Table 1.
Study characteristics and findings
| Author name, country, population, and sample size | Type of mental health and measurement of tool | Results | Result by sex | Association |
|---|---|---|---|---|
| Lin et al.[24] Iran Young adult n=1078 (Male=628, Female=450) | 1. Psychological Distress (HADS) 2. Insomnia (ISI) 3. Problematic Social Media Use (BSMAS) 4. Fear Of Covid-19 (FV- 19S) 5. Covid- 19 Misunderstanding (SELF DEVELOPED) |
Mean (SD) 1. Psychological distress=19.16 (7.84) 2. Problematic social media use=17.15 (4.86) 3. Fear of Covid=10.28 (4.45) 4. Covid 19 misunderstanding=2.18 (1.02) 5. Insomnia=9.25 (5.86) (All P<0.01) |
1. Problematic media use was associated with psychological distress (β=0.375) and insomnia (β=0.095). 2. Psychological distress associated and triggered by fear of Covid- 19 and Covid- 19 misunderstanding 3. Insomnia induced by fear of covid-19 |
|
| Zakout et al.[25] Saudi Arabia n=215 (Male=129, Female=86) | 1. Stress, Anxiety and Depression (DASS-21) | 1. Most of the participants (69.3%) using social media as a primary source of information. 2. Prevalence: Stress (37.67%) and depression (36.74%) were most frequent issue as compare to anxiety (20%) 3. Mean (SD): Depression=8.39 (0.629) Anxiety=4.09 (0.416) Stress=9.91 (0.656) |
Anxiety: Female (30.23%) >Male (13.17%). Stress: Female (54.65%) >Male (26.35%) | 1. Anxiety level is high in daily covid 19 news followers as compared to non-daily followers (9.61% vs. 3.60%) 2. Most of the (55.8%) participants felt media coverage creates stress and anxiety among them. |
| Hou et al.[26] China n=3063 (Male=1327, Female=1736) | 1. Depression (PHQ-2) 2. Anxiety (GAD-2) 3. Resilience To Stress (CD-RISC-10) 4. Perceived Stress (10 POINT ITEMS SCALE) |
1. Source of information: Social media - 95.89% Traditional media-4.11% 2. Total Prevalence: Depression- 14.14% Anxiety- 13.25% |
Prevalence: 1) Depression- Males (14.92%)> Females (13.52%) Anxiety: Males (21.21%) >Females (14.04%) | 1. Age, marriage status, occupation, adaption, resilience and stress associated with depression. 2. Marriage, education, health status, time on covid 19 related information, adaption, resilience and stress associated with anxiety |
| Yang et al[3] China n=3,159 (Female=1,611, Male=1,548) | 1. Life Satisfaction (MHQ) 2. Sense of Adequacy, Depression, Anxiety (GHQ-20) 3. Social Media Activities (SELF DESIGNED ITEMS) 4. Emotion Regulation Strategies (SELF DEVELOPED) |
1. Over half of the participants use the internet more than 6 hours for COVID-19 news. 2. Lowlife satisfaction level-2.7% 3. Low sense of adequacy- 5.1% 4. High depression level-6.8% 5. High anxiety level-7.4% |
1. Between life satisfaction and COVID-19 online discussion (β=-0.295), social media judgment (β= -0.395), Positive COVID-19 information sharing (0.189). 2. Between depression and Social media dependence (0.776), Social media self-expression (0.340), COVID-19 information Sharing (-0.340), feeling toward social media (-0.833). (All values are at the level of P<0.001) 3. COVID-19 information sharing, feeling toward COVID-19 information, and feelings toward social media interaction had negative relationship with anxiety (-0.454, -0.365, -0.630) |
|
| Majeed et al.[14] Pakistan n=267 (Male=177, Female=90) | 1. Problematic Social Media Use (BFAS) 2. Fear of COVID-19 (7-item scale developed by Ahorsu et al.) 3. Mindfulness (MAAS) 4. Depression (PHQ- 9) |
Prevalence of depression: Minimal- 0% Mild- 3% Moderate- 19.10% Moderately severe- 42.69 Severe-35.21% | Correlation: 1. Problematic social media usewith fear of Covid 19 (r=0.38), depression (r=0.41) 2. Mindfulness of employee negatively correlated with problematic social media use (r=-0.22), fear of COVID-19 (r= -0.27), and depression (r= -0.12) 3. Fear of COVID-19 positively correlated with employee depression (r=0.45) |
