Digital meditation platforms have rapidly expanded access to contemplative practices, yet relatively little research has examined how users spontaneously experience guided meditation within open digital environments. This study analysed user responses to five guided meditations focused on equanimity, compassion and attentional presence hosted on the Insight Timer platform. The recordings were released in May 2020, and the study examines user engagement and reflections accumulated over almost six years of public availability (May 2020–March 2026). During this period, the recordings accumulated approximately 12,000 listens within a profile totalling 12.7k plays, alongside 848 user ratings (average rating 4.64) and 444 followers. A dataset of approximately 112 publicly available written comments was analysed using reflexive thematic analysis informed by Braun and Clarke (2019). No demographic data were available for the accounts associated with the comments. Five themes were generated: (1) stabilising presence and calming the mind; (2) self-compassion and emotionally supportive experiences; (3) expanding relational awareness through equanimity; (4) productive difficulty and contemplative challenge; and (5) repeat engagement and everyday integration. The comments suggest that the practices were frequently described not only as relaxation exercises but as meaningful contemplative engagements associated with attentional regulation, experiences of emotional processing, and relational reflection. The findings highlight the potential role of digital meditation platforms as emerging infrastructures through which contemplative practices such as equanimity and compassion are encountered and integrated into everyday life. These findings represent subjective accounts expressed within the comments rather than evidence of therapeutic or clinical effectiveness. Clinical trial number: not applicable.
The Attitudes Towards Psychological Online Interventions Questionnaire (APOI) is designed to measure attitudes towards online treatments. This study aimed to adapt and validate the APOI for the Mexican population. Participants included 2,953 adults who had actively registered to receive an online psychotherapeutic intervention for emotional disorders, with a majority being women (78.5
Robotic Process Automation (RPA) is increasingly adopted to streamline back-office operations, reduce human error, and enhance efficiency. Yet, a critical challenge is employees’ reluctance to accept automation, particularly in emerging economies where psychological and contextual factors remain underexplored. This study proposes and tests an enriched Unified Theory of Acceptance and Use of Technology (UTAUT) model—extended with perceived risk, technology fear, and self-efficacy—to examine RPA acceptance among office employees in Ecuador’s cosmetics manufacturing and distribution industry. Using a seven-point Likert-scale survey with theoretically established constructs, data were collected from 210 employees at an organization undergoing RPA implementation. Analysis via PLS-SEM and confirmatory factor analysis showed that the extended model explained 58.2
Digital self-monitoring tools are increasingly used as health interventions to support goal achievement. However, many mobile health (mHealth) applications prioritise quantitative metrics, overlooking qualitative dimensions critical for understanding user engagement and behavioral change. This study explored students’ perceptions of a habit-tracking app’s usability and acceptability, and its effectiveness in facilitating behavior change over five weeks. Twelve university students (aged 18–32; 11 female, 1 non-binary) across UK undergraduate, postgraduate, and doctoral students participated. Using a within-person repeated-assessments qualitative design, data were collected through two methods: Think-Aloud protocols for initial impressions and semi-structured focus groups after five weeks of app use. Thematic analysis was applied, following Standards for Reporting Qualitative Research (SRQR) guidelines. Think-Aloud sessions yielded three themes: usability, acceptability, and challenges. Focus groups identified four themes: design, engagement, individual differences, and mechanisms of effect. The app was most effective for short-term habit tracking but limited in sustaining long-term habits. Features such as reminders and gamification enhanced engagement and supported positive behavioral change. Future development should prioritize goal-relevant, customizable features that foster autonomy, competence, and sustained behavior change.
This study investigates the perceptions of higher education students regarding the use of GPT variants for online guided inquiry (OGI). Historically, technology has supported teaching and learning without significant adverse effects; however, the growing concern about its potential to replace human involvement, particularly in guided inquiry created impetus for this study. A cross-sectional study using mixed-methods approach was conducted with 150 students from Science, Mathematics, and Engineering disciplines at both undergraduate and graduate levels. A nine-construct model was developed and validated using both newly developed and adapted instruments. The results indicated an acceptable model fit (SRMR = 0.12, NFI = 0.89) and explained variance of R2 = 0.461R2. Despite concerns about inaccuracy, misuse, and over-dependence on generative AI, students generally held positive views about its use for OGI. Factors contributing to this positive perception included familiarity with technology (β = 0.346), help-seeking behavior (β = 0.21), perceived enjoyment (β = 0.281), and multitasking abilities (β = 0.25). Conversely, social influences, such as subjective norms, did not significantly impact perceptions. It can be concluded that academic help-seeking, enjoyment derived from its use, and the nature of being multitasking are key factors that encourage students to adopt GPT variants, in contrast to the prevailing subjective norms regarding their use. Consequently, higher education institutions should implement strategies to monitor and regulate the use of generative AI to enhance educational experiences and outcomes.
