| Literature DB >> 35564538 |
Sandra Carvalho1, Catarina G Coelho2, Bruno Kluwe-Schiavon2, Juliana Magalhães2, Jorge Leite3.
Abstract
People with pre-pandemic health conditions are more vulnerable and more likely to suffer greater psychosocial impact due to the current COVID-19 pandemic and the lockdown measures. Thus, the objective of this work was to systematically review the impact of the early stages COVID-19 pandemic on people with pre-existing psychiatric disorders. The search was performed between 23 January and 2 September 2021 in PubMed, PsycINFO, and EMBASE. A total of 4167 published results were identified; however, only 49 were included in this review. Results show that there was considerable heterogeneity among studies, which resulted in a low consensus. However, it seems that the impact of the first stage of the COVID-19 pandemic on psychiatric disorders was two-fold: (1) an overall effect, in which people suffering from psychiatric disorders in general experienced more psychological distress and anxiety when compared to people who had no psychiatric diagnosis, and (2) a condition-specific effect, namely in people suffering from eating disorders and obsessive compulsive disorders. Moreover, the current work highlights that there were also some external factors that were related to worsening symptoms. For instance, unemployment or experiencing work and financial difficulties can be a trigger for greater distress during the pandemic for people with mood disorders, and being alone and in social isolation during the COVID-19 pandemic may actually increase substance use and relapse rates. Further studies are needed to prospectively investigate the long-term effects of the current COVID-19 pandemic on people with (pre)-existing psychiatric conditions and on the onset or deterioration of psychiatric-related symptoms in a larger number of participants, as well as exploring the long-term effects of the current pandemic on mental health.Entities:
Keywords: COVID-19 pandemic; mental health; psychiatric disorders; systematic review
Mesh:
Year: 2022 PMID: 35564538 PMCID: PMC9104538 DOI: 10.3390/ijerph19095140
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Figure 1PRISMA flow diagram for the systematic review detailing the database searches, the number of abstracts screened, and the full texts retrieved for prospective and cross-sectional studies.
Study design and sample characteristics.
| First Author (Year) | Study Categorization | Sample | Healthcare Information |
|---|---|---|---|
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| Yocum et al. (2021) [ | Prospective | - BD: 345 (nr (nr)) | - Participants admitted as outpatient or inpatient in clinical services |
| Zhang et al. (2021) [ | Cross-sectional | - MDD group: 90 (15 (80)) | - Outpatients |
| Carmassi et al. (2020) [ | Cross-sectional | - BD, PTSS: 17 (nr (88)) | - Online/telephone intervention |
| Di Nicola et al. (2020) [ | Prospective | - No psychological distress: 29 (43 (48)); | - Psychopharmacological treatment. |
| Franchini et al. (2020) [ | Cross-sectional | - Euthymic MD: 101 (62 (65)) | - Online/telephone intervention |
| Pinkham et al. (2020) [ | Prospective | - SPD: 92 (43 (54)) | - Outpatients |
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| Rogers et al. (2021) [ | Cross-sectional | - AD: 99 (35 (67)) | - Treatment-seeking patients |
| Plunkett et al. (2020) [ | Prospective | - AD: 30 (39 (60)) | - Outpatients |
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| Alonso et al. (2021) [ | Prospective | - OCD:127 (42 (54)) | - Outpatients |
| Hassoulas et al. (2021) [ | Cross-sectional | - OCD: 254 (nr (nr)) | NA |
| Khosravani et al. (2021) [ | Cross-sectional | - OCD: 300 (36 (59)) | - Treatment-seeking patients |
| Benatti et al. (2020) [ | Cross-sectional | - OCD, worsening: 44 (40 (46)) | - Outpatients |
| Chakraborty et al. (2020) [ | Cross-sectional | - OCD: 84 (nr (76)) | - Outpatients |
| Davide et al. (2020) [ | Prospective | - OCD: 30 (43 (53)) | - Psychopharmacological treatment |
| Matsunaga et al. (2020) [ | Prospective | - OCD: 60 (42 (58)) | - Outpatients |
| Nissen et al. (2020) [ | Cross-sectional | - OCD clinical group: 65 (15 (63)) | - Outpatients |
| Tanir et al. (2020) [ | Cross-sectional | - OCD: 61 (14 (44)) | - Outpatients |
