting task. The retrospective protocols were analyzed through qualitative content analysis to ascertain how interpreters experience and manage cognitive and affective states induced by the interpretation task. Our findings show that interpreters 1) represent and regulate global and local goals about the interpreting communicative purpose; 2) experience positive and negative affective states induced by the interpreting task; and 3) put in place a few self-regulatory strategies to stay aligned with the interpreting goal.

Keywords: interpreters’ self-regulation, emotions, goal system, subjective experience, cognition

1. Introduction

Interpreting is a communicative activity aimed to enable understanding by accurately re-expressing what has been said in another language within an immediate communicative context (Pöchhacker 2019: 45). As a goal-directed activity, interpreting requires interpreters to mobilize complex cognitive resources, and to engage in metacognitive mechanisms like monitoring, planning, problem-solving, and decision-making (Tiselius and Hild 2017). These resources and mechanisms enable interpreters to navigate real-time comprehension, translation, and production in two languages, essential for the immediacy and accuracy that interpreting demands (Díaz-Galaz and Winston 2025).

In addition to cognitive demands, interpreters —being subjective agents— experience various emotions and affective states during interpreting. Emotions can significantly influence cognitive performance and the quality of interaction outcomes, yet research has traditionally focused mainly on states of stress and anxiety and their impact on interpreters’ performance (Moser-Mercer et al. 1998). Interpreters often face stress due to task-related factors such as speed of delivery, lack of preparation, strong accents, prolonged turns, and high-performance standards (Korpal 2021). These stressors can lead to physiological responses (increased blood pressure, heart rate, and cortisol levels) and subjective experiences of stress and anxiety (Riccardi 2015). Beyond task conditions, interpreters may also experience emotional reactions to the content of speeches, emotionally converging with speakers in specific communicative situations (Korpal and Jasielska 2019). In public service settings, for example, interpreters report experiencing immediate effects like distress, frustration, and anger, as well as long-term impacts, including burnout and vicarious trauma (Valero-Garcés 2015).

Given these stress-inducing conditions, the ability to manage emotions and cope with challenging situations seems to be a critical skill that develops with training and practice in interpreters, as some evidence suggests. For instance, Timarová and Salaets (2011) found that interpreting trainees with higher tolerance to stress were more successful in their training programs. Similarly, Bontempo and Napier (2011) observed an inverse correlation between negative affectivity and perceived competence among professional sign-language interpreters, while Hild (2014) reported that experienced interpreters demonstrated advanced self-regulation skills, including metacognition and emotional regulation, compared to trainees.

However, the role of interpreters’ emotions and subjective experiences during interpreting remains underexplored in Interpreting Studies. Although there is already a body of research on this topic (Rojo López and Foulquié Rubio 2025), studies have yet to address how interpreters experience and manage affective states to achieve the communicative goals of interpreting. This limited focus reveals a critical gap in our knowledge on the role of emotions in interpreting training and expertise acquisition (Hild 2014; Rojo López et al. 2021).

Thus, the questions that guide this study are the following: 1) What affective states, both positive and negative, do interpreters experience during interpreting? and 2) What cognitive self-regulation strategies do interpreters use to manage these affective states? To explore these questions, we designed an explorative qualitative study using video-stimulated recall, a retrospective technique that allows interpreters to comment on their experience of affective states and the self-regulation strategies used during interpreting. Investigating these aspects can deepen our understanding of interpreters’ cognition, subjective experience of emotion, and self-regulation.

2. Literature review

2.1. Emotions and emotion processes

Emotions are complex interfaces between an organism and its dynamic environment. Emotions connect dynamic external events and contexts in the environment with the organism’s adaptive response and subjective experience (Frijda 2008; Scherer and Moors 2019). Early work on emotions focused on identifying emotional states as discrete categories, with Ekman (1999) identifying basic emotions, such as fear, anger, sadness, disgust, surprise, and happiness, which are considered innate, universal, and short-term reactions, that have been observed with similar facial expressions across cultures and species, which suggests an evolutionary basis. In contrast, complex emotions like love or jealousy, emerge from combinations of basic emotions, are more enduring, and their expression varies from culture to culture (Oatley and Johnson-Laird 1987).