Clinical neuropsychology training institutions face the challenge of providing up-to-date instruction on rapidly evolving healthcare innovations, including teleneuropsychology (teleNP). This study explored the training needs, priorities, and preferences of Australian clinical neuropsychology trainees and supervisors to inform future training. An exploratory qualitative design was employed. Semi-structured interviews were conducted with 13 postgraduate neuropsychology trainees and 11 supervisors. Data were analyzed using reflexive thematic analysis. Four broad themes and four subthemes were generated: (1) initial disruption evolved into confidence with practice; (2a) knowledge and skill gaps and (2b) practice considerations; (3) building competence through structured learning and practice resources; (4a) teleNP training needs and (4b) competencies. In early-stage teleNP implementation, a lack of formal training led to high levels of anxiety which interfered with learning. Adjustment was supported by a collaborative “learning together” process that leveraged the variable technical and clinical skills of each party. Trainees sought observational and practical learning, while supervisors provided scaffolded training, progressing from foundational skills to simulated teleNP practice. Overall, both groups believed teleNP training should be embedded within postgraduate training. Seven training considerations and 11 teleNP competencies are proposed, derived through integration with the extant literature, to guide future implementation. The findings support the need for structured, competency-based teleNP training to be embedded early within clinical neuropsychology education. Such training aligns with emerging competency frameworks, prepares trainees to provide safe, ethical services, and supports efforts to improve healthcare access.
Mobile health (mHealth) applications are increasingly promoted as tools to support access, efficiency, and continuity of care across behavioral health and primary care settings. While patient engagement with mHealth technologies has been widely studied, clinicians play a critical role in determining whether these tools are recommended and sustained in practice. Understanding clinician readiness for mHealth applications can inform behavioral health training, workflow planning, and future technology evaluation. This exploratory study examined integrated care clinicians’ readiness for mHealth applications using Technology Acceptance Model (TAM)-informed domains, with attention to provider role, personal mHealth experience, and years of clinical experience. This cross-sectional exploratory study analyzed survey data from 59 clinicians practicing in integrated care settings in the United States. Participants included primary care physicians and behavioral health providers. Clinicians completed a Technology Acceptance Model-informed questionnaire assessing perceived usefulness, perceived ease of use, attitude toward use, facilitating conditions, and intention to use mHealth applications. Descriptive statistics characterized overall readiness. Group differences were examined using independent-samples t tests with Hedges’ g effect sizes. Correlations examined associations with years of clinical experience and intention to use. Sensitivity analyses assessed distributional assumptions, ordinal response patterns, and multiple-testing concerns. Analyses emphasized effect sizes, confidence intervals, and exploratory interpretation. Overall, clinicians reported neutral to moderately favorable readiness across TAM-informed domains. Readiness did not differ meaningfully by provider role. Compared with clinicians reporting no personal mHealth use, clinicians reporting personal use had lower, more favorable scores for perceived usefulness (M = 2.95 vs. 3.59, g = 0.64), perceived ease of use (M = 2.70 vs. 3.32, g = 0.62), and attitude toward use (M = 2.82 vs. 3.56, g = 0.55). These associations did not remain statistically significant after Holm adjustment. Years of clinical experience showed a modest association with less favorable attitudes toward mHealth adoption (r = 0.28, 95
Exam-related anxiety is common in higher education and can undermine students’ performance and well-being, yet timely support is often limited by access barriers and service capacity. This mixed-methods study examined whether a brief voice-based Conversational AI (CAI) interaction is associated with short-term reductions in self-reported state anxiety in undergraduate students and probed the experiential mechanisms underlying any change. Thirty students who scored high on the State subscale of the State–Trait Anxiety Inventory (STAI-S) but below the clinical trait-anxiety threshold completed the STAI-S, engaged in a 10 to15-minute private voice conversation with the agent, and repeated the STAI-S. They then joined one of six focus-groups (five participants each); transcripts were subjected to reflexive thematic analysis. Quantitatively, mean state anxiety declined from 52.13 (± 5.31) to 47.97 (± 5.62), a large within-subject effect (t = 6.16, p <.001, d = 1.12). However, post-intervention mean scores remained elevated, indicating that anxiety levels were reduced but not resolved. Topics gleaned from post-treatment focus groups yielded 16 codes clustered into eight higher-order themes. Positive appraisals highlighted the chatbot’s non-judgmental emotional “safe space,” its capacity for cathartic venting and rapid re-regulation, and the convenience of round-the-clock, persona-tailored access. These positive appraisals may help contextualize the observed pre-post decline in anxiety scores. Nonetheless, participants voiced reservations: superficial or repetitive advice, occasional misinterpretations, a disconcerting “uncanny” tone, and concern that habitual reliance might blunt real-world coping. Many therefore cast the agent as an adjunct valuable for low-stakes relief, but insufficient for deeper crises. Taken together, the findings demonstrate cautious evidence on the CAI associated pre-post change in anxiety relief along with design implications to maximize sustained benefit.
