ISSN 2215-3535

Actualidades en Psicología, 39 (138), January-June, 2025, 1-XX

https://doi.org/10.15517/ap.v39i138.54969

Esta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.

www.revistas.ucr.ac.cr/index.php/actualidades

Universidad de Costa Rica

A Pilot Study of Obesity Management: Contributions of

Cognitive-Behavioral Group Therapy to Stress, Anxiety,

and Emotional Eating

Un Estudio Piloto sobre el Manejo de la Obesidad: Contribuciones de la Terapia

Cognitivo-Conductual Grupal al Estrés, la Ansiedad y la Alimentación Emocional

Andressa Paiva Porto 1

https://orcid.org/0000-0003-4907-9533

Livia Nascimento Rabelo 2

https://orcid.org/0000-0001-9291-7569

Ezequiel Batista do Nascimento 3

https://orcid.org/0000-0002-5844-8524

1 Psychology Department, Centro Universitário Católica do Rio Grande do Norte, Brazil

2 Graduate Program in Psychobiology, Universidade Federal do Rio Grande do Norte, Brazil

3 Psychology Department, Health Sciences Center, Universidade Federal do Sul da Bahia, Brazil

1 andressapaiva_@hotmail.com 2 livia.rabelo@edu.isd.org.br 3 ezequiel.nascimento@ufsb.edu.br

Received: 23/06/2023. Accepted: 04/12/2025.

Abstract. Objetive.Cognitive-Behavioral Group Therapy (CBGT) is a group approach that assesses the interconnec-

tions between thoughts, emotions, and behaviors in a group setting. This study aimed to assess the feasibility and

preliminary eectiveness of a CBGT protocol focused on emotion regulation, in reducing emotional reactivity and

its potential impact on components of emotion-driven eating behaviors. Method. Twenty participants underwent an

8-week intervention, with half receiving psychoeducational intervention and the other half receiving CBGT with a

focus on emotional regulation. We used questionnaires to assess anxiety and eating behavior, and we measured psy-

chophysiological changes through cortisol levels and heart rate variability. Results. After six weeks, the CBGT group

had lower scores for emotional and uncontrolled eating, along with an increase in parasympathetic modulation and

a decrease in cortisol levels. These results suggest that CBGT may hold potential for improving emotional regulation

and reducing emotion-based eating behavior; however, further research is needed to conrm its eectiveness.

Keywords. Eating Behavior, Anxiety, Stress, Group Therapy, Obesity

Resumen. Objetivo. La Terapia Cognitivo-Conductual Grupal (TCCG) es un enfoque grupal que evalúa las intercone-

xiones entre pensamientos, emociones y comportamientos en un entorno grupal. Este estudio tuvo como objetivo

evaluar la viabilidad y la efectividad preliminar de un protocolo de TCCG enfocado en la regulación emocional, en la

reducción de la reactividad emocional y su posible impacto en los componentes de los comportamientos alimen-

tarios impulsados por las emociones. Método. Veinte participantes se sometieron a una intervención de 8 semanas,

con la mitad recibiendo una intervención psicoeducativa y la otra mitad recibiendo TCCG con un enfoque en la re-

gulación emocional. Utilizamos cuestionarios para evaluar la ansiedad y el comportamiento alimentario, y medimos

cambios psicosiológicos a través de niveles de cortisol y variabilidad de la frecuencia cardíaca. Resultados. Después

de seis semanas, el grupo de TCCG presentó puntuaciones más bajas en la alimentación emocional y descontrolada,

junto con un aumento en la modulación parasimpática y una disminución en los niveles de cortisol. Conclusión: Estos

resultados sugieren que la TCCG puede tener potencial para mejorar la regulación emocional y reducir el comporta-

miento alimentario basado en emociones; sin embargo, se necesita más investigación para conrmar su efectividad.

Palabras clave. Primera Ayuda Psicológica, voluntarios, empatía, estrategias de afrontamiento.

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

Introduction

The number of overweight individuals has signifi-

cantly increased in the past decade, and this rise can

be attributed to a combination of genetic, lifestyle,

and eating-related factors (Murray et al., 2020). With

respect to this, the World Health Organization (WHO,

2024) reported that in 2022, approximately 43% of

the global adult population was classified as overwei-

ght, and 16% was living with obesity. Consequently,

overweight and obesity are currently recognized as a

risk factor for the onset of physical illness and mental

disorders and a public health issue of pandemic pro-

portions (Dassen et al., 2018; Leutner et al., 2023).

Primary clinical evidence indicates that both obe-

sity and overweight are linked to elevated glucose

levels, which exacerbate adipose tissue dysfunction.

This dysfunction exacerbates insulin resistance, pro-

motes weight gain, and results in metabolic dysfunc-

tion and inflammatory responses. These changes can

be initiated in the overweight condition and become

more pronounced in obesity, with obesity represen-

ting a more severe stage (Barbosa & Carvalho, 2023;

Lafortuna et al., 2017). Accumulation of adipose tis-

sue is acknowledged as a complex condition. Evi-

dence indicates the interaction of genetic, hormonal,

behavioral, and lifestyle factors, alongside an obe-

sogenic environment and cognitive and emotional

response (Bose et al., 2009; Dallman, 2010; Kollei et

al., 2018; Silva, 2015).

Beyond the well-established physical heal-

th factors extensively discussed in the literature on

overweight and obesity, cognitive and emotional

components have emerged as critical elements in

explaining obesogenic behaviors. These factors not

only contribute to the etiology of increased adipose

tissue accumulation but also pose significant cha-

llenges for long-term treatment, particularly in the

management of glucose glycemic control, weight

maintenance, and the increase in weight regain (Ra-

man et al., 2013, 2020).

The relationship between emotional responses

and eating behavior is explained by theoretical mo-

dels that link cognitive and emotional vulnerabilities

to human eating patterns. From this perspective,

cognitive and emotional factors interact, demonstra-

ting that individuals under stress, particularly those

with emotional dysregulation, may exhibit eating

behaviors inuenced by emotions, disinhibition, and

cognitive biases. These behaviors often serve as co-

ping mechanisms in distressing situations (Kollei et

al., 2018; Van Strien et al., 2014). The cognitive and

emotional components predicted in the concept of

human eating behavior, including cognitive control,

disinhibition, and emotional eating, are indeed the

focus of one of the most generally recognized hypo-

theses about the relationship between emotion and

eating behavior (Arexis et al., 2023).

Emotional eating refers to the excessive con-

sumption of food in response to negative emo-

tions or stress, serving as a coping mechanism

where highly palatable foods alleviate psycholo-

gical distress (Bilici et al., 2020). In contrast, cog-

nitive restriction involves the mental eort to limit

food intake to control eating behavior (Aoun et al.,

2019). Disinhibited eating is marked by overeating

in response to external food cues, driven by their

salience and reduced self-regulation (Esteves et al.,

2012). While these eating behaviors are often con-

sidered non-psychopathological, they can become

dysfunctional when associated with emotional di-

culties or stress-related disorders, such as anxiety,

depression, and eating disorders (Arexis et al., 2023;

Waller & Osman, 1998).