Emotion as a process has been traditionally described as consisting of three components: a) a physiological reaction to a stimulus, b) a behavioral response, and c) a feeling or the subjective experience of the emotion (Gazzaniga et al. 2014).

Klaus Scherer’s Component Process Model (2009) further refines the understanding of emotions by proposing that emotion processes result from a sequential appraisal of events, behaviors, situations, and memories according to several evaluative criteria. These criteria determine whether the event is relevant, beneficial, or harmful in relation to the person’s needs, plans, or values. The appraisal sequence leads to a multicomponent emotional response that is appropriate for dealing with the event. The resulting emotional response includes a physiological component (such as arousal), a motivational component (action readiness or action tendencies), a motor expression (facial or vocal expression), and a subjective feeling (the conscious experience of the emotion as feeling happy, anxious, or afraid). This process is highly dynamic and recursive as the appraisal criteria and the response components interact in a reciprocal way to produce a situated and adaptive response to changing contexts and situations (Scherer 2009).

Having established the complex interplay of cognitive, physiological and behavioral components of emotion processes, we now turn our attention to the capacity of individuals to modulate the impact of their emotional responses through self-regulation strategies.

2.2. Emotion regulation

According to classic emotion appraisal theory, individuals assess stimuli through cognitive appraisal, comparing their current state to a desired goal. This appraisal considers multiple dimensions, such as relevance, likelihood, and agency, to determine whether the current state is advantageous or detrimental to the individual’s goal. When a discrepancy arises, an emotional response is triggered, and a recursive feedback loop of regulatory processes ensues, where the person continuously monitors and reassesses how effective the regulation strategies are (Ellsworth 2013; Gaurav et al. 2013; Gross 2014).

In emotion regulation, the goal is often to achieve a specific emotional state. When the current state is appraised as misaligned with this goal, regulation strategies are applied to reduce the discrepancy. Emotion generation and emotion regulation are considered a continuum and an overarching process of goal-directed behavior (Gross and Barrett 2011). To pursue any goal, a person must apply self-regulation, involving intrinsic adjustments to stay aligned with their objectives (Carver and Scheier 2016). This self-regulation process consists in establishing standards and goals, monitoring the current versus desired state, and executing strategies to bridge any gap between the two (Baumeister and Heatherton 1996).

Gross’s Model of Emotion Regulation (2014) outlines a set of cognitive strategies that can be applied either proactively or reactively to manage emotional responses. Proactive strategies aim to prevent unwanted emotions by modifying the situation before the emotion arises. Reactive strategies are applied after an emotional response has been triggered and include: modifying the situation to change its emotional impact; controlling the attentional focus either by distraction (away from the emotional stimulus) or concentration (by focusing more narrowly on specific, non-emotional details); cognitive change or reappraisal, where the person alters the interpretation of a situation to change its emotional effect; and response modulation, which involves managing the expression and physiological response to an emotion, like suppressing facial expressions or taking deep breaths to calm down.

These classic models of emotion regulation provide a valuable framework for understanding emotional processes. However, interpreting is an activity of unique demands and pressures that elicit different types of emotions and require a set of self-regulation strategies specifically tailored to attain the goal of delivering accurate interpretations.

2.3. Interpreters’ emotions and self-regulation

Research on the role of emotions in interpreting has explored the various emotional challenges that interpreters face across conference and community interpreting settings. While interpreters often work in high-stakes or emotionally charged situations, the direct impact of these factors on performance remains under-researched and not fully established.

In public service interpreting, research has focused on the effects of vicarious trauma in interpreters (Valero-Garcés 2015; Naimi 2022), while in conference interpreting, studies have examined the impact of stress and anxiety on interpreter performance. These studies typically adopt an experimental approach and employ physiological measures, such as cortisol levels (Moser-Mercer et al. 1998), heart rate and galvanic skin response (Korpal 2016, Korpal and Jasielska 2019) to assess stress responses under different task conditions, including variations in speed of delivery, turn length and interpreters’ level of training. The underlying assumption in these studies is that stress is a negative state that may impair interpreter’s performance (Rojo López and Foulquié-Rubio 2025).

Beyond task conditions, other studies, have examined the effect of working conditions on both performance and job satisfaction. For example, a study conducted by the International Association of Conference Interpreters (AIIC 2002) investigated environmental factors such as air quality, space, lighting, temperature, and visibility of the speaker. The findings highlighted that unfavorable working conditions not only negatively affected performance but also reduced job satisfaction, marking an early acknowledgement of the role of job-related emotions and interpreters’ well-being.

