Longitudinal development of well-being among Finnish employees during 2019-2021: Relationships with personality trait profiles

We examined well-being profiles among Finnish employees before and during the COVID-19 pandemic and their links with personality trait profiles. Longitudinal survey data were collected in 2019-2021, and 733 respondents participated in all five surveys. The data were analyzed with a person-centered approach using latent profile analysis (LPA). Measures included burnout, work engagement, psychological distress; and Big Five personality traits. Six well-being profiles: Disengaged, Declined, Engaged, Fluctuated, Stable, and Burned-out, and four personality profiles: Ordinary, Reserved, Resilient, and Overcontrolled were identified. Resilient participants typically belonged to the Engaged well-being profile and Reserved to Burned-out and Fluctuated well-being profiles. Although some separation in developmental well-being profiles existed, overall, well-being was rather stable. Personality trait profiles played a crucial role in maintaining well-being.

Advancing residents' use of shared spaces in Nordic superblocks with intelligent technologies

To support the sustainability of future cities, residents' living spaces need to be built and used efficiently, while supporting residents' communal wellbeing. Nordic superblock is a new planning, housing, and living concept in which residents of a neighborhood-a combination of city blocks-share yards, common spaces and utilities. Sharing living spaces is an essential element of this approach. In this study, our goal was to study the ways in which intelligent technology solutions-such as proactive, data-driven Artificial Intelligence (AI) applications-could support and even motivate the use of common areas in superblocks. To this end, we conducted a two-phase qualitative study: in the first phase, potential superblock residents (N = 12) shared their perspectives of sharing of living spaces in general, and more specifically of how intelligent technologies could support sharing spaces. In the second phase, two workshops with experts (N = 7) were held to gather understanding of possibilities of intelligent technologies in meeting the residents' expectations of space sharing. The results illustrate space sharing and communality as supportive factors for one another, enabled but also complicated by social interaction. Major possibilities for intelligent technologies to advance space sharing were seen in organizing the use of spaces and facilitating social interaction in the community. As an outcome, four roles incorporating several use purposes of intelligent technologies were found. The findings can inform the Human-Centered AI (HCAI) research and design improving sustainable living in future urban neighborhoods.

Affective Attitudes Toward Robots at Work: A Population-Wide Four-Wave Survey Study

Robotization of work is progressing fast globally, and the process has accelerated during the COVID-19 pandemic. Utilizing integrated threat theory as a theoretical framework, this study investigated affective attitudes toward introducing robots at work using a four timepoint data (n = 830) from a Finnish working population longitudinal study. We used hybrid multilevel linear regression modelling to study within and between participant effects over time. Participants were more positive toward introducing robots at work during the COVID-19 pandemic than before it. Increased cynicism toward individuals’ own work, robot-use self-efficacy, and prior user experiences with robots predicted positivity toward introducing robots at work over time. Workers with higher perceived professional efficacy were less and those with higher perceived technology-use productivity, robot-use self-efficacy, and prior user experiences with robots were more positive toward introducing robots at work. In addition, the affective attitudes of men, introverts, critical personalities, workers in science and technology fields, and high-income earners were more positive. Robotization of work life is influenced by workers’ psychological well-being factors and perceived as a welcomed change in the social distancing reality of the pandemic.

Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions

As an inevitable process, the number of older adults is increasing in many countries worldwide. Two of the main problems that society is being confronted with more and more, in this respect, are the inter-related aspects of feelings of loneliness and social isolation among older adults. In particular, the ongoing COVID-19 crisis and its associated restrictions have exacerbated the loneliness and social-isolation problems. This paper is first and foremost a comprehensive survey of loneliness monitoring and management solutions, from the multidisciplinary perspective of technology, gerontology, socio-psychology, and urban built environment. In addition, our paper also investigates machine learning-based technological solutions with wearable-sensor data, suitable to measure, monitor, manage, and/or diminish the levels of loneliness and social isolation, when one also considers the constraints and characteristics coming from social science, gerontology, and architecture/urban built environments points of view. Compared to the existing state of the art, our work is unique from the cross-disciplinary point of view, because our authors' team combines the expertise from four distinct domains, i.e., gerontology, social psychology, architecture, and wireless technology in addressing the two inter-related problems of loneliness and social isolation in older adults. This work combines a cross-disciplinary survey of the literature in the four aforementioned domains with a proposed wearable-based technological solution, introduced first as a generic framework and, then, exemplified through a simple proof of concept with dummy data. As the main findings, we provide a comprehensive view on challenges and solutions in utilizing various technologies, particularly those carried by users, also known as wearables, to measure, manage, and/or diminish the social isolation and the perceived loneliness among older adults. In addition, we also summarize the identified solutions which can be used for measuring and monitoring various loneliness- and social isolation-related metrics, and we present and validate, through a simple proof-of-concept mechanism, an approach based on machine learning for predicting and estimating loneliness levels. Open research issues in this field are also discussed.

Older Adults' Loneliness, Social Isolation, and Physical Information and Communication Technology in the Era of Ambient Assisted Living: A Systematic Literature Review

BACKGROUND

Loneliness and social isolation can have severe effects on human health and well-being. Partial solutions to combat these circumstances in demographically aging societies have been sought from the field of information and communication technology (ICT).

OBJECTIVE

This systematic literature review investigates the research conducted on older adults' loneliness and social isolation, and physical ICTs, namely robots, wearables, and smart homes, in the era of ambient assisted living (AAL). The aim is to gain insight into how technology can help overcome loneliness and social isolation other than by fostering social communication with people and what the main open-ended challenges according to the reviewed studies are.

METHODS

The data were collected from 7 bibliographic databases. A preliminary search resulted in 1271 entries that were screened based on predefined inclusion criteria. The characteristics of the selected studies were coded, and the results were summarized to answer our research questions.

RESULTS

The final data set consisted of 23 empirical studies. We found out that ICT solutions such as smart homes can help detect and predict loneliness and social isolation, and technologies such as robotic pets and some other social robots can help alleviate loneliness to some extent. The main open-ended challenges across studies relate to the need for more robust study samples and study designs. Further, the reviewed studies report technology- and topic-specific open-ended challenges.

CONCLUSIONS

Technology can help assess older adults' loneliness and social isolation, and alleviate loneliness without direct interaction with other people. The results are highly relevant in the COVID-19 era, where various social restrictions have been introduced all over the world, and the amount of research literature in this regard has increased recently.

Loneliness and psychological distress before and during the COVID-19 pandemic: Relationships with social media identity bubbles

Impacts of the COVID-19 pandemic on well-being and mental health are a concern worldwide. This article is based on two longitudinal studies that investigated the role of social media use in loneliness and psychological distress before and during the COVID-19 pandemic. Study 1 utilized nationally representative 3-point longitudinal data (n = 735) collected in 2017–2020 on the Finnish population. Study 2 utilized 5-point longitudinal data (n = 840) collected in 2019–2021 representing the Finnish working population. We analyzed the data using multilevel mixed-effects regression analysis. A longitudinal analysis of Study 1 showed that perceived loneliness did not increase among the Finnish population during the COVID-19 pandemic. Stronger involvement in social media identity bubbles predicted lower loneliness during the pandemic. Study 2 results showed that since the outbreak of the pandemic, psychological distress has increased among lonely individuals but not among the general working population. Involvement in social media identity bubbles predicted generally lower psychological distress during the COVID-19 pandemic, but it did not buffer against higher psychological distress among lonely individuals. The findings suggest that perceived loneliness is a risk factor for prolonged negative mental health effects of the pandemic. Social media identity bubbles can offer meaningful social resources during times of social distancing but cannot protect against higher psychological distress among those who perceive themselves as often lonely.

