Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Study Protocol

Effect of internet-delivered cognitive behavioral therapy on insomnia in convalescent patients with COVID-19: Protocol for a systematic review and meta-analysis

  • Yan Chen,

    Roles Conceptualization, Formal analysis, Writing – review & editing

    Affiliation Institute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, Henan, China

    ⨯
  • Xiang Zhou,

    Roles Methodology, Software

    Affiliation Henan University of Traditional Chinese Medicine, Zhengzhou, Henan, China

    ⨯
  • Jie Liu,

    Roles Writing – review & editing

    Affiliation Huaihe Hospital of Henan University, Kaifeng, Henan, China

    ⨯
  • Rui Li,

    Roles Conceptualization

    Affiliation Institute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, Henan, China

    ⨯
  • Zihan Jiang,

    Roles Conceptualization, Writing – review & editing

    Affiliation Institute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, Henan, China

    ⨯
  • Lina Wang,

    Roles Supervision

    Affiliation Huaihe Hospital of Henan University, Kaifeng, Henan, China

    ⨯
  • Shuya Wang,

    Roles Conceptualization, Data curation, Formal analysis

    Affiliation Huaihe Hospital of Henan University, Kaifeng, Henan, China

    ⨯
  • Bo Li

    Roles Funding acquisition

    10210022@vip.henu.edu.cn

    Affiliation Institute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, Henan, China

    ⨯

Abstract

Introduction

Coronavirus Disease 2019 (COVID-19) has made a serious public health threat worldwide. Recent evidence has indicated that COVID-19 patients in convalescence frequently experience insomnia, which reduces their quality of life and causes unknown risks. The positive effect of cognitive behavior on insomnia has been well addressed in previous studies. Given the high infectivity and epidemicity of COVID-19, Internet-delivered intervention may be safer than face-to-face treatment. However, whether Internet-delivered cognitive behavioral therapy can effectively improve the insomnia of COVID-19 patients in convalescence has not been completely determined yet. Therefore, we conducted a meta-analysis and systematic review to evaluate the effects of Internet-delivered cognitive behavioral therapy on insomnia in COVID-19 patients in convalescence, with the aim to confer some guidance for its clinical application.

Methods and analysis

This systematic review and meta-analysis has been registered in the International Prospective Register of Systematic Reviews (PROSPERO). Two researchers will retrieve the relevant literature on Internet-delivered cognitive behavioral therapy for insomnia in convalescent patients with COVID-19 in PubMed, Web of Science, Embase, MEDLINE, Cochrane Library, Clinical Trials gov, Chinese Biomedical Literature Database (CBM), and Chinese National Knowledge Infrastructure (CNKI) from inception to 11th of December. In addition, we will review the relevant trials and references of the included literature and manually searched the grey literature. The two researchers will independently extracted data and information and evaluated the quality of the included literature. The Review Manager software (version 5.3) and Stata software (version 14.0) will be used for data analysis. The mean difference or the standardized mean difference of 95% CI will be used to calculate continuous variables to synthesize the data. In addition, I2 and Cochrane will be used for heterogeneity assessment.

Trial registration

PROSPERO registration number CRD42021271278.

Citation: Chen Y, Zhou X, Liu J, Li R, Jiang Z, Wang L, et al. (2022) Effect of internet-delivered cognitive behavioral therapy on insomnia in convalescent patients with COVID-19: Protocol for a systematic review and meta-analysis. PLoS ONE 17(6): e0269882. https://doi.org/10.1371/journal.pone.0269882

Editor: Luigi Lavorgna, Universita degli Studi della Campania Luigi Vanvitelli, ITALY

Received: December 28, 2021; Accepted: May 17, 2022; Published: June 14, 2022

Copyright: © 2022 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Deidentified research data will be made publicly available when the study is completed and published.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

