The Impact of COVID-19 Pandemic on Mental Health: A Scoping Review
Liverpool John Moores University, UK in Partnership with UNICAF University
Turks and Caicos Islands Community College, Turks and Caicos Islands
Institute of Nursing Research Nigeria
Lupane State University, Zimbabwe
*Corresponding author Email: josiahblessing141@gmail.comAbstract
Background
This scoping review assessed the COVID-19 impacts on mental health and associated risk factors.
Methods
A systematic literature search for relevant articles published in the period March 2020 to July 2022, was conducted in the APA PsychInfo, JBI Evidence Synthesis, Epistemonikos, PubMed, and Cochrane databases.
Results
A total of 72 studies met the inclusion criteria. Results showed that the commonly used mental health assessment tools were the Patient Health Questionnaire (41.7%), Generalized Anxiety Disorder Scale (36%), 21-item Depression, Anxiety, and Stress (13.9%), Impact of Event Scale (12.5%), Pittsburgh Sleep Quality Index (9.7%), Symptom Checklist and the General Health Questionnaire (6.9% each). The prevalence rate of depression ranged from 5-76.5%, 5.6-80.5% for anxiety, 9.1-65% for Post-Traumatic Stress Disorder, 8.3-61.7% for sleep disorders, 4.9-70.1% for stress, 7-71.5% for psychological distress, and 21.4-69.3% for general mental health conditions. The major risks included female gender, healthcare-related/frontline jobs, isolation/quarantine, poverty, lower education, COVID-19 risk, age, commodities, mental illness history, negative psychology, and higher social media exposure. The incidence of mental disorders increased along with the increasing cases of COVID-19 and the corresponding government restrictions.
Conclusion
Standard assessment tools were used for mental health assessment by the reviewed studies which were conducted during COVID-19. Mental health disorders like depression, anxiety, and stress increased during the COVID-19 pandemic and lockdowns. Various factors impacted the prevalence of mental health disorders. Policymakers need to provide social protective measures to improve coping capacities during critical health events to avoid negative impacts on the population. Further studies should investigate the effectiveness of interventions for reducing the prevalence and risk factors for mental health conditions during a public health challenge.
Background
Article notes
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
None
Introduction
The COVID-19 outbreak was declared a pandemic in 2020, with over half a billion cases and over 6 million deaths by the end of May 2022 (1). The high transmissibility, morbidity, and mortality rate led governments to adopt strict measures such as quarantines, restrictions on social gatherings, travel, and closure of borders, schools, churches, and workplaces which disrupted the lives of many people (2,3). COVID-19-related factors, especially the response measures, induced significant levels of stress among people (4–6). An increase in mental health conditions has been recently observed due to these disruptions and stresses (2,7).
Some review studies have been conducted on the pandemic’s impact on mental health in the general population, including a systematic review by Xiong et al. which used studies conducted before the 18th of May 2020 (8). There is also another study conducted by Hannemann et al., but the study population was limited only to medical staff (9). Another scoping review was conducted on the impact of the pandemic on people with similar mental health conditions (10), however, the review only included evidence and literature from the first year of the pandemic (i.e., 2020). Similarly, a scoping review (11) conducted among children and young people only included evidence from the early stage of the pandemic. Meanwhile, all the studies identified pointed toward an occurrence or expectation of a heightened prevalence of mental disorders during the COVID-19 pandemic.
A study conducted in the United States found that almost half of the study participants experienced high levels of anxiety and stress three months into the COVID-19 pandemic (12). About one-third of the population in the UK likewise experienced high levels of anxiety according to the Office for National Statistics (ONS) (13). In Italy, several people suffered from COVID-19-related stress, severe anxiety, and insomnia (6). Although several primary studies have investigated these mental health conditions, there is a lack of recent scoping reviews to summarise findings on this key concept. Consequently, this review summarises findings on the assessment tools, prevalence, risk factors, and trends of mental health conditions during the COVID-19 pandemic.