In addition to negative affective states arising from task-related or external factors, a distinct line of research has focused on the subjective experience of interpreters when interpreting emotionally laden speeches. For instance, Korpal and Jasielska (2019) used physiological and self-report measures to show that interpreters often exhibit emotional convergence with the speaker, indicating a high degree of empathy and emotional engagement with the communicative situation.

A substantial body of research has focused on interpreters’ self-regulation, especially within the perspective of interpreter training and education (Díaz-Galaz and Winston 2025). Findings from these studies suggest that self-regulation is a skill that evolves through training and practice. It forms part of a broader set of strategic skills that interpreting students gradually acquire as they become more aware of the unique characteristics and challenges inherent in the interpreting process (Herring 2025).

While significant progress has been made in identifying the stressors interpreters face and the impact of various task-related and environmental factors on their performance, less is known about interpreters’ subjective experience of emotion and how they actively manage these emotional challenges to maintain effective communication. Specifically, few studies have examined the self-regulation strategies interpreters employ to control their emotional states in high-pressure or emotionally charged situations. This gap is particularly critical, as interpreters’ ability to self-regulate may play an essential role in expertise acquisition as well as in achieving accurate and effective interpretation despite emotional challenges. Addressing this research problem could offer insights into the emotional resilience and self-regulation skills that interpreters develop, and how these skills contribute to their performance across diverse interpreting contexts.

3. The study

An exploratory study was conducted to describe the interpreters’ emotional experience and their self-regulation strategies used to effectively achieve the goal of interpreting. The guiding questions were 1) What affective states, both positive and negative, do interpreters experience during interpreting? and 2) What cognitive self-regulation strategies do interpreters use to manage these affective states? To elicit data, the study employed a video-stimulated recall technique, a variation of a retrospective protocol, in which participants’ comments are elicited by a vivid stimulus. In this case, the stimulus was a video recording of the participant performing the task in a laboratory setting. This technique allows researchers to access participants’ memory of conscious processes involved in monitoring, problem-solving, and decision-making, while these processes are still accessible in memory (Díaz-Galaz 2022; Gass and Mackey 2016).

3.1. Participants

Thirteen interpreters participated in the study, including seven professional conference interpreters and six advanced interpreting students. However, four (two professional interpreters and two student interpreters) were excluded from the analysis due to invalid protocol reports (see Protocol data preparation section below). The final sample had nine participants: five professional interpreters and four student interpreters. All participants were native Spanish speakers (L1) with English as a second foreign language (L2). Among the professional interpreters (three women and two men) the average experience was 15 years (range: 4 to 28 years). They worked in the private market and averaged 53 interpreting hours per month in the 12 months before participating in the study (range: 25 to 100 hours). Interpreting students (three women and one man) had completed 2.5 years of training in an undergraduate English-Spanish conference interpreting program which involved at least 10 hours of weekly practice in consecutive and simultaneous interpreting.

As part of a more extensive study, participants’ lexical knowledge was assessed as a measure of L2 proficiency (Stæhr 2009), using the LexTALE Test (Lemhöfer and Broersma 2012) and the Vocabsize Test (Nation and Beglar 2007). In the LexTALE test, which measures lexical knowledge through word and pseudoword recognition, participants scored an average of 77.75 per cent accuracy (SD=6.4; range: 70 per cent to 93.75 per cent), indicating a high level of vocabulary knowledge. Similarly, participants’ average vocabulary knowledge on the Vocabsize test was 11,210 word-families (SD= 910.9; range: 9,700 to 12,900), confirming a high level of lexical coverage suitable for proficient language use (Schmitt and Schmitt 2014). Both these scores are indicative of high L2 vocabulary size and high L2 proficiency, thus no participant was excluded for low scores in these measures. No significant differences were found between professional interpreters and interpreting students in Vocabsize test (t(7)= 2.84; p= 0.19); or Lextale scores (t(7)=2.085; p= 0.07).

