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Recognizing other's affective states is essential for successful social interactions. Alexithymia, characterized by difficulties in identifying and describing one's own emotions, has been linked to deficits in recognizing emotions and mental states in others. To investigate how neural correlates of affective state recognition are affected by different facets of alexithymia, we conducted an fMRI study with 53 healthy participants (aged 19 to 36 years, 51 % female) using the Reading the Mind in the Eyes Test (RMET) and three different measures of alexithymia (TSIA, TAS-20 and BVAQ). In addition, we examined brain activity during the RMET and replicated previous findings with task-related brain activation in inferior frontal and temporal gyri and the insula. No association was found between alexithymia and behavioral performance in the RMET, possibly due to the low number of participants with high alexithymia levels. ROI-based analyses revealed no associations between alexithymia and amygdala or insula activity during the RMET. At whole-brain level, both a composite alexithymia score and the unique variance of the alexithymia interview (TSIA) were associated with greater activity in visual processing areas during the RMET. This may indicate that affective state recognition performance in alexithymia relies on a higher, compensatory activation in visual areas.

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Empathy, crucial for social interaction, is impaired across various neuropsychiatric conditions. However, the genetic and neural underpinnings of empathy variability remain elusive. By combining forward genetic mapping with transcriptome analysis, we discover that aryl hydrocarbon receptor nuclear translocator 2 (ARNT2) is a key driver modulating observational fear, a basic form of affective empathy. Disrupted ARNT2 expression in the anterior cingulate cortex (ACC) reduces affect sharing in mice. Specifically, selective ARNT2 ablation in somatostatin (SST)-expressing interneurons leads to decreased pyramidal cell excitability, increased spontaneous firing, aberrant Ca2+ dynamics, and disrupted theta oscillations in the ACC, resulting in reduced vicarious freezing. We further demonstrate that ARNT2-expressing SST interneurons govern affective state discrimination, uncovering a potential mechanism by which ARNT2 polymorphisms associate with emotion recognition in humans. Our findings advance our understanding of the molecular mechanism controlling empathic capacity and highlight the neural substrates underlying social affective dysfunctions in psychiatric disorders.

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The human-animal relationship is crucial for animal welfare. Gentle handling enhances pigs' comfort while rough handling causes fear and stress. This study examined how different human-animal relationship qualities affect the behavior and heart rate variability (linear and non-linear parameters) of 36 nursery pigs. Over six weeks, pigs experienced positive (n = 12), minimal (n = 12), or negative (n = 12) human handling. Their responses to handlers were then assessed in an experimental arena with four phases: habituation, exposure to the handler standing and sitting, and forced interaction. Pigs subjected to negative handling exhibited increased fear-related behaviors, spending less time in contact with the handler. They also exhibited heightened stress responses, with greater LF/HF ratio and Lmean values compared with positively handled pigs. Conversely, gently handled pigs displayed affiliative behaviors, accepting more strokes, and higher parasympathetic activation, indicated by greater RMSSD/SDNN and SampEn values, suggesting a more positive affective state. Minimally handled pigs exhibited some behavioral similarities to gently handled pigs, although physiological data indicated that the interaction was likely more rewarding for the gently handled pigs. These results emphasize the impact of human-animal relationships on pig welfare and highlight the value of incorporating non-linear heart rate variability parameters in such evaluations.

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The recognition of animals as sentient beings has raised societal awareness of the welfare of farmed animals. This has been instrumental in increasing the legislative pressure towards welfare-conscious farming practices and, more lately, greater consumer demand for ethically sourced products. Besides, improved animal welfare is a key driver for enhanced performance, particularly in breeding boars, as welfare conditions strongly influence reproductive outcomes. The stressors associated with confinement impact testicular physiology and semen quality and the efforts to improve the welfare of breeding boars have so far focused on mitigating the negative consequences associated with stressors. The Five Freedoms framework and the European Food Safety Authority (EFSA)'s 'welfare consequences' approach prioritise the alleviation of suffering. In breeding boars, key welfare negative consequences include movement restriction, isolation stress, inability to engage in exploratory behaviours, locomotory disorders, and prolonged hunger. The negative consequences, which can be mitigated by improved housing and management practices, should be tackled in any commitment to improve the welfare of breeding boars. Animal welfare science, however, has recently shifted towards cultivating positive welfare experiences and a life worth living, beyond just alleviating suffering. The Five Domain Model systematically evaluates animal welfare, considering both negative and positive aspects. Encouraging positive welfare states involves facilitating species-specific behaviours, such as exploration and play, and fostering positive human-animal interactions. In breeding boars, strategies promoting positive welfare include providing enriching environments, encouraging exploration, and cultivating positive interactions with caretakers. Thus, for an overall welfare improvement of breeding boars, not only should the absence of suffering be guaranteed, but also the promotion of positive experiences that make their lifes worth living.

