Message Format Research Articles

The effects of supervisory negative feedback and coaching on employees' responses to feedback: The moderating role of mindset

AbstractFeedback is a vital human resource development (HRD) practice, extensively researched and used to regulate employee behavior and performance. However, despite a century of research and immense significance and use, we still do not fully know why some accept feedback while others reject it. Critics blame both providers and recipients, as well as feedback message format, for this failure. In this study, I investigated whether the focus of the supervisory feedback (negative vs. negative and facilitative) could enhance employees' responses to feedback (e.g., acceptance and use). I also examined whether employees' mindset (i.e., fixed vs. growth) would moderate these relationships. I proposed that employee coaching (i.e., negative and facilitative) would be more accepted than negative feedback alone. In addition, I expected a positive moderating role of the growth mindset between supervisory feedback and employees' responses. To test these assumptions, I conducted a laboratory experimental vignette study (N = 69). In line with propositions, employee coaching had a larger effect on the employees' responses to feedback (e.g., feedback acceptance; M = 4.95, SD = 1.24) than negative feedback alone (M = 4.08, SD = 1.35). In addition, simple slope results showed that employee coaching was significantly higher than negative feedback for growth mindset (i.e., +1 SD). Finally, path analysis revealed that the interaction between negative feedback, employee coaching, and mindset yielded the strongest positive effect on employees' responses to feedback. Overall, findings add to and endorse calls for more future‐focused HRD practices during feedback interventions. In addition, for effective feedback, this study calls for HRD practitioners to account for all critical factors involved in feedback exchanges, from provider to recipient and feedback message.

The Media Culture of Telegram Media Channels: Coverage of the Palestinian-Israeli Conflict

This article focuses on the study of the media culture of Telegram journalism. This messenger has long ceased to be a platform for messaging between users. Journalists have subordinated the functionality of Telegram to their activities: here they unite the audience, transmit information in the format of a personal message and provide a fi eld for expression. Russian journalists have begun to actively use the messenger for their professional activities since 2022: editorial offi ces of large media outlets create channels, and traditional media outlets quote publications from their own Telegram channels and the channels of colleagues in their materials. The relevance of the study lies in the fact that the media culture of Telegram media channels remains poorly studied, while the messenger is gaining popularity among online platforms for journalistic activities, posing strong competition to traditional media sites. In the process of research, the author used sampling, comparison and comparison methods and also turned to scientifi c theoretical materials on Internet journalism, journalism in social media and, in particular, the journalistic activities of Telegram. The purpose of the research is to study the media culture of modern Telegram journalism. The objective of the study is to use the example of practical material, namely, based on posts from the Telegram channels RIA Novosti, Readovka and Mash during the beginning of the Palestinian-Israeli confl ict, to study the tools of work of journalists in the messenger and determine their features in comparison with work on the websites of publications. The study revealed the features of the media culture of Telegram media channels: journalists more willingly and quickly transmit information in the messenger, in comparison with the publication’s website, actively integrate different formats for transmitting content, tools for infl uencing the attention of the audience, including at the stylistic level. The conducted research introduces the media culture of Telegram journalism and demonstrates the need for further and detailed study of the concept of Telegram journalism, the prospects for the development of modern Internet journalism, in particular in social media. Keywords: Telegram-journalism, media culture, messenger, online media, RIA Novosti, Mash, Readovka

Language abnormalities in Alzheimer's disease indicate reduced informativeness.