Stress appears to be a critical factor as it inuen-

ces emotional regulation and facilitates the occu-

rrence of unhealthy eating behaviors, such as in-

creased emotional eating and reward-driven eating

(Verdejo-Garcia et al., 2019). In obesogenic environ-

ments, stress can often result in an increase in the

consumption of hyperpalatable foods, which tem-

porarily alleviate distress but reinforce unhealthy

eating patterns and weight gain (Leigh et al., 2018;

Yau & Potenza, 2013).

Stress conditions may increase individuals’ pre-

ference for hyperpalatable and comfort foods, as

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

compared to eutrophic weight controls (Strüven et

al., 2021; Yadav et al., 2017).

Michopoulos et al. (2015) investigated the link

between emotional dysregulation and eating pat-

terns in obese children, nding that childhood trau-

ma contributes to emotional dysregulation, which,

in turn, inuences emotional eating behaviors.

Neurological evidence from functional magnetic

resonance imaging (fMRI) studies revealed increa-

sed limbic activity and negative emotions associa-

ted with anticipatory well-being responses to food

consumption in women, a phenomenon absent in

those with neutral or positive mood states (Bohon

et al., 2009). These ndings suggest that emotional

eating activates reward pathways as a compensa-

tory response to emotional distress (Volkow et al.,

2011). Supporting this, Chua et al. (2004) found

that melancholic-themed lms increased negative

emotions and food consumption in 42 participants.

Similarly, a meta-analysis of 33 studies with 2491

participants conrmed a direct correlation between

negative emotional states and increased food in-

take (Cardi et al., 2015).

Conventional treatments for managing overwei-

ght and obesity, such as dietary counseling and

physical activity recommendations, often show li-

mited long-term ecacy (Baker et al., 2022; Dansin-

ger et al., 2007; Wadden et al., 2020). This limitation

is largely attributed to their inability to address the

emotional and behavioral factors underlying eating

patterns. Emotional dysregulation and maladaptive

responses to stress are key contributors to overea-

ting and weight gain, yet they remain unaddressed

in many traditional interventions.

Cognitive-Behavioral Therapy (CBT) is a promi-

sing approach for managing overweight and obesi-

ty by targeting emotional regulation and modifying

eating behaviors. It promotes adherence to healthy

lifestyle changes and addresses the psychological

and emotional factors underlying obesogenic be-

haviors (Cha et al., 2020). Among CBT methods,

Cognitive-Behavioral Group Therapy (CBGT) stands

out as an eective, evidence-based intervention for

emotional distress can trigger the consumption of

such foods as a coping mechanism, activating reward

pathways to alleviate emotional distress (Leigh et

al., 2018; Sominsky & Spencer, 2014). Neurobiologi-

cal evidence links these behaviors to alterations in

hypothalamic-pituitary-adrenal (HPA) axis reactivity,

potentially inuencing the lateral hypothalamic area

(LHA) to promote ghrelin-mediated consumption

of sugar- and fat-rich foods. Additionally, the ven-

tral tegmental area (VTA) is implicated in enhancing

reward-seeking behaviors through increased dopa-

minergic transmission (Linders et al., 2022; Rebello &

Greenway, 2016). Clinical studies further support this

model, showing that cortisol secretion and sensitivity

are associated with increased adipose tissue accu-

mulation in overweight and obese patients compa-

red to eutrophic individuals (Lengton et al., 2022;

Martens et al., 2021).

The stress reaction is directly correlated with

emotional expression. A set of psychophysiological

and behavioral changes occurs when individuals face

stressors, preparing the organism to cope with and

adapt to challenging situations. However, when the

stressor persists, it leads to allostatic overload, initia-

lly characterized by an imbalance in the autonomic

nervous system (ANS), with increased sympathetic

activity and reduced parasympathetic regulation.

This imbalance contributes to the maintenance

of a state of emotional distress and predisposes

individuals to emotional dysregulation and anxie-

ty-related conditions (Bian et al., 2022; Candia-Ri-

vera et al., 2023). ANS dysfunction, particularly in

psychiatric disorders, is often observed through

alterations in heart rate variability (HRV). This mea-

sure provides insights into the sympathetic and pa-

rasympathetic branches of the ANS, which are cru-

cial for understanding stress reactivity and adaptive

emotional responses in mental health conditions

(Agorastos et al., 2023). In fact, clinical evidence ob-

served through HRV parameters suggests a sym-

pathovagal imbalance, characterized by heightened

sympathetic activity and reduced parasympathetic

modulation, in overweight and obese individuals

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

alleviating anxiety and improving emotional regu-

lation. CBGT is particularly eective in addressing

emotional eating and other maladaptive behaviors

by targeting cognitive and emotional vulnerabilities

(Chonthannathi et al., 2022; Malivoire et al., 2024;

Wittkamp et al., 2023). As a group-based therapy,

CBGT is also cost-eective, accessible, and scalable

for diverse healthcare settings, making it a practical

option for managing emotional and behavioral ea-

ting challenges

This pilot study aimed to assess the feasibility

and preliminary eectiveness of a CBGT protocol

focused on emotion regulation, in reducing emo-

tional reactivity and its potential impact on com-

ponents of eating behavior. To achieve this, we as-

sessed the stress response through salivary cortisol

levels and sympathetic/parasympathetic balance, as

indicators of emotional dysregulation. Additionally,

the study explored the relationship between emo-

tional states and emotion-driven eating behaviors,

hypothesizing that improvements in emotional re-

gulation would be associated with positive changes

in eating behavior components. To evaluate the e-

cacy of the protocol, participants were divided into

two groups: an intervention group, which received

CBGT focused on emotion regulation, and a control

group, which attended psychoeducational sessions

addressing general dietary and health behaviors.

Method

Participants

A power analysis was conducted using G*Power

(version 3.1.9) to estimate the required sample size

for this pilot study, which focused on methodology

and feasibility for preliminary data collection (Lan-

caster et al., 2004). Using an estimated power of

90%, an alpha level of 5%, and an effect size of .8,

the minimum sample size required was determined

to be N = 8 per group (Critical F = 5.31). Therefore,

the sample size of N = 10 per group used in this

study exceeds the minimum requirement, ensuring

that the study hypothesis could be adequately tes-

ted while maintaining the exploratory nature of pi-

lot studies.