Methods
This scoping review was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines (14), and recommendations of the Joanna Briggs Institute Manual for Evidence Synthesis (15), and similar studies for the protocol design (16,17).
Identification of relevant studies
The APA PsychInfo, JBI Evidence Synthesis, Epistemonikos, PubMed, and Cochrane databases were searched to identify relevant articles (Table 1). A final search string with truncations was (mental health* OR mental illness* OR psychiatric situation* OR sanity* OR psychological* OR psychiatric disorder* OR mental health condition* OR mental health disorder* OR mental disease* OR mental stress*) AND (COVID-19 OR COVID-19 pandemic* OR pandemic* OR COVID-19 outbreak* OR lockdown measures* OR Coronavirus* OR SARS-COV2 OR epidemic*) AND (impact* OR effect* OR cause* OR influence* OR result of OR challenge*). In addition, a manual search was done on the references of the most relevant peer-reviewed papers to gather more results suitable for this study (Fig 1).
Inclusion and exclusion criteria
The eligibility criteria for this review considered:
- peer-reviewed papers that focused on the mental health impact of the COVID-19 pandemic.
- primary research studies whose full texts were publicly and freely accessible.
- papers published after March 11, 2020 - when the WHO declared COVID-19 a pandemic.
- papers that were published in the English language.
Data extraction, analysis, synthesis, and reporting
After a thorough full-text assessment and collation of 72 selected relevant articles, data extraction and setting up of the selected bibliography and abstracts was done using Mendeley Cite® software. The abstracts were then examined for key findings which were then charted into a summary table (Table 2). Each study was then critically read to capture more information from the full texts. The findings were collated in Microsoft word documents and then key data was carefully transferred into Excel spreadsheets for further descriptive analysis. Results were then presented in tables and graphs. The information captured author names, country of study, study setting and population, study design, study aims and objectives, mental health assessment tools used, type, risk factors, and prevalence of mental health conditions studied. Where quantitative measurements were used, the numeric data were collated, grouped, and compared according to selected populations and geographical metrics such as gender, age, continents, and countries, and then presented in tables and chats. The risks identified were further summarised in a table (Table 5) and discussed as they relate to the research objectives. An arithmetic mean value was calculated for the prevalence of mental health conditions by taking the arithmetic mean of all the prevalence reported to provide an estimate of the trends of prevalence over time. Various gaps identified were further discussed with necessary recommendations.
Quality appraisal
The Newcastle-Ottawa Scale (NOS) (18) was used to assess the methodological quality of primary studies in this review. For cross-sectional studies, we used a modified version of the NOS, as described by Modesti et al., (19). The modified NOS contains 3 major sections, with a total of 7 categories, which assess representativeness, sample size, non-respondents comparability, risk factor, confounding factors, assessment, and statistical issues. Quality assessment on cohort studies was carried out using a modified NOS for cohort studies (20). It has a total of 8 categories assessing representativeness, selection of non-exposed cohort, exposure, the outcome of interest, confounders control, outcome assessment, and follow-up duration and adequacy graded over 9 stars. The final quality scores for each study were assigned by modifying the scales used in previous studies (18–21): A score of 7 and above denoted a high-quality paper with low risk for bias, 4 – 6 were moderate quality papers with low risk for bias, and scores less than 4 were considered very low-quality papers with high risk for bias (18).
Results
Search results
The initial search of APA PsychInfo, JBI Evidence Synthesis, Epistemonikos, PubMed, and Cochrane databases produced 34,037 results (Table 1). Of these results, 2,016 were primary studies with the accessible full text, out of which 1,672 studies were published between March 2020 – July 2022. The references were initially imported into Mendeley reference management software, where 365 were identified as duplicates and removed, leaving a total of 1,307. The abstracts and titles were screened. A total of 826 papers did not meet the relevance and/or eligibility requirements for the review. The full text of the remaining 481 papers was assessed and 72 papers met the inclusion criteria. and their quality.
