Psychological profiles of mindfulness and tourist fatigue: a latent profile analysis in a digital travel context

Abstract

The study examined how the different psychological constructs of mindfulness, anxiety, and positive fantasy engagement influence tourist fatigue in digitally mediated tourism experiences. In response to the increasing anxiety regarding cognitive overload in AI-driven travel ecosystems, the study reconceptualizes fatigue as configuration-dependent, but not uniformly experienced. Composite measures of mindfulness (MAAS), anxiety (GAD-7), positive fantasy engagement, and tourist fatigue were determined using survey data of 646 tourists. Latent Profile Analysis was used to identify psychological subgroups, after which ANOVA and multinomial logistic regression were run to test the differences in fatigue and demographic predictors. It is a framework that combines self-control theory, conservation of resources theory, and broaden-and-build theory in the digitally accelerated tourism context. There were four different types of profiles of mindfulness-dominated positive fantasy, emotionally distressed, high-positive psychological capital, and balanced-average. The profiles had a significant difference in fatigue levels (η² = 0.254), with the highest fatigue reported by the Emotionally Distressed group and the lowest by the High Positive Psychological Capital group. Mostly, the demographic predictors were insignificant, which emphasized the importance of psychological configuration rather than the structural characteristics. The findings advance tourism psychology by showing that fatigue is a result of the interaction between attentional regulation, emotional load, imaginative engagement, and the intensity of the digital environment. The study will add a multi-level psychological architecture of tourist fatigue by combining person-centered modeling with digital tourism scholarship. In the context of smart tourism system in China and AI-mediated traveling systems that continue to grow worldwide, the application of digital mindfulness and attentional scaffolding systems within platform design can potentially help reduce the fatigue of psychologically vulnerable users. This work goes beyond variable-based models to uncover the interaction of internal regulatory systems, tourism infrastructures that are mediated by digital technologies, to provide a worldwide applicable model of maintaining experiential well-being as technologically enhanced travel environments are experienced.

Introduction

It is a generally accepted fact that tourism is seen as one of the ways of psychological rejuvenation, allowing stress, emotional, and mental healing^1,2. However, modern traveling conditions, characterized by congestion, movement necessities, overstimulation via the Internet, and performance stressors, tend to have a reverse effect. Instead of replenishing used resources, travel can cause a condition of psycho-physiological stress often known as tourist fatigue^3,4. This state includes physical fatigue, emotional instability, and mental exhaustion, which negatively affect the restorative nature of leisure traveling⁵.

Digital health interventions (DHIs), especially digital mindfulness training, have been increasingly used as a response to increasing worries about the strain of traveling^6,7. Mindfulness-based applications are available, affordable, and are becoming more and more relevant to the digital ecosystem of tourism⁸. Nevertheless, empirical studies always indicate a large degree of variation in the effectiveness of interventions. Although mindfulness is reportedly theoretically correlated with better attentional control and emotional regulation⁹, its impact seems to depend on such personal factors as baseline anxiety and cognitive-affective dispositions^10,11.

The existing studies have mainly used variable-focused methodologies, which involve the study of mindfulness, anxiety, and positive cognitive attitudes like fantasy orientation as independent variables of well-being outcomes^12,13. Even though this method is informative, it assumes that the population is homogeneous and ignores the fact that these traits co-occur within individuals. Psychological traits do not work independently, but they are organized into meaningful patterns that can possibly precondition how people will be responsive to digital interventions^14,15. Therefore, there is an important question that is not discussed thoroughly: Who can be the most effective at reducing the impact of fatigue in tourists due to the use of digital mindfulness training?

In order to fill this gap, the current research focus on the person-centered view of Latent Profile Analysis (LPA) in determining naturally occurring psychological profiles among tourists in terms of mindfulness, generalized anxiety, and positive fantasy^16–18. The breakthrough of averaged relationships through the current approach enables latent heterogeneity of the tourist population to be captured and enables us to test the relationship between specific psychological configurations and the level of fatigue after digital mindfulness training.