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Personal identification systems based on electroencephalographic (EEG) signals have their own strengths and limitations. The stability of EEG signals strongly affects such systems. The human emotional state is one of the important factors that affects EEG signals' stability. Stress is a major emotional state that affects individuals' capability to perform day-to-day tasks. The main objective of this work is to study the effect of mental and emotional stress on such systems. Two experiments have been performed. In the first, we used hand-crafted features (time domain, frequency domain, and non-linear features), followed by a machine learning classifier. In the second, raw EEG signals were used as an input for the deep learning approaches. Different types of mental and emotional stress have been examined using two datasets, SAM 40 and DEAP. The proposed experiments proved that performing enrollment in a relaxed or calm state and identification in a stressed state have a negative effect on the identification system's performance. The best achieved accuracy for the DEAP dataset was 99.67% in the calm state and 96.67% in the stressed state. For the SAM 40 dataset, the best accuracy was 99.67%, 93.33%, 92.5%, and 91.67% for the relaxed state and stress caused by identifying mirror images, the Stroop color-word test, and solving arithmetic operations, respectively.

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Introduction: Facial emotion recognition abilities of children have been the focus of attention across various fields, with implications for communication, social interaction, and human behavior. In response to the COVID-19 pandemic, wearing a face mask in public became mandatory in many countries, hindering social information perception and emotion recognition. Given the importance of visual communication for children's social-emotional development, concerns have been raised on whether face masks could impair their ability to recognize emotions and thereby possibly impact their social-emotional development. Methods: To this extent, a quasiexperimental study was designed with a two-fold objective: firstly, to identify children's accuracy in recognizing basic emotions (anger, happiness, fear, disgust, sadness) and emotional neutrality when presented with faces under two conditions: one with no-masks and another with faces partially covered by various types of masks (medical, nonmedical, surgical, or cloth); secondly, to explore any correlation between children's emotion recognition accuracy and their affective state. Sixty-nine (69) elementary school students aged 6-7 years old from Greece were recruited for this purpose. Following specific requirements of the second phase of the experiment students were assigned to one of three (3) distinct affective condition groups: Group A-Happiness, Group B-Sadness, and Group C-Emotional Neutrality. Image stimuli were drawn from the FACES Dataset, and students' affective state was registered using the self-reporting emotions-registration tool, AffectLecture app. Results: The study's findings indicate that children can accurately recognize emotions even with masks, although recognizing disgust is more challenging. Additionally, following both positive and negative affective state priming promoted systematic inaccuracies in emotion recognition. Most significantly, results showed a negative bias for children in negative affective state and a positive bias for those in positive affective state. Discussion: Children's affective state significantly influenced their emotion recognition abilities; sad affective states led to lower recognition overall and a bias toward recognizing sad expressions, while happy affective states resulted in a positive bias, improving recognition of happiness, and affecting how emotional neutrality and sadness were actually perceived. In conclusion, this study sheds light on the intriguing dynamics of how face masks affect children's emotion recognition, but also underlines the profound influence of their affective state.

