Mood and anxiety disorders are not only common and responsible for much functional disability [1], but epidemiological studies also indicate that their prevalence, circa 10% in Western countries, has not fallen since the 1970s despite the development of evidence-based treatments [2‒8]. Prevalence refers to the percentage of adults in the general population that meet diagnostic criteria in a defined period, usually the 30 days (point prevalence) or 12 months (12-month prevalence) preceding the examination irrespective of possible earlier episodes.

In sharp contrast, multiple studies have documented substantial increases in expenditures on mental health care and in treatment rates in Western countries [9‒15]. The evidence on increased treatment rates comes from both general practice [16‒18], nation-wide morbidity registrations [19, 20], and repeated population-based surveys [8, 21]. The treatment rate increase was bolstered by the introduction of a new class of drugs in the 1980s, the selective serotonin reuptake inhibitors, aggressively marketed by Big Pharma [22]. In addition, a number of evidence-based psychological treatments became available for people with mood and anxiety disorders.

The trend data on prevalence and treatment rate reveal a remarkable paradox: more treatment but not less disorders, the treatment-prevalence paradox. The expectation to see a declining trend in the prevalence of mood and anxiety disorders with an increasing trend in treatment is not unfounded. Treatment seeks to shorten illness episodes, prevent worsening and the development of comorbidity, reduce relapses and curtail recurrences. If effective, increased treatment rates should result in lower prevalence rates in the general population, but this prevalence reduction has not occurred. The increase in the use of statins has led to significant reduction in population cholesterol levels [23]. Likewise, more and better treatment of hypertension has led to less hypertension and associated illness such as heart attacks and strokes illness [24, 25]. At least seven hypotheses can explain why more and better treatments have not reduced common mental disorder prevalence:

1. Increased willingness of individuals to report symptoms and pressures to diagnose distress as anxiety or depression has inflated prevalence rates and masked a true treatment-driven prevalence drop (further: diagnostic inflation).

2. Mood and anxiety disorders first incidence has increased and offset a treatment-driven prevalence drop.

3. Randomized controlled trials (RCTs) have overestimated the acute-phase treatment efficacy and so have [4] treatments targeted at maintaining acute-phase treatment gains.

5. Trial efficacy does not generalize to real-world effectiveness.

6. Treatment has benefited nonrecurrent/nonchronic cases more than chronic-recurrent cases while treatment’s population-level impact is much larger for the latter.

7. Counterproductive effects of treatment have reduced its effectiveness to impact at the population level.

Willingness of individuals to present distress in treatment settings on the one hand and over-medicalization by providers on the other may have increased in recent decades [22, 26‒28]. In combination with the lack of physiological criteria, the imperfections in measurement and diagnostic systems including the increase of diagnostic entities and changes in diagnostic criteria [29‒31], these trends could have inflated prevalence rates in epidemiological studies [32]. Stable prevalence rates would then mask a true treatment-driven prevalence drop.

Although it is likely that the trends of increased willingness and medicalization have inflated prevalence rates in general medical settings [22, 28, 33], the evidence suggests that it is less likely that any systematic drift in “caseness” has occurred in population-based epidemiologic surveys if these surveys have been conducted by well-trained interviewers using structured interviews (e.g., Diagnostic Interview Schedule, DIS; Composite International Diagnostic Interview, CIDI) to generate well-standardized diagnostic classifications (e.g., DSM-3 and -4) [29‒31, 34, 35]. Thus, it is unlikely that an increase in false positives has masked a treatment-driven drop in “true” prevalence.

Another obvious explanation is that a rise in first incidence has offset the expected treatment-driven decrease in prevalence of mood and anxiety disorders. First incidence refers to the percentage of individuals in the general population that meet the diagnostic criteria for a particular disorder for the first time in their life during a particular period, usually a year (annual first-incidence rate); lifetime prevalence refers to the percentage of individuals in the general population that meet diagnostic criteria for a particular disorder at least once during their lifetime and thus equals first incidence during lifetime. Table 1 presents incidence rates of mood and anxiety disorders as observed in the few post-1980 first-incidence studies of epidemiological samples that meet the following criteria: N ≥ 1,000, operationally defined diagnostic classification, standardized psychiatric interview administered by well-trained interviewers, and follow-up periods of ≤3 years. If the first incidence has increased since the 1980s, the annual rates should show a consistently increasing trend over the years. The annual incidence rates from the periods 1981–1982, 1997–1999, 2004–2006, and 2008–2011 do not suggest a consistent increase. The incidence rates of major depression, generalized anxiety disorder, and panic disorder show a temporary increase in the late 1990s whereas the incidence rate of social anxiety disorder has decreased. However, it should be stressed that the evidence on first incidence is scarce, heterogeneous, and ends around the early 2010s [36]. We conclude that it is unlikely that a significant rise in first incidence has offset a treatment-driven prevalence drop, but the data are too limited for any definite conclusion [36].

Table 1.

Annual incidence per 1,000 pyar of post-1980 incidence studies of CMDs meeting the inclusion criteriaa

 Annual incidence per 1,000 pyar of post-1980 incidence studies of CMDs meeting the inclusion criteriaa
 Annual incidence per 1,000 pyar of post-1980 incidence studies of CMDs meeting the inclusion criteriaa

Leading clinical practice guidelines on anxiety and depression indicate that antidepressants and benzodiazepines and/or any of several empirically supported psychological treatments are efficacious. However, if treatment efficacies are more modest than guidelines suggest, it is possible that, even with more people receiving gold standard interventions, any decrease in prevalence would be small and elusive. This could help to explain the treatment-prevalence paradox.

