ABSTRACT People with disabilities receive fewer callbacks when applying for jobs compared to people without disabilities. To minimize the adverse effects of having a disability in the job application process, some people with disabilities use mitigation strategies during the disclosure of a disability. We test the impact of two often‐used and recommended mitigation strategies in resumes: (1) claiming, that is, emphasizing positive attributes, and (2) downplaying, that is, shifting attention away from the disability towards other characteristics. Across two survey experiments ( n = 445 and n = 1999), we find that employers give socially desirable answers about which candidate they advance. Using a Bayesian Truth Serum—a scoring method that helps lower social desirability—we find that disclosing a disability leads to discrimination in this part of the application process. Mitigation strategies are ineffective or backfire, depending on the wording. In a field experiment with 1509 applications, we verify these results: Employers discriminate against people with disabilities. The claiming mitigation strategy, in which people emphasize the positive attributes of disabilities, has negative effects. These findings show that people who disclose their disabilities in their resumes are discriminated against, and that mitigation strategies do not reduce such discrimination; some even increase it.

Background: Burnout is a growing concern among medical doctors, particularly in high-pressure environments, which has been exacerbated by the COVID-19 pandemic. This study investigates the prevalence and determinants of burnout among physicians working in a large hospital in Southern Italy. Methods: This online cross-sectional survey evaluated burnout and emotional distress among physicians and trainees at Catania Hospital using the Maslach Burnout Inventory (MBI) and General Health Questionnaire (GHQ-12). Data collection (July–August 2025) incorporated strict anonymity to mitigate social desirability bias. Statistical analyses, including chi-squared tests with Tukey adjustments and Pearson correlations, were stratified by sex and specialization area to identify significant psychological associations. Results: High levels of burnout were observed across all dimensions: 76.7% of respondents reported low personal gratification, 70.8% showed high depersonalization, and nearly 50% experienced high emotional exhaustion. Female physicians and recent graduates (after 2020) exhibited significantly lower levels of gratification and higher psychological distress. Service-area professionals reported lower emotional exhaustion, but also lower gratification compared to surgical specialties. Notably, otorhinolaryngology showed both the highest burnout risk and the highest gratification scores. Conclusions: Burnout is alarmingly prevalent among Italian medical doctors, and there is significant variation across sexes, graduation cohorts, and medical specialties. Despite the high burnout levels identified, the cross-sectional design and non-probability sampling necessitate a cautious interpretation of these findings. Future longitudinal research involving larger, more representative cohorts is essential to validate these results and inform targeted institutional interventions.

The clinical evaluation of craving in the context of Substance Use Disorders, is still heavily dependent on subjective self-reports, which are frequently tainted by patient anosognosia and social desirability bias, despite advancements in addiction science. Moreover, the qualitative internal states described by Indian Knowledge Systems (IKS) and the subtle neurocognitive antecedents of relapse outlined by the Binding and Retrieval in Action Control (BRAC) model are not captured by existing diagnostics. By creating a ground-breaking Multimodal AI Fusion Framework, this study fills this diagnostic gap. The goal of the study is to translate the abstract philosophical concepts of Triguna, more especially, the transition from Tamasic inertia to Sattvik balance, into objective, measurable bio-behavioral indicators. The study uses a unique,non-invasive web-based battery that synchronizes three different data streams to produce a composite Relapse Risk Index using a cross-sectional tool-development approach (N=50). First, computer vision oculometrics calculates gaze entropy using common webcams to understand the hypervigilant scanning behaviour typical in high craving states. Second, in order to identify the microscopic motor rigidities linked to maladaptive event file binding, kinematic analysis records mouse cursor movements during cognitive interference tasks, similar to an Alcohol stroop test, by examining trajectory curvature and velocity peaks. Third, speech recordings are analyzed by Acoustic and Semantic NLP to determine the prosodic signs (jitter/shimmer) of Sattvik clarity against Tamasic depression. This study goes beyond conventional psychometrics by creating a machine learning classifier to merge various physiological information. The Vedic Lifestyle Scale and the Obsessive Compulsive Drinking Scale (OCDS) are used to validate these algorithmic features. By developing a scalable, culturally based methodology, the study makes a significant addition to precision psychiatry. It makes the case that effective rehabilitation involves more than just quitting drugs; rather, it involves a quantifiable change in neuro-cognitive economy, which can now be identified, measured, and tracked thanks to the convergence of artificial intelligence and traditional psychology theory.