This study aims to elucidate the cognitive underpinnings of language abnormalities in Alzheimer's Disease (AD) using a computational cross-linguistic approach and ultimately enhance the understanding and diagnostic accuracy of the disease. Computational analyses were conducted on language samples of 156 English and 50 Persian speakers, comprising both AD patients and healthy controls, to extract language indicators of AD. Furthermore, we introduced a machine learning-based metric, Language Informativeness Index (LII), to quantify empty speech. Despite considerable disparities in surface structures between the two languages, we observed consistency across language indicators of AD in both English and Persian. Notably, indicators of AD in English resulted in a classification accuracy of 90% in classifying AD in Persian. The substantial degree of transferability suggests that the language abnormalities of AD do not tightly link to the surface structures specific to English. Subsequently, we posited that these abnormalities stem from impairments in a more universal aspect of language production: the ability to generate informative messages independent of the language spoken. Consistent with this hypothesis, we found significant correlations between language indicators of AD and empty speech in both English and Persian. The findings of this study suggest that language impairments in AD arise from a deficit in a universal aspect of message formation rather than from the breakdown of language-specific morphosyntactic structures. Beyond enhancing our understanding of the psycholinguistic deficits of AD, our approach fosters the development of diagnostic tools across various languages, enhancing health equity and biocultural diversity.

Examining the Influences of Message Formats, Context-Induced Moods, and Issue-Relevant Determinants on the Effectiveness of Ecolabels

We examined how young adults processed ecolabels (i.e. environmental warning labels), specifically by investigating how different warning message conditions and issue-relevant factors influenced the effectiveness of environmental warning messages. Findings from a 3 (message context formats: ads vs. positive PSAs vs. negative PSAs) x 3 (product categories: conservation vs. recycling vs. eco-friendly) mixed within- and between-subjects experimental design indicated that the effectiveness of ecolabels, assessed via message recall, message recognition, attitudes, and behavioral changes, was influenced by various issue-relevant determinants, as well as message context formats and context-induced moods. We also found that these predictors exhibited distinct patterns of influences for different types of environment-friendly products. Theoretical implications, as well as empirical suggestions for environmental communication professionals and policymakers to enhance the effectiveness of ecolabels and young adults’ awareness of environmental threats, were discussed.

The evolution of exceptions and investigations messaging and flows

This paper aims to provide the reader with information concerning the migration of exceptions and investigations (E&I) messages from the FIN MT format to the ISO 20022 format. In addition to this format migration, there are improvements that Swift will implement as part of their Case Manager product, such as smart routing of E&I messaging, automated confirmation of receipt messages and automated reminder generation. These enhancements will bring many benefits for financial institutions, such as cost reductions, due to a decrease in the number of cases being raised (ie no need to raise a case when playing the role of an intermediary for some investigation types), increased automation due to the new, structured elements of the ISO messaging format and clear investigation types, speed of resolution due to the smart routing logic and reduction of messaging legs required and fewer processes for operators as generation of the confirmation of receipt and the reminder/chaser messages are initiated by the Case Manager rather than requiring an operator to initiate these. This paper provides an overview of the ‘As is’ and ‘To be’ message formats and flows to enable the reader to fully understand the benefits that this migration will bring and the changes that will be mandated within the industry in the E&I space.

The Story My Friend Told Me: Examining the Interplay of Message Format and Relational Closeness in Misinformation Correction

ABSTRACT Narrative messages have been considered a potentially useful tool for correcting misinformation. However, prior research has found that the effect of narrative condition is often moderated by other communication characteristics. On social media, the relational closeness to an information endorser may serve as a heuristic cue to the endorser’s trustworthiness, ultimately influencing the acceptance of the endorsed information. In the current study, a 2 (message format: narrative vs. non-narrative) × 2 (relational closeness: distant vs. close friend) between-subjects online experiment tested the effects of narrative communication in correcting misinformation related to nicotine replacement therapy, conditioned by relational closeness to the person endorsing the correction on social media. The effects of the correction messages and relational closeness to the endorsers were assessed in an immediate test (T1) and a one-week delayed test (T2). When the correction was imagined to be endorsed by a close friend, narrative correction was more effective in increasing perceived trustworthiness of the correction endorser, leading to more favorable persuasion outcomes including T1 beliefs, T1 attitude, T2 beliefs, and T2 attitude. The indirect effect was not significant if participants imagined the correction was endorsed by a distant friend.