Although meta-analyses and umbrella reviews have serious limitations for clinical practice [37‒39], they are useful to illustrate the impact of methodological weaknesses on efficacy estimates (see Table 2 for important biases). Meta-analyses that adjust for biases show that efficacy is substantially smaller than conventionally believed. Two comprehensive umbrella reviews, published in 2014 and 2022, clearly demonstrate the impact of biases on reported efficacy. The 2014 review [40] reported a medium overall effect size (SMD = 0.50), across psychotherapies and medications. In contrast, the 2022 review [41] found a small overall effect size of 0.34 for psychotherapies and 0.36 for medications. The 2022 review included only RCTs that had used placebo or care-as-usual as comparison group, formally assessed study quality, and included meta-analyses published since 2014. Individual meta-analyses that adjust for risk of bias report substantial drops in efficacy [42, 43].

Table 2.

Bias in RCTs and their meta-analyses

 Bias in RCTs and their meta-analyses
 Bias in RCTs and their meta-analyses

What do such modest efficacies mean for the treatment-prevalence paradox? Here, we must realize, first, that what matters from the population perspective is efficacy relative to no treatment and not relative to placebo or care-as-usual. Both control conditions likely have slightly better outcomes than no treatment but how much better is unknown because no-treatment control groups are rare [44]. The second caveat is that adjustment has typically been limited to publication bias and exclusion of trials that do not report intention-to-treat analysis or include wait list control groups. Efficacies could even be smaller as the cumulative effect of all biases is unclear [45]. Especially, unblinding remains difficult to quantify validity threat, obviously for psychotherapy trials, but for medication trials as well. Hence, it is possible that even the efficacy relative to no treatment is too small to matter at the population level and if true helps to explain the treatment-prevalence paradox.

Many patients do not maintain their acute-phase treatment response, about a fifth (psychotherapy) to a third (medication) relapse within 1 year [46‒50]. To prevent relapse recurrence, interventions were developed and indeed substantial benefits have been reported for continued medication and preventive psychotherapy relative to controls although the evidence for anxiety disorders is limited. Continuing antidepressant medication halves risk of relapse/recurrence relative to substitution to PLA within the first year [48, 49, 51, 52]. Psychotherapies are significantly better than routine clinical management in reducing relapse/recurrence risk in patients who are at least in partial remission at randomization; interestingly, they seem also slightly more successful than continued medication [53]. Most follow-ups lasted 12–24 months.

However, methodological concerns remain, complicating interpretation, including misclassification of medication withdrawal symptoms, unblinding, heterogeneity of control conditions, and therapeutic allegiance problems. In addition, two other issues are relevant as well. First, patients without response to acute-phase treatment were not eligible for these trials. Second risk of relapse/recurrence, albeit substantially reduced by continued medication or preventive psychotherapy, remains significant [48, 54]. Despite these interpretation problems, if widely and adequately implemented in real-world settings, relapse-recurrence preventive interventions should have some impact at the population level.

The limited RCT-based treatment efficacy may not generalize well to “real-world” practice: the well-recognized distinction between treatment efficacy as established in RCTs (i.e., under optimal conditions) versus treatment effectiveness as realized in routine care (i.e., under typical conditions) [55]. First, the typical patient in routine care may have two additional disadvantages compared to his RCT counterpart: poorer prognosis and less optimal treatment [49]. Indeed, remission rates in routine practice are substantially lower than in meta-analyses for all treatment modalities (32% vs. 40–74%) [56].

In addition, research indicates substantial treatment gaps in the dissemination and implementation of treatment protocols [57‒64]. The WHO World Mental Health surveys reported that the 12-month service use among the 1,238 participants from 10 high-income countries with a severe 12-month CIDI-DSM-IV anxiety, depressive, or substance use disorder ranged from 24% to 61% (mean 55%). Only on average 35% of these service users had received minimally adequate treatment [65]. Other studies report similar observations [66, 67]. Another problem is that some RCT-based treatments are so highly specialized that they are difficult to implement into routine care. Although the consequences of these gaps are not fully clear [68, 69], the conclusion seems inescapable that not only the efficacy of treatment has been overestimated but also its generalizability to routine care settings. Thus, poor generalizability helps to explain the treatment-prevalence paradox.

Even with better treatments being more widely available, its impact on the prevalence is dependent on how optimal they are targeted. Crucial here is the distinction between recurrent-chronic cases and those with one or two lifetime episodes (nonrecurrent cases) since effective treatment of recurrent-chronic cases has much more impact at the population level than effective treatment of nonrecurrent cases, even if the nonrecurrent cases by far outnumber the recurrent-chronic cases [70‒74]. The reason for the larger population-level impact is that recurrent-chronic cases make up the majority in prevalence rates as the total time during their life that they meet diagnostic criteria is much longer than for the nonrecurrent cases because of which they have a much higher probability to be picked up in epidemiological prevalence studies.

The recurrence issue has two, potentially important, implications or scenarios. First, if the RCTs on the efficacy of treatments have largely been obtained on episodes of nonrecurrent-nonchronic cases and not on those of recurrent-chronic cases, efficacy may have been overestimated as by all clinical accounts, effective treatment of recurrent-chronic cases is more difficult [75, 76]. Second, if in routine care relatively efficacious treatments to prevent relapse/recurrence have not been optimally targeted, the impact at the population level will have been small.