While life expectancy in the US has increased among both sexes, a significant sex gap in mortality has been consistently observed during the past 2 decades. To examine differences in mortality rates between males and females for overall mortality and the leading 9 causes of mortality (coded by the National Death Index as diseases of the heart, malignant neoplasms, chronic lower respiratory diseases, unintentional injuries, cerebrovascular diseases, Alzheimer disease, diabetes, influenza and pneumonia, and nephritis, nephrotic syndrome, and nephrosis). This prospective cohort study included adults 20 years or older participating in the National Health and Nutrition Examination Survey (NHANES) cycles between 1999 and 2016. Data were linked to the National Death Index from the date of survey participation through December 31, 2019. Data were analyzed from July 16, 2024, to August 14, 2025. Participation in the 1999-2016 NHANES cycles. Cox proportional hazards regression was used to estimate male-to-female hazard ratios (MF HR) for overall and cause-specific mortality, adjusting for sociodemographic characteristics (eg, age, race and ethnicity), behavioral factors (eg, smoking, alcohol use), and chronic conditions (eg, diabetes, hypertension). The adjusted MF HRs were stratified by self-rated health, race and ethnicity, income, and educational level. Among 47 056 participants (52.0% female and 48.0% male [weighted]), 12.9% (12.2% females and 13.6% males) were deceased at the end of follow-up. Males had a 63% higher risk of all-cause mortality compared with females, with the largest difference in mortality among individuals who died from heart disease (MF HR, 1.96; 95% CI, 1.72-2.24). The MF HR differed significantly across race and ethnicity for heart disease (range, 0.92 [95% CI, 0.36-2.35] for individuals of other race or ethnicity to 2.11 [95% CI, 1.80-2.48] for White individuals; P = .02 for interaction) and across income quartiles for mortality due to cerebrovascular diseases (range, 0.59 [95% CI, 0.25-1.38] for highest to 2.25 [95% CI, 1.31-3.86] for lowest income; P = .03 for interaction) and accidents (range, 0.57 [95% CI, 0.16-1.99] for highest income to 2.40 [95% CI, 1.03-5.58] for third highest income; P = .02 for interaction). No difference in the MF HR was found across self-rated health categories or education attainment levels. Information on covariates was largely collected by self-report, resulting in underreporting or overreporting due to social desirability bias. How these factors may have changed leading up to the time of mortality could not be accounted for. In this cohort study of adult NHANES participants, after accounting for a wide range of risk factors, the sex gap in mortality remained for most causes of mortality, suggesting there may be intrinsic biological factors (eg, sex hormones, chromosomes, immune response) associated with sex differences in mortality. Further research should investigate the effects of sex-linked biological factors on mortality.

Waterpipe (shisha) smoking has gained popularity among teens and young adults and is now prevalent in Japan. Yet, waterpipe smoking in the Japanese population remains understudied. This study examined the prevalence, characteristics, and knowledge/attitudes related to waterpipe use among Japanese teens and young adults, aiming to inform efforts to prevent further use. A cross-sectional analysis of the 2024 Japan Society and New Tobacco Internet Survey was conducted among individuals aged 16-29years (N = 5564). Inverse probability weighting was used to generate estimates representative of the Japanese national population. Descriptive analyses assessed waterpipe use prevalence, use status, and reasons for use. Multivariable logistic regression-controlling for demographic, socioeconomic, and substance use covariates-evaluated associations between knowledge/attitudes and any lifetime (versus never) waterpipe use. Among teens and young adults, 10.2% reported waterpipe use, with 65% of current users smoking occasionally. Usage was highest among the 20-24 age group. Common reasons for use included peer influence (59.7%), interest in shisha bars/cafés (54.2%) or interest in flavors (47.9%), and perceived reduced harm (40.7%). After adjusting for covariates, perceiving waterpipe use as less harmful (adjusted odds ratio [AOR] = 1.75) or "cool" (AOR = 1.44) remained strongly associated with significantly higher odds of lifetime use. Waterpipe smoking prevalence among young people in Japan is a public health concern, driven by peer influence, product appeal, and misperceptions of reduced harm. Targeted education and regulation to address perceptions about harm and social acceptability, along with continued monitoring, are warranted. To our knowledge, this is the first study to examine waterpipe smoking among teens and young adults in Japan, the most prevalent age group for waterpipe smokers globally. The reasons cited for use were similar to those in other countries, including peer influence and appealing flavors, with misconceptions about reduced harm and viewing waterpipe use as "cool" being particularly associated with use. Efforts to address misperceptions of reduced harm and social desirability are essential to reducing youth vulnerability. Our findings highlight the need for continued monitoring, targeted education, and policy interventions to tackle this emerging public health concern.

