Synthetic biology, as an emerging field that integrates life sciences and engineering technology, is driving profound transformations in global science, ethics, and legal systems. In international legal framework, the Biological Weapons Convention (BWC) and the Convention on Biological Diversity (CBD) have established initial hard law governance systems. However, these frameworks still face structural limitations in terms of technical adaptability, the scope of provisions, and institutional coordination. Soft law, with its flexibility, non-binding nature, and ability to build consensus, is increasingly becoming an essential supplement to the international response to the ethical risks of synthetic biology. International organizations, industry alliances, and non-governmental actors are constructing a multi-layered soft law governance network through ethical guidelines, policy recommendations, and codes of conduct, providing institutional support for risk identification, technology classification, and behavioral guidance. Soft law is well-suited to perform the roles of guiding and providing feedback in governance, while hard law should focus on the construction of systems of rights and responsibilities and the establishment of obligations. There is a collaborative governance model that integrates both soft and hard law. This model, characterized by "soft law guidance, hard law consolidation, and soft law feedback," aims to create a flexible and enforceable governance framework. This approach ensures that soft law provides a timely and adaptive starting point, hard law offers a uniform and accountable foundation, and a feedback loop allows for continuous adjustment based on practical experience.
To examine temporal patterns in self-reported driving under the influence of alcohol (DUIA) and cannabis (DUIC) in Chile between 2012 and 2022, and to assess whether trends are consistent with substitution or complementarity between substances in the context of strengthened alcohol-impaired driving sanctions introduced by the Emilia law (2014), and comparatively weaker cannabis enforcement. We analyzed six waves of repeated cross-sectional data (2012-2022) of the nationally representative Chilean Drugs Population Survey (N = 26,242 licensed drivers). Outcomes were self-reported DUIA and DUIC, analyzed separately and jointly. Survey year served as a proxy for exposure to Chile's traffic laws. Descriptive prevalence estimates were calculated across waves. Temporal patterns were examined using survey-weighted logistic regression models for DUIA and DUIC and multinomial logistic regression models comparing DUIA only, DUIC only, and combined DUIA and DUIC (DUIA&C) relative to no impaired driving. Models were adjusted for sex, age, age at alcohol onset, household income, and administrative region. Most respondents reported no impaired driving, ranging from 84.6% in 2012 to 88.8% in 2022. DUIA alone was reported at 12.9% in 2012 and 7.9% in 2022, DUIC alone was measured at 0.8% to 1.6% respectively, and DUIA&C remained rare (1.2-1.9%). Adjusted logistic regression showed that the odds of DUIA, when compared to 2012, went from 0.897 (95% CI: 0.798-1.008) in 2014 to 0.600 (95% CI: 0.526-0.685) in 2022 with the difference between these two years being statistically significant (z = 4.46, p < .05). In contrast, the odds of DUIC increased from 1.345 (95% CI: 1.043-1.736) in 2014 to 1.673 (95% CI: 1.290-2.172) in 2022, with this difference also reaching statistical significance (z = 1.97, p < .05). Multinomial analyses revealed a statistically significant divergence between trends in DUIA and DUIC (difference in slope = 0.132; 95% CI: 0.101-0.164; z = 8.16, p < .001), indicating that while alcohol-impaired driving decreased, cannabis-impaired driving rose. Following the 2014 Emilia laws, DUIA in Chile declined substantially, suggesting the contribution of strengthened alcohol-focused interventions. In contrast, DUIC increased modestly, suggesting potential substitution behaviors in response to stricter alcohol regulations and weaker cannabis enforcement. These findings highlight the importance of considering cross-substance dynamics in road safety policies and underscore the need for integrated strategies that target both alcohol and cannabis, to prevent unintended behavioral adaptations and enhance overall traffic safety.