It remains unclear to what degree these two scenarios reflect past clinical practice. If frequently and adequately provided, therapeutic advances for preventing relapse/recurrence should have produced a robust treatment-induced prevalence drop. If rarely or nonoptimally provided, it could help explain the treatment-prevalence paradox.

Both medication and psychological treatment of mood and anxiety disorders can have adverse effects [77]. How frequently these adverse effects occur and outbalance the benefits of treatment is less clear. In particular, medication has been associated with a variety of adverse effects: paradoxical effects, manifestations of tolerance (loss of clinical effect, refractoriness), withdrawal symptoms and disorders [78‒81]. Significant adverse effects of psychological treatments have been noted as well [82, 83].

Two important counterproductive consequences have been proposed: reduction of self-help activities and loss of agency coping [84] and behavioral toxicity including oppositional perturbation and symptom return [77, 78, 80, 81]. They merit consideration as possible contributors to the treatment-prevalence paradox.

Reduction of self-help activities and loss of agency: medication treatment without behavioral management and psychoeducation (mono-medication) has the risk of being counterproductive if it reduces self-help activity and active coping [84]. The same might apply to low-fidelity-to-guideline psychotherapy [80]. The argument is that depressed and anxious people often engage in helpful strategies subsumed in self-help programs and psychological treatments, such as exercising, increasing pleasant activities, reducing stressful situations, and meditating, which tend to improve their “agency,” “self-efficacy” for coping with underlying problems [32], and perhaps even their neural plasticity [85]. Mono-medication and low-fidelity-to-guideline psychotherapy have the risk to reduce these helpful strategies.

Behavioral “toxicity” including oppositional perturbation: behavioral toxicity refers to the “pharmacological actions of a drug that, within the dose range in which it has been found to possess clinical utility, may produce alterations in mood, perceptual, cognitive and psychomotor functions, that limit the capacity of the individual or constitute a hazard to his/her well-being” ([77], p.130). An important form of behavioral toxicity is “oppositional perturbation” that seeks to account for unintended and unwanted effects of medication on illness course, including symptom return after discontinuation, and a progressive loss of effectiveness (tachyphylaxis) across repeated anti-depressant medication trials [78‒81]. Importantly, direct evidence for oppositional perturbation is lacking, but intriguing indirect evidence is available [78, 79].

RCTs have not actively searched for adverse consequences, perhaps because it was not in the interest of the funding bodies or researchers. Medication monotherapy and low-fidelity-to-guideline psychotherapy are probably uncommon in RCTs, where treatment protocols are specified and carefully monitored, unlike treatment in real-world settings. In addition, no-treatment arms are considered unethical and medication-withdrawal studies may have missed the bigger picture of improved ultimate outcomes, due to misinterpreted withdrawal symptoms and too short follow-ups [79, 86]. In conclusion, although hard data are lacking, counterproductive effects could significantly help to explain the treatment-prevalence paradox, but solid evidence is lacking.

Since the early 1980s, mental health care expenditures for mood and anxiety disorders have increased substantially in the Western world, especially treatment with medications, typically serotonin reuptake inhibitors. However, reductions in the prevalence of mood and anxiety disorders have not accompanied this expansion, the treatment-prevalence paradox. Our analysis suggests that it is unlikely that substantial increases of false positives or first incidence have offset a true treatment-driven reduction in prevalence. Instead, it seems likely that the treatment-prevalence paradox is, at least in part, due to overrated efficacy of treatment and major quality gaps in routine care settings. In addition, it is possible that nonoptimal targeting of treatment (too little on recurrent and chronic cases) and counterproductive effects of treatment account for part of the paradox, but convincing evidence is lacking. Compared to short-term outcome, much less is known about long-term outcome and outcome in terms of quality of life and socio-economic functioning. Thus, more research on long-term outcome, optimal treatment targeting, and counterproductive treatment effects is crucial. The overoptimistic view of treatment efficacy in clinical guidelines is not only due to significant methodological weakness in RCTs and meta-analyses but to publication, outcome reporting, spin, and citing bias as well [45]. In addition, co-morbidity has hardly been addressed in treatment studies. There is a clear need of treatment studies taking into account the co-morbidity of the patients involved, not only of co-morbid anxiety and mood disorders but of substance abuse as well [87].

To reduce mood and anxiety disorders prevalence not only more efficacious, better implemented and targeted treatments are needed but also prevention given the limited population-level impact of treatment and the substantial continuity of psychopathology across childhood, adolescence, and adulthood [88‒91]. If prevention could interrupt this continuity and turn around maladaptive pathways, prevalence would drop substantially. In order to be successful, various authors have argued that effective prevention will have to be structural, well-funded, long-term, socially embedded, starting at an early age, addressing both parenting, kids, and schools, and combining universal (health promotion) and indicated/selective prevention [15, 92‒94]. In short, we need a paradigm shift in both treatment, prevention, and their evaluation to reduce mental disorder prevalences [15, 93].

All authors report no financial interests or potential conflicts of interest.

This paper was supported by a subgrant from the Netherlands Organization for Scientific Research to the first author (Mother Grant NWO-Gravitation 024.001.003).

Ormel conceived and wrote the first draft of the manuscript and the revision. Emmelkamp added relevant data on anxiety disorders and improved the revision.