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Brief exercise bouts can have positive effects on the affective state, which in turn could affect the intention for future exercise. Such benefits may be enhanced by manipulating expectations. The aim of this study was to examine whether the affective state after physical activity or the intention for future exercise can be influenced by manipulating expectations. Furthermore, the relationship between affect and intention was investigated. In an online experiment, 121 persons completed either a 10-minute workout (PA), a workout after manipulation of expectations (PA + EM), or a control intervention (CG) after randomized group allocation. Data on affective state, expectations, and intention were collected before and after the intervention using questionnaires. After intervention, PA groups showed significantly more positive values than CG in several affective parameters, in other affective parameters, only PA + EM differed from CG. Affect was positively associated with intention alongside outcome expectations. No difference was found in intention. Although no significant effects of expectation manipulation on affective state or intention were found, latent effects cannot be ruled out. Further exploration of the importance of word choice in describing physical activity in the context of interventions to increase physical activity is necessary. Here, affect should be considered.

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Robots are becoming an increasingly important part of our society and have started to be used in tasks that require communicating with humans. Communication can be decoupled in two dimensions: symbolic (information aimed to achieve a particular goal) and spontaneous (displaying the speaker's emotional and motivational state) communication. Thus, to enhance human-robot interactions, the expressions that are used have to convey both dimensions. This paper presents a method for modelling a robot's expressiveness as a combination of these two dimensions, where each of them can be generated independently. This is the first contribution of our work. The second contribution is the development of an expressiveness architecture that uses predefined multimodal expressions to convey the symbolic dimension and integrates a series of modulation strategies for conveying the robot's mood and emotions. In order to validate the performance of the proposed architecture, the last contribution is a series of experiments that aim to study the effect that the addition of the spontaneous dimension of communication and its fusion with the symbolic dimension has on how people perceive a social robot. Our results show that the modulation strategies improve the users' perception and can convey a recognizable affective state.

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PURPOSE: To examine the relative importance of social cognitive predictors (ie, performance accomplishment, vicarious learning, verbal persuasion, affective state) on health promotion self-efficacy among older adults during COVID-19. DESIGN: Cross-sectional. SETTING: Data collected online from participants in British Columbia (BC), Canada. SUBJECTS: Seventy-five adults (n = 75) aged ≥65 years. MEASURES: Health promotion self-efficacy was measured using the Self-Rated Abilities for Health Practices Scale. Performance accomplishment was assessed using the health directed behavior subscale of the Health Education Impact Questionnaire; vicarious learning was measured using the positive social interaction subscale of the Medical Outcomes Survey - Social Support Scale (MOS-SSS); verbal persuasion was assessed using the informational support subscale from the MOS-SSS; and affective state was assessed using the depression subscale from the Depression Anxiety Stress Scale (DASS-21). ANALYSIS: Multiple linear regression was used to investigate the relative importance of each social cognitive predictor on self-efficacy, after controlling for age. RESULTS: Our analyses revealed statistically significant associations between self-efficacy and performance accomplishment (health-directed behavior; ß = .20), verbal persuasion (informational support; ß = .41), and affective state (depressive symptoms; ß = -.44) at P < .05. Vicarious learning (ß = -.15) did not significantly predict self-efficacy. The model was statistically significant (P < .001) explaining 43% of the self-efficacy variance. CONCLUSION: Performance accomplishment experiences, verbal persuasion strategies, and affective states may be the target of interventions to modify health promotion self-efficacy among older adults, in environments that require physical and social distancing.

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This crossover randomized controlled trial examined the acute psychological effects of a bout of moderate-intensity continuous aerobic exercise (MICE) and a bout of high-intensity functional exercise (HIFE), relative to a no-exercise sedentary control (SED), in participants (N = 21; 15 f; 24.7 ± 9.3 years) with subsyndromal post-traumatic stress disorder (PTSD). Affective state (Energy, Tiredness, Tension, Calmness) was assessed before (Pre), immediately after (Post 0), 20-min after (Post 20), and 40-min after (Post 40) each condition. Affective valence was assessed during each condition, and exercise enjoyment was assessed at Post 0. Enjoyment was significantly greater following HIFE and MICE relative to SED. Energy was significantly increased Post 0 HIFE and MICE but decreased Post 0 SED. Tension was reduced following all conditions and was significantly lower at Post 40 relative to Pre for HIFE, MICE, and SED. Tiredness was significantly reduced at Post 40 relative to Pre following MICE only, while Calmness was significantly lower at Post 40 relative to Pre following MICE and SED. Overall, both exercise conditions were enjoyed to a greater extent than the control, but MICE may provide greater psychological benefits with respect to Calmness and Tiredness. This study is among the first to assess acute changes in affective states relative to various exercise modes in individuals living with subsyndromal PTSD.

