Lockdown locomotion: the fast-forwarding effects of technology use on digital well-being due to COVID-19 restrictions

ABSTRACT

Increasing dependency on digital technologies introduces queries related to well-being–when and how digital technology poses a threat, or when it is the most appreciated by users? People have some expectations before using technology, which sometimes may be met, but there might be a mismatch at other times. Nevertheless, the digitalization of services advances and companies modify existing or produce new technologies that do not satisfy users' demands, putting their well-being at risk. Through an empirical inquiry, the present research explores experiences with technologies to shed more light on the main factors that enrich or diminish technology value and influence well-being. Exploiting the circumstances created by the COVID-19 pandemic that fast-forwarded technology use and development, an online inquiry was conducted to assess positive and negative experiences of technologies, focusing on the contexts of work, learning, entertainment, information-seeking, and health. The findings from 578 participants indicate that depending on the role of technologybeing a substitute for certain activities or an opportunity to perform them differently–consequences on well-being can more or less follow expectations. The results are discussed in the context of past research and practical implications for, e.g. technology design or managerial changes that could help overcome users' current challenges.

1. Introduction

Digitization has enabled many digitalised trends and processes toward achieving economic growth. Moreover, we are in the fourth industrial revolution and thus experience the effects of the rapid development of technologies and changes influencing societies. Digital transformation is imperative for businesses' strategic success (Fitzgerald et al. 2014); therefore, we notice the continuous innovative digitalization of products and services. Digital transformation can be defined as ‘the profound and accelerating transformation of business activities, processes, competencies, and models to fully leverage the changes and opportunities brought by digital technologies and their impact across society in a strategic and prioritised way’ (Demirkan, Spohrer, and Welser 2016, p. 14).

The digital transformation process has been fast-forwarded from December 2019, when the first coronavirus disease (COVID-19) case was identified. Rapidly spreading worldwide, the virus has been classified as a global pandemic. Most countries implemented measures to control the disease, including strict lockdowns and restrictions, aiming to stop people from spreading the virus physically. These measures highly affected people's lives, impacting different activities, including socializing, work, and education. Simultaneously, they provided a space for identifying and swiftly implementing new solutions that could help people adjust to new realities. Often such solutions relied on digital technologies, rapidly advancing digitalization. For instance, different communication platforms were utilised or newly developed to maintain contact with other people, work, and participate in school. Similarly, different digital services use has dramatically increased to minimise contact with others in the context of leisure-related activities (e.g. food delivery, entertainment), home-related tasks (e.g. e-commerce), or health care (e.g. telemedicine).

Although most technological solutions existed before the pandemic, the ongoing crisis highly increased the reliance on such solutions. Digital technology had almost an invasive effect on people's lives, as frequently, they could not do anything else. The borders between physical and digital have been blurred by transposing physical activities (e.g. meeting friends) into the digital space. Such changes and extensive reliance on digital technology affect people's well-being. In the present research, we use the circumstance created by the pandemic to investigate people's experiences with technology within this heavily socially-restricted time. We investigate people's experiences to gain insights into the relationship between digital technology and well-being.

Well-being can be defined as ‘a state of persons which designates that they are happy or flourishing and that their life is going well for them,’ and it might be perceived as the highest of values, even as encompassing other values (Brey 2015 , p. 2). Digital well-being is an impact that digital technologies might have on a human in the context of the information society, on how good life is Burr, Taddeo, and Floridi (2020). It concerns the affective state of an individual (e.g. emotions), domain satisfaction (e.g. relationships), and life satisfaction in the context of the social environment and use of digital media (Büchi 2021). Vanden Abeele proposed a definition of digital well-being in the context of mobile technology as

‘a subjective individual experience of optimal balance between the benefits and drawbacks obtained from mobile connectivity. This experiential state is comprised of affective and cognitive appraisals of the integration of digital connectivity into ordinary life. People achieve digital well-being when experiencing maximal controlled pleasure and functional support, together with minimal loss of control and functional impairment’ (Vanden Abeele 2021, p. 938).

The present research leans towards the latter definition, beyond mobile connectivity, and considers both technology's negative and positive effects on well-being. Moreover, due to the close relationship between well-being and human values, and the user-focused nature of the study, the present research considers categories of user values, as proposed by Boztepe (2007). These include utility (convenience, quality & performance, economy), social significance (social prestige, identity), emotional (pleasure, sentimentality), and spiritual categories.

Digital well-being is concerned with self-control, and researchers often recommend digital detox to maintain it Brown and Kuss (2020). Online services add well-being features to their systems, and researchers propose independent tools to help people maintain self-control (Lyngs et al. 2019, Roffarello and Russis 2021). Simultaneously, some recognise that self-control-based solutions are insufficient (Cecchinato et al. 2019). Research suggests that, particularly in the multi-device environment, the traditional lock-out design of applications that are supposed to help maintain well-being is no longer satisfactory (Roffarello and Russis 2021). Although the present research does not directly investigate design for well-being, it adds to the field through knowledge about people's needs and preferences during their extensive use of technology. The findings about positive and negative experiences with technology extend beyond design's problematics to infrastructural changes (both in the context of technology practicalities and managerial aspects of work, education, and similar).

Burr, Taddeo, and Floridi (2020), reviewing research on ethics of digital well-being, identified social domains where digital well-being is particularly relevant: health and healthcare (both mental and physical), education and employment, governance and social development, media and entertainment (including, e.g. self-understanding, social relatedness, use of social media). In an exploratory study, Alaqra and Kitkowska (2021) found that the use of technology in contexts similar to these domains (work, entertainment, information, health, and communication) significantly changed during the COVID-19 pandemic, and it was associated with various internal factors (e.g. loneliness). Moreover, their qualitative results hinted that people's experiences with technologies had different effects, such as beneficial opportunities, concerns, or behavioral changes.

Considering the social dimensions described by Burr, Taddeo, and Floridi (2020) and drawing on findings from Alaqra and Kitkowska (2021), this article investigates the use of technology in five different contexts: work and education, health, entertainment, information seeking, and social interaction. This research takes an opportunity to evaluate the use of technology during a crisis, such as the global pandemic since it highly influences how people interact with technology. The research identifies potential barriers to technology acceptance by focusing on positive and negative technological experiences. In particular, the hindrances of psychological (e.g. emotions) or physical (e.g. physical health, technology practicalities) nature are discussed. The article also provides an overview of potential relationships between different psychological constructs (loneliness, ability to cope, ability to bounce back, and life satisfaction) and the use of technology.

2. Related work

Past research investigated the use of technology in times of crisis, mainly how technology use altered. This section presents examples of such research, focusing on the five dimensions of technology studied in the present article: work and education, health, socializing, entertainment, and information seeking.

2.1. Work and education

Global crises, such as the COVID-19 pandemic, force some people to work or study from home. They must rely on technology to perform daily tasks, communicate with others, and more. Kniffin et al. (2021) describe the impacts of a pandemic on work-related activities. In particular, changes that it causes in work practises (e.g. working from home, virtual team activities, virtual leadership) and changes in individual workers (e.g. distancing, loneliness, mental well-being, unemployment).

Working from home (WFH) is one such change, but it can be challenging for some workers. People may struggle with boundaries between work and home, e.g. due to the lack of commuting (Kniffin et al. 2021). Moreover, other WFH-related issues may arise, such as employers' surveillance and privacy violations, e.g. omnipresent oversight and checks of employees' performance.

With the blurry work-non-work boundaries, some research shows that digital work connectivity can be associated with withdrawal behaviors (Chadee, Ren, and Tang 2021). Employees might need a break or try to reduce stress or similar. Research on remote work during pandemic on desk workers implies that working from home reducing the in-person interactions has both positive (e.g. workers giving more attention to their well-being) and negative (e.g. increased screen time) effects (Gibbs et al. 2021). While being at home had negative associations with health, e.g. worse sleeping habits, frequent mood swings, and reduced work health, WFH does not worsen health behaviors or well-being. Remote workers (working all the time remotely) are more negatively affected by the pandemic (more significant decline related to physical activities and a higher stress level) than by working from home (Gibbs et al. 2021).

Learning from home through technological means introduces problems similar to WFH. For instance, the blurry boundary between study and life or difficulties related to collaborative learning (Chen et al. 2021). Technology's role is crucial when educational institutions are closed to diminish interruption, maintain student-teacher relationships, and more (Onyema et al. 2020). However, it might be problematic, as there is often a lack of adequate infrastructure to ensure distance education. Similarly, not all students are equipped with the technologies required for such an education.

2.2. Health

The use of technology can have an overall positive effect on health improvement. In applications, wearable-mobile devices or assistive devices, technologies have been developed to promote health and well-being. Benefits to the health and well-being of users as a result of using assistive technologies have been reported (Balasubramanian, Beaney, and Chambers 2021).

Similarly, literature reviews show that technology can be used to diminish the detrimental effects that crises might have on mental health. For instance, telemedicine, video-conferencing, or in-house platforms could be used to assist in providing mental support, e.g. providing safe space to the affected person (Strudwick et al. 2021, Vargo et al. 2021). Similarly, such platforms can transform traditional healthcare delivery, enabling diagnosis and doctor-patient consultations online.

Mobile health applications vary and are used to promote a better quality of life and healthier lifestyles for different target groups of the population, e.g. using smartphone apps to promote healthier dietary behaviors for pregnant women suffering from obesity (Sandborg et al. 2021). Smartphone interventions can be used to monitor and aid in people's health; positive effects are reported to be blood pressure reduction and an increase in medication adherence for the case of people with hypertension (Xu and Long 2020). Like web-based solutions, mobile devices provide an opportunity for mental health care, which can be customised to the needs of an individual.

Mobile phone stores offer a plethora of health and well-being applications. While the reports show that health-related apps during the COVID-19 pandemic were globally downloaded more in 2020 than in 2019–Medical apps 66% more and Health & Fitness apps 50% more (Sensor Tower 2020) – there are still issues with such technologies. Despite the growing numbers of health-related applications available through mobile app stores, the researchers warn that their design often lacks scientific backing (Figueroa and Aguilera 2020), which might result in adverse effects on well-being.