Artificial intelligence (AI) technologies are increasingly being integrated into mental health settings to support tasks such as clinical documentation and decision-making. In parallel, AI-enabled deception detection, which leverages multimodal behavioral cues like facial expressions, vocal tone, and body movements, is an emerging research area. These technologies may hold relevance in mental health contexts, where deception can compromise treatment outcomes and therapeutic trust. However, most research on AI-based deception detection has focused on law enforcement domains, resulting in a limited understanding of its applicability to mental health. The ethical, relational, and practical implications of using such technologies in clinical settings remain underexplored. This study explored stakeholder perspectives on the responsible integration of AI-enabled deception detection in therapeutic contexts. We examined what ethical frameworks and safeguards are needed to guide the use of such tools in therapy (research question 1), what technical and procedural protections are necessary to uphold client confidentiality (research question 2), and what design and evaluation strategies can mitigate bias and promote fairness in clinical applications of AI-based deception detection (research question 3). We conducted 6 virtual focus groups (n=18) with individuals who were both mental health clinicians and current therapy clients. Participants responded to a hypothetical scenario describing the integration of AI-based deception detection into therapy. A semistructured guide was used, and transcripts were analyzed thematically using a combination of inductive and deductive coding strategies. Participants expressed a range of concerns about the integration of AI-enabled deception detection in therapy, highlighting potential ethical, relational, and contextual challenges. In response to research question 1, participants described fears of a "Big Brother" atmosphere and distractions from in-session notifications. However, many viewed telehealth as a less intrusive context and emphasized respecting disclosure timing and maintaining client agency. For research question 2, participants raised concerns about unconscious data capture, subpoena risks, and unclear data protections. For research question 3, participants cautioned that such tools may exacerbate power imbalances, erode trust through false positives, and lack cultural or contextual sensitivity. Informed by these findings, the research team developed design and policy recommendations, including minimizing in-session notifications; ensuring ongoing consent; establishing transparent data policies; training models on diverse populations; exploring modeling personalization; and developing equitable use policies. While AI-enabled deception detection technology holds promise for augmenting clinical insight, its integration into therapy must be guided by a commitment to safe, ethical practice. Researchers and clinicians should collaborate to design systems that (1) integrate seamlessly into therapy without disrupting therapeutic relationships, (2) prioritize data security and transparency to protect client confidentiality, and (3) implement fairness safeguards that address cultural representation and power dynamics. Addressing these challenges is essential to ensure that AI-based deception detection enhances, not undermines, therapeutic practice.
The rise in popularity of electronic cigarettes (e-cigarettes) among adolescents in the United States during the past decade is concerning because of the device's novelty and potential long-term health effects. In response, a federal Tobacco 21 (T21) law was enacted in 2019 to raise the minimum age for purchasing tobacco products and e-cigarettes from 18 to 21 years. We examined changes in adolescent e-cigarette use after implementation of T21 during a period of broader federal tobacco control activity. We analyzed data from the 2019 and 2020 National Youth Tobacco Survey (NYTS) to assess changes in e-cigarette use among middle and high school students aged 9 to 19 years (most aged 13-17 y) following implementation of the federal T21 law. Weighted logistic regression models examined associations between policy implementation and current e-cigarette use, controlling for demographic characteristics and perceived harm and addictiveness. The prevalence of current e‑cigarette use declined from 16% (95% CI, 15%-18%) in 2019 to 11% (95% CI, 10%-13%) in 2020. After implementation of the federal T21 law in December 2019, adolescents were significantly less likely to use e‑cigarettes, with a 24% reduction in the odds of current use (odds ratio = 0.76; 95% CI, 0.64-0.91; P = .003). Federal legislation such as increasing the minimum age for purchasing tobacco and nicotine products may be an effective strategy in reducing and preventing e-cigarette use among adolescents. Future research should assess the sustainability of the effects of T21 legislation over time and examine how federal policies interact with other public health interventions to influence adolescent e-cigarette use.
Electronic health records (EHR) mostly consist of highly sensitive data, whose sharing is highly regulated due to privacy and security concerns. To address privacy protections, de-identification and anonymization techniques offer a more secure way of data transmission to ensure patient's privacy. Principal components analysis (PCA) has emerged as an anonymization technique. The applicability of more diverse and complex dimensionality reduction (DR) techniques such as Factor Analysis of Mixed Data (FAMD), or Autoencoder (AE), remains largely unexplored. The objective of this study is an investigation into the potential of FAMD and AE as anonymizers for EHR. The goal of this study is to apply advanced DR methods on three EHR datasets of varying sizes. Subsequently, a supervised prediction task is performed on the anonymized EHR using an artificial neural network (ANN), and the performance of the prediction task is compared to the performance of the original, non-anonymized EHR. The findings indicate that the use of FAMD and AE in the anonymization of EHR results in a comparable performance to that of the original, non-anonymized EHR in a downstream prediction task. This study thus indicates the potential of advanced DR as an anonymization technique for EHR, thereby underscoring the necessity for further investigation.