Summary of studies
Most studies (95.8%) used a cross-sectional design methodology. A few studies (4.2%) were cohort studies. Three-quarters of the studies had more female participants than males. The total number of study participants was 914,078. Three papers studied multiple countries, but a greater number (32) of the studies were conducted in China (44%), 5 in Italy (7%), 4 each in the United States and India (6% each), 3 in Indonesia (4%), 3 each in Brazil and Saudi Arabia (3% each), and 1 from every other country (Table 3), making up a total of 24 countries spanning 5 continents; Africa, Asia, Europe, and North and South America. The study objectives varied slightly around the mental health of participants during the pandemic, a one-time comparison between different groups, or a time-lapse comparison of mental health statistics before and during the pandemic in a single group. A total of 27 papers were published in 2020, 34 in 2021, and 11 in 2022. Almost all the studies collected data directly in 2020 (68), and 2021 (4), but 5 studies did not report the exact time except for data submission/publication dates.
Mental health assessment tools
In total, 62 mental health assessment tools were used. The most used tools include the Patient Health Questionnaire [PHQ] (41.7%), Generalized Anxiety Disorder Scale [GAD] (36%), 21-item Depression, Anxiety, and Stress [DASS-21] (13.9%), Impact of Event Scale [IES] (12.5%), Pittsburgh Sleep Quality Index [PSQI] (9.7%), Symptom Checklist [SCL] and the General Health Questionnaire [GHQ] (6.9% each). Three studies (4.1%) used a custom-made questionnaire that had the standard elements for the assessment of mental health conditions. The most studied mental health symptom was depression (73.6%) and anxiety (70.8%). Also, some assessed stress (41.6%), sleep issues/insomnia (26.4%), general mental health status (19.4%), general psychological states (13.8%), and post-traumatic stress disorder/symptoms (8.3%). Coping, fatigue, loneliness, and general well-being were also assessed. Specific tools used included PHQ-2/4/8/9 for depression, GAD-2/7 for anxiety, ISI for insomnia, IES/PSS for stress, CD-RISC resilience, PSQI for sleep quality, and DASS-21 as a stand-alone tool to measure anxiety, depression, and stress.
Quality assessment
Using the NOS star rating as shown in Table 3, out of the 69 cross-sectional studies reviewed, 50 (72.5%) were of high quality, and the other 19 (27.5%) and the 3 cohort studies (Table 4) reviewed were of moderate qualities (Fig 2).
Prevalence Rate and Identified Risk Factors Mental Health Conditions
Table 5 represents the compiled risk factors for various health conditions across the studies. Various incident rates were also computed from different studies for mental health conditions, and the minimum, maximum, and arithmetic mean of prevalence was calculated for depression, anxiety, PTSD, sleep disorder, stress, psychological distress, and other studies which used general health conditions for showing the average pattern of prevalence.
Variations in the Incidence of Mental Health Conditions
Some epidemiological differences were observed in different population groups, places, and periods of study.
Demographic Variations in Prevalence of Mental Health Conditions
Variations in the incidence of various mental health conditions among different demographic groups are depicted in Table 6.
Variations in mental health prevalence over time
The prevalence of depression, anxiety, and PTSD were compiled for the studies conducted on them, which were mostly in 2020. Arithmetic means a calculation involving the groping of values over three months intervals, which was carried out on the reported prevalence from January to September 2020. Three months interval was selected because some months did not have any or enough studies conducted on the selected conditions. The resulting pattern showing the average dynamic of the prevalence is summarized in Fig. 3.
Variations across countries and continents
Table 7 shows the maximum, mean, and minimum prevalence of mental health disorders across the assessed five continents. Only one study was found written on some disorders in some continents, while fewer than 5 were found in most other continents per disorder.
In selected eight (8) countries with the highest prevalence records during the pandemic, the chart below (Fig 4) contains the data on the prevalence of depression and anxiety
Discussion
The scoping review describes the prevalence of mental health disorders, the mental health tools used, and the risk factors identified by researchers during conditions during the COVID-19 pandemic.