3.2. Materials

To elaborate source speeches for the interpreting tasks, we first preselected 20 short descriptive texts from an encyclopedic visual dictionary (Dorling Kindersley Inc. 2012), which defined general concepts such as the Moon, dinosaurs, golf, insects, soccer, plants, and the Earth. These texts were analyzed with the Coh-Metrix tool (McNamara et al. 2010) to assess various linguistic and textual properties, including word count, word frequency, lexical density, and lexical diversity. Based on this analysis, nine texts that were comparable in textual characteristics and content complexity were selected (see Table 1).

Table 1: Linguistic and textual properties of selected source texts.

Each selected text was adapted into a speech of approximately 90-120 seconds, incorporating features of the conference lecture genre to simulate realistic source speech features in interpreting. Praat software (Boersma and Weenink 2014) Syllable Nuclei script (de Jong and Wempe 2008) was used for automatic analysis of delivery features, such as syllable count, number of pauses (pauses are identified by detecting silence below the 25dB threshold), total duration, phonation time (total speaking time, excluding pauses), speech rate (syllables per second, including pauses), and articulation rate (syllables per second, excluding pauses) (Table 2). These metrics were used to ensure that each speech was consistent in prosodic features and suitable for the interpreting task.

The nine speeches were video-recorded by a female native speaker of American English, aiming for clear articulation and consistent delivery style across all recordings. As part of a larger project, these nine speeches were used in a counterbalanced order across three different tasks: L2 listening, consecutive interpreting, and simultaneous interpreting. This report focuses on the analysis of the simultaneous interpreting task.

Table 2: Prosodic features of selected source speeches

3.3 Data collection procedure

The study received approval from the host institution’s Ethical Committee, and informed consent was obtained from all participants prior to participation. Data collection involved a video-stimulated recall session, conducted as described in Díaz-Galaz (2022) and consisted in two main stages:

1. Simultaneous interpreting task: Participants performed an English-Spanish simultaneous interpreting task using one of the source speeches described above. Participants’ interpreting performance was video recorded.
2. Video-stimulated recall: Immediately after completing the task, participants watched the video of their performance. At this moment, they provided retrospective verbal comments describing the thoughts and strategies they recalled using while interpreting. The goal of this protocol was to capture participants’ reports of their conscious experiences during the interpreting task.

To help participants feel comfortable with the procedure, a practice block of a simultaneous interpreting task was conducted at the beginning of the session. This practice session allowed participants to familiarize themselves with the format of the video-stimulated recall protocol and the expectation to verbalize their thought processes while interpreting.

The stimulated-recall protocol was conducted in English, to maintain participants in the bilingual mode (Grosjean 2013) for the task and the verbalization of their retrospective comments. Following standard guidelines (Díaz-Galaz 2022; Gass and Mackey 2016), participants were not asked any guiding questions beyond the instruction to “verbalize what you were thinking at this moment when interpreting”.

4. Data analysis

4.1. Protocol data preparation

To ensure the validity of data obtained through retrospective reports, protocol data from each participant were transcribed and organized into data sets for the coding process. For this study, the data set corresponding to the simultaneous interpreting task was further analyzed.

In line with guidelines from Gass and Mackey (2016), and Díaz-Galaz (2022) an initial round of analysis was conducted to identify invalid verbalizations. According to these guidelines, invalid comments include reflections, elaborations or explanations that participants produce in hindsight -either as a result of watching themselves in the recording or as evaluative comments on their performance. These invalid verbalizations must be excluded from the analysis as they do not align with the protocol instruction of verbalizing what the participant was thinking during the task. Only valid verbalizations – comments in which participants report what they were thinking or feeling during the task were retained for further analysis.

4.2. Coding procedure

The data analysis aimed at identifying the affective states that interpreters may have experienced during interpreting and learning the self-regulation strategies they may have implemented to manage those affective states. The protocols from professional and student interpreters were analyzed using qualitative content analysis, an interpretative technique for identifying patterns, themes, and categories within the data to derive and understand meaning (Saldanha and O’Brien 2014). In this study, we used a deductive approach, applying predefined categories from Baumeister and Heatherton’s (1996) framework for self-regulation. This framework emphasizes three components of self-regulation: establishing goals, monitoring the current state, and comparing it to the goals, and applying corrective efforts to reduce discrepancies between the current state and the goal. Thus, it was important to identify whether interpreters represented goals for the interpreting task in general and for local situations that may trigger an emotion response. Likewise, the analysis aimed at detecting reports of emotions experienced during the interpreting task and how they relate to their goals. Finally, the analysis focused on any of the self-regulation strategies that may reduce discrepancies between the state triggered by the emotion response and their goals, oriented by Gross’s (2014) categories of emotion regulation strategies.

