High Social Engagement Research Articles

Examining the Association between Social Media Use and Dietary Habits among College Students in Riyadh, Saudi Arabia.

Food culture plays a vital role in societal dynamics, with various factors influencing dietary choices beyond hunger. Among these factors are external eating, triggered by environmental cues, and emotional eating, which are common stress-coping mechanisms among college students. Social media has a significant impact on nutrition by providing access to food-related content, which can lead to restrictive diets or unhealthy eating habits. High social media engagement is associated with an increased risk of chronic diet-related conditions such as metabolic syndrome. This study investigated the association between social media use and dietary habits among college students in Riyadh, Saudi Arabia. The cross-sectional study surveyed 401 participants online. The findings revealed that 74.6% of participants were women, with a mean age of 20.75 years. A significant portion (51.9%) reported spending over four hours daily on social media, with TikTok, Instagram, and YouTube being the primary sources of nutritional information. Statistical analysis indicated significant differences in dietary scores related to having children, medical conditions, and social media usage time. This study highlights the negative impact of extensive social media use on dietary habits and suggests the need for targeted public health interventions. Recommendations include promoting reliable nutrition-related content on social media, offering affordable healthy food options on campuses, and conducting further research to establish causality between social media use and dietary habits.

How Does Successful Aging Apply To Black Women?: A Latent Class Analysis.

Although prior research has identified racial/ethnic and gender differences in successful aging (SA), heterogeneity within groups has been little examined. We consequently explore the variety of aging experiences among older Black women. We used the 2010/2012 U.S. Health and Retirement Study, limiting analyses to Black women who completed the Psychosocial Leave-Behind Questionnaire (N = 1,186). We conducted latent class analysis (LCA) using indicators of physical health, psychological well-being, social support/strain, and social engagement. Six SA latent classes were identified and labeled according to their distinctive characteristics: infirm, isolated, taxed, independent, vivacious, and robust. The infirm class had uniformly poor health, while the isolated class was in poor physical health but also lacked social relations. Although both had average physical health and psychological well-being, the taxed class experienced high levels of social support and social strain compared to the high support (and unpartnered) independent class. The vivacious and robust classes exhibited high physical health and psychological well-being, high social support/low social strain, and high social engagement, but vivacious women (23% of respondents) were unpartnered and robust women (16% of respondents) were partnered. The robust class had the highest physical and psychological well-being, and best social relations across all classes. Using nationally representative data, we reveal significant heterogeneity in Black women's aging experiences. Although many face difficult aging experiences, 39% of older Black women fit the SA framework well. Future work should recognize that Black women's aging experiences are not homogenous.

Navigating Purchase Intentions: The Influence of Reviewers' Comments Moderated by Risk and Trust.

Despite previous research on the impact of social media reviews on purchase intention, it is still unclear how individual reviewers' comments impact purchase intentions. To fill in the gap, this study examines the impact of product-related comments on purchase intentions. In terms of contributions, this study evaluates people's dependence on social media for product information and purchase intention while considering risk and trust as moderating factors. The data were collected quantitatively using surveys. The sample consisted of 384 academically advanced adults with high social media engagement. The study hypotheses were tested using the PROCESS macro after exploratory and confirmatory factor analysis, and correlation analysis were conducted. Among those surveyed, it was confirmed that most people sought product-related comments on social media when seeking information about a product they might be interested in purchasing. It was also observed that the risk factor reduced the impact of other variables in the model presented in this study. In conclusion, this investigation is more reliable, and its outcomes benefit scholars, supervisors, merchants, and webmasters, for instance, in establishing a study for future research efforts and providing practical guidance that could boost promotional efforts and marketing activities, especially in this era of artificial intelligence.

The African American Dementia and Aging Project (AADAPt): An Oregon-based Longitudinal Study.

The vast majority of studies on aging, cognition, and dementia focus on non-Hispanic white subjects. This paper adds to the extant literature by providing insight into the African American aging experience. Here we describe the study design and baseline characteristics of the African American Dementia and Aging Project (AADAPt) study, which is exploring aging and cognition in African American older adults in Oregon. African American older adults (n=177) participated in AADAPt, a longitudinal study that collected data on cognitive, physical, and social functioning in annual visits since 2000. AADAPt participants had risk factors for developing dementia in future, such as hypertension and hyperlipidemia, but also reported protective factors such as high social engagement. The AADAPt project offers new insights into aging in older African Americans that includes data on cognition, social engagement, and physical health, which are crucial for understanding the experience of under-represented groups and making future studies more inclusive. These findings reflect a window of time for a geographically-focused cohort, and the lessons learned from this study likely have broader implications for shaping the health of these older African American adults. Keywords: African American, Dementia, Observational Study.

Social engagement and cognitive impairment among nursing home residents: The role of sensory impairment

Background and objectivesUsing US national nursing home data, this cross-sectional study sought to evaluate 1) the association between lack of social engagement and level of cognitive impairment; and 2) the extent to which this association differs by hearing and visual impairment. Research design and methodsOur sample included 793,846 nursing home residents aged ≥ 50 years. The Index of Social Engagement was categorized as none/lower (0, 1, 2) or higher levels (3 through 6). Cognitive Performance Scale was grouped as intact/mild (0, 1, 2), moderate (3, 4), or severe (5, 6). Multinomial models provided adjusted odds ratio (aOR) and 95 % confidence intervals (CI) between none/lower social engagement and cognitive impairment. We estimated relative excess risk due to interaction (RERI) to quantify the joint effects of social engagement and sensory impairment types. ResultsOverall, 12.6 % had lower social engagement, 30.3 % had hearing impairment, and 40.3 % had visual impairment. Compared to residents with high social engagement, those with lower social engagement were more likely to have moderate/severe cognitive impairment (aORmoderate = 2.21, 95 % CI 2.17–2.26; aORsevere = 6.49, 95 % CI 6.24–6.74). The impact of low social engagement on cognitive impairment was more profound among residents with hearing impairment and/or visual impairment (RERIhearing = 3.89, 95 % CI 3.62–4.17; RERIvisual = 25.2, 95 % CI 23.9–26.6)). Discussion and implicationsResidents with lower social engagement had higher levels of cognitive impairment. Residents with sensory impairments are potentially more susceptible to the negative impact of lower levels of social engagement on level of cognitive impairment.

Characterizing Anti-Vaping Posts for Effective Communication on Instagram Using Multimodal Deep Learning.

Instagram is a popular social networking platform for sharing photos with a large proportion of youth and young adult users. We aim to identify key features in anti-vaping Instagram image posts associated with high social media user engagement by artificial intelligence. We collected 8972 anti-vaping Instagram image posts and hand-coded 2200 Instagram images to identify nine image features such as warning signs and person-shown vaping. We utilized a deep-learning model, the OpenAI: contrastive language-image pre-training with ViT-B/32 as the backbone and a 5-fold cross-validation model evaluation, to extract similar features from the Instagram image and further trained logistic regression models for multilabel classification. Latent Dirichlet Allocation model and Valence Aware Dictionary and sEntiment Reasoner were used to extract the topics and sentiment from the captions. Negative binomial regression models were applied to identify features associated with the likes and comments count of posts. Several features identified in anti-vaping Instagram image posts were significantly associated with high social media user engagement (likes or comments), such as educational warnings and warning signs. Instagram posts with captions about health risks associated with vaping received significantly more likes or comments than those about help quitting smoking or vaping. Compared to the model based on 2200 hand-coded Instagram image posts, more significant features have been identified from 8972 AI-labeled Instagram image posts. Features identified from anti-vaping Instagram image posts will provide a potentially effective way to communicate with the public about the health effects of e-cigarette use. Considering the increasing popularity of social media and the current vaping epidemic, especially among youth and young adults, it becomes necessary to understand e-cigarette-related content on social media. Although pro-vaping messages dominate social media, anti-vaping messages are limited and often have low user engagement. Using advanced deep-learning and statistical models, we identified several features in anti-vaping Instagram image posts significantly associated with high user engagement. Our findings provide a potential approach to effectively communicate with the public about the health risks of vaping to protect public health.

Multimorbidity, Social Engagement, and Age-Related Cognitive Decline in Older Adults from the Rancho Bernardo Study of Healthy Aging.

Multimorbidity is associated with increased rate of cognitive decline with age. It is unknown whether social engagement, which is associated with reduced risk of dementia, modifies associations between multimorbidity and cognitive decline. To examine the associations of multimorbidity with longitudinal cognitive test performance among community-dwelling older adults, and to determine whether associations differed by levels of social engagement. We used data from the Rancho Bernardo Study of Healthy Aging, a community-based prospective cohort study. Starting in 1992-1996, participants completed a battery of cognitive function tests at up to 6 study visits over 23.7 (mean = 7.2) years. Multimorbidity was defined as≥2 of 14 chronic diseases. Social engagement was assessed using items based on the Berkman-Syme Social Network Index. Multivariable linear mixed-effects models were used to test associations of multimorbidity and cognitive performance trajectories. Effect measure modification by social engagement was evaluated. Among 1,381 participants (mean age = 74.5 years; 60.8% women; 98.8% non-Hispanic White), 37.1% had multimorbidity and 35.1% had low social engagement. Multimorbidity was associated with faster declines in Mini-Mental State Examination (MMSE; β= -0.20; 95% CI -0.35, -0.04), Trail-Making Test Part B (β= 10.02; 95% CI 5.77, 14.27), and Category Fluency (β= -0.42; 95% CI -0.72, -0.13) after adjustment for socio-demographic and health-related characteristics. Multimorbidity was associated with faster declines in MMSE among those with low compared to medium and high social engagement (p-interaction < 0.01). Multimorbidity was associated with faster declines in cognition among community-dwelling older adults. Higher social engagement may mitigate multimorbidity-associated cognitive decline.

The European Portuguese version of the Fear of Missing Out scale (FoMOs-P) in higher education students

AbstractThis study adapted and validated the European Portuguese version of the Fear of Missing Out scale (FoMOs-P) and determined an “optimal” cutoff score for higher education students with high social media engagement. Five hundred Portuguese students (M = 22.37, SD = 5.68) completed FoMOs-P and measures of sleep quality, rumination, and social media. Following previous conflicting results, Confirmatory Factor Analysis (CFA) was conducted to compare two competing factor structures. Model invariance regarding sex was tested using multi-group CFA. FoMOs-P’ internal consistency, convergent and discriminant validity were analyzed, and an “optimal” cutoff point was explored through Receiver Operating Characteristic (ROC) analysis. When comparing CFA models, the two-related-factor model fit best (Δχ2 (1) = 495.01, p &lt; .001), demonstrating a good fit (χ2/df = 2.96; CFI = .98; TLI = .97; RMSEA [90 CI] = .063 [.049;.077]). This model showed metric invariance but not scalar invariance across sex. There was adequate reliability for both factors and total scale (ω &gt; .7). Convergent and discriminant validity were supported. ROC analysis revealed an AUC = .742 (p &lt; .001) and an “optimal” cutoff point of 20 (70.1% sensitivity, 68.4% specificity) to detect probable disruptive social media engagement. FoMOs-P was shown to be a reliable and valid instrument, supporting its use among higher education students. FoMOs-P appears to be composed of two factors [(i.e., internalizing and externalizing Fear of Missing Out (FoMO)] and has moderate accuracy to screen students with high social media usage.

Social engagement and the risk of incident dementia: the Atherosclerosis Risk in Communities study

AbstractBackgroundStrong psychosocial health has been linked to preserved cognition and functional independence in older adults. Associations between late‐life psychosocial health and dementia risk have been established in older adults, but it remains less clear how one’s social interactions in mid‐life may relate to dementia risk in late life. We hypothesized that social engagement in mid‐life will be negatively associated with the risk of dementia in late‐life.MethodWe included data from 13,216 dementia‐free participants at midlife (mean age: 57.0 years, SD: 5.7 years, 54.9% female, 23.8% Black) from the Atherosclerosis Risk in Communities (ARIC) cohort study. Social support and isolation were assessed via interviewer‐administered questionnaires (visit 2: 1990‐1992). Based upon categorization of both factors, participants were classified as having high, intermediate, or low mid‐life social engagement. Incident dementia cases were identified from visit 2 through December 31, 2019 with ongoing surveillance (e.g., in‐person neurocognitive testing, informant interviews, and hospitalization codes). Primary analyses used Cox proportional hazards regression models and were adjusted for demographics, APOE ε4, occupational/marital status, depressive symptoms, and vascular risk factors measured at visit 2. Secondary analyses examined whether sex and/or race modified the association between mid‐life social engagement and dementia risk with formal tests for interaction.ResultAmong 13,261 participants, 2,555 developed dementia (median follow‐up: 23.7 years). Participants with high (hazard ratio (HR): 0.77, 95% CI: 0.68 ‐ 0.86) or intermediate social engagement (HR: 0.84, 95% CI: 0.74 – 0.95) in mid‐life had a lower risk for developing dementia, compared to participants with low social engagement in mid‐life (Figure 1, Table 1). Sex modified this effect (p‐value for interaction = 0.042) whereas race did not. In males, only those with high social engagement in mid‐life had a lower risk of dementia; the association between males with intermediate social engagement in mid‐life and dementia risk was not significant (Table 2).ConclusionGreater social engagement in mid‐life is associated with a lower risk of dementia. This finding provides further evidence that mid‐life may be a critical time window for dementia prevention. Longitudinal studies evaluating the mechanisms by which psychosocial factors modify the likelihood of incident dementia are needed.

Online communication styles of narcissistic content and low versus high social media engagement: evidence from Instagram

Online communication styles of narcissistic content and low versus high social media engagement: evidence from Instagram

Investigating the impact of food tourism vlogger entrepreneurs' language characteristics on audiences' attitude and behaviours

PurposeDespite entrepreneurial linguistic style gaining increased attention in entrepreneurship studies, the field for digital vlogger entrepreneurs still lacks a comprehensive understanding of how linguistic patterns enhance audiences attitude and behaviour. This study aims to propose a conceptual model of “language-mental imagery-attitude-behaviour model” that leads to the examination of rich sensory language style of food travel vlogger entrepreneurs and its persuasive effect on audiences' attitude and behavioural intention.Design/methodology/approachThe present study utilises a stimulus-based survey method that involves a sensory-rich vlog script extracted from a high social media engagement authentic vlog. Data are collected through an online questionnaire distributed to a sample of 355 participants via the Amazon Turk mechanism. The study employs confirmatory factor analysis and structural equation modelling to test the proposed hypotheses, with the aim of contributing to the advancement of theories of embodied cognition in entrepreneurial language by examining the attitudes and behaviours of audiences exposed to sensory-rich language. The findings of this research provide valuable insights into the effects of sensory-rich language on audience responses and can inform future research on the role of embodied cognition in entrepreneurial communication.FindingsThe findings demonstrate that vlogger entrepreneurial sensory-rich linguistic communication style positively influence audiences' attitude, behavioural involvement with food and intention to taste. Visit intention will be enhanced via the mediating effects of attitude, behavioural involvement with food and intention to taste.Practical implicationsThis research highlights the significance of sensory-rich language for vlogger entrepreneurs in entrepreneurial communication, digital storytelling and for destination marketing enterprises in creating a digital sensory engagement marketing strategy.Originality/valueThe study contributes to the literature by elucidating the theories of embodied cognition in entrepreneurial communication. By examining the relationships between vlogger communication evoked mental imagery, audiences attitude and behaviours, this study provides novel insights into the effectiveness of sensory-rich language in vlogger entrepreneurial communication and its impact on audience engagement. These findings have important implications for communication scholars and practitioners alike, shedding light on the role of embodied cognition in entrepreneurial language and the potential of sensory-rich language to enhance audience engagement.

How Social Connection and Engagement Relate to Functional Limitations and Depressive Symptoms Outcomes After Stroke.

Stroke commonly leads to disability and depression. Social connection and engagement can be protective against functional decline and depression in the general population. We investigated the effects of social connection and engagement on trajectories of function and depressive symptoms in stroke. This is a longitudinal study, which included 898 participants with incident stroke from the HRS study (Health and Retirement Study) between 1998 and 2012. Multilevel modeling was used to examine associations of social connection and engagement with changes in functional limitations in instrumental activities of daily living (IADLs) and depressive symptoms over time. Models controlled for age, gender, education, and race/ethnicity. Moderation analyses examined whether high social connection and engagement reduced depressive symptoms for survivors with high IADL impairment. Social connection and engagement were generally associated with fewer IADL limitations and depressive symptoms at the time of stroke and after stroke. For example, participants who felt lonely and did not provide help to others before stroke had more IADL limitations. Prestroke volunteering was associated with less increase in IADL limitations with stroke and increase in having friends and providing help to others compared with one's prestroke status were associated with fewer IADL limitations after stroke. For depressive symptoms, participants who felt lonely and did not have a friend or partner before stroke had more depressive symptoms, and participants who had children residing nearby before stroke showed less increase in depressive symptoms. Moderation effects were not found for social connection and engagement on high IADL impairment and depressive symptoms. Findings suggest that social connection and engagement may reduce the negative physical and psychological outcomes of stroke, both at baseline and after stroke. Efforts to enhance social engagement and diminish loneliness may both enhance population well-being and enhance resilience and recovery from stroke and other illnesses.

