Abstract
Depression is widely acknowledged to be a heterogeneous entity, and the need to further characterize the individual patient who has received this diagnosis in order to personalize the management plan has been repeatedly emphasized. However, the research evidence that should guide this personalization is at present fragmentary, and the selection of treatment is usually based on the clinician's and/or the patient's preference and on safety issues, in a trial‐and‐error fashion, paying little attention to the particular features of the specific case. This may be one of the reasons why the majority of patients with a diagnosis of depression do not achieve remission with the first treatment they receive. The predominant pessimism about the actual feasibility of the personalization of treatment of depression in routine clinical practice has recently been tempered by some secondary analyses of databases from clinical trials, using approaches such as individual patient data meta‐analysis and machine learning, which indicate that some variables may indeed contribute to the identification of patients who are likely to respond differently to various antidepressant drugs or to antidepressant medication vs. specific psychotherapies. The need to develop decision support tools guiding the personalization of treatment of depression has been recently reaffirmed, and the point made that these tools should be developed through large observational studies using a comprehensive battery of self‐report and clinical measures. The present paper aims to describe systematically the salient domains that should be considered in this effort to personalize depression treatment. For each domain, the available research evidence is summarized, and the relevant assessment instruments are reviewed, with special attention to their suitability for use in routine clinical practice, also in view of their possible inclusion in the above‐mentioned comprehensive battery of measures. The main unmet needs that research should address in this area are emphasized. Where the available evidence allows providing the clinician with specific advice that can already be used today to make the management of depression more personalized, this advice is highlighted. Indeed, some sections of the paper, such as those on neurocognition and on physical comorbidities, indicate that the modern management of depression is becoming increasingly complex, with several components other than simply the choice of an antidepressant and/or a psychotherapy, some of which can already be reliably personalized.
Keywords: Depression, personalization of treatment, symptom profile, clinical subtypes, severity, neurocognition, functioning, quality of life, clinical staging, personality traits, psychiatric antecedents, psychiatric comorbidities, physical comorbidities, family history, early environmental exposures, recent environmental exposures, protective factors, dysfunctional cognitive schemas
Depression is the syndrome most frequently diagnosed in psychiatric practice. There is a wide acknowledgement that this syndrome is not a homogeneous entity, and that a further clinical characterization of the individual patient would be needed in order to personalize the management plan1, 2. However, it is common practice to base the choice of treatment in each case solely on the syndromal diagnosis. Clinical trials have found a variety of medications and psychotherapies to be “equivalent” in the treatment of the syndrome, and these interventions are therefore commonly perceived as interchangeable.
The choice of treatment for depression is at present usually based on the clinician's and/or the patient's preference and on safety issues, in a trial‐and‐error fashion, paying little attention to the individual features of the specific case. This may be one of the reasons why the majority of patients with a diagnosis of depression do not achieve remission after the first treatment they receive 3 , and at least 30% do not respond to two consecutive evidence‐based treatments and may be classified as treatment‐resistant 4 .
Treatment guidelines do not help in this respect. They tend to emphasize the severity of the depressive episode as the main or only element on which to base the choice of treatment5, 6, but this emphasis is undermined in clinical practice by the lack of a reliable and widely accepted way to evaluate that severity. In fact, the definitions of the various degrees of severity of a depressive episode provided by the DSM‐5 7 and ICD‐11 8 (arguably, somewhat generic, without clear anchor points, not evidence based, and with poor interrater reliability) are often ignored by clinicians. Furthermore, the most recent research evidence does not seem to support the idea that response to antidepressant medications or psychotherapies depends upon the severity of the depressive syndrome9, 10.
A variety of clinical and biological predictors of response or non‐response to antidepressant medication in general, or to specific antidepressants or psychotherapies, have been proposed over the decades, but the relevant evidence is fragmentary and sometimes inconsistent. So, the personalization of treatment of depression is on the one hand commonly considered essential, but on the other often perceived as unfeasible in current clinical practice.
This pessimism has recently been tempered by some secondary analyses of databases from clinical trials, using approaches such as individual patient data meta‐analysis and machine learning, which indicate that there may indeed be different symptom profiles associated with the response to different antidepressant drugs, and to antidepressant medications as opposed to specific psychotherapies11, 12. Studies using machine learning are also suggesting that other, non‐symptom variables may contribute to the identification of patients who are likely to respond to a given antidepressant drug13, 14 . The need to develop decision support tools guiding the personalization of depression management has been emphasized 15 , and the point made that these tools should be developed through large observational studies using a comprehensive battery of inexpensive self‐report and clinical measures.
The present paper aims to describe systematically the salient domains that should be considered in this effort to personalize the treatment of depression (Table 1). For each of these domains, the available research evidence is briefly reviewed, and the relevant assessment instruments are considered, with special attention to their suitability for use in routine clinical practice, also in view of their possible inclusion in the above‐mentioned comprehensive battery of measures. The main unmet needs that research should address in this area are emphasized. Where the available evidence allows providing the clinician with specific advice that can already be used today to make the management plan for an individual patient with depression more personalized, this advice is highlighted.