Participants were recruited through social media

advertisements and posters in health clinics. A total

of 22 volunteers (10 females and 12 males) expres-

sed interest and attended an initial session to recei-

ve study information and undergo screening. Inclu-

sion criteria included being aged 18–60, having a

BMI of 30 or greater, difficulty losing weight, and no

history of eating disorders, depressive symptoms,

or psychotropic medication use. All 22 volunteers

met the criteria and were randomly assigned to ei-

ther the control group (n = 10) or the CBGT group

(n = 12). Both groups participated in a baseline data

collection session. During the intervention, dropout

criteria included starting weight loss medication,

missing three consecutive sessions, or developing a

physical or psychiatric condition. Two participants in

the CBGT group were withdrawn for missing three

consecutive sessions, leaving a final follow-up sam-

ple of 20 participants: 10 in the control group and

10 in the CBGT group (Figure 1). After completing

the study, control group participants were invited to

join the CBGT clinical protocol.

Ethical Aspect

This study was approved by the Ethics

Committee of Universidade Potiguar (CAAE:

00336818.8.0000.5296, Nº 2.955.998) and conduc-

ted in accordance with the guidelines of the Natio-

nal Ethics Committee (CONEP) and the principles

outlined in the Declaration of Helsinki. Participants

were fully informed about the study’s objectives,

potential benets, and risks before their participa-

tion. All participants signed an Informed Consent

Form, ensuring their understanding and voluntary

agreement to take part in the research.

Clinical Screening

Clinical Interview

To determine eligibility based on inclusion crite-

ria, all volunteers participated in a session conduc-

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

Figure 1. Flowchart illustrating the recruitment, randomization, and follow-up of

participants in the intervention and control group

Note. Flowchart illustrating the recruitment, randomization, intervention, and follow-up process for participants. A

total of 22 participants were recruited, all of whom met the inclusion criteria. Participants were randomly assigned to

the control group (n = 10) or the intervention group (n = 12). During the intervention stage, 2 participants from the

intervention group were removed based on dropout criteria, resulting in a nal analyzed sample of 20 participants.

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

deiros et al. (2017). The Brazilian version replicated

the hypothetical model with good fit indices (χ²/df

= 2.24, CFI = .97, TLI = .96, and RMSEA = .05), as

observed in confirmatory factor analyses. Additio-

nally, reliability was assessed using Cronbach’s al-

pha, demonstrating adequate internal consistency

for the three domains (UE: α = .83, EE: α = .92, and

CR: α = .83). This measure was designed to assess

the participants’ eating behaviors.

Beck Depression Inventory (BDI-II)

A self-report instrument consisting of 21 ques-

tions designed to assess depression symptoms in

adults (Beck et al., 1996). For the Brazilian popula-

tion version, the Cronbach’s alpha coefficient for

this instrument in the community sample was .93,

indicating a high level of internal consistency (Go-

mes-Oliveira et al., 2012). It is suggested for people

between the ages of 17 and 80. Because the absen-

ce of depressive symptoms was one of the inclusion

criteria, this measure was used for screening and

eligibility purposes in the study, with a cutoff score

of >13 points indicating a clinical sample, according

to the instrument’s technical manual.

The State-Trait Anxiety Inventory (STAI)

The STAI is a self-report instrument common-

ly used to measure trait (STAI-T) and state anxiety

(STAI-S). It is frequently applied in clinical research

and settings to assess and diagnose anxiety-related

disorders (Spielberger, 2010). The two scales each

have 20 Likert scale items. The goal of this measure

was to assess the occurrence of anxious symptoms

in the current state as well as an anxiety-prone func-

tional prole. The instrument asks the participant to

describe how they feel “at this moment” to mea-

sure the emotional state factor, whereas the trait

factor considers the participant’s response to how

they “usually feel”. The Brazilian version used in this

study was based on the adaptation by Fioravanti et

al. (2006), which demonstrated good internal con-

sistency of the items analyzed using Cronbach’s Al-

pha, with a score of .89 for state anxiety (STAI-S), re-

ted by the research team and a clinical psycholo-

gist from the University Psychology Service-School.

During this session, a structured questionnaire was

initially administered, collecting sociodemographic

data and general information on physical health,

lifestyle, eating habits, sleep habits and medical his-

tory, with a particular focus on the clinical history

of obesity. Screening for the presence of previous

eating disorders, depressive disorders, and other

psychiatric conditions was performed using the

Structured Clinical Interview for DSM-5 (SCID-5-CV,

Osório et al., 2019). Additionally, the Beck Depres-

sion Inventory (BDI-II) was applied to precisely as-

sess depressive symptomatology.

Anthropometric Measurements

During the interview, anthropometric parame-

ters such as weight and height were measured to

calculate the Body Mass Index (BMI). The BMI was

calculated as BMI = W/H², where W represents the

participant’s current weight in kilograms and H² re-

presents the participant’s height in meters squared.

Weight was measured with an electronic scale and

height with a traditional stadiometer. We used the

eligibility criterion for BMI > 30.0kg/m² (obesity),

following the classication of the World Health Or-

ganization (Oliveira et al., 2012).

Instruments

The Three Factor Eating Questionnaire (TFEQ-R21)

The TFEQ-R21 is a globally recognized and revi-

sed instrument that is designed to evaluate compo-

nents of human eating behavior using the three-fac-

tor model: cognitive restraint (CR), emotional eating

(EE), and uncontrolled eating (UE). The scale con-

sists of 21 items on a Likert scale ranging from 1 to

4, with scores calculated on a scale ranging from 0

to 100 points and raw scores converted to percen-

tages. The revised questionnaire was proposed by

Tholin et al. (2005), and the Brazilian translation and

psychometric validation were conducted by De Me-

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

to assess autonomic nervous system (ANS) activity

through R-R interval analysis, allowing inferences

about the balance between the sympathetic nervous

system (SNS) and the parasympathetic nervous sys-

tem (PNS). Sympathetic modulation was evaluated

using SDNN (standard deviation of normal RR inter-

vals), which reflects overall heart rate variability with

sympathetic predominance, and LF (low frequency,

.04 - .15 Hz), which primarily reflects sympathetic ac-

tivity with minimal vagal influence. Parasympathetic

modulation was assessed using RMSSD (root-mean-

square of successive differences), reflecting short-

term PNS activity; PNN50 (percentage of adjacent

R-R intervals differing by more than 50 ms), which

indicates parasympathetic predominance; and HF

(high frequency, .15 - .4 Hz), a marker of vagal tone

that reflects parasympathetic activity (Table 1). Mea-

surements were conducted in a controlled, quiet en-

vironment during the pre-intervention and follow-up

sessions, prior to administering other instruments.

HRV parameters were selected based on existing li-

terature (Georgieva-Tsaneva, 2019; Hartmann et al.,

2019; Shaffer & Ginsberg, 2017).