Particularly, this research has three purposes. We first of all establish latent psychological subgroups of tourists. Second, we test whether these profiles have any difference in fatigue severity. Third, we explore demographic forecasts of profile membership. The combination of digital well-being research and person-centered approach will increase knowledge about the borderline circumstances within which mindfulness-based interventions can be at their best.

With theory, this study undermines the unspoken homogeneity concept of psychological restoration through tourism and presents a typological model of intervention responsiveness¹⁹. It has a methodological implication as it adds to the use of LPA in the psychology of tourism. In practice, the results offer advice on how digital mindfulness programs can be customized to specific segments of tourists, which would increase the accuracy of fatigue prevention programs.

Literature review

Tourist fatigue as a psychophysiological strain response

Tourism has traditionally been conceptualized as a form of restorative activity that can help to restore exhausted psychological resources¹. However, there is growing evidence that modern traveling settings can cause significant cognitive and emotional stress. Tourist fatigue has been characterized as a multidimensional syndrome that includes physical exhaustion, attentional stress, and emotional fatigue⁴. In contrast to the exhaustion experienced at work, which occurs within the frameworks of formal employment, tourist exhaustion appears when people are on vacation, thus causing a problem with the assumption that traveling is inherently restorative. The recent literature supports the idea that the issue of travel-related exhaustion can be caused by the presence of high-density schedules, information overload, physical movement, and digital hyper-connectivity⁸. Psycho-physiologically, the prolonged mental activity and environmental excessive stimulation may undermine the ability to restore attention and control emotions⁵. Additionally, personal differences have a decisive effect on fatigue vulnerability because recovery processes are dependent on baseline psychological resources (e.g., self-regulations and resilience)²⁰. These results indicate that tourist burnout is not just contextual, but it is at least partly dependent upon personal psychological set-ups. In line with this, a more detailed comprehension of vulnerability and resilience in tourism conditions may be provided by identifying heterogeneity in the psychological profiles.

Digital mindfulness training as a mechanism of self-regulation

Mindfulness, which can be described as non-judgmental awareness of current experience⁹, improves attentional regulation and emotional control. An emerging body of literature proves that mindfulness-based interventions enhance psychological well-being, reduce stress reactivity, and enhance cognitive flexibility⁷. The introduction of digital mindfulness training as a mobile-based and web-based service has become widely recognized due to its scalability and accessibility⁶. Empirical studies indicate that digital mindfulness interventions can reduce stress and fatigue symptoms by enhancing regulatory processes and meta-cognitive awareness²¹. However, the results of interventions are very diverse. Although some respondents display a significant response, others show an insignificant response¹⁰. This inconsistency suggests that the efficacy of mindfulness can require the presence of cognitive-affective propensities. Patients with high baseline anxiety can have difficulties in maintaining their attentional focus during the process of mindfulness, thus limiting intervention effectiveness¹³. On the other hand, people with strong attentional control as well as favorable psychological capital can also enjoy more benefits of digital mindfulness practices²².

Anxiety, positive fantasy, and psychological configuration

Generalized anxiety is characterized by persistent worry and hyper sensitivity of threats, which drain cognitive functions and inhibit attentional control¹³. High levels of anxiety have been linked to higher levels of fatigue because of prolonged physiological arousal and mental rumination⁵. Stress can also increase among anxious people in situations demanding new environments, which leads to enhanced fatigue acquisition in the tourism settings. Positive fantasy, which is the tendency to think of positive future processes¹², is a more complex construct. Although positive fantasy in moderate amounts can be beneficial to motivation and optimism, excessively depending on fantasy can lead to escapism and abrogate awareness of the present, which can conflict with the principles of mindfulness¹⁰. Therefore, positive fantasy can be a psychological resource or a weakness depending on the responses it has with mindfulness and anxiety. The majority of antecedent studies have investigated mindfulness, anxiety, and positive fantasy separately and utilized variable-focused approaches. Even though such a methodology identifies linear relationships, it is unable to explain how these characteristics combine in individuals to form consistent psychological portrayals (N. Zhang et al.,¹⁵. These limitations restrain our understanding of the role that such arrangements play in determining fatigue outcomes.