|
| Brailovskaia et al.[27] Germany n=501 (Female=383, Male=118 Italy n=951 (Female=737, Male=214) | 1. Stress Symptoms (DASS-21) 2. Burden caused by COVID-19 (6 ITEM SCALE) |
In both countries, most of the participants use official government sites as the source of information (Germany=74.3%, Italy=75.3%) Social media use (Germany=49.3%, Italy=59%) | Germany: Social media usepositive correlated with stress symptoms (r=0.128, P<0.01) And Burden (r=0.132, P<0.01) Italy: Social media use positively co related with stress symptoms (r=0.131) and burden (r=0.136, P<0.01) | |
| Radwan et al.[28] Gaza Strip, Palestine n=942 (school students) (Female=620, Male=322) | 1. Demographic Characteristics 2. Social Media Platform 3. Effect of Social Media Panic (Questionnaire Developed by Ahmed and Murad) |
1. Facebook is mostly used application among students (81.8%) 2. Most frequently topic seen, read, watch and heard are health news (56.2%) 3. About 76.4% of the participants thought that posting more information related to COVID-19 on social media has spread panic among individuals. |
Female students had a higher likelihood than male students to use their face book platform to get news about COVID-19. | Significant association of gender and age with the type of social media used to get information about COVID-19 |
| Sharma et al.[29] India n=320 (Male -141, Females - 179) | 1. Use Of Mass Media 2. Psychological Health 3. Physical Health 4. Social Health 5. Minner Mental Health (Self-Questionnaire developed using Google Form) |
1. Majority of participants were using television and social media for COVID-19 news 2. 27.81% of respondents felt anxious and nervous after watching the COVID-19 news 3. 38.75% of the respondents are dissatisfied with their sleep during the COVID-19 period. 4. 31.9% participants thought that there is big difference between news and reality. 5. 29.8% thought that media only gives us stress due to continuous. |
Correlation 1. Between hours spend on social media for COVID news and anxiety, r=0.54, P = <0.01 2. Between hours spend on social media for COVID news and stop worrying, r=0.41, P≤0.01 3. Between hours spend on social media for COVID news and quality of life, r=0.48, P = <0.01 |
|
| Zaho et al.[30] China n=512 college students (Female -320, Male- 192) | 1. Social Media Use (Assessment tool developed by Lin et al.) 2. Covid 19 Stressor (10-item checklist developed by main et al.) 3. Negative Effect (PANAS) 4. Secondary Traumatic Stress (STSS-SM) 5. Depression (PHQ-9) 6. Anxiety (GAD -7) |
1. Social media use was positively related to negative effect (r=0.12), depression (r=0.10), stress (r=0.14) and anxiety (r=0.10) 2. Online media use positively correlated with stress r=0.10 3. Disaster-related social media use is negatively associated with mental health. |
1. Association of social media use with stress (β= 0.18, p<.001) depression (β= 0.11, P=0.019) and anxiety (β= 0.12, P=0.014) 2. Participants who spent more time on social media reported more mental health problems. |
|
| Ahmad M et al.[14] Saudi Arabia n=371 (Male -272, Female-99) | 1. Anxiety (GAD-7) 2. Depression (CES-D-10) 3. Loneliness (6 ITEM DJGLS) |
1. Low level of education had less exposure to social media than higher education. 2. Prevalence: anxiety, depression and social isolation which was 47.82%, 47.57% and 46.42% respectively. 3. Frequent exposure to social media had a higher level of anxiety, depression and social isolation as compared to less exposure. |
1. Anxiety, depression and social isolation were low among males. 2. Social media exposure was higher among women (77.77%) than men (73.16%), higher among married (71.23%) than unmarried participants (51.97%). |