This study examines the impact of Augmented Reality (AR)-supported LEGO applications on the creative thinking behaviors and cognitive processes of gifted children compared to traditional LEGO activities. Utilizing a pre-test–post-test control group, two-factor mixed (split-plot) true experimental design, the research was conducted with 30 identified gifted students aged 10–13. Data were collected via a “Creativity Test” and a “Creativity Observation Scale,” and subsequently analyzed using mixed-design ANOVA. The findings revealed that while groups were initially homogeneous in creativity levels, the interaction between time and the AR-supported application resulted in a statistically significant increase in creative behaviors. The experimental group exhibited a superior developmental trajectory across all cognitive and affective sub-dimensions, including fluency, flexibility, originality, imagination, and tolerance for ambiguity. Furthermore, the integration of physical play within a digital context was observed to trigger vital affective behaviors such as risk-taking, curiosity, and self-confidence. The study concludes that the high interaction, immersion, and multi-sensory stimuli provided by AR technology support meaningful gains in creative productivity by dynamically restructuring children’s cognitive schemas. Ultimately, AR serves as an innovative and powerful pedagogical tool that optimizes technology-behavior interaction in unlocking the potential of gifted individuals.
Smartphones are now woven into everyday behavior across development, yet much of the evidence linking digital technology to health relies on broad exposure categories, sparse measurement, and age-siloed literatures. As a result, current research is poorly positioned to evaluate chronic smartphone exposure as a device-specific, developmentally situated phenomenon. This commentary does not argue that smartphones are inherently harmful or beneficial, nor does it claim that smartphone use causes long-term cognitive decline. Instead, it argues that existing research designs are insufficient for anticipating the developmental and lifespan health implications of chronic smartphone exposure. Evidence from youth links problematic or early smartphone use with mental health symptoms, sleep disruption, physical inactivity, obesity-related outcomes, and social relationship patterns, whereas studies of older adults often suggest that digital technology use may support cognitive aging through stimulation, compensation, and social connection. These literatures are not contradictory so much as incomplete, reflecting different cohorts, devices, contexts, and developmental periods. A life-course research agenda is needed that centers smartphone-specific measurement, intensive longitudinal methods, measurement-burst designs, passive sensing, digital phenotyping, and privacy-preserving governance for long-term behavioral data collection. Such an agenda would allow researchers to examine when, for whom, and under what conditions smartphone engagement intersects with modifiable behavioral and psychosocial risk domains relevant to cognitive health.
Digital technologies have significantly transformed individual experiences by offering unprecedented global connectivity and access to online resources. However, this widespread digital engagement is fraught with substantial personal risks, such as cyberbullying, cybercrime and psychological challenges. In this context, digital resilience has emerged as a vital resource which enables individuals to effectively navigate and bounce back from digital risks. Despite the importance of digital resilience, a unified conceptualisation of its various dimensions and the main factors promoting resilience appears to be somewhat lacking in the current state of research. Without a clear consensus on these dimensions and the promoting factors, efforts to measure, foster or apply practical digital resilience are likely to remain fragmented or inconsistent. This study systematically reviewed the digital resilience discourse to produce an integrated framework that clarifies the dimensions and promoting factors of digital resilience. Our research identified two dimensions: the individual dimension and one’s socio-environmental realm. The former consists of five factors, and the latter of two factors that promote resilience against digital adversities. The findings provide empirical evidence that future conceptualisations of digital resilience should incorporate both individual and socio-environmental dimensions. This integrated model addresses the lack of a consistent and empirically grounded conceptualisation of digital resilience identified by previous researchers.
