MASTER’S THESIS
A SYSTEMATIC OVERVIEW OF UMBRELLA REVIEWS ON RISK AND PROTECTIVE FACTORS FOR PSYCHOLOGICAL DISORDERS
Victòria Jiménez Amengual
Master’s Degree in General Health Psychology Centre for Postgraduate Studies
Academic Year 2021
A SYSTEMATIC OVERVIEW OF UMBRELLA
REVIEWS ON RISK AND PROTECTIVE FACTORS FOR PSYCHOLOGICAL DISORDERS
Victòria Jiménez Amengual
Master’s Thesis
Centre for Postgraduate Studies University of the Balearic Islands
Academic Year 2021
Keywords:
mental health research, mental health prevention, psychological disorders, risk and protective factors and umbrella review.
Thesis Supervisor’s Name: Miquel Tortella-Feliu
Abstract
Nowadays health research faces a moment of massive publication. Every day it grows, resulting not only in tons of new papers, but also systematic reviews (SR), meta-analysis (MA) and, research syntheses. Umbrella reviews (UR) are systematic reviews of multiple SR and MA on a certain topic and have appeared as a solution to the excess of emerging
published information, helping decision-makers to be updated on the latest evidence for their professional practice. The overarching aim of the current study was to provide a big picture of the topics covered by UR and to summarize knowledge of those focused on risk and protective factors for diagnosed mental disorders.
In this systematic overview first, Scopus, PubMed, and Web of Science databases were systematically searched finding 575 UR. Second, mental health articles were screened and classified by field giving us a broader view of the current state of research in the
specialty. And third, the highest quality evidence available on risk and protective factors for different mental disorders was analyzed through 10 UR published on the topic. Extracting around half a thousand risk/protective factors and their association measures and classifying them by topic in order to assess and grade the evidence acquired. As a result, 564 non purely genetic risk/protective factors for diagnosed psychological disorders were synthetized.
Concretely, 553 potential risk factors and 11 potential protective factors. Even though, many were associated with up to 6 different disorders which support the transdiagnostic hypothesis, only 25 factors meet criteria to be considered class I evidence, making the existence of the association very clear.
As a result of the incorporation of UR as research tools, various astonishingly clear associations have been found on risk/protective factors, providing valuable information to the scientific community and leading the path to enhance the knowledge and practice in mental health.
Index
ABSTRACT... 3
A SYSTEMATIC OVERVIEW OF UMBRELLA REVIEWS ON RISK AND PROTECTIVE FACTORS FOR PSYCHOLOGICAL DISORDERS ... 5
METHODS ... 8
SEARCH STRATEGY ...8
DEFINITION OF UR ...8
DEFINITION OF RISK/PROTECTIVE FACTORS ...9
DATA EXTRACTION ...9
RESULTS ... 11
SELECTION CRITERIA ... 11
ASSESSMENT OF UR ... 13
MAIN EVIDENCE REGARDING RISK/PROTECTIVE FACTORS ... 14
Autism Spectrum Disorder ... 15
Attention Deficit Hyperactivity Disorder ... 16
Neurodevelopmental Disorders ... 16
Schizophrenia Spectrum Disorder/Psychosis ... 17
Bipolar Disorder ... 17
Depression ... 18
Anxiety Disorders ... 19
Obsessive-Compulsive Disorder ... 20
Posttraumatic-Stress Disorder ... 20
Eating Disorders ... 21
PROTECTIVE FACTORS ... 21
Autism Spectrum Disorder. ... 21
Attention Deficit Hyperactivity Disorder. ... 23
Schizophrenia. ... 23
Major Depressive Disorder. ... 23
Anxiety Disorders (Specific Phobia, Generalized Anxiety Disorder, and Panic Disorder). ... 23
Obsessive-Compulsive Disorder. ... 23
COGENT FACTORS FOR MENTAL DISORDERS ... 23
DISCUSSION ... 26
REFERENCES ... 32
A systematic overview of umbrella reviews on risk and protective factors for psychological disorders
Nowadays health research faces a moment of massive publication. Every day it grows, resulting not only in tons of new papers, but also systematic reviews (SR), meta-analysis (MA) and, research syntheses available for the healthcare professionals to read. The production overload affects mental health research as well. This large productivity of
research may seem a good sign of the scientific community’s shape, being capable of moving forward and improving its knowledge thanks to investigation and, therefore, publication of discoveries. Looking at it that way, the more research is made, the more the science
progresses, and consequently, decision-makers receive evidence-based information to better their task (Pollock et al., 2016; Schultz et al., 2018).
However, the publication rate is so high that may result overwhelming for any professional working in a health field to catch up with it. Making it very difficult to be updated on all the findings of their concern. And the reality is that something that may be contributing to this research saturation is the duplication of content which outnumber the publications while increasing confusion. This is not assisting the science to develop due to the lack of discoveries added to the chaos generated (Fusar-Poli, & Radua, 2018). Little it helps to have available information, if the people who are supposed to use the knowledge from the research don’t really have access to it (Aromataris et al., 2015).
It requires much time and effort to, first of all, filter all the SR and MA published on a specific topic and second of all, compare and contrast the results prioritizing the ones that have been conducted correctly in terms of methodology, to reassure the information’s quality.
Therefore, if we are interested in the development of health science in the first place, it is crucial that we find a way for the knowledge we get from research to reach the public is meant to help, always keeping in mind that SR and MA form the best evidence to make
informed decisions and that is why they are crucial in the healthcare profession, to begin with (Aromataris et al., 2015). The poor translation of evidence-based procedures and methods into practice does not surprise in this scenario. All the above may specifically concern decision-makers whose practices are at stake and, finally the patients affected by those (Schultz et al., 2018).
In light of this situation, we undeniably need a solution to make it possible for the decision-makers in mental health to receive the knowledge they need in order to use it in their practice. This information would have a positive impact on the decision-making process, overall professional practice, and ultimately, the patients’ health.
Umbrella reviews (UR) also called overviews of systematic reviews, synthesis of reviews, or review of reviews have appeared as an answer to this status quo, a solution to a problem concerning the excess of emerging information in the healthcare field (Lunny et al., 2018). UR are systematic reviews of multiple SR and MA on a certain topic. They consist of a new type of research design, and they aim to compare and analyze SR and MA, and then contrast and integrate their results. The process ends up in a synthesis of results from SR and MA’s content about a concrete scientific question. This summary provides a picture of findings that healthcare professionals can use to make informed decisions based on evidence, therefore has an impact on the decision-making processes.
UR form a tool to more easily spread scientific knowledge by means of a
comprehensive abstract of evidence, making it accessible for the decision-makers (Pollock et al., 2016). This changes the situation, enabling interventions to be more adjusted to scientific evidence which improves health care overall (Bastian et al., 2010). Despite its short history, the number of UR has increased notably in the last few years. It has been little more than 10 years when the first medical UR was published in 2007 and little after the first UR on mental health appeared in 2009. In spite of their short existence, their role in the scientific
community has obtained an astonishing relevance. It can be explained due to the need they meet, and the massive number of SR and MA accessible (Fusar-Poli & Radua, 2018; Lunny et al., 2017).