With the strengthening of public health, Chinese female college students have shown higher levels of HPV vaccination intention, but the actual vaccination rate is very low. This significant intention-behavior gap has become a major challenge for the prevention and control of HPV among colleges and universities. This study aims to explore the intention-behavior gap for HPV vaccine uptake among Chinese female college students on the basis of eHealth literacy (eHL) and the health belief model (HBM). A cross-sectional survey was conducted from June 16 to July 16, 2024, to assess socioeconomic status, eHL and HBM among female college students at Guangdong Medical University. Descriptive statistics were calculated, and binary logistic regression analysis was performed using SPSS 29.0 to identify significant independent associations between female college students' HPV vaccination intentions and behavior. Among the 2884 valid participants with an intention to receive an HPV vaccination, only 41.3% had converted from intention to uptake (≥ 1 dose).The key influencing factors included being from urban areas (adjusted OR: 1.24; 95% CI 1.04- 1.47; p = 0.018), monthly consumption (adjusted OR: 1.24; 95% CI 1.13-1.37; p < 0.001), household income (adjusted OR: 1.10; 95% CI 1.01 -1.21; p = 0.029), and parental education level (adjusted OR: 1.23; 95% CI 1.13-1.33; p < 0.001). Moreover, the participants' eHL level positively influenced their HPV vaccination conversion rate (adjusted OR: 1.02; 95% CI 1.00-1.04; p = 0.036). For HBM, trust in formal information had a significant positive influence on HPV vaccination conversion rate (adjusted OR: 1.10; 95% CI 1.04-1.16; p = 0.002), whereas perceived behavioral barriers had a significant negative influence (adjusted OR: 0.72; 95% CI 0.66 - 0.79; p < 0.001). This study confirms a substantial HPV vaccination intention‒behavior gap among Chinese female college students, influenced by socioeconomic factors, eHL, and health beliefs-specifically trust in formal information and perceived barriers. Therefore, we suggest that targeted measures should be undertaken to reduce socioeconomic gaps, improve the eHL of those with pre-existing vaccination intention, enhance institutional trust in formal medical institutions and authoritative information channels, and reduce the psychological and practical obstacles to HPV vaccination to effectively bridge the intention-behavior gap and thereby improve vaccination coverage female college students in China.
The management of risk associated with clinical processes is gaining increasing importance in both health policy and medical research. Data show that among mental health professionals, cases of violence and burnout are on the rise. Implementing appropriate risk management strategies in psychiatry should be considered a key objective. This study aims to provide an overview of the current state of psychiatric risk management, with particular focus on Italian community-based mental health services. Through a non-systematic review of international and national literature, we identify the main areas of risk in psychiatry, which can be summarized as: interpersonal violence, coercive interventions, environmental safety, adverse drug events, clinical errors, and professional burnout. In the Italian context, critical issues mainly concern the protection of staff well-being and safety, the management of forensic patients according to Law 81/2014, and the acquisition of informed consent. The National Action Plan for Mental Health 2025-2030 formally recognizes risk management as a field of action, outlining related priorities and operational strategies. For the effective implementation of risk management in community-based psychiatry, it appears to be necessary the dissemination of standardized assessment and monitoring tools, promote workforce continuous training, and strengthen the culture of consent and shared decision-making.