Purpose This study examines the effects of digital health technologies on enhancing children's healthcare utilization in the Kigoma region of Tanzania. It also investigates the factors that influence both the adoption and the extent of usage of digital health technologies among caregivers. Design/methodology/approach A cross-sectional research design was employed, using data collected from 400 respondents selected through a multi-stage sampling technique. A double-hurdle model was applied to analyze the determinants of digital health technology adoption and usage intensity, while a probit model was used to assess the effect of digital health usage on children's healthcare utilization. Findings The results indicate that awareness (ß = 0.643; p = 0.061), ease of use (ß = 0.113; p = 0.000), internet connectivity (ß = 0.512; p = 0.000), and participation in digital health education campaigns (ß = 0.373; p = 0.000) significantly increase the likelihood of adopting digital health technology. In contrast, negative attitudes (ß = −0.738; p = 0.069), low household income (ß = −0.649; p = 0.000), and larger household sizes (ß = −0.217; p = 0.000) reduce the probability of adoption. Among adopters, usage intensity is significantly enhanced by ease of use (ß = 0.747; p = 0.000), better internet connectivity (ß = 0.406; p = 0.001), higher household income (ß = 0.429; p = 0.000), participation in health education programs (ß = 0.607; p = 0.000), and healthcare provider assistance (ß = 0.419; p = 0.001). The double-hurdle model is strongly significant (?2 = 148.61; p = 0.000), confirming the explanatory strength of the selected variables. Regarding children's healthcare utilization specifically on vaccination uptake, mobile health applications (dy/dx = 0.384; p = 0.000) and online appointment/reminder systems (dy/dx = 0.725; p = 0.000) have significant positive effects, while electronic health records show a marginal positive influence (dy/dx = 0.162; p = 0.075). Also, socio-economic factors such as education level of the respondent (dy/dx = 0.118, p < 0.01) is positively and significantly associated with timely vaccination, Household income (dy/dx = 0.074, p < 0.05) similarly shows a positive and statistically significant effect, Participation in health education campaigns (dy/dx = 0.244, p < 0.01) is positively associated with vaccination uptake. Research limitations/implications Although the study provides valuable insights, several limitations should be considered. First, the cross-sectional design restricts causal interpretation of the observed associations. Second, self-reported measures on digital health usage may be influenced by recall or social desirability bias. Third, the study focused on mothers with children under five years, and perspectives from fathers or other caregivers were not captured. Lastly, findings are limited to Kigoma and may not fully represent all regions of Tanzania with different digital health infrastructures. Future studies could adopt longitudinal or mixed-method approaches to strengthen causal inference and generalizability. Practical implications The study recommends expanding digital health training, improving internet access, subsidizing digital health services and strengthening trust-building initiatives to enhance adoption and utilization. Policymakers should focus on integrating digital health into mainstream healthcare services to maximize its impact on healthcare accessibility, particularly for children in resource-constrained settings such as Kigoma. Originality/value This study is among the first to empirically assess both the determinants and effects of digital health technology adoption on children's healthcare utilization in a resource-constrained setting such as Kigoma, Tanzania. By applying a double hurdle model alongside a probit framework, it provides a nuanced understanding of adoption drivers, usage intensity and health outcomes. The findings highlight the distinct impact of mobile health applications and online reminder systems on pediatric healthcare access, offering actionable insights for policymakers and practitioners aiming to integrate digital health into underserved healthcare systems.