The coding process involved several stages to ensure depth and consistency in capturing participants’ reported thoughts during the interpreting tasks:

1. Open coding: In the first stage, the author conducted open coding by assigning initial labels to participants’ comments based on their descriptions of thoughts and strategies used while performing the task. This round of initial coding aimed to capture a wide range of possible emotional states and self-regulation strategies without imposing rigid categories prematurely.
2. Review for consistency and coverage: In the second stage, the codes were reviewed for consistency and coverage across the data set, ensuring they accurately reflected participants’ experiences and aligned with the self-regulation framework. This step involved comparing and refining codes to enhance reliability and comprehensiveness across participants' comments.

3. Grouping into broader categories: The initial codes were grouped into broader categories representing key aspects of self-regulation during interpreting (see section 5 below). These emerging categories were further refined, defined, and described in detail to ensure that they accurately represented the range of emotions and self-regulation strategies employed by participants.

5. Findings and discussion

This study aimed to describe the interpreters’ emotional experience and their self-regulation strategies during a simultaneous interpreting task. The guiding questions of this exploratory study were: 1) What affective states, both positive and negative, do interpreters experience during interpreting? and 2) What cognitive self-regulation strategies do interpreters use to manage these affective states? Immediately after performing a brief simultaneous interpreting task, we conducted a stimulated-recall protocol in which professional and student interpreters watched a video-recording of their performance and commented on what they were thinking while performing the task. Retrospective comments were consequently analyzed and coded following Baumeister and Heatherton’s (1996) framework for self-regulation and Gross (2014) model for emotion regulation strategies. These theories emphasize the importance of goal setting, monitoring current state and applying self-regulation strategies to reduce discrepancies between the current state and the task goal. Table 3 below summarizes the retrospective comments made by both professional and student interpreters.

Table 3: Number of retrospective comments verbalized by professional and student interpreters

The first finding of the study is the number of valid comments reported by participants, with professional interpreters providing more comments (27) than students (18) across all categories. This difference may reflect professionals’ extensive experience and heightened awareness of their own cognitive and emotional processes or perhaps a better ability to articulate their thoughts and feelings about the task. Studies have shown that experienced interpreters show advantages in certain components of the self-regulation process, particularly monitoring (Moser-Mercer et al. 2000; Herring 2018; Herring and Tiselius 2020).  

Through content analysis of the retrospective protocols, three broad categories were identified: 1) representation of a global goal and local goals for the interpreting task; 2) recognition of emotions and affective states; and 3) self-regulation strategies. The retrospective comments quoted below were reported by professional experienced interpreters (E) or student interpreters (S).

5.1. Representation of a global goal and local goals for the interpreting task

a. Representation of a global goal for the interpreting task

As mentioned above, the emotion regulation process requires that a goal is in place to act as a guidepost against which to compare the ongoing development of a task or event, and to determine the self-regulation strategies that will lead the process to be aligned with that goal again. The protocols indicate that participants viewed interpreting as a communicative activity, requiring both accurate comprehension of the source speech, and the production of an adequate, precise speech in the target language. Comprehension involves understanding, making sense, connecting, and organizing information, while production involves delivering a natural speech in the target language, according to a cognitive representation of the audience’s needs. This primary goal serves as a standard that guides strategic processing during the task.

While I was doing that, I missed a piece of information. I was trying to connect the ideas, but I don’t think I actually succeeded in that part. (E1)

In my head, I’m just trying to understand the way ideas connect. With some specifics, of course. (E3)

Right there, I’m trying to create a structure in my head, like a list. [I’m] trying to memorize, I mean, trying to remember and organize thoughts. (S19)

[Participant moves his body in tune with his speech] I’m moving as I’m explaining myself and by the movements of my hands. I don’t know if I’m trying, but in my mind -in a very naive way- I believe that is going to help people to understand. But I know people will not watch it. So it’s just for me, it’s a way of expressing myself in a clearer way because that stops me from mimicking the structures of English. So as I move and change the structures, I can express things in a more appropriate way to the target language, in a more natural way (E3).

b. Representation of task local goals

Participants’ comments reveal that as the task unfolds, they establish local goals that help them stay aligned with the primary goal. These local goals are i) identifying information that needs to be retained in memory; and ii) sustaining focused attention and resisting potential distractions.