Mental health assessment tools
All reviewed studies used standard mental health assessment tools (89–93). The popular Patient Health Questionnaire (41.7%), and Generalized Anxiety Disorder Scale (36%) were the most applied tool by researchers in the assessment of mental health conditions. This strongly corresponds to the high number of studies that engaged in the assessment of depression, anxiety, and either stress or PTSD during the pandemic (23,25,28,40,42,94).
Prevalence of mental disorders during the COVID-19 pandemic
Depression, anxiety, and stress were the most studied mental health conditions. Most studies reported a high (prevalence ≥ 50%) vulnerability to these three mental conditions (21, 22, 36, 39, 43, 44, 47, 57, 62, 74, 86) This finding is consistent with previous studies (95, 96).On the contrary, Jörns-Presentati et al., (94), reported a lower prevalence (29.0%) of depression. According to the WHO, the pandemic spiked with a 25% increase in the prevalence of mental disorders worldwide (7,95,96). Indeed, these differences were mostly attributed to the stress of COVID-19 by most of the studies. Some studies, however, reflected closer findings to Jörns-Presentati et al., (94), for mental health challenges with prevalence ranging between 20% and 49% for depression, anxiety, and stress. This included Alshumrani et al., (35), Bella Nichole and Jonathan, (33), Chi et al., (28), Naser et al., (65), Nguyen et al., (64), Simegn et al., (67), Zhang et al., (71), and various other studies. Most studies were conducted before the lockdown and during periods when the lockdown was being relaxed around the world. Some studies also reported a lower prevalence, especially those conducted in places or periods with lower cases of COVID-19 (54,58,75). Public crises can cause mental health disorders to rise way more than is naturally experienced among people, therefore, public health practitioners should be alert to the mental health of people and patients in crises.
Factors associated with mental health disorder prevalence
This study revealed that many risk factors were associated with the presence of mental health mental disorders experienced during the COVID-19 pandemic. Most of the studies reported a higher prevalence of mental health challenges such as anxiety and depression among females who are usually more vulnerable to stress and psychological distress such as PTSD (73,97–99), in line with earlier studies (65,100–105). On the contrary Liu et al (44) and Oginni et al (106) found a higher prevalence of PTSD among males. Pregnant women and lactating mothers also showed a higher prevalence of mental disorders during the pandemic (107).
On the other hand, the higher prevalence of mental health conditions among females may also be attributable to the fact that higher numbers of the COVID-19 frontline workers such as nurses and other categories of caregivers are females who were faced with heightened COVID-19 challenges both at work and home during the pandemic (65,66,68,73,98,99,108,109). This finding is consistent with past studies (71,108,110) which found that health workers were vulnerable to the key risk factors for developing stress, anxiety, depression, and PTSD. Some studies reported that the length of one work experience, training, and support mechanisms helped reduce extreme burnout, psychological stress, and distress (111,112).
Equally noteworthy, people who shared proximity to places with higher COVID-19 cases had a higher level of mental health challenges (22,45,82). This finding is in line with the WHO observation that depression and anxiety disorders were higher in places with higher COVID-19 cases (113,114). This is supported by previous studies that showed that the fear and anxiety associated with the threatening numbers of cases and death in people’s neighborhood was seen earlier to increase the serious risk for mental breakdown (115) since a perceived or actual increase in the risk of exposure to COVID-19 was a major driver for adverse mental health (48,74).
Some studies reported that poor psychosocial support increased the prevalence and severity of mental health disorders among vulnerable population groups such as strictly isolated or heavily quarantined persons (116), individuals who lacked family support or care (117), elderly persons in need of nursing care (49,118), persons at risk of losing their jobs (33), persons without financial and social support (24,30,42,47,54,63,69,77,119), divorced persons (23,65,79), and relatives and guardians of sick persons (84). This finding indicates that social connections are a strong mechanism of survival and stress management for humans. Once this bond is disturbed by any stressors (120,121), such as done by COVID-19 pandemic, the mind is bound to be impacted if no interventions are put in place (8,117,122–125).