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[This corrects the article DOI: 10.3389/fvets.2024.1366933.].

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Transcranial direct current stimulation (tDCS) targeting the prefrontal cortex has emerged as a valuable tool in psychiatric research. Understanding the impact of affective states, such as stress at the time of stimulation, on the efficacy of prefrontal tDCS is crucial for advancing tDCS interventions. Stress-primed tDCS, wherein stress is used as a priming agent, has the potential to modulate neural plasticity and enhance cognitive functions, particularly in emotional working memory. However, prior research using stress-primed tDCS focused solely on non-emotional working memory performance, yielding mixed results. In this sham-controlled study, we addressed this gap by investigating the effects of stress-primed bifrontal tDCS (active versus sham) on both non-emotional and emotional working memory performance. The study was conducted in 146 healthy individuals who were randomly assigned to four experimental groups. The Trier Social Stress Test (TSST) or a control variant of the test was used to induce a stress versus control state. The results showed that stress priming significantly enhanced the effects of tDCS on the updating of emotional content in working memory, as evidenced by improved accuracy. Notably, no significant effects of stress priming were found for non-emotional working memory performance. These findings highlight the importance of an individual's prior affective state in shaping their response to tDCS, especially in the context of emotional working memory.

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PURPOSE: Non-verbal utterances are an important tool of communication for individuals who are non- or minimally-speaking. While these utterances are typically understood by caregivers, they can be challenging to interpret by their larger community. To date, there has been little work done to detect and characterize the vocalizations produced by non- or minimally-speaking individuals. This paper aims to characterize five categories of utterances across a set of 7 non- or minimally-speaking individuals. METHODS: The characterization is accomplished using a correlation structure methodology, acting as a proxy measurement for motor coordination, to localize similarities and differences to specific speech production systems. RESULTS: We specifically find that frustrated and dysregulated utterances show similar correlation structure outputs, especially when compared to self-talk, request, and delighted utterances. We additionally witness higher complexity of coordination between articulatory and respiratory subsystems and lower complexity of coordination between laryngeal and respiratory subsystems in frustration and dysregulation as compared to self-talk, request, and delight. Finally, we observe lower complexity of coordination across all three speech subsystems in the request utterances as compared to self-talk and delight. CONCLUSION: The insights from this work aid in understanding of the modifications made by non- or minimally-speaking individuals to accomplish specific goals in non-verbal communication.

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Stalls or crates are a very common type of housing used on pig farms that restrict an animal's movement. How this confinement impacts the animal's affective states is seldom investigated. We conducted a preference test over 7 days where trios of gilts (n = 10 trios, 27.4 ± 1.5 weeks old) had free access between individual self-locking stalls (~ 1.2 m2) and a shared open area allowing 2.8 m2/animal (71% of total area). Gilts had access to ad libitum feed and water both inside the crates and in the open area. After 7 days, personality traits of the animals were assessed with open field (OF) and novel object (NO) tests. Principal Component Analysis (PCA) yielded two main components, which we defined as Passivity and Engagement. The median time spent outside the crate was 95.2% as 21/29 of the gilts exhibited a significant preference for pen over crate during the 7-day trial (p < 0.05). Passivity had no relationship with time spent in the open area, but engagement during OF/NO was associated with less use of the open area (OR = 0.39, 95CI = [0.25, 0.60]). Interestingly, gilts were likely to spend less time in the open area at nighttime compared to daytime (Odds Ratio = 0.49, 95CI = [0.40, 0.60]), as well as experimental days passed (OR = 0.70, 95CI = [0.66, 0.73]). During the first daytime and nighttime, 1/29 and 2/29 animals preferred the crate respectively, whereas by the last daytime and nighttime 5 and 9 gilts preferred the crate respectively (p < 0.05). While both intrinsic (personality) and extrinsic (time of day, experimental day) factors appear to influence the gilt's housing preferences, most gilts significantly prefer an open area to a crate when free access is provided between the two. A smaller subpopulation of animals developed a preference for stalls but still utilize both the stall and the pen throughout the day.

