We found prospective associations between aspects of computer use and several mental health outcomes in this population-based sample of young adults. Some of the associations were enhanced in interaction with mobile phone use. A major strength of the study is its longitudinal design, with exposure assessed among symptom-free participants prior to outcome assessment. (Extra analyses, including also participants with symptoms at baseline and adjusting for baseline health, gave results in the same direction as the presented results, although with lower PRs). However, the latency period in our study is fairly long (1 year) and we have no information about the exposure and mental health outcomes in the latency period. The mental health symptoms are common in the population and may come and go in the latency period. Hence, the time span between measurements may not be optimal for assessing possible effects of the exposure on mental health. For example, it is possible that long-term exposure is needed to develop, say, depression, or that a short-term exposure/short latency period is relevant for perceived stress.
The results were not consistent for all outcomes or for both men and women. For example, for men, hours spent on general computer use was a risk factor; by contrast, for women, it was the intensity of use, i.e., using the computer without breaks. The mental health outcome that seemed most affected for men was sleep disturbances, while for women, a more general pattern occurred.
Effects of computer exposure on perceived current stress at follow-up were mostly seen in parallel with sleep disturbances. This could be expected since the current stress item actually encompasses sleep problems. We have not assessed the relationship between the different mental health outcomes or pursued possible comorbidity within the study. For example, we do not know if other mental health symptoms were present among those participants who were symptom-free in the outcome concerned in the specific analysis. Sleep disturbances can be a first step towards depression (and is a diagnostic criterion for depression, according to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM IV)). For example, in one study of young adults
, sleep disorders was a predictor of major depression onset with an odds ratio of nearly 4. It is possible that those who developed symptoms of depression in our study already had sleep disturbances at baseline.
With regard to inconsistency of results, there was even a negative association between high email/chat use and stress among the men (while the association was positive for the women), implying that men who communicated via the computer more than 2 hours per day had less than half the risk to perceive stress a year later, compared to low users. On the other hand, at the same time, they had an almost double risk for developing sleep disturbances. There is of course a risk of chance findings when performing multiple tests, as in this study. However, the variables we tested were not chosen at random, and the results are in part supported by a previous study in a university sample of young adults
, where, e.g., high chat use and high email use (as separate variables) were associated with symptoms of depression in women.
It has been claimed that women, more than men, use the computer for communication purposes
. In our study, men and women reported almost the exact same levels of email/chat use It is possible to develop and maintain large social networks via email, SMS, Facebook, web forums, and other social aspects of ICT. The positive effects of the social aspects of ICT use are often emphasized (e.g., among the subjects participants in
). Social support is a well-known factor that both promotes health and buffers negative effects of psychosocial strain
[36, 37]. Interestingly, there seemed to be little or no association between hours spent emailing or chatting and perceived social support in our study. It should be noted that the study was carried out before Facebook (and other networking services) became a widespread and popularly used application. In future studies, besides including social media use, it should be taken into consideration that social media as well as emails are increasingly accessed via the mobile phone and other portable devices, and developments seem to be towards an ever-increasing accessibility.
The email/chat use variable in our study concerned leisure use. Email use in work life can also induce stress. In a study among employees in an engineering company
, time spent emailing was associated with feeling overloaded, and the overload was independent of the hours worked. While participants spent time on other activities their emails accumulated, and email use also implied interference between work and private life. It was concluded that emailing became a symbol of stress, as it seemed to be experienced as stressful regardless of the amount of work it generated, and even made the participants overlook other aspects of work that contributed to overload
Social isolation is another possible consequence of high computer use, and a negative loop has been suggested
[11, 23]. Morahan-Martin and Schumacher
 found support for the position that loneliness leads to increased Internet use, while Caplan
 concludes that social anxiety (rather than loneliness) explains the preference for online social interaction, because of benefits in comparison to face-to-face communication. Such benefits, according to the author, include having control of self-presentation, phrasing, and the speed of interaction, and therefore feeling safer and more confidence than during interactions “in real life.”
Addiction to the Internet has been suggested as a possible mental health risk factor, but was not assessed in the present study. In a Norwegian cross-sectional adult population sample
, the prevalence of Internet addiction was 1% and that of at risk users was approximately 5%. Problematic Internet use (addicted and at risk users) was more common among men and younger age groups, and was also associated with self-reported sleeping disorders and depression.