The person-centered perspective and latent profile analysis

Latent Profile Analysis (LPA) is a person-centered technique that allows researchers to determine naturally occurring subgroups that are delineated by unique patterns of psychological characteristics^14,18. As opposed to variable-centered methods, LPA based on heterogeneity within populations seeks to reveal latent structures behind the indicators observed. LPA has been useful in identifying resilience profiles, subgroups subject to stress vulnerability, and variable sensitivity to interventions in health and psychological studies¹⁷. However, there is a lack of its use in tourism psychology. With the implementation of LPA, the current study goes beyond average impacts and answers the critical question of who digital mindfulness training could be most effective for. By using this person-centered model, it would be possible to explain psychological gatekeeping processes, configurations of mindfulness, anxiety, and positive fantasy that could vary in their capacity to moderate the level of fatigue after the digital mindfulness training. Synthesizing the literature reveals three major gaps:

First, tourist fatigue research has emphasized situational factors while underexamining individual psychological configurations.

Second, digital mindfulness intervention studies demonstrate heterogeneous outcomes but lack theoretical models explaining differential responsiveness.

Third, prior studies rely predominantly on variable-centered methods, failing to capture latent psychological heterogeneity.

These gaps suggest a need for a person-centered framework capable of identifying psychological subgroups and examining how these subgroups relate to fatigue severity in digital mindfulness contexts.

The present study addresses these gaps by applying Latent Profile Analysis to identify naturally occurring psychological configurations among tourists and examining how these profiles differentially relate to fatigue severity.

Hypothesis development

Theoretical foundation: self-regulation and resource depletion

This study is based on the theoretical foundations of the self-regulation theory and the resource-based approaches to psychological functioning. The self-regulation theory postulates that attentional and affective control processes are utilized by individuals to work out environmental requirements⁹. Regulatory resources run out, which results in strain, cognitive fatigue, and emotional exhaustion in individuals⁵. Tourist fatigue can be theorized as the expression of the imbalance of regulatory resources. The travel environment has sensorial, cognitive, and social demands. These demands result in fatigue, not only depending on the exposure in the situation but also on the regulatory capacity at the beginning. Mindfulness enhances meta-cognitive awareness and reduces automatic stress responsivity, thus maintaining regulatory resources⁷. On the other hand, generalized anxiety dominates cognition through all-consuming anticipatory processing and increased threat vigilance¹³. Positive fantasy can be a motivational tool based on regulatory consciousness, but it can create maladaptive escapism when it is not linked to the present moment¹⁰. As a result, susceptibility to fatigue should be reflective of the organizational trend of these psychological resources as opposed to isolated trait levels.

Hypothesis 1: emergence of distinct psychological profiles

Prior studies on mindfulness, anxiety, and psychological capital tend to statistically presume that these variables are independent predictors. Nevertheless, psychological traits do not usually exist in isolation; rather, they co-exist in repeated patterns that indicate underlying resilience or vulnerability frameworks¹⁵. Such research designs as person-centered studies in health psychology prove that regulatory capacity and emotional vulnerability combinations result in different latent profiles with varied outcomes¹⁴. Since mindfulness promotes regulation, whereas anxiety degrades it, and since positive fantasy can either reinforce or provide protection, it can be argued that tourists will form subgroups of individuals with unique psychological architectures.

Accordingly:

H1

Distinct latent psychological profiles characterized by different configurations of mindfulness, generalized anxiety, and positive fantasy will emerge among tourists.

This hypothesis reflects the expectation that psychological heterogeneity is structured rather than random.