Supplemental Material for Communicating Nonviolence Messages: Effects of Racial Cues and Message Format on Black Parents’ Message Credibility Perceptions and Behavioral Change

Supplemental Material for Communicating Nonviolence Messages: Effects of Racial Cues and Message Format on Black Parents’ Message Credibility Perceptions and Behavioral Change

The impact of exposure to FDA e-cigarette authorization messages on product perceptions and interest - an experiment with adults who smoke and youth.

In the United States, e-cigarettes have entered a new regulatory era, needing authorizations from FDA to remain on or enter the marketplace. This study explored the impact of e-cigarette authorization messages on product perceptions and interest. We conducted an online experiment in June 2022 with nationally-representative samples of adults (21+) who smoke cigarettes (n=866) and youth ages 15-20 (n=859). They were randomized to one of five conditions: viewing an ad for a fictional e-cigarette brand with no reference to FDA (control), an ad with an "authorized for sale by FDA" claim in varying presentation styles (plain text, FDA "approved" stamp, FDA logo), or reading a fictional news excerpt about the product's authorization plus control ad. We compared group differences on product interest, susceptibility, harm perceptions and message perceptions. Among adults who smoke, there were no effects on product interest nor susceptibility, but ratings of the product's harmfulness compared to cigarettes were lower among those in the news versus control condition (β=-0.25, p=.04). Among youth, odds of susceptibility were higher among ever e-cigarette users who viewed the ad with the FDA logo authorization message relative to the control ad (OR=6.3, 95% CI:1.67-23.9, p<0.01). About 40% of all participants agreed the authorization claim makes them think the product is safe to use, but fewer (14-19%) agreed it makes them more interested in trying it. FDA e-cigarette authorization messages may impact some beliefs about product harm. More research is needed to track potential impacts on product use. This study provides new data about the potential impact of messages about FDA authorization of e-cigarette products (presented as ad claims or a news story) on authorized product perceptions, interest and susceptibility among adults who smoke cigarettes and youth. Our results suggest that FDA e-cigarette authorization messages may impact harm-related beliefs among adults who smoke and product susceptibility among youth who have ever used e-cigarettes before, though real-world effects are likely to be impacted by message type and format, and perceived message source and credibility. Authorization messages are likely to be misinterpreted as "FDA approval" by some; therefore, providing clarifications about authorization meaning and standards are relevant where possible.

Exploring the impact of automated correction of misinformation in social media

AbstractCorrecting misinformation is a complex task, influenced by various psychological, social, and technical factors. Most research evaluation methods for identifying effective correction approaches tend to rely on either crowdsourcing, questionnaires, lab‐based simulations, or hypothetical scenarios. However, the translation of these methods and findings into real‐world settings, where individuals willingly and freely disseminate misinformation, remains largely unexplored. Consequently, we lack a comprehensive understanding of how individuals who share misinformation in natural online environments would respond to corrective interventions. In this study, we explore the effectiveness of corrective messaging on 3898 users who shared misinformation on Twitter/X over 2 years. We designed and deployed a bot to automatically identify individuals who share misinformation and subsequently alert them to related fact‐checks in various message formats. Our analysis shows that only a small minority of users react positively to the corrective messages, with most users either ignoring them or reacting negatively. Nevertheless, we also found that more active users were proportionally more likely to react positively to corrections and we observed that different message tones made particular user groups more likely to react to the bot.

Research on Deformation Prediction of VMD-GRU Deep Foundation Pit Based on PSO Optimization Parameters.