Purpose This study aims to examine how three contextual factors – reciprocity history with the knowledge seeker, communication media richness and the type of requested knowledge – influence knowledge workers’ responses in terms of knowledge hiding (playing dumb and evasive hiding) and knowledge sharing (partial or full sharing). Design/methodology/approach This study uses a quasi-experimental design, using a serious game with a simulated realistic scenario to collect data. A total of 199 knowledge workers from a German automotive company participated in the game, providing valuable insights into their responses to knowledge requests. Findings The results show that knowledge workers vary their knowledge hiding and sharing behaviours depending on reciprocity history with colleagues, the type of knowledge requested and the communication medium used. These findings suggest that a straightforward classification of knowledge hiding and sharing fails to capture the complex and nuanced ways employees manage knowledge requests in organisational settings. Originality/value This paper broadens the scope of knowledge hiding research by examining both knowledge hiding and knowledge sharing behaviours within a single framework and empirically testing the relationships between key antecedents and these behaviours. In addition, the use of a quasi-experimental design, based on a serious game for data collection, offers a novel methodological approach. This method reduces social desirability bias by capturing more authentic knowledge hiding and sharing behaviours compared to traditional approaches, providing a foundation for future research in knowledge management, particularly in the study of socially undesirable behaviours.

ABSTRACT Integrating empathy ability into service robots can be regarded as a potential resolution to enhance harmonious human-robot interaction experiences. However, it remains unclear whether and how service robots’ empathy ability impacts unethical consumer behavior (UCB). Therefore, according to social exchange theory, this research explores how service robots’ empathy ability impacts UCB and the underlying mechanism. Through four experiments, we discover that service robots’ empathy ability reduces UCB, with anticipatory guilt serving as the mediator. Moreover, the salience of anticipatory guilt weakens the impact of empathy ability on UCB. Additionally, consumers’ social desirability moderates the impact of service robots’ empathy ability on UCB through anticipatory guilt. These findings not only broaden our insight into UCB in human-robot interaction but also provide guidance for enterprises to develop more well-designed service robots to tackle UCB.

The authors explored the theory that spontaneity and nonspontaneity represent two separate continua rather than opposite states of mind by means of a newly designed Spontaneity Assessment Inventory (SAi) and Spontaneity Deficit Inventory (SDI). The authors administered the SAI, the SDI, the Friedman Well-Being Scale (FWBS), and the Marlowe-Crowne Social Desirability Scale (MCSDS) to agroup of 103 male and female students. The results confirmed the overall notion that spontaneity and nonspontaneity cannot coexist at the same time. However, they can exist within the same person. The two-continua hypothesis was supported. The SAi and SDI showed a satisfactory split-half reliability, correlated in the expected direction with the FWBS scores, and correlated positively with the MCSDS. The authors also discuss the possible implications of the findings.

The utilization of health research evidence is essential for informed decision-making, especially in health planning and achieving Universal Health Coverage (UHC). However, limited information exists regarding its use in planning in Lower Middle-Income Countries (LMICs), including Tanzania. This study assessed the use of health research evidence and factors influencing its utilization among health planning teams. A descriptive qualitative approach was used to examine determinants of evidence use in health planning. Data were collected through six focus group discussions and 34 in-depth interviews with planning team members from regional, council, and health facility levels. The COM-B model (Capability, Opportunity, Motivation) was applied to assess factors influencing evidence use, and thematic analysis was conducted on the transcribed data. Although participants reported using available planning guidelines, the incorporation of health research evidence into planning was limited. Capability barriers included inadequate knowledge and skills for evidence-based planning. Opportunities included planning guidelines that supported evidence use, research coordinators, policymaker-researcher interactions, and infrastructure such as computers and the internet; however, access to knowledge translation tools was limited. Motivation was influenced by incentives such as extra duty allowances, promotions, and professional development opportunities. The use of health research evidence in planning processes in Tanzania is low, influenced by capability, opportunity, and motivation factors. Enhancing capacity-building, fostering collaboration, strengthening policy support, and improving infrastructure are recommended. Future research should evaluate the effectiveness of these interventions and their impact on healthcare planning and delivery. Efforts were made to minimize social desirability and selection biases.