Hypothesis 2: profile-based differences in fatigue severity

If fatigue is a symptom of regulatory imbalance, then different psychological profiles will display systematically different fatigue results. Individuals with low levels of mindfulness and anxiety are more likely to experience increased levels of physiological arousal and poor attentional control. Anxiety-related persistent cognitive rumination promotes the depletion of resources¹³, thus exposing fatigue to greater severity⁵. On the other hand, high mindfulness allows people to have greater control over emotions and attention and process travel-related requirements without overconsumption of resources^9,7. Such individuals, when mixed with adaptive positive fantasy, can be able to maintain their optimism without breaking away from what they are currently going through. Therefore, the degree of fatigue cannot drop and rise arbitrarily but must be consistent with resource configuration.

H2

Fatigue severity will significantly differ across latent psychological profiles, such that profiles characterized by lower mindfulness and higher anxiety will report greater fatigue severity, whereas profiles characterized by higher mindfulness and stronger psychological resources will report lower fatigue severity.

This hypothesis introduces an explanatory mechanism linking profile structure to fatigue outcomes.

Hypothesis 3: demographic structuring of psychological profiles

There is a heterogeneous distribution of psychological resources in populations. Socio-economic status has been found to determine the exposure to stress, availability of coping resources, and psychological capital accumulation²². University education promotes cognitive flexibility and contemplative ability, which may work to improve mindfulness activities. High income can counteract exposure to chronic stress and expand access to digital health resources⁸. The prevalence of the levels of anxiety has always been registered as higher in women, who report a higher level¹³. These variations can inform the distribution of persons in vulnerability-oriented profiles. Provided that psychological configurations are an indicator of cumulative regulatory resources; the demographic traits should be good predictors of profile membership.

H3

Gender, education level, and income level will significantly predict latent profile membership, with lower education and income associated with increased likelihood of belonging to less resource-rich profiles.

This hypothesis extends the theoretical model by incorporating structural determinants of psychological configuration.

Methods

Research design

The current paper used a cross-sectional observational research design. There was no experimental manipulation or standardized digital-based mindfulness intervention. The study did not test how a training program caused individual differences in mindfulness, generalized anxiety, and positive fantasy, but instead identified natural occurrences of individual differences in a digitally mediated tourism environment. An analytical method that focused on individuals was used, and this technique was meant to detect latent psychological structures among tourists and also to determine whether these structures were linked to variations in fatigue severity. Since the structure is of an observational type, the results are not representative of causal relationships.

Participants and procedure

Data were collected from 660 tourists recruited through online travel platforms and digital tourism communities. The participants were chosen on the condition that they experienced recent travel experiences in digitally mediated settings (e.g., used travel applications, planned their itineraries online, or used digital tourism services). The survey participants were provided with a questionnaire on the secure digital platform. The questionnaire contained an indicator of mindfulness, generalized anxiety, positive fantasy, the severity of fatigue, and demographic data. The response was voluntary and anonymous. The informed consent was electronically obtained before the survey was completed. The research followed the ethical standards of conducting research with human participants. The last sample was made up of 646 respondents (30.9% male, 69.1% female). The sample was spread over the age groups, education levels, and income groups, and the demographic analysis of latent profile membership became possible.

Measures

Mindfulness

The measure of mindfulness was through the Mindful Attention Awareness Scale (MAAS;⁹. The MAAS is used to measure dispositional attention and awareness of the present-moment experiences. The questions were rated on a Likert scale (e.g., 1 = almost always to 6 = almost never). An increase in scores brings about improved trait mindfulness. The MAAS has proved to enjoy high reliability and construct validity in different cultural settings.

Generalized anxiety

The Generalized Anxiety Disorder − 7 (GAD − 7;¹³ defines generalized anxiety. The participants were asked to rank the frequency of anxiety-related symptoms in the last two weeks on a 4- point scale (0 = not at all to 3 = nearly every day). The scores are higher, which means that the anxiety is more severe. The GAD-7 is highly valid and has substantial psychometric qualities.