Salivary cortisol concentrations

Salivary cortisol concentrations were measu-

ecting current worry states, and .88 for trait anxiety

(STAI-T), associated with a predisposition to anxious

thoughts and a stable mood state. Evidence for trait

anxiety was further tested by Andrade et al. (2001),

who observed that the STAI-T items consistently in-

fer a pattern of anxiety maintained by neuroticism

and a predisposition to mood-worrying dimension.

A daily record of food intake

The study implemented a self-monitoring food

diary for the CBGT group, a key strategy in weight

loss cognitive-behavioral therapy, to help parti-

cipants track cognitive patterns and emotions in-

fluencing eating behavior. A customized diary was

developed for recording meals, behaviors, emotions,

thoughts, motivations, binge episodes, and session

goals. It was incorporated as a qualitative self-mo-

nitoring tool, adapted from standard CBT guidelines

(Gormally et al., 1982; Lindgreen et al., 2018; Schuma-

cher et al., 2021; Wilson & Vitousek, 1999).

Heart rate variability measures

Following the standardization by Esco and Fla-

tt (2014), heart rate variability (HRV) was measured

using an ECG finger monitor (ithlete Ltd, Southamp-

ton, UK) for 15 minutes under resting conditions

Time Domain Parameters Units ANS analysis

SDNN Standard Deviation of N-N intervals ms SNS

rMSSD Root mean square of successive R-R interval ms PNS

PNN50 Percentage of successive RR intervals that differ by more

than 50 ms %SNS/PNS↑

Frequency Domain

HF Power of high-frequency range .15 Hz a .4 Hz % PNS

LF Power of low-frequency range .04 HZ a .15 HZ % SNS

Note. This table presents heart rate variability (HRV) parameters analyzed in the time and frequency domains. SDNN

reects overall variability (SNS), rMSSD and HF indicate parasympathetic activity (PNS), and PNN50 represents a

balance between SNS and PNS. LF reects sympathetic activity (SNS), corresponding to the low-frequency range (.04

- .15 Hz), while HF corresponds to the high-frequency range (.15 - .4 Hz) and parasympathetic activity (PNS).

Table 1. Heart rate variability assessment parameters for time and frequency domains

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

to attend weekly sessions but were not informed

about their group allocation.

The CG received an eight-session intervention

with a script of activities centered on psychoedu-

cation in thematic areas linked to an emotional re-

action, emotional eating, and healthy eating beha-

viors. Following that, six weeks after the previous

meeting, follow-up data were collected.

In the CBGT group, the intervention performed

was cognitive-behavioral psychotherapy focused

on emotional regulation and elements of cognitive

restructuring, with eight weekly meetings, lasting

two hours each, and pre-established interventions.

The intervention was structured into sessions orga-

nized around thematic axes, focusing on psychoe-

ducation, cognitive restructuring, skills training, and

strategies for recognizing, monitoring, and ma-

naging situations related to emotions and eating

behaviors. The sessions included skills training for

emotional regulation, behavioral techniques such

as graduated exposure and behavioral activation,

as well as relapse prevention strategies (Table 2).

Techniques and activities were adapted from die-

rent protocols focused on emotional regulation and

stress management to meet the specic needs of

the participants (Castelnuovo et al., 2017; Guerrini

Usubini et al., 2022; Neufeld et al., 2021; Saranapala

et al., 2022; Torres et al., 2020).

The study opted to collect data on psychophy-

siological measures and self-reported measures of

anxiety and eating behavior 6 weeks after the inter-

vention. This decision was made to observe long-

term eects while avoiding the immediate impact of

the therapeutic intervention on these measures and

minimizing potential bias associated with post-in-

tervention eects (Clarke et al., 2018).

Statistical Analysis

The Kolmogorov-Smirnov test was used to de-

termine the data’s normality. Data from the Three

Factor Eating Questionnaire - R21 (TFEQ-R21) as-

sessments, the State-Trait Anxiety Inventory (STAI),

heart rate variability, and circulating cortisol con-

red before the intervention and 6 weeks later (fo-

llow-up). Participants were instructed to collect sa-

liva immediately upon awakening in the morning,

no later than 8:00 a.m., to assess baseline corti-

sol concentrations upon awakening. Participants

were also advised not to drink, eat, or brush their

teeth for at least 60 minutes prior to collection.

Saliva samples were collected in Salivette® tu-

bes (Sarstedt, Germany) and stored at -80°C until

analysis. Before analysis, samples were centrifu-

ged at 10,000g for 20 minutes, and cortisol con-

centrations were determined using a commercia-

lly available kit (DSL-10-671000 ACTIVE® cortisol

enzyme immunoassay – EIA). This study opted to

assess baseline morning cortisol as a practical and

reliable measure of stress response. Interventions

affecting stress or basal HPA axis functioning are

often associated with flatter cortisol slopes, which

can be evaluated using waking morning salivary

cortisol levels (Adam & Kumari, 2009). The 6-week

gap for salivary cortisol measurement was imple-

mented to minimize potential acute influences of

the intervention on this parameter.

Procedures

After screening and obtaining participants’ con-

sent, a second data collection session was schedu-

led. Participants received the salivary cortisol collec-

tion kit along with general instructions for proper

sample collection and information regarding the

scheduled data collection session. On the designa-

ted day, the salivary cortisol samples were checked,

and individual data collection sessions were con-

ducted according to a predened schedule. The

data collection process began with the assessment

of heart rate variability, followed by the application

of the anxiety scale and the eating behavior ques-

tionnaire. Participants were then randomly divided

into two groups: a control group (CG), which fo-

cused on psychoeducation, and a Cognitive-Be-

havioral Group Therapy (CBGT) group focused on

emotional regulation. Participants were instructed

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

Session Theme Techniques

01 - Group presentation, objectives, and the therapeutic

contract

- Introduction to Cognitive-Behavioral Group Therapy

- Presentation of the daily food intake record

- Psychoeducation

- Socratic questioning

- Daily record of food intake

02 - Cognitive-Behavioral Model of Eating Behaviors

- Stress and obesity

- Psychoeducation

- Cognitive restructuring

- Guided discovery

03 - Distinction between losing weight and maintaining

weight

- Diculties losing weight

- Automatic negative thoughts

- Emotion regulation and stress coping

- Psychoeducation

- Cognitive restructuring

- ABC functional analysis

- Reframe negative thoughts

- Guided discovery

04 - Core and Intermediate Beliefs - Psychoeducation

- Cognitive restructuring

- ABC functional analysis

- Reframe negative thoughts

- Guided discovery

05 - Cognitive Behavioral Approach to Emotional Eating - Psychoeducation

- ABC functional analysis

- Daily record of food intake

- Guided discovery

06 - Recognizing and Managing Emotions

- Emotional regulation and emotional eating

- Relaxation and stress reduction techniques

- Fact-checking

- Successive approximation

- Mindfulness eating

- The downward arrow

07 - The role of healthy habits (physical activity, coping

with stress, and nutritional education)

- Relapse prevention strategies

- Psychoeducation

- Coping cards

- Fact-checking

- Mindfulness eating

- Fact-checking

08 - Ending stage of the group and feedback - Feedback

Note. The intervention protocol was conducted over 8 consecutive weeks, with each session structured around

specic themes and corresponding cognitive-behavioral techniques.