I was thinking, “Leave all the weird terminology very away from your head; just stick to what you can actually imagine and what you can actually understand, and you can relate.” I was basically remembering the first part of the process of photosynthesis and trying to memorize the most important things and say just what I understand, which is the process of photosynthesis. (E28)

I was thinking, “Okay, I’m going to remember this.... and not remember the weird terminology”. So basically, like trying to determine what I really could remember. (E28)

 So, like I said, there was this distraction that I couldn’t get over, and then [the speaker] mentioned these two processes that I didn’t know of, so I just… lost them. That’s why I was trying to… I was trying to get more concentrated. (E1)

I don’t think about it; I just close my eyes to be able to process more information, maybe by drowning out other information. It’s involuntary. (S19)

Both professional and student interpreters identified similar local goals related to regulating their cognitive resources such as memory and attention to stay focused and aligned with the global goal. Participants in this study also represented controlled sub-goals associated to regulation of cognitive resources, like memory and attention to retain the important information and maintain focus despite distractions. These findings provide evidence about the representation of interpreting’s communicative purpose, and that this purpose guides specific regulatory processes and strategies during the task (Díaz-Galaz and Torres 2019). 

5.2 Recognition of emotions and affective states

a. Negative emotions and affective states

The retrospective comments indicate that participants acknowledged experiencing negative affective states, namely nervousness and frustration. Nervousness was triggered by an appraised sense of lack of control, which tells of the anticipation processes that unfold prior to the task. Frustration was triggered by the inability of the participant to attain a goal previously set, despite efforts to attain it.

Simultaneous interpreting makes me feel nervous; I feel that there are more factors out of my control. It is probably the modality that makes me feel the most nervous and insecure. (E23)

It’s frustrating because, in the beginning, I made an effort to remember the points. And it’s frustrating, ‘cause I can’t remember them. I’m trying to remember and list the same things, but ugh... I just get this feeling of frustration and helplessness. (S19)

b. Positive emotions and affective states

Participants also reported positive affective states, particularly associated with monitoring processes: comfort, and satisfaction. Comfort comes from asserting the resources needed to attain the task and the available resources. Satisfaction also arises when establishing that a strategy had a successful outcome.

Since I listened to [the speaker] before I felt more comfortable with her this time, her way of speaking, so that helped. I felt more comfortable in this part. Despite a couple of technical words, like chlorophyll and those words that got me stuck. (E23)

I knew what photosynthesis is. I wasn’t, like, ‘oh, what’s a chloroplast?’ I remember because we saw that in school, so I was like, yeah, this is kind of something I’m a little more comfortable with.  (E28)

In terms of the interpreters’ affective state, participants in our study experienced subjective feelings of nervousness, frustration, satisfaction, and comfort during the task. These affective states emerged as part of the monitoring processes within their self-regulation of emotion. Participants reported affective responses at various stages: a) nervousness when evaluating the potential difficulty of the task; b) frustration or satisfaction when assessing the results of their efforts; c) comfort when comparing their prior knowledge of the topic or task with the knowledge required to perform the task. Monitoring, a critical component of self-regulation, involves comparing the current state with the global or local goals (Baumeister and Vohs 2016). This comparison produces either a high, neutral or low discrepancy from the goal, generating a negative affect or a positive affect in anticipation of achieving the goal (Carver and Scheier 2016; Yih et al. 2019). When interpreters perceive an unexpected difficulty level or an ineffective strategy, they experience nervousness and frustration. In response, they report implementing a strategy to try to regulate these negative emotions. However, when regulation is ineffective, goal pursuit may be compromised, sometimes prompting interpreters to modify the primary goal.

Positive affective states, such as comfort and satisfaction, play a vital role in sustaining goal pursuit by reinforcing interpreters’ sense of self-efficacy, meaning that they feel capable of executing the task and their commitment to the goal is higher. In our study, interpreters reported feeling comfort and satisfaction when their self-monitoring yielded positive feedback on their knowledge and strategies, indicating a low discrepancy between their current state and the global or local goal. These positive states foster interpreters’ commitment to the task and support sustained effort toward achieving the interpreting goal.

