The growing need for and interest in geomatics in the medical sector, as well as the pandemic crisis, led us to create a France-wide geomatics project aimed at producing several atlases of all-cause mortality at the municipal and submunicipal district levels via uMap France, a free and open-source collaborative map-sharing platform. In 2020, we decided to circumvent the obstacle of accessing detailed COVID-19 data by adopting a mortality-based approach to map the consequences of the crisis. The aim of the uMap study was to provide a webmapping platform with original visualization and knowledge, as well as decision-making aids that complement existing information and are relevant to public and healthcare professionals. Our main hypotheses are as follows: 1- the medical sector could develop a private uMap platform dedicated to health; 2- interest in a municipal mortality atlas for France linked to the pandemic crisis will increase, even if it is produced after the pandemic; and 3- sharing the atlases with the uMap community will enhance their appeal and inspire the creation of similar atlases, owing to the new "experimental choropleth layer" recently developed by the uMap team. This approach focuses on three main parts-data management (data collection, cleansing and scheduling) and geomatic engineering-through a two-step geomatic action plan to create atlases of the first lockdown period in France, displayed on the uMap platform. A logarithmically transformed variable allows us to obtain an immediate statistical signal of excess mortality or submortality via the Traffic-Light Atlas. The uMap Traffic-Light display provides instant statistical signals at a glance owing to the semantic interplay of colors. The atlas's double legends make it easy to compare specific regions (northeast, northwest, southeast, and southwest) to all of France. The atlas revealed excess mortality in 42% of the municipalities (14,503) out of 34,833. Thirty-five percent are in the green class (close to average to twice the average), 5% are in the orange class (2-4 times the average), and 2% are in the red class (4-11 times higher than average). We innovated, enriched, and reinforced the value of uMap for visual rendering by instantiating colored choropleth map atlases and double legends and showed its relevance to the healthcare sector. We focused on the Traffic-Light Atlas, which is the most relevant because of the instant message it conveys and its interpretability for all audiences. The uMap community can share our all-cause mortality atlases. A second version of the atlas encompassing four periods in 2020 and containing a minor error will be updated using either the "experimental choropleth layer" feature recently developed by the uMap team or, if this feature proves insufficient, the geomatic optimization process via the R-project. Not applicable.

Objective: This study examines the relationship between objectively measured social media use and non-suicidal self-injury (NSSI) and suicidal behaviors, addressing the limitations of prior research that relied on self-reported data. Method: Conducted across six universities in Shaanxi, China, the study tracked weekly social media usage using smartphone monitoring, with a sample size of 7,401 participants. Social media types were classified into social networking applications (SNA), text messaging and messaging applications (TMMA), online forums and community applications (OFCA), and short video applications (SVA). Logistic regression and cubic spline curves were used to estimate the relationships of the overall social media duration or its sub-types with the odds of NSSI and suicidal behaviors. Results: Each one-hour increase in social networking applications was significantly associated with increased odds of both NSSI (OR = 1.018; 95% CI: 1.007–1.028) and suicide ideation (OR = 1.016; 95% CI: 1.007–1.025). In addition, each one-hour increase in online forums and community applications was linked to increased odds of suicide ideation (OR = 1.063; 95% CI: 1.029–1.097), while text messaging and messaging applications was associated with higher odds of NSSI (OR = 1.010; 95% CI: 1.002–1.017). In contrast, prolonged duration in short videos applications was observed to be associated with decreased odds of NSSI (OR = 0.983; 95% CI: 0.975–0.991) and suicide ideation (OR = 0.988; 95% CI: 0.981–0.995). Conclusion: However, no statistically significant association was found between suicide attempt and the total time spent on social media, nor with any of its subtypes. Furthermore, the restricted cubic spline analysis showed linear associations of social networking applications and text messaging and messaging applications with the prevalence of NSSI, but U-shaped relationships of text messaging and messaging applications and short videos applications duration with suicide ideation was observed (P for non-linearity < 0.05).