Table 2. Description of the intervention performed in the experimental group (CBGT)

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

domain indicated a group eect [F(1,18) = 7.285, p

= .01, ηp

2 = .28], a session eect [F(1,14) = 31.277,

p = .001, ηp

2 = .69], and a group × session inte-

raction eect [F(1,14) = 6.39, p = .02, ηp

2 = .44]. A

post-hoc Tukey correction applied to the group ×

session interaction eect revealed that the control

and CBGT groups did not dier statistically at ba-

seline. However, post-hoc analysis revealed that

the CBGT group showed a signicant reduction in

EE scores during the follow-up compared to their

baseline scores. Additionally, when comparing EE

scores between the CBGT and control groups at

the follow-up phase, the CBGT group demonstra-

ted lower scores, indicating that participants who

underwent the emotional regulation intervention

reported improvements in emotion-based eating

behavior (see Table 3).

The statistical analysis for the domain of uncon-

trolled eating (UE) found no group eect [F(1,18) =

0.54, p = .40], but did nd a session eect [F(1,18) =

20.52, p = .002, ηp

2 = .52] and a group × session inte-

raction eect [F(1,18) = 13.50, p = .001; ηp

2 = .42]. The

post-hoc Tukey test for group × session interaction

demonstrated that the CBGT group signicantly re-

duced self-reported UE scores when comparing fo-

centrations were then examined using repeated

measurements. To support the assumption of equal

variance of dierences between conditions, ANO-

VA and Mauchly’s sphericity test were performed.

Partial eta squared (ηp2) was used to calculate the

size of the eect. The reference values for eect size

in this study were classed as small (.20), moderate

(.50), and large (.80; Cohen, 1988).

Using scores from the TFEQ-R21 instrument,

multiple linear regression models were used to

examine the post-intervention predictive eect of

salivary cortisol, sympathetic modulation (SDNN

and HF frequency parameters), and parasympathe-

tic modulation (rMSSD parameters, PNN50, and LF

frequency) on emotion-based eating behavior do-

mains. With a p-value of .05, all dierences were ju-

dged statistically signicant. Data are expressed as

Mean ± Standard Deviation (SD) or Standard Error

of the Mean (SEM). Statistica 7.0 for Windows was

used to execute statistical procedures.

Results

TFEQ-R21 (Three Factor Eating Question-

naire)

Statistical analysis of the emotional eating (EE)

Instruments Baseline (t = 0) Follow-up (t= 6 weeks)

CG CBGT pCG CBGT p

TFEQ-R21 EE 20.2 ± 2.1 20.5 ± 2.5 .901 18.4 ± 2,6 14.7 ± 1.8* .005

UE 23 ± 2.1 26.4 ± 4.9 .458 20 ± 2.4 16.2 ± 2.2* .001

CR 14.1 ± 2.6 12.8 ± 2.4 .677 17.8 ± 1.1* 18.5 ± 1.6* .001

STAI STAI-S 52.1 ± 3.7 45.2 ± 5.16 .102 44.4 ± 5.7 38.8 ± 4.6 .437

STAI-T 51.9 ± 3.5 53.2 ± 4.1 .912 50.8 ± 6.2 50.2 ± 3.6 .967

Note. Repeated measures ANOVA was used, followed by Tukey’s correction. Statistical signicance was set at *p < .005 for com-

parisons within the CBGT group and between the CBGT and control groups (CG) in EE scores 6 weeks post-intervention. For

UE scores, a signicant level of *p = .001 indicated statistical dierences when comparing the CBGT group at follow-up versus

baseline. Additionally, dierences in UE scores were observed between the CBGT and CG groups at follow-up. For CR scores,

a signicant level of *p = .001 indicated statistical dierences when comparing both groups at follow-up versus baseline. The p

values in the table represent the signicant levels for interaction eects in EE and UE, as well as session eects in CR. The data is

presented as mean ± SD.

Table 3. The anxiety and emotional eating behavior dimensions at baseline (t = 0)

and 6 weeks post-intervention (t = 6 weeks)

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

llow-up to baseline. Additionally, signicant dieren-

ces were observed when comparing the CBGT group

to the CG at the follow-up phase, indicating that the

reduction in UE scores was specically related to the

group that underwent the intervention focused on

emotional regulation (see Table 3).

The repeated measures ANOVA did not de-

monstrate a group eect [F(1,18) = 0.94, p = .34] or

a group × session interaction eect [F(1,18) = 1.56,

p = .22] in the analysis of the last domain, cogniti-

ve restraint (CR), but a session eect was detected

[F(1,18) = 38.12, p = .001, ηp

2 = .67]. As a result, a

change in this factor is proposed over the sessions

for both groups (see Table 3).

State-Trait Anxiety Inventory (STAI)

The STAI instrument was used in this study to

evaluate the eect of intervention on anxiety. Repea-

ted measures ANOVA revealed a signicant eect

of sessions on STAI-S [F(1,18) = 12.55, p = .001, ηp

= .41], but no signicant eects were observed for

groups [F(1,18) = 3.00, p = .10] or the group × ses-

sion interaction [F(1,18) = 0.65, p = .82]. These results

indicate that all participants, regardless of group, ex-

perienced a reduction in state anxiety following the

intervention. For STAI-T, no signicant eects were

found for groups [F(1,18) = 0.08, p = .77], sessions

[F(1,18) = 2.98, p = .10], or the group × session inte-

raction [F(1,18) = 0.84, p = .36, see Table 3].

Heart Rate variability

Heart rate variability measures were employed in

the study as an indicator of sympathetic/parasym-

pathetic modulation in emotional reaction. For the

time domain, considering the SDNN parameter,

the statistical analysis did not show any eect of

the group [F(1,14) = 0.08, p = .77], sessions [F(1,14)

= 0.19, p = .66], or groups × sessions interaction

[F(1,14) = 2.25, p = .15].

The statistical analysis of the rMSSD parameter

revealed no inuence of group [F(1,14) = 1.33, p =

.26], but it was able to notice an eect of sessions

[F(1,14) = 5.11; p = .04, ηp

2 = .26] and of groups

× sessions interaction [F(1,14) = 11.55, p = .004; ηp

= .45]. The Tukey post-hoc correction test revealed

that the CBGT group showed a statistically signi-

cant increase in the rMSSD parameter at follow-up

compared to baseline. Additionally, a higher rMSSD

was observed in the CBGT group compared to the

CG at follow-up, suggesting that this measure only

varied for the CBGT group (see Table 4).