Positive fantasy

The Positive Fantasy Scale¹² was used to measure positive fantasy, and it is a scale that measures how people think about positive future events. The items were rated on a Likert-type scale, where a higher score indicated increased fantasy orientation.

Fatigue severity

The validated fatigue severity instrument was adapted to the tourism settings, and tourist fatigue was measured⁴. The scale measures the cognitive, emotional, and physical dimensions of fatigue. Items were rated by the participants on a Likert scale, where a high score means that the severity of fatigue is high. The participants were clearly told that they should answer fatigue items based on their last tourism experiences. The initial part of the survey was a reminder to the respondents to base their answers on emotions that they have during or immediately after activities related to travel, as opposed to feelings of general stress that have been encountered in life. Although it is not a possibility to eliminate the effect of external influences in cross-sectional research, contextual framing was applied to increase the specificity of the constructs.

Demographic variables

Participants reported gender (0 = male, 1 = female), age, education level, and income level. Education and income were treated as ordinal variables in subsequent analyses.

Analytical strategy

Latent profile analysis (LPA)

Latent Profile Analysis (LPA) was used to establish subgroups of tourists with unique mindfulness, generalized anxiety, and positive fantasy configurations. LPA is a model-based clustering method, which presupposes the heterogeneity of the populations and determines the latent subpopulations according to continuous indicators¹⁴. Models specifying one through five profiles were estimated. Various statistical selection criteria were used to decide on the model, including:

• Akaike Information Criterion (AIC).

• Bayesian Information Criterion (BIC).

• Sample-size Adjusted BIC.

• Entropy.

• Lo–Mendell–Rubin likelihood ratio test (LMR-LRT).

Lower AIC/BIC values are associated with improved model fit, whereas entropy values that are closer to 1 are associated with better classification accuracy. The best solution has been chosen through the criteria of statistical fit, interpretability, and theoretical coherence.

Analysis of fatigue differences

After identifying latent profile differences in the severity of fatigue between profiles, were compared with one-way analysis of variance (ANOVA). Post-hoc comparison was used to determine any significant differences on a pairwise basis.

Multinomial logistic regression

Multinomial logistic regression analysis was conducted to study the demographic predictors of profile membership. Profile membership was considered the nominal dependent variable, and the mindfulness-dominant profile was used as the reference group. They were gender, age, education level, and income level. To interpret the significance of associations, odds ratios (ORs) and 95% confidence intervals were obtained.

Statistical software

All analyses were conducted using SPSS version 20. Statistical significance was evaluated at the p < .05 level.

Results

Preliminary analyses: reliability and descriptive statistics

Internal consistency for all scales was satisfactory to excellent. Cronbach’s alpha coefficients were:

• MAAS (15 items): α = 0.91.

• GAD-7 (7 items): α = 0.88.

• Positive Fantasy (10 items): α = 0.89.

• Tourist Fatigue (9 items): α = 0.92.

These values indicate strong internal reliability and support the use of composite scores for subsequent analyses. Descriptive statistics indicated meaningful variability across participants in mindfulness, anxiety, fantasy engagement, and tourist fatigue.

Hypothesis 1: latent profile analysis

To examine whether distinct psychological configurations emerged among tourists, Latent Profile Analysis (LPA) was conducted using composite scores of mindfulness (MAAS_total), anxiety (GAD7_total), and positive fantasy (PositiveFantasy_total).

Models specifying one through five profiles were estimated. Model comparison indices are presented in Table 1.

Table 1.

Model fit indices for latent profile solutions.

Profiles	AIC	BIC	Entropy
1	6801.57	6828.39	—
2	5869.70	5927.82	0.98
3	4976.42	5065.83	0.96
4	4794.96	4915.67	0.98
5	4939.58	5091.58	0.84

The four-profile solution demonstrated the lowest BIC and high entropy (0.98), indicating superior model fit and strong classification accuracy. Therefore, the four-profile solution was retained.