In personality psychology, questionnaires are an established tool for assessing psychological traits. In forensic risk assessment, however, their use is often met with skepticism. The aim of this review is to critically evaluate the role of self-report information for assessing the risk of sexual recidivism. Focusing on individuals convicted of sexual offending, about 500 publications were identified through a systematic, string-based search across three electronic databases. The final sample was constituted by 95 publications that met the inclusion criteria - empirical studies using or investigating self-report measures in sexual risk assessment, with a minimum of 50 participants. Various risk-relevant constructs assessed by self-reports were examined. The results predominantly support the validity of self-report measures, particularly for assessing sexuality-related constructs, offense-supportive cognitions, prior offenses, and aggression. Comparing self-reports to other instruments showed some unique variance to the prediction of recidivism. The association with desirable responding was found to have an overall small effect size. Additionally, social desirability often emerged not as a response bias but as a risk-relevant trait. However, contextual factors, such as confidentiality and incentives, may significantly influence response distortion, presenting limitation for their use in high-stakes forensic decision-making. Overall, self-reported information appears to be a valuable complement to other assessment methods, significantly contributing to the prediction of recidivism. Nevertheless, the relationship between self-reports, contextual factors, and offender characteristics should be carefully considered when selecting the most appropriate assessment method. The findings of this study, along with its limitations and implications for future research, are discussed.

This study presents DeepVisionAnalytics, an integrated framework that combines eye tracking, OpenCV-based computer vision (CV), and machine learning (ML) to support objective analysis of consumer behaviour in visually driven tasks. Unlike conventional self-reported surveys, which are prone to cognitive bias, recall errors, and social desirability effects, the proposed approach relies on direct behavioural measurements of visual attention. The system captures gaze distribution and fixation dynamics during interaction with products or interfaces. It uses AOI-level eye tracking metrics as the sole behavioural signal to infer candidate choice under constrained experimental conditions. In parallel, OpenCV and ML perform facial analysis to estimate demographic attributes (age, gender, and ethnicity). These attributes are collected independently and linked post hoc to gaze-derived outcomes. Demographics are not used as predictive features for choice inference. Instead, they are used as contextual metadata to support stratified, segment-level interpretation. Empirical results show that gaze-based inference closely reproduces observed choice distributions in short-horizon, visually driven tasks. Demographic estimates enable meaningful post hoc segmentation without affecting the decision mechanism. Together, these results show that multimodal integration can move beyond descriptive heatmaps. The platform produces reproducible decision-support artefacts, including AOI rankings, heatmaps, and segment-level summaries, grounded in objective behavioural data. By separating the decision signal (gaze) from contextual descriptors (demographics), this work contributes a reusable end-to-end platform for marketing and UX research. It supports choice inference under constrained conditions and segment-level interpretation without demographic priors in the decision mechanism.

Aggression is a complex behavior that is difficult to capture using traditional methods, such as questionnaires and lab-based aggression tasks. These methods present challenges due to social desirability bias and limitations in translating findings into real-world situations. In this review, we discuss how emerging technologies, including virtual reality, video games, hyperscanning, biosignal recording, ecological momentary assessment and social media analysis, offer improved construct and ecological validity and can contribute to the refinement of integrative theoretical models of aggression. We comprehensively address advantages (e.g., immersion, realistic simulation, real-time and context-sensitive data collection and interpersonal dynamics) and limitations of each technology compared to traditional methods and highlight remaining gaps in aggression research. Additionally, we examine aggressive behavior related to the emergence of new technologies in digital spaces, focusing particularly on cyberbullying and the metaverse. We also review machine learning approaches for detecting cyber-aggression on social media platforms. We propose shifting from static, individual-level assessments to dynamic, context-sensitive frameworks that capture aggression in real time, in more ecological settings and digital environments. This shift in operationalization holds the potential to advance theoretical understanding, guide future research and inform clinical and forensic interventions.

Purpose This study aims to develop and validate a Digital Conformity Scale (DCS) to understand individuals' conformity to digital norms, addressing the erosion of individuality influenced by pervasive social media exposure. The research explores conformity factors through a meta-analysis and scale development grounded in Social Influence Theory and Banerjee's Herding Behavior Theory. Design/methodology/approach A meta-analysis was conducted to explore the determinants of conformity in various contexts. After that, data were collected from three diverse groups: 282, 468 and 100, respectively. An exploratory factor analysis (EFA) was performed on a preliminary scale with 50 items. This was followed by a confirmatory factor analysis (CFA) for validation. Finally, the last study assessed digital conformity alongside related constructs for convergent and discriminant validity. Findings The scale demonstrated good consistency, with EFA indicating four distinct factors. The CFA supported a four-factor model with 25 items, fitting well within the data. Research limitations/implications Self-report measures may introduce biases and social desirability effects, limiting generalizability. Additionally, the scale's length may burden respondents. Practical implications The DCS is a valuable tool for understanding digital conformity, promoting well-being and contributing positively to societal welfare. Social implications Insights from this research can inform guidelines and regulations to encourage responsible digital interaction, contributing to a healthier digital society. Originality/value The digital era requires rethinking traditional social influence principles, incorporating modern phenomena like trend adoption (TA) and fear of missing out (FoMo). The DCS integrates these characteristics into Social Influence Theory, guiding and navigating the digital landscape and fostering genuine online relationships.