This study estimates the prevalence of various forms of intimate partner violence (IPV) and examines their associations with depressive and post-traumatic stress disorder (PTSD) symptoms among lesbian and bisexual women (LBW) in India. This cross-sectional online survey included 53 self-identified LBW college women in India. Participants were recruited through social media platforms, instant messaging applications, and student listservs. Interested participants were invited to complete an online survey assessing IPV experiences and symptoms of depression and PTSD. Overall, 58.5% of participants reported experiencing at least one form of IPV. Psychological IPV was most prevalent (49.1%), followed by digital IPV (34%), physical IPV (28.3%), injuries (26.4%), and sexual IPV (26.4%). Approximately 26.4% of participants met the threshold for probable depression and 30% for probable PTSD. Correlational analyses revealed significant associations between various forms of IPV and symptoms of depression and PTSD. Negative binomial regression analyses indicated that experiencing IPV, particularly psychological and digital IPV, was associated with higher levels of depressive and PTSD symptoms. This exploratory study observed substantial IPV prevalence among lesbian and bisexual college women in India, highlighting its impact on mental health symptoms. Targeted interventions designed to address both IPV and its associated mental health consequences can potentially enhance help-seeking behavior within this vulnerable population.

ABSTRACT Based on a year-long ethnographic research into everyday life in Santiago’s dense high-rises, this paper analyses the emergence of everyday digital economies among building occupants through messaging applications. In this context, novel neighbor-based commercial interactions have, to some extent, overturned the impersonal character of Chilean verticality. Infused with a communitarian ethos, these transactional encounters reshape residents’ perceptions of neighborliness in dense, heterogeneous vertical settings, fostering a sense of togetherness reminiscent of traditional neighborhood imaginaries, while enabling residents from diverse backgrounds to generate unexpected relationships. I therefore argue that consumption practices within these buildings add complexity and nuance to the experience of living in verticalizing South American cities. Specifically, they reveal alternative ways in which seemingly rigid residential structures are transformed through ordinary inhabitation as neighbor relations become more digitalized. In doing so, this paper contributes to the expanding interest in understanding vertical ordinariness in the region.

ABSTRACT In vocational education, a growing emphasis is being placed on the development of professional agency; that is, professionals who can adapt and contribute to shaping changing work practices. This study aims to understand how professional agency in vocational education students develops. For this, we employ Cultural-Historical Activity Theory (CHAT), which views professional agency as the dialectical and generative relationality between individuals and their work environment. We conducted a multiple case study analysis, where students were observed in learning-work environments of different professional domains and were interviewed immediately afterwards about moments that concerned them during work. Additionally, students were asked to report such moments via an end-to-end encrypted app for instant messaging, followed by another interview. The development of professional agency was compared and summarised using one case as a starting point and contrasting it with other cases. The analysis of 110 cases provided us with deepened insights in how students construct themselves in work practices and how they participate in the construction of work practices. These results challenged us to discuss the concept of professional agency in terms of both CHAT and, more specifically, the concept of zone of proximal development.

PT Citra Wahana Nusantara Unit Dua Kelinci is a labor outsourcing company recruits an average of 40 employees per day. The recruitment process is still conducted using conventional methods, including manual registration, the management of applicant data that is not yet integrated, and the delivery of information via messaging applications such as WhatsApp. This makes the selection process less efficient, prone to registration errors, and difficult to monitor the status of applications in real time. This study aims to design and build a web-based Employee Recruitment Information System, equipped with online registration, test scheduling, application tracking, and Fixed-Term Employment Contract (FTE) management, to improve the efficiency of human resource management. This study employs an applied research approach using the waterfall (a sequential software development lifecycle model) system development method, which includes the stages of needs analysis, system design, implementation, testing, and maintenance. Data collection was carried out through direct observation, interviews with the Human Resources Department, and literature reviews. The system was developed using the PHP programming language with a MySQL database. The study results demonstrate that the developed system integrates the entire recruitment process onto a single digital platform, from online registration, document verification, and test scheduling, to real-time tracking of application status and the management of employment contracts. This study recommends implementing an integrated information system as a solution for digitizing human resource management, especially in outsourcing companies with high recruitment volumes.