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| Giel et al. (2021) [ | Prospective | - ED: 23 (nr (nr)) | - Outpatients |
| Baenas et al. (2020) [ | Prospective | - ED, worse: 19 (33 (nr)) | - Outpatients |
| Castellini et al. (2020) [ | Prospective | - ED: 74 (32 (100)) | - Outpatients |
| Fernández-Aranda et al. (2020) [ | Cross-sectional | - AN: 55 (24 (89)) | - Pre-pandemic: outpatients |
| Schlegl et al. (2020) [ | Cross-sectional | - Adults with AN: 112 (25 (100)) | - Outpatient, inpatient and online/telephone intervention |
| Schlegl et al. (2020) [ | Cross-sectional | - Inpatients with BN: 55 (24 (nr)) | - Pharmacological treatment |
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| Blithikioti et al. (2021) [ | Prospective | - SUD: 303 (49 (37)) | - Outpatients |
| Chappuy et al. (2021) [ | Cross-sectional(changes) | - SUD: 219(43 (22)) | - Outpatients |
| Lev Bar-Or et al. (2021) [ | Cross-sectional (changes) | - SUD: 92 (40 (38)) | - Outpatients |
| Cousijn et al. (2020) [ | Prospective | - Daily cannabis users: 120 (18–46 (nr)) | NA |
| Martinotti et al. (2020) [ | Cross-sectional | - SUD inpatients: 56 (nr (nr)) | - Outpatients. |
| Yazdi et al. (2020) [ | Cross-sectional | - Abstinent: 37 (51 (35)) | - Outpatient |
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| Becker et al. (2020) [ | Cross-sectional | - ADHD: 118 (17 (35)) | - Pharmacological treatment |
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| Ma et al. (2020) [ | Prospective | - Isolated patients: 30 (43 (60)); | - Inpatients |
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| Mataix-Cols et al. (2020) [ | Cross-sectional | - TS/CTD: 178 (31 (57)) | NA |
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| Cheng et al. (2021) [ | Cross-sectional | - dCBT-I group: 102 (45 (73)) | - Online psychotherapy treatment (CBT) |
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| De Nardi et al. (2021) [ | Cross-sectional | - SSD group: 58 (15 (52)) | - Outpatients |
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| Favreau et al. (2021) [ | Cross-sectional | - GPP: 538 (70 (36)) | - Inpatients |
| Imai et al. (2021) [ | Cross-sectional | - GPP: 425 (53 (53)) | - Outpatients |
| Mergel et al. (2021) [ | Prospective | - CMD: 25–27 (50 (48)) | - Outpatients |
| Ting et al. (2021) [ | Cross-sectional | - GPP: 193 (16–20 (7.3); 21–30 (14.5) | - Outpatients |
| Tundo et al. (2021) [ | Prospective | - No relapse/worsening: 365 (52 (59)) | - Outpatients |
| Vissink et al. (2021) [ | Cross-sectional | - GPP: 189 (40 (46)) | - Outpatients |
| Burrai et al. (2020) [ | Cross-sectional | - GPP: 77 (47 (34)) | - Inpatients |
| Chang et al. (2020) [ | Cross-sectional | - GPP: 414 (46 (44)) | - Inpatients |
| Hao et al. (2020) [ | Cross-sectional | - Psychiatric patients: 76 (33 (37)) | - Outpatients |
| Iasevoli et al. (2020) [ | Cross-sectional | - GPP: 205 (nr (nr)) | - Outpatients |
| Marchitelli et al. (2020) [ | Prospective | - Patients with psychiatric diagnosis: 47 (46 (77)) | - Psychotherapy treatment |
| Muruganandam et al. (2020) [ | Cross-sectional | - SMI outpatients: 132 (34 (52)) | - Outpatients |
| Pan et al. (2020) [ | Prospective | - With psychiatric disorder: 1181 (56 (67)) | - Outpatients |
| Porcellana et al. (2020) [ | Cross-sectional | - GPP: 140 (50 (55)) | - Treatment-seeking patients |
| Zou et al. (2020) [ | Cross-sectional | - Fatigue: 501 (62 (69)) | - Outpatients |
Note: AD, anxiety disorders; ADHD, attention-deficit hyperactivity disorder; AMD, acute mental disorder; AN, anorexia nervosa; BD, bipolar disorder; BN, bulimia nervosa; CBT, cognitive behavioral therapy; CMD, chronic mental disorder; CTD, chronic tic disorder; dCBT-I, digital cognitive behavioral therapy for insomnia; ED, eating disorders; GPP, multiple psychiatric disorders; MD, mood disorders; MDD, major depressive disorder; OCD, obsessive compulsive disorders; OSFED, other specified feeding or eating disorder; PTSS, post-traumatic stress symptoms; SMI, severe mental illness; SPD, schizophrenia or other psychotic disorder; SSRIs, selective serotonin reuptake inhibitors; SSD, somatic symptom disorder; SUD, substance-related disorders; TS, Tourette syndrome; WDC, without diagnosis category; WMD, without mental disorder.
Data collection procedure and assessment time.