2.3. Entertainment

Reports show that the entertainment services providing online video content, such as Netflix or Amazon Video, during the first year of the COVID-19 pandemic grew numbers of new consumers, with Netflix's record number of 28 million new users (Cook 2021). Even more significant increase was observed in services and mobile applications that offer live streaming or independent content creation. For instance, TikTok was globally the top downloaded mobile application (Sensor Tower 2020). Streaming platforms can also assist with physical activities. One study shows that among people who used digital platforms as physical activity assistants, about 40% of respondents (adults and adolescents) most commonly used streaming services (Parker et al. 2021).

Further, online streaming services, especially those that enable live streaming, could be used to maintain the connection with pre-crisis communities and enable the maintenance of behaviors that people had in the past (Garfin 2020). Live streaming services might help replace types of entertainment based on passive participation (e.g. religious masses). For instance, streaming certain ceremonies, e.g. funerals and masses, enables people to ‘participate,’ although only virtually. Still, it is unlikely that such digital participation substitute experiences of socially engaging events rich in physical interactions. Research shows that, for instance, in the case of music concerts, people tend to enjoy the online live stream and try to mimic some of the typical interactions, e.g. through live commenting and the use of signals such as emoji (Vandenberg, Berghman, and Schaap 2021). Despite their findings showing that live-streamed music successfully brings the live events home, most of the comments accompanying the live streams have a lamentation-like tone. People express a longing for joint participation and activities that might only be experienced when participating in music events in person.

2.4. Socializing and technology

Some studies show that even before the pandemic started, people spent less time in person with others than they did in the past, especially considering relationships with relatives and/or friends (Brown and Greenfield 2021). This is particularly visible among people from different age groups, e.g. youngsters with less freedom to see their friends, young adults leaving their hometowns early, and the decreasing number of multi-generational housing. Some work shows that youngsters are using online channels to spend time with their friends on the days when in-person meetings are not possible (Manago et al. 2019).

The early empirical findings of the use of technology during the COVID-19 pandemic suggest a significant increase in the use of online technologies in different contexts (Brown and Greenfield 2021, Alaqra and Kitkowska 2021). To maintain contact with others, people, especially those residing in the geographic areas that enforced the stay-in-home approach, have adapted to the new situation via the utilization of different communication technologies (Brown and Greenfield 2021). To some extent, such online technologies may replace personal communication, especially technologies richer in contextual cues, such as video communications, instead of traditional voice calls. Further, some of these online technologies allow people to communicate in groups. Thus enabling virtual gatherings resembling in-person communications, be it gathering family members, friends, or co-workers.

The basic need for connectedness with others does not only mean the need for communication with acquaintances. The COVID-19 pandemic resulted in the advent of technologies concerning interactions or ‘being close’ with strangers. People utilise technology to organise virtual dinner parties, religious services, weddings, live music events, and virtual reality-based activities, such as playing poker or climbing mountains (Kirk and Rifkin 2020). Some technology-based coping mechanisms lead to pro-social behaviors, for instance, an online pub offering regular quizzes raising funds for charity, which is not common in brick-and-mortar pub quizzes (Bakar 2020).

2.5. Information seeking

Social media is the most popular medium to seek and share information during a crisis and cope with loss (Palen and Hughes 2018). However, it is also a tool for direct communication between peers, meaningful during natural disasters when geographical communities are affected. Moreover, some social media enable adjustments to accommodate the needs created by disasters. One example was the creation of Twitter's hashtag to filter the information (Palen and Hughes 2018).

Social media may also provide people with a space for emotional support. Nevertheless, as shown in online forums, it may lead to anti-social behaviors (e.g. trolling) (Qu, Wu, and Wang 2009). Social media is also an essential tool during protests and political uprisings. For instance, retweets might be used to coordinate meetings or gain supporters for social movements, drawing attention and sustaining social solidarity (Starbird and Palen 2012).

Similarly, social networks might be critical during wars. For instance, studies on conflicts in the Middle East show that such technology provides people with a connection to family and friends and enables meeting new people (Mark, Al-Ani, and Semaan 2009, Mark and Semaan 2008). The anonymity of online space enables new connections and considerations of different points of view over the conflict. However, using technology during the conflict may have a different purpose–people self-organise communication networks and identify the safest ways to travel. Students may be responsible for recording and distributing course materials to those who cannot access the university. Studies show that regardless of scarce resources, such as access to electricity, people prioritise using energy to ensure Internet connectivity instead of powering up different appliances, which is yet another evidence that the role of technology in crisis is crucial (Mark, Al-Ani, and Semaan 2009, Mark and Semaan 2008).

3. Research objectives

As discussed above, the increasing digitalization of services influences digital well-being at the individual and societal levels. On the one hand, digitalization provides people with tools that improve their life. However, it can also have adverse effects. For instance, past research shows that it is challenging to maintain digital well-being, as technology might distract and interrupt people's activities (Feng et al. 2019, Chen, Nath, and Tang 2020). It can also affect mental and physical well-being and become addictive (Alimoradi et al. 2019, Kuss and Griffiths 2017, Klein 2020).

Despite the relatively large body of research dedicated to using technology and its effects on well-being, there is a lack of comprehensive insights from end-users about their experiences with technology, considering different spheres of digital well-being. The present research addresses this gap, exploiting the circumstances – the global COVID-19 pandemic that constrained people's lives and influenced relationships with digital technology. The present research aims to gain in-depth knowledge of peoples' experiences to identify how the use of digital technology changed during the pandemic and how these changes affect subjective well-being. Such insights are crucial to the digital transformation process, as defined in the Introduction Section 1. The knowledge gained in the present research can benefit services and system designers and outline the path for innovative solutions. The omnipresent technologies should be designed in the way that is the least harmful to users' well-being, resulting in the balanced use of technology and health (both physical and mental).

To achieve the research aims, we pose the following research questions:

RQ1 How has the use of technology changed during the pandemic (increase vs. decrease)?

RQ2 What is the relationship between the select intrinsic factors, life satisfaction, and the use of technology during the pandemic?

RQ3 How do experiences with digital technologies affect well-being and acceptance of technologies?

Answering the research questions helps assessing when technologies create and foster human values and when the opposite happens. Such knowledge should be used as a bedrock for digitalization processes. Moreover, answering these research questions can produce insights highlighting human-centered problems around technology acceptance and solutions beyond digital technologies' design.

The main focus of the present research is to answer the third research question, as the COVID-19 pandemic was utilised in this research as an essential factor. Based on past research and findings from statistical reports (Pew Research Center 2021, Feldmann et al. 2021, Wallinheimo and Evans 2021), we considered that the overall COVID-19 pandemic fast-forwarded the use of technology, permitting people who have not previously used certain digital services to become users. Still, to ensure that the investigated sample experienced increased use of technology, we investigated RQ1, and to gain a better understanding of potential confounding factors that might affect people's relationship with technology use, we addressed RQ2. These two research questions build the foundation for our main findings–experiences with digital technologies and their effects on well-being and technology acceptance.

4. Methods

In order to answer our research questions, we designed an online study. The study was conducted between June and July 2021–approximately one and a half year through the pandemic. The study protocol can be divided into five main sections. Before commencing the participation, participants were presented with informed consent, which they needed to acknowledge to proceed with the study. Next, the participants were presented with the following study sections:

(1)	Study introduction. Because our study focused on questions related to the use of technology, in the first phase of the study, we informed participants on how we understand technology. Next, we presented them with a short introduction to the next section of the study (see Appendix 1 for details).
(2)	Technology use questions. In this section of the study, we asked participants to, in their own words, describe negative and positive experiences that they had with technology during the COVID-19 pandemic (see Appendix 2). Participants were to respond in a text field, and their responses' length had no limits. The two open-ended questions were followed by questions related to the changes in the use of technology that participants experienced during the pandemic. We asked respondents whether their use of technology was decreased or increased during the pandemic compared to pre-pandemic. We asked this question individually about five different context of technology use: work or education, entertainment, health, information seeking, and social interactions. The responses were collected on a Likert-like scales, ranging from 1 (Much lower) to 5 (Much higher) (see Appendix A.5). The order of these questions was randomised to avoid ordering effects.
(3)	Attitudes and behaviors during the pandemic. Participants were asked questions measuring their attitudes and behaviors during the pandemic in this section. The section commenced with a short introductory text explaining what questions participants can expect next (see Appendix sec A.6). Next, we measured loneliness and the ability to cope. To measure loneliness, we used a previously validated scale obtained from Cornwell and Waite (2009). The scale consists of three questions, and responses are measured with a three-point Likert scale (hardly ever, some of the time, often). We used a previously validated scale from Power, Smith, and Brown (2021) to measure the ability to cope. The original scale contained eight dimensions, but for the purposes of our study, we only measured four: support seeking, acceptance, disengagement, and active coping. We omitted substance use, humor, religion, and self-blame as we found them unsuitable for the present research context. Next, we asked participants a series of ad hoc questions related to the pandemic and technology (see Appendix A.9). We asked whether they bought or lack of technology. We also asked whether the respondents followed the authorities' recommendations related to the pandemic.
(4)	General attitudes and behaviors. This section contained questions related to participants' general attitudes and behaviors. Before answering this section's questions, participants were presented with a short introductory text (see Appendix A.10). Next, we measured the ability to bounce back and life satisfaction. The ability to bounce back was measured with a scale obtained from Smith et al. (2008) (see Appendix A.11). The scale consisted of five items, with response options ranging from 1 (Not true at all) to 5 (True nearly all the time). Similarly, life satisfaction was obtained from Margolis et al. (2019) and was measured with six items ranging from 1 (Not true at all) to 5 (True nearly all the time) (see Appendix A.12). Lastly, participants were asked for basic demographic information, such as gender, age, living status, country of residence, and employment status (see Appendix A.12.1).

At the end of the study, participants were thanked for participation and automatically redirected to the Prolific website¹.

4.1. Ethical considerations

The study design underwent an ethical review by the [blind for review] Ethical Review Board. The review board determined that this work would not expose participants to undue risk. To comply with the legal requirements, the researchers made an effort to minimise data collection and reduce the probability of identifying an individual. No personally identifying information was requested from the participants.

4.2. Data analysis method

The collected data was analysed using the mixed-method approach. To answer research questions 1 and 3, we applied a standard statistical approach, e.g. descriptive statistics, correlations, and regression analysis (see Section 5).

To analyze open-ended questions, we used QDA Miner and Wordstat², following the recommendations from Silver and Lewis (2017). Because of our research's exploratory nature and rather precise research questions that map onto the open-ended questions appended in our study, we created and followed the plan presented in Figure 1.