ObjectiveTele-delivered interventions can benefit autistic children and families in low-resource settings, but the digital divide may worsen existing disparities. To address this, we adapted a Naturalistic Developmental Behavioural Intervention (NDBI)-based caregiver coaching program for tele-delivery to enhance fit for low-resource families in Cape Town, South Africa. This manuscript examines the contextual fit (acceptability, appropriateness, feasibility) and implementation facilitators/barriers of the adapted intervention.MethodsA mixed-method design was used to assess implementation outcomes in a pilot study of 16 participants (caregivers and practitioners), with quantitative (Acceptability of Intervention Measure, AIM; Intervention Appropriateness Measure, IAM; Feasibility of Intervention Measure, FIM) and qualitative data. Quantitative data were analysed using descriptive statistics and qualitative interview data using framework analysis.ResultsQuantitative data showed high scores for acceptability, appropriateness and feasibility (AIM intervention materials = 4.5/5; AIM session structure = 4.4/5; IAM intervention materials = 4.6/5; IAM session structure = 4.5/5; FIM session structure = 4.4/5), supported by qualitative findings. Barriers included small text size on intervention materials and internet connectivity. Facilitators included minimal text in intervention materials, an accessible delivery platform (WhatsApp), collaborative caregiver-practitioner relationships, data and technical support, protected practitioner time, and school leadership support.ConclusionThis is one of the first studies in a LMIC to assess implementation of an asynchronous autism caregiver coaching program delivered entirely via a low-cost instant messaging platform (WhatsApp). Findings suggest the tele-delivered intervention fit well in this low-resource South African setting. Results are promising, and evaluating caregiver and child outcomes is a key next step.

In recent years, the demand for remote communication and online collaboration solutions has increased significantly, particularly in the fields of education, recruitment, and professional assessment. Organizations and educational institutions are rapidly shifting toward digital platforms to conduct interviews, technical assessments, and candidate evaluations efficiently. Traditional interview methods often involve several challenges such as geographical limitations, travel costs, scheduling conflicts, infrastructure dependency, and timeconsuming coordination processes. These issues become even more difficult when organizations need to conduct interviews with candidates located in different cities or countries. To overcome these limitations and support modern recruitment requirements, the TalentIQ Interview Management System has been developed as a smart and efficient web-based interview platform. The TalentIQ platform is designed to facilitate real-time online technical interviews directly through a web browser without requiring any external or third-party video conferencing software. The system enables interviewers and candidates to communicate seamlessly through live video calls, instant messaging, and collaborative coding environments within a single integrated platform. By providing all interview-related functionalities in one centralized system, the platform simplifies the overall interview process and improves user experience for both interviewers and candidates.

ABSTRACT Gambling-related harms are a growing public health concern, particularly amid the rapid expansion of online sports betting. Young men, who comprise a large portion of online sports bettors, are especially vulnerable due to increased exposure, cultural normalization of gambling in sports, and reduced barriers to participation. While research has explored mutual help within online forums, limited work has examined how social support functions in real-time messaging platforms popular among young adults. This study addressed this gap by analyzing messages exchanged within a Discord channel dedicated to problem gambling, embedded in a larger sports betting community. Publicly available chat messages spanning four National Football League seasons were coded using Social Support Behavior Code and analyzed through qualitative content analysis. Informational support (e.g., advice, teaching) was most common and often grounded in personal experiences with gambling harm and recovery. Emotional support (e.g., empathy, encouragement) frequently occurred in messages expressing shared struggle, while esteem, network, and tangible support appeared less often but contributed to cohesion and sustained participation. Findings highlight how peer-driven support can organically emerge on instant messaging platforms, offering culturally relevant, low-barrier spaces for young adults at risk of gambling harm and emphasizing the need for research on their behavioral impact.

Purpose This study explores the unique aspects of gaming privacy by proposing a dual-factor model of privacy concerns: breadth (BPC) and depth (DPC). It aims to examine how privacy concerns in gaming differ from those in other online contexts and to provide explanatory insights into the factors associated with users' privacy perceptions and behaviors in entertainment-driven environments. Flow, defined as a state of deep immersion and engagement, is introduced as a moderating factor, shaping the relationships between privacy concerns and disclosure intentions within gaming contexts. Design/methodology/approach Two empirical studies were conducted. Study 1, a 2×2 online experiment (N = 240), compared privacy concerns between utility-driven instant messaging applications and entertainment-driven games. Study 2 employed the Antecedent-Privacy Concern-Outcome model to validate the relationships among privacy concerns, perceived vulnerability, and information disclosure intentions (N = 766), with flow as a moderating factor. Findings Study 1 revealed that users generally exhibited lower privacy concerns in gaming contexts, though privacy cues can increase their DPC. Study 2 showed that gaming contexts encourage users to trade privacy for entertainment, with flow experiences amplifying this effect. Originality/value Theoretically, this study introduces a dual-factor privacy concerns framework, contributing to the understanding of gaming privacy and its formation. The study also provides a novel explanation for the privacy paradox by incorporating flow. Practically, it advises game developers to enhance privacy cues and transparency and recommends policymakers stabilize gaming privacy regulations to avoid confusion from frequent changes. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2025-0510

Unveiling user activities on instant messaging platforms: A study of activity fingerprinting through traffic analysis and machine learning techniques

Messaging across borders: WhatsApp as a tool for global burn surgery collaboration.