1.
Vigo
D
,
Thornicroft
G
,
Atun
R
.
Estimating the true global burden of mental illness
.
Lancet Psychiatry
.
2016 FEB
;
3
(
2
):
171
8
.
2.
Baxter
AJ
,
Scott
KM
,
Ferrari
AJ
,
Norman
RE
,
Vos
T
,
Whiteford
HA
.
Challenging the myth of an “epidemic” of common mental disorders: trends in the global prevalence of anxiety and depression between 1990 and 2010
.
Depress Anxiety
.
2014 Jun 2014
;
31
(
6
):
506
16
.
3.
Steel
Z
,
Marnane
C
,
Iranpour
C
,
Chey
T
,
Jackson
JW
,
Patel
V
.
The global prevalence of common mental disorders: a systematic review and meta-analysis 1980–2013
.
Int J Epidemiol
.
2014 Apr
;
43
(
2
):
476
93
.
4.
Richter
D
,
Wall
A
,
Bruen
A
,
Whittington
R
.
Is the global prevalence rate of adult mental illness increasing? Systematic review and meta-analysis
.
Acta Psychiatr Scand
.
2019
;
140
(
5
):
393
407
.
5.
Ferrari
AJ
,
Somerville
AJ
,
Baxter
AJ
,
Norman
R
,
Patten
SB
,
Vos
T
,
.
Global variation in the prevalence and incidence of major depressive disorder: a systematic review of the epidemiological literature
.
Psychol Med
.
2013 Mar
;
43
(
3
):
471
81
.
6.
GBD 2016 Disease and Injury Incidence and Prevalence Collaborators
.
Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016
.
Lancet
.
2017 Sep 16
;
390
(
10100
):
1211
59
.
7.
Bretschneider
J
,
Janitza
S
,
Jacobi
F
,
Thom
J
,
Hapke
U
,
Kurth
T
,
.
Time trends in depression prevalence and health-related correlates: results from population-based surveys in Germany 1997–1999 vs. 2009–2012
.
BMC Psychiatry
.
2018 Dec 20
;
18
(
1
):
394
.
8.
Kessler
RC
,
Demler
O
,
Frank
RG
,
Olfson
M
,
Pincus
HA
,
Walters
EE
,
.
Prevalence and treatment of mental disorders, 1990 to 2003
.
N Engl J Med
.
2005 Jun 16
;
352
(
24
):
2515
23
.
9.
Jorm
AF
,
Patten
SB
,
Brugha
TS
,
Mojtabai
R
.
Has increased provision of treatment reduced the prevalence of common mental disorders? Review of the evidence from four countries
.
World Psychiatry
.
2017 Feb
;
16
(
1
):
90
9
.
10.
Olfson
M
,
Kroenke
K
,
Wang
S
,
Blanco
C
.
Trends in office-based mental health care provided by psychiatrists and primary care physicians
.
J Clin Psychiatry
.
2014 Mar 2014
;
75
(
3
):
247
53
.
11.
Mark
TL
,
Levit
KR
,
Vandivort-Warren
R
,
Buck
JA
,
Coffey
RM
.
Changes in US spending on mental health and substance abuse treatment, 1986–2005, and implications for policy
.
Health Aff
.
2011 Feb
;
30
(
2
):
284
92
.
12.
Niaounakis
TK
.
Productiviteitstrends in de geestelijke gezondheidszorg: een empirisch onderzoek naar het effect van regulering op de productiviteitsontwikkeling tussen 1982 en 2010
;
2013
.
13.
Marcus
SC
,
Olfson
M
.
National trends in the treatment for depression from 1998 to 2007
.
Arch Gen Psychiatry
.
2010 Dec
;
67
(
12
):
1265
73
.
14.
Saxena
S
,
Maulik
PK
.
Mental health services in low- and middle-income countries: an overview
.
Curr Opin Psychiatry
.
2003 Jul
;
16
(
4
):
437
42
.
15.
Ormel
J
,
Cuijpers
P
,
Jorm
A
,
Schoevers
RA
.
What is needed to eradicate the depression epidemic, and why
.
Ment Health Prev
.
2020
;
17
:
200177
. Epub ahead of print. https://doi.org/10.1016/j.mhp.2019.200177.
16.
Rait
G
,
Walters
K
,
Griffin
M
,
Buszewicz
M
,
Petersen
I
,
Nazareth
I
.
Recent trends in the incidence of recorded depression in primary care
.
Br J Psychiatry
.
2009 Dec
;
195
(
6
):
520
4
.
17.
John
A
,
Marchant
AL
,
McGregor
JI
,
Tan
JOA
,
Hutchings
HA
,
Kovess
V
,
.
Recent trends in the incidence of anxiety and prescription of anxiolytics and hypnotics in children and young people: an e-cohort study
.
J Affect Disord
.
2015 Sep 1
;
183
:
134
41
.
18.
Walters
K
,
Rait
G
,
Griffin
M
,
Buszewicz
M
,
Nazareth
I
.
Recent trends in the incidence of anxiety diagnoses and symptoms in primary care
.
PLoS One
.
2012 Aug 3
;
7
(
8
):
e41670
.
19.
Filatova
S
,
Upadhyaya
S
,
Kronstrom
K
,
Suominen
A
,
Chudal
R
,
Luntamo
T
,
.
Time trends in the incidence of diagnosed depression among people aged 5–25 years living in Finland 1995–2012
.
Nord J Psychiatry
.
2019 Nov 17
;
73
(
8
):
475
81
.
20.
Steffen
A
,
Thom
J
,
Jacobi
F
,
Holstiege