In the matter of creating new prevention methods, it is indispensable to know the risk and protective factors involved in the development of a mental disorder. And not only for developing preventive intervention but also for a better understanding on factors contributing to the emergence and maintenance of psychological disorders that could also inform on specific treatment targets. Even though the number of studies about those variables is large, a wide list of determinants of mental health, including personal, environmental, and
socioeconomic factors, appears in handbooks and technical reports (Barlow et al. 2018;
WHO, 2012), multifinality and equifinality are often advocated, although actually little is known about the real impact each of them has on every specific mental disease in terms of their strength and overall relevance as true risk or protective factor (Huizink & De Rooij, 2018; Radua et al., 2018). Moreover, most of these studies are purely correlational and cross- sectional and, also, usually include data on psychopathological symptoms (i.e., symptoms of anxiety) instead of a diagnosed mental disorder, which is a common limitation of this kind of research in psychopathology.
A piece of better knowledge on risk and protective factors would provide clinicians and decision-makers with incredible tools to improve patient lives and to promote strategies to prevent some psychological disorders to appear in the first place.
The overarching aim of the current study was to provide an overview of published UR on mental health from inception to November 2020. Specifically, I aimed to:
(a) Provide a big picture of the topics covered by UR and
(b) Summarize knowledge of those focused on studying risk and protective factors for diagnosed mental disorders. Excluding molecular genetic studies as well as those focused on
biomarkers as they cannot be strictly considered risk or protective factors, nor sufficiently reliable to be used as clinical criteria (Kim et al., 2020).
Methods Search Strategy
The Scopus, PubMed, and Web of Science (WoS) databases were systematically searched from inception to November 16 2020 to identify published UR containing the keywords: (
"umbrella review" OR "overview of reviews" OR "review of systematic reviews and meta- analyses" ) AND ( "psych* disorder" OR psych* OR "neurodevelopmental disorder" OR
"neurocognitive disorder" OR anxiety OR depression OR depressive OR psychosis OR schizophrenia OR "bipolar disorder" OR "posttraumatic stress disorder" OR "dissociative disorder" OR "sleep disorder" OR "sleep-wake disorder" OR "sexual dysfunction" OR
"gender dysphoria" OR "paraphilic disorder" OR paraphilia OR "conduct disorder" OR
"impulse control disorder" OR "disruptive disorder" OR "substance abuse" OR "addictive disorder" OR "personality disorder" OR "eating disorder" ).
Articles found with the search algorithm were initially screened on the basis of title and abstract reading in order to get a broader view of topics covered by the investigation on mental health and start the selection process described below in the section “Selection Criteria”.
Definition of UR
In this study, mental health UR were systematically searched following the definition given by Fusar-Poli & Radua, (2018) p.95):
“They are reviews of previously published systematic reviews or meta-analyses and consist in the repetition of meta-analyses following a uniform approach for all factors to allow their comparison. Therefore, they represent one of the highest levels of evidence synthesis currently available”. (p. 95)
Definition of Risk/Protective Factors
We used the definition of risk factor provided by Tortella-Feliu et al. (2019), based on
Kramer et al. (1997) and Mrazek and Haggerty (1994) "that characteristic, variable, or hazard preceding the outcome of interest that, if present for a given individual, makes it more likely that this individual, rather than someone selected from the general population, will develop a given disorder". In the same vein, a protective factor is that characteristic or variable
prospectively associated with a reduced probability to develop a specific disorder.
Data Extraction
From the reviewed UR, we extracted two main kinds of data: the association measures between risk/protective factors and outcomes (i.e. Hedge's g, Cohen's d, odd ratios (OR), incidence rate ratio (IRR), risk ratio (RR), and hazard ratio (HR)), and grades of evidence (Table 1) of these associations, when available. From the association measures, OR or equivalent OR (eOR) were prioritized.
We have excluded purely genetic or molecular UR. However, biomarkers analyzed for the elected UR were included as risk/protective factors.
Regarding grades of evidence, all the evidence extracted from MA and SR is not equal in terms of methodological quality, which it is transferred to UR, and it has an impact on credibility of the obtained results. With the purpose of making a distinction, Ioannidis (2009) first introduced criteria intended to classify evidence taking into consideration these differences. These criteria are presented in Table 1 and considered of recommended use according to Fusar-Poli & Radua (2018).
Table 1
Credibility assessment criteria for meta-analyses of observational studies
Classification Class Specifications
Convincing I • Number of cases >1000
• p<10-6
• I2<50%
• 95% prediction interval excluding the null
• No small-study effects
• No excess significance bias Highly
suggestive
II • Number of cases >1000
• p<10-6
• Largest study with a statistically significant effect
• Class I criteria not met Suggestive III • Number of cases >1000
• p<10-3
• Class I-II criteria not met
Weak IV • p<0.05
• Class I-III criteria not met
Non-significant NS • p>0.05
Note. Based on Fusar-Poli & Radua (2018).
The focus has been set on class evidence I and II, in its absence or when considered of relevance other classes of evidence were also included. All factors graded as class III, IV, and Non-significant (NS) evidence are depicted in Annex 1.
Due to its extension, all annexes containing the collected data besides other material discussed in this article, can be found in the Supplementary Material.
Results Selection Criteria
The process of search and selection is illustrated in a flowchart in Figure 1.
Figure 1
PRISMA flowchart showing the literature search results
The initial search (see the “search strategy” section above) resulted in 575 UR, remaining 10 eligible papers once the process was finished. First of all, repeated articles were removed.
Afterward, those which didn’t meet the criteria to be considered UR and those belonging to another health-related professional field were excluded. UR focused only on SR or MA and not both were excluded, solely considering UR embracing as much data available as possible.
MA is a key factor for an article to be considered a UR. Therefore, papers published as UR which hadn’t meta-analyzed the data extracted from original articles were also excluded, as well as those titled as protocol, narrative synthesis or commentary. Since only English papers were eligible, 3 articles were eliminated due to language reasons.
Through this first assessment, the remaining papers were categorized by the following topics: Methodology and professional practice, human behavior, health psychology, and clinical psychology. Taking special relevance those in the clinical psychology group, target of the vast majority of research on mental health (63%), which was divided into four major subgroups: Psychopathology, treatment, and risk/protective factors (see Table 2 and Annex 2). In the first place, psychopathology encompasses studies of biomarkers, epidemiology, and studies referring to symptoms instead of clinical diagnoses. In the second place, treatment stands for any intervention on either a symptom or a clinical diagnosed mental disorder, including pharmacological and psychological ones. In the third place, risk/protective factors studies include those analyzing the relation between specific factors and a clinical diagnosed mental disorder or a neurodevelopmental problem. The risk/protective factor subgroup represents the target of the present research. Even though, purely genetic or biomarkers’
studies were included as valid UR for the topic classification of research in mental health, those studies were not considered to be profoundly analyzed as an elected article for this review. However, isolated biomarkers analyzed in elected UR were included as
risk/protective factors.