Effectiveness of a blended in-person and online parenting programme in reducing violence against children in rural Thailand: a cluster randomised controlled trial

The extensive use of short-form video platforms and instant messaging among Indian adults aged 18-45 is increasingly linked to attention fragmentation-the repeated interruption of sustained focus-and emotional distress, including anxiety and impaired regulation. While international studies connect media-induced attentional lapses to poorer mental health, national mixed-methods evidence from India remains limited. Integrating modern digital-community paradigms, this study aimed to quantify fragmentation, examine its association with emotional distress, and test its role as a mediating associate. A sequential explanatory mixed-methods design was conducted between May and December 2025. A quantitative survey of 582 adults was performed using stratified quota sampling across 18 Indian states. Attention fragmentation was operationalized through the Mindful Attention Awareness Scale (MAAS), where reverse-scored items served as a proxy for frequent task-switching and awareness lapses. Emotional distress was assessed via the DASS-21 and PANAS scales. This was followed by 32 purposive semi-structured interviews to explore lived experiences. Quantitative data were analyzed using PROCESS Model 4 with 5,000 bootstrapped resamples, while qualitative data underwent reflexive thematic analysis. High fragmentation (lowest MAAS tertile) affected 46.4% of participants and correlated significantly with daily social media hours (r = -.42) and emotional distress (DASS-21 total r = -0.61). Mediation analyses indicated that attention fragmentation is a significant associated mechanism, accounting for 68% of the relationship between engagement and anxiety, and 63% for depression. Qualitative themes revealed that perpetual context-switching, driven by Instagram Reels and WhatsApp pings, leads to "mental clutter" and sleep disruption. Cultural factors, such as family expectations for instant responsiveness, were found to amplify fragmentation-related stress. These findings suggest that attention fragmentation is a significant pathway consistent with a mediation model linking social media use to emotional distress in the Indian context. Results indicate that interventions focusing on attentional recovery, notification batching, and culturally tailored mindful digital habits may be more effective for protecting emotional wellbeing than simply reducing total screen time. Expanding digital mental health ecosystems, such as Tele-MANAS, to address fragmentation is recommended. Not applicable.

Objectives: To explore the experiences of ex-smokers acting as peer supporters delivering chat-based instant messaging smoking cessation support in a post- randomized controlled trial qualitative study. Methods: We used purposive sampling to recruit 21 ex-smokers, who had previously provided chat-based instant messaging behavioral support to smokers in Hong Kong. Individual online semi-structured interviews were conducted. All interviews were audiotaped and transcribed verbatim. The transcripts were analyzed using inductive thematic analysis following Braun and Clarke’s six-phase framework. Results: Five themes were identified: stepping into the supporter role as ex-smokers, contributions beyond facilitating smoking cessation, mutual benefits as ex-smoking peer supporters, challenges in providing support, and the potential of mobile health-based peer support. Participants identified experiential sharing as a key mechanism for engaging motivated smokers, although its impact was limited by low user responsiveness. They described extending their support beyond smoking cessation (e.g., stress relief and healthier lifestyles), and reported mutual benefits, such as enhanced happiness, a positive attitude, and prevention of smoking relapse. Nevertheless, participants’ ability to effectively support smoking was challenged by limited interaction in the mHealth setting, difficulties offering timely responses, and uncertainty about how to handle complex personal situations. They suggested that future mobile health peer support can consider involving famous people as peer supporters, using personalized messaging, and adding incentives in the program to increase smokers’ motivation. Conclusions: Ex-smoking peer support in mHealth settings appears feasible and mutually beneficial, but its effectiveness may be constrained by low engagement and unclear role expectations.

Applying the interpersonal psychological theory of suicide, this study explored how instant messaging app use is associated with suicidal ideation through thwarted belongingness and perceived burdensomeness. Furthermore, the study examined the moderating role of emotional support in the indirect route to suicidal ideation. Using online panel survey data collected in South Korea, this study performed an SPSS PROCESS macro analysis (Models 4 and 7). The results revealed that instant messaging app use is positively related to lower levels of thwarted belongingness and perceived burdensomeness, which in turn is associated with lower levels of suicidal ideation. Moreover, emotional support significantly moderated the mediating relationship between instant messaging app use and suicidal ideation through thwarted belongingness and perceived burdensomeness. This study suggests that the use of instant messaging apps is indirectly associated with a lower risk of suicidal ideation.