Profile characteristics

Table 2 presents the means and standard deviations of psychological indicators and fatigue across profiles.

Table 2.

Profile characteristics (N = 646).

Profile	n	%	Mindfulness (M)	Anxiety (M)	Fantasy (M)	Fatigue (M)
C1 Mindfulness-Dominant Positive Fantasy	193	29.9	4.57	2.81	4.14	4.03
C2 Emotionally Distressed	121	18.7	2.59	3.00	2.26	5.23
C3 High Positive Psychological Capital	49	7.6	4.70	2.79	4.31	3.81
C4 Balanced-Average	283	43.8	2.66	2.84	2.78	4.97

Profiles were meaningfully differentiated:

• C1: High mindfulness + high fantasy.

• C2: Low mindfulness + high anxiety (distress configuration).

• C3: Highest mindfulness + high fantasy + lowest fatigue.

• C4: Moderate configuration.

H1 Supported: Distinct latent psychological profiles emerged.

Hypothesis 2: differences in tourist fatigue across profiles

A one-way ANOVA was conducted to examine differences in Tourist Fatigue across the four profiles.

Table 3.

ANOVA results for tourist fatigue.

Source	SS	df	F	p
Profile	180.28	3	72.76	< 0.001
Residual	530.22	642	–	–

Effect size: η² = 0.254.

The analysis revealed a significant main effect of profile membership on tourist fatigue, F(3, 642) = 72.76, p < .001, with a large effect size (η² = 0.254).

Post hoc comparisons

Tukey HSD tests indicated:

• C2 (Emotionally Distressed) reported significantly higher fatigue than all other profiles (p < .001).

• C3 (High Positive Psychological Capital) reported the lowest fatigue.

• C1 and C3 did not differ significantly from each other.

• C4 reported moderate fatigue, significantly higher than C1 and C3.

These findings demonstrate that psychological configuration meaningfully differentiates fatigue experiences. H2 Supported: Tourist fatigue varies significantly across latent profiles.

Hypothesis 3: demographic predictors of profile membership

Multinomial logistic regression was conducted to examine whether gender, age, education level, and income level predicted profile membership (reference category = C1).

Model fit statistics indicated modest explanatory power:

• Pseudo R² = 0.011.

• Likelihood Ratio Test p = .145.

Table 4.

Multinomial logistic regression results (Reference = C1).

Comparison	Predictor	B	OR	p
C2 versus C1	Education level	-0.17	0.85	0.006
C2 versus C1	Gender (Female = 1)	0.42	1.52	0.099
C3 versus C1	All predictors	ns	—	> 0.05
C4 versus C1	All predictors	ns	—	> 0.05

Education level significantly predicted membership in the Emotionally Distressed profile relative to the Mindfulness-Dominant profile, such that lower education was associated with higher odds of distress classification.

Other demographic variables were not significant predictors.

H3 Partially Supported: Education showed a significant association; other demographic predictors did not.

Summary of hypothesis testing

Hypothesis	Result
H1: Distinct psychological profiles emerge	Supported
H2: Profiles differ in tourist fatigue	Supported
H3: Demographics predict profile membership	Partially Supported

The results show that the phenomenon of tourist fatigue is not homogeneous, and it manifests itself systematically depending on the specific psychological constructions. Participants who are characterized by high anxiety and low mindfulness (Cluster C2) seem to be especially vulnerable to fatigue, and participants characterized by great mindfulness and positive fantasy involvement (Cluster C3) are rather resilient. The impact of demographic variables was relatively small, which indicates that the influence of psychological configurations can be central in the fatigue outcomes determination as compared to fundamental sociodemographic factors.