A few studies reported that living with a partner and being married were risk factors for mental health disorders, especially for individuals who also had mental or physical health challenges (71). During the Covid-19 pandemic, stressors from work and home were multi-factorial triggers to mental health distress (126,127), just as living with a partner with fears, mental stress, and emotional vulnerability, which was more prevalent during COVID-19, has been linked in the past to the presence of psychological stress (76,121,128).
Several articles found that one’s emotional or psychological state contributed to mental health conditions (52,119,129–133). Positive feelings such as hope, optimism, and self-efficacy were generally associated with better mental health status than helplessness, pessimism, worry/fear, distress, and anxiety (129,131,134,135). Ying Zhang et al. (73), however, reported that participants with higher self-efficacy had an increased risk of mental breakdown, similar to Khalil et al. (52,136), which explained that participants with higher self-efficacy reported having lower assertiveness, which was a stronger predictor of mental illnesses (134,135).
Similarly, one’s socioeconomic status was linked to an increased risk of mental health problems in almost all of the reviewed articles following similar findings (137–139). Sampaio et al., (98), reported a higher risk of depression among healthcare practitioners with higher incomes, which is justifiable looking at the fact that some healthcare workers doing overtime and extra shifts make more money, but at the risk of severe adverse health effects (98,139).
Persons with pre-existing mental and non-mental health issues, especially persons suffering from chronic illnesses, were more prone to higher mental health illnesses than otherwise healthy individuals (140–143), in agreement with the established relationships between health status and mental health (140) by studies such as MacMillan (144) and MHF (145). Mental health challenges among COVID-19 patients were higher than the general population in most of the studies (59,80,146,147), except Alshumrani et al., (35) who found that COVID-19 patients were less likely to suffer from mental health breakdown during the pandemic, which they attributed to factors such as lesser fear of unknown or increased confidence among COVID-19 survivors (35).
Although the impact of specific details of contents people got exposed to were not reported in any studies, some evidence showed that increased social media exposure was linked to an increase in the risk of mental health conditions (148–150). There was, however, no clear conclusion whether social media exposure led to an increase in mental health conditions. While some studies posited that social media can be a force for good when used properly, others suggested that the spread of uncensored content and unverified information would have been the reason behind the higher occurrence of mental disturbances among people with more social media usage (150–152).
Trends in the prevalence of mental health conditions
Using the average values of the data collated the result showed that just as the pandemic grew stronger, the global prevalence of mental health conditions rose sharply from 30.31%, 29.97%, and 31.74% to 41.31%, 39.61%, and 58% for depression, anxiety, and post-traumatic stress disorder respectively (7,95,96,113,147). A decline to 31.83%, 31.03%, and 24.10% was also observed for the three disorders as the cases and restrictions started reducing in various places (33,42,73,87,95,96,113), although the impact continued to linger (95). There were variations in mental health prevalence across different population groups from 24 different countries in Asia, Africa, North America, South America, and Europe (Table 7). The differences observed in countries were mostly related to outbreak severity, degree of government-imposed restrictions, and socioeconomic status of the region (22,60,61,66,85,86).
Variations due to sociodemographic attributes
The females (65), frontline workers (109,110), people who were ill (41,66), who work long hours (68,153), whose job increased their exposure to COVID-19 (48,74), were living in proximity to COVID-19 cases, (22,45,82), were young or older (4,5,35,62,83,84,107,116,118,154–159), had lower economic & education status, weak psychological makeup, and low social supports (142) had higher levels of mental health conditions during the pandemic (7,113,148), which serves as a call to set up protective measures for this population during any interventions.