17 UR on risk/protective factors were found. With regard to the topics, 2 UR on neurodegenerative diseases were excluded. After full-test screening, 5 UR were excluded for not meeting UR criteria, which leaves us with 10 elected UR to be analyzed. (See Annex 2 to find out the excluded documents).
Table 2
Classification of published umbrella reviews on mental health by topics
Topic Number of umbrella
reviews found per topic
Percentage distribution
Methodology and professional practice 1 1%
Human behavior 4 4.3%
Health psychology 29 31.5%
Clinical Psychology 58 63%
Psychopathology 10 10.9%
Treatment 31 33.7%
Risk/protective factors 17 18.5%
Note. The classification above is based on title and abstract screening, therefore, some of the umbrella reviews mentioned in this table may not meet criteria following the given definition to be considered one.
Assessment of UR
For descriptive purposes, risk and protective factors were classified as perinatal factors, biomarkers, socio-demographic and parental factors, developmental milestones, personality traits, infectious agents, drugs and other toxic substances, dietary factors, habits and lifestyle, medical conditions and comorbid diseases, mental health conditions and psychopathology, antecedents, and potentially traumatic events.
Overall, data from the 10 UR that met the eligibility criteria were extracted (see Table 3). Environmental risk/protective factors with their respective evidence of association grading and metrics were extracted from every UR. As far as metrics are concerned, random-effects measure (prioritizing OR/eOR when available), effect size and, confidence interval were extracted. When several reviews were accessible for the same association, two criteria were
used: methodological quality and recency. Psychosis and schizophrenia spectrum disorders (SSD) were clustered together therefore the data were classified accordingly.
Main Evidence Regarding Risk/Protective Factors
Specifically, from the analyzed umbrella reviews, including a total of 333 individual SR and MA, evidence has been found for ten diagnostic classes: autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), mental disorders with onset in
childhood/adolescence (including neuromotor deficits, mental development, dyslexia, cognitive and intellectual delay, emotiomal/behavioral problems, intellectual disability, and tic disorders), psychosis/SSD, bipolar affective disorder (BPAD), major depressive disorder (MDD), anxiety and obsessive-compulsive disorder (OCD), posttraumatic-stress disorder (PTSD), and eating disorders (ED) (listed in Table 3).
Table 3
Eligible umbrella reviews on risk/protective factors for psychological disorders
Authors Psychological disorder/neurodevelopmental problem Number of SR/MA included
Kim et al. (2019) Autism Spectrum Disorder 46
Kim et al. (2020) Attention-Deficit/Hyperactivity Disorder 35
Solmi et al. (2020) Mental disorders with onset in childhood/adolescence: neuromotor deficits, mental development, dyslexia, cognitive and intellectual delay; emotional/behavioural problems, intellectual disability, tic disorders.
10
Belbasis et al. (2018) Schizophrenia Spectrum Disorders 41
Radua et al. (2018) Psychosis 55
Bortolato et al. (2017) Bipolar Disorder 7
Köhler et al. (2018) Depression 78
Fullana et al. (2020) Anxiety and Obsessive-Compulsive Disorder 19
Tortella-Feliu et al. (2019) Posttraumatic Stress Disorder 33
Solmi et al. (2020) Eating Disorders 9
Note. SR/MA - Systematic Review/Meta-Analysis.
In the subsections below we synthesize the main outcomes regarding the
risk/protective factors with higher levels of evidence (class I) for each of the diagnostic classes mentioned above.
Autism Spectrum Disorder
As we can see in Table 4, seven risk factors met the criteria for class I evidence: Maternal age older than 35 years old, maternal chronic hypertension, maternal gestational hypertension, maternal pre-pregnancy overweight, maternal preeclampsia, pre-pregnancy maternal use of antidepressant and maternal SSRI exposure during pregnancy.
Some of those being elements of maternal metabolic syndrome (chronic hypertension, gestational hypertension, pre-eclampsia, and overweight).
Table 4
Class I evidence for Autism Spectrum Disorder
Note.
CI -
Confidence Interval; ES - Effect Size; OR - Odds Ratio; RR - Risk Ratio; SSRI - Selective Serotonin Reuptake Inhibitors.
Factor Random-effects measure, ES (95% CI)
Maternal age ≥35 years vs 25-29 years RR=1.31 (1.18-1.45)
Maternal chronic hypertension OR=1.48 (1.29-1.7)
Maternal gestational hypertension OR=1.37 (1.21-1.54)
Maternal pre-pregnancy or during pregnancy overweight
RR=1.28 (1.19-1.36)
Maternal preeclampsia RR=1.32 (1.2-1.45)
Pre-pregnancy maternal antidepressant use vs unexposed group
RR=1.48 (1.29-1.71)
Maternal SSRI exposure during pregnancy OR=1.84 (1.6-2.11)
Additionally, the factors of maternal overweight before or during pregnancy and SSRI use during pregnancy remained class I evidence even after sensitivity analyses.
Attention Deficit Hyperactivity Disorder
Class I evidence for ADHD is presented in Table 5. Three factors of maternal metabolic syndrome (hypertensive disorders during pregnancy, maternal preeclampsia, and maternal pre-pregnancy obesity) showed class I evidence. Maternal pre-pregnancy or during
pregnancy overweight is another factor related to maternal metabolic syndrome and it was associated with ADHD with highly suggestive evidence. Apart from those, childhood eczema also showed to be a convincing factor. As well as, acetaminophen use during pregnancy.
Table 5
Class I evidence for Attention Deficit and Hyperactivity Disorder
Factor Random-effects measure, ES (95% CI) Hypertensive disorders during pregnancy OR=1.29 (1.22-1.36)
Maternal preeclampsia OR=1.28 (1.21-1.35)
Acetaminophen use during pregnancy RR=1.25 (1.17-1.34)
Maternal pre-pregnancy obesity OR=1.63 (1.49-1.77)
Childhood eczema OR=1.31 (1.2-1.44)
Note. CI - Confidence Interval; ES - Effect Size; OR - Odds Ratio; RR - Risk Ratio.
Neurodevelopmental Disorders
Neither class I nor II association between any risk/protective factor and any mental disorder with onset in childhood/adolescence were found. The only association with suggestive evidence is between neuromotor deficits and maternal exposure to lithium and antipsychotics during pregnancy.
Schizophrenia Spectrum Disorder/Psychosis
Results concerning class I associations are presented in Table 6. After analyzing 170 factors and their respective association with SSD and psychosis, 2 factors were graded as class I evidence. One having Black-Caribbean ethnicity in England and the other being ultra-high- risk state.