This study challenges the assumption that collaboration beyond work-unit boundaries consistently enhances performance and demonstrates that the impacts of inter-unit collaboration are not uniform across different government agencies. Using multi-group analysis of Federal Employee Viewpoint Survey (FEVS) data, we compare two U.S. federal agencies with contrasting institutional logics: a bureaucratic law enforcement agency (ICE) and an entrepreneurial science research center (GSFC). In doing so, we propose a model explaining how inter-unit collaboration influences performance through knowledge acquisition and resource availability as mediating variables. The analysis revealed that inter-unit collaboration had a significantly greater impact on work unit performance in the bureaucratic ICE than in the entrepreneurial GSFC. Specifically, the total effect of inter-unit collaboration on unit performance was 0.166 for ICE and 0.087 for GSFC, whereas the total effect of intra-unit collaboration reached 0.525 and 0.686, respectively. These findings contradict our hypothesis that inter-unit collaboration will be more beneficial in entrepreneurial agencies. Looking closely at the mediating paths, we argue that high technical complexity and rigid task compartmentalization in scientific agencies create barriers to lateral sharing, whereas law enforcement tasks are often case-based and emergency-driven and require more effective real-time coordination among units. Paradoxically, this unexpected result reinforces our initial assumption that inter-unit collaboration can produce diverse outcomes by showing that the nature of tasks and the resulting collaboration structures-factors we initially overlooked-serve as contingencies for performance gains.
With expanding cannabis legalization, normalization, and diversifying products and delivery methods in the United States (US), cannabis use disorder (CUD) prevalence is rising. Various modes of cannabis use may influence pharmacokinetics, usage patterns, and harm, affecting CUD risk. We measured associations between modes of cannabis use, including multi-modal patterns, and CUD prevalence and severity. This cross-sectional study analyzed data from a nationally representative sample of US adults using the 2022-2023 National Survey on Drug Use and Health (NSDUH) data. Multivariable logistic regression analyses were employed to estimate the association between modes of cannabis use and past-year CUD, adjusting for potential confounders and covariates. Analyses were stratified by sex, age, and cannabis use frequency. Among multi-modal users, common combinations and their associations with CUD were further examined. Respondents 18 years or older who reported past-year cannabis use (unweighted n = 25 549; weighted N = 58 850 309). Exposure of interest was the mode of cannabis use, primarily categorized as smoke-only, vape-only, oral/mucosal-only, dab-only, topicals-only, and multi-modal (≥ two modes). The outcome variable was CUD in the past year, and CUD severity, based on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria. Covariates included age, sex, race/ethnicity, income, education, state cannabis law status, age of cannabis initiation, cannabis use motive, frequency of use, perceived risk of smoking cannabis, illicit drug use, past year mental illness, nicotine dependence, and alcohol use disorder. Of the total past-year cannabis users, 53.9% reported multi-modal cannabis use. Overall, CUD prevalence was 30.3%, ranging from 4.4% among oral/mucosal-only to 40.5% among multi-modal, and 28.9% among dab-only users (p < 0.0001). Moderate-to-severe CUD affected 13.2% of all users and was concentrated among multi-modal and dab-only users. In multivariable regression, multi-modal users had fourfold higher odds of CUD (adjusted odds ratio [AOR] = 4.14; 95% confidence interval [CI]: 2.91-5.90). Elevated odds were also observed among smoke-only (AOR = 2.98; 95% CI: 2.02-4.39) and vape/dab-only users (AOR = 1.89; 95% CI: 1.09-3.29), compared with oral/mucosal-only users. Analyses of multi-modal combinations showed the highest CUD odds among those using smoke + vape + oral/mucosal + dab (AOR = 19.74; 95% CI: 9.11-42.75), compared with oral/mucosal + topicals users. In the United States, modes of cannabis use appear to be statistically significantly associated with prevalence and severity of cannabis use disorder, with multi-modal and inhaled routes conferring the greatest risk. Findings underscore the importance of considering mode of use alongside frequency and potency in clinical assessment, prevention, and policy strategies aimed at reducing cannabis-related harms.