Geographical variations
Table 7 shows that the highest prevalence of depression and anxiety was in North America, precisely the United States (47), followed by China (39), and Bangladesh (21). Stress and sleep disorders were highest in Asia, especially Thailand (57) and Bangladesh (21) respectively. Also, the prevalence of psychological distress was highest in Brazil (69) which represented South America, while general mental health disorders or conditions showed up more in Africa (87), followed closely by Europe (13,56) (Fig 4). The review found that at the country level, Bangladesh, the USA, and China were at the top of the list for both depression and anxiety during the pandemic (21,43,119).
Gaps in literature
Although COVID-19 and mental health are crucial global issues, most studies were conducted in Asia, with few from Europe, while North & South America and Africa had a very limited number. Based on the inclusion criteria for this review, no relevant articles were found in Australia or Antarctica. This partially limited the ability to draw a clear line on the global prevalence of mental health conditions.
Few studies investigated the impacts of COVID-19 on the mental health of other vulnerable populations, such as students, pregnant women, children, the elderly, and persons with chronic diseases. Few studies examined the specific relationship between government restrictions and mental health conditions. More research is needed to examine these issues in detail to guide future interventions by governments and policymakers.
Conclusion and recommendations
Conclusion
This review found that various standard tools were used to assess mental health disorders during the COVID-19 pandemic. These included the Patient Health Questionnaire, Generalized Anxiety Disorder Scale, 21-item Depression, Anxiety, and Stress, Impact of Event Scale, and Pittsburgh Sleep Quality Index. The prevalence of mental health conditions increased during the COVID-19 pandemic and decreased as the COVID-19 prevalence reduced. Also, the relaxation of the COVID-19 restrictions contributed to a decrease in the prevalence rate of mental health conditions. The review showed that one’s profession, occupation, gender, age, marital status, family relationships, socioeconomic status, access to information, psychological makeup, and longstanding health status, played important parts in the development of mental health conditions during the pandemic. Healthcare workers were more prone to the challenges as they were highly strained and faced by the pandemic than many other professions.
Although the number of articles from each varied, there were observed differences in the reported prevalence of mental health conditions from each continent and between countries assessed. It is clear, therefore, that the pandemic caused a significant rise in mental health challenges across the world which requires critical attention for better local and global health policies and processes management.
Recommendations
- Governments and policymakers in public and private organizations should increase social protection as it is an essential ingredient in helping the public cope with such critical events.
- Efforts should be made towards putting mechanisms in place to mitigate mental health challenges during public health interventions in the future.
- More attention should be paid to providing support and training on how to improve their coping mechanisms during public health challenges.
- Further studies should investigate the effectiveness of interventions for reducing the prevalence and risk factors for mental health conditions in a public health crisis.
- More studies should continue to focus on the trends in mental health conditions, because the COVID-19 disease may have reduced, but the health impacts might linger
- While more studies on health crises relative to public health outbreaks and interventions are needed in Africa, America (North and South), and even Europe on mental, Australia and Antarctica need to be researched or reviewed for similar circumstances.
- Areas such as economic and social well-being, and stress-related illnesses such as hypertension, metabolic disorders, and gastrointestinal diseases which are possibly impacted by the pandemic should be further investigated or reviewed.
Data Availability
This article is a scoping review. All sources reviewed and cited are listed in the reference list of this work. The methods section also has the steps followed in obtaining and screening the articles for review.
Limitations
The review considered articles written in the English language, which may limit the generalizability of the study findings to the non-English speaking regions. The timeframe was also from March 2020 to July 2022, hence all other studies before and after this period will have findings that may support or contradict this study. The review included only open-source articles and did not include any articles that required payments or prior consent before review. This may have also limited the content of this review and the generalizability of the findings.