Healthcare workers (HCWs) report elevated distress. Accessible and personalized mental health intervention programs for HCWs are limited. Technology-based intervention support programs could mitigate adverse health outcomes in HCWs. Using a feasibility approach, we report engagement with a technology-based mental health screening, brief intervention, and referral to treatment program designed for HCWs from a quality improvement project. 598 HCWs across seven hospital units were invited to participate. Participants were not recruited as a treatment-seeking sample. HCWs completed a baseline survey and could opt-in to brief, tailored text-based screenings with real-time feedback. HCWs completed a 90-day follow-up survey. Of the 598, 80 (13
Self-disclosure (SD), or the process of sharing personal information with others, plays a key role in the formation and maintenance of relationships in online spaces. While previous research has consistently demonstrated the importance of individual demographic, mood and social factors on SD, many studies have focused only on isolated components or younger age groups. This study examined the self-reported self-disclosure behaviours of 493 (286 women, 202 men, 5 non-binary) adults aged 18–91 years (Mage = 43.7, SD = 19.3). The aim of this study was to investigate how sociodemographic factors such as age, gender, income and mood influence SD patterns (measured by disclosure appropriateness, intimacy, quantity and valence) in a diverse adult sample. Age, gender and mood were all seen to influence reported self-disclosure behaviours, whereas income was not. Younger participants reported disclosing more intimate information than older participants did (p < .001). Men found it more appropriate to disclose personal information publicly, reported disclosing more intimately and at a higher rate than women did (all p < .05). Furthermore, those with higher levels of depression, anxiety and stress all reported disclosing more intimately online (all p < .001) than those with lower scores did. These findings provide foundational knowledge of how demographic factors and mood states may shape online disclosure. Future research could examine the impact of other factors, including personality traits and privacy concerns and utilise observational measures of self-disclosure. Furthermore, clear classification of culture and recruitment of diverse individuals should be ensured in future online disclosure studies.
The global proliferation of mobile health (mHealth) applications has generated a rich but dispersed evidence base spanning gamification design, privacy governance, and user trust—three constructs that are rarely studied together despite their interdependence in shaping adoption and sustained engagement. This study addresses that gap through a mixed-methods design comprising two distinct components. The first component is an evidence-mapping review based on a systematic protocol covering six databases and relevant regulatory grey literature. It maps representative and methodologically significant studies published between 2000 and 2025 and integrates the three research streams through a unified coding framework. The second component is an exploratory analysis of 494 publicly available user reviews of three patient portal applications using Kruskal–Wallis tests, Mann–Whitney U tests, and binary logistic regression. The evidence map shows that studies of gamification effectiveness rarely incorporate privacy or trust models, while privacy and trust research seldom examines specific gamification mechanisms. Regulatory traceability is also inconsistently reported. In the patient portal dataset, operational reliability, rather than privacy governance or gamification sophistication, was the trust-related factor most strongly associated with negative evaluations. Furthermore, the study found that gamification is most likely to support engagement when it is introduced after basic system reliability has been established. The study contributes an integrated framework for understanding gamification, privacy, and trust in mHealth and outlines implications for information systems theory, equitable health-app design, regulatory policy, and future research.
Extending conventional health and well-being services with technology has proven to be acceptable and effective. However, implementing such technology in routine care requires contextual tailoring to ensure successful uptake. The Unified Theory of Acceptance and Use of Technology (UTAUT2) is an established model with predictors and moderators of intention to use technology and use behavior. The current study aimed to design a concise screener for technology acceptance in the health and well-being field based on UTAUT2 predictors and to provide a preliminary evaluation of the instrument. The 11-item UTAUT2-Screener includes 7 predictors, i.e., performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit, as well as three moderators and behavioral intention. A within-subject repeated measures design was used. Spearman’s correlations were used to test the convergent validity concurrent validity, and the test-retest reliability. Analyses on 184 individuals from the general population demonstrated a moderate association with the original UTAUT2 (mean ρ = 0.63), with some variability across the subscales. More specifically, facilitating conditions had the weakest, but still moderate association, while hedonic motivation exhibited the strongest correlation. As an instrument with single-item scales, the UTAUT2-Screener is provided for use in contexts where only brief measures are feasible and researchers or clinicians are willing to accept the reduced psychometric robustness that comes with shorter assessments. The screener provides insights into specific barriers for technology adoption and can consequently support the development of tailored acceptance-promoting interventions, hereby supporting the uptake of digital health and well-being services in practice.
As AI-driven chatbots increasingly support mental health interventions, understanding how their assigned disclosure label influences user experience is crucial. This mixed-methods study (N = 187; recruited via Prolific; ages 19–68; 52
Social comparison on social media is an increasingly studied phenomenon, particularly in relation to its emotional and behavioral implications as they vary across different usage patterns. This study explores how the personality trait of agreeableness influences social comparison on social media, particularly through passive usage (content consumption without interaction). A moderated mediation model was tested where passive use mediates the link between agreeableness and comparison behaviors, and positional thinking (evaluating oneself relative to others) moderates this relationship. Using data from 476 Italian participants, the findings reveal that higher agreeableness is associated with less comparison-based social media use, and that this association is fully mediated by lower levels of passive, consumption-based use. The hypothesized moderating effect of positional thinking on the direct path was not supported, although conditional total effects suggested that the overall negative association between Agreeableness and comparison-based use may be stronger at medium and high levels of positional thinking. Overall, the results highlight the combined impact of personality and cognitive style on social media experiences, offering insights into how individual differences shape online behavior.