Discussion

Reframing tourist fatigue: a configuration-based perspective in a digitally accelerated era

The study contributes to the growing body of research on tourism psychology by explaining why tourist fatigue is imbued in specific psychological constructions, rather than arising uniformly, as a result of environmental exposure. With the help of the latent profile analysis, we managed to determine four significant subgroups that demonstrated regular differences in the level of fatigue. Person-centered approach fits existing persuasions in the tourism literature to go beyond variable-based models to embrace heterogeneity in the experiential results^23–26. There is a dire need to place these results in the modern digital tourism ecosystem. Algorithms, artificial intelligence, simulated experience, and mobile-first planning platforms are all forms of mediation of touristic experiences²⁷. Attentional regulation and emotional control become the crucial resources within such contexts. We conclude that fatigue is not the result of digital intensity per se, but emerges as a result of the interaction between internal regulatory mechanisms and external digital stimulation.

Mindfulness as regulatory infrastructure in smart tourism systems

In fact, mindfulness serves as one of the major protective measures against tourist fatigue. Profiles that were characterized by increased mindfulness were significantly less fatigued, especially those clusters that were typified by High Positive Psychological Capital. Such observation is consistent with the self-regulation theory²⁸, attentional control models, according to which mindfulness increases cognitive stability and alleviates depletion⁹. In the Chinese market of smart tourism, where digital tools are thoroughly integrated, travelers are faced with a significant level of information overload due to the optimization of itineraries, the creation of personalized services, and the delivery of this in real time. Although it can be stated that these systems definitely increase the efficiency of operations, they also contribute to increased cognitive loads. In line with this, we argue that mindfulness is one of the regulatory infrastructures existing in these settings, which protects individuals against overstimulation and decision fatigue. The observation builds on the previous research on the topic of digital tourism and AI-mediated travel behavior^29,27 by anticipating internal psychological settings as a major mediating variable. Digital systems do not equal enhance or exhaust users; instead, the combination of their effects relies on the attentional and affective structure through which a user interacts with technology.

Anxiety, resource depletion, and adaptive capacity

The Emotionally Distressed profile had the most fatigue and was typified by increased levels of anxiety and low levels of mindfulness. This trend is in line with Conservation of Resources (COR) theory³⁰, which argues that stress and depletion are a result when people feel deprived of resources or when they feel that their resources are being lost or diminished. Anxiety takes up cognitive tasks and reduces the attentional space³¹, making tourism environments in digital form especially taxing.

Ramkissoon³², argues that it is adaptive psychological capacity that dictates well-being outcomes during disruption and uncertainty. This logic is extrapolated by our findings to the context of digitally accelerated tourism, which is not pandemic-specific. This weakness that can be found in the Emotionally Distressed profile reveals that digital tourism can compound any emotional pressure already present in an individual, instead of being a universal restorative experience. Therefore, we balance conflicting results in the sphere of tourism wellbeing studies^33,34. The restorative effects of tourism depend on the pre-existing regulatory capacity.

Positive fantasy, prosocial capital, and broaden-and-build processes

Positive fantasy engagement played a nuanced role. When it is combined with strong mindfulness (Cluster C3), it corresponds to minimal fatigue. This correspondence to broaden-and-build theory³⁵ implies that positive cognitive-emotional states increase the resources of the psychology. Ramkissoon,³² emphasizes the significance of prosociality, trust, and adaptive psychological resources in determining the outcomes of well-being. Even though prosociality was not quantified directly, the High Positive Psychological Capital cluster could be a reflection of more general accumulation of resources such as optimism, imaginative activity, and regulatory stability. These resources not only aid fatigue resilience, but also positive social interactions during the tourism experiences. On the other hand, fantasy that does not have enough attentional grounding (Cluster 4 C4) does not provide the same protection. It means that imaginative work can be adaptive only when framed by regulatory consciousness, a fact which explains the controversy around the view of fantasy as escapism or experience-enrichment.

Limited demographic determinism and psychological primacy

The Demographic predictors had low explanatory power, with education as the only significant distinguishing factor. This point confirms current studies that focus on psychological and experiential segmentation instead of demographic segmentation in the context of tourism²⁴. The comparative weakness of the demographic impacts highlights how fatigue susceptibility is deep-seated in the internal regulatory structure as opposed to structural features. This realization brings together the conceptual change of demographic determinism to psychological configuration models.