Introduction: There is an increasing need for psychological counseling services during adolescence, due to the many changes the adolescents go through during this period in all areas of their development, This study aimed to investigate the effectiveness of a group-counseling program based on Zumba exercises in enhancing the emotional well-being among a sample of adolescent female students. Method: Thirty teenagers from the Greek Catholic Secondary Girls' School, affiliated with the Directorate of Education in the First Zarqa District participated in the study. They volunteered to participate in the developmental counseling program, their ages ranging between 13 and 16 years old, with an average age of 14.5 years. The participants were randomly assigned to two equal groups, one experimental and the other control, each consisting of 15 students. A pre- and post-test was applied to them, while a follow-up test was applied to participants of the experimental group one month after the end of the group-counseling program. the researcher developed a group-counseling program based on Zumba exercises. Additionally, the researcher translated the Sterling Emotional Well-Being Scale for Children and Adolescents, consisting of 15 items distributed across three dimensions: positive emotional state, positive outlook, and social desirability. The psychometric characteristics of validity and reliability of the scale were verified. The program was implemented for the participants in the experimental group over the course of 10 sessions, with each session lasting 60 minutes, conducted twice a week. Results: statistical analysis indicated statistically significant differences in posttest scores between the experimental and control groups, favoring the experimental group in the total score of the Sterling Emotional Well-being Scale for Children and Adolescents, as well as subscales. Furthermore, the results indicated no differences in the scores of the experimental group on the posttest and follow up test after one month, indicating the maintenance of emotional well-being levels among the experimental group members one month after the counseling program ended. Conclusion: This suggested that the group counseli ng program based on Zumba exercises used in this study contributed to enhancing emotional well-being among the sample of adolescent female students in the city of Zarqa, in addition to the persistent effect of the program after one-month follow-up. Recommendation: the implementation of Zumba-based programs with adolescent female students to help enhance their emotional well-being. It also suggested conducting experimental studies based on Zumba exercises and positive psychology on diverse samples of students across different educational levels and individuals from the local community of all ages.

Background/Objectives: Cyber bystanders can choose from several different strategies during cyberbullying incidents and have a significant effect on the situation. Hence, cyber bystanders are specifically targeted by prevention programmes and research investigating variables influencing cyber bystander responses is crucial for such programmes. The aim of our study was (1) to explore contextual factors’ effect on cyberbullying incidents’ perceived severity and (2) the most frequent cyber bystander responses. We also aimed (3) to learn how the context of cyberbullying incidents affects cyber bystander responses and the joint effect of individual and contextual variables on cyber bystander responses. Methods: In total, 314 Hungarian high school students participated in our online survey (mean age = 16.15, SD = 3.28). The respondents filled in self-administered questionnaires that measured cyber bystander responses, severity of different cyberbullying incidents, empathy, moral disengagement, social desirability, and cyberbullying engagement. Results: First, our results showed that the respondents perceived public and visual cyberbullying, and when the victim was upset by it the most severe incidents. Second, in almost every condition, the two most likely cyber bystander responses were ignorance and emotional support for the victim. Third, the individual and contextual variables had a joint effect influencing cyber bystander responses except for emotional support to the victim that was only influenced by individual variables, i.e., empathy, moral disengagement, and social desirability. Conclusions: All in all, our results showed that all cyberbullying contexts were associated with cyber bystander responses and the prominent association between moral disengagement, social desirability, empathy, and prosocial cyber bystander responses. Moreover, these results could guide cyberbullying prevention to focus on cyber bystanders’ empathy training, decreasing their moral disengagement, and educating them about the effects of online contextual variables.