Table 1.
Salient domains to be considered in the clinical characterization of a patient with a diagnosis of depression
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We acknowledge that a significant effort is ongoing to identify biological markers that may help in the selection of treatment for depression. However, since none of these markers is currently ready for use in routine clinical practice, we do not consider them in this paper. On the other hand, we believe that biological research can benefit from a systematic clinical characterization of patients with a diagnosis of depression, since this is likely to facilitate the identification of more homogeneous subtypes of the syndrome.
This paper focuses on adult syndromal depression not secondary to another medical condition and not induced by a substance or a medication. We do not address issues relevant to subthreshold depressions or to syndromal depression in children, adolescents or the elderly. Gender‐ and culture‐related issues are considered in some sections of the paper, when relevant, rather than being addressed in specific sections. Perinatal depression is covered elsewhere in this issue of the journal 16 .
SYMPTOM PROFILE
The symptoms listed in the DSM‐5 and ICD‐11 for the diagnosis of depression are almost identical7, 8. Nine symptoms (depressed mood; markedly diminished interest or pleasure in activities; reduced ability to think or concentrate, or indecisiveness; feelings of worthlessness, or excessive or inappropriate guilt; recurrent thoughts of death, or suicidal ideation, or suicide attempts or plans; insomnia or hypersomnia; significant change in appetite or weight; psychomotor agitation or retardation; and fatigue or loss of energy) are shared by the two systems, while one (hopelessness about the future) appears only in the ICD‐11 list. In both systems, the presence of at least five of these symptoms is required most of the day, nearly every day, for at least two weeks, and the occurrence of either depressed mood or diminished interest or pleasure is mandatory.
There is some empirical evidence supporting the validity of these lists of symptoms. In fact, in a logistic regression analysis 17 , all nine symptoms listed in the DSM‐5 were found to be significant independent predictors of the diagnosis of depression, with the first two symptoms on the list having the highest positive predictive values. In a further analysis 18 , hopelessness about the future, the only ICD‐11 symptom not included in the DSM‐5, outperformed about half of the DSM‐5 symptoms in differentiating depressed from non‐depressed subjects. One additional symptom, diminished drive, performed more strongly than almost all of the DSM‐5 symptoms. Further items – such as lack of reactivity of mood (i.e., the individual's mood fails to brighten even temporarily in response to positive stimuli), anger, irritability, psychic anxiety, and somatic concomitants of anxiety (e.g., headaches, muscle tension) – also discriminated significantly between depressed and non‐depressed subjects 18 .
Indeed, a study carried out by using a network approach 19 has reported that the core symptoms of depression include “sympathetic arousal” (i.e., palpitations, tremors, sweating) and anxiety, in addition to energy loss, sadness, interest loss, pleasure loss, concentration problems, appetite problems and insomnia. Furthermore, a systematic review of qualitative studies of depression carried out worldwide 20 has found that some somatic items (i.e., general aches and pains, headaches, and “issues with the heart” such as heavy heart, heart pain and palpitations) are among the symptoms most frequently reported worldwide by depressed patients, albeit being somewhat more frequent in non‐Western populations.
Overall, although the lists of depressive symptoms provided by current diagnostic systems are supported by some empirical research, there is also some evidence that further components of the depressive syndrome are not included in those lists. Among these components, anxiety and somatic complaints are particularly prominent.
Not surprisingly, the symptoms included in the most frequently used rating scales for depression – the Hamilton Rating Scale for Depression (HAM‐D) 21 , the Montgomery‐Åsberg Depression Rating Scale (MADRS) 22 , the Beck Depression Inventory (BDI) 23 , the Center for Epidemiological Studies ‐ Depression (CES‐D) 24 , the Quick Inventory of Depressive Symptoms (QIDS) 25 , the Inventory of Depressive Symptoms (IDS) 26 , and the Zung Self‐Rating Depression Scale (SDS) 27 – exceed in number those included in the DSM‐5 and ICD‐11 definitions 28 (see Table 2).
Table 2.
Main components of the depressive syndrome and their coverage in diagnostic systems and rating scales
| ICD‐11 | DSM‐5 | HAM‐D | MADRS | BDI | SDQ | QIDS | CES‐D | |
|---|---|---|---|---|---|---|---|---|
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+ | + | + | + | + | + | + | + |
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+ | + | + | + | + | + | + | + |
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+ | + | + | + | + | + | + | + |
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+ | + | + | + | + | + | + | + |
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+ | + | + | + | + | + | + | + |
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+ | + | + | + | + | + | + | + |
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+ | + | + | + | + | + | + | + |
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+ | + | + | + | + | + | + | + |
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+ | + | + | + | + | + | + | + |
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+ | – | + | + | + | + | + | + |
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– | – | + | + | – | + | – | + |
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– | – | + | – | + | + | – | – |
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– | – | + | – | + | + | – | – |
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– | – | – | – | – | + | – | – |
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– | – | – | – | – | + | – | + |
HAM‐D – Hamilton Rating Scale for Depