Personality of organizational social media accounts and its relationship with characteristics of their photos: analyses of startups' Instagram photos.

BACKGROUND: Organizational accounts of social networking sites (SNSs) are similar to individual accounts in terms of their online behaviors. Thus, they can be investigated from the perspective of personality, as individual accounts have been in the literature. Focusing on startups' Instagram accounts, this study aimed to investigate the characteristics of Big Five personality traits and the relationships between the traits and the characteristics of photos in organizational SNS accounts. METHODS: The personality traits of 108 startups' accounts were assessed with an online artificial intelligence service, and a correspondence analysis was performed to identify the key dimensions where the account were distributed by their personality. Photo features were extracted at the content and pixel levels, and correlational analyses between personality traits and photo features were conducted. Moreover, predictive analyses were performed using random forest regression models. RESULTS: The results indicated that personality of the accounts had high openness, agreeableness, and conscientiousness and moderate extraversion and neuroticism. In addition, the two dimensions of high vs. low in neuroticism and extraversion/openness vs. conscientiousness/agreeableness in the accounts' distribution by their personality traits were identified. Conscientiousness was the trait most associated with photo features-in particular, with content category, pixel-color, and visual features, while agreeableness was the trait least associated with photo features. Neuroticism was mainly correlated with pixel-level features, openness was correlated mainly with pixel-color features, and extraversion was correlated mainly with facial features. The personality traits, except neuroticism, were predicted from the photo features. CONCLUSIONS: This study applied the theoretical lens of personality, which has been mainly used to examine individuals' behaviors, to investigate the SNS communication of startups. Moreover, it focused on the visual communication of organizational accounts, which has not been actively studied in the literature. This study has implications for expanding the realm of personality research to organizational SNS accounts.

Swedish women reaching post-traumatic growth after an intimate partner violence relationship: A study of formal help and growth after trauma.

AIMS: This study examined whether women in Sweden who had been in an intimate partner violence (IPV) relationship reached post-traumatic growth (PTG) and if the level of PTG differed for women who had received formal help compared with women who had not received formal help. The study also examined whether there was a difference in the level of PTG depending on which type of formal help the women had received. METHODS: The data were collected through an online self-report survey. A total of 166 women took part in the study. RESULTS: The results showed that 69.3% (n = 115) of the women reported a pre-determined or higher level of PTG attainment and that those who had received formal help reported a higher level of PTG than those who had not received formal help. There was no difference in the level of PTG depending on which type of formal help the women had received. CONCLUSIONS: The majority of the Swedish women in this study who had lived in an IPV relationship attained PTG. Although formal help appeared to help the women attain PTG, the type of the formal help did not seem to have a crucial role in attaining different levels of PTG. These findings are discussed in the light of the future research directions and public health measures to better support women who experience IPV.

Immediate effects of multimodal cognitive therapy in mild cognitive impairment.

BACKGROUND: Current therapeutic evidence suggests limited efficacy of the cognitive and exercise training in mild cognitive impairment (MCI) on depression, anxiety, memory retention, comprehension, calculation, concentration, orientation, dual-task performance, and sleep disorders. Nevertheless, the immediate effects of multimodal cognitive therapy (MCT) have recently developed and its individual effects remains unknown in MCI. OBJECTIVE: This study aimed to compare the immediate effects of MCT on cognitive and psychological measures between young healthy and older adults with MCI. METHODS: Forty young healthy and older adults with MCI underwent immediate MCT (5 minutes each), including transcranial direct current stimulation (tDCS), light therapy, computerized cognitive therapy (CCT), robotic-assisted gait training (RAGT), core breathing exercises (CBE), and music therapy. Outcome measures included memory retention, comprehension, calculation, attention, orientation, dual-task performance, awareness, depression, anxiety, and sleep disorders. The Mann-Whitney U test and Friedman's test were used at P < 0.05. RESULTS: Significant differences in depression, anxiety, memory retention, comprehension, calculation, attention, orientation, dual-task performance, and awareness were observed between the tDCS, CCT, and music therapy groups (P < 0.05). CONCLUSION: MCT was beneficial for mitigating depression, anxiety, memory retention, comprehension, calculation, attention, orientation, dual-task performance, and awareness.

Bolstering Cognitive and Locomotor Function in Post-Stroke Dementia Using Human-Robotic Interactive Gait Training.

Studies have reported inconclusive results regarding the effectiveness and clinical indications of the exclusive use of human-robotic interactive gait training (HIT) in patients with post-stroke dementia (PSD). This study aimed to compare the effects of human-robotic interactive gait training (HIT) and conventional physiotherapy (CPT) on cognitive and sensorimotor functions, trunk balance and coordination, dynamic and static balance, and activities related to daily living performance in patients with PSD. Forty-eight patients with PSD who received 60-minute therapy sessions three times per week for 6 weeks were assigned to either the CPT (n = 25) or HIT (n = 23) group. The clinical outcomes included the scores of the mini-mental state examination (MMSE), Fugl-Meyer assessment (FMA), trunk impairment scale (TIS), Berg balance scale (BBS), and modified Barthel index (MBI). Friedman tests were conducted at p < 0.05. The Friedman tests showed that HIT had superior effects to CPT in relation to MMSE, FMA, and TIS (p < 0.05), but not in relation to BBS and MBI (p > 0.05). Our results provide promising clinical evidence that HIT significantly improves cognitive and sensorimotor recovery functions, as well as trunk balance and coordination, in patients with PSD who cannot concurrently perform dual cognitive-locomotor tasks.

Effects of Integrative Autism Therapy on Multiple Physical, Sensory, Cognitive, and Social Integration Domains in Children and Adolescents with Autism Spectrum Disorder: A 4-Week Follow-Up Study.

This study aimed to compare the effects of conventional autism therapy (CAT) and integrative autism therapy (IAT) in children and adolescents with autism spectrum disorder (ASD). A convenience sample of 24 children with ASD was recruited and underwent either CAT or IAT for 60 min/day, twice a week, for 20 sessions over 10 weeks. Outcome measures included the following: (1) physical domain (pediatric balance scale, PBS), (2) sensory domain (short sensory profile), (3) cognitive domains (functional independence measure, FIM; and childhood autism rating scale), and (4) social integration domain (Canadian occupational performance measure, COPM; short falls efficacy scale; and pediatrics quality of life questionnaire). Two-way repeated analysis of variance (ANOVA) was used to determine the intervention-related changes in the four domains across the pre-test, post-test, and follow-up test at p < 0.05. ANOVA showed significant interaction effects on the PBS, FIM, and COPM (p < 0.05) variables. Moreover, time main effects (p < 0.05) were observed in all four domain variables, but no group main effect was noted. This study provides promising evidence that IAT is more effective than CAT for managing children and adolescents with ASD.

Personality of nonprofit organizations' Instagram accounts and its relationship with their photos' characteristics at content and pixel levels.

Nonprofit organizations (NPO) can utilize social networking sites (SNSs) for their activities. Like individual users, they can create SNS accounts, upload posts to show what they are doing, and communicate with other users. Thus, their accounts can be investigated from the same perspective of personality which has been one of the key lenses through which SNS posts of individual users was investigated. In the line of literature that analyzed the personality of non-human objects such as products, stores, brands, and websites, the present research analyzed the personality of NPOs' Instagram accounts using an online AI service. Also, it investigated how their personality traits were related to the characteristics of the uploaded photos at content and pixel levels. The results of analysis of 223,446 photos on 177 Instagram accounts suggested that the personality of NPOs' Instagram accounts can be summarized as being high in openness and agreeableness but low in extraversion and neuroticism. And it was found that openness and agreeableness were the personality traits that associated the most with the photo features. Also, the personality traits of NPOs' Instagram accounts, except neuroticism, were predicted from the photo features with an acceptable level of accuracy. Implications of this research and suggestions for further research were presented.

#Nomask on Instagram: Exploring Visual Representations of the Antisocial Norm on Social Media.

Social media (SM) functions such as hashtags and photo uploading can enrich and expedite user interactions, but can also facilitate the online spread of antisocial norms. Mask aversion is one such antisocial norm shared on SM in the current COVID-19 pandemic circumstances. This study utilized the social representation theory (SRT) to explore how mask aversion is visually represented in the Instagram photos tagged with #NoMask. It examined the overall content of the photos, the characteristics of the faces portrayed in the photos, and the presented words in the photos. Additionally, the study grouped the photos through k-means clustering and compared the resulting clusters in terms of content, characteristics of the faces, presented words, pixel-level characteristics, and the public's responses to the photos. The results indicate that people, especially human faces, were visually represented the most in the Instagram photos tagged with #NoMask. Two clusters were generated by k-means clustering-Text-centered and people-centered. The visual representations of the two clusters differed in terms of content characteristics and pixel-level attributes. The texts presented in the photos manifested a unique way of delivering key messages. The photos of the people-centered cluster received more positive comments than the text-centered one; however, the two clusters were not significantly different in eliciting engagement. This study can contribute to expanding the scope of SRT to visual representations and hashtag movements.

Post-Traumatic Growth during COVID-19: The Role of Perceived Social Support, Personality, and Coping Strategies.

Although many studies on mental health have been conducted among various populations during the COVID-19 pandemic, few studies have focused on post-traumatic growth (PTG) in the general population. The current study aimed to explore whether perceived social support, personality, and coping strategies are associated with PTG in the COVID-19 pandemic period. The study also investigated whether coping strategies mediate the relations between perceived social support, personality, and PTG. A total of 181 participants (Mage = 24) completed the self-report questionnaire online, which was distributed via various online channels, mainly in China and Sweden. The relations between the study variables were examined with correlation analyses and a multiple mediation analysis. Results showed that more than half of the participants (60.8%) reported experiences of PTG during the pandemic. Additionally, perceived social support, personality traits (extraversion, emotional stability, agreeableness, and conscientiousness) and coping strategies (problem-focused coping, emotion-focused coping, and social support coping) were positively correlated with PTG. In addition, coping strategies (problem-focused coping, emotion-focused coping, and avoidance coping) mediated the relations between perceived social support, personality traits and PTG. Theoretical and practical implications of this study are discussed, concluding that the findings of this study have the potential to guide intervention efforts to promote positive change during the pandemic.

Exploration of the Relationships Among Narcissism, Life Satisfaction, and Loneliness of Instagram Users and the High- and Low-Level Features of Their Photographs.

We examined the associations between the characteristics of Instagram users and the features of their photographs. Narcissism, life satisfaction, and loneliness were employed for user variables and the features at high- (content) and low-levels (pixel) were employed to analyze the Instagram photographs. An online survey was conducted with 179 university students, and their Instagram photographs, 25,394 in total, were collected and analyzed. High-level features were extracted using Computer Vision and Emotion Application Programming Interfaces (APIs) in Microsoft Azure Cognitive Services, and low-level features were extracted utilizing the program written by the authors. The results of correlation analysis indicate that narcissism, life satisfaction, and loneliness were significantly associated with a part of photograph features at high- and low-levels. The results of the predictive analysis suggest that narcissism, loneliness in total, and social loneliness could be predicted with acceptable accuracy from Instagram photograph features, while characteristics such as life satisfaction, family loneliness, and romantic loneliness could not be predicted. Implications of this research and suggestions for further research were presented.

A Framework-Based Approach to Assessing Mental Health Impacts of the COVID-19 Pandemic on Children and Adolescents.

The COVID-19 pandemic has yielded extensive impacts globally in the year of 2020. Although the mental health of children and adolescents may be particularly susceptible to stressors stemming from the pandemic and anti-contagion policies, most ongoing efforts are geared toward curbing the viral spread. In the current perspective, we have identified four domains of factors corresponding to an ecological framework that may directly or indirectly influence the mental health of children and adolescents during the pandemic. The evidence suggests that anti-contagion policies might trigger cascades that impact the mental health of children and their families through multiple different sectors that used to form a safety net for youths. Additionally, children with neuropsychiatric disorders could experience exacerbated symptoms during the pandemic. Furthermore, the risk of domestic violence has surged during the pandemic, which further compounds the imminent mental health crisis. A mental health pandemic could be inevitable if no proactive prevention strategies were in place. Therefore, we recommend understanding each individual mental health risk pathway via the ecological framework in order to develop integrative prevention and intervention strategies.

Effectiveness of Intervention Strategies on MERS-CoV Transmission Dynamics in South Korea, 2015: Simulations on the Network Based on the Real-World Contact Data.

The MERS-CoV spread in South Korea in 2015 was not only the largest outbreak of MERS-CoV in the region other than the Middle East but also a historic epidemic in South Korea. Thus, investigation of the MERS-CoV transmission dynamics, especially by agent-based modeling, would be meaningful for devising intervention strategies for novel infectious diseases. In this study, an agent-based model on MERS-CoV transmission in South Korea in 2015 was built and analyzed. The prominent characteristic of this model was that it built the simulation environment based on the real-world contact tracing network, which can be characterized as being scale-free. In the simulations, we explored the effectiveness of three possible intervention scenarios; mass quarantine, isolation, and isolation combined with acquaintance quarantine. The differences in MERS-CoV transmission dynamics by the number of links of the index case agent were examined. The simulation results indicate that isolation combined with acquaintance quarantine is more effective than others, and they also suggest the key role of super-spreaders in MERS-CoV transmission.

Personality of Public Health Organizations' Instagram Accounts and According Differences in Photos at Content and Pixel Levels.

Organizations maintain social media accounts and upload posts to show their activities and communicate with the public, as individual users do. Thus, organizations' social media accounts can be examined from the same perspective of that of individual users' accounts, with personality being one of the perspectives. In line with previous studies that analyzed the personality of non-human objects such as products, stores, brands, and websites, this study analyzed the personality of Instagram accounts of public health organizations. It also extracted features at content and pixel levels from the photos uploaded on the organizations' accounts and examined how they were related to the personality traits of the accounts. The results suggested that the personality of public health organizations can be summarized as being high in openness and agreeableness but lower in extraversion and neuroticism. Openness and agreeableness were the personality traits associated the most with the content-level features, while extraversion and neuroticism were the ones associated the most with the pixel-level features. In addition, for each of the two traits associated the most with either the content- or pixel- level features, their associations tended to be in opposite directions with one another. The personality traits, except for neuroticism, were predicted from the photo features with an acceptable level of accuracy.

#Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses.

A dramatic increase has been registered in the number of social media posts in photo form as well as in hashtag activism. Hashtags, which manifest thoughts and feelings clearly and concisely, originated on Twitter, where the length of a post is limited; their use, however, has expanded into other social media services, including Instagram. Hashtags, which make it easy to find and express support for posts of interest, have been widely used for online activism, although they have been criticized for fostering confirmation bias. Moreover, hashtag activism in photo form has been relatively understudied. This research analyzed Instagram photos with antivaccination hashtags as an example of hashtag activism through photos. In addition, we examined how the photo features were related to public response, which was manifested via engagement and comment sentiment. The results suggest that the photos which were categorized into "text" took the largest share. It was also found that the major way of claiming was to imprint key messages that persuade people not to vaccinate with remarks from professionals on photos and provide a source of supporting information in the post text with hashtags of antivaccine intention. Various photo features showed associations with engagement and comment sentiment, but the directions of correlation were usually the opposite: these results suggest that engagement and comment sentiment are separate domains that reveal different public responses.

Modeling influenza transmission dynamics with media coverage data of the 2009 H1N1 outbreak in Korea.

Recurrent outbreaks of the influenza virus continue to pose a serious health threat all over the world. The role of mass media becomes increasingly important in modeling infectious disease transmission dynamics since it can provide public health information that influences risk perception and health behaviors. Motivated by the recent 2009 H1N1 influenza pandemic outbreak in South Korea, a mathematical model has been developed. In this work, a previous influenza transmission model is modified by incorporating two distinct media effect terms in the transmission rate function; (1) a theory-based media effect term is defined as a function of the number of infected people and its rage of change and (2) a data-based media effect term employs the real-world media coverage data during the same period of the 2009 influenza outbreak. The transmission rate and the media parameters are estimated through the least-squares fitting of the influenza model with two media effect terms to the 2009 H1N1 cumulative number of confirmed cases. The impacts of media effect terms are investigated in terms of incidence and cumulative incidence. Our results highlight that the theory-based and data-based media effect terms have almost the same influence on the influenza dynamics under the parameters obtained in this study. Numerical simulations suggest that the media can have a positive influence on influenza dynamics; more media coverage leads to a reduced peak size and final epidemic size of influenza.

Classroom Disorder and Internalizing Problems Among Swedish Adolescents: Changes Between 1988 and 2011.

BACKGROUND: Internalizing problems have increased among Swedish adolescents. We examined whether classroom disorder was associated with internalizing problems and whether it explained the trends in internalizing problems. Furthermore, we examined whether school contextual factors were associated with internalizing problems and whether they moderated the association between classroom disorder and internalizing problems. METHODS: We used repeated cross-sectional survey data (1988-2011) among all 15- to 16-year-old students in Värmland, Sweden (N = 9491 boys, N = 9313 girls). School-level factors were the proportions of students with a low/average socioeconomic or an immigration background. RESULTS: Results from mixed effects models showed that classroom disorder was associated with internalizing problems across the years of investigation but did not explain the trends in internalizing problems. This association was moderated by the school-level proportion of students with a low/average socioeconomic background but not the school-level proportion of students with an immigration background. CONCLUSIONS: Students who perceived their classroom to be disorderly more often also reported more internalizing problems. Future studies are necessary to investigate other potential school factors that may explain the trends in internalizing problems.

A latent class analysis of changes in adolescent substance use between 1988 and 2011 in Sweden: associations with sex and psychosomatic problems.

AIMS: To characterize changes in patterns of adolescent substance use in Sweden between 1988 and 2011, and to assess whether sex and psychosomatic problems were associated with substance use and whether these associations changed over time. DESIGN: Secondary analysis of repeated cross-sectional survey data. Survey data were collected eight times and analyzed as four cohorts (1988-91, 1995-98, 2002-05 and 2008-11). SETTING AND PARTICIPANTS: The sample included all 15-16-year-olds in Värmland County, Sweden (n = 20 057). MEASUREMENTS: Binary-coded substance use measures included life-time use of alcohol and tobacco, getting drunk and past school year use of inhalants. An eight-item scale was used to assess psychosomatic problems. FINDINGS: A three-class model fitted the data best (i.e. non/low use, mainly alcohol use and polysubstance use). The patterns of substance use were different among cohorts; most notably, adolescents in the last cohort had lower odds of being included in the alcohol and polysubstance use classes rather than the non/low use class than in the earlier cohorts (all Ps < 0.001). Males had higher odds than females of being in the polysubstance use class rather than the non/low use class among the first three cohorts (all Ps < 0.001) but not the last. Sex was not associated with inclusion in the alcohol use class rather than the non/low use class. Adolescents who reported more psychosomatic problems had higher odds of being included in the alcohol and polysubstance use classes rather than the non/low use class (all Ps < 0.001). The associations of sex and psychosomatic problems with class inclusion did not change during the study period. CONCLUSIONS: Between 1988 and 2011, patterns of substance use among adolescents in Sweden shifted away from polysubstance use and alcohol use to non-use or low use. Associations between patterns of substance use and sex and psychosomatic problems remained largely consistent across the study period.

Using photos for public health communication: A computational analysis of the Centers for Disease Control and Prevention Instagram photos and public responses.

This study aims to explore the use of Instagram by the Centers for Disease Control and Prevention, one of the representative public health authorities in the United States. For this aim, all of the photos uploaded on the Centers for Disease Control and Prevention Instagram account were crawled and the content of them were analyzed using Microsoft Azure Cognitive Services. Also, engagement was measured by the sum of numbers of likes and comments to each photo, and sentiment analysis of comments was conducted. Results suggest that the photos that can be categorized into "text" and "people" took the largest share in the Centers for Disease Control and Prevention Instagram photos. And it was found that the Centers for Disease Control and Prevention's major way of delivering messages on Instagram was to imprint key messages that call for actions for better health on photos and to provide the source of complementary information on text component of each post. It was also found that photos with more and bigger human faces had lower level of engagement than the others, and happiness and neutral emotions expressed on the faces in photos were negatively associated with engagement. The features whose high value would make the photos look splendid and gaudy were negatively correlated with engagement, but sharpness was positively correlated.

Mental Health Problems Among Adolescents in Sweden from 1995 to 2011: The Role of Immigrant Status and the Proportions of Immigrant Adolescents in Their Surrounding Community.

We compared the mental health of native and immigrant adolescents in Sweden from 1995 to 2011 and examined whether the municipality-level proportion of immigrant adolescents moderated the association between individual-level immigrant status and mental health. The sample (14,189 adolescents aged 15-16) was obtained from a repeated cross-sectional study conducted from 1995 to 2011. Adolescent self-report data (gender, immigrant status, economic situation, and mental health) and municipality-level data (proportion of immigrant adolescents) were used in multilevel linear regression analyses. Immigrant adolescents reported more mental health problems than their native Swedish peers. The long-term trend in mental health problems did not differ between the two groups. The association between individual immigrant status and mental health did not differ according to the municipality-level rate of immigrant adolescents. These findings highlight the need for public health attention to and efforts to address immigrant adolescents' mental health problems in Sweden.

Towards explaining time trends in adolescents' alcohol use: a multilevel analysis of Swedish data from 1988 to 2011.

BACKGROUND: Alcohol use has decreased among Swedish adolescents in the past few decades. We examined peer and parent factors (i.e. time spent with peers, time spent with parents and parental monitoring) that could contribute to explaining this trend by investigating their main effects and interaction effects with investigation years on alcohol use. We furthermore examined whether municipality-level socioeconomic conditions could contribute to explaining the trend. METHODS: We used data from a repeated cross-sectional study that took place eight times between 1988 and 2011. The study targeted all ninth grade students (15-16 years old) in Värmland County, Sweden. Adolescents (N = 22 257) reported their monthly alcohol use, time spent with peers and parents and parental monitoring. Municipality-level socioeconomic conditions were based on parent education levels. RESULTS: Logistic multilevel regression analyses showed that peer and parent factors and municipality-level socioeconomic conditions were associated with alcohol use among adolescents. The interaction effects between peer and parent factors and investigation years were not significant. The decreased trend in time spent with peers was associated with the decreased trend in frequency of alcohol use over time. CONCLUSIONS: The findings of the current study provide an indication that the decreased trend in alcohol use that has been observed in Swedish adolescents over the past few decades may be related to changes in adolescents' social interactions with peers.

Agent-Based Modeling for Super-Spreading Events: A Case Study of MERS-CoV Transmission Dynamics in the Republic of Korea.

Super-spreading events have been observed in the transmission dynamics of many infectious diseases. The 2015 MERS-CoV outbreak in the Republic of Korea has also shown super-spreading events with a significantly high level of heterogeneity in generating secondary cases. It becomes critical to understand the mechanism for this high level of heterogeneity to develop effective intervention strategies and preventive plans for future emerging infectious diseases. In this regard, agent-based modeling is a useful tool for incorporating individual heterogeneity into the epidemic model. In the present work, a stochastic agent-based framework is developed in order to understand the underlying mechanism of heterogeneity. Clinical (i.e., an infectivity level) and social or environmental (i.e., a contact level) heterogeneity are modeled. These factors are incorporated in the transmission rate functions under assumptions that super-spreaders have stronger transmission and/or higher links. Our agent-based model has employed real MERS-CoV epidemic features based on the 2015 MERS-CoV epidemiological data. Monte Carlo simulations are carried out under various epidemic scenarios. Our findings highlight the roles of super-spreaders in a high level of heterogeneity, underscoring that the number of contacts combined with a higher level of infectivity are the most critical factors for substantial heterogeneity in generating secondary cases of the 2015 MERS-CoV transmission.