Societal impact within China

These results have salient implications for the Chinese digitally integrated tourism ecosystem. The user well-being has become a strategic issue, considering the rise of smart tourism services and AI-based service realms. This research provides policy suggestions, demarcating psychologically vulnerable profiles of users to policymakers and platform designers. Intervention strategies to reduce cognitive overload can be used in high-risk users of digital tourism platforms through embedding brief attentional cues, formal decision-support systems, or interface designs that are less insurance sensitive. This way, integrating technological innovation and psychological sustainability will allow avoiding the unintended consequence of digital acceleration, causing experiential burnout. Therefore, the research is a contribution to ongoing national efforts of making a balance between digital progress and quality-of-life considerations in service domains.

Global relevance and cross-cultural transferability

The analogous digital transformations of tourism systems are being experienced in the rest of the world beyond China. Immersive digital marketing, AI-based travel assistants, and algorithmic personalization are global phenomena. Based on this, it is hardly probable that the psychological configurations found here are culturally independent. By showing that fatigue is an effect of the interaction of internal regulation systems as well as digital mediation systems, this study makes a contribution to the discourses on global digital wellbeing, human-centered AI design, and sustainable tourism development. Besides, adaptive psychological resilience is one of the key policy goals in the context of post-pandemic tourism recovery. The current results indicate that the strengthening of attentional control and positive imaginative involvement can contribute to the experience sustainability in various tourism markets.

Theoretical integration: toward a psychological architecture of digital tourism

Integrating self-regulation theory³⁶, Conservation of Resources theory³⁰, and broaden-and-build theory³⁷, the findings suggest that tourist fatigue emerges from the interaction between:

• Attentional control (mindfulness),

• Emotional load (anxiety),

• Imaginative engagement (positive fantasy),

• Digital environmental intensity.

This multi-level framework situates fatigue at the intersection of internal regulatory architecture and external technological mediation. By adopting a person-centered methodology and embedding it within contemporary digital tourism scholarship^27,29, the study advances both theoretical and methodological development in tourism psychology.

Limitations and future directions

Despite the contributions, there are a number of methodological limitations, which should be subject to stringent analysis. This is because the structure of the cross-sectional design makes it impossible to infer causation, creating temporal precedence. Although latent profile construction is able to capture the heterogeneity in the sample, its reliance on certain contextual factors restricts the opportunity to generalize. Besides, the use of self-report-based tools means that the data is vulnerable to common-method variance, which may overstate the correlations between variables. Researchers should use longitudinal research designs, combine experimental results of digital mindfulness techniques, and use multi-method fatigue scales, such as physiological markers, in future studies to triangulate the results. The cross-cultural replication would also clarify whether the determined psychological configurations are or not culturally universal or rather context-specific.

Conclusion

The present study redefines tourist fatigue as a configuration-specific phenomenon, with the interplay of mindfulness, anxiety, positive fantasy, and mediation by digital technology dynamics. The empirical work is progressive to the field of tourism, as it joins the psychological resource theories and the current discussions of AI-enhanced travel ecosystems. The study provides insights into the localized context in China and internationally transferable implications by preempting the applicability of these findings to the emerging smart-tourism landscape in China and the larger trend of digital transformation overall, meaning that it informs approaches to maintain the experiential wellness within the context of the growing digitized tourism environment.

Author contributions

G: Data analysis and writing of the first draft of the paperY: Data analysis and research questionnaire designY: Data analysisW: Assist in data analysisC: Assist in data analysisT(CorrespondingAuthor): Provide research funding support.

Data availability

The dataset supporting the findings of this study is available from the corresponding author upon reasonable request (Email: JunCao03@outlook.com).

Declarations

Competing interests

The authors declare no competing interests.

Ethical approval

All methods were carried out in accordance with relevant guidelines and regulations. All experimental protocols were approved by a named institutional and/or licensing committee.