In the evaluation of the PNN50 parameter, the

repeated measures ANOVA did not show a group

eect [F(1,14) = 0.06, p = .79], but a session eect

was observed [F(1,14) = 21.77, p = .001, ηp

2 = .57], as

well as a groups × sessions interaction eect [F(1,14)

= 10.95, p = .003, ηp

2 = .37]. For the group × session

interaction eect, the Tukey post-hoc correction test

revealed that the CBGT group was the only group to

show a signicant increase in this parameter at fo-

llow-up compared to baseline. Additionally, higher

PNN50 scores were observed in the CBGT group

compared to the CG at follow-up (see Table 4).

The parameters LF% and HF% were employed in

the study to evaluate frequency domains. For LF%, a

measure of the sympathetic modulation, the repea-

ted measures ANOVA revealed only a group eect

[F(1,14) = 10.04, p = .005, ηp

2 = .35], with no statisti-

cal dierences for the session eect [F(1,14) = 0.06,

p = .96], as well as the interaction between groups

and sessions [F(1,14) = 0.19, p = .66]. The data indi-

cate that the CBGT group had a higher frequency of

sympathetic modulation than expected by the LF%

parameter in general, although there was no decli-

ne during the sessions (see Table 4).

Regarding the parameter of HF%, an indicator of

parasympathetic modulation, statistical analysis re-

vealed a group eect [F(1,14) = 46.09, p = .001, ηp

= .71], a session eect [F(1,14) = 13.52, p = .001, ηp

= .42], and a group × session interaction [F(1,14) =

13.94; p = .001, ηp

2 = .42]. The Tukey correction test

observed a general increase in HF% for the CBGT

group. Furthermore, the test for the group × ses-

sion interaction eect revealed that the CBGT group

showed a signicant increase in HF% when compa-

ring follow-up to baseline. Additionally, higher HF%

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

Parameters Baseline (t = 0) Follow-up (t= 6 weeks)

CG CBGT pCG CBGT p

TIME

DOMAIN

SNS

modulation

SDNN 37.5 ± 6.4 36.2± 11.1 .310 34.3 ± 5.5 34.5 ± 4.3 .630

PNS

modulation

rMSSD 32.8 ± 3.8 29.2 ± 5.6 .803 30.5 ± 2.4 37.5 ± 5.4* .004

PNN50% 24.3 ± 2.9 17.3 ± 11.3 .227 26.8 ± 2.6 32.0 ± 8.9* .003

FREQUENCY

DOMAIN

SNS

modulation

LF% 53.1 ± 5.8 69.3 ± 11.8* .062 55.3 ± 7.5 66.4 ± 22.1* .005

PNS

modulation

HF% 32.2 ± 3.3 38.3 ± 8.7 .132 31.6 ± 3.8 55.6 ± 11.7* .001

Note. Repeated measures ANOVA followed by Tukey’s correction was used. For SDNN, no significant differences were observed.

For rMSSD, statistical significance was found (*p < .004) when comparing the CBGT group at follow-up versus baseline and CBGT

versus CG at follow-up. For PNN50%, significance was observed (*p < .001) when comparing the CBGT group at follow-up versus

baseline and CBGT versus CG at follow-up. For LF%, a group effect was observed, with generally higher LF% in the CBGT group

(*p < .005). For HF%, significant differences were observed (*p < .001) when comparing the CBGT group at follow-up versus

baseline and CBGT versus CG at follow-up. The p values in the table represent the level of significance for interaction effect

(rMSSD, PNN50%, and HF%) and group effect for LF%. All data are presented as mean ± SD.

Table 4. The parameters of heart rate variability at baseline (t = 0)

and 6 weeks after the intervention ended (t = 6 weeks)

was observed in the CBGT group compared to CG at

follow-up (see Table 4). These ndings suggest that

the increase in this parasympathetic modulation pa-

rameter occurred exclusively in the CBGT group.

Salivary Cortisol Levels

The study used repeated measures ANOVA to

evaluate the eect of treatment interventions on

waking basal cortisol expression. The analysis re-

vealed a signicant group eect [F(1,14) = 6.75, p

= .01, ηp

2 = .24], session eect [F(1,14) = 57.52; p

= .001; ηp

2 = .76], and group × session interaction

[F(1,14) = 35.56; p = .001; ηp

2 = .66]. Tukey’s post-hoc

correction indicated that the CBGT group showed

a statistically signicant reduction in cortisol levels

at follow-up compared to baseline, as well as when

compared to the CG at follow-up. This suggests

that only the CBGT group experienced a reduction

in waking basal cortisol expression during the wa-

king phase (see Figure 2).

The predictive eect of emotional response on

eating behavior

The study’s goal was to predict the ecacy of

therapy models on emotional response and its im-

pact on emotional-based eating behavior domains

(disinhibition and emotional eating). The predictive

inuence of basal cortisol and sympathetic and pa-

rasympathetic modulation was investigated using

multiple linear regression models.

Multiple-linear regression analysis for the con-

trol group revealed no predictive model of salivary

cortisol on the domains of uncontrolled and emo-

tional eating [F(1,8) = 0.043, p = .84, R2 = .05], nor a

predictive eect of sympathetic modulation [F(2,7)

= 3.40, p = .09, R2 = .49] or parasympathetic mo-

dulation [F(3,6) = 2.85, p = .12, R2 = .58]. As a result,

the multiple-linear regression models used in this

study could not predict the occurrence of uncon-

trolled and emotional eating behaviors. However,

a tendency toward sympathetic modulation was

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

Figure 2. DWaking salivary cortisol concentrations at baseline (t = 0)

and 6 weeks after the intervention ended (t = 6 weeks).

Note. Salivary cortisol concentrations for the control group (CG) and experimental group (CBGT) at base-

line and 6 weeks post-intervention. *p < .05 indicates a signicant reduction in cortisol levels for the CBGT

group at follow-up compared to baseline and versus the CG at follow-up. Only the CBGT group showed a

reduction in waking basal cortisol expression. All data expressed as Mean ± SEM.

Models Emotional eating

Model I (psychoeducation) βF p R2

Salivary Cortisol .251 0.43 .84 .05

SNS modulation (SDNN+LF) .257 0.40 .09 .49

PNS modulation (sMSSD + PNN50% + HF) .457 0.85 .12 .58

Model II (Psychotherapy focused on emotion regulation) βF p R2

Salivary Cortisol -.23 0.431 .71 .19

SNS modulation (SDNN+LF) -.56 2.03 .20 .36

PNS modulation (sMSSD + PNN50% + HF) -.71 5.15 .04* .72

Note. Multiple-linear regression model. Statistical signicance of *p < .05 for the predictive eect of

parasympathetic modulation on emotional eating behavior.