Hate and harassment in academia: the rising concern of the online environment

Hostile online communication is a global concern. Academic research and teaching staff are among those professionals who routinely give public comments and are thus vulnerable to online attacks. This social psychological and criminological study investigated online harassment victimization among university researchers and teachers. Survey participants (N = 2,492) were university research and teaching staff members from five major universities in Finland. Victimization was assessed with a 20-item inventory. The study included a wide range of both background and general measures on well-being at work. Participants also took part in an online experiment involving a death threat targeting a colleague. Results showed that 30% of the participants reported being victims of online harassment during the prior 6 months. Victims were more often senior staff members, minority group members, and from the social sciences and humanities. Those active in traditional or social media were much more likely to be targeted. Victims reported higher psychological distress, lower generalized trust, and lower perceived social support at work than non-victims. Individuals who were targeted by a colleague from their work community reported higher post-traumatic stress disorder scores and a higher impact of perceived online harassment on their work compared to other victims. In the experimental part of the study, participants reported more anxiety when a close colleague received a death threat. Participants also recommended more countermeasures to a close colleague than to an unknown person from the same research field. Results indicate that online harassment compromises well-being at work in academia. There is an urgent need to find ways of preventing online harassment, both in workplaces and in society at large.

Trust Toward Robots and Artificial Intelligence: An Experimental Approach to Human-Technology Interactions Online

Robotization and artificial intelligence (AI) are expected to change societies profoundly. Trust is an important factor of human-technology interactions, as robots and AI increasingly contribute to tasks previously handled by humans. Currently, there is a need for studies investigating trust toward AI and robots, especially in first-encounter meetings. This article reports findings from a study investigating trust toward robots and AI in an online trust game experiment. The trust game manipulated the hypothetical opponents that were described as either AI or robots. These were compared with control group opponents using only a human name or a nickname. Participants (N = 1077) lived in the United States. Describing opponents with robots or AI did not impact participants' trust toward them. The robot called jdrx894 was the most trusted opponent. Opponents named "jdrx894" were trusted more than opponents called "Michael." Further analysis showed that having a degree in technology or engineering, exposure to robots online and robot use self-efficacy predicted higher trust toward robots and AI. Out of Big Five personality characteristics, openness to experience predicted higher trust, and conscientiousness predicted lower trust. Results suggest trust on robots and AI is contextual and it is also dependent on individual differences and knowledge on technology.

Regulation and Trust: 3-Month Follow-up Study on COVID-19 Mortality in 25 European Countries

BACKGROUND

The outbreak of the coronavirus disease (COVID-19) has dramatically changed societies in 2020. Since the end of February, Europe has been hit particularly hard by COVID-19, but there are major country differences in both the spread of the virus and measures taken to stop the virus. Social psychological factors such as institutional trust could be important in understanding the development of the epidemic.

OBJECTIVE

The aim of this study was to examine country variations of COVID-19 mortality in Europe by analyzing social risk factors explaining the spread of the disease, restrictions and control measures, and institutional trust.

METHODS

The present study was based on a background analysis of European Social Survey data on 25 European countries (N=47,802). Multilevel mixed effects linear regression models focused on 84 days of the COVID-19 epidemic (January 22 to April 14, 2020) and modelled the daily COVID-19 mortality. Analysis focused on the impact of social relations, restrictions, and institutional trust within each country.

RESULTS

The spread of the COVID-19 epidemic has been fast everywhere, but the findings revealed significant differences between countries in COVID-19 mortality. Perceived sociability predicted higher COVID-19 mortality. Major differences between the 25 countries were found in reaction times to the crisis. Late reaction to the crisis predicted later mortality figures. Institutional trust was associated with lower COVID-19 mortality.

CONCLUSIONS

The analyses demonstrated the importance of societal and social psychological factors in the spread of the COVID-19 epidemic. By considering multiple perspectives, this study showed that country differences in Europe are major, and this will have an impact on how countries will cope with the ongoing crisis in the following months. The results indicated the importance of timely restrictions and cooperation with people.