| Study ID | Country | Previous Assessments | Data Collection Method | 2020 | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | ||||
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| Yocum et al. (2021) [ | United States | None | - Online | o | o | ||||||||||
| Zhang et al. (2021) [ | China | 2019 | - Telephone/Online | o | |||||||||||
| Carmassi et al. (2020) [ | Italy | None | - Online | o | |||||||||||
| Di Nicola et al. (2020) [ | Italy | Dec 2019 | - Online | o | o | o | |||||||||
| Franchini et al. (2020) [ | Italy | None | - Telephone | o | o | ||||||||||
| Pinkham et al. (2020) [ | United States | 2018 | - T0: Face-to-face/T1: Telephone | o | o | o | |||||||||
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| Rogers et al. (2021) [ | Spain | None | - Online | o | |||||||||||
| Plunkett et al. (2020) [ | Ireland | None | - Telephone/Face-to-face | o | o | ||||||||||
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| Alonso et al. (2021) [ | Spain | None | - Telephone/Online | o | o | ||||||||||
| Hassoulas et al. (2021) [ | United Kingdom | None | - Online | o | o | o | o | ||||||||
| Khosravani et al. (2021) [ | Iran | None | - Face-to-face/Telephone/Online | o | o | o | |||||||||
| Benatti et al. (2020) [ | Italy | None | - Telephone/Face-to-face | ||||||||||||
| Chakraborty et al. (2020) [ | India | None | - Telephone | o | o | ||||||||||
| Davide et al. (2020) [ | Italy | None | - Face-to-face | o | o | o | |||||||||
| Matsunaga et al. (2020) [ | Japan | None | - Face-to-face | o | o | ||||||||||
| Nissen et al. (2020) [ | Denmark | None | - Online | o | o | ||||||||||
| Tanir et al. (2020) [ | Turkey | None | - Telephone/Online | o | o | ||||||||||
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| Giel et al. (2021) [ | Germany | 2017 | - Telephone/Online | o | o | o | |||||||||
| Baenas et al. (2020) [ | Spain | None | - T0: Face-to-face/T1: Telephone | o | |||||||||||
| Castellini et al. (2020) [ | Italy | Dec 2019 | - T0: Face-to-face/T1, T2: Online | o | o | o | o | o | |||||||
| Fernández-Aranda et al. (2020) [ | Spain | None | - Online | o | o | ||||||||||
| Schlegl et al. (2020) [ | Germany | None | - Online | o | |||||||||||
| Schlegl et al. (2020) [ | Germany | None | - Online | o | |||||||||||
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| Blithikioti et al. (2021) [ | Spain | 2019 | - Online | o | o | ||||||||||
| Chappuy et al. (2021) [ | French | None | - Face-to-face | o | o | ||||||||||
| Lev Bar-Or et al. (2021) [ | Israel | None | - Face-to-face | o | |||||||||||
| Cousijn et al. (2020) [ | Netherlands | 2019 | - Online | o | o | o | o | o | |||||||
| Martinotti et al. (2020) [ | Italy | None | - Face-to-face/Online | o | o | o | |||||||||
| Yazdi et al. (2020) [ | Austria | None | - Face-to-face | o | o | o | |||||||||
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| Becker et al. (2020) [ | United States | None | - Online | o | o | ||||||||||
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| Ma et al. (2020) [ | China | None | - Face-to-face | o | o | ||||||||||
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| Mataix-Cols et al. (2020) [ | Europe/North America | None | - Online | o | o | ||||||||||
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| Cheng et al. (2021) [ | United States | 2016, 1017 | - Online | o | |||||||||||
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| De Nardi et al. (2021) [ | Italy | None | - Online | o | o | ||||||||||
|
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| Favreau et al. (2021) [ | Germany | None | - Online | o | o | o | o | o | o | o | o | o | |||
| Imai et al. (2021) [ | Japan | None | - Face-to-face | o | o | o | o | o | |||||||
| Mergel et al. (2021) [ | Germany | 2019 | - Face-to-face | o | o | o | |||||||||
| Ting et al. (2021) [ | China | None | - Online | o | o | ||||||||||
| Tundo et al. (2021) [ | Italy | None | - Face-to-face/Online | o | o | o | o | ||||||||
| Vissink et al. (2021) [ | Netherlands | None | - Online/face-to-face | o | o | o | o | o | |||||||
| Burrai et al. (2020) [ | Italy | None | - Online | o | o | ||||||||||
| Chang et al. (2020) [ | Taiwan | None | - Face-to-face | o | o | o | o | ||||||||
| Hao et al. (2020) [ | China | None | - Online | o | |||||||||||
| Iasevoli et al. (2020) [ | Italy | None | - Telephone | o | |||||||||||
| Marchitelli et al. (2020) [ | Italy | None | - Online | o | o | ||||||||||
| Muruganandam et al. (2020) [ | India | 2019 | - Telephone | o | o | o | |||||||||
| Pan et al. (2020) [ | Netherlands | 2006, 2008, 2010, 2012, 2014 | - Online | o | o | ||||||||||
| Porcellana et al. (2020) [ | Italy | None | - Face-to-face | o | |||||||||||
| Zou et al. (2020) [ | China | None | - Face-to-face | o | o | o | |||||||||
Note: T0, baseline measure; T1, first follow-up; T2, second follow-up. The vertical line indicates the official onset of the pandemic state on 11 March. The bullet points indicate the month in which the data were collected, and the dotted vertical line represents the beginning of the pandemic state on 11 March. o: is used to identify the month of the year.
Studies’ aims and main findings.