World Health Organization (WHO) has reported that the ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected 200,840,180 people and resulted in 4,265,903 deaths worldwide by 6th August 2021 [1]. COVID-19 has rapidly developed into a pandemic and seriously threatened public health all over the world [2, 3]. COVID-19 pandemic seriously jeopardizes human physical and mental health [4] and attracts the concerns of numerous researchers [5]. The exploration of novel prevention, diagnosis, and treatment strategies has become a hot topic among scholars [6, 7], but little attention is paid to the mental health of COVID-19 patients in convalescence [8]. Studies have shown that the confirmed patients with COVID-19 tend to experience various psychological disorders such as stress, anxiety, depression, irritability, depression, and despair [9, 10]. Even though the mood of patients recovering from COVID-19 infection has improved, their symptoms of insomnia and fatigue still persist [11]. A considerable number of patients still suffer from insomnia and other symptoms of sleep disorders in the convalescent period [12]. A prospective cohort and nested case-control study has revealed that 29.17% of COVID-19 patients in convalescence experience insomnia [13].

Insomnia is defined as difficulties in falling asleep, maintaining asleep, or waking up too early at least three times per week for at least 3 months [14] and is one of the most common problems experienced by convalescent patients with COVID-19 [13]. COVID-19-related worries and loneliness are the major contributors to clinical insomnia in addition to education status, virus infection, and pre-existing mental health disorders [14, 15]. Poor sleep quality leads to adverse outcomes of physical [16] and mental health [17]. If left untreated, insomnia can aggravate anxiety, depression, and post-traumatic stress disorder and eventually compromise the quality of life [18]. Moreover, severe insomnia disorder or irregular sleep-wake cycle may damage the immune system and inflammatory response and increase the susceptibility to virus infection [19].

At present, primary health care and outpatient mental health institutions are responsible for the treatment of insomnia [20]. Drug therapy remains the most commonly used intervention method for insomnia. Despite the rapid curative effects, drug therapy fails to achieve radical treatment and also results in many adverse reactions [21–23]. Cognitive behavioral therapy, as an evidence-based option, has been found to effectively improve sleep outcomes [24, 25] and its therapeutic effect is equivalent to or better than that of drug therapy [26]. Since SARS-CoV-2 spreads through close contact between people [27], keeping a distance of more than two meters and using an N-95 mask are the most effective ways to prevent the spread of COVID-19 [28]. Under the guidance of therapists, the effect of Internet-delivered cognitive behavioral therapy on some mental and physical diseases is equivalent to that of face-to-face cognitive behavioral therapy [29], because the possibility of novel coronavirus pneumonia reinfection is unknown [30]. As a kind of digital therapy, Internet-delivered cognitive behavioral therapy provides patients with evidence-based treatment interventions, which are driven by software to prevent, manage, or treat medical disorders or diseases [31]. It can be used independently or in concert with medications, devices, or other therapies [31]. Internet-delivered cognitive behavioral therapy represents a promising option to solve the obstacles of psychotherapy [32], which overcomes several limits related to traditional clinical practice [33] and possesses the advantages of low cost [31], high efficiency [31], and continuous monitoring [33]. Therefore, the cognitive behavioral therapy provided by the Internet may also have potential advantages in improving the insomnia of COVID-19 patients in the convalescent period.

The existing studies have shown that Internet-delivered cognitive behavioral therapy can improve symptoms of insomnia in adults [34]. However, a recent study has also found that Internet-delivered cognitive therapy has no significant effect on improving the insomnia of COVID-19 patients [35]. Therefore, this protocol is established to determine the effectiveness of Internet-delivered cognitive behavioral therapy for relieving insomnia symptoms in newly recovered patients with COVID-19.

Review questions

Under the current COVID-19 epidemic background, can Internet-delivered cognitive therapy improve insomnia in rehabilitative patients?

Objectives

The main purpose of this study is to conduct a systematic review and meta-analysis through randomized controlled trials (RCTs) to determine whether the Internet-delivered cognitive behavioral therapy can relieve insomnia in convalescent patients with COVID-19, improve the sleep quality of convalescent patients with COVID-19, and then improve the psychological condition of these patients.

Materials and methods

The protocol is in line with the Preferred Reporting Items for Systematic Reviews and Meta-analysis for Protocol (PRISMA-P) [36].

Inclusion criteria of the study

This systematic review protocol includes the following studies:

Types of studies

We included randomized controlled trials (RCTs). These trials report the effects of Internet-delivered cognitive behavioral therapy on insomnia in convalescent patients with COVID-19.