1. Correlation between social media exposure and anxiety, depression, and social isolation were 0.368, 0.355 and 0.342 respectively. (All were significant at P 0.01) 2. Exposure to misinformation via social media has a significant positive relationship with anxiety, depression and social isolation. |
| Gao J et al.[31] China n=4872 (Male=1560, Female=3267) | 1. Depression (WHO-5 Well-being Scale) 2. Anxiety (GAD - 7) |
1. Participants with low education had a lower frequency of social media use as compared to higher education. 2. Prevalence- Depression 48.3%, Anxiety 22.6%. Combination of depression and anxiety 19.4%. 3. Unmarried participants had low depression than a married one. |
Social media use frequency. Men=78.4% Women=83.8% | Social media use were positively associated with high odds of anxiety (or=1.72, 95% CI=1.31-2.26) |
| Liu. M et al.[32] China n=4991 (Female -2514, Male - 2477) | 1. Anxiety (SAS-20) | 1. Anxiety levels: Normal=79.4%, mild to moderate anxiety=14%, moderate to severe=5.1%, severe anxiety=1.5%. 2. Participants who knew someone infected with COVID-19 or those who lived within the neighborhood with COVID-19 cases also experience a high level of anxiety. |
1. Education associated with anxiety (β = 0.04, P= < 0.01) who have higher education reported more anxiety 2. Age negatively associated with anxiety, (β = -0.14, P<0.001) 3. gender and income were not associated with anxiety |
|
| Bendau et al.[33] Germany n=6233 (Female -4387, Male - 1793) | 1. Anxiety (DSM - 5 Severity major for specific phobia adult scale) 2. Depression (PHQ -4) |
1. Average daily social media use was 2.40±2.01 h. 2. Mean frequency of media consumption was 7.23 times per day. 3. Participants who reported the use of official sites as a primary source of information showed less anxiety and depression. |
1. Daily average time of media consumption was significantly and positively correlated with anxiety. 2. Frequency of media use positively correlated with specific covid 19 related fever, r=0.10, and unspecific anxiety (r=0.09) and depression symptoms (r=0.09) (all values are at the level of P<0.001) |
|
| Liu et al.[34] China n=6233 (Female -4387, Male - 1793) | 1. Media Vicarious Traumatization (VTS) 2. Anxiety (SAS) |
1. 50% of participants Spend, 1-3 hours per day on social media. 2. Participants who stayed alone were significantly more anxious than those who stayed with their family or with a friend/roommate/classmate) 3. Media vicarious traumatization was important mediator between different type of media exposure and anxiety. 4. Commercial media was the one that was most strongly linked to vicarious traumatization followed by oversees media, social media and official media. |
1. Anxiety was positively related to age, r=0.11, P≤0.01 2. Anxiety was negatively related to health conditions r= −0.16, P=0.01 3. Gender, education and socio-economic status are not associated with anxiety. |
HADS=Hospital Anxiety and Depression Scale, ISI=Insomnia Severity Index, BSMAS=Bergen Social Media Addiction Scale, FCV-19S=Fear of COVID-19 Scale, DASS-21=Depression, Anxiety And Stress Scale, PHQ=Patient Health Questionnaire, GAD=Generalized Anxiety Disorder Scale, CD-RISC-10=Connor- Davidson Resilience Scale, MHQ=Multiple Happiness Questionnaire, GHQ=General Health Questionnaire, BFAS=Bergen Face Book Addiction Scale, MAAS=Mindful Attention And Awareness Scale, PANAS=Positive and Negative Affect Schedule, STSS-SM=Secondary Traumatic Stress Scale For Social Media Users, CES-D-10=Centre For Epidemiology Studies Depression Scale, DJGLS=De Jong Gierveld Loneliness Scale, SAS=Self-Rating Anxiety Scale, VTS=Vicarious Trauma Scale