| First Author | Aim | Assessment Instruments during Pandemic and/or Lockdown | Main Results |
|---|---|---|---|
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| Yocum et al. (2021) [ | To evaluate the impact of the COVID-19 pandemic and lockdown on individuals with BD, as compared to healthy controls. | Pandemic and lockdown: CIS; GAD-7; PHQ-9; PSQI. | - Both BD patients and heathy controls reported a negative impact of lockdown measures. |
| Zhang et al. (2021) [ | To evaluate the impact of the COVID-19 outbreak at 1 month after the start on the mental health of adolescents with or without MDD. | Pandemic: BDI-II; CRIES-13. | - Adolescents with MDD were more likely than those without MDD to experience severe psychological stress and symptoms of PTSD. |
| Carmassi et al. (2020) [ | To investigate acute PTSS symptoms in patients with BD in a telepsychiatry service. | Lockdown: GAD-7; HAM-D; IES-R; YMRS. | - PTSS and moderate to severe depressive symptoms were reported by 17% of the patients, while severe anxiety was reported by 26%. |
| Di Nicola et al. (2020) [ | To investigate the effects of lockdown on psychological distress perceived in people with MDD and BD. To assess the usefulness of serum 25(OH)D levels as a predictor of distress severity. | Lockdown: clinical interview; K10; biological data: serum 25(OH)D levels. | - A total of 74% perceived a form of psychological distress at the time of the study; 26% reported no likelihood of psychological distress; 31% displayed mild psychological distress; and 43% displayed moderate to severe psychological distress. |
| Franchini et al. (2020) [ | To describe the telephone-based mental illness surveillance on euthymic MD patients to evaluate reactions to lockdown measures. | Lockdown: physical conditions; psychiatric conditions: emotional stressors and unpleasant experiences during the lockdown. | - The main concerns were frustration due to restrictions (76%); fears about infection (54%); financial concerns (46%); anxiety (45%); and low mood (41%). Moreover, about 30% of the participants reported somatization, increased alertness, and insomnia. |
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| Rogers et al. (2021) [ | To examine the association between anxiety sensitivity with COVID-19 worry, functional impairment, and symptom severity in a community sample as compared to people with anxiety disorders. | Pandemic: ASI-3; COVID-19 screening. and symptoms; COVID-19 worry index; COVID-19 functional impairment; COVID-19 anxiety; severity of COVID-19 symptoms. | - Increased anxiety sensitivity was significantly associated with increased COVID-19-related worry, anxiety, functional impairment, and symptom severity. |
| Plunkett et al. (2020) [ | To examine the impact of social restrictions on people with AD. | Lockdown: BAI; HAMA; CGI-I; CGI-S; GAF; Y-BOCS. | - A total of 50% of the participants described a deleterious effect of the COVID-19 pandemic on their mental health; 40% described a deleterious effect pertaining to their levels of anxiety. |
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| Alonso et al. (2021) [ | To investigate the impact of the COVID-19 pandemic on individuals with OCD, as compared to a community sample at an early stage of the pandemic. | Pandemic: clinical interview, Y-BOCS, VAS (depression/ anxiety levels); HDRS. | - Worsening of symptoms in 65% of the patients; 31% of OCD patients showed an increase of more than 25% in their pre-pandemic Y-BOCS scores; 45% developed an obsession related to the risk of getting infected by SARS-CoV2; however, only 10% reported it as being their main obsessive concern. |
| Hassoulas et al. (2021) [ | - To investigate the impact of the COVID-19 pandemic on individuals with OCD. | Lockdown: OCI-R; SHAI; brief COVID-19 impact measure. | - Pandemic-related restrictions impacted mental well-being in 57% of the participants. Moreover, 22% reported impacts in terms of physical health, 10% reported impacts due to their social isolation, and 5% mentioned financial and occupational impacts. |
| Khosravani et al. (2021) [ | - To compare COVID-19-related stress reactions among patients with AD and OCD. | Pandemic: CSS; PHQ-4; FCV-19S; C19P-S; SHAI; VOCI; XS; HCQ-54; OCI-R; OCS. | - Patients with OCD, generalized AD, and panic disorder might have a higher risk for COVID-19 stress syndrome and COVID-19 stress disorder when compared to other ADs. |
| Benatti et al. (2020) [ | - To describe the impact of COVID-19 pandemics in a sample of patients with OCD. | Pandemic: clinical interview. | - More than 1/3 of the sample reported OCD worsening; 30% of the worsening group developed new obsessions and compulsions and 41% re-experienced past obsessions and compulsions; 66% of these patients experienced an increase in avoidance behaviors; 71% had significantly higher rates of pharmacological therapy adjustment; 9% reported suicidal ideation; and 52% reported sleep disturbances. |
| Chakraborty et al. (2020) [ | - To assess the impact of COVID-19 on OCD patients. | Pandemic: interview: changes in symptoms; Y-BOCS. | - Most of the participants did not report any deterioration of symptoms due to the pandemic; 3 of the participants were in complete remission, and 2 were in partial remission. Only 2% of the participants had a >25% increase in the Y-BOCS total score. |
| Davide et al. (2020) [ | - To evaluate changes due to the pandemic in a group of OCD patients that underwent psychiatric treatment before the pandemic period. | Lockdown: Y-BOCS; questionnaire on COVID-19 pandemic and life during the quarantine. | - Out of the 40% of patients that were remitted before the quarantine, 13% relapsed with clinically significant OCD. |
| Matsunaga et al. (2020) [ | - To investigate the acute impact of the COVID-19 pandemic in fully or partially remitted OCD patients. | Pandemic: Y-BOCS. | - A total of 10% experienced increased symptom severity, while 7% had additional or renewed OCD symptoms associated with COVID-19. |