The study aims to evaluate how attitude, subjective norms, perceived behavioral control, and behavioral intention influence the use of AI among public university students of Bangladesh. The study collected data from the students of public universities of Bangladesh by using convenience sampling. We have collected data from 416 participants through a questionnaire designed with a five-point Likert scale. Data were analyzed using IBM SPSS Statistics 27 and SmartPLS 4.1.1.5. The study’s findings revealed that attitude, subjective norms, perceived behavioral control, and behavioral intention positively and significantly influence students’ desire and actual behavior to adopt AI tools. Perceived behavioral control is identified as the most influential factor (directly and indirectly), subsequently attitude, and subjective norms of both behavioral intention and actual use behavior to adopt AI tools. The study assists academics and policymakers in comprehending the elements that inspire students to utilize AI tools, enabling them to formulate user-friendly policies for student development. The study’s scope was confined to students at public universities in Bangladesh. Data were collected using a closed-ended, structured questionnaire, which limited participants’ opportunity to offer detailed explanations. Additionally, the cross-sectional design prevents establishing causal relationships among the variables. This is the first study in the Bangladesh context that examines students’ actual behavior toward AI, utilizing the Theory of Planned Behavior, a framework overlooked in prior research.
Mental health and well-being issues are prevalent in undergraduate students, and universities are struggling to meet demand for services. Virtual reality (VR) interventions have emerged as a tool for mental health and well-being, but research lacks end-user perspective. To examine the impact of engagement with five different virtual reality applications on mood and stress and document the user perception of students, a single group (N = 20), pre-post study design was used to evaluate mood and stress before and after the use of five commercial virtual reality applications. Students completed a visual analog scale for mood (VAS-M) and stress (VAS-S), numerically ranked their perception of each application's potential to contribute to their well-being, and numerically rated how they perceived each application to positively contribute to their well-being if used regularly. Paired samples t-tests for mood and stress revealed statistically significant VAS-M changes for Linelight [t(19) = -3.65, p <.01], MultiBrush [t(19) = -4.01, p <.001], and Nature Treks VR [t(19) = -4.06, p < .001]. Guided Meditation [t(19) = 3.08, p <.01] and Nature Treks VR [t(19) = 3.22, p < .01] yielded statistically significant changes in VAS-S scores. Brief engagement with VR applications shows potential mental health and well-being benefits to undergraduate university students. Additionally, end users perceive multiple commercial applications as holding potential to benefit their mental health and well-being. This suggests commercial VR applications could be offered to undergraduate students as well-being services on university campuses.
Transformative experiences (TEs) are brief and profound experiences that can lead to significant changes in self-perception and emotional understanding. Recent literature suggests that immersive virtual reality (VR), through its properties such as sensory immersion and sense of presence, can be a powerful tool to elicit TEs. This experimental study aimed to investigate the transformative potential of a VR-TE compared to a traditional media-based TE (audio-TE) on epistemic expansion (broadening one’s understanding) and positive emotions (PEs). The role of individual differences, such as mindful attention, engagement with beauty, and gender, was also explored. Seventy-eight young adults from Italy and Spain, aged 18–30, were randomly assigned to either a VR or audio-TE condition. The VR-TE group experienced a 10-minute virtual TE (a metaphorical journey in a natural setting), whereas the audio-TE group heard the same narrative without visuals. Both groups completed questionnaires before (t0) and after the intervention (t1). Student’s t-test showed that the VR-TE group reported significantly higher epistemic expansion (p = .020) and greater increases in PEs at t1, especially in self-transcendent PEs such as awe (p < .001) and hope (p < .001) compared to the audio-TE group. These effects emerged regardless of participants’ gender, baseline mindful attention, or engagement with beauty (epistemic expansion: ANCOVA, F(1,73) = 7.99, p < .006, partial η² = 0.09; PEs: MANCOVA, F(8,65) = 4.18, p < .001, partial η² = 0.34), suggesting that VR’s capacity to induce transformative states may transcend these individual differences. This study contributes to the growing body of research on technology-mediated transformation and offers insights for designing personalized VR interventions aimed at enhancing personal growth, reflection, and psychological well-being. Future research should investigate the long-term effects of VR-based transformative experiences and explore their applicability across diverse and clinical populations.