As a key guarantee and cornerstone of building quality, the importance of deformation prediction for deep foundation pits cannot be ignored. However, the deformation data of deep foundation pits have the characteristics of nonlinearity and instability, which will increase the difficulty of deformation prediction. In response to this characteristic and the difficulty of traditional deformation prediction methods to excavate the correlation between data of different time spans, the advantages of variational mode decomposition (VMD) in processing non-stationary series and a gated cycle unit (GRU) in processing complex time series data are considered. A predictive model combining particle swarm optimization (PSO), variational mode decomposition, and a gated cyclic unit is proposed. Firstly, the VMD optimized by the PSO algorithm was used to decompose the original data and obtain the Internet Message Format (IMF). Secondly, the GRU model optimized by PSO was used to predict each IMF. Finally, the predicted value of each component was summed with equal weight to obtain the final predicted value. The case study results show that the average absolute errors of the PSO-GRU prediction model on the original sequence, EMD decomposition, and VMD decomposition data are 0.502 mm, 0.462 mm, and 0.127 mm, respectively. Compared with the prediction mean square errors of the LSTM, GRU, and PSO-LSTM prediction models, the PSO-GRU on the PTB0 data of VMD decomposition decreased by 62.76%, 75.99%, and 53.14%, respectively. The PTB04 data decreased by 70%, 85.17%, and 69.36%, respectively. In addition, compared to the PSO-LSTM model, it decreased by 8.57% in terms of the model time. When the prediction step size increased from three stages to five stages, the mean errors of the four prediction models on the original data, EMD decomposed data, and VMD decomposed data increased by 28.17%, 3.44%, and 14.24%, respectively. The data decomposed by VMD are more conducive to model prediction and can effectively improve the accuracy of model prediction. An increase in the prediction step size will reduce the accuracy of the deformation prediction. The PSO-VMD-GRU model constructed has the advantages of reliable accuracy and a wide application range, and can effectively guide the construction of foundation pit engineering.

“It’s My Moral Responsibility to Protect Others!” Examining the Effects of Moral Framing and Message Format on Influenza Vaccination Attitude and Intention

ABSTRACT Vaccinations serve a dual purpose: safeguarding the vaccinated individuals while also preventing potential transmission to others. However, the pro-vaccine message has primarily emphasized the personal health risks and harms of not getting vaccinated, while rarely highlighting the moral responsibility of getting vaccinated to protect others. Guided by the Model of Intuitive Morality and Exemplars (MIME) along with the narrative persuasion framework, the current study conducted a 2 (moral framing: vaccination to protect oneself vs. protect others) X 2 (message format: statistical vs. narrative) between-subject online experiment to examine the effects of moral framing and message format on vaccination decision-making. The results revealed that individuals exposed to a pro-vaccine message framing vaccination as a moral responsibility to protect others from harm reported significantly higher levels of perceived moral responsibility and elevation, more positive attitudes toward the flu vaccine, and an increased intention to get vaccinated compared to a pro-vaccine message emphasizing vaccination for self-protection. Counterintuitively, presenting the moral responsibility of receiving the flu vaccine to safeguard others in a statistical format was discovered to be more effective in fostering favorable attitudes toward vaccination and increasing the intention to get vaccinated. This study offers a valuable insight: promoting vaccination as a moral duty could be a promising strategy for motivating individuals to get vaccinated.

Accuracy of a large language model in distinguishing anti- and pro-vaccination messages on social media: The case of human papillomavirus vaccination

ObjectiveVaccination has engendered a spectrum of public opinions, with social media acting as a crucial platform for health-related discussions. The emergence of artificial intelligence technologies, such as large language models (LLMs), offers a novel opportunity to efficiently investigate public discourses. This research assesses the accuracy of ChatGPT, a widely used and freely available service built upon an LLM, for sentiment analysis to discern different stances toward Human Papillomavirus (HPV) vaccination. MethodsMessages related to HPV vaccination were collected from social media supporting different message formats: Facebook (long format) and Twitter (short format). A selection of 1,000 human-evaluated messages was input into the LLM, which generated multiple response instances containing its classification results. Accuracy was measured for each message as the level of concurrence between human and machine decisions, ranging between 0 and 1. ResultsAverage accuracy was notably high when 20 response instances were used to determine the machine decision of each message: .882 (SE = .021) and .750 (SE = .029) for anti- and pro-vaccination long-form; .773 (SE = .027) and .723 (SE = .029) for anti- and pro-vaccination short-form, respectively. Using only three or even one instance did not lead to a severe decrease in accuracy. However, for long-form messages, the language model exhibited significantly lower accuracy in categorizing pro-vaccination messages than anti-vaccination ones. ConclusionsChatGPT shows potential in analyzing public opinions on HPV vaccination using social media content. However, understanding the characteristics and limitations of a language model within specific public health contexts remains imperative.