Figure 1. Qualitative data analysis process.

Figure presents phases of qualitative data analysis. Phase 1: Planning, includes familiarization, design analytic plan, data preparation, analysis set-up. Phase 2: Dictionary building, includes exploration, category building, category refinement, validity checks. Phase 3: Coding, includes dictionary based coding, review coding, narrative coding, consistency checks, review analytic plan. Phase 4: Patterns and relationships, includes what is discussed, related topics, topics by socio-demographics, review analytic plan. Phase 5: Interpretation, includes review previous stages, results writing.

First, in the planning phase, we explored the data in Wordstat, looking at the frequencies of words, most commonly used phrases, misspellings, suggestions, and similar. Next, we prepared the analytic plan, focusing on methodological, practical, and technological objectives. We followed it with cleaning and organizing data and finished with a set-up ready for QDA Miner analysis.

In the second stage of the data analysis, remaining in Wordstat, we focused on building a dictionary. When building a dictionary, we first considered phrases and single words frequencies. Looking at keywords in contexts and checking suggestions, we created dictionary entries. The dictionary was based on responses to both open-ended questions. Before applying the dictionary to the data set, we further evaluated the dictionary by checking keywords in context and sharing the dictionary data set with two other researchers. The final version of the dictionary contained 476 entries, including flexible words ending with (*).

In the next phase of the analysis, we applied the dictionary to the data set and returned to QDA Miner to continue with coding. Therefore, the first codes were added automatically by the software, based on the dictionary entries. One researcher was responsible for coding, and worked in an iterative manner. First, the researcher checked for, when possible, sentence-level coding. However, because many of the responses included only lists of words or lacked proper punctuation, some codes were applied to the whole responses. Then the uncoded and coded responses were reviewed, retrieving the texts to ensure validity. The coding-responsible researcher re-read the responses multiple times and re-coded when necessary.

Finally, when the coding phase was completed, we examined the patterns and relationships in the data set. In particular, we looked at code frequencies and co-occurrences and checked code distributions by different variables (e.g. increased use of technology in different contexts and demographic information). Upon completing this phase, we revisited the analytical plan, focusing on the research questions. Next, we proceeded with the last phase of the analysis and interpreted the data based on the analytical steps and the data content.

4.3. Participants

In order to gather responses to our survey, we used an online platform–Prolific Academic–allowing for quick and feasible distribution of the link of the study. Everyone 18 years old and above and speaking English could participate in the study. All participants received financial compensation of 1.50 GBP per response; the average completion time was approx. 8.5 minutes.

In total, we received 608 responses, of which 578 responses were complete. To check the validity of responses, we used an attention check question ‘The flower test is simple, when asked for your favourite flower you must enter the word rose in the text box,’ and all respondents provided correct answers. We have also checked response time, using the parameter called the relative speed index, following recommendations from Leiner (2019).

Among participants, 280 identified themselves as male, 294 as female, and four as other. Most of the participants, at the time of the study, were employed, with $42\text{\%}$ employed for wages (n = 245), $9.2\text{\%}$ self-employed (n = 53). Many of participants were students–$34.4\text{\%}$ (n = 199, of which n = 48 were students with salary). Considering the geographical distribution of our participants, there was an all-around distribution; n = 129 ($22.3\text{\%}$) participants from the UK, n = 92 ($15.9\text{\%}$) from South Africa, and other countries (see Table 1 for details). The participants' age ranged from 18 to 74, but the majority belonged to the younger population, M = 28.8, Mdn = 26. We also asked whether participants lived alone, and only $13.3\text{\%}$ (n = 77) stated that they did.

Table 1. Demographic characteristics of the sample.

Demographics		N	%
Gender	Male	280	48.4
	Female	294	50.9
	Other	4	0.7
Employment	Employed for wages	245	42.4
	Self-employed	53	9.2
	Out of work/unemployed	45	7.8
	A student	151	26.1
	A student with salary	48	8.3
	Retired	2	0.3
	Unable to work	6	1
	Lost work because of COVID-19	18	3.1
	Other	10	1.7
Country of residence	UK	129	22.3
	South Africa	92	15.9
	Poland	47	8.1
	Portugal	47	8.1
	Italy	38	6.6
	Mexico	31	5.4
	USA	28	4.8
	Greece	22	3.8
	Spain	18	3.1
	Canada	15	2.6
	Ireland	15	2.6
	Others	96	16.7

Moreover, considering the pandemic, we asked participants how they behaved–if they followed the pandemic-related recommendations given by local authorities. The overwhelming majority of participants (n = 549, $95\text{\%}$) stated that they did. The remaining five percent stated that they could not follow recommendations for reasons such as their life circumstances did not allow it or they did not care, among others. We also asked participants if they bought any new technology during the pandemic. In total, 266 participants responded yes. Among the most frequently mentioned were computer/PC, laptop, smartphone/iPhone/mobile, tablet/iPad, headphones, watch, console, smart products (e.g. watch, TV), and Nintendo switch. Lastly, we asked participants whether, during the pandemic, they lacked some technologies. We received 66 positive responses. Most commonly, participants mentioned topics related to laptops (e.g. ‘I need a laptop/desktop for myself’) and the internet (e.g. ‘Also, better quality and stability of internet connection has been a constant issue’).

5. Results

5.1. Changes in the use of technology

In the first research question, we asked about the changes in the use of technology that the participants experienced during the pandemic. First, we examined the overall changes in the use of technology, assessing the mean scores of answers to the five questions about technology use in different contexts (see Appendix A.5). The results indicate that overall, there was a slight increase in the use of technology (M = 3.52, SD = 0.7). Next, we looked at the responses to each question (see Table 2 for details). In the context of work and education, most participants indicated that they used technology more than before the pandemic (N = 341, $59\text{\%}$). However, a large number of participants indicated that they used technology for work and education about the same amount or lower compared to before the pandemic's beginning (N = 237, $41\text{\%}$). Similarly, there appears to be an increase in the use of technology in other contexts, observable in the context of entertainment (increased use reported by N = 366, $63.3\text{\%}$ of respondents) and information seeking (increased use reported by N = 350, $60.6\text{\%}$ of respondents).

Table 2. Changes in the use of technology in the five different contexts. See Appendix A.5 for the exact wording of the question.

Technology use for	Much Lower	Lower	About the same	Higher	Much higher	M	SD
	$N$	$N$	$N$	$N$	$N$
	%	%	%	%	%
Work and education	29	66	142	152	189	3.70	1.18
	5%	11.4%	24.6%	26.3%	32.7%
Health	35	129	225	145	44	3.06	1.01
	6.1%	22.3%	38.9%	25.1%	7.6%
Entertainment	21	69	122	201	165	3.73	1.11
	3.6%	12%	21.1%	34.8%	28.5%
Information seeking	10	35	183	216	134	3.74	0.93
	1.7%	6.1%	31.6%	37.4%	23.2%
Social interactions	60	113	103	159	143	3.37	1.32
	10.4%	19.6%	17.8%	27.5%	24.7%

In the context of social interaction, participants' answers indicate that their use of technology did not increase as much when considering the social distancing and lockdown measures used in many countries during the pandemic. N = 302 ($52.2\text{\%}$) respondents reported increased use of technology, while N = 173 ($30\text{\%}$) stated that their use of technology in this context was lower than during the pandemic. The lowest change in technology use was in the health context. Here, N = 225 ($38.9\text{\%}$) participants indicated no change, and N = 164 ($28.4\text{\%}$) stated that they actually used technology less than before the pandemic.

5.1.1. Relationship with intrinsic factors

Because our research did not include manipulation, we did not assume causal relationships between the investigated variables. Hence, we used correlation analysis to gain an overall picture of potential relationships of constructs investigated with the changes in technology. Because in the data set we identified some outliers, and the data did not satisfy the assumption of normality, we decided to use non-parametric tests, Spearman rho rank correlation coefficient. The details of analysis results are presented in Table 3, below we describe only correlations at the significant level.

Table 3. Spearman rho correlations between the changes in the use of technology and intrinsic constructs.

Variable	M	SD	1	2	3	4	5	6	7	8	9	10	11	12
1. Work and education	3.70	1.18	–
2. Health	3.06	1.01	.26${}^{\ast \ast }$	–
3. Entertainment	3.73	1.10	.25${}^{\ast \ast }$	.11${}^{\ast \ast }$	–
4. Information seeking	3.74	.93	.15${}^{\ast \ast }$	.12${}^{\ast \ast }$	.26${}^{\ast \ast }$	–
5. Social interactions	3.37	1.32	.32${}^{\ast \ast }$	.29${}^{\ast \ast }$	.36${}^{\ast \ast }$	.13${}^{\ast \ast }$	–
6. Support seeking	2.99	.79	−.01	.13${}^{\ast \ast }$	.06	.09${}^{\ast }$	.10${}^{\ast }$	–
7. Disengagement	1.76	.73	−.10${}^{\ast \ast }$	−.12${}^{\ast \ast }$	−.03	.00	−.05	.12${}^{\ast \ast }$	–
8. Active coping	3.56	.64	.05	.11${}^{\ast \ast }$	.06	.18${}^{\ast \ast }$	.09${}^{\ast }$	.30${}^{\ast \ast }$	.02	–
9. Acceptance	4.05	.73	.04	.14${}^{\ast \ast }$	.08${}^{\ast }$	.10${}^{\ast }$	.12${}^{\ast \ast }$	.11${}^{\ast \ast }$	−.32${}^{\ast \ast }$	.21${}^{\ast \ast }$	–
10. Loneliness	1.99	.59	.03	−.08${}^{\ast }$	−.03	.05	−.02	.03	.27${}^{\ast \ast }$	.00	−.09${}^{\ast }$	–
11. Bounce back	3.2	.72	.04	.07	.08${}^{\ast }$	.01	.04	−.076	−.26${}^{\ast \ast }$	.10${}^{\ast }$	.11${}^{\ast \ast }$	−.33${}^{\ast \ast }$	–
12. Life satisfaction	3.11	.87	.06	.03	.05	−.05	.05	.06	−.26${}^{\ast \ast }$	.04	.13${}^{\ast \ast }$	−.39${}^{\ast \ast }$	.28${}^{\ast \ast }$

There was a negative correlation between the use of technology for work and disengagement. The use of technology for health had positive correlations with support seeking, active coping, and acceptance. It also correlated negatively with disengagement and loneliness. The use of technology for entertainment had positive correlations with acceptance and ability to bounce back. Information seeking was positively correlated with active coping and acceptance. Finally, using technology for social interaction positively correlated with acceptance and active coping.