Abbreviations
- ACE
- Adverse Childhood Experience
- ADQ
- Author Designed Questionnaire
- AIS
- Athens Insomnia Scale
- ASDS
- Acute Stress Disorder
- AUDIT
- Alcohol Use Disorders Identification Test
- BAI
- Beck Anxiety Inventory
- BDI-II
- Beck Depression Inventory-II
- Brief COPE
- Brief Coping Orientation to Problem Experienced
- BRCS
- Brief Resilience Coping Scale
- CDI-S
- Children’s Depression Inventory-Short Form
- CCMH
- Copenhagen Corona-Related Mental Health Questionnaire
- CES-D
- Center for Epidemiologic Studies Depression scale
- CMD
- Common Mental Health Diseases
- CMHDQA-4
- Four-item Common Mental Health Disorder Questionnaire Anxiety subscale
- CSES
- Coping Self-Efficacy Scale
- CD-RISC
- Connor-Davidson Resilience Scale
- CD-RISK-10
- Abbreviated Version of the Connor–Davidson Resilience Scale
- CDI
- Child Depression Inventory
- COVID-19
- Coronavirus Disease 2019
- DAR-5
- Dimensions of Anger Reactions-Revised
- DASS-21
- 21-item Depression, Anxiety, and Stress Scale
- FSS
- Fatigue Severity Scale
- GAD-7
- 7-item Generalized Anxiety Disorder scale
- GHQ-12
- General Health Questionnaire-12
- GPS
- Global Psychotrauma Screen
- HADS
- Hospital Anxiety and Depression Scale
- IES
- Impact of Event Scale
- IES-R
- 22-item Impact of Event Scale-Revised
- ISI
- Insomnia Severity Index
- K-10
- Kessler Psychological Distress Scale
- LCKRS-2
- Long COVID Kids Rapid Survey 2
- MBI
- Maslach Burnout Inventory
- MHC-SF
- Mental Health Continuum Short Form
- MSBS
- Multidimensional State Boredom Scale
- NPI-Q
- Neuropsychiatric Inventory Questionnaire
- PANAS
- Positive and Negative Affect Scale
- PCL
- Abbreviated PTSC Checklist
- PCL-5
- PTSD Checklist
- PC-PTSD-5
- Posttraumatic Stress Symptoms scale
- PCQ
- Psychological Capital Questionnaire
- PHQ-4
- 4-item Patient Health Questionnaire
- PHQ-9
- 9-point Patient Health Questionnaire
- PROMIS
- Patient-Reported Outcomes Measurement Information System
- PSC
- Pediatric Symptom Checklist
- PSQI
- Pittsburgh Sleeping Quality Index
- PSS
- Perceived Stress Level
- PSS-10
- 10-item Perceived Stress Scale
- PSQI
- Pittsburgh Sleep Quality Index
- PSWQ-C
- Penn State Worry Questionnaire for Children
- PTGI
- Post Traumatic Growth Inventory
- SAS
- Self-rating Anxiety Scale
- SCARED
- Screen for Child Anxiety-Related Emotional Disorders
- SCL-90
- Symptom checklist 90
- SCSQ
- Short Coping Style Questionnaire
- SDS
- Self-rating Depression Scale
- SRSS
- Self-Rating Scale of Sleep
- SRQ-20
- 20-item Self Reporting Questionnaire
- STAI-Y
- State-Trait Anxiety Inventory-Form Y
- STATE-A
- Anxiety subsequent to a specific situation
- ULS-3
- 3-item UCLA Loneliness Scale
- ULS-8
- 8-item UCLA Loneliness Scale
- VTQ
- Vicarious Traumatization Questionnaire
- Z-SAS
- Zung Self-Rating Anxiety Scale
Acknowledgments
The first author would like to extend his sincere appreciation to the management and staff of Liverpool John Moores University and UNICAF University for their scholarship support towards his postgraduate studies and to his co-author, Dr. Frances Ncube, for his relentless guidance and contributions. The authors wish to thank Ms. Brontie A. Duncan for proofreading this article. The support and encouragement from Mrs. Felicia Otoboyor, Mr. Ndidi L. Otoboyor, Mr. Oghosa G. Josiah, Miss. Chinelo Uzor, Ms. Doren Francis, and Mr. Joshua Okonkwo are much appreciated.
Funding
None
Conflict of interest
None