GymHydro: An Innovative Modular Small-Scale Smart Agriculture System for Hydroponic Greenhouses

In response to the challenges posed by climate change, including extreme weather events, such as heavy rainfall and droughts, the agricultural sector is increasingly seeking solutions for the efficient use of resources, particularly water. Pivotal aspects of smart agriculture include the establishment of weather-independent systems and the implementation of precise monitoring and control of plant growth and environmental conditions. Hydroponic cultivation techniques have emerged as transformative solutions with the potential to reduce water consumption for cultivation and offer a sheltered environment for crops, protecting them from the unpredictable impacts of climate change. However, a significant challenge lies in the frequent need for human intervention to ensure the efficiency and effectiveness of these systems. This paper introduces a novel system with a modular architecture, offering the ability to incorporate new functionalities without necessitating a complete system redesign. The autonomous hydroponic greenhouse, designed and implemented in this study, maintains stable environmental parameters to create an ideal environment for cultivating tomato plants. Actuators, receiving commands from a cloud application situated at the network’s edge, automatically regulate environmental conditions. Decision-making within this application is facilitated by a PID control algorithm, ensuring precision in control commands transmitted through the MQTT protocol and the NGSI-LD message format. The system transitioned from a single virtual machine in the public cloud to edge computing, specifically on a Raspberry Pi 3, to address latency concerns. In this study, we analyzed various delay aspects and network latency to better understand their significance in delays. This transition resulted in a significant reduction in communication latency and a reduction in total service delay, enhancing the system’s real-time responsiveness. The utilization of LoRa communication technology connects IoT devices to a gateway, typically located at the main farm building, addressing the challenge of limited Internet connectivity in remote greenhouse locations. Monitoring data are made accessible to end-users through a smartphone app, offering real-time insights into the greenhouse environment. Furthermore, end-users have the capability to modify system parameters manually and remotely when necessary. This approach not only provides a robust solution to climate-induced challenges but also enhances the efficiency and intelligence of agricultural practices. The transition to digitization poses a significant challenge for farmers. Our proposed system not only represents a step forward toward sustainable and precise agriculture but also serves as a practical demonstrator, providing farmers with a key tool during this crucial digital transition. The demonstrator enables farmers to optimize crop growth and resource management, concretely showcasing the benefits of smart and precise agriculture.

Envisioning the Future

The highly contagious nature of the novel Coronavirus locks-unlocks and economic uncertainty around the world have changed the complete landscape of the tourism sector. To attract tourists, it is necessary to revise the content strategy of Destination Marketing Organizations (DMOs) in the post-Covid economy. This study explores how different characteristics of DMO’s social media posts influence tourists’ online engagement. We used 876 posts from July 2021 to June 2022 on the official Facebook handle of Incredible India, through which we assessed the tourists’ ‘engagement’, using the number of likes, comments, and shares. Additionally, linguistic features-based categorization of posts was done using LIWC. The results demonstrate that message format, message appeal, motives, and time orientation of posts significantly influence the tourists’ online engagement. These findings are relevant to information dissemination and provide valuable insights for DMOs. DMOs could use this study to design their future messages to gather maximum engagement through social media posts.