Participants

Participants are COVID-19 patients with sleep disorders in the convalescent period. Mental disorders will be involved in the meta-analysis.

Ethics and dissemination

Since this study reviews the published data, ethical approval is not required. The results of this systematic review and meta-analysis will be published in peer-reviewed journals.

Interventions

The intervention group will receive Internet-delivered cognitive behavioral therapy. Internet-delivered cognitive behavioral therapy will be conducted under the guidance of experienced psychotherapists or trained therapists. Patients will log into a secure website to access, read, and download online materials organized in a series of lessons or modules, including cognitive reconstruction, loosening practice, knowledge explanation, health education, and so on.

Comparisons

Patients in the control group will receive routine care, such as self-regulation, medical consultation, and support.

Outcome indicators

The sleep indicators for COVID-19 patients in convalescence will be as follows: (1) sleep quality (SQ), (2) time in bed, (3) sleep time (ST), (4) sleep efficiency (SE), (5) sleep disturbance (SD), (6) daytime function (DF), (7) Pittsburgh Sleep Quality Index (PSQI), and (8) Insomnia Severity Index (ISI).

Search strategy

Two researchers (YC, XZ) will retrieve the relevant English and Chinese literature independently in the following databases from inception to 11th of December: PubMed, Web of Science, Embase, MEDLINE, Cochrane Library, ClinicalTrials.gov, Chinese Biomedical Literature Database (CBM), and Chinese National Knowledge Infrastructure (CNKI). PubMed literature search is as follows: (Table 1).

thumbnail
Download:
Table 1. Search strategy for PubMed.

https://doi.org/10.1371/journal.pone.0269882.t001

Literature selection and data extraction

Literature selection

The literature screening process will follow the steps in the PRISMA flow chart (Fig 1). Firstly, after retrieving all databases, we will use Endnote 9.0 software to eliminate duplicate studies. Then, the two researchers will independently examined the titles and abstracts of the documents obtained after weight removal and preliminarily screened the documents. Subsequently, the two researchers will independently read the preliminarily screened literature according to the inclusion and exclusion criteria we formulate in advance. Finally, the literature screened by the two researchers will be compared to determine the literature finally included in the analysis. A third independent researcher will be consulted to achieve a final consensus in case of disagreement between both researchers.

thumbnail
Download:
Fig 1. Flow diagram of study selection process.

https://doi.org/10.1371/journal.pone.0269882.g001

Data extraction

The extraction of data and information in the literature will be completed by two researchers independently, including first author, publication date, country, intervention implementer, sample number, sample age, sample source, intervention time of online cognitive behavioral therapy, intervention frequency, dropout rate, insomnia assessment tool, and other details. Data will be collected and analyzed in the near future.

Risk of bias assessment in the included literature

The two researchers will use the Cochrane bias risk assessment tool to independently assess the risk of publication bias of each included literature (random sequence generation, random assignment concealment, blind method, incomplete result data, selective reporting bias, and other bias). The bias risk will include the risk of high, unclear, or low bias [37]. If there are any differences in the assessment, a third researcher will be consulted to resolve the dispute.

Data synthesis and statistical analysis

Review Manager 5.3 software and Stata 14.0 software will be used for quantitative data analysis, including overall forest mapping, heterogeneity analysis, subgroup analysis, sensitivity analysis, and funnel mapping. For the diverse insomnia assessment tools, the standardized mean difference (SMD) and its 95% confidence interval (CI) will be used to describe the size of the effect. On the contrary, the mean difference (MD) and 95% CI will be used to represent the size of the effect.

Assessment of heterogeneity

The heterogeneity assessment will be conducted using the Rev Man 5.3 software. The Chi-Squared test and I2 will be adopted to examine the statistical heterogeneity of the included studies. The random-effect model (P ≤ 0.1 and I2 > 50%) or fixed-effect model (P > 0.1 and I2 ≤ 50%) will be selected according to the values of P and I2.