Background: Childhood is a key period for the development of body composition and physical activity habits that may influence health throughout life. Although physical activity has been widely associated with adiposity indicators, the role of enjoyment of physical activity as a motivational and affective component remains less explored. Therefore, the aim of this study was to analyze the relationship between several anthropometric indicators and both the level of physical activity and enjoyment of physical activity in schoolchildren. Methods: An observational, analytical, cross-sectional study was conducted with 386 schoolchildren (176 boys and 210 girls) with a mean age of 11.15 ± 0.66 years. Anthropometric indicators included body mass index, waist circumference, hip circumference, waist-to-hip ratio, and triceps and subscapular skinfold thickness. Physical activity level was assessed using the Physical Activity Questionnaire for Children (PAQ-C), and enjoyment of physical activity was evaluated using the Physical Activity Enjoyment Scale (PACES). Multiple linear regression analyses were performed, adjusting for age and sex. Results: Higher levels of physical activity were significantly associated with lower body mass index (B = -1.592; p < 0.001), waist circumference (B = -8.010; p < 0.001), hip circumference (B = -8.227; p < 0.001), waist-to-hip ratio (B = -0.008; p < 0.001), triceps skinfold thickness (B = -0.910; p = 0.002), and subscapular skinfold thickness (p < 0.05). Greater enjoyment of physical activity was significantly associated with lower body mass index (B = -1.778; p < 0.001), reduced waist circumference (B = -8.944; p < 0.001), hip circumference (B = -9.185; p < 0.001), waist-to-hip ratio (B = -0.008; p < 0.001), and triceps skinfold thickness (B = -1.100; p = 0.001). Greater enjoyment was also associated with lower anthropometric indicators of central adiposity (waist circumference and waist-to-hip ratio), whereas no significant association was observed with subscapular skinfold thickness (p = 0.066). Conclusions: Physical activity level and enjoyment of physical activity were associated with multiple anthropometric indicators in children, although physical activity showed more consistent associations, whereas enjoyment demonstrated a more selective pattern depending on the specific adiposity measure. These findings highlight the importance of considering both behavioral and affective dimensions of physical activity when promoting healthy morphofunctional development during childhood.
For many people with serious mental disorders, the carceral system often serves as the first point of contact in a mental health crises, yet little is known about how law enforcement personnel in low resource settings, for example, in rural Uganda, recognize and respond to such crises. We conducted 84 in-depth qualitative interviews with individuals representing five groups involved in law enforcement in rural Uganda: Local Council I Chairpersons, Local Council 1 Secretary for Defense, Prisons Officers, Local Defense Personnel, and Criminal Investigation Directorate (CID) officers. Participants were recruited through purposive and snowball sampling across two districts in eastern Uganda. Data were analyzed using the framework method. Participants described a common trajectory. Mental health problems were identified through visible behaviors or alerts from family or neighbors. Officers tried to de-escalate crises before arranging referral, whether informal (i.e., through local leaders) or formal (e.g., health care or criminal justice facilities). They identified numerous barriers, including the need to transport patients long distances, lack of availability of medications, and stigma. Many expressed compassion for people with mental illness, but several described behavioral enactments of stigma, including community vigilantism. They proposed concrete interventions, including brief role-tailored training, structured family involvement, checklists, and supporting basic needs.The Ugandan law enforcement apparatus is commonly called upon to address mental health crises but lack standardized guidance or resources. Psychoeducation and brief role-based training could potentially improve safety and continuity of care.
Digital health governance frameworks have primarily focused on prospective safeguards, including informed consent at the point of data collection, lawful processing, and data security. Comparatively less attention has been devoted to the long-term circulation of legacy clinical materials, particularly pediatric clinical images reused across educational and digital infrastructures. This viewpoint examines governance challenges associated with the prolonged educational and digital reuse of pediatric clinical images without identifiable evidence of consent. Drawing on a longitudinal case spanning more than 3 decades (1991-2026), this article illustrates how clinical images may continue circulating across textbooks, educational repositories, conference materials, e-books, and online teaching platforms long after their original creation and publication context. The case is informed by archival educational materials, institutional correspondence, publisher communications, and formal regulatory findings, including a decision issued by the Polish Patient Rights Ombudsman confirming continuing violations related to dissemination of intimate pediatric clinical images without identifiable consent. This article argues that current digital health governance frameworks remain insufficiently equipped to address persistence, traceability, provenance, and coordinated withdrawal of legacy clinical materials once they enter distributed educational ecosystems. Fragmented accountability across health care institutions, publishers, educational systems, libraries, repositories, and digital platforms may allow sensitive clinical materials to remain accessible despite regulatory intervention or removal requests. The article further discusses how publicly accessible educational materials may become incorporated into downstream artificial intelligence and machine learning ecosystems through digitization, aggregation, web scraping, and secondary dataset reuse. In this context, unresolved historical consent deficiencies may become embedded within artificial intelligence-enabled infrastructures without effective provenance tracking or remediation mechanisms. To address these limitations, this viewpoint proposes a lifecycle-oriented governance framework emphasizing long-term consent traceability, provenance-aware dissemination systems, verification checkpoints before reuse or republication, periodic review of legacy educational archives, and coordinated cross-platform withdrawal procedures.