Table 6
Class I evidence for Schizophrenia Spectrum Disorder/Psychosis
Factor Random-effects measure, ES (95% CI)
Ultra-high-risk state for psychosis RR=9.32 (4.91-17.72)
Black-Caribbean ethnicity in England IRR=4.87 (3.96-6.00)
Note. CI - Confidence Interval; ES - Effect Size; IRR - Incidence Rate Ratio; RR - Risk Ratio.
Minor physical anomalies were associated with psychosis, a relation supported with class II evidence. Results indicated a weak association with the male gender and a highly suggestive association with age (15-35 years old vs other ages). Exposure to stressful events during adulthood, exposure to childhood adversities, cannabis use, and serum folate level were associated with SSD supported with class II evidence. A history of obstetric
complications was associated with an increased risk of SSD onset.
Once sensitivity analysis were applied, the factor ultra-high-risk state remained as class I evidence, the only factor remaining in this category for SSD. Being Black-Caribbean ethnicity in England moved back in grading to class IV evidence after the sensitivity
analyses. Urbanicity remained class III and childhood adversities class II.
Bipolar Disorder
Irritable bowel syndrome (ES=2.48, 95% CI 2.35-2.61) happened to be the only class I evidence risk factor for BD.
A few other high-quality pieces of evidence for this disease are childhood trauma (graded as class II), obesity, and asthma (both graded as class III).
Depression
Seven factors reach class I evidence associations with MDD as displayed in Table 7.
Although after sensitivity analysis of the prospective studies the protective factors tea intake and dietary zinc didn't remain significant.
Metabolic risk factors showed a correlation with MDD, with convincing evidence having 4 or 5 metabolic risk factors, highly suggestive evidence having 3 metabolic factors, suggestive evidence having 2 metabolic factors, decreasing to weak evidence in the case of having 1 metabolic factor. Overall, being overweight was associated with MDD (class IV evidence) as well as obesity (class III evidence). Sedentary behavior was graded as class II evidence implying an increased risk for MDD. Vegetable intake was associated with MDD as class IV evidence and fruit intake as class III. Overall Mediterranean dietary patterns and the adherence to those patterns were also associated with MDD (class IV) in addition to
traditional/healthy dietary patterns (class III).
Table 7
Class I evidence for Major Depressive Disorder
Factor Random-effects measure, ES (95% CI)
Physical abuse in childhood OR=1.98 (1.68-2.33)
4 or 5 metabolic risk factors OR=2.06 (1.59-2.68)
Sexual dysfunction OR=2.71 (1.93-3.79)
Dietary zinc RR=0.65 (0.57-0.75)
Tea intake RR=0.68 (0.61-0.77)
Job strain OR=1.77 (1.46-2.13)
Widowhood (vs any other marital status) RR=5.59 (3.79-8.23) Note. CI - Confidence Interval; ES - Effect Size; OR - Odds Ratio; RR - Risk Ratio.
Although little is known about late-life depression (LLD) stages since no convincing evidence for any risk/protective factor has been found, health-related problems were
associated with this specific type of depression. Specifically, poor health and having a chronic disease showed class II and III evidence respectively.
Anxiety Disorders
On the one hand, being male was associated with decreased risk for most of the disorders analyzed (specific phobia (SP), generalized anxiety disorder (GAD), and panic disorder (PD)). On the other hand, neuroticism was associated with increased risk for SP, social anxiety disorder (SAD), and OCD. Criteria had to be adjusted in both cases, changing from class IV evidence to class I and II respectively. Neuroticism maintained this evidence grade (class II) even after the sensitivity analyses were taken.
Additionally, other risk factors, as for early traumatic experiences were associated with all anxiety disorders investigated (SAD, GAD, PD, and OCD).
In the subsections below, risk factors specifically related with each of the individual anxiety disorders are summarized.
Specific Phobia. It hasn't been found any class I nor II association for this disorder. It was only when the n>1000 criterion was removed that being a male became a class I
evidence protective factor to specific phobia.
Social Anxiety Disorder. Early physical and sexual trauma resulted to be the only class I evidence (OR = 2.59, 95% CI 2.17-3.1) and class III evidence risk factors for SAD, respectively.
Early physical trauma was reported by Fullana et al., (2020) as "the single most consistent risk factor– class I – for SAD" and it remained class I even after the sensitivity analyses.
Generalized Anxiety Disorder. The evidence for GAD was class IV for all factors analyzed. Only when removing the n>1000 criterion better quality results were found. In spite of this adaptation, no convincing evidence was found for any of the factors except for being male which has already been addressed.
Panic Disorder. No factor showed convincing evidence as a risk factor for PD. After removing the n>1000 criterion the factors of separation anxiety in childhood and early physical trauma became convincing evidence.
Obsessive-Compulsive Disorder
No factor was graded as convincing evidence for OCD. Removing the n>1000 criterion enhanced the association with the factors: use of cocaine simultaneously with another drug (excluding cannabis), parental rearing style, and neuroticism. Those factors became class II evidence risk factors for OCD. Although these changes were preserved after the sensitivity analyses only for the first two listed risk factors.
Posttraumatic-Stress Disorder
Class I factors associated with PTSD are presented in Table 8. Disease history, being indigenous people of the Americas, and family history of psychiatric disorders showed a convincing association with PTSD. Furthermore, being a woman, trauma severity,
cumulative exposure to potentially traumatic experiences, and being trapped showed highly suggestive evidence for the increased risk of PTSD.
Table 8
Class I evidence for Posttraumatic-Stesss Disorder
Factor Random-effects measure, ES (95% CI)
Disease history OR=2.29 (2.07-2.52)
Indigenous people of the Americas OR=1.47 (1.28-1.69)
Family history of psychiatric disorder OR=1.80 (1.48-2.19) Note. CI - Confidence Interval; ES - Effect Size; OR - Odds Ratio.
After sensitivity analyses, there weren’t changes in class I, II nor III factors, except for the factor being indigenous people of the Americas which became a NS factor in predicting the disorder's risk afterward.
Some of the factors that didn't obtain significant results are low education, low intelligence, coping styles, social and, familiar support.
Eating Disorders
Even though no factor showed convincing evidence as a risk factor for ED, appearance- related teasing victimization showed highly suggestive evidence as a risk factor for any ED.
Initial body dissatisfaction, initial perceived pressure to be thin, ADHD, and initial negative affect were associated with ED with class III evidence.
In the subsections below, risk factors specifically related with each of the individual ED are summarized.
Anorexia nervosa. The factor 5 minutes of Apgar score below 7 points was related to anorexia nervosa (AN) with class III evidence.
Bulimia nervosa. When it comes to bulimia nervosa (BN), child sexual abuse is a class II and initial self-responding dieting a class III risk factor for the disorder.
Binge eating disorder. Physical abuse in childhood and ADHD showed class III associations with binge eating disorder (BED).