190 Translating Alzheimer’s Disease Research to Improve Dementia Screening Through Health Message Design in the Community: A Qualitative Study

OBJECTIVES/GOALS: This study engaged Black adults who reside in a rural area of Kentucky to explore their beliefs, norms, knowledge, attitudes, and health-related behaviors about Alzheimer’s disease (AD) (RQ1) and what message elements are most relevant for designing a health message aimed at encouraging them to get screened for AD (RQ2). METHODS/STUDY POPULATION: This qualitative study was guided bythe Integrative Model of Behavior. Participants were recruited from a faith-based institution in rural Kentucky. Black adults aged 50+ years were invited to participate in the study, which consisted of two focus groups. Group 1 gained information about behavioral determinants (RQ1) and examined which message design elements were important to Black adults by asking for feedback on a handout from the Alzheimer’s Association that encouraged AD screening (RQ2). The handout was redesigned based on feedback from Group 1. Group 2 was involved in a discussion of the redesigned handout, asking for further feedback. Focus groups were audio recorded and transcribed verbatim. Data analysis included thematic analysis of transcripts of the focus groups and quantitative analysis. RESULTS/ANTICIPATED RESULTS: Participants (N=18) were all female and Black with a mean age of sixty-two years. For RQ1, Results revealed that 1) limited knowledge of AD led to feelings of not being able to do anything about the disease, whereas awareness and education led to hope; 2) past healthcare experiences informed subsequent beliefs and behaviors, and 3) culture impacted beliefs, with a cultural norm of “what happens in our house, stays in our house” being prominent. For RQ2, results revealed the importance of regionally specific messaging for AD. Generic statements that applied broadly did not appeal to participants. Message delivery, layout, and format for low literacy individuals are key for maximizing audience impact. Pictures give hints about the message and aid in understanding. DISCUSSION/SIGNIFICANCE: Barriers such as past experiences, lack of knowledge, and cultural norms negatively impact the likelihood that Black adults will get screened for AD, resulting in delayed healthcare or healthcare avoidance. Regionally specific health messaging for AD has the potential to encourage modifications in health-related behaviors.

Cross-Chain Digital Asset System for Secure Trading and Payment

Blockchain as a ledger technology is attractive without the need for central servers. There are many types of blockchains in different fields, such as digital asset trading and payment, which have business interactions. In the fields, the digital asset and payment information on their blockchains need to be securely cooperative with each other. However, some business activities are on different blockchains, which have different consensus algorithms and network architectures, thus limiting the interoperability among these activities and making each blockchain an island. Cross-chain technology can connect different blockchains and realize the interoperability and sharing of information among them. This work designs a cross-chain digital asset system for secure trading and payment. It builds two parallel chains, i.e., digital asset chain (DAC) and payment chain (PC), and their functions are analyzed and designed. The cross-chain, i.e., relay chain (RC), is used to realize cross-chain interoperability, where the cross-chain message format and authority setting are designed to endow parallel chains with the ability to recognize. The decentralized characteristic of the RC allows cross-chain messages to be safely transmitted to ensure secure trading and payment. Through testing and analysis, the proposed system can provide more secure trading and payment than its peers.

PrioMQTT: A prioritized version of the MQTT protocol

MQTT is an application layer protocol that, thanks to its simplicity and low overhead, is widely used in the Internet of Things (IoT) devices typically found in home automation and consumer applications. The MQTT properties make it an interesting option also for Industrial IoT (IIoT) applications. However, MQTT is not specifically devised for IIoT applications requiring low-latency and the support for time-constrained transmissions. For this reason, this paper proposes an IIoT-enabled version of MQTT called a Prioritized MQTT (PrioMQTT) that is able to provide low latencies to time-critical messages. Unlike the standard MQTT, PrioMQTT adopts the UDP/IP stack, which is more suitable than TCP/IP for low-latency communications. Moreover, PrioMQTT introduces a mechanism to prioritize the time-critical messages over the non-time-critical ones. The combination of the UDP/IP stack and priority support in the PrioMQTT protocol is achieved while maintaining the compliance with the MQTT standard message format. As a result, PrioMQTT can be implemented on commercial-off-the-shelves (COTS) devices without hardware modifications. The paper describes the PrioMQTT protocol and investigates its performance through an assessment in a realistic industrial scenario and in comparison with the standard MQTT protocol.