| Nissen et al. (2020) [ | - To examine how children and adolescents with OCD react to the COVID-19 crisis. | Pandemic: self-developed questionnaire on well-being (i.e., perceived changes in quality of life, psychiatric symptoms’ severity, avoidance behaviors). | - Clinical group: 45% reported a worsening of their symptoms, namely, 32% concerning anxiety; 34% concerning depressive symptoms; and 19% concerning avoidance behavior. |
| Tanir et al. (2020) [ | - To investigate the effects of COVID-19-related home confinement on the profile, severity, and exacerbation of symptoms in OCD individuals. | Lockdown: CGI-S; CY-BOCS. | - A total of 54% reported an increase in symptom severity; there was a significant increase in the frequency of contamination obsessions and cleaning/washing compulsions during the pandemic; 34% of the patients reported no change in symptom severity; 11% reported a decrease in CY-BOCS scores; 56% relapsed with obsessive compulsive symptoms; and 31% returned to clinically significant levels of OCD during the pandemic. |
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| Giel et al. (2021) [ | - To investigate ED symptoms, as well as general psychopathology, after the first COVID-19 lockdown in patients with a history of BED. | Lockdown: BDI-II; EDE-Q. | - Comparing the results obtained before and during COVID-19, there was a reduction of 50% in BED and a reduction of 14% in comorbid mental disorder. |
| Baenas et al. (2020) [ | - To assess the level of deterioration in functioning and the factors that impact the adjustment of people with ED to the COVID-19 confinement. | Lockdown: EDI-2; SCL-90-R; TCI-R; YFAS-2. | - A total of 70% of the patients reported concerns related with the confinement; 26% reported non-adaptive reactions; 42% reported anxiety symptoms; and 30% reported depression symptoms. |
| Castellini et al. (2020) [ | - To evaluate the impact of COVID-19 on ED patients, considering the role of pre-existing vulnerabilities. | Lockdown: BSI; CTQ-SF; ECR-R; EDE-Q; IES-R. | - 13% of the patients experienced full remission from baseline to pre-lockdown, and 25% of the patients achieved partial remission. |
| Fernández-Aranda et al. (2020) [ | - The impact of confinement on eating symptomatology; and to explore the general acceptance of the use of telemedicine among people with ED. | Lockdown: CIES. | - AN patients reported less impact on eating symptoms, changes in eating habits and in emotion regulation. Obese patients reported decreased weight, BMI, and changes in eating habits; |
| Schlegl et al. (2020) [ | - To explore effects of the COVID-19 pandemic on ED symptoms and other psychological aspects in former inpatients with AN. | Pandemic: self-developed questionnaire on the overall impact of the COVID-19 pandemic on eating disorders symptoms and general well-being. | - Around 50% of the patients reported a deterioration of their quality of life; 17% indicated no worsening of it; 70% of the sample reported an increase in loneliness, inner restlessness, and sadness; 50% of the patients indicated fears of not being able to stop or control worries and worried that feelings get out of control; 50% of the patients reported that worries were related to infectng others and relapse; and 47% reported increases in family conflicts. No changes were reported in terms of friendships, romantic relationships, or workplace conflicts for 80% of the individuals. |
| Schlegl et al. (2020) [ | - To investigate the impact of the current pandemic on patients with BN. | Pandemic: self-developed questionnaire on the overall impact of the COVID-19 pandemic on ED symptoms and general well-being. | - A total of 49% of the patients experienced worsening of ED symptomatology, while 62% had decreased quality-of-life scores. Moreover, binge eating increased in 47% of the patients, whereas self-induced vomiting increased in 36%. |
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| Blithikioti et al. (2021) [ | - To assess risk factors of adverse mental health outcomes during lockdown in a SUD population. | Lockdown: questions of the ASSIST Screening Test; CTQ-SF; LEC; DTS; BDI; STAI; perception about symptom change due to quarantine measures. | - Increased consumption of: alcohol (13%), cannabis (1%), cocaine (3%), methamphetamine (1%), and sedatives (9%). One participant reported an increase in opioid consumption. |
| Chappuy et al. (2021) [ | - To measure the impact of the COVID-19 lockdown on the addictions of SUD; to examine how anxiety, mood, and sleep are related to consumption; to investigate changes in their condition due to COVID-19. | Lockdown: online questionnaire (all questions were related to the lockdown period in France). | - Increased consumption of: alcohol (29%), cannabis (28%), psychostimulants (36%), heroin (40%), anxiolytics (26%), methadone (14%), and buprenorphine (23%). There was a 49% increase in addictive behaviors. |
| Lev Bar-Or et al. (2021) [ | - To investigate changes in addictive behaviors among individuals treated in a specialized outpatient addiction treatment clinic. | Lockdown: interview: initiated, increased, decreased, or ceased use of various specific addictive substances and behaviors. | - A total of 36% increased their addictive behavior or the use of at least one substance: 25% alcohol, 29% cannabis, 29% stimulants, 15% sedatives, 15% pornography, and 11% gambling; 11% initiated an addictive behavior or the use of an addictive substance. |
| Cousijn et al. (2020) [ | - To investigate the influence of the lockdown on SUD. | Lockdown: MINI (SUD section); AUDIT; motives for cannabis use; DSM-5-CCSM; COVID-19-related worries; social contact. | - There was a significant increase in cannabis use during the first months of lockdown. However, there was no evidence of a change in substance disorder symptoms’ severity. The lockdown period was weakly associated with reductions in substance disorders symptoms. |