Protective Factors
As a way to better understand the data analyzed, protective factors were also described separately and depicted for each specific psychological disorder in Table 9. Protective factors were clustered by mental disorder and discussed in the sections below.
Autism Spectrum Disorder. In terms of protective factors, two factors were found to decrease the likelihood of the disorder. Those are: folic acid supplementation during pregnancy and breastfeeding, both of them graded as weak evidence.
Table 9
Protective factors for different mental disorders
Category Factor ASD ADHD SSD/
psychosis
MDD Anxiety Disorders OCD
SP GAD PD
Perinatal factors
Folic acid supplementation
during pregnancy
IV RR=0.77
(0.64- 0.93) Perinatal
factors
Breastfeeding IV OR=0.61
(0.45- 0.83)
IV OR=0.7
(0.53- 0.93) Socio-
demographic and parental
factors
60-69 year-old vs. other
IV IRR=0.26
(0.14- 0.51) Socio-
demographic and parental
factors
55-64 year-old vs. other
IV IRR=0.30
(0.17- 0.51) Socio-
demographic and parental
factors
50-59 year-old vs. other
IV IRR=0.50
(0.27- 0.93) Socio-
demographic and parental
factors
40-49 year-old vs. other
IV IRR=0.54
(0.35- 0.83) Socio-
demographic and parental
factors
35-44 year-old vs. other
IV IRR=0.80
(0.70- 0.93) Dietary
factors
Tea intake I
RR=0.68 (0.61-
0.77) Dietary
factors
Dietary zinc I
RR=0.65 (0.57-
0.75) Socio-
demographic and parental
factors
Male gender IV
OR=0.43 (0.36-
0.51)
IV OR=0.5
(0.41- 0.59)
IV OR=0.5
(0.39- 0.64) Socio-
demographic and parental
factors
Warmth from father
IV eOR=0.31
g= -0.64 (-0.87 to - 0.42) Note. ADHD - Attention Deficit Hyperactivity Disorder; ASD - Autism Spectrum Disorder; eOR - Equivalent Odds Ratio; GAD - Generalized Anxiety Disorder; IRR - Incidence Rate Ratio; MDD - Major Depressive Disorder; OCD - Obsessive-Compulsive Disorder; OR - Odds Ratio; PD - Panic Disorder; RR - Risk Ratio; SP - Specific phobia; SSD - Schizophrenia Spectrum Disorder.
Attention Deficit Hyperactivity Disorder. Breastfeeding showed to be a protective factor for
ADHD with a class IV association.
Schizophrenia. Age over 35 years old showed to be a protective factor with class IV
association evidence for psychosis.
Mendelian randomization studies found a suggestive association of serum C-reactive protein (CRP) level and schizophrenia, but this evidence should be inspected due to the potential biases involved such as reverse causality.
Major Depressive Disorder. Tea consumption and dietary zinc intake were found to be class
I protective factors. Proving that those variables may protect from developing depression.
Anxiety Disorders (Specific Phobia, Generalized Anxiety Disorder, and Panic Disorder).
Being a male was found to be a class IV protective factor, becoming class I after removing the criterion of n>1000.
Obsessive-Compulsive Disorder. Emotional warmth from the father showed class IV
statistically significant protective effects against OCD. Becoming class II after removing the criterion of n>1000.
Cogent Factors for Mental Disorders
Several factors, from diverse categories (e.g. perinatal, sociodemographic, medical conditions, personality traits…) were found to be significantly associated to more than 3 diagnoses (listed in Table 10). The class of evidence, effects measure, effect size, and confidence interval are indicated for every association below.
Having diabetes while pregnant has been associated with ASD (class III, RR=1.49 [1.28-1.74]), ADHD (class III, HR=1.36 [1.19-1.55]), and SSD/psychosis (class IV, OR=10.12 [1.84-55.72]).
Table 10
Significant risk/protective factors for 3 or more mental disorders.
Category Risk/protective factors Mental disorders related to a specific factor
1 2 3 4 5
Perinatal factors Diabetes in pregnancy ASD ADHD SSD/
psychosis Pre-pregnancy obesity ASD ADHD Conduct
disorders
Cognitive and intellectual delay
SSD/
psychosi s Socio-demographic
and parental factors
Male gender SP GAD PD
Personality traits Neuroticism SSD/
psychosis
SP SAD OCD
Medical conditions and comorbid diseases
Diabetes MDD BN ED
Traumatic brain injury/
head injury
SSD/
psychosis
BPAD MDD
Mental health conditions and psychopathology
ADHD PTSD BED ED
MDD SAD PD PTSD
Potentially traumatic events
Childhood trauma SSD/
psychosis
BPAD PD
Early physical trauma SAD GAD PD
Early sexual trauma SAD GAD PD
Emotional abuse in childhood
MDD ANR BN BED
Physical abuse ANR ANBP BN BED ED
Physical abuse in childhood
MDD GAD BED
Sexual abuse AN ANBP BN BED ED
Sexual abuse in childhood MDD AN BN BED
Note. ADHD - Attention Deficit with Hyperactivity Disorder; ANBP - Binge-Purge Anorexia Nervosa; ANR - Restrictive Anorexia Nervosa; ASD - Autism Spectrum Disorder; BED - Binge Eating Disorder; BN - Bulimia Nervosa; BPAD - Bipolar Anxiety Disorder; ED - Eating Disorder; GAD - Generalized Anxiety Disorder; MDD - Major Depressive Disorder; OCD - Obsessive-Compulsive Disorder; PD - Panic Disorder; PTSD -
Posttraumatic-Stress Disorder; SAD - Social Anxiety Disorder; SSD - Schizophrenia Spectrum Disorder; SP - Specific Phobia.
Pre-pregnancy obesity to ASD (class IV, OR=1.36 [1.12 1.65]), ADHD (class I, OR=1.63 [1.49-1.77]), cognitive and intellectual delay (class IV, OR=1.51 [1.37-1.66]), conduct disorders (class IV, OR=1.42 [1.23-1.64]), and SSD/psychosis (class IV, OR=1.99 [1.26-3.14]).
Being a male showed to be a protective factor related to anxiety disorders, specifically SP (class IV, OR=0.43 [0.36-0.51]), GAD (class IV, OR=0.5 [0.41-0.59]), and PD (class IV, OR=0.5 [0.39-0.64]).
Neuroticism with SSD/psychosis (class IV, eOR=8.76, g=1.20 [0.88-1.52]), SP (class IV, eOR=4.35, g=0.81 [0.57-1.05]), SAD (class IV, eOR=5.02, g=0.89 [0.67-1.12]), and OCD (class IV, eOR=9.31,g=1.23 [0.96-1.5]).
Diabetes has been related to MDD (class IV, RR=1.25 [1.17-1.34]), BN (class IV, eOR=1.94, d=0.36 [0.13-0.60]), and ED (class IV, eOR=2.30, d=0.46 [0.10-0.82]).