Hardware Sequence Combinators

Recent advances in formal methods for constructing parsers have employed the notion of combinators: primitive elemental parsers with well-defined methods for combining them in sequences or through choice. This paper explores the subtleties associated with leveraging sequence combinators to produce compact, custom hardware traffic validators. This involves a fully automated process that takes as input a formal grammar specifying message formats and produces a parsing circuit capable of validating traffic headers and payload content. The resulting circuit is deployed through network guard appliances that employ Field Programmable Gate Array (FPGA) devices, or alternatively, within the on-chip FPGA associated with System-on-Chip (SoC) devices, such as the Xilinx UltraScale MPSoC. Each guard appliance acts as a hidden “bump-in-the-wire” that either forwards or drops individual packets based on the message parsing outcome, thereby hardening network segments against zero-day attacks and persistent implants. Guards may operate on a wide variety traffic protocols and formats including TCP/IP, CAN/J1939, or MIL-STD-1553. The central step in parser construction is to build a collection of standard shift/reduce parsing tables that can be employed by a push-down automata to check each byte in a message. Typically, these tables are sparse, resulting in excessive use of FPGA circuit resources to represent them. By leveraging sequence combinators, along with other optimizations, we have been able to produce highly compact representations that can reduce table size by up to 95% for non-trivial grammars. Depending on the grammar, this translates directly into FPGA resource reductions. The reductions now make it viable to implement complex parsers on small, inexpensive FPGA’s, or alternatively combine parsers with encryption and encapsulation to enhance guard capabilities.

The Effects of Peer Mental Illness Narratives on Reducing Stigma Among U.S. Marginalized College Students

ABSTRACT Mental health stigma remains a significant barrier to accessing mental health care and treatment, particularly among racial, ethnic, gender, and LGBTQIA+ underrepresented groups in the United States. This study aimed to investigate the relative persuasiveness of mental health narratives featuring both marginalized and non-marginalized characters in reducing stigma among college students. We conducted an online between-subjects experiment with a sample size of 292 participants to explore the impacts of message format (narrative vs. non-narrative), narrative point of view (first-person vs. third-person), and character similarity (marginalized vs. non-marginalized voices) on the persuasion process, specifically targeting the reduction of stigma and changes in attitudes toward those seeking mental health services. Findings revealed that the use of narrative messaging had no effect on reducing mental health stigma or treatment attitudes, but narrative campaigns featuring members of underrepresented groups did enhance one’s perceived similarity with mediated characters, which in turn resulted in more support for seeking mental health treatment. These findings have implications for the design of social media-based anti-stigma interventions and narrative persuasion in mental health research.

Model of formation of a typical message for evaluating the performance of the information-measuring system functioning

Currently, one of the topical issues arising in the functioning of information and measurement systems (AIS) for various purposes is the issue of evaluating its effectiveness. For AIS of various classes, a significant complication of the background-target situation, based primarily on an increase in the number objects of observation in near-Earth outer space is the main problem. The throughput capacity is provided for each AIS in their tactical and technical characteristics. This characteristic is determined even at the design stage based on the actual working conditions for targets and interference, taking into account the provision of their guaranteed observation. However, based on the above, it turns out that modern AIS, depending on the location and direction of the viewing area, are already working at the limits of their capacity capacity, or this will happen in the near future. On the AIS, the throughput is determined by such a parameter as the rate of formation of the first typical messages with a given probability. Based on the relevance of the described problem, it is of interest to simulate the operation of ICS in the conditions of extreme loads in terms of throughput in order to assess the real probability of the formation of the first vehicle, as well as to determine the factors that have a negative impact on the considered indicators.