| Martinotti et al. (2020) [ | - To evaluate the impact of the COVID-19 pandemic and the containment measures on patients with SUD and/or behavioral addictions. | Lockdown: BDI-II; DTS; IDAS; SAS; VAS (level of craving for the substance). | - A total of 23% of our sample reported moderate/severe depressive symptoms; 30% reported moderate/severe anxiety symptoms. |
| Yazdi et al. (2020) [ | - To investigate addictive behavior, craving, and PTSD symptoms, as well as various COVID-19 factors in a clinical sample of patients with SUD. | Pandemic: AUDIT; PC-PTSD5; interview: physiological, economic, and substance use factors related to COVID-19. | - A total of 29% of patients were abstinent; 38% were consuming; 32% relapsed. In the total sample, psychosocial COVID-19 distress was reported by 53.5% of the patients. |
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| Becker et al. (2020) [ | - To examine remote learning practices and difficulties during initial stay-at-home orders in adolescents with and without ADHD. | Lockdown: Home Adjustment to COVID-19 Scale; Adolescent Routines Questionnaire; COVID-19 Adolescent Symptom and Psychological Experience Questionnaire. | - The lack of routines during stay-at-home mandates, negative effects, and trouble concentrating were associated with remote learning difficulties in adolescents with ADHD. |
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| Ma et al. (2020) [ | - To explore the influence of social isolation on the psychological characteristics of hospitalized SPD patients. | Lockdown (in patients): CPSS; HAMA; HAMD; PANSS; PSQI. | - Inpatients with schizophrenia who went through social isolation showed higher and more severe levels of stress, anxiety, and depression, and worse sleep quality afterwards than those who were not isolated. |
| Pinkham et al. (2020) [ | To examine the effects of the pandemic on people with pre-existing SMI’s (including people with schizophrenia spectrum disorder or severe affective disorders). | Pandemic: EMA; MADRS; PANSS; SUMD; YMRS. | - There were no significant changes in mood or psychotic symptoms and sleep duration over time; there was a small but significant increase in the number of substances used. |
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| Mataix-Cols et al. (2020) [ | - To investigate the impact of the COVID-19 outbreak on tic severity in people with TS or CTD. | Lockdown: self-developed Likert scale (Do you feel that your tics have worsened since the start of the coronavirus pandemic? | - Around 50% of the participants experienced a worsening in their tic symptomatology. |
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| Cheng et al. (2021) [ | - To examine resilience in the sleep and stress systems during the COVID-19 pandemic in participants with ID. | Life Events Checklist; CIS; ISI; IES COVID-19; QIDS-SR; PROMIS; GMH; GPH. | - More than two-thirds of the sample (67%) reported a direct impact from the pandemic; |
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| De Nardi et al. (2021) [ | - To evaluate how the COVID-19 lockdown affected adolescents with and without SSD. | Lockdown: MASC-2-SR; CDI-2-SF. | - Adolescents with SSD presented slightly lower significant anxiety raw scores and lower mean anxiety levels when compared to the controls. The physical symptoms, social anxiety, tension and restlessness scores, and levels of depression were also significantly lower in the SSD group than the controls. |
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| Favreau et al. (2021) [ | - To evaluate the impact of the pandemic on patients with GPP who were admitted to inpatient treatment. | Pandemic: Questionnaire: changes in symptom severity, quality of life and treatment; restrictions and pandemic-related worries. | - More than 50% reported worsening of symptoms; a 40% increased need of therapeutic support; nearly 1/4 reported a setback in treatment. |
| Imai et al. (2021) [ | - To investigate the impact of masks and plastic partitions on patient-doctor communication and subjective anxiety for infection in patients with psychiatric disorders. | Pandemic: questionnaire: differences in the variable’s barrier to communication and anxiety for infection for use of masks and partitions. | - A total of 91% of the patients answered that there was no change with regard to communication when the doctor was wearing a mask or using a plastic partition (83%). |
| Mergel et al. (2021) [ | - To investigate social participation, inclusion and psychological well-being in adults with and without pre-pandemic mental disorders. | Pandemic and lockdown: F-INK; IMET; BSI-18; specific questions regarding their subjective concerns; subjective possibilities of events in relation to the COVID-19 pandemic. | - The group with CMD did not report an impact in terms of their social participation. The group with pre-pandemic AMD exhibited fewer impairments during the lockdown period, whereas the group without mental disorders exhibited some impairments, which were transient and decreased over time, as the limitations were lifted. |
| Ting et al. (2021) [ | - To examine the prevalence of posttraumatic stress response towards COVID-19, among patients with pre-existing psychiatric illness. | Pandemic: questionnaire: impact of Effect of COVID-19 on patients’ psychological response; IES-R; PHQ-2. | - PTSD-like symptoms were reported by more than 45% of the participants. |
| Tundo et al. (2021) [ | - To examine the psychological and psychopathological impact of the pandemic stress on patients with pre-existing MD, AD and OCD. | Pandemic and lockdown: HAMD; Y-MANIA; Y-BOCS; PAAS; BSPS. | - A total of 11% of the patients reported higher distress levels than their family and friends regarding the fear of being infected; 5% reported changes in lifestyle; and 1% also reported changes in terms of financial burden. However, 37% of the patients reported that they were better-adapted than family and friends; |