Table 5. The predictive eect of emotional response on the emotional eating domain

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

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INTRO METHOD RESULTS DISCUSSION REFERENCES

in the literature have looked into the relationship

between emotional state and behavioral changes,

particularly compensatory behaviors for emotional

discomfort and stress. Casagrande et al (2020), for

example, discovered a positive correlation between

an increase in alexithymia symptoms and dicul-

ties in emotional regulation, as well as both posi-

tively correlating with body mass index in a clinical

sample of individuals diagnosed with alexithymia, a

psychiatric condition marked by diculties in per-

ceiving emotional states, feelings, and bodily sensa-

tions. Another study, which looked at the relations-

hip between emotional dysregulation and impulsive

eating patterns in a group of bariatric surgery pa-

tients, discovered binge eating and overeating du-

ring times when the participants reported diculty

with emotional regulation (Benzerouk et al., 2020).

Along with other studies with similar sample

characteristics (Debeuf et al., 2020; Torres et al.,

2020), our participants had high pre-intervention

scores in emotional eating and food disinhibition

domains, indicating the occurrence of these ea-

ting patterns in this sample of obese individuals.

After the intervention, individuals in the psycho-

therapy group focused on emotional regulation

showed a reduction in these areas, suggesting

that this intervention model may represent a pro-

mising approach to addressing emotional eating

behavior. However, it is important to note that the

observed eects could also be inuenced by other

factors. For example, the regulation of eating pa-

tterns may be indirectly aected by CBT through

improvements in self-esteem and body dissatisfac-

tion, which have a direct impact on weight con-

trol (Neufeld et al., 2012). Additionally, the direct

eects of applied techniques on components such

as self-regulation, motivation, and self-ecacy may

also suggest other variables that could inuence

the observed outcomes (Intarakamhang & Inta-

rakamhang, 2015). Other intervention strategies,

such as those focusing on mindfulness for emo-

tional regulation, also support these ndings, as

O’Reilly et al. (2014) discovered in a systematic re-

observed, though it did not reach statistical signi-

cance (see Table 5). This trend warrants further in-

vestigation with a larger sample size to conrm its

potential signicance.

For the CBGT group, considering cortisol as a

predictor, multiple-linear regression showed no as-

sociation between salivary cortisol response and

any of the domains of uncontrolled eating and

emotional eating [F(1,8) = 0.469, p = .71, R² = .19]. In

addition, for sympathetic modulation, the analysis

did not observe statistical dierences for predictive

eect on the eating behavior domains analyzed by

the instrument [F(2,7) = 2.03, p = .20, R² = .36], but

it was possible to observe a predictive eect of pa-

rasympathetic modulation on the emotional-based

eating behavior domains [F(3,6) = 5.15, p = .04, R²

= .72], suggesting that parasympathetic activation

may predict the occurrence of this behavior for the

experimental therapeutic group. According to the

model, an increase in parasympathetic activation

can predict a decrease in emotional eating and un-

controlled eating occurrences (Table 5).

Discussion

The main ndings of this study for participants

in the Experimental Therapeutic Group (CBGT) fo-

cused on emotional regulation, 6 weeks after the

intervention, were: (1) a reduction in emotional ea-

ting and uncontrolled eating domain scores; (2) a

reduction in state-anxiety domain scores, indicating

an improvement in emotional response; and (3) the

ndings highlight improvements in HRV parameters

(rMSSD, PNN50%, and HF%) and a reduction in ba-

sal cortisol levels upon awakening 6 weeks post-in-

tervention in the group undergoing the interven-

tion focused on emotional regulation. Additionally,

multiple linear regression analysis suggested that

increases in these parameters could predict a re-

duction in emotion-based eating behaviors.

In our study, we observed that the intervention

based on a protocol focused on emotional regula-

tion was eective in reducing eating behaviors as-

sociated with emotional expression. Some studies

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

the eating behavior of anorexic and bulimic pa-

tients (Tatham et al., 2016).

In this study, it was determined whether the

group intervention model focusing on emotional

regulation would have direct eects on emotional

response components and, as a result, on featu-

res of emotional eating. Anxiety markers, autono-

mic nervous system modulation, and basal cortisol

awakening response were used to accomplish this.

The study used an instrument capable of analyzing

anxiety characteristics as a trait phenotype inherent

in the subject’s temperament and an anxious state,

a more instantaneous measure of emotional res-

ponse, to analyze participants’ anxiety proles (Bie-

ling et al., 1998).

In terms of trait anxiety, individuals had a consis-

tent anxiety prole before the intervention that did

not dier regardless of the therapeutic paradigm

used (see Table 2). This points to the occurrence of

an anxious endophenotype, which is unlikely to be

altered by the recommended treatment interven-

tions. According to some studies, trait anxiety is a

personality dimension based on neuroticism, with

a strong tendency to experience emotional patter-

ns associated with psychological discomfort caused

by attentional biases to negative stimuli, distress,

worries, and anxiety in various aversive events (De-

beuf et al., 2020; Mielimąka et al., 2017; Morsy, 1983;

San-Antolín et al., 2020). Evidence suggests that

brain correlates for trait anxiety exist, which can be

a risk factor for mental diseases (Bishop & Forster,

2013; Liu et al., 2021; Mitchell & Kumari, 2016; Savio-

la et al., 2020). In addition, numerous research has

found a link between state anxiety and emotional

eating in a sample of obese people (Ostrovsky et al.,

2013; Schneider et al., 2010).

Our ndings observed a reduction in state anxie-

ty during the follow-up period across both groups,

indicating that both intervention models eectively

reduced scores in this domain. This result aligns

with ndings from Moltrecht et al. (2021), whose

meta-analysis of 21 studies on emotional regulation

interventions demonstrated ecacy in managing

view that mindfulness interventions are eective in

reducing obesity-related eating behaviors such as

binge eating and emotional eating. In this analysis,

the ecacy of these therapies was 87%, and around

63% of the analyzed studies used emotional regu-

lation measures to minimize emotional eating.

Glisenti and Strodl (2012) compared CBT and

Dialectical Behavior Therapy (DBT) for the treatment

of emotional eating in a group of obese people.

Both therapies received 22 sessions throughout the

research. The CBT intervention included features

such as recognizing beliefs and behaviors related

to weight reduction issues, setting therapy goals to

address these ideas and behaviors, and providing

psychoeducation on healthy eating and increased

physical activity. DBT therapies, on the other hand,

included emotion regulation, stress, and anxiety

management, and skills training to help recognize

and control unpleasant emotions. After 8 weeks of

follow-up, the DBT group lost 10.1% and 7.6% of

their initial body weight, respectively, whereas the

CBT group lost 0.7% and 0.6% of their initial body

weight. Furthermore, the DBT group demonstrated

a reduction in emotional response indicators, inclu-

ding stress reaction, anxiety, and emotional eating.