5.3 Self-regulation of emotions and affective states

Participants were not very expressive of their emotion regulation strategies, except for a few comments that explicitly identify the self-regulation strategies of experienced interpreters, namely self-control and reducing the performance level.

I think I’ve never interpreted a dinosaur topic before, so I was nervous. But then I was like, “No! Control yourself! Breathe!” before starting. (E28)

If [the interpreting assignment] is too hard , making it sound well is left out, and trying to get the message across is what I concentrate on. (E3).

For the analysis of the self-regulation strategies, we followed Gross’s (2014) process model for emotion regulation. This model identifies five families of strategies, that classify strategies according to the time in the emotion process that the strategy is implemented. These strategies are: situation selection, situation modification, attentional deployment, cognitive change, and response modulation. Our findings so far reveal that participants established a primary goal for the interpreting task, which is interpreting to communicate, and local goals that involve mainly regulating their focus of attention and memory. Participants also experienced both positive (comfort and satisfaction) and negative affective states (nervousness and frustration) in response to the task. Notably, experienced interpreters’ reports in this study indicate that in response to negative emotions they implemented self-regulation strategies linked to the management of cognitive resources, particularly memory and attention. This self-regulation strategy corresponds to the attentional deployment category in Gross’s framework, which refers to “how individuals direct their attention within a given situation to influence their emotions” (2014: 13). The comments show that participants direct attention away from the emotion to focus on maintaining the local goal of sustaining the focus of attention and avoid distractions. This system contributes to regulate the effect of negative emotions and to stay on track in achieving the global goal of producing an accurate interpretation.

The direction of attention allows participants to focus on the task and implement strategies, like self-control and reducing performance level. Hild (2014) found that inexperienced interpreters facing stress and frustration often coped by lowering performance standards or temporarily disengaging from the task. In our study, a similar response is observed , with one participant reporting a shift in focus to content accuracy as a way to manage frustration. In these instances, interpreters in practice may adjust their goal to better match their perceived abilities, thereby enhancing their sense of efficacy in reaching the goal.

6. Conclusion

Although the data collected is limited, the theoretical implications of these findings are significant. The monitoring and regulatory mechanisms observed in this study are applied not only to the input content, but also to the interpreter’s subjective experience, perception of task goals, strategic knowledge, and affective states. Traditional cognitive approaches to interpreting, rooted in an information- processing paradigm, have primarily focused on input content (e.g. source speech and context) as the sole source of information that an interpreter processes. This perspective tends to reinforce the notion that interpreters function as mere conduits, mechanically transforming input into output.

However, both the literature reviewed above, and our findings suggest a need for more comprehensive account of interpreters’ cognition that includes their subjective experience, and self-regulatory knowledge as essential components of skilled performance. Additionally, any description of the cognitive processes involved in interpreting should consider how affective states influence decision-making and problem-solving strategies. This expanded view acknowledges the interpreter as an active agent who integrates both cognitive and affective dimensions to adaptively manage the complexities of the task, thereby challenging the traditional conduit model.

The limitations of this study must be acknowledged. First, the data on emotional experiences and regulation is limited. This is likely due to the nature of the stimulated recall technique, which prevents the use of guiding questions. As a result, participants’ reports are confined to what they recall in the moment or choose to share with the researcher. Consequently, the conclusions drawn from this data should be interpreted with caution. Further research is essential to gain a more comprehensive understanding of interpreters’ emotional experiences during interpretation.

While the stimulated-recall technique effectively elicits explicit information that participants can readily recall, it shares the limitations of other retrospective methods, including susceptibility to recall biases and the influence of participants’ subjective interpretation of their thoughts. To better understand interpreters’ emotion processes, future research could address these limitations by triangulating retrospective comments with quantitative data collection techniques, such as physiological measures of galvanic skin response, heart rate and cognitive load. This approach would enable a more comprehensive examination of implicit regulatory processes or mechanisms that may not be accessible through conscious recall.  Also, additional data can be collected through standardized tests or questionnaires that measure self-regulatory mechanisms to complement protocol data.

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