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This study aims to investigate the impact of message framing (emotional vs rational) on social media users' ability to accurately detect information and their intention to share messages about the COVID-19 vaccine.

Using an experimental design approach, the authors recruited 600 adult participants via a crowdsourcing platform. Participants were randomly assigned to receive emotional or rational messages and their ability to accurately detect information and intention to share messages were assessed.

The results showed a significant multivariate effect of message framing on both the detection of accurate information and intention to share (p < 0.001). Participants who received emotional messages demonstrated better performance in the detection and sharing task than those who received rational messages. Gender and age also had significant main effects on the outcomes, with women performing better than men and younger participants performing better than older participants in detecting the accuracy of information. The interaction effects of the independent variables were not statistically significant (p = 0.098).

The findings highlight the importance of considering emotional factors in combating the spread of messages about the COVID-19 vaccine on social media. Practitioners responsible for social media content should strengthen the content review mechanism, with an emphasis on screening content with high emotional arousal.

Learning organization (LO) concept has received much attention in the last decades. The purpose of an LO is to proactively shape its future by fostering a culture of continuous learning among its members. This approach empowers the organization to adapt, evolve and innovate, aligning with the needs and aspirations of both internal and external stakeholders. As a result, the assessment of an organization’s LO level, whether strong or weak, becomes a matter of significance. This study aims to use Senge’s LO Questionnaire (SLOQ) in conjunction with latent profile analysis (LPA) to identify latent classes within the organization. This approach seeks to enhance the organization‘s learning potential and facilitate its evolution.

This research was a cross-sectional study conducted at Hamadan University of Medical Sciences, Iran. The statistical population consisted of 451 managers and employees across seven departments based at the university headquarters. The sample included 295 individuals, and data was collected using the SLOQ.

The LPA has shown an excellent accuracy (97%) in identifying SLOQ cut-off points (three classes of good, moderate and low). Most of the participants are considered as a moderate LO (55.9%), which implies the possibility of improving learning, especially enhancing “common vision” and “systemic thinking.” Also, individuals belonging to the high-class category were more likely to be male and hold associate degree than individuals in other categories.

This study depends on self-report, and different perceptions of questions can cause percept bias. Another limitation is about the nature of this research, which is cross-sectional, which may bring back causality among variables. The other is only three demographic variables have been considered, and it is necessary to pay attention to other influential variables in future studies.

The originality of this study lies in its use of the SLOQ in combination with LPA to identify latent classes in an organization to improve learning potentials.

Understanding the factors that influence individuals’ adherence to social distancing is critical to effective policymaking in respiratory pandemics such as COVID-19. This study aims to explore the role of social factors in relation to social distancing measures.

Stratified convenience sampling was used in this survey research, involving 450 adults residing in both rural and urban areas of Aligodarz County, Lorestan, Iran.

The findings showed that approximately 14% of participants did not adhere to any of the assessed social distancing behaviors, while only around 30% adhered to all four assessed behaviors. On average, participants reported having 5.13 (SD = 3.60) close physical contact within the 24 h prior to completing the questionnaire. Bridging social capital and gender emerged as the most frequently observed predictors across the assessed social distancing measures. Additionally, age, employment status and residential setting were identified as influential factors for some of the evaluated measures.

This study contributes to the field by highlighting that the likelihood of non-adherence to social distancing measures tends to increase among male participants, those aged above 60, employed individuals, urban residents and those with a higher level of bridging social capital.