RESEARCH QUESTION 1:

 

Changes in Mental Health Symptoms

Methods Notes: Eligible studies must report changes in symptom levels, proportion of participants above a cutoff threshold, or proportion of participants who change by a pre-defined magnitude (e.g., minimal clinically important difference) across a delineated COVID-19 related event. This could include comparisons of pre-COVID-19 and COVID-19 symptoms, symptoms at the initiation of the outbreak to the peak, or symptoms during highly restrictive isolation periods to subsequent periods, for instance. Studies with < 100 participants are excluded.

 

We are not including cross-sectional studies that report percentages of participants with scores above cutoff thresholds on commonly used symptom questionnaires. Conclusions that can be drawn from that type of data about mental health effects from COVID-19 and clinical implications, however, are limited, and, per our protocol, we have not included those studies. This is because percentages of people who score above a threshold on standardized questionnaires vary, sometimes dramatically, between populations, even in normal times. For example, the percentage of participants with scores of at least 10 on the Patient-Health Questionnaire-9,[1] a commonly used measure of depressive symptoms, in large, randomly selected, regional or national general population samples, has been reported as 4% in Hong Kong (N = 6,028);[2] 6% in Germany (N = 5,018);[3] 7% in Shanghai, China (N = 1,045);[4] 8% in the United States (N = 10,257);[5] 8% in the province of Alberta, Canada (N = 3,304);[6] 11% in Sweden (N = 3,001);[7] and 22% in Jiangsu Province, China (N = 8,400).[8] Even within populations from the same region, the percentage can vary dramatically depending on sample characteristics. In Jiangsu Province, for example, the percentage among rural residents (32%) is twice that of urban residents (16%); it is also several times higher for older adults (25% for 55-64 years; 87% for ≥ 65 years) than for young adults (8% for 18-34 years).[8] Further complicating interpretation when there is not a time-based or other relevant comparator, percentages from symptom measures such as the PHQ-9 tend to dramatically overestimate prevalence that would be obtained from validated methods for ascertaining prevalence of mental health disorders, and there is too much heterogeneity between samples in the difference to correct for this statistically.[9]
 
Summary of Results: Only one study, which included 209 undergraduate students from Switzerland, has reported mental health symptoms during COVID-19 compared to previously. In that study, symptoms of depression increased by 0.53 (0.33 to 0.72) standard deviations, stress by 0.40 (0.20 to 0.59), loneliness by 0.29 (0.10 to 0.49), and symptoms of anxiety by 0.17 (-0.02 to 0.37).

 

Comment: Among university students for whom social relationships are likely highly valued and for whom risk of complications from COVID-19 is generally lower than among other adults, symptoms of depression increased substantially more than anxiety. It will be important to understand to what degree this finding is replicated in other university students and whether anxiety is relatively more important in more vulnerable populations. 
 

References:

1.    Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606-613.
2.    Yu X, Tam WWS, Wong PTK, Lam TH, Stewart SM. The Patient Health Questionnaire-9 for measuring depressive symptoms among the general population in Hong Kong. Compr Psychiatry. 2012;53:95-102.
3.    Kocalevent RD, Hinz A, Brähler E. Standardization of the depression screener Patient Health Questionnaire (PHQ-9) in the general population. Gen Hosp Psychiatry. 2013;35:551-555.
4.    Wang W, Bian Q, Zhao Y, et al. Reliability and validity of the Chinese version of the Patient Health Questionnaire (PHQ-9) in the general population. Gen Hosp Psychiatry. 2014;36:539-544.
5.    Cao C, Hu L, Xu T, et al. Prevalence, correlates, and misperception of depression symptoms in the United States, NHANES 2015-2018. J Affect Disord. 2020;269:51-57.
6.    Patten SB, Schopflocher D. Longitudinal epidemiology of major depression as assessed by the Brief Patient Health Questionnaire (PHQ-9). Compr Psychiatry. 2009;50:26-33.
7.    Johansson R, Carlbring P, Heedman A, Paxling B, Andersson G. Depression, anxiety and their comorbidity in the Swedish general population: point prevalence and the effect on health-related quality of life. PeerJ. 2013;1:e98.
8.    Lu S, Reavley N, Zhou J, et al. Depression among the general adult population in Jiangsu Province of China: prevalence, associated factors and impacts. Soc Psychiatry Psychiatr Epidemiol. 2018;53:1051-1061.
9.    Levis B, Benedetti A, Ioannidis JPA, et al. Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: an individual participant data meta-analysis. J Clin Epidemiol. 2020;122:115-128.

CHARACTERISTICS

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Characteristics 

OUTCOMES

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Study Outcomes

RISK OF BIAS

Study Quality

Assessment

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STUDY CHARACTERISTICS

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*Abbreviations: CES-D= Center for Epidemiologic Studies Depression Scale; GAD-7= Generalized Anxiety Disorder; PSS= Perceived Stress Scale; ULS-9= University of California, Los Angeles (UCLA) Loneliness Scale

RISK OF BIAS

 

GRAPHS

 

Please contact us if you identify an error or if we have not included an eligible study

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