The European Health Data Space (EHDS) Regulation enables the secure sharing of health data, unlocking a wide range of valuable applications from continuous health monitoring, to digital twins, and precision health. To ensure that this sharing is both effective and efficient, the EHDS must be deployed on secure and trustworthy architectures. However, this presents a substantial challenge for two main reasons: (i) health data may originate from or be sent to untrusted devices (such as end-user smartphones), and (ii) while the EHDS establishes the legal framework for security, it does not provide concrete technical specifications to enforce it. Building on the technical work of the xShare project and its "Yellow Button" mechanism, we propose a data sharing framework that translates European data protection obligations (e.g., GDPR) into actionable technical controls. These controls encompass encryption, pseudonymization, secure coding practices, and auditability. The result is a operational model for implementing trust for the EHDS.
This study evaluates the Avatar method for generating synthetic health data while preserving privacy. Using a cancer prediction dataset of 1,500 patients, we analyzed the balance between data utility and privacy protection across different parameter settings. Results show that avatars can approximate the statistical structure of the original data (utility metric: 97.96%, Hellinger distance: 0.13) while reducing re-identification risks (privacy rate: 91.7%, hidden rate: 92.4%). However, the study highlights that the choice of parameters, particularly the neighborhood size k, is critical to achieving a suitable utility-privacy trade-off. Careful tuning is therefore required before applying Avatarization in real clinical contexts.
Name.Narrate.Navigate (NNN) is a trauma-informed program for justice-involved young people aged 12-18 years, recognising that experience and use of violence are often interconnected and may involve serious criminal behaviour, including vulnerability to criminal exploitation. NNN addresses a gap in evidence-based, culturally responsive tertiary interventions for this cohort in regional New South Wales (NSW), Australia, integrating dialectical behaviour therapy (DBT) principles with Aboriginal ways of knowing and doing, co-designed through community-based participatory research (CBPR) with Aboriginal community members, young people, and frontline practitioners. The program aims to strengthen skills for self-awareness, self-regulation and healthy connection through relational, creative, and participatory approaches. Using a realist evaluation framework, this paper examines what works in NNN, for whom, and under what circumstances. Drawing on participant session ratings, practitioner observations, program documentation, and interviews, findings are organised across four domains: effects, mechanisms, moderators, and implementation. Indicative findings show that engagement, emerging changes in the narratives of self, and developing skills for self-regulation were most evident when trauma-informed and culturally safe practice was enacted within genuinely relational, strengths-based encounters. These conditions are identified and discussed as transferable principles for the field, key amongst them that intervention readiness must be treated as a capacity to be actively built rather than a precondition to be screened for; and that creative, participant-led methods represent an epistemological commitment to whose knowledge counts in practice. This case study contributes to a critically underserved evidence base by documenting not only what a tertiary youth violence intervention looks like, but the conditions under which it begins to work and for whom.