Additionally, the correlation analysis identified positive correlations between loneliness and disengagement, and a negative correlation between loneliness and acceptance. The ability to bounce back was negatively correlated with disengagement and loneliness. It was positively correlated with active coping and acceptance. Similarly, life satisfaction was negatively correlated with disengagement and loneliness. It was positively correlated with acceptance and the ability to bounce back.

5.2. Experiences with technology

Among the responses, 187 were missing–participants did not provide answers to the open-ended questions about their experiences with technology. The qualitative data analysis resulted in the three high level categories: technology-enabled activities, effects of technology, and practical aspects of technology. The technology-enabled activities category contains the following subcategories: socializing, learning, work, leisure, information seeking, shopping, and other services. The effects of technology contains the following subcategories: financial, time-related, health-related, and misinformation. The last category does not contain subcategories.

5.2.1. Technology-enabled activities

The first high-level category–technology-enabled activities–contains seven subcategories consisting of different codes, as presented in Table 4.

Table 4. Subcategories and codes for technology-enabled activities.

Subcategory	Code name	Code frequency
Socializing	Interactions with specific people	218
	Social interactions in general	73
Learning	Certified	180
	New ways/skills	81
Work	Individual	96
	Group	53
	Remote/from home	75
Leisure	Watching/streaming	73
	Hobbies/interests	19
	Gaming	33
	Other leisure	52
Information seeking	Pandemic-related	65
	Other information	40
Shopping	Acquiring food	23
	Shopping in general	25
Other services	E-health	16
	Various services	26

Socializing. This subcategory is the most mentioned. Here, participants mainly described how technology affects interactions with others, focusing predominantly on relationships with specific people, e.g. friends, family, and loved ones. Typically, people to whom they were emotionally attached. Respondents often referred to different communication channels, including video conferencing software, chatting applications, social media, or similar.

Learning. Participants wrote about certified learning–organised learning in school or courses that lead to certification. They described how technology made learning accessible, despite the pandemic-related restrictions. They wrote about video conferencing and communication tools that allow previews of lectures and lessons and facilitate contact with teachers and fellow students. They also described new ways/skills. Participants predominantly wrote about how they utilised the technologies they were already familiar with in new ways or obtained new skills through technological means.

Work. In the work subcategory, the respondents described their experiences primarily as individuals, working from home, and at times referred to the collaborative aspects of work. They wrote about how technology allowed them to continue working during the pandemic's difficult times, although not without challenges. They had to learn how to use new tools, interact in a group, or find a balance between work and private life when they worked from home or remotely.

Leisure time. In this subcategory, participants mostly noted that their entertainment was entirely done through technology. Many referred to watching movies through streaming services (e.g. Netflix). Some also described using content-sharing applications (e.g. TikTok) and social networks to watch/stream content. Others commented about listening to audiobooks and music, with a few mentioning events they usually would participate in (e.g. live concerts). They also wrote about their hobbies and interests that technology helped them discover or maintain. Gaming was a frequently described leisure activity.

Information seeking. Many participants wrote about using online technologies to find information, mainly about the pandemic. Technology allowed them to stay updated with the pandemic's dynamic changes, e.g. information about the virus spread, symptoms, and vaccination development. Some participants also wrote about utilising technologies for information seeking in a more generic sense, looking for non-pandemic-related news, or learning to find the information they can rely on/trust.

Shopping. Some participants described how technology affected their shopping experiences. They wrote about using online technologies to order food, buy products in the store, and have them delivered. Others mentioned substituting cooking or going out to restaurants with ready-made food deliveries. Participants also wrote about the overall shopping experience and technology, allowing them to buy everything they want online. Everything became easy to reach from home because of the new (or existing but previously not used) online services.

Other services. There were two more codes arising from the answers belonging to the activities category. First related to e-health services. Participants wrote about their experiences with healthcare-related systems, focusing on digital appointments. The second code contains miscellaneous services, including dating applications, payment services, virus tracking, translating services, VPNs, and non-specified apps.

5.2.2. Effects of technology

This category contains the effects that the technology had on participants during the pandemic. Table 5 presents belonging here subcategories and their codes.

Table 5. Subcategories and codes for effects of technology.

Subcategory	Code name	Code frequency
Financial	Earning	42
	Spending & costs	12
Time-related	Losing time	135
	Gaining time	32
	Continuous availability	15
Health-related	Health & physiological issues	80
	Well-being improvement	21
	Feelings & emotions	172
	Technology addiction	20
Misinformation	About Covid	16
	General misinformation	14

Financial. Many participants explained how technology affected their economic situation. The opposite codes surfaced in participants' responses: earning and spending/costs. The first one consisted of answers indicating how people could continue working and find new jobs or sources of income that they previously did not even think of through technology. Additionally, some participants referred to gaining money indirectly–through saving on travels or not spending money on certain services, because these services became freely available online. On the other hand, in the second code, some participants described additional spending and costs related to the technology. Here, the costs usually result from increased utilities or data transfer charges.

Time-related. Participants also described how technology affected their time, particularly gaining or losing time. Considering gaining time, participants mentioned how technology allowed them to save time, for instance, on traveling to work or school. In exchange, they could use this saved time for other purposes.

The code losing time was described more frequently. Participants noted too much screen time and its effects on health and well-being. Respondents also described the growing dependency on technology, its distracting nature, and technology taking over life while time could be used in better ways.

Health-related. In this subcategory, participants described different dimensions of health. In the first code, many participants noted health and physiological issues resulting from using technology. Participants mentioned issues such as eye strain, headaches, and bad posture. The second code that surfaced among responses was feelings and emotions. Participants mentioned their mental health overall or described specifics such as anxiety, loneliness, stress, anger, depression, procrastination, lack of motivation, fatigue, and similar. However, respondents also stated that technology helped them reduce such feelings, keeping them from boredom, allowing them to feel close to others, and keeping sanity. A small segment of respondents mentioned addiction to technology, where participants realised that it is easy to become addicted since they spent so much time in front of the screen.

Misinformation. Another subcategory that emerged among the effects of technology is misleading information. Technology affects it by enabling easy distribution of false information and making it accessible through various technological means. Here, participants sometimes mentioned how difficult it might be to verify the information. The two codes included in this subcategory are information about Covid and general misinformation.

5.2.3. Practical aspects of technology

The last category describes the practical use of technology, mostly focusing on technical issues. No subcategories were identified in this category. Instead there were three codes: connection n = 64 (related to internet connectivity), hardware/software n = 33 (e.g. problems with computers, broken phones), and other technical n = 36 (unspecified statements, e.g. technical problems). The majority of responses in this category carried a negative weight, with only a few exceptions.

5.3. Activity based model

After coding the data and conducting a primary analysis, it became transparent that the identified categories of data intertwine, and their relationships might fit a simple conceptual model, as presented in Figure 2. The activities were central to our respondents. Through the description of activities, participants' responses were associated with either the positive or negative effects of technology. At times, the relationship between activities and effects was, in a sense, mediated by practical aspects of technology, increasing the negativeness of the effects of technology. This is conceptually presented in Figure 2 with ‘+’ and ‘−’ signs refer to positive and negative experiences with technology, respectively. For instance, technology-enabled socializing may lead to positive feelings & emotions, such as described by participants feeling connected but it may also lead to negative feelings, such as feeling awkward because of the video chat. However, technology-enabled activities might be ‘moderated’ by practical aspects of technology, which in our data-set predominantly results in negative technology effects. For instance, participants described work during which software crashed in the middle of the online work-meeting, which resulted in feeling guilt and pressured.

Figure 2. A conceptual model of the relationship between categories. The ‘+’ and ‘−’ signs refer to positive and negative experiences with technology, respectively.

Model contains three elements. On the left, at the bottom are Technology enabled activities, which directly connect with Technology affects (bottom right). At the top there are Practical aspects of technology, which are influenced by Technology enabled activities. Practical aspects of technology are mediating the relationship between Technology-enabled activities and Technology effects.

In this section, we attempt to zoom into those relationships, emphasizing the negative and positive experiences that the participants described. For simplicity, we will focus on the most frequently discussed activities: social connection, learning, work, leisure, and information seeking, and present their relationships with the effects or practicalities most relevant for a given activity. To assess such relevance, when possible, we used proximity plots (see Figures 3, 4, 5, 6, and 7). Proximity plots consider similarity of code co-occurrences, and we conducted them separately on codes for positive and negative experiences. We used Jaccard's coefficient index to measure the similarity.

Figure 3. Proximity plots for social connection activities. Numbers on the x-axis indicate similarity index of code co-occurrences (Jaccard's coefficient). (a) Negative (b) Positive.

Figure 4. Proximity plots for learning activities. Numbers on the x-axis indicate similarity index of code co-occurrences (Jaccard's coefficient). (a) Negative (b) Learning positive.

Figure 5. Proximity plots for work activities. Numbers on the x-axis indicate similarity index of code co-occurrences (Jaccard's coefficient). (a) Negative (b) Positive.

Figure 6. Proximity plots for leisure activities. Numbers on the x-axis indicate similarity index of code co-occurrences (Jaccard's coefficient). (a) Negative (b) Positive.

Figure 7. Proximity plots for information seeking activities. Numbers on the x-axis indicate similarity index of code co-occurrences (Jaccard's coefficient). (a) Negative (b) Positive.

5.3.1. Socializing

Negative experiences. Some participants complained about shifting social interactions into a digital space. Many felt that it was not the same as in-person interactions and that digital connections could not completely replace them. As indicated in the proximity plots (Figure 3(a)), participants described such feelings and emotions. In particular, they expressed feeling awkward because of video chats; they sometimes found digital interactions depressive and overwhelming and linked them to the loss of time. Some talked about fatigue associated with the use of videoconferencing tools. Others felt overwhelmed by interactions with specific people or forced to connect with them continuously, recognizing the potential negative consequences of such interactions for life in the post-pandemic future. Examples of participants responses are presented in Table 6.

Table 6. Example responses about socializing activities. Codes: [IS] – interactions with specific people, [SG] – social interactions in general.

Negative experiences: socializing.
‘I often feel overwhelmed and suffocated by friends constantly texting and messaging throughout the day. Everyone else was off work and expected me to answer phone calls and texts instantly because of the pandemic and knowing I was home.’ [IS]
‘I communicated through chat apps only with no voice more than usual (and I use chat a lot). That made me feel a bit like I was living in a dream or something. Days past and couldn't really feel all the conversations with my colleagues and friends, like they didn't happen.’ [IS]
‘Fatigue of using technology, especially video conferencing for staying in touch with people. The initial excitement of easy communication quickly wore off after a day of too many work meetings. I further felt isolated from my partner who was glued to their social media apps even prior to the pandemic; lockdown just amplified this behaviour and caused many conflicts.’[IS, SG]
‘I no longer feel like going out, i prefer to stay connected via online. Now when i try to socialise i feel weird, i am slowly forgetting what was it like to live with other people besides my core family.’ [SG]
Positive experiences: socializing.
“Technology has also given us opportunity to keep in touch with friends despite not seeing them and therefore, maintaining mental health and friendships.” [IS]
‘I was able to keep working and to stay in contact with my boyfriend and see him even if we couldn't meet due to all the restrictions. It was a way to feel close to him.’ [IS]
‘Technology helped me stay in touch with people leaving in other cities and/or countries and this I was not feeling alone.’ [SG]
‘Through the use of technology I was able to make new social connections and join discord groups to find some kind of social life while under quarantine’ [SG]

Positive experiences. Many participants described their positive experiences when speaking about socializing with friends and family. They predominantly praised the technology for enabling them to keep in touch with others, communicate, and connect. This social connection was possible because of chats, videoconferencing tools, social networks, and similar. Some recognised how technology allowed them to maintain relationships with people who live far away, continuing with activities similar to those offline, even when in lockdown, such as organizing online parties and having random chats. Others mentioned that their relationships with people living abroad increased, which would not happen in normal circumstances.

Considering the proximity plots (Figure 3(b)), participants described many of their feelings and emotions in the context of positive experiences. They clarified how technology helped them maintain social relationships and, as a result, good mental health, reduced boredom, enabled feeling close and staying connected with others, and reduced feelings of loneliness and stress.

Socializing was also mentioned in proximate to the financial effects of technology, particularly close to earning. Here, a few participants described saving on international phone connections, growing online businesses due to increased ability to connect with others, or making it easier to get hold of people. Examples of responses about positive experiences in socializing are presented in Table 6.

5.3.2. Learning

Negative experiences. The negative experiences related to learning were predominantly described in the context of certified learning (see Figure 4(a)). Many participants mentioned their health and physical issues that mainly resulted from the extended amount of time they had to spend in front of their computers/laptops. These led to a decline in their physical health, affecting their eyesight, causing headaches, and similar.

Moreover, many participants wrote about certified learning in close proximity to various feelings and emotions (Figure 4(b)). They described how easy it became to get distracted and lose attention and motivation. They also addressed issues related to increased levels of stress, anxiety, depression, and even bullying.

Some participants mentioned certified learning next to losing time. For instance, they noted extensive time spent on learning while reading from the screen or spending too much time using different applications, which negatively affected their grades (lower grades). These descriptions are often interwoven with descriptions of participants' feelings, emotions, or health issues.

Further, quite a few respondents complained about the practical aspects of technology. All three codes of practical aspects of technology appeared close to the responses about certified learning. Here, participants mentioned problems with the internet connection and the adverse outcomes that resulted from it, such as stress or anxiety. Others described hardware-related issues, mainly problems related to personal computers that failed them in some ways (being slow and breaking down). Lastly, they described other technological issues without specifying them. Examples of responses about the negative experiences in the context of learning activities are presented in Table 7.

Table 7. Example responses about learning activities. Codes: [CE] – certified, [NW] – new ways/skills.

Negative experiences: learning.
‘My eyes begin to hurt, which is something unavoidable due to the many hours of classes and studying’ [CE]
‘I wasn't able to learn as much from online classes and felt more depressed.’ [CE]
‘[…] before COVID, during an exam I would be doing the interview with at most a couple of people listening in. During COVID suddenly anyone on the course could listen to the exams: this stressed me immensely, because I felt like every mistake I made would be public. It got to the point where I would postpone exams for fear of this situation.’ [CE]
‘I had to delete my email app from my phone to avoid seeing school-related stuff outside “office hours”, otherwise it would affect my mental health and my sleep.’ [CE]
‘While online learning, technology failed me a few times, especially when giving presentations – the connection was poor, the audio didn't work well and the camera quality was definitely not the best.’ [CE]
Positive experiences: learning.
‘my postive experiences were an improvement in learning how social media works how people can generate income using technology for example being a content creator on tiktok or starting affiliate marketing to generate passive income.’ [NW]
‘I was able to participate in classes from other countries and cities. For example I was able to take a course on korean culture and language with a university from other city and take summer courses on japanese language and culture form universities in tokyo while being in portugal which didn't cost me as much as it would if I had to travel for that country.’ [CE]
‘As a collage student, all of my studies for the past year have been online. While I don't prefer this type of learning, I have been able to save a lot of time that would otherwise be used to travel to and from the campus, allowing me to use that time in better ways’ [CE]
‘The e-learng has positiv impact on my sleep, as i dont have to wake up early to travel to university’ [CE]

Positive experiences. One of the topics mentioned next to learning, in the context of positive experiences, was earning, particularly in the context of learning new ways/skills (Figure 4). Participants described how they learned to use the internet or social media to earn income. For example, the new way of making money was through getting more active in online banking or participating in online surveys. Others mentioned the free courses and how technology allowed them to participate in such courses, which they would otherwise not take due to financial constraints.

Participants also described how using technology in education and learning enabled saving time. The availability of online courses allowed them to save time they would otherwise spend commuting, using both private and public means of transport.

Some participants also talked about positive feelings and emotions in connection with learning, acknowledging the positive aspects of technology. Here, respondents described certified learning and new ways/skills as gratifying experiences that kept them mentally healthy and sane. Examples of responses about positive experiences in the context of learning are presented in Table 7.

5.3.3. Work

Negative experiences. The negative experiences with technology around work-related activities were described next to the topic of continuous availability (Figure 5(a)). When describing working in groups, some participants expressed experiencing pressure from their peers and feeling expected to be available all the time. They also mentioned how working remotely/from home increased such feelings of pressure, invading their personal home space.

Another negative topic appearing close to responses related to work was the practicalities of technology. Here, participants complained about the failure of technology and how their devices broke when they performed work-related tasks. They also mentioned internet connection issues, which were incredibly frustrating during group work activities, such as meetings. Some also noted the need for better internet infrastructure, as the current one is not prepared for a large volume of people who suddenly shifted to work from home, and the network could not handle it.

Some participants also described their negative feelings and emotions. They explained how online meetings resulted in uncomfortable feelings, e.g. loneliness, boredom, intolerance, intrusiveness, or feeling unprofessional. These negative emotions, at times, result from practical technological issues. Other times, such negative emotions result from group work, and participants questioned whether collaborative work over the digital medium is practical.

Participants also mentioned that many of their feelings related directly to remote working. They struggled with maintaining an appropriate work-life balance, which became even more difficult since other aspects of life, beyond work, also heavily relied on technology. Examples of negative responses about work are presented in Table 8.

Table 8. Example responses about working activities. Codes: [IN] – individual, [GR] – group, [RH] – remote/from home.

Negative experiences: working.
‘As a number of my colleagues are based internationally (ie not in my home country) this meant I had less free time outside of regular office hours, whereas previously I would have left my work in the office. I dreaded video conferences and the need to “be seen” regardless of my mental state.’ [GR]
‘I have never been so accessible within the walls of my own home. People think they have the right to reach me whenever they want just because they can. Working at home should not mean that I am accessible at night or at the weekends.’ [RH]
‘Trying to have board meetings using MS Teams sometimes crashes my computer. It is frustrating to be in the middle of a video meeting when the wifi drops out. Sometimes I feel guilty when I do not message someone back straight away and it makes me feel pressured.’ [GR]
‘Teleconferencing cannot substitute real meetings and, most important, side by side cooperation. Also staying at home teleworking, increases loneliness.’ [GR] [RH]
‘Working from home for 1.5 years in studio apartment makes it difficult to have a healthy work/life balance since I'm using same devices for work and for entertainment after work.’ [IN] [RH]
Positive experiences: working.
‘Whilst I have been working harder and not been able to go about my normal routine, I have found my home work life balance has improved because of being able to save money, get jobs in the house done and have been more economic within the home.’ [RH]
‘I think some companies and universities have noticed that they dont need to send thousands of dollars on offices and classrooms, as the same work can be done in the employer's house.’ [RH]
‘And a lot of unnecessary face to face meetings that used to waste time have been replaced by quick emails or fast catch ups online so it streamlined time usage more.’ [IN]
‘I have been working from home and so have moved all my meetings etc online which is big time saver and I think they run more efficiently.’ [GR]

Positive experiences. Using technology for work has also been described in the context of positive experiences (Figure 5(b)). In particular, the earning topic appeared close to work-related activities. The main positive experience was that even during the difficult times when participants' freedom of movement was restricted, they could continue working and earn regular income thanks to technology. Some participants also mentioned losing jobs and using technology to substitute their income; others recognised financial benefits for themselves as well as for companies that may save when employees work remotely/from home.

Furthermore, the participants acknowledged that technology allowed them to gain time in the work context. They mentioned that they gained time because they did not need to commute, and the saved time could be used in other ways (e.g. spending time with family and household assignments); the time was also saved because face-to-face meetings were replaced with fast online catch-ups. Respondents also described online meetings positively, with some perceiving them as more efficient and organised than in-person meetings. Examples of responses about positive experiences in the work context are presented in Table 8.

5.3.4. Leisure

Negative experiences. Quite a few participants mentioned the issues of addiction to technology (Figure 6(a)). Many participants described interactions with entertaining technologies as addictive, preventing productivity and goal achievement. Gaming was one of the more prominently described activities in the context of technology addiction, not only from the players' point of view but also from the parents' point of view–recognizing that kids might become addicted because they spend too much time with technology.

To some extent, related to addiction is another topic described among the negative experiences with the technology used for leisure activities–losing time. Participants mentioned losing time on gaming or simply aimlessly scrolling through phones, noting the limits they had to place on themselves to stop wasting too much time. Losing time on leisure activities was also associated with mental and physiological health issues. Respondents mentioned that the increased screen time, streaming, and watching online content, lead to problems with the eyes, headaches, and mental exhaustion.

These adverse effects of technology-based leisure activities, of course, influenced how participants felt. Respondents described stress, obsession, anger, and being overloaded with information. Some mentioned the negative impact of the new habit of scrolling or continuous watching/streaming beyond the pandemic. In particular, it might be uneasy becoming stimulated by entertainment technologies after ‘overusing’ them for such a prolonged time. Examples of responses about negative experiences in the context of leisure are presented in Table 9.

Table 9. Example responses about leisure activities. Codes: [WS] – watching/streaming, [HI] – hobbies/interests, [GM] – gaming, [OL] – other leisure.

Negative experiences: leisure.
‘Aside from everyday activities, most of my leisure time was spent watching tv, being on my phone, using social media, etc. When I got bored I switched from one technological medium to another (phone, tv, laptop, etc). I felt like I was mindlessly scrolling and sitting in front of a screen not being productive simply because I was bored and felt there was nothing to. ’ [WS] [OL]
‘I have picked up bad habits with scrolling social media for hours on end, especially Tiktok. I live in what is considered a conservative state so a lot of people were anti mask, making it so I felt uncomfortable even trying to do outdoor activities. That left me stuck inside 24/7, relying solely on my phone and TV for entertainment. Now I struggle with lack of stimulation from my phone or TV.’ [WS] [OL]
‘I completely immersed myself in internet-based entertainment to take my mind off the outside world, and at some point ended up damaging some relationships that were now sitting mostly defunct.’ [OL]
‘I became more addicted to videogames which made me more stressed and angry.’ [GM]
Positive experiences: leisure.
‘Thanks to some social networks (ig and Fb) I've been able to follow a dance course, improving my abilities and becoming helthier’ [HI]
‘smartwatch encouraged me to keep up my health and fitness regime with the use of the pedometer and calorie tracker.’ [OL]
‘Surfing on the internet and on social media also entertains me during the quarantine, keeps me from being depressed, makes me feel connected, and also stay up to date to the current situation happening around the world.’ [WS]
‘It played a crucial part in maintaining a social life as well as my sanity during the pandemic. I was also able to find online groups to play Dungeons and Dragons with.’ [GM]

Positive experiences. Technology-mediated leisure activities also brought some positive experiences (Figure 6(b)). Participants recognised that some of the hobbies and interests enhance their well-being, such as using different applications, online classes, or even social networks, encouraging physical activities, e.g. yoga lessons, exercising, and dancing.

Similarly, these leisure activities elicited some positive feelings and emotions. Some participants recognised that gaming helps maintain a social life, keeping ‘sanity.’ Hobbies, interests, and other leisure activities made participants feel happy and connected. The digital leisure activities filled participants' time, preventing boredom and possible adverse effects that lockdowns and pandemics could have had on participants' mental health. Examples of responses about positive experiences in the leisure subcategory are presented in Table 9.

5.3.5. Information seeking

Negative experiences. The negative experiences with technology in the context of information seeking were often mentioned by participants, next to descriptions of their feelings and emotions (Figure 7(a)). Negative experiences were described in the context of information about the pandemic, e.g. statistics about the spread of the virus or deaths. Participants focused on how continuous negativity in the news, omnipresent and difficult to avoid, affected how they felt. Some mentioned that escaping such negativity was problematic, as it was present on traditional news channels, social media, and other digital spaces where participants previously experienced joy and entertainment. The overwhelming negativity was often associated with feeling depressed, stressed, anxious, and frightened. Some responses about these negative experiences and emotions evaluated the role of social media loaded with negative information, which is hard to avoid. At times, this resulted in participants deleting online accounts to disconnect from the information overflow. Interestingly, some mentioned that the national health services also contributed to eliciting negative emotions by distributing information about the pandemic, e.g. sending too many text messages.

Another aspect mentioned was how information affected not only themselves but also their family members or vulnerable populations. For instance, people suffering from mental-health-related issues or older generations might be more affected by the negative information.

The negativity of information seeking was also related to misinformation. Participants mentioned that it became problematic to distinguish between true and false information. Some mentioned that digital space was filled with conspiracy theories, the spread of false personal opinions, and contradictory information.

Participants' responses indicate that the continuous availability was described as near negative experiences with information seeking. Participants correlated the constantly incoming information with the feeling of being continuously online and available.

Some of the participants also described topics related to health while talking about information seeking. Being connected for a prolonged time to read news, learn more and stay up to date about the pandemic resulted in adverse effects on health. Some participants mentioned headaches, eyestrain, or sleep problems. Examples of responses about negative experiences in the context of information seeking are presented in Table 10.

Table 10. Example responses about information seeking activities. Codes: [PA] – pandemic-related, [OI] – other information.

Negative experiences: information seeking.
‘I also felt that I was browsing social media and news sites more, which made me more anxious as I followed devastating events unfolding each hour. I also felt that users of social media promoted productive outcomes (for example learning new skills, languages, cooking, fitness) for our time spent in lockdown. This added to the social pressure, isolation and instability I was already feeling.’ [PA] [OI]
‘I'm missing something out if I'm not looking for news, or memes, videos all the time.’ [OI]
‘Found constant alerts and scaremongering annoying and incessant, including huge amounts of nhs texts regarding the vaccine.’ [PA]
‘The use of social media and messaging services to distribute wrong and/or dangerous information regarding Covid-19. I recieved several cut-and-paste messages from various friends and family members giving wrong or potentially dangerous advice about how to cure or protect yourself from CV-19 such as gargling with hot water or strong alcoholic drinks.’ [PA]
‘I found myself staring at screens a lot more than I used to and not sleeping well, mostly caused by anxiety related issues because of all the news and never ending information about the pandemic and not knowing when I would be able to come back home.’ [PA]
Positive experiences: information seeking.
‘convenient to find news/updates on what's happening with the pandemic (e.g. twitter, ny times).’ [PA]
‘I was able to do more research on covid 19, the symptoms, possible home remedies and to actually research the numbers of people infected and affected, technology really helped.’ [PA]
‘I watched interesting videos about news and actuality.’ [OI]
‘I had some positive experience for example i get to know first about covid and other news faster than if i would watch tv.’ [PA]

Positive experiences. Considering positive experiences with information-seeking activities, the results of proximity plots seem to be coincidental. However, both information seeking about the pandemic and other information enabled by technology were perceived positively by some participants. They mentioned the importance of staying updated with current events, particularly with frequently changing information about the pandemic. Some praised the technology for access to information, enabling easy and quick reach to the news. Participants also described the availability of information, considering the physical location of the information receiver (e.g. learning news from the ‘couch’) and where the information comes from (e.g. anywhere on earth). They also related positive experiences with the different sources of information (e.g. apps, social media, and individuals sharing information online). Examples of responses about positive experiences in the context of information seeking are presented in Table 10.

5.3.6. Shopping and other services

Negative experiences. Considering shopping, only a few participants wrote about difficulties related to buying some products online or spending too much on shopping. Considering other services, a fewer participants mentioned health related services. These descriptions were made from the point of view of a patient and healthcare staff. Particularly due to practical aspects of technology, for instance, poor internet connection or system designs lacking functionality. Others mentioned time-consuming and inconvenient doctor visits. Some also noted that healthcare-related systems or applications are difficult to use, particularly by certain users–for instance, the elderly. Similarly to e-health services, the most negative experiences with various services are related to technology failures (e.g. internet connection) or immature technology (e.g. applications and systems difficult to use–e.g. banking services). Some examples of the negative experiences are presented in Table 11.

Table 11. Example responses about shopping and other services. Codes for shopping: [SG] – shopping in general, [AF] – acquiring food. Codes for other services [EH] – e-health, [VS] – various services.

Negative experiences: shopping and other.
‘Negative experiences i have had with technology was using grocery store apps to order food and necessities only to get mixed up orders and scammed off my money thinking the company is legit.’ [AF]
‘Over spending via online shopping due to having the luxury of working from home.’ [SG]
‘Some things are simply easier to do in person, some online services like the doctors were very time consuming and inconvenient.’ [EH]
‘I work in healthcare lag during meetings and during clinical appointments of apps such as teams resulting in lack of continuity during appointments. Inaccessibility of some apps to the older generation.’ [EH]
‘Banking technology in South Africa was dysfunctional and difficult to use.’ [VS]
‘A lot of small local businesses are coming out with their own apps but my experience with them has been very hit-or-miss since the development of those apps seems to have been rushed.’ [VS]
Positive experiences: shopping and other.
‘Ordering delivery when i didnt want to cook or be around people, these were both positive for me adjusting to life during the pademic.’ [AF]
‘I introduced some online services which i never used before. For example online daily shopping. During the COVID it became a daily routin what save a lot of time for me. I used this time for workout and other healty stuff.’ [VS]
‘A new only therapy service started in my country due to lockdown and I probably would not have gone for in person therapy to treat my PPD, so I'm grateful for that.’ [EH]
‘For example you could have detail chats with local doctors online about any issue. this mean from now on people dont really not to do out to get most of their services they need becasue most thing are online now.’ [EH]
‘I have had doctors appointments via zoom, allowing for a quicker diagnoses and shorter waiting times’ [EH]
“Online services being prioritised more than before means additional convenience especially for people who are less able to do things in person.”[VS]
‘More public services became available during pandemic (e.g. signing agreement without leaving home).’ [VS]

Positive experiences. Among participants reflecting on their shopping-related experiences, most of them expressed positive views of these activities. They mentioned the easiness and efficiency of online shopping, particularly in the context of grocery shopping and food delivery. Considering other services, some participants described their experiences with the digital visits of healthcare workers as predominantly positive, less time-consuming, and enabling quicker diagnosis. They also mentioned that the online availability of mental health-related services encouraged them to start therapy. Considering other services, participants wrote a lot about the growing number of online services and how they positively affect their lives by enabling easy access from home instead of doing certain chores in person (in particular, payment for services and signing agreements online). Some examples of participants' responses are presented in Table 11.

6. Discussion

6.1. Use of technology during the pandemic

The present study's first and second research questions are concerned with self-reported behavior–use of technology during the crisis, such as the pandemic–and factors that relate to such behavior. Because the present study did not include manipulation or experimental design, the quantitative part of the research can only rely on a correlational analysis, which might indicate how some technology-use behaviors relate to the examined latent constructs.

The first question addressed in the present research followed findings from previous research and reports concerning the COVID-19 pandemic indicating that the crisis advanced the use of technology (Alaqra and Kitkowska 2021, Pew Research Center 2021, Feldmann et al. 2021, Wallinheimo and Evans 2021). Still, according to the current results, this change was smaller than one could expect, considering the restrictions of many countries' authorities, particularly bans on travel, social gatherings, or frequent work from home. Nevertheless, the results indicate the differences in the increased or decreased use of technology throughout the various contexts investigated in the current research. For instance, many participants used technology the same amount or even less in the contexts of work and education, socializing, and, notably, health–where numerous participants indicated reduced use of technology. Such findings might be interpreted in different ways. First, it could be the effect of the time when the study was conducted, June-July 2021, already a year and a half through the pandemic. Since our study results draw on self-reported behaviors, it is possible that participants struggled to remember how much they used technology before the COVID-19 pandemic. Second, because a relatively long time has passed from the beginning of the pandemic to the time of the study, it is possible that many people turned towards using technology more to conduct many daily activities, and such a use of technology in many aspects of life became a norm. The third explanation might be that most people's activities are already highly digitalised or that participants were tech-savvy within the population sample of the present study. Hence, many respondents reported using technology about the same amount as before the pandemic. An exception to such explanations might be the use of technology in the context of health, which might have been lower since such technologies often relate to physical activities that were constrained or entirely forbidden during the pandemic (e.g. the inability to visit gyms or go outside).

Considering the second research question of the present research, the correlational results are as anticipated. Although the identified correlations between constructs are primarily small, their direction is logical. For the present research, of particular interest are the positive relationships between the use of technology (especially for health, information seeking, and socializing) and different coping strategies, for instance, support seeking, active coping, and acceptance. Similarly of interest are their negative relationships with disengagement and loneliness. Such findings indicate that people may use technologies for different purposes to cope with the crisis and reduce its adverse effects on well-being, such as loneliness. Simultaneously, the lack of significant relationships between the ability to bounce back or life satisfaction with the use of technology, yet the significant relationships they had with the coping strategies and loneliness imply that these factors might be strong predictors of behavior on their own. Moreover, in the study design, participants were asked to think about the pandemic when answering questions about their use of technology, loneliness, and coping strategies. At the same time, the remaining constructs were measured as general attitudes and behaviors beyond the constraints of the pandemic. Therefore, it is plausible that the study participants, paying attention to the way questions are being asked, truly differentiated between reporting their attitudes and behaviors, taking into account the presence or absence of the pandemic.

6.2. Digital well-being

The third research question of the present article explored the experiences with technology and its effects on digital well-being. The proposed activity-based model shows that different activity-related technology uses can positively or negatively affect people. The effects can be tangible, such as economic (financial gain or loss) or health (physiological issues, improvement of well-being). They can also be intangible, including effects on time (loss, gain, continuous availability), health (mental well-being, feelings, emotions, addiction), and misinformation. Additionally, the adverse effects of technology on well-being may increase because of practical issues with technologies, e.g. lack of internet infrastructure or software and hardware errors.

The analysis of open-ended questions drew on the proposed conceptual activity-based model–Figure 2. A closer look at the analysis results and participants' data suggests that our participants sometimes referred to digital technologies as substitute, other times as opportunity. They referred to it as a substitute when they used technology because there was no other option. For instance, when participants described working or socializing, which they could not do in person due to social-distancing restrictions. Mostly, these descriptions of using technology as a substitute carried a negative weight, where technology could not fulfill the needs replacing physical interactions, and one could assume that this is not what participants expected from technology-based interactions. These unexpected negative experiences were predominantly more robust if participants described technology's practical aspects. On the other hand, when participants referred to technology as to opportunity, they still had other options, for instance, they found an opportunity of having an online professional skills course that is facilitated with technology, instead of the burden of going to a course at a local college/university, and their experiences seemed to be more predictable and carried positive weight. Perhaps this is because participants' expectations of using technology in this scenario lead to expected consequences.

Thus, we propose to discuss the results of our study in the context of technology expectations, use, and consequences that the technology leads to, as shown in Figure 8. Usually, people begin using technologies with certain expectations, presumably positive–expecting that technology might help achieve explicit goals, complete tasks, or similar. However, technology's consequences do not always correspond to such expectations. They may rely on how technology was used to perform particular activities–depending on whether it is substituting certain real-life activities or is it only an opportunity to find a solution for a given activity. We define technology as an opportunity as a choice given to people, i.e. people can decide to use technology but can also complete the same activity differently (e.g. reading e-books vs. reading paper books). We define technology as a substitute when people have a minimal choice or no choice–when they are forced to use technology instead of other means to perform a specific activity (e.g. an employee must fill in a digital spreadsheet to report work, the paper documentation is not allowed).

Figure 8. Potential relationships between user expectations, use of technology, and its consequences, affecting user values and well-being. The dotted line indicate possible weaker relationship.

The proposed conceptual model (Figure 8) resembles a comparison presented in the research on the effects of the COVID-19 pandemic, showing a negative effect of using media on mental well-being (Chao et al. 2020). Here, the researchers found potentially harmful psychological effects of new media use (e.g. social media) compared to traditional media (e.g. newspapers). To some extent, such findings support our conceptual proposal, implying that when technology substitutes non-digital means, its impact on people is more likely to be negative. Still, we emphasise that some unexpected consequences might result from using technology as an opportunity, and some expected consequences might result from using technology as a substitute. Below we discuss the two uses of technology–opportunity and substitute–and their consequences in the context of value and, thus, well-being.

6.2.1. Technology as an opportunity

When technology is used as an opportunity it means that for some activities, the agreement between expectations and consequences seems to be the most accurate. It is the most prominent in the descriptions of positive experiences with technology, assisting in maintaining well-being. For instance, in the context of socializing, using digital means to communicate with others is appreciated more when communicating with people located far away. The consequence of such communication is to stay close and up-to-date with those whom, typically, one would not be able to meet in person daily. Therefore, the expectation that technology will enable distant communication is met, and such an expected consequence adds value to people's lives. Similarly, in the context of other activities, like learning, working, information seeking, and leisure, the opportunity-like use of technology matches people's expectations, bringing some value and adding to well-being.

Following terminology proposed by Boztepe (2007), the values mentioned above can be described as self-oriented user values. These are extrinsic utilitarian values, such as convenience and ease of access (e.g. working from home and learning online). Moreover, the expected consequences that improve the financial situation directly by enabling work and indirectly by allowing to save time (e.g. less time spent on travel and shopping) can also be treated as extrinsic utilitarian values. Nevertheless, there are also intrinsic emotional values among the positive experiences with technology and the expected consequences when technology is used as opportunity. For instance, having joy with online entertainment, meeting friends online to play games, participating in online events, or self-development (e.g. gaining new skills).

The positive experiences result primarily in the expected consequences of technology-enabled activities. Some of these consequences fit findings from previous research. For instance, the results from research about WFH point to how such a form of work, enabled by technology, allows for better time management and may positively affect well-being, permitting self-development and improvement of household relationships (Gibbs et al. 2021).

Similarly to previous research (Strudwick et al. 2021, Vargo et al. 2021), the present study results imply that people appreciate how different technologies can assist in maintaining mental health. Still, none of the responses indicate that people recognise that health-related technological solutions need more scientific grounds.

Among the present study results are also some differences in comparison to previous findings related to entertainment. For instance, despite the many compliments given to technology in the context of entertainment, unlike in Parker et al. (2021), the respondents of the present study did not seem to appreciate streaming services for their influence on physical activities. Instead, such services are described as mechanisms to keep entertained, develop different interests/hobbies, or learn new skills.

6.2.2. Technology as a substitute

The effects of technology on well-being differ when technology entirely replaces certain activities. The mismatch between user expectations and technology consequences increases and can be even more misaligned due to the practical aspects of technology, such as hardware or software issues and lack of infrastructures supporting technology use. The consequences of technology become unexpected, and as suggested by Boztepe (2007), the value might be created by the purposeful rejection of the use of technologies. Such consequences are, presumably, unexpected and undesired by users. For instance, the descriptions of negative experiences in the present study suggest that people stop using social media or different digital applications because they realise the damaging effects of such technologies on their physical well-being.

Self-imposed technological restrictions or resignation from using technology also result from realizing other potential unexpected consequences, mainly concerning mental well-being. The many descriptions of negative emotions and mental-health-related issues such as depression, anxiety, mindlessness, and noticeable addiction devalue technology. Technology practicalities place extra pressure on mental well-being, furthering negative emotional states, particularly during activities related to digital interactions with other people (e.g. online meetings, connecting with health-care staff, school-related presentations, and examinations). These effects negatively affect users' social significance values, such as impression management, group belongingness, role fulfillment, and utility values (quality and performance) (Boztepe 2007). Similarly, many negative physical health issues have been recognised as unexpected effects of using technology for different activities, particularly the extended use of digital technology that affects vision or causes headaches. It also results in more traditional ergonomic problems related to bad posture caused by prolonged sitting. These health-related consequences affect utility values (convenience–physical compatibility; safety).

The quantitative results indicate that in the context of health, the use of technology did not increase during the pandemic compared to the other contexts. The self-imposed technological restrictions caused by negative health-related experiences described in responses to open-ended questions can be somewhat perceived as confirmatory of such findings. Although the results imply that to mitigate unexpected consequences of technology, people attempt to alter the ways they interact with technologies, the participants did not mention specific technologies that could help maintain a healthier relationship with technology. Perhaps people are unaware of such solutions, or, as suggested by Roffarello and Russis (2021), the traditional lock-out-based applications are insufficient, and there is a need for different technological or non-technological solutions.

Structural and managerial changes could be one possible way to tackle the problems related to the overuse of technologies, particularly in the context of work or learning. For instance, providing people with more freedom around their work/study hours (which recently gained a lot of attention in the context of work, where shortened working weeks are being tested in many countries as a way of overcoming issues of efficiency, stress, and similar (Kuta 2022, Joly 2022)), or designing and distributing tasks that are disconnected from technology (e.g. use of traditional pen and paper instead of a computer, giving students tasks that have to be done outdoors). However, other problems are emerging around using technology in different contexts, for instance, leisure or socializing. Here, technological solutions, other than time-limiting or locking-out applications, should be developed to help users overcome the unexpected consequences of technology use.

Another profoundly concerning unexpected consequence described in the current study is the negativity and growing misinformation omnipresent in different technological channels. Unlike previous research that praised digital communication channels and social media for a positive and supportive role during the crisis (Mark and Semaan 2008, Mark, Al-Ani, and Semaan 2009, Palen and Hughes 2018, Qu, Wu, and Wang 2009), the present results paint a different picture relating more to what (Klein 2020) discussed: adverse effects of social media, misinformation, self-centrism, and digital content leading to social polarization. The increasing negativity in the news and misleading and fearmongering posts on social media–a digital space where users commonly seek joy, entertainment, and relief from daily struggles–all advanced detrimental effects of technology on well-being. These findings suggest that we need better ways and controls over what information is presented to users, particularly on channels that are not dedicated to reporting news, such as social media. The effects of misinformation can be enormous and far greater than ‘just’ negative emotions. They can also directly affect public health, as in the case of health-related information. Past research recognises these issues and proposes solutions to mitigate the spread of such misinformation (van der Linden 2022, Lewandowsky and Van Der Linden 2021). Although service providers have made some technological efforts to regulate the spread of misinformation (e.g. Twitter and its ban on voting-related information), as Lewandowsky and Van Der Linden (2021) noted, to fix misinformation, we must engage many disciplines and treat it as a political problem.

The present study results imply that it is not only the misinformation that causes a problem but also the negativity of information and its overwhelming amount. This issue has not been given much attention in research, and it is challenging to state whether the matter will continue after the pandemic is over. However, some of the comments related to the topic, such as the issue of vulnerable populations that might be more affected by such negative information (especially receiving it from public institutions), suggest a need for a human-centered approach and solutions. Such solutions could personalise the dissemination of certain health-related information.

6.3. Limitations and future work

The present research is not without limitations. First, the participants' sample was broad and did not focus on a specific population. However, the study's exploratory nature and the inclusion of participants with different cultural and geographic backgrounds (beyond the more frequently studied western population) allowed us to assess whether similar experiences with technologies appear among such a wide range of participants. Still, future work could focus on studying specific populations and systematically comparing them to seek potential differences.

Second, we used qualitative inquiry and standardised scales to measure certain attitudes and self-reported behaviors quantitatively. Such an approach might not result in the most reliable and valid findings. Future work could use different methdological approaches; for instance, user diaries could provide more insights into the longitudinal effects of technology, supported by quantitative questionnaires presented over a longer period. Nevertheless, the correlations between the constructs investigated in the present study, and results that, to some extent, correspond with other early literature investigating technology use during the pandemic, imply that the methods used in the study provide reliable results.

Third, the results of the quantitative inquiry about the changes in the use of technology for different contexts are based on self-reported information. Therefore, the answers might not be true-to-life, affecting our findings' reliability. However, tracking participants before and during the pandemic to conduct a comparative analysis of factual data was impossible since the pandemic was not predictable. Moreover, such tracking would have raised serious ethical considerations. Assuming that the quantitative inquiry was not the most essential for our study and all we needed from the participants was an approximate indication of whether their technology use was affected, we accept the self-reported data as a starting point for our qualitative inquiry. Additionally, taking into account social restrictions introduced in many countries and reports that indicate an increase in the use of technology during the pandemic (Pew Research Center 2021, Wallinheimo and Evans 2021, Feldmann et al. 2021), we believe that our data set reflects well the actual use of digital technology.

7. Conclusions

The present study investigated the use of digital technologies in times of crisis in order to gain a better understanding of people's experiences that might have an effect on their (digital) well-being. The results suggest that people perceive their experiences through the lens of different values and associate them with well-being. Although the participants appreciate many digital technologies, such as convenient methods to connect, shop, and perform work- or study-related activities, people report that the increased dependency on technology may bring adverse effects. The experiences with technologies are often described with an emphasis on physical and mental health. They are also emotionally weighted, indicating that people perceive digital technology as an integral part of their lives and recognise its benefits, drawbacks, and shortcomings.

The findings, through the list of positive and negative effects of technology on well-being, present enablers and barriers to technology acceptance. Technology designers could use such knowledge to improve technology acceptance and employment. There is a need for applications that are less detrimental to individuals, considering the different physical and mental constraints that current solutions place on users–technologies that create value. On the other hand, it seems that many functional (e.g. hardware or software) and infrastructural (e.g. Internet connectivity) issues should be resolved to add value to interactions with different technologies. Nevertheless, technology itself might not be sufficient to tackle problems related to digital well-being. The results hint that there might be a need for changes at the managerial level, particularly in the context of work and education. There must be a strive for a balance between the digital and physical worlds. One possible way to achieve it could be through changes in the distribution of tasks and activities that can be done offline and off-screen. Other solutions might be possible, and future research should be conducted to identify them.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 Prolific is a company enabling easy and feasible data collection for research purposes. https://www.prolific.co/about

2 QDA Miner and Wordstat are text analytic tools produced by Provalis. https://provalisresearch.com/products/

Appendices

Appendix 1.

Introduction

A.1. Definition of technology

Many of the questions included in this survey are about the use of technology, especially during the COVID-19 pandemic.

In this study, by technology, we refer to digital devices (e.g. computer, smartphone, smartwatch) and services (e.g. social media, online and offline applications) that allow communicating and connecting.

A.2. Introduction

The use of technology can have positive and negative effects on life. Some people might find technology crucial to achieve their day-to-day tasks or to entertain themselves. Others might be concerned about their use of technology, perceiving it as unnecessary and damaging to their lives. In this section, we want you to tell us about your experiences with technology, considering its use during the COVID-19 pandemic.

Appendix 2.

Technology use questions

A.3. Negative experiences with technology

Participants instructions: Thinking about using technology during the COVID-19 pandemic, could you describe some of the negative experiences that you had with technology during that period? Please provide an example(s).

If you did not have any negative experiences, please write N/A in the text field.

A.4. Positive experiences with technology

Thinking about using technology during the COVID-19 pandemic, could you describe some of the positive experiences that you had with technology during that period? Please provide an example(s).

If you did not have any positive experiences, please write N/A in the text field.

A.5. Changes in the use of technology

Participants instructions: Thinking about the last few months and how you used technology (e.g. apps, devices, videos, portals), please read the statements below. For each statement, select the answer that best describes your behavior over these last few months.

Compared with the time before the COVID-19 pandemic, my use of technology during the pandemic for

• work or education was…

• entertainment was…

• information seeking was…

• health (both mental and physical) was…

• social interactions was…

Responses: Much lower; Lower; About the same; Higher; Much higher.

Appendix 3.

Attitudes and behaviors during the pandemic

A.6. Introduction text

Thank you for sharing your experiences with technology during the pandemic.

On the next pages, we will ask you some questions about yourself, your attitudes, and your behaviors during the pandemic. Please think about yourself as you are, not as you wish to be. There are no right or wrong answers; please be as honest as you can when you answer.

A.7. Perceived isolation: loneliness

Participants instructions: How often do you…

• Feel that you lack companionship?

• Feel left out?

• Feel isolated from others?

Responses: Hardly ever; Some of the time; Often.

A.8. Coping

Coping

Participants instructions: Thinking about yourself during the pandemic, to what extent the following sentences are true

• Support seeking

  • – I've been getting emotional support from others

  • – I've been getting help and advice from other people

  • – I've been comfort and understanding from someone

  • – I've been trying to get advice from other people about what to do

• Acceptance

  • – I've been looking for something good in what is happening

  • – I've been accepting the reality of the fact that it has happened

  • – I've been learning to live with it

  • – I've been thinking hard about what steps to take

• Disengagement

  • – I've been saying to myself ‘this isn't real’

  • – I've been giving up trying to deal with it

  • – I've been refusing to believe that it has happened

  • – I've been giving up the attempt to cope

• Active coping

  • – I've been turning to other activities to take my mind off things

  • – I've been concentrating my efforts on doing something about the situation I'm in

  • – I've been taking action to try to make the situation better

Responses: Not true at all; Rarely true; Sometimes true; Often true; True nearly all the time.

A.9. Ad hoc questions

(1)	During the pandemic, have you bought any new technology? [No, Yes (please specify)]
(2)	During the pandemic, have you experienced a lack of a certain technology? [No, Yes (please explain why)]
(3)	During the pandemic, have you followed recommendations given by the authorities (e.g. a national recommendation regarding social distancing) aiming at mitigating COVID-19 spread? [No, Yes] If No: Which of the following reasons influenced your decision to do not to follow recommendations aiming to stop the spreading of the COVID-19 pandemic? (You can select multiple answers.) [I am already protected against the virus; My life circumstances (e.g. work) did not allow me; I do not care/I'm not afraid; Other (please specify)]

Appendix 4.

General attitudes and behaviors

A.10. Introduction

Thank you for telling us about your attitudes and behaviors during the pandemic.

On the next pages, we will ask you some questions about yourself, your attitudes, and your behaviors in general. Please think about yourself as you are, not as you wish to be. There are no right or wrong answers; please be as honest as you can when you answer.

A.11. Bounce back

Thinking about yourself in general, please indicate to what extent the following statements are true. [Not true at all; Rarely true; Sometimes true; Often true; True nearly all the time]

• I tend to bounce back quickly after hard times

• I have a hard time making it through stressful events

• It does not take me long to recover from a stressful event

• I usually come through difficult times with little trouble

• I tend to take a long time to get over set-backs in my life

A.12. Life satisfaction

Thinking about yourself in general, please indicate to what extent the following statements are true.

[Not true at all; Rarely true; Sometimes true; Often true; True nearly all the time]

• I like how my life is going

• If I could live my life over, I would change many things

• I am content with my life

• Those around me seem to be living better lives than my own

• I am satisfied with where I am in life right now

• I want to change the path my life is on

A.12.1. Demographics

(1)	How would you describe your gender? [Male; Female; Other; Prefer not to answer]
(2)	What is your age? [drop-down selection]
(3)	Do you live alone? [No; Yes]
(4)	What is your country of residence? [drop-down selection]
(5)	What is your employment status? [Employed for wages; Self-employed; Out of work/Unemployed; A student; A student with a salary; Retired; Unable to work; Lost work because of COVID-19; Other]