How should B2B firms create image content for high social media engagement? A multimodal analysis

PurposeThis study evaluates the effect of the media image content of business to business (B2B) organizations to accelerate social media engagement. It highlights the importance of strategically designing image content for business marketing strategies.Design/methodology/approachThis study designed a computation extensive research model based upon the stimulus-organism-response (SOR) theory using 39,139 Facebook posts of 125 organizations selected from Fortune 500 firms. Attributes from images and text were estimated using deep learning models. Subsequently, inferential analysis was established with ordinary least squares regression. Further machine learning algorithms, like support vector regression, k-nearest neighbour, decision tree and random forest, are used to analyze the significance and robustness of the proposed model for predicting engagement metrics.FindingsThe results indicate that the social media (SM) image content of B2B firms significantly impacts their social media engagement. The visual and linguistic attributes are extracted from the image using deep learning. The distinctive effect of each feature on social media engagement (SME) is empirically verified in this study.Originality/valueThis research presents practical insights formulated by embedding marketing, advertising, image processing and statistical knowledge of SM analytics. The findings of this study provide evidence for the stimulating effect of image content concerning SME. Based on the theoretical implications of this study, marketing and media content practitioners can enhance the efficacy of SM posts in engaging users.

Stakeholders' engagement through social media analytics in promoting sustainable development practices in the mobile supply chain: A cross‐country analysis

AbstractThe stakeholders' perceptions can significantly impact the management of the supply chain; however, there has been little comparative research on customers' opinions in various regions of the world. This paper conducted a thematic analysis to determine the differences between consumers' perceptions in developed and developing countries. This study analyzes six countries—the United States, the United Kingdom, Germany, India, Japan, and China—with a high social media engagement rate. Then, sentiment analysis was utilized to uncover consumers' emotions. The results indicate that social media users in developing nations are increasingly concerned about the sustainability of the mobile supply chain. Also, developing nations tweeted primarily about socially sustainable practices, whereas developed nations were more concerned with environmentally sustainable practices. This study contributes to the theory of stakeholders and institutions by concentrating on external stakeholders and analyzing their perspectives to determine how to enhance sustainable practices in supply chains.

Different personality profiles in patients with cluster headache: a data-driven approach.

Cluster headache (CH) is usually comorbid to mood spectrum disorders, but the psychopathological aspects are poorly explored. We aimed at identifying discrete profiles of personality traits and their association with clinical features. Based on the personality scales of the Millon Clinical Multiaxial Inventory-III, principal component analysis (PCA) identified psychological patterns of functioning of 56 CH patients. PCA outcomes were used for hierarchical cluster analysis (HCA) for sub-groups classification. Eighty-seven percent of patients had personality dysfunctions. PCA found two bipolar patterns: (i) negativistic, sadic-aggressive, borderline, and compulsive traits were distinctive of the psychological dysregulation (PD) dimension, and (ii) narcissistic, histrionic, avoidant, and schizoid traits loaded under the social engagement (SE) component. PD was associated with disease duration and psychopathology. SE was related to educational level and young age. HCA found three groups of patients, and the one with high PD and low SE had the worst psychological profile. Personality disorders are common in CH. Our data-driven approach revealed distinct personality patterns which can appear differently among patients. The worst combination arguing against mental health is low SE and high PD. Linking this information with medical history may help clinicians to identify tailored-based therapeutic interventions for CH patients.

Mild Neurocognitive Disorder, Social Engagement, and Falls Among Older Primary Care Patients

Objectives(1) To estimate the association between social engagement (SE) and falls; (2) To examine the relation between mild neurocognitive disorder (MNCD) and falls by different levels of SE. DesignWe performed a secondary data analysis using prospective cohort study design. SettingPrimary care. ParticipantsA total of 425 older adult primary care patients at risk for mobility decline (N=425). As previously reported, at baseline, 42% of participants exhibit MNCD. Main Outcome MeasuresThe outcome variable was the number of falls during 2 years of follow-up. Exposure variables at baseline included (1) MNCD identified using a cut-off of 1.5 SD below the age-adjusted mean on at least 2 measures within a cognitive performance battery and (2) SE, which was assessed using the social component of the Late-Life Function and Disability Instrument. High SE was defined as having a score ≥ median value (≥49 out of 100). All models were adjusted for age, sex, education, marital status, comorbidities, and pain status. ResultsOver 2 years of follow-up, 48% of participants fell at least once. MNCD was associated with a higher rate of falls, adjusting for the covariates (Incidence Rate Ratio=1.6, 95% confidence interval: 1.1-2.3). There was no significant association between MNCD and the rate of falls among people with high SE. In participants with low SE (having a score less than 49.5 out 100), MNCD was associated with a higher rate of falls as compared with participants with no neurocognitive disorder (No-NCD). ConclusionsAmong participants with low SE, MNCD was associated with a higher rate of falls, but not among participants with high SE. The findings suggest that high SE may be protective against falls among older primary care patients with MNCD.