Subgroup analysis

When heterogeneity is found in the results, subgroup analysis will be performed on the basis of ensuring sufficient data. The criteria will include characteristics (such as country or sample source), study quality, type of control intervention, and duration. In addition, we will analyze any other subgroups reported in the literature.

Assessment of reporting bias

Publication bias will be assessed by visual inspection of the funnel plot asymmetry and Egger’s regression test [38].

Sensitivity analysis

The robustness of analysis results will be explored by sensitivity analysis. Sensitivity analysis will be performed by excluding each uncertain factor to determine the sensitive factor exerting an important impact on the overall results.

Quality of evidence

The researchers will assess the quality of evidence for the entire study in accordance with the Grades of Recommendation, Assessment, Development, and Evaluation system established by the WHO and international organizations. The GRADE system will rate the quality of evidence as “high,” “medium,” “low,” and “lowest” [39].

Discussion

Insomnia seriously impairs the quality of life of COVID-19 patients in convalescence and causes severe mental disorders such as anxiety, depression, and fear [40]. Therefore, the use of scientific psychological intervention to treat insomnia is of great practical significance. Previous studies have shown that Internet-delivered cognitive behavioral therapy can make insomnia patients achieve lasting sleep improvement over a period of time with fewer side effects [41]. Based on the existing evidence, we reasonably speculate that cognitive behavioral therapy can also relieve the insomnia of COVID-19 patients in convalescence.

Due to the impact of methodological quality, information bias, and adequacy of results reporting of the included literature, the therapeutic effect of Internet-delivered cognitive behavioral therapy on insomnia in COVID-19 patients in convalescence may be affected. Therefore, we need to conduct large-scale and high-quality research in the future to obtain more accurate results.

Supporting information

S1 Checklist. PRISMA-P 2009 checklist.

https://doi.org/10.1371/journal.pone.0269882.s001

(DOC)

S1 Fig. Flow diagram of study selection process.

https://doi.org/10.1371/journal.pone.0269882.s002

(DOCX)