Spy Shield is a new IoT-based personal safety device, which is aimed at ensuring quick response and security, especially in cases where a woman is at risk. The wearable device is an integration of camera and ultrasonic sensor to sense danger within the range of 10-15 cm to automatically take pictures, videos and audio of the victim and assailant. Spy Shield is an Arduino Uno-based device equipped with a GSM and GPS module to activate a loud alarm, and to send instant messages, including the accurate geographic position, to emergency contacts and local authorities pre-registered with SMS or email. The system expands the immediate response by enabling family and friends to be aware of the real-time location, access multimedia evidence, and coordinate the intervention by using Bluetooth or SIM connectivity. In addition to emergency response, Spy Shield can be used as a forensic tool, which will create essential evidence to identify and prosecute attackers. Its multi-layered safety system provides instant alerts, real time tracking and post attack forensic functions that enable users and their networks to respond promptly to a crisis. Spy Shield is a powerful and efficient security software that can be used to ensure personal safety, functioning independently and using GSM.

With the explosive growth of remote work, instant messaging software usage (IMSU) has become an important part of modern working patterns. However, previous studies have insufficiently explored its association with subsequent work engagement and potential delayed spillover patterns. Employing hierarchical regression analysis on 519 single-time-point datasets and 325 dual-time-point datasets, informed by the Job Demands-Resources (JD-R) model, this study explores the relationship between IMSU in remote work and work engagement, as well as potential explanatory pathways. The findings indicate that: (1) IMSU is negatively associated with work engagement; (2) Psychological detachment mediates the relationship between IMSU and work engagement; (3) Mindfulness was associated with a reduction in the negative association between IMSU and psychological detachment, and thus mitigated the indirect negative association between IMSU and work engagement via psychological detachment. This study enriches the exploration of outcomes related to IMSU, introduces the cross-domain bidirectional spillover patterns of “work → non-work → work” highlights the new challenge of blurred work-life boundaries in the context of digitalization and intelligence, examines the protective role of mindfulness, and extends the boundary conditions of individual resources in the relationship dynamics of IMSU in remote work, providing a new theoretical perspective for understanding work-life balance in remote work contexts.

In this paper, we present conversational longitudinal ecological assessment (CLEA), a novel conversational AI-enabled method for collecting ecologically valid, temporally sensitive qualitative health data via mobile instant messaging. We report findings from an exploratory deployment of an instantiation of CLEA within a 12-week community-based weight management programme, delivered by a charity partner in an area of deprivation. Using WhatsApp, we deployed our CLEA chat-agent to conduct twice-weekly conversational data collection sessions with participants, to elicit data about their experience of the programme and associated behaviour change. This was followed by in-person semi-structured interviews (N = 9) to examine user experiences and perceptions of interacting with the chat-agent. Participants reported that WhatsApp's familiarity supported accessibility and sustained engagement, while the conversational format encouraged reflection directed towards the research focus. Responding to chat-agent prompts required cognitive effort, leading some participants to defer engagement until they had adequate time and mental space; however, this reflective demand was largely experienced as beneficial within the programme context. The AI's quasi-human interactional qualities fostered a sense of support while reducing social judgement, enabling more candid disclosure. Together, these findings suggest initial feasibility and acceptability of this CLEA implementation within a community-based programme in an area of deprivation. Further, while the responses in single messages were often brief, useful, relevant, and meaningful insights appeared to develop over the course of conversational sessions. The study highlights both the opportunities and trade-offs of conversational AI for qualitative data collection, including design implications for health researchers looking to implement or extend the method. Finally, we position CLEA in relation to other longitudinal methods of qualitative health data elicitation.

Finding reliable local service providers in India—such as plumbers, electricians, carpenters, and painters—often depends on informal networks and word-of-mouth recommendations. This results in delays, inconsistent pricing, and a lack of trust in service quality. LocalConnect is a full-stack, AI-powered digital marketplace designed to bridge this gap by connecting customers with verified, nearby service providers. The platform integrates location-based search, real-time price negotiation, and AI-driven problem classification using image recognition. Users can upload images of household issues, which are analyzed by AI to recommend suitable vendors. Real-time chat and bargaining are supported through Socket.IO, while scalable backend APIs manage listings, bookings, reviews, and authentication. This paper presents the design, methodology, and implementation of LocalConnect along with its performance, advantages, and limitations.