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This review discusses how welfare scientists can examine vocalizations to gain insight into the affective states of individual animals. In recent years, researchers working in professionally managed settings have recognized the value of monitoring the types, rates, and acoustic structures of calls, which may reflect various aspects of welfare. Fortunately, recent technological advances in the field of bioacoustics allow for vocal activity to be recorded with microphones, hydrophones, and animal-attached devices (e.g., collars), as well as automated call recognition. We consider how vocal behavior can be used as an indicator of affective state, with particular interest in the valence of emotions. While most studies have investigated vocal activity produced in negative contexts (e.g., experiencing pain, social isolation, environmental disturbances), we highlight vocalizations that express positive affective states. For instance, some species produce vocalizations while foraging, playing, engaging in grooming, or interacting affiliatively with conspecifics. This review provides an overview of the evidence that exists for the construct validity of vocal indicators of affective state in non-human mammals. Furthermore, we discuss non-invasive methods that can be utilized to investigate vocal behavior, as well as potential limitations to this line of research. In the future, welfare scientists should attempt to identify reliable, valid species-specific calls that reflect emotional valence, which may be possible by adopting a dimensional approach. The dimensional approach considers both arousal and valence by comparing vocalizations emitted in negative and positive contexts. Ultimately, acoustic activity can be tracked continuously to detect shifts in welfare status or to evaluate the impact of animal transfers, introductions, and changes to the husbandry routine or environment. We encourage welfare scientists to expand their welfare monitoring toolkits by combining vocal activity with other behavioral measures and physiological biomarkers.

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Affective state encompasses emotional responses to our physiology and influences how we perceive and respond within our environment. In affective disorders such as depression, cognitive adaptability is challenged, and structural and functional brain changes have been identified. However, an incomplete understanding persists of the molecular and cellular mechanisms at play in affective state. An exciting area of newly appreciated importance is perineuronal nets (PNNs); a specialised component of extracellular matrix playing a critical role in neuroprotection and synaptic plasticity. A scoping review found 24 studies demonstrating that PNNs are still a developing field of research with a promising general trend for stress in adulthood to increase the intensity of PNNs, whereas stress in adolescence reduced (potentially developmentally delayed) PNN numbers and intensity, while antidepressants correlated with reduced PNN numbers. Despite promising trends, limited research underscores the need for further exploration, emphasizing behavioral outcomes for validating affective states. Understanding PNNs' role may offer therapeutic insights for depression and inform biomarker development, advancing precision medicine and enhancing well-being.

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Background: Robots offer many unique opportunities for helping individuals with autism spectrum disorders (ASD). Determining the optimal motion of robots when interacting with individuals with ASD is important for achieving more natural human-robot interactions and for exploiting the full potential of robotic interventions. Most prior studies have used supervised machine learning (ML) of user behavioral data to enable robot perception of affective states (i.e., arousal and valence) and engagement. It has previously been suggested that including personal demographic information in the identification of individuals with ASD is important for developing an automated system to perceive individual affective states and engagement. In this study, we hypothesized that assessing self-administered questionnaire data would contribute to the development of an automated estimation of the affective state and engagement when individuals with ASD are interviewed by an Android robot, which will be linked to implementing long-term interventions and maintaining the motivation of participants. Methods: Participants sat across a table from an android robot that played the role of the interviewer. Each participant underwent a mock job interview. Twenty-five participants with ASD (males 22, females 3, average chronological age = 22.8, average IQ = 94.04) completed the experiment. We collected multimodal data (i.e., audio, motion, gaze, and self-administered questionnaire data) to train a model to correctly classify the state of individuals with ASD when interviewed by an android robot. We demonstrated the technical feasibility of using ML to enable robot perception of affect and engagement of individuals with ASD based on multimodal data. Results: For arousal and engagement, the area under the curve (AUC) values of the model estimates and expert coding were relatively high. Overall, the AUC values of arousal, valence, and engagement were improved by including self-administered questionnaire data in the classification. Discussion: These findings support the hypothesis that assessing self-administered questionnaire data contributes to the development of an automated estimation of an individual's affective state and engagement. Given the efficacy of including self-administered questionnaire data, future studies should confirm the effectiveness of such long-term intervention with a robot to maintain participants' motivation based on the proposed method of emotion estimation.