Traumatic brain injury to SSD/psychosis (class IV, OR=1.49 [1.09-2.05]), BPAD (class IV, ES=1.85 [1.17-2.94]), and MDD (class IV, OR=3.41 [2.40-4.84]).
ADHD has been significantly related with increased probabilities to develop PTSD (class IV, RR=3.13 [1.12-8.73]), BED (class III, OR=3.93 [2.09-7.38]), and ED (class III, OR=4.24 [2.62-6.87]).
MMD with SAD (class IV, IRR=9.35 [4.71-18.54]), PD (class IV, OR= 2.03 [1.66- 2.49]), and PTSD (class IV, OR=2.8 [1.17-6.67]).
Childhood trauma has been related to SSD/psychosis (class III, OR=2.87 [2.07-3.98]), BPAD (class II, ES=2.86 [2.03-4.04]), and PD (class IV, OR=3.56 [1.86-6.8]).
Early physical trauma to SAD (class I, OR=2.59 [2.17-3.1]), GAD (class IV, OR=2.39 [1.92-2.98]), and PD (class IV, OR=2.46 [1.95-3.11]).
Early sexual trauma to SAD (class III, OR=3.18 [1.73-5.86]), GAD (class IV,
OR=3.28 [2.6-4.14]), and PD (class IV, OR=2.91 [1.67-5.08]). Related to that, when the risk
factor has been specifically labeled as sexual abuse in childhood it has also been associated to MDD (class II, OR=2.42 [1.94-3.02]), AN (class IV, OR=1.92 [1.13-3.27]), BN (class II, OR=2.73 [1.96-3.79]), and BED (class III, OR=2.31 [1.66-3.20]).
Emotional abuse in childhood is associated to MDD (class II, OR=2.78 [1.89-4.09]), restrictive anorexia nervosa (ANR) (class IV, OR=3.52 [1.68-7.38]), BN (class IV, OR=5.13 [2.80-9.39]), and BED (class IV, OR=2.44 [1.73-3.48]).
Physical abuse in childhood has been related to MDD (class I, OR=1.98 [1.68-2.33]), GAD (class IV, OR=1.82 [1.33-2.48]), and BED (class III, OR=3.10 [2.48-3.88]).
Physical abuse (irrespective of age) to ANR (class IV, OR=2.65 [1.33-5.28]), Binge- Purge Anorexia Nervosa (ANBP) (class IV, OR=2.76 [1.44-5.29]), BN (class IV, OR=3.43 [2.19-5.39]), BED (class IV, OR=2.57 [1.99-3.30]), and ED (class IV, OR=2.96 [1.89-4.62]).
And finally, sexual abuse (irrespective of age) to AN (class IV, OR=1.74 [1.09-2.79]), ANBP (class IV, OR=2.80 [1.23-6.36]), BN (class IV, OR=2.48 [1.70-3.60]), BED (class IV, OR=1.88 [1.38-2.55]), and ED (class IV, OR=2.29 [1.36-3.87]).
Discussion
This systematic overview of the 10 UR published on the topic provides a synthesis on the 564 non purely genetic risk/protective factors, identified in the 233 individual SR and MA
included in them, for diagnosed psychological disorders. And, perhaps more important, the strength of every association between those factors and the specific psychopathological diagnostic categories and the relevance every factor has indeed, if it had any, have been reported.
Five hundred and fifty-three potential risk factors and 11 potential protective factors have been identified by the different UR analyzed. Of all of them, only 25 meet criteria to be considered class I evidence, making the existence of the association very clear.
This set of evidence is extremely valuable due to the inherent quality of UR research, meeting the most demanding criteria which only allows for the best methodological SR and MA to be selected, and thus its findings.
In another vein, we have more knowledge regarding ASD, ADHD, and MDD than for ED, anxiety, and other NDDs different from ASD and ADHD. In fact, NDDs, LLD, SP, GAD, PD, OCD, and the whole aggregate of ED have no class I association with any of the risk/protective factors analyzed.
It appears to be clear that there, contrary to what we might think, we have limited knowledge on true risk factors for some highly prevalent disorders (e.g. anxiety disorders or ED) as none of the studied risk factors have been strongly and consistently found to be
associated with an increased probability to develop some of these disorders. In that sense, UR can be seen as a useful tool to identify these gaps and also to correct the potential bias on what we really know in the field of mental health.
On the contrary, some risk factors are clearly associated with most of mental disorders. Factors in the category “potentially traumatic events” have been related with almost all the disorders with available published UR, specifically, SSD, BPAD, MDD, SAD, GAD, PD, AN, ANR, ANBP, BN, BED, and ED. Convincingly proving that they are a crucial cluster of risk factors.
With regard to the association between a preexisting mental health disorder and the emergence of another mental health condition, ADHD and MDD have shown to be solid risk factors to suffer other mental health disorders as diverse as PTSD, BED, ED, and PTSD, SAD, and PD, respectively. But MDD doesn’t always act as a risk factors, it has been shown to be related to many medical conditions as a consequence. For example, it has been proved that traumatic brain injury is a risk factor for different disorders: SSD, BPAD, and MDD as well. Another example of a clear risk factor is diabetes related to MDD, BN, and ED, in
addition to being considered a risk factor during pregnancy as well, in this case increasing the risk of ASD, ADHD, and SSD/psychosis.
Several authors support the idea of a common cause for mental disorders since
comorbidities are pretty high (Radua, 2018). Accordingly, some shared risk/protective factors found in this research support the transdiagnostic hypothesis. Given the fact that many factors are significantly associated with up to 6 different disorders.
Along the same line of reasoning, comorbidity between ASD and ADHD has been found. Some components of the metabolic syndrome and acetaminophen exposure during pregnancy showed robust association with both disorders. Those findings support the
pathological similarities and open the possibility of shared risk factors implying multifinality together with equifinality features. Future investigation into this topic would be of great importance.
For ASD, convincing evidence manifested that maternal age is a powerful predictor of the offspring's possibilities of having the disorder. Elements of maternal metabolic syndrome:
chronic hypertension, gestational hypertension, pre-eclampsia, and overweight are class I risk factors for ASD.
Overall, maternal health before and during pregnancy shows to be decisive in predicting the risk of the disorder. The same evidence was found for ADHD, proving the relevance of metabolic factors in the risk of the disorder’s onset. Emphasizing metabolic health of the mother as a key factor during pregnancy.
Moving to depression, sedentary behavior is a risk factor with class II evidence which translates into higher probabilities of MDD. This fact supports the premise of Cognitive and Behavior Therapy (Rush, Khatami, & Beck, 1975) and Behavioral Activation Therapy (Jacobson et al., 1996).