GEOMETRICAL MODELLING OF RECIDIVISM

Recidivism is engaging in criminal activity again after having previously been involved with the criminal justice system, which continues to pose a severe problem for all civilizations. In order to create successful methods for crime prevention, offender rehabilitation, and community reintegration, it is essential to understand the elements that lead to recidivism. This research was undertaken to investigate the ideas and associates of recidivism. We used the quantitative research design and approached 240 criminals using simple random sampling from the Sahiwal division. We used a structured questionnaire, survey method, and face-to-face interview schedule for data collection. The study explored that lower self-containment, high social engagement, appreciable mental health, history of drug usage, especially marijuana, single marital status, and no religious practices are associated with recidivism. We suggested using the self-containment model to prevent recidivism. Keywords: Geometrical Modeling, Recidivism, Criminal Activities, Criminal Justice System.

Association between social integration and risk of dementia: A systematic review and meta-analysis of longitudinal studies.

Dementia is an emerging public health issue. Growing evidence emerged on the association between social integration and the risk of dementia. However, the magnitude of the association between different aspects of social integration and the risk of dementia is unclear. Five databases were systematically searched. Newcastle-Ottawa scale for assessing the quality of the reporting was used for quality appraisal. Longitudinal cohort studies examining the association between social integration and the risk of dementia were analyzed using random effects model. A series of sensitivity analyses was conducted to enhance the robustness of the findings. Forty publications generated from 32 studies/databases were included. The meta-analysis showed that strong social engagement (overall RR=0.81, 95% CI=0.74-0.89, p < 0.001) and frequent social contact (overall RR=0.86, 95% CI=0.76-0.97, p=0.018) were positively associated with decreased risk of dementia. The influence of social support (overall RR=0.92, 95% CI=0.80-1.06, p=0.238) and close social contact (overall RR=0.74, 95% CI=0.48-1.13, p=0.167) was not significant. Loneliness was significantly associated with an increased risk of dementia (overall RR=1.42, 95% CI=1.26-1.60, p < 0.001), whereas the influence of social isolation (overall RR=1.58, 95% CI=0.80-3.12, p=0.192) was not significant. A larger social network size (RR=0.75, 95% CI=0.59-0.97, p=0.028) was a promising influencing factor even though the number of studies was insufficient for a meta-analysis. However, the heterogeneity among studies was generally high even though sensitivity analysis was conducted. Our findings reveal that high social engagement and frequent social contact are significantly associated with a lower risk of dementia, whereas loneliness is associated with a higher risk. The promising impact of large social network size is also identified. Substantial heterogeneity appeared in most of the analysis, making the inference tentative. Nevertheless, the sensitivity analysis provided valuable implications that enhancing social engagement and reducing loneliness may prevent or delay the onset of dementia among middle-aged and older adults.

Digital cooperation on Facebook and Twitter and financial impact on political crowdfunding campaigns

Although political crowdfunding has been a growing digital tool for resource mobilisation over the last decade, there has been little academic analysis on this topic. To fill this gap, we analysed the impact of digital cooperation materialised through Facebook and Twitter on the financial results and number of individual donations in more than 200 campaigns. Statistical tests show a positive association between the number of endorsements for the dissemination of a campaign message received on Facebook and Twitter from public figures and social and political actors such as associations, trade unions and political parties and the financial results and number of individual donations obtained. In conclusion, we found that digital cooperation improves financial results and allows political crowdfunding campaigners to mitigate the limitations of Facebook and Twitter and to expand their message among new audiences characterised by high social and political engagement.

Mitigating screen time barriers: Lessons from the COVID‐19 pandemic

The COVID‐19 pandemic forced colleges and universities across the country to shift emergently to virtual learning platforms. Health science programs needed to reimagine their curricula and mandatory clinical training under tremendous time pressure. The move to online learning decreased barriers for many students with disabilities, such as the need to traverse campus or high in‐person social engagement. In other circumstances, pandemic‐related shifts created obstacles. In this piece, we highlight some barriers for students with disabilities created by the increase in screen time necessitated by the pandemic, and possible solutions. We identified these barriers and solutions through our work as disability resource professionals for health science programs and as members of the Access in Medicine group, a national collective addressing pandemic‐related changes in medical education. Given the potential for schools to employ increased hybrid and online learning as we move through and beyond the pandemic, we propose individual and Universal Design solutions to mitigate these effects.