Caring for individuals with dementia at home poses significant challenges for family caregivers, particularly in families with amigration background. Previous studies have primarily relied on interviews and surveys, which may be biased by shame and social desirability. In contrast, caregivers often express themselves more spontaneously and less filtered on social media, potentially providing new insights into their reality of life. This study aims to examine social media posts from Turkish origin family caregivers regarding their experiences in the context of home care. Atotal of 123 posts from Instagram, Facebook, TikTok, YouTube and online forums were analyzed using qualitative content analysis. Overall, three main themes were identified: (1)psychological and physical burdens, (2)criticism of the healthcare system, and (3)managing caregiving responsibilities. Social media offer aspace for exchange and support for family caregivers, while structural deficits, lack of culturally sensitive services and bureaucratic barriers complicate care. The often culturally embedded responsibility for family-based care can be both asource of overload and aresource. Future measures should promote structural improvements and diversity-sensitive support services.

A cluster analysis of veterinarians' antimicrobial prescription preferences for companion animals in Portugal.

Social relationships are central to well-being because they fulfill social affiliation needs. To explain how social needs are regulated, theories describe daily-life processes among social desire, social contact, and affect. Still, these processes remain empirically underexplored because of their complexity. In this study, we estimated multivariate associations of social desire and affect with social contact across different modalities (in-person, digital), time scales (hourly, daily), and levels of analysis (between-person, contemporaneous, temporally lagged). Participants from two age-heterogeneous samples answered experience sampling questions and contributed data through unobtrusive smartphone sensing, with roughly hourly assessments across 2 days (N = 303) and daily assessments across 14 days (N = 377). Multilevel vector autoregressive network models revealed associations between social contact, social desire, and affect across levels of analysis. Results were highly specific to the examined time scale. When measured at an hourly timescale, people desired more social contact than usual when they engaged in more in-person contact, and higher social desire predicted more future social contact in both experience sampling and smartphone sensing. In contrast, at a daily timescale, social desire did not predict future contact. Bidirectional linkages of affect and social contact were also much denser hourly (vs. daily). Compared with in-person contact, calls and communication app usage generally showed distinct associations with affect. We discuss theoretical implications for the dynamic regulation of social needs, especially regarding homeostatic temporal processes and the role of positive affect in predicting social contact. Finally, we delineate future directions of multimethod research into daily-life social dynamics. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Although a growing body of work is detailing the barriers to compassion in healthcare, few studies have examined how providers sustain compassion over time. Prior studies have predominantly been qualitative. Extend prior studies by assessing the structure and likely efficacy of compassion-maintaining strategies. Secondary analysis of cross-sectional physician data gathered as part of a larger project (Consedine et al.J Gen Intern Med, 40(9), 2080-2086,26). In the parent study, 1065 patients nominated a primary care physician. Of 575 doctor invitations sent, 219 unique doctors (38.1% of invitees) responded. Participants provided demographic and training/work data, before completing measures of burnout, trait compassion, compassion strategy use, social desirability, and compassionate behaviour. Principal components analysis revealed two broad classes of compassion-sustaining strategies-compassion-specific (focused directly on the generation and/or maintenance of compassion) and general (focused on general self-care as a means to sustain compassion). Correlations showed that while compassion-specific strategy use was closely linked to greatertrait compassion and compassionate behaviour, general self-care strategy use was more closely tied to workload and burnout variables. Although compassion is routinely challenged in healthcare, providers use an array of strategies to sustain their compassion for patients. In identifying potential targets for intervention, the current report suggests that while some strategies appear more directly tied to compassion, others are focused on sustaining compassion through self-care. Preparing healthcare trainees and doctors for the challenges to compassion may be supplemented by training in the different ways evidence suggests compassion can be enhanced. The known: Evidence suggests that compassion in healthcare is routinely challenged and can be interfered with by a range of personal, patient, clinical, and environmental factors. The new: Doctors also engage in strategies to sustain compassion, with two broad types in evidence-psychological, compassion-specific strategies and strategies to sustain compassion through self-care. These different strategies have distinct links to patient-facing and occupational health outcomes (e.g., burnout). The implications: Providers use an array of strategies to sustain compassion for patients. In identifying targets for intervention, these data suggest we should target different strategies depending on the outcomes of interest.