| Vissink et al. (2021) [ | - To investigate the effects of COVID-19 and the restrictive measures on stress, anxiety and loneliness in patients with psychiatric disorders. | Pandemic: BAI; BDI; PSWQ; PQL-5; PSS; WHO-ASSIST questionnaire. | - Patients reported a deterioration in general health and mental health, as well as the presence of depressive symptoms and loneliness. |
| Burrai et al. (2020) [ | - To assess the psychological and emotional impact of isolation on patients compared to healthy controls. | Lockdown: DASS-21; BRCS; risk perception; worry about the present emergency situation; knowledge about COVID-19. | - GPP patients demonstrated lower stress compared to healthy controls; however, they presented a higher perceived risk of getting infected with COVID-19, higher levels of worry, and higher levels of anxiety relative to healthy controls. |
| Chang et al. (2020) [ | - To investigate the potential factors explaining preventive COVID-19 infection behaviors among individuals with mental illness. | Pandemic: BCIS; DASS-21; FCV-19S; PCIBS; SSS-S. | - Most of the patients reported experiencing self-stigma, fear of COVID-19, trust in COVID-19 information, engagement in preventive behaviors, and psychological distress. |
| Hao et al. (2020) [ | - To compare the immediate stress and psychological impact experienced by people with and without psychiatric disorder during the pandemic. | Pandemic and lockdown: IES-R; DASS-21; ISI. | - Psychiatric patients when compared to healthy controls reported a significant increase in: worries about their physical health (29% vs. 5%); moderate to severe anger and impulsivity (21% vs. 0.9%); and moderate to severe suicidal ideation (12% vs. 0.9%). |
| Iasevoli et al. (2020) [ | - To examine the severity of COVID-19-related perceived stress, anxiety, depressive, and psychotic symptoms in patients with serious mental disorders, caregivers, and control group. | Pandemic and lockdown: PSS; GAD-7; PHQ-9; SPEQ. | - Patients with mental illness had higher rates of perceived stress severity, moderate to severe anxiety, and significantly higher severe depressive symptoms compared to healthy controls. |
| Marchitelli et al. (2020) [ | - To identify psychological and psychosocial variables that predict weight gain in overweight patients with and without a psychiatric diagnosis. | Lockdown: BES; DASS-21; DERS; GHQ-12; PAPF-SC; risk perception. | - Among the surveyed patients affected by overweight/obesity, 50% of those without a psychiatric diagnosis and 66% of those with a psychiatric diagnosis reported weight gain during the COVID-19 lockdown. |
| Muruganandam et al. (2020) [ | - To determine the impact of COVID-19 in patients with SMI and identify its relationship with their COVID-19 knowledge. | Pandemic: questionnaire: self-developed questionnaire on awareness about symptoms of COVID-19. | - A total of 73% of the SMI patients did not report any anxiety/fear of contracting COVID-19. |
| Pan et al. (2020) [ | - To compare the perceived mental health impact on depressive symptoms, anxiety, worry, and loneliness before and during the COVID-19 pandemic among people with/without mental disorders. | Pandemic: NESDA: QIDS; BAI; PSWQ; DJGLS; | - Only 3% of the participants without a history of mental health disorders scored above the threshold for moderate to severe depressive symptoms during the pandemic. By contrast, in individuals with the largest mental health disorder burden, no overall increase in symptom severity was seen. |
| Porcellana et al. (2020) [ | - To evaluate the relationship between traumatic aspects of COVID-19 and clinical correlates of consecutive outpatients in a community mental health setting. | Lockdown: CGI-S; BPRS-18; IES-R; SRQ-20. | - A total of 34% of the participants reported mild symptoms of distress; 32% reported moderate symptoms of distress; and 26% reported severe symptoms of distress. SRQ-20 total score was positive in 59% of the patients, particularly in the female population aged 45–65. Actively working and SRQ-20 significantly predicted IES-R total score. |
| Zou et al. (2020) [ | - To investigate the prevalence of psychiatric symptoms and pain in older, clinically stable patients with and without psychiatric disorders during the COVID-19 pandemic. | Lockdown: questionnaire: self-developed questionnaire for current fatigue; | - A total of 47% of older, clinically stable patients with psychiatric disorders reported fatigue during the COVID-19 outbreak. |
Note: AMD, acute mental disorder; AN, anorexia nervosa; ASI-3, Anxiety Sensitivity Index-3; AUDIT, Alcohol Use Disorder Identification Test; BAI, Beck Anxiety Inventory; BCIS, Believing COVID-19 Information Scale; BD, bipolar disorder; BDI-II, Beck Depression Inventory-II; BED, binge eating disorder; BES, Binge Eating Scale; BN, bulimia nervosa; BPRS-18, Brief Psychiatric Rating Scale; BRCS, Brief Resilient Coping Scale; BSI, Brief Symptom Inventory; BSPS, Brief Social Phobia Scale; CDI-2-SF, Children’s Depression Inventory Short Form; CGI-I, Clinical Global Impression Improvement; CGI-S, Clinical Global Impression–Severity Scale; CIES, COVID Isolation Eating Scale; CIS, Coronavirus Impact Scale; C19P-S, COVID-19 Phobia Scale; CMD, chronic mental disorder; CPSS, Chinese Perceived Stress Scale; CRIES-13, Children’s Impact of Event Scale; CSS, COVID Stress Scales; CTQ-SF, Childhood Trauma Questionnaire—Short Form; CY-BOCS, Children’s Yale–Brown Obsessive Compulsive Scale; DASS-21, Depression, Anxiety and Stress Scale-21; DD, depressive disorder; DERS, Difficulties in Emotional Regulation Scale; DJGLS, De Jong Gierveld Loneliness Scale; DSM-5-CCSM, DSM-5 self-rated level 1 cross-cutting symptom measure—adult; DTS, Davidson Trauma Scale; ECR-R, Experiences in Close Relationships—Revised; EDE-Q, Eating Disorder Examination Questionnaire; EDI-2, Eating Disorders Inventory-2; EMA, Ecological Momentary Assessments; FCV-19s, Fear of COVID-19 scale; F-INK, Measure of Participation and Social Inclusion for Use in People with a Chronic Mental Disorder; GAD-7, Generalized Anxiety Disorder Scale; GAF, Global Assessment of Function; GMH, Global