In the same line of thought, lifestyle could come to mind. Vegetable intake, fruit intake, Mediterranean dietary patterns, adherence to those patterns, and traditional/healthy dietary patterns were associated with MDD. Even though is not the strongest set of data, it brings to the table the importance of lifestyle choices when it comes to mental health, as well as the interconnection between both physical and mental health and dietary choices (Bujtor et al., 2021).
The association between SSD with the exposure to physical or psychological adversities during childhood and adulthood, and cannabis was supported with robust evidence and tremendous effect size.
Cannabis as a risk factor for SSD is supported by class II evidence which goes by the findings for this spectrum of disorders (Andrade, 2016; Vaucher et al., 2018). Heavy
cannabis use was found to be a weak risk factor, even though this could be explained by the singular level of vulnerability, developing those individuals with higher vulnerability to the disorder in the first stages of consumption.
Even though phobias are pretty common in the general population, we know near to nothing in terms of risk factors. The reason could be the nonclinical nature of those phobias which tend to be either subclinical or nonrelevant for the person suffering from it (Belloch, Sandín & Ramos, 2011).
Despite the fact that most factors associated with anxiety disorders were rated as weak, the consistency of those correlations through the specific disorders gives them more value. The possibility of shared risk between anxiety disorders and OCD should be noticed.
As for GAD, factors related to trauma were graded as class IV associations for the disorder which corroborates one of Borkovec’s possible causes for this disorder, more investigation is needed to verify the presence of insecure bonding (Belloch, Sandín, & Ramos, 2009). GAD was also associated with harm avoidance (class IV evidence).
Interestingly, neuroticism hasn’t been proven to have a strong association with any of the anxiety disorders. Showing class IV association with SP, SAD, and OCD.
In the case of PTSD, post-trauma factors have less predictive value than pre and peri- trauma ones, which is a game-changer as far as prevention is concerned.
ED are a set of psychological pathologies with a lack of convincing evidence which could be caused by deficiency of investigation or the great clinical heterogeneity in particular cases. ED patients share common features and, often, mental health comorbidities. Some of them are MDD, anxiety, OCD, interpersonal sensitivity, and feelings of ineffectiveness.
According to Solmi et al., (2020) those features have a greater impact than any specific or behavioral psychopathology.
Specificity of risk factors could be reduced following this evidence's guide. The transdiagnostic nature of risk factors happens to be unexplored even though it could allow the transdiagnostic detection and intervention of ED.
Appearance-related teasing victimization was identified as a class II risk factor to suffer any kind of ED, supporting the hypothesis of social and interpersonal performance as a risk factor for ED (Solmi et al., 2020).
Another issue that cannot be ignored is the rate at which UR publications have hastily been increasing since UR was originated. For UR to be sustainable and serve the purpose for which was intended, it appears to be relevant to use it according to its definition. If it is done like so, it will be easier to discriminate from other articles. Apart from serving to slow down the publication rate.
On the whole, as a result of the incorporation of UR as research tools, it is clear that even though there isn’t as much certain evidence as we would have thought, there are various astonishingly clear associations providing valuable information to the scientific community,
both researchers and clinicians. Evidence that leads the path to be followed to enhance the knowledge and practice in mental health.
References
Andrade, C. (2016). Cannabis and neuropsychiatry, 2: The longitudinal risk of psychosis as an adverse outcome. Journal of Clinical Psychiatry, 77(6), e739-e742.
doi:10.4088/JCP.16f10918
Aromataris, E., Fernandez, R., Godfrey, C. M., Holly, C., Khalil, H., & Tungpunkom, P.
(2015). Summarizing systematic reviews: Methodological development, conduct and reporting of an umbrella review approach. International Journal of Evidence-Based Healthcare, 13(3), 132-140. doi:10.1097/XEB.0000000000000055
Barlow, D. H., Durand, V. M. & Hofmann, S. G. (2018). Abnormal Psychology. An integrative approach (8th edition). Cengage Learning.
Bastian, H., Glasziou, P., & Chalmers, I. (2010). Seventy-five trials and eleven systematic reviews a day: How will we ever keep up? PLoS Medicine, 7(9)
doi:10.1371/journal.pmed.1000326
Belbasis, L., Köhler, C. A., Stefanis, N., Stubbs, B., van Os, J., Vieta, E., Seeman, M. V., Arango, C., Carvalho, A. F., & Evangelou, E. (2018). Risk factors and peripheral biomarkers for schizophrenia spectrum disorders: An umbrella review of meta- analyses. Acta Psychiatrica Scandinavica, 137(2), 88-97. doi:10.1111/acps.12847 Belloch, A., Sandín, B., & Ramos, F. (2009). Manual de Psicopatología (Vol. II). McGraw
Hill Interamericana.
Bortolato, B., Köhler, C. A., Evangelou, E., León-Caballero, J., Solmi, M., Stubbs, B., Belbasis, L., Pacchiarotti, I., Kessing, L. V., Berk, M., Vieta, E., & Carvalho, A. F.
(2017). Systematic assessment of environmental risk factors for bipolar disorder: An umbrella review of systematic reviews and meta-analyses. Bipolar Disorders, 19(2), 84-96. doi:10.1111/bdi.12490
Bujtor, M., Turner, A. I., Torres, S. J., Esteban-Gonzalo, L., Pariante, C. M., & Borsini, A.
(2021). Associations of dietary intake on biological markers of inflammation in children and adolescents: A systematic review. Nutrients, 13(2), 1-29.
doi:10.3390/nu13020356
Fullana, M. A., Tortella-Feliu, M., Fernandez de la Cruz, L., Chamorro, J., Perez-Vigil, A., Ioannidis, J. P. A., Solanes, A., Guardiola, M., Almodovar, C., Miranda-Olivos, R., Ramella-Cravaro, V., Vilar, A., Reichenberg, A., Mataix-Cols, D., Vieta, E., Fusar- Poli, P., Fatjo-Vilas, M., & Radua, J. (2020). Risk and protective factors for anxiety and obsessive-compulsive disorders: an umbrella review of systematic reviews and meta-analyses. Psychological Medicine, 50(8), 1300-1315.
https://doi.org/10.1017/s0033291719001247
Fusar-Poli, P., & Radua, J. (2018). Ten simple rules for conducting umbrella reviews.
Evidence-Based Mental Health, 21(3), 95-100. Doi:10.1136/ebmental-2018-300014 Huizink, A. C., & De Rooij, S. R. (2018). Prenatal stress and models explaining risk for
psychopathology revisited: Generic vulnerability and divergent pathways.
Development and Psychopathology, 30(3), 1041-1062.
doi:10.1017/S0954579418000354
Jacobson, N. S., Dobson, K. S., Truax, P. A., Addis, M. E., Koerner, K., Gollan, J. K., Gortner, E., & Prince, S. E. (1996). A component analysis of cognitive - behavioral treatment for depression. Journal of Consulting and Clinical Psychology, 64(2), 295- 304. doi:10.1037/0022-006X.64.2.295
Ioannidis, J.P.A., 2009. Integration of evidence from multiple meta-analyses: a primer on umbrella reviews, treatment networks and multiple treatments meta-analyses. Can.