References

  1. 1. Dressel A, Mkandawire-Valhmu L. Celebrate World Health Day: Nursing and Global Health. J Contin Educ Nurs. 2019; 50(4):145–147. pmid:30942887
  2. 2. Jiang S, Du L, Shi Z. An emerging coronavirus causing pneumonia outbreak in Wuhan, China: calling for developing therapeutic and prophylactic strategies. Emerg Microbes Infect. 2020; 9(1):275–277. pmid:32005086
  3. 3. Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol. 2020; 5(4):536–544. pmid:32123347
  4. 4. Majumder J, Minko T. Recent Developments on Therapeutic and Diagnostic Approaches for COVID-19. AAPS J. 2021; 23(1):14. pmid:33400058
  5. 5. Zhang S, Liu L, Yang B, Li R, Luo J, Huang J, et al. Clinical characteristics of 134 convalescent patients with COVID-19 in Guizhou, China. Respir Res. 2020; 21(1):314. pmid:33243228
  6. 6. Cohen MS, Corey L. Combination prevention for COVID-19. Science. 2020; 368(6491):551. pmid:32381692
  7. 7. Ahn DG, Shin HJ, Kim MH, Lee S, Kim HS, Myoung J, et al. Current Status of Epidemiology, Diagnosis, Therapeutics, and Vaccines for Novel Coronavirus Disease 2019 (COVID-19). J Microbiol Biotechnol. 2020; 30(3):313–324. pmid:32238757
  8. 8. Liu HQ, Yuan B, An YW, Chen KJ, Hu Q, Hu XP, et al. Clinical characteristics and follow-up analysis of 324 discharged COVID-19 patients in Shenzhen during the recovery period. Int J Med Sci. 2021; 18(2):347–355. pmid:33390803
  9. 9. Guo Y, Cheng C, Zeng Y, Li Y, Zhu M, Yang W, et al. Mental Health Disorders and Associated Risk Factors in Quarantined Adults During the COVID-19 Outbreak in China: Cross-Sectional Study. J Med Internet Res. 2020; 22(8):e20328. pmid:32716899
  10. 10. Serafini G, Rihmer Z, Amerio A, Aguglia A, Amore M. COVID-19 infection and mental disorders: a call for action to enhance protection and break down barriers. Psychiatr Hung. 2020; 35(3):245–246. pmid:32643615
  11. 11. Becker PM. Overview of sleep management during COVID-19. Sleep Med. 2021: S1389-9457(21)00248-3. pmid:33975774
  12. 12. Pappa S, Ntella V, Giannakas T, Giannakoulis VG, Papoutsi E, Katsaounou P. Prevalence of depression, anxiety, and insomnia among healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis. Brain Behav Immun. 2020; 88:901–907. pmid:32437915
  13. 13. Li L, Gou CY, Li XM, Song WY, Wang XJ, Li HY, et al. Effects of Chinese Medicine on Symptoms, Syndrome Evolution, and Lung Inflammation Absorption in COVID-19 Convalescent Patients during 84-Day Follow-up after Hospital Discharge: A Prospective Cohort and Nested Case-Control Study. Chin J Integr Med. 2021; 27(4):245–251. pmid:33534076
  14. 14. Kwak A, Jacobs J, Haggett D, Jimenez R, Peppercorn J. Evaluation and management of insomnia in women with breast cancer. Breast Cancer Res Treat. 2020; 181(2):269–277. pmid:32314110
  15. 15. Kokou-Kpolou CK, Megalakaki O, Laimou D, Kousouri M. Insomnia during COVID-19 pandemic and lockdown: Prevalence, severity, and associated risk factors in French population. Psychiatry Res. 2020; 290:113128. pmid:32563951
  16. 16. Itani O, Jike M, Watanabe N, Kaneita Y. Short sleep duration and health outcomes: a systematic review, meta-analysis, and meta-regression. Sleep Med. 2017; 32:246–256. pmid:27743803
  17. 17. Baglioni C, Nanovska S, Regen W, Spiegelhalder K, Feige B, Nissen C, et al. Sleep and mental disorders: A meta-analysis of polysomnographic research. Psychol Bull. 2016; 142(9):969–990. pmid:27416139
  18. 18. De Lorenzo R, Conte C, Lanzani C, Benedetti F, Roveri L, Mazza MG, et al. Residual clinical damage after COVID-19: A retrospective and prospective observational cohort study. PLoS One. 2020; 15(10):e0239570. pmid:33052920
  19. 19. Mello MT, Silva A, Guerreiro RC, da-Silva FR, Esteves AM, Poyares D, et al. Sleep and COVID-19: considerations about immunity, pathophysiology, and treatment. Sleep Sci. 2020; 13(3):199–209. pmid:33381288
  20. 20. Schutte-Rodin S, Broch L, Buysse D, Dorsey C, Sateia M. Clinical guideline for the evaluation and management of chronic insomnia in adults. J Clin Sleep Med. 2008; 4(5):487–504. pmid:18853708
  21. 21. Mitchell MD, Gehrman P, Perlis M, Umscheid CA. Comparative effectiveness of cognitive behavioral therapy for insomnia: a systematic review. BMC Fam Pract. 2012; 13:40. pmid:22631616