Mental Health; GPH, Global Physical Health; GHQ-12, General Health Questionnaire-12; HDRS, Hamilton Depression Rating Scale; HAMA, Hamilton Anxiety Scale; HAMD, Hamilton Depression Scale; HAM-D, Hamilton Depression Rating Scale; HCQ-54, Health Concerns Questionnaire-54; IDAS, Irritability Depression Anxiety Scale; IES COVID-19, Impact of Events Scale; IES-R, Impact of Event Scale-Revised; IMET, Index for the Assessment of Health Impairments; ISI, Insomnia Severity Index; K10, Kessler 10 Psychological Distress Scale; LEC, Life Event Checklist; MADRS, Montgomery–Asberg Depression Rating Scale; MASC-2-SR, Multidimensional Anxiety Scale for Children Self Report; MDD, major depressive disorder; NESDA, Netherlands Study of Depression and Anxiety; NESDO, Netherlands Study of Depression in Older Persons; NOCDA, Netherlands Obsessive Compulsive Disorder Association Study; NPRS, Numeric Pain Rating Scale; OCI-R, Obsessive Compulsive Inventory—Revised; OCS, Obsession with COVID-19 scale; PAAS, Panic Attack and Anticipatory Anxiety Scale; PANSS, Positive and Negative Syndrome Scale; PAPF-SC, Parents’ Assessment of Protective Factors: Social Connections Subscale; PCIBS, Preventive COVID-19 Infection Behaviors Scale; PC-PTSD5, Primary Care PTSD Screen for DSM-5; PHQ, Patient Health Questionnaire; PROMIS, Patient-Reported Outcomes Measurement Information System; PCL-5, Post-Traumatic Stress Disorder derived from DSM-V; PSQI, Pittsburg Sleep Quality Index; PSS, Perceived Stress Scale; PSWQ, Penn State Worry Questionnaire; PTSD, post-traumatic stress disorder; PTSS, post-traumatic stress symptoms; QIDS-SR, Quick Inventory of Depressive Symptomatology; SAS, Self-rating Anxiety State; SCL-90-R, Symptom Checklist-90-Revised; SHAI, Short Health Anxiety Inventory; SMI, severe mental illness; SPEQ, Specific Psychotic Experience Questionnaire; SRQ-20, Self-Report Questionnaire; SSS-S, Self-Stigma Scale-Short; STAI, State-Trait Anxiety Inventory; SUMD, Scale to Assess Unawareness of Mental Disorder; TCI-R, Temperament and Character Inventory-Revised; VAS, Visual Analogue Scale; VOCI, Vancouver Obsessional Compulsive Inventory; XS, Xenophobia Scale; WHOQOL-BREF, World Health Organization Quality of Life-brief version; WMD, without a mental disorder; YMRS, Young Mania Rating Scale; Y-BOCS, Yale–Brown Obsessive Compulsive Scale; YFAS-2, Yale Food Addiction Scale 2.0; YMRS, Young Mania Rating Scale.
Summary of main findings.
| Psychiatric Disorders | Main Results | Major Concerns or Potential Risk Factors |
|---|---|---|
| Mood |
No or mild/moderate impact. BD: Greater impact when compared to healthy controls; Slower recovery over time. People with MDD were more likely to develop PTSD-like symptoms, as compared to healthy controls. Reduced negative impact when comorbid psychotic symptoms were present. |
Frustration due to restrictions was the most common stressor. Work and financial difficulties. Fear of infection. |
| Anxiety |
Modest impact, although greater for those with comorbid conditions. Some patients reported improvement as compared to evaluation prior to the beginning of the pandemic restrictions. Individuals with GAD and PD reported higher levels of stress associated with COVID-19 pandemic. |
Anxiety sensitivity may be a potential vulnerability factor for COVID-19-related mental health impacts. Reduced social functioning and quality of life were positively correlated to the greatest impact of the COVID-19 restrictions. |
| Obsessive compulsive |
Significant worsening of OCD symptoms. Emergence of COVID-related OC symptoms in some patients. |
Higher risk of OCD symptoms worsening:
Presence of pre-pandemic depression; Higher Y-BOCS scores; contamination/washing symptoms; Lower perceived social support. |
| Eating |
Significant ED worsening symptoms:
Some studies showed that the effect was higher in people with AN; Other studies showing that it was in people with BN. Significant negative interference in the recovery process. Significant increase in binge eating episodes. |
ED worsening symptoms related to: Dysfunctional coping strategies; Lower self-directedness; Personality trait; History of adverse childhood experiences. Fear for the safety of loved ones, as well as worsening of depressive and anxiety symptoms might lead to an increase in binge eating episodes. |
| Substance use and addiction |
Mixed results in the literature of worsening or improvement of substance use or addictive behaviors. The impact of the lockdown on mental health in cannabis users might have been minimal. |
Greater impact of the pandemic: Trauma exposure; Perceived stress and isolation; Income reduction and financial uncertainty; Alcohol abuse. Isolation, anxiety, depression, and living alone may be associated with a higher risk of relapsing. |
| Attention-deficit hyperactivity |
Adolescents with ADHD experienced greater negative effects and more difficulties concentrating. |
Remote learning seems to be more challenging for adolescents with ADHD, as compared to healthy individuals. |
| Schizophrenia Spectrum |
Greater psychological (depression, anxiety, and sleep quality) impact for those that were socially isolated during hospitalization due to pandemic restrictions |
Social isolation associated with burden. |
| Tourette Syndrome or Chronic Tic Disorder |
Tic worsening. |
Increased stress and anxiety: Preoccupations about finances, future, and family; Confinement and lack of physical exercise/activity; Fewer distractions, change in or lack of routines, having to go to work, and being exposed to the public. Possible stigma related to: Coughing tics; Exacerbation of the tics while using a mask; Increase in self-injury behaviors. |
| Insomnia |
Moderate to severe insomnia. | |
| Somatic Symptom Disorders |
Adolescents with SSD experienced fewer physical, depressive, and anxiety symptoms, as compared to healthy controls, during the COVID-19 blockade period. |
Lockdown may be related to reduced symptomatology in adolescents with SSD due to reduced social distress. |