To assess the level of health system responsiveness (HSR) and its associated factors among outpatients attending primary healthcare units (PHCU) in Arba Minch, South Ethiopia. Facility-based cross-sectional study. Three PHCUs (one primary hospital and two health centres) in Arba Minch town, Southern Ethiopia. A total of 379 outpatients aged 18 years and above were selected using a systematic random sampling. Primary outcome: level of HSR, measured across seven domains (communication, confidentiality, basic amenities, dignity, choice, prompt attention and autonomy) using a 28-item tool adapted from the WHO HSR framework. Secondary outcome: factors associated with HSR, identified via bivariate and multivariable linear regression. The overall HSR was 59.4%. The highest-performing domains were confidentiality (73.9%) and dignity (70.7%), while the choice of healthcare provider was rated lowest (34.6%). In multivariable linear regression analysis, factors significantly associated with HSR score were travel time to reach the health facility on foot (β = -0.26, 95% CI -0.37 to -0.14); out-of-pocket payment for transport (β = -6.51, 95% CI -8.33 to -4.70); patient satisfaction score (β=1.57, 95% CI 1.27 to 1.88) and perceived quality of healthcare score (β=0.32, 95% CI 0.14 to 0.49). HSR among outpatients in PHCU was moderate, with several individual and service-related factors associated with patient experiences. These findings suggest the need for focused interventions to improve responsiveness domains, although more research is required to demonstrate causal relationships.
Background: A conversation between a victim and a perpetrator of sexual abuse has the potential to reduce posttraumatic stress disorder (PTSD) symptoms in the victim. However, an actual conversation may not always be possible or feasible. Deepfake technology may offer a way to simulate a conversation in a clinical context. Therefore, a feasible, acceptable and potentially effective intervention protocol is required.Objective: We aimed to develop an intervention protocol for a deepfake victim-perpetrator conversation to be used in the treatment of patients with sexual abuse-related PTSD, that would be technologically, legally, ethically, and clinically feasible as well as acceptable. In addition, we aimed to design a single-case experimental design (SCED) multiple baseline study to evaluate its efficacy.Method: The intervention protocol was developed through an iterative multidisciplinary process following established guidelines for complex intervention development. Based on a literature review and interviews with 15 experts and patient representatives, a draft intervention protocol was created and subsequently evaluated, piloted and refined. A consequent study protocol was then designed in accordance with the SPIRIT guidelines.Results: The development process resulted in an intervention protocol for a half-day perpetrator conversation using deepfake technology. The intervention is grounded in cognitive-behavioural therapy and emotional processing theory, and consists of a preparatory session, a deepfake session, and a debriefing session, to be conducted by two therapists. The intervention is tested in a SCED multiple baseline study of 10 patients with sexual abuse-related PTSD who are randomly assigned to a baseline period of 10, 15 or 20 days. Outcomes (changes in negative cognitions, PTSD, guilt and shame, forgiveness, and empowerment) are assessed through 20-30 daily measurements and four main assessments, and analysed using Bayesian statistics.Conclusion: A feasible and acceptable intervention protocol for a deepfake intervention was developed. Its efficacy is tested in a multiple-baseline study. We developed an intervention protocol for a deepfake perpetrator conversation for patients with sexual abuse-related PTSD.The intervention protocol appeared ethically, legally, and clinically feasible, as well as acceptable to patients with PTSD.Its efficacy is examined in a multiple baseline study. Objetivo: El objetivo fue desarrollar un protocolo de intervención para una conversación simulada entre víctima y perpetrador para ser utilizada en el tratamiento de pacientes con TEPT relacionado con abuso sexual, que pudiera se factible tecnológica, legal, ética y clínicamente, así como también aceptable. Además, nos propusimos diseñar un estudio de línea de base múltiple con diseño experimental de caso único (SCED por sus siglas en inglés) para evaluar su eficacia. Método: El protocolo de intervención se desarrolló a través de un proceso multidisciplinario iterativo siguiendo las guías establecidas para el desarrollo de intervenciones complejas. Basados en una revisión de la literatura y entrevistas con 15 expertos y representantes de pacientes, se creó un borrador del protocolo de intervención que posteriormente se evaluó, se piloteó y se perfeccionó. A continuación, se diseñó un protocolo de estudio definitivo de acuerdo con las directrices SPIRIT. Resultados: El proceso de desarrollo dio como resultado en un protocolo de intervención para una conversación de medio día con el perpetrador utilizando tecnología deepfake. La intervención se basa en la terapia cognitivo conductual y la teoría del procesamiento emocional y consiste en una sesión preparatoria, una sesión deepfake y una sesión evaluación, dirigida por dos terapeutas. La intervención se prueba en un estudio de línea de base múltiple SCED para 10 pacientes con TEPT relacionado con abuso sexual que son asignados en forma aleatoria a un periodo basal de 10,15 o 20 días. Los resultados (cambios en las cogniciones negativas, TEPT, la culpa y la vergüenza, el perdón y el empoderamiento) se evalúan mediante 20–30 mediciones diarias y cuatro evaluaciones principales y se analizan utilizando estadística Bayesiana. Conclusión: Se desarrolló un protocolo de intervención factible y aceptable para una intervención con deepfake. Su eficacia se evaluó en un estudio de línea de base múltiple.