J
,
Bätzing
J
.
Trends in prevalence of depression in Germany between 2009 and 2017 based on nationwide ambulatory claims data
.
J Affect Disord
.
2020 Jun 15
;
271
:
239
47
.
21.
De Graaf
R
,
Ten Have
M
,
Van Gool
C
,
Van Dorsselaer
S
.
Prevalence of mental disorders, and trends from 1996 to 2009. Results from NEMESIS-2
.
Tijdschr Psychiatr
.
2012
;
54
(
1
):
27
38
.
22.
Donohue
JM
,
Cevasco
M
,
Rosenthal
MB
.
A decade of direct-to-consumer advertising of prescription drugs
.
N Engl J Med
.
2007
;
357
(
7
):
673
81
.
23.
Mann
D
,
Reynolds
K
,
Smith
D
,
Muntner
P
.
Trends in statin use and low-density lipoprotein cholesterol levels among US adults: impact of the 2001 National Cholesterol Education Program guidelines
.
Ann Pharmacother
.
2008 Sep
;
42
(
9
):
1208
15
.
24.
Gu
Q
,
Burt
VL
,
Dillon
CF
,
Yoon
S
.
Trends in antihypertensive medication use and blood pressure control among United States adults with hypertension the national health and nutrition examination survey, 2001 to 2010
.
Circulation
.
2012 Oct 23
;
126
(
17
):
2105
14
.
25.
Baigent
C
,
Keech
A
,
Kearney
P
,
Collins
R
,
Simes
J
.
Efficacy and safety of cholesterol-lowering treatment–Authors’ reply
.
Lancet
.
2006
;
367
(
9509
):
470
1
.
26.
Schomerus
G
,
Schwahn
C
,
Holzinger
A
,
Corrigan
PW
,
Grabe
HJ
,
Carta
MG
,
.
Evolution of public attitudes about mental illness: a systematic review and meta-analysis
.
Acta Psychiatr Scand
.
2012
;
125
(
6
):
440
52
.
27.
Reavley
NJ
,
Jorm
AF
.
Willingness to disclose a mental disorder and knowledge of disorders in others: changes in Australia over 16 years
.
Aust N Z J Psychiatry
.
2014 Feb
;
48
(
2
):
162
8
.
28.
Moncrieff
J
.
Against the stream: antidepressants are not antidepressants - an alternative approach to drug action and implications for the use of antidepressants
.
BJPsych Bull
.
2018 Feb
;
42
(
1
):
42
4
.
29.
Andrews
G
,
Peters
L
.
The psychometric properties of the composite international diagnostic interview
.
Soc Psychiatry Psychiatr Epidemiol
.
1998
;
33
(
2
):
80
8
.
30.
Brugha
TS
,
Jenkins
R
,
Taub
N
,
Meltzer
H
,
Bebbington
PE
.
A general population comparison of the Composite International Diagnostic Interview [CIDI] and the Schedules for Clinical Assessment in Neuropsychiatry [SCAN]
.
Psychol Med
.
2001
;
31
(
6
):
1001
13
.
31.
Wittchen
HU
,
Kessler
RC
,
Zhao
S
,
Abelson
JL
.
Reliability and clinical validity of UM-CIDI DSM-III-R generalized anxiety disorder
.
J Psychiatr Res
.
1995
;
29
(
2
):
95
110
.
32.
Haslam
N
.
Concept creep: psychology’s expanding concepts of harm and pathology
.
Psychol Inq
.
2016 Jan 2
;
27
(
1
):
1
17
.
33.
Ormel
J
,
Hollon
SD
,
Kessler
RC
,
Cuijpers
P
,
Monroe
SM
.
More treatment but no less depression: the treatment-prevalence paradox
.
Clin Psychol Rev
.
2022
;
91
:
102111
.
34.
Haro
JM
,
Arbabzadeh-Bouchez
S
,
Brugha
TS
,
de Girolamo
G
,
Guyer
ME
,
Jin
R
,
.
Concordance of the Composite International Diagnostic Interview Version 3.0 [CIDI 3.0] with standardized clinical assessments in the WHO World Mental Health surveys
.
Int J Methods Psychiatr Res
.
2006 12
;
15
(
4
):
167
80
.
35.
Kessler
RC
,
Avenevoli
S
,
Green
J
,
Gruber
MJ
,
Guyer
M
,
He
Y
,
.
National Comorbidity Survey replication Adolescent supplement [NCS-A]: III. Concordance of DSM-IV/CIDI diagnoses with clinical reassessments
.
J Am Acad Child Adolesc Psychiatry
.
2009 Apr
;
48
(
4
):
386
99
.
36.
Somers
JM
,
Goldner
EM
,
Waraich
P
,
Hsu
L
.
Prevalence and incidence studies of anxiety disorders: a systematic review of the literature
.
Can J Psychiatry
.
2006 Feb
;
51
(
2
):
100
13
.
37.
Concato
J
,
Horwitz
RI
.
Limited usefulness of meta-analysis for informing patient care
.
Psychother Psychosom
.
2019
;
88
(
5
):
257
62
.
38.
Cosci
F
,
Fava
GA
.
When anxiety and depression coexist: the role of differential diagnosis using clinimetric criteria
.
Psychother Psychosom
.
2021
;
90
(
5
):
308
17
.
39.
Balon
R
.
What is a review article and what are its purpose, attributes, and goal [s]
.
Psychother Psychosom
.
2022
;
91
(
3
):
152
5
.
40.
Huhn
M
,
Tardy
M
,
Spineli
LM
,
Kissling
W
,
Förstl
H
,
Pitschel-Walz
G
,
.
Efficacy of pharmacotherapy and psychotherapy for adult psychiatric disorders: a systematic overview of meta-analyses
.
JAMA psychiatry
.
2014
;
71
(
6
):
706
15
.
41.
Leichsenring
F
,
Steinert
C
,
Rabung
S
,
Ioannidis
JPA
.
The efficacy of psychotherapies and pharmacotherapies for mental disorders in adults: an umbrella review and meta-analytic evaluation of recent meta-analyses
.
World Psychiatry
.
2022
;
21
(
1
):
133
45
.
42.
Cuijpers
P
,
Karyotaki
E
,
Reijnders
M
,
Ebert
DD
.
Was Eysenck right after all? A reassessment of the effects of psychotherapy for adult depression
.
Epidemiol Psychiatr Sci
.
2019 Feb
;
28
(
1
):
21
30
.
43.
Carpenter
JK
,
Andrews
LA
,
Witcraft
SM
,
Powers
MB
,
Smits
JAJ
,
Hofmann
SG
.
Cognitive behavioral therapy for anxiety and related disorders: a meta-analysis of randomized placebo-controlled trials
.
Depress Anxiety
.
2018
;
35
(
6
):
502
14
.
44.
Ormel
J
,
Ruhe
HG
,
Bockting
CLH
,
Nolen
W
,
Schene
AH
,
Spijker
J
,
.
Antidepressants are frequently prescribed but still critized; a perspective on causes and solutions
.
Tijdschr Psychiatr
.
2020
;
62
(
3
):
213
22
.
45.
de Vries
YA
,
Roest
AM
,
de Jonge
P
,
Cuijpers
P
,
Munafò
MR
,
Bastiaansen
JA
.
The cumulative effect of reporting and citation biases on the apparent efficacy of treatments: the case of depression
.
Psychol Med
.
2018
;
48
(
15
):
2453
5
.
46.
Bockting
CL
,
Hollon
SD
,
Jarrett
RB
,
Kuyken
W
,
Dobson
K
.
A lifetime approach to major depressive disorder: the contributions of psychological interventions in preventing relapse and recurrence
.
Clin Psychol Rev
.
2015 Nov
;
41
:
16
26
.
47.
Vittengl
JR
,
Clark
LA
,
Dunn
TW
,
Jarrett
RB
.
Reducing relapse and recurrence in unipolar depression: a comparative meta-analysis of cognitive-behavioral therapy’s effects
.
J Consult Clin Psychol
.
2007 Jun
;
75
(
3
):
475
88
.
48.
Sim
K
,
Lau
WK
,
Sim
J
,
Sum
MY
,
Baldessarini
RJ
.
Prevention of relapse and recurrence in adults with major depressive disorder: systematic review and meta-analyses of controlled trials
.
Int J Neuropsychopharmacol
.
2016 Feb
;
19
(
2
):
pyv076
.
49.
Batelaan
NM
,
Bosman
RC
,
Muntingh
A
,
Scholten
WD
,
Huijbregts
KM
,
van Balkom
AJLM
.
Risk of relapse after antidepressant discontinuation in anxiety disorders, obsessive-compulsive disorder, and post-traumatic stress disorder: systematic review and meta-analysis of relapse prevention trials
.
Bmj-british Med J
.
2017 Sep 13
;
358
:
j3927
.
50.
Levy
HC
,
O’Bryan
EM
,
Tolin
DF
.
A meta-analysis of relapse rates in cognitive-behavioral therapy for anxiety disorders
.
J Anxiety Disord
.
2021
;
81
:
102407
.
51.
Zimmerman
M
,
Posternak
MA
,
Ruggero
CJ
.
Impact of study design on the results of continuation studies of antidepressants
.
J Clin Psychopharmacol
.
2007 Apr
;
27
(
2
):
177
81
.
52.
Donovan
MR
,
Glue
P
,
Kolluri
S
,
Emir
B
.
Comparative efficacy of antidepressants in preventing relapse in anxiety disorders: a meta-analysis
.
J Affect Disord
.
2010 Jun
;
123
(
1–3
):
9
16
.
53.
Biesheuvel-Leliefeld
KEM
,
Kok
GD
,
Bockting
CLH
,
Cuijpers
P
,
Hollon
SD
,
van Marwijk
HW
,
.
Effectiveness of psychological interventions in preventing recurrence of depressive disorder: meta-analysis and meta-regression
.
J Affect Disord
.
2015 Mar 15
;
174
:
400
10
.
54.
Kuyken
W
,
Warren
FC
,
Taylor
RS
,
Whalley
B
,
Crane
C
,
Bondolfi
G
,
.
Efficacy of mindfulness-based cognitive therapy in prevention of depressive relapse an individual patient data meta-analysis from randomized trials
.
Jama Psychiatry
.
2016 Jun
;
73
(
6
):
565
74
.
55.
Streiner
DL
.
The 2 “Es” of research: efficacy and effectiveness trials
.
Can J Psychiatry
.
2002 Aug
;
47
(
6
):
552
6
.
56.
van der Lem
R
,
van der Wee
NJA
,
van Veen
T
,
Zitman
FG
.
Efficacy versus effectiveness: a direct comparison of the outcome of treatment for mild to moderate depression in randomized controlled trials and daily practice
.
Psychother Psychosom
.
2012
;
81
(
4
):
226
34
.
57.
Boerema