Med. Assoc. J., 181, 488–493. https://doi.org/10.1503/cmaj.081086.
Kim, J. H., Kim, J. Y., Lee, J., Jeong, G. H., Lee, E., Lee, S., Lee, K. H., Kronbichler, A., Stubbs, B., Solmi, M., Koyanagi, A., Hong, S. H., Dragioti, E., Jacob, L., Brunoni, A.
R., Carvalho, A. F., Radua, J., Thompson, T., Smith, L., Oh, H., Yang, L., Grabovac, I., Schuch, F., Fornaro, M., Stickley, A., Rais, T. B., Salazar de Pablo, G., Shin, J. I.,
& Fusar-Poli P. (2020). Environmental risk factors, protective factors, and peripheral biomarkers for ADHD: an umbrella review. Lancet Psychiatry, 7(11), 955-970. doi:
10.1016/S2215-0366(20)30312-6
Kim, J. Y., Son, M. J., Son, C. Y., Radua, J., Eisenhut, M., Gressier, F., Koyanagi, A, Carvalho, A. F., Stubbs, B., Solmi, M., Rais, T. B., Lee, K. H., Kronbichler, A., Dragioti, E., Shin, J. I., & Fusar-Poli, P. (2019). Environmental risk factors and biomarkers for autism spectrum disorder: An umbrella review of the evidence. The Lancet Psychiatry, 6(7), 590-600. doi:10.1016/S2215-0366(19)30181-6
Köhler, C. A., Evangelou, E., Stubbs, B., Solmi, M., Veronese, N., Belbasis, L., Bortolato, B., Melo, M. C. A., Coelho, C. A., Fernandes, B. S., Olfson, M., Ioannidis, J. P. A., &
Carvalho, A. F. (2018). Mapping risk factors for depression across the lifespan: An umbrella review of evidence from meta-analyses and mendelian randomization studies. Journal of Psychiatric Research, 103, 189-207.
doi:10.1016/j.jpsychires.2018.05.020
Kraemer, H. C., Kazdin, A. E., Offord, D. R., Kessler, R. C., Jensen, P. S., & Kupfer, D. J.
(1997). Coming to terms with the terms of risk. Archives of General Psychiatry, 54(4), 337-343. doi:10.1001/archpsyc.1997.01830160065009 Lunny, C., Brennan, S. E., McDonald, S., & McKenzie, J. E. (2017). Toward a
comprehensive evidence map of overview of systematic review methods: Paper 1- purpose, eligibility, search and data extraction. Systematic Reviews, 6(1)
doi:10.1186/s13643-017-0617-1
Lunny, C., Brennan, S. E., McDonald, S., & McKenzie, J. E. (2018). Toward a
comprehensive evidence map of overview of systematic review methods: Paper 2 - risk of bias assessment; synthesis, presentation and summary of the findings; and assessment of the certainty of the evidence. Systematic Reviews, 7(1)
doi:10.1186/s13643-018-0784-8
Mrazek, P.J., Haggerty, R.J., (1994). Reducing Risks for Mental Disorders. National Academies Press, Washington, D.C. https://doi.org/10.17226/2139.
Pollock, M., Fernandes, R.M., Becker, L.A., Featherstone, R., & Hartling, L. (2016). What guidance is available for researchers conducting overviews of reviews of healthcare interventions? A scoping review and qualitive metasummary. Systematic Reviews, 5(1) doi:10.1186/s13643-016-0367-5
Radua, J., Ramella-Cravaro, V., Ioannidis, J. P. A., Reichenberg, A., Phiphopthatsanee, N., Amir, T., Thoo, H. Y., Oliver, D., Davies, C., Morgan, C., McGuire, P., Murray, R.
M., & Fusar-Poli, P. (2018). What causes psychosis? an umbrella review of risk and protective factors. World Psychiatry, 17(1), 49-66. doi:10.1002/wps.20490
Rush, A. J., Khatami, M., & Beck, A. T. (1975). Cognitive and behavior therapy in chronic depression. Behavior Therapy, 6(3), 398-404. doi:10.1016/S0005-7894(75)80116-X Schultz, A., Goertzen, L., Rothney, J., Wener, P., Enns, J., Halas, G., & Katz, A. (2018). A
scoping approach to systematically review published reviews: Adaptations and recommendations. Research Synthesis Methods, 9(1), 116-123.
doi:10.1002/jrsm.1272
Solmi, M., Dragioti, E., Arango, C., Radua, J., Ostinelli, E., Kilic, O., Yilmaz, U. E.,
Yalcinay-İnan, M., Soares, F. C., Mariano, L., Mosillo, P., Cortese, S., Correll, C. U., Carvalho, A. F., Shin, J. I., & Fusar-Poli, P. (2020). Risk and protective factors for mental disorders with onset in childhood/adolescence: An umbrella review of
published meta-analyses of observational longitudinal studies. Neurosci Biobehav Rev, 120, 565-573. doi: 10.1016/j.neubiorev.2020.09.002.
Solmi, M., Radua, J., Stubbs, B., Ricca, V., Moretti, D., Busatta, D., Carvalho, A. F., Dragioti, E., Favaro, A., Monteleone, A. M., Shin, J. I., Fusar-Poli, P., & Castellini, G. (2020). Risk factors for eating disorders: an umbrella review of published meta- analyses. Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999), 43(3), 314-323.
https://doi.org/10.1590/1516-4446-2020-1099
Tortella-Feliu, M., Fullana, M. A., Pérez-Vigil, A., Torres, X., Chamorro, J., Littarelli, S. A., Solanes, A., Ramella-Cravaro, V., Vilar, A., Gonzalez-Parra, J. A., Andero, R.,
Reichenberg, P. A., Mataix-Cols, P. D., Vieta, E., Fusar-Poli, P., Ioannidis, P. J. P. A., Stein, P. M. B., Radua, J., & Fernandez de la Cruz, L. (2019). Risk factors for
posttraumatic stress disorder: An umbrella review of systematic reviews and meta- analyses. Neuroscience and Biobehavioral Reviews, 107, 154-165.
doi:10.1016/j.neubiorev.2019.09.013
Vaucher, J., Keating, B. J., Lasserre, A. M., Gan, W., Lyall, D. M., Ward, J., Smith, D. J., Pell, J. P., Sattar, N., Pare, G., & Holmes, M. V. (2018). Cannabis use and risk of schizophrenia: A mendelian randomization study. Molecular Psychiatry, 23(5), 1287- 1292. doi:10.1038/mp.2016.252
World Health Organization, Secretariat for the development of a comprehensive mental health action plan (2012). Risk to mental health: An overview of vulnerabilities and risk factors. Ginebra: World Health Organization. Access at
www.who.int/mental_health/mhgap/risks_to_mental_health_EN_27_08_12.pdf