  22. 22. Riemann D, Perlis ML. The treatments of chronic insomnia: a review of benzodiazepine receptor agonists and psychological and behavioral therapies. Sleep Med Rev. 2009; 13(3):205–14. pmid:19201632
  23. 23. Morin CM, Bootzin RR, Buysse DJ, Edinger JD, Espie CA, Lichstein KL. Psychological and behavioral treatment of insomnia: update of the recent evidence (1998–2004). Sleep. 2006; 29(11):1398–414. pmid:17162986
  24. 24. Trauer JM, Qian MY, Doyle JS, Rajaratnam SM, Cunnington D. Cognitive Behavioral Therapy for Chronic Insomnia: A Systematic Review and Meta-analysis. Ann Intern Med. 2015 4; 163(3):191–204. pmid:26054060
  25. 25. Irwin MR, Cole JC, Nicassio PM. Comparative meta-analysis of behavioral interventions for insomnia and their efficacy in middle-aged adults and in older adults 55+ years of age. Health Psychol. 2006; 25(1):3–14. pmid:16448292
  26. 26. Smith MT, Perlis ML, Park A, Smith MS, Pennington J, Giles DE, et al. Comparative meta-analysis of pharmacotherapy and behavior therapy for persistent insomnia. Am J Psychiatry. 2002; 159(1):5–11. pmid:11772681
  27. 27. Cheng VCC, Wong SC, Chen JHK, Yip CCY, Chuang VWM, Tsang OTY, et al. Escalating infection control response to the rapidly evolving epidemiology of the coronavirus disease 2019 (COVID-19) due to SARS-CoV-2 in Hong Kong. Infect Control Hosp Epidemiol. 2020; 41(5):493–498. pmid:32131908
  28. 28. Chu DK, Akl EA, Duda S, Solo K, Yaacoub S, Schünemann HJ; COVID-19 Systematic Urgent Review Group Effort (SURGE) study authors. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. Lancet. 2020; 395(10242):1973–1987. pmid:32497510
  29. 29. Andersson G, Cuijpers P, Carlbring P, Riper H, Hedman E. Guided Internet-based vs. face-to-face cognitive behavior therapy for psychiatric and somatic disorders: a systematic review and meta-analysis. World Psychiatry. 2014; 13(3):288–95. pmid:25273302
  30. 30. Wolraich ML, Hagan JF Jr, Allan C, Chan E, Davison D, Earls M, et al. Clinical Practice Guideline for the Diagnosis, Evaluation, and Treatment of Attention-Deficit/Hyperactivity Disorder in Children and Adolescents. Pediatrics. 2019; 144(4):e20192528. pmid:31570648
  31. 31. Abbadessa G, Brigo F, Clerico M, De Mercanti S, Trojsi F, Tedeschi G, et al. Digital therapeutics in neurology. J Neurol. 2022; 269(3):1209–1224. pmid:34018047
  32. 32. Xiang X, Wu S, Zuverink A, Tomasino KN, An R, Himle JA. Internet-delivered cognitive behavioral therapies for late-life depressive symptoms: a systematic review and meta-analysis. Aging Ment Health. 2020;24(8):1196–1206. pmid:30913898
  33. 33. Khirasaria R, Singh V, Batta A. Exploring digital therapeutics: The next paradigm of modern health-care industry. Perspect Clin Res. 2020;11(2):54–58. pmid:32670828
  34. 34. Seyffert M, Lagisetty P, Landgraf J, Chopra V, Pfeiffer PN, Conte ML, et al. Internet-Delivered Cognitive Behavioral Therapy to Treat Insomnia: A Systematic Review and Meta-Analysis. PLoS One. 2016;11(2):e0149139. pmid:26867139
  35. 35. Aminoff V, Sellén M, Sörliden E, Ludvigsson M, Berg M, Andersson G. Internet-Based Cognitive Behavioral Therapy for Psychological Distress Associated With the COVID-19 Pandemic: A Pilot Randomized Controlled Trial. Front Psychol. 2021;12:684540. pmid:34194374
  36. 36. Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. pmid:19621072
  37. 37. Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928. pmid:22008217
  38. 38. Irwig L, Macaskill P, Berry G, Glasziou P. Bias in meta-analysis detected by a simple, graphical test. Graphical test is itself biased. BMJ. 1998;316(7129): 470–1. pmid:9492687
  39. 39. Guyatt G, Oxman AD, Akl EA, Kunz R, Vist G, Brozek J, et al. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64(4):383–94. pmid:21195583
  40. 40. Mazza MG, Palladini M, De Lorenzo R, Magnaghi C, Poletti S, Furlan R, et al. COVID-19 BioB Outpatient Clinic Study group, Rovere-Querini P, Benedetti F. Persistent psychopathology and neurocognitive impairment in COVID-19 survivors: Effect of inflammatory biomarkers at three-month follow-up. Brain Behav Immun. 2021;94:138–147. pmid:33639239
  41. 41. Zachariae R, Lyby MS, Ritterband LM, O’Toole MS. Efficacy of internet-delivered cognitive-behavioral therapy for insomnia—A systematic review and meta-analysis of randomized controlled trials. Sleep Med Rev. 2016;30:1–10. pmid:26615572