AM
,
ten Have
M
,
Kleiboer
A
,
de Graaf
R
,
Nuyen
J
,
Cuijpers
P
,
.
Demographic and need factors of early, delayed and no mental health care use in major depression: a prospective study
.
BMC Psychiatry
.
2017 Nov 16
;
17
(
1
):
367
.
58.
Demyttenaere
K
,
Bruffaerts
R
,
Posada-Villa
J
,
Gasquet
I
,
Kovess
V
,
Lepine
JP
,
.
Prevalence, severity, and unmet need for treatment of mental disorders in the World Health Organization World Mental Health Surveys
.
JAMA
.
2004
;
291
(
21
):
2581
90
.
59.
Fullerton
CA
,
Busch
AB
,
Normand
SLT
,
McGuire
TG
,
Epstein
AM
.
Ten-year trends in quality of care and spending for depression 1996 through 2005
.
Arch Gen Psychiatry
.
2011
;
68
(
12
):
1218
26
.
60.
Harris
MG
,
Hobbs
MJ
,
Burgess
PM
,
Pirkis
JE
,
Diminic
S
,
Siskind
DJ
,
.
Frequency and quality of mental health treatment for affective and anxiety disorders among Australian adults
.
Med J Aust
.
2015 Mar 2
;
202
(
4
):
185
9
.
61.
Spiers
N
,
Qassem
T
,
Bebbington
P
,
McManus
S
,
King
M
,
Jenkins
R
,
.
Prevalence and treatment of common mental disorders in the English national population, 1993–2007
.
Br J Psychiatry
.
2016 Aug
;
209
(
2
):
150
6
.
62.
Young
AS
,
Klap
R
,
Shoai
R
,
Wells
KB
.
Persistent depression and anxiety in the United States: prevalence and quality of care
.
Psychiatr Serv
.
2008 Dec
;
59
(
12
):
1391
8
.
63.
Wang
PS
,
Aguilar-Gaxiola
S
,
Alonso
J
,
Angermeyer
MC
,
Borges
G
,
Bromet
EJ
,
.
Use of mental health services for anxiety, mood, and substance disorders in 17 countries in the WHO world mental health surveys
.
Lancet
.
2007 Sep 8
;
370
(
9590
):
841
50
.
64.
Baldwin
DS
,
Anderson
IM
,
Nutt
DJ
,
Allgulander
C
,
Bandelow
B
,
den Boer
JA
,
.
Evidence-based pharmacological treatment of anxiety disorders, post-traumatic stress disorder and obsessive-compulsive disorder: a revision of the 2005 guidelines from the British Association for Psychopharmacology
.
J Psychopharmacol
.
2014 May
;
28
(
5
):
403
39
.
65.
Wang
PS
,
Gruber
MJ
,
Powers
RE
,
Schoenbaum
M
,
Speier
AH
,
Wells
KB
,
.
Mental health service use among hurricane Katrina survivors in the eight months after the disaster
.
Psychiatr Serv
.
2007 Nov
;
58
(
11
):
1403
11
.
66.
Alonso
J
,
Lepine
JP
;
ESEMeD/MHEDEA 2000 Scientific committee
.
Overview of key data from the European Study of the Epidemiology of Mental Disorders [ESEMeD]
.
J Clin Psychiatry
.
2007
;
68
(
Suppl 2
):
3
9
.
67.
Smolders
M
,
Laurant
M
,
Verhaak
P
,
Prins
M
,
van Marwijk
H
,
Penninx
B
,
.
Adherence to evidence-based guidelines for depression and anxiety disorders is associated with recording of the diagnosis
.
Gen Hosp Psychiatry
.
2009
;
31
(
5
):
460
9
.
68.
Trivedi
MH
,
Rush
AJ
,
Crismon
ML
,
Kashner
TM
,
Toprac
MG
,
Carmody
TJ
,
.
Clinical results for patients with major depressive disorder in the Texas medication algorithm project
.
Arch Gen Psychiatry
.
2004
;
61
(
7
):
669
80
.
69.
van Dijk
MK
,
Oosterbaan
DB
,
Verbraak
MJPM
,
van Balkom
AJLM
.
The effectiveness of adhering to clinical-practice guidelines for anxiety disorders in secondary mental health care: the results of a cohort study in The Netherlands
.
J Eval Clin Pract
.
2013 Oct
;
19
(
5
):
791
7
.
70.
Monroe
SM
,
Harkness
KL
.
Recurrence in major depression: a conceptual analysis
.
Psychol Rev
.
2011 10
;
118
(
4
):
655
74
.
71.
Monroe
SM
,
Anderson
SF
,
Harkness
KL
.
Life stress and major depression: the mysteries of recurrences
.
Psychol Rev
.
2019
;
126
(
6
):
791
816
.
72.
Rottenberg
J
,
Devendorf
AR
,
Kashdan
TB
,
Disabato
DJ
.
The curious neglect of high functioning after psychopathology: the case of depression
.
Perspect Psychol Sci
.
2018 Sep
;
13
(
5
):
549
66
.
73.
Ormel
J
,
Oldehinkel
T
,
Brilman
EI
,
van den Brink
W
.
Outcome of depression and anxiety in primary care: a three-wave 3 ½-year study of pschopathology and disability
.
Arch Gen Psychiatry
.
1993
;
50
(
10
):
759
66
.
74.
Eaton
WW
,
Shao
H
,
Nestadt
G
,
Lee
HB
,
Bienvenu
OJ
,
Zandi
P
.
Population-based study of first onset and chronicity in major depressive disorder
.
Arch Gen Psychiatry
.
2008 May
;
65
(
5
):
513
20
.
75.
Lee
AS
.
Better outcomes for depressive disorders
.
Psychol Med
.
2003
;
33
(
5
):
769
74
.
76.
Burcusa
SL
,
Iacono
WG
.
Risk for recurrence in depression
.
Clin Psychol Rev
.
2007
;
27
(
8
):
959
85
.
77.
Fava
GA
,
Rafanelli
C
.
Iatrogenic factors in psychopathology
.
Psychother Psychosom
.
2019
;
88
(
3
):
129
40
.
78.
Andrews
PW
,
Kornstein
SG
,
Halberstadt
LJ
,
Gardner
CO
,
Neale
MC
.
Blue again: perturbational effects of antidepressants suggest monoaminergic homeostasis in major depression
.
Front Psychol
.
2011
;
2
:
159
.
79.
Fava
GA
,
Offidani
E
.
The mechanisms of tolerance in antidepressant action
.
Prog Neuropsychopharmacol Biol Psychiatry
.
2011 Aug
;
35
(
7
):
1593
602
.
80.
Ormel
J
,
Bosker
FJ
,
Hollon
SD
,
Ruhe
HG
.
Can loss of agency and oppositional perturbation associated with antidepressant monotherapy and low-fidelity psychological treatment dilute the benefits of guideline-consistent depression treatment at the population level
.
Eur Psychiatry
.
2020
;
63
(
1
):
e89
.
81.
Amsterdam
JD
,
Lorenzo-Luaces
L
,
DeRubeis
RJ
.
Step-wise loss of antidepressant effectiveness with repeated antidepressant trials in bipolar II depression
.
Bipolar Disord
.
2016 Nov
;
18
(
7
):
563
70
.
82.
Linden
M
.
How to define, find and classify side effects in psychotherapy: from unwanted events to adverse treatment reactions
.
Clin Psychol Psychother
.
2013
;
20
(
4
):
286
96
.
83.
Parry
GD
,
Crawford
MJ
,
Duggan
C
.
Iatrogenic harm from psychological therapies–time to move on
.
Br J Psychiatry
.
2016
;
208
(
3
):
210
2
.
84.
Meadows
GN
,
Prodan
A
,
Patten
S
,
Shawyer
F
,
Francis
S
,
Enticott
J
,
.
Resolving the paradox of increased mental health expenditure and stable prevalence
.
Aust N Z J Psychiatry
.
2019
;
53
(
9
):
844
50
.
85.
Maya Vetencourt
JF
,
Sale
A
,
Viegi
A
,
Baroncelli
L
,
De Pasquale
R
,
O'Leary
OF
.
The antidepressant fluoxetine restores plasticity in the adult visual cortex
.
Science
.
2008
;
320
(
5874
):
385
8
.
86.
Fava
GA
,
Gatti
A
,
Belaise
C
,
Guidi
J
,
Offidani
E
.
Withdrawal symptoms after selective serotonin reuptake inhibitor discontinuation: a systematic review
.
Psychother Psychosom
.
2015
;
84
(
2
):
72
81
.
87.
Crowe
M
,
Inder
M
,
Thwaites
B
.
The experience of mood disorder and substance use: an integrative review
.
Psychiatr Ment Health Nurs
.
2022
. https://doi.org/10.1111/jpm.12876.
88.
Asselmann
E
,
Wittchen
HU
,
Lieb
R
,
Höfler
M
,
Beesdo-Baum
K
.
Does help-seeking alter the risk for incident psychopathology in adolescents and young adults with and without fearful spells or panic attacks? Findings from a 10-year prospective-longitudinal community study
.
J Affect Disord
.
2014 Dec 1
;
169
:
221
7
.
89.
Caspi
A
,
Houts
RM
,
Ambler
A
,
Danese
A
,
Elliott
ML
,
Hariri
A
,
.
Longitudinal assessment of mental health disorders and comorbidities across 4 decades among participants in the Dunedin Birth Cohort Study
.
JAMA Netw Open
.
2020 Apr 21
;
3
:
e203221
.
90.
Carrellas
NW
,
Biederman
J
,
Uchida
M
.
How prevalent and morbid are subthreshold manifestations of major depression in adolescents? A literature review
.
J Affect Disord
.
2017 Mar 1
;
210
:
166
73
.
91.
Copeland
WE
,
Adair
CE
,
Smetanin
P
,
Stiff
D
,
Briante
C
,
Colman
I
,
.
Diagnostic transitions from childhood to adolescence to early adulthood
.
J Child Psychol Psychiatry
.
2013 Jul
;
54
(
7
):
791
9
.
92.
Jacka
FN
,
Reavley
NJ
,
Jorm
AF
,
Toumbourou
JW
,
Lewis
AJ
,
Berk
M
.
Prevention of common mental disorders: what can we learn from those who have gone before and where do we go next
.
Aust N Z J Psychiatry
.
2013 Oct
;
47
(
10
):
920
9
.
93.
National Academies of Sciences
.
Engineering, and medicine. Fostering healthy mental, emotional, and behavioral development in children and youth
:
A National Agenda
;
2019
.
94.
Ormel
J
,
VonKorff
M
.
Debate: giving prevention a chance to prove its worth in lowering common mental disorder prevalence: how long will it take
.
Child Adolesc Ment Health
.
2021 Feb
;
26
(
1
):
86
8
.