Similarly to the previously stated study, we were

unable to identify an eect of the psychoeducation

intervention model on lowering emotion-based

eating behavior (see Table 3), despite an increase in

cognitive restraint domain scores in both groups.

Because the cognitive restraint domain evaluates

an individual’s eort and use of cognitive resources

to regulate food intake and maintain body weight

(Bond et al., 2001), this evidence could be explai-

ned as a possible inuence of psychoeducation on

this component of eating behavior. Identical n-

dings have been reported in other investigations.

Cash and Hrabosky (2003), for example, investiga-

ted the ecacy of psychoeducation in an interven-

tion model aimed at changing body image, which

resulted in increased self-esteem, healthy eating

attitudes, and decreased anxiety. Another nding

demonstrated the eect of psychoeducation on

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

sion, while mindfulness-based interventions have

shown inconsistent results (O’Leary et al., 2016). Our

study adds to the growing evidence linking emo-

tional regulation interventions to physiological and

behavioral improvements, such as increased pa-

rasympathetic modulation, reduced cortisol levels,

and decreases in emotional eating. However, these

ndings should be interpreted cautiously, as stress

eects on emotion and behavior are inuenced by

multiple factors, Including stress intensity, individual

variability, social conditions, and genetic or neural

vulnerabilities (Flores-Kanter et al., 2021). Further

research with more robust methodologies is nee-

ded to conrm these results and assess their long-

term impact.

A linear regression model was used to test the

hypothesis of the predictive eect of emotional

response on emotional eating behavior in both

groups. HRV variables (sympathetic and parasym-

pathetic modulation) and salivary cortisol were

used as predictor variables on aspects of emotional

eating. We found no predictive inuence of any of

the emotional response variables on emotional ea-

ting domains in the model I. In model II, however,

a substantial negative linear connection was identi-

ed for the parasympathetic modulation predictor

variable, indicating that an increase in parasympa-

thetic excitation can predict a reduction in emotio-

nal eating for the intervention group focused on

emotional regulation. Although regression models

showed predictive eects, these may be due to in-

dividual heterogeneity in responses or the short fo-

llow-up time, emphasizing the need for longitudi-

nal approaches to properly capture these dynamics.

Replicating this intervention in populations with

clinically relevant stress conditions or across age

and gender groups could reveal emotional and be-

havioral changes predicted by the diathesis-stress

model, which emphasizes individual vulnerabilities

and environmental stressors.

Certain limitations to this study should be con-

sidered. Variables such as neuroendocrine loop

characteristics for women during their menstrual

psychiatric disorders in young populations. Simi-

larly, psychoeducation models have shown bene-

ts in controlling anxiety symptoms (Dolan et al.,

2021; Chillemi et al., 2020; Norr et al., 2017). A pos-

sible explanation lies in psychoeducation’s ability

to transfer knowledge about emotional and beha-

vioral processes, integrating emotional awareness,

motivation, and behavioral strategies to manage

stress. This empowers individuals to regulate their

emotional responses and adopt functional coping

behaviors. These ndings highlight the potential of

combining emotional regulation interventions and

psychoeducational approaches in weight manage-

ment programs to address the emotional drivers of

eating behaviors. However, larger and more contro-

lled studies are needed to clarify the specic eects

of each approach.

The study assessed emotional state components

using heart rate variability (HRV) to examine sympa-

thetic/parasympathetic balance and basal salivary

cortisol upon awakening. These psychophysiologi-

cal indicators reect emotional response changes

mediated by the Sympathetic-Adreno-Medullary

(SAM) and Hypothalamic-Pituitary-Adrenal (HPA)

axes, key systems in stress and emotional regula-

tion. While sympathetic modulation remained un-

changed in both groups, participants in the emo-

tional regulation intervention exhibited increased

parasympathetic modulation.

Preliminary ndings suggest that the emotional

regulation strategies, such as cognitive restructu-

ring and relaxation techniques, may have inuenced

HPA axis excitability and reactivity. The intervention

could have balanced HPA axis activity by enhancing

parasympathetic activation and reducing stress-in-

duced sympathetic dominance. Lower basal corti-

sol levels in the CBGT group may reect improved

stress coping or emotional regulation, though these

assumptions remain speculative due to the study’s

methodological limitations, which preclude deniti-

ve conclusions. Supporting evidence comes from a

meta-analysis by Mikkelsen et al. (2021), which re-

ported favorable eects of CBT on cortisol expres-

CBGT for Obesity: Impact on Stress, Anxiety, and Emotional Eating

Actualidades en Psicología, 39(138), 2025.

INTRO METHOD RESULTS DISCUSSION REFERENCES

tions, including the small sample size and lack of

clinical populations with eating disorders, these re-

sults should be interpreted cautiously. Further stu-

dies with larger samples and controlled designs are

necessary to validate the intervention’s long-term

eectiveness and explore its broader applicability in

managing dysfunctional eating behaviors.

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cycle, resilience traits, socioeconomic indicators,

and educational level were not controlled for in the

study and could have directly inuenced the exa-

mined parameters. Furthermore, because this was

a community-based sample, the participants might

represent a motivated and self-selected group see-

king therapy. Although the overall results were pro-

mising in certain explored aspects, various potential

moderating factors of treatment response, such as a

possible placebo eect due to participants’ belief in

being part of a therapeutic group focused on emo-

tional regulation, could not be ruled out. Additiona-

lly, the anthropometric variables adopted, such as

BMI, may not accurately reect adipose tissue accu-

mulation or metabolic alterations related to obesity.

More precise measures, such as body composition

analysis, should be considered in future research

to enhance the validity of these ndings. Similar-

ly, more accurate assessments of cortisol response,

such as the Cortisol Awakening Response (CAR),

could provide deeper insights into stress reactivity

and its relationship with emotion-based eating pa-

tterns. The small sample size also limits the genera-

lizability of the ndings, emphasizing the need for

future studies with larger samples, including clinical

populations with eating disorders, to better evalua-

te the eects and applicability of the intervention.

Finally, other variables were not controlled during

the follow-up period, which may have inuenced

the observed outcomes.

In conclusion, the 8-week group-based interven-

tion focused on emotional regulation demonstrated

preliminary ecacy in reducing aspects of emotional

reactivity with a potential impact on components of

emotion-driven eating behaviors. The eects of the

CBGT intervention were more pronounced compa-

red to the psychoeducation group, suggesting its

potential as a promising approach. These ndings

highlight the feasibility and safety of implementing

group-based therapeutic interventions for obese

individuals while addressing key psychophysiolo-

gical and behavioral variables such as emotional

eating. However, given the methodological limita-

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