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BACKGROUND: In recent decades, numerous studies have investigated the effects of transcranial direct current stimulation (tDCS) on cognitive functioning. However, results of these studies frequently display inconsistency and pose challenges regarding replicability. The present work aimed at testing the hypothesis of mood as potential moderator of prefrontal tDCS effects on executive functions (EF). This hypothesis refers to the relationship between mood and EF, as well as to the association of mood with the dorsolateral prefrontal cortex (dlPFC) activity. METHODS: We conducted a meta-analysis of 11 articles where the dlPFC was stimulated with anodal tDCS, EF were measured, and mood was assessed prior to the stimulation. We then conducted a meta-regression to examine whether mood moderated the tDCS effects on EF. RESULTS: While no significant effect of tDCS on EF emerged from the meta-analysis, the meta-regression indicated that mood plays a significant role as moderator, with greater tDCS effects on EF in individuals with higher depressive symptoms. LIMITATIONS: The limited number of studies included, the heterogeneous samples considered, and the limited generalizability to other non-invasive brain stimulation techniques and affective states. CONCLUSIONS: Findings suggest that evaluating mood prior to stimulation could increase the sensitivity and specificity of tDCS application, and provide the first meta-analytic evidence in favor of the affective state-dependency hypothesis.

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Affective states are long lasting mood states resulting from an accumulation of experiences. The knowledge of the affective state of animals can significantly help maintain and/or increase animal welfare. The aim of the study was to recognize the affective state of 13 adult rams reared under an intensive system and to further associate their affective state with hierarchy, sociability order and maintenance and social behaviour. The affective state was estimated by exposing them to an attention bias test and two novel object tests. Individuals with negative affective states performed reduced head hanging (p = 0.014), reduced agonistic behaviour (p = 0.033), increased social proximity (p = 0.009) and received less affiliative behaviours (p = 0.006). The study estimated the affective state of the rams and indicated easily recognizable maintenance and social behaviours correlated with negative affective state. Such behaviours could increase the awareness of the animals' welfare and thus improve management practices.

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Background: Although motivational interviewing was originally developed to address abuse disorders, scientific evidence confirms that it is an increasingly used and effective approach in a wide range of therapeutic interventions. To date, however, no studies have analyzed the use of this tool in patients with persistent symptoms following coronavirus disease 2019, a condition known as Long COVID. Purpose: To analyze the effectiveness of motivational interviewing with regard to the adherence to telerehabilitation for Long COVID using a mobile application. As a secondary objective, factors related to greater motivation before and after the motivational interviewing techniques were analyzed. Patients and Methods: This longitudinal design substudy used a sample of 52 adult patients with Long COVID participating in the intervention group of a randomized clinical trial. This trial examined the effectiveness of a telerehabilitation program for this population using a mobile application. This program included three motivational interviews to achieve maximum treatment adherence. In this study, the main variables were motivation and adherence to application use. Sociodemographic and clinical data, personal constructs, and affective state were also collected. Subsequently, a descriptive, correlational, and regression statistical analysis was performed using the SPSS Statistics program. Results: The median motivation prior to the first motivational interview was 8 (IQR 2), the median at the end of the last motivational interview was 8.5 (IQR 2.75), and the change in motivation levels after the three motivational interviews was 0.5 (IQR 1). Affective state and final motivation scores were predictors of greater adherence to telerehabilitation treatment. Conclusion: A high level of motivation after participating in motivational interviewing appears to be related to higher levels of adherence to telerehabilitation in patients with Long COVID. This suggests that motivational interviewing may be an effective tool in the treatment of this disease.