The Aarhus Bereavement Study (TABstudy) was established to assess the health and societal impact of bereavement and pathological grief. This is the first register-identified bereavement cohort, linked to a longitudinal survey on grief, with non-bereaved controls. The entire cohort (N = 68,960), followed from Danish register creation until 2030, includes annual data on socio-economic demographics, income, workforce, government financial assistance, education, incidence of somatic health conditions, incidence of psychiatric health conditions, prescription medication sales, and cause of mortality for bereaved spouses, matched controls, and all their children. The longitudinal self-reported survey (N = 1,227, 54% response rate) of recent spousal-loss and parental-loss in Aarhus, Denmark, from 2017 to 2018 collected data on lifestyle factors, substance use, personality, significant life changes, well-being, and psychological measures in 8 waves across 5 years. A final 10-year follow-up survey wave is planned for 2027, while register data will cover until 13 years after loss. The cohort at bereavement was on average 51 years old, 56% women, most attained secondary education or higher, and most were employed. Bereaved and control subsamples were similar on nearly all characteristics. Data are stored at Statistics Denmark. Researchers interested in collaboration should contact the Unit for Bereavement Research, Aarhus, Denmark (maja@psy.au.dk, Dr. Maja O'Connor).
Sexual harassment (SH) in academia constitutes a pervasive form of gender-based violence that undermines individual well-being and academic equity. While existing research has largely investigated risk factors, less attention has been paid to protective factors, coping strategies, and the cumulative burden generated by the reporting process itself. This qualitative study explores how victims of SH in Italian universities mobilize resources when disclosing their experiences informally to peers and colleagues or formally through institutional channels and how this process generates extra-fatigue: the cumulative cognitive, emotional, and practical labor victims have to perform as a direct consequence of inadequate institutional responses. Drawing on semi-structured interviews, we employed thematic and dialogical narrative analyses to examine cognitive, emotional, and behavioral coping dimensions. Findings highlight the central role of informal networks in enabling victims to recognize harassment, validate their narratives, and mobilize coping strategies. Trusted colleagues and supportive professors provided cognitive clarity, emotional relief, and practical protection. However, institutional responses were frequently perceived as inadequate or emotionally detached, reinforcing self-doubt and generating significant extra-fatigue to absorb largely alone or through informal support. Understanding extra-fatigue as structurally produced labor, rather than individual fragility, has implications for designing victim-centered institutional responses and structural reform in universities.
As cannabis legalization expands in the United States, edibles have grown in popularity. Often perceived as less harmful than smoked cannabis, edibles are packaged like food products with imagery and product descriptors that may impact consumer perceptions, potentially increasing risks of overconsumption. We conducted two randomized online experiments among adults aged 18-65 between March and June 2024. In one experiment (N = 1260), participants were randomized to view packages with flavor, outdoor nature, medical, animal, or no-imagery. In a second experiment (N = 2521), participants viewed packages with one of nine product descriptors or no-product descriptors. Outcomes included measures of appeal, safety, and behavioral intent and were preregistered on ClinicalTrials.gov (NCT06358144, NCT06171399). Compared to no-imagery, flavor imagery was associated with greater appeal, safety, and healthiness, while outdoor nature and medical imagery conveyed healthiness. Animal imagery was associated with perceptions of greater appeal to children. In contrast, product descriptors (e.g. "all natural," "organic," "handcrafted," and "energy boost") were associated with less appeal and interest in trying relative to control packages and did not enhance perceived safety. Package imagery, particularly flavor imagery, may mislead consumers by increasing the appeal and perceived safety of edibles, while product descriptors may have the opposite effect. These findings highlight the need for more comprehensive packaging regulations and further research on real-world purchasing behavior.