Computer gaming was more common among the men than the women in our study (as in other studies (e.g.,
). Only a few percent of the women played games more than 2 hours per day, and playing 1–2 hours per day almost doubled the risk of symptoms of depression among the women. This was, however, the only risk category in the analysis of computer gaming. Computer gaming may, on the other hand, be a way of coping with stress. In a study of online game players
, playing computer games in the workplace was associated with recovery experience. By contrast, playing long hours and at night may have detrimental effects. In a population of Internet game players, habitual gaming at night was related to an increase in depression scores in adolescents (13–17 years) and emerging adults (18–22 years), though not in the group defined as young adults (23–30 years)
. The association with depression was independent of total time spent playing, and gaming at night was not related to sleep problems. However, the study was cross-sectional, which limits interpretation of causality. In a laboratory study
, computer gaming before going to bed increased sleep latency and heart rate, and decreased subjective sleepiness and rapid eye movement (REM) sleep, compared to controlled conditions. Getting stuck behind the screen and thus losing sleep was reported as a problem in our interview study
 and was the basis for constructing the variable CU causing lost sleep, which also turned out to be a risk factor for several mental health outcomes including reduced performance, for both men and women. It may be argued that the variable involves circular reasoning, since it encompasses lost sleep as part of the exposure, which at the same time may be considered an outcome.
High ICT use can mirror a hectic lifestyle with high demands (extrinsic as well as intrinsic). It can mirror a lifestyle with lack of recovery, and have potential effects on sleep. Moreover, it is possible that ICT use contributes to a sedentary lifestyle. A sedentary lifestyle can have negative effects on mental health, while physical activity has positive effects on mental health and is acknowledged as a possible complementary treatment for depression and stress-related disorders
[43, 44]. A review suggests that sedentary behavior, including TV viewing and computer/Internet use, is associated with an increased risk of depression
. However, the possible role of physical activity was not assessed in the present study.
There are several limitations in the study, which need to be considered, for example the inconsistencies in the results, as discussed above. The study was performed in a population-based sample of young adults, which is one of its strengths. However, caution must be taken when generalizing the results. The study suffered from a high dropout rate, as is common in questionnaire studies administered in the general population (and probably more so among young adults), resulting in, e.g., women and native-born Swedes being overrepresented in the study group. It is possible that ICT exposure in the study group differs from that of the source population. There is probably a healthy participation selection bias in the cohort, which may be further enhanced when excluding participants with symptoms at baseline before analysis, as the remaining participants might differ from the source population in several aspects including health and resilience. We did adjust for potential confounding by occupation, educational level, and relationship status. However, this was done only at baseline and situations may have changed during the latency period, which will not have been accounted for. Furthermore, we adjusted for potential confounding in all analyses, even though all confounders were not relevant in all analyses. Moreover, geographical confounding may be present because half of the source population was from one region of Sweden and the other half was from the rest of the country. Gender bias was eliminated by separately analyzing men and women.
There are several limitations in using a questionnaire to collect information on exposure and health aspects. Recall bias and recall difficulties are most likely present. Agreement between self-reported and registered exposure clearly was low in one validity study concerning computer use
 where more than 80% of respondents misclassified their computer use, with almost all respondents overestimating their use. Perhaps in a future study, we would want to use objective exposure assessment via technical registration, rather than self-report.
Some of the mental health outcomes used in the study were not validated (sleep disturbances and reduced performance due to stress, depressed mood or tiredness), including the social support variable, which is a limitation of the study. It is important to point out that the study concerns subjective symptom reports and not actual mental disorders or diagnoses. The prevalence of reported depressive symptoms was alarmingly high in our study group; approximately 50% of the men and almost 65% of the women confirmed at least one of the two depressive items. Following the suggested PRIME-MD procedure
[29, 30], a predictive power of 33%
 would imply that about 20% of the study group was clinically depressed. However, the prevalence of depression in a population such as the one included in this study is most likely lower than in primary care populations. For comparison, the 1-month prevalence of depression among Finnish young adults (20–24 years of age) was 9.6%
. Suspecting that the instrument would be too sensitive for our population, we chose to adapt the analysis accordingly, expecting that the two-item outcome would have higher specificity than if following the suggested procedure.
The computer use variables based on time spent at the computer in our study did not permit us to evaluate extreme use, since the cutoff for the highest category of general computer use was 4 hours per day, which was the time that almost 40% of the men and 30% of the women spent on the computer. The cutoff for the high category in email/chat use and computer games was 2 hours per day. It is possible that more extreme exposure is more hazardous to health than the tested exposures and having more categories with higher cutoffs may have enabled a more detailed dose–response analysis. Perhaps the variables concerning intensity of use (i.e., CU without breaks, and CU causing lost sleep) can reflect a more extreme and, possibly, destructive use, than those concerning mere hours of use. Also, it is important, though difficult, to keep up to date with advances in technology and applications, and to create items that sufficiently capture relevant exposure, especially in longitudinal studies.
Aspects of ICT use can contain risk factors for mental wellbeing among young adults, and may be markers for (other) mechanisms associated with mental health risks. Consequently, it seems desirable to support healthy use of modern technologies in order to prevent possible destructive uses or effects, since ICT is an ever-increasing part of daily life, at work, at school, and at leisure. Since sleep and recovery are essential for maintained health, further studies could focus on mechanisms relating ICT use to sleep disturbances, to deepen our understanding and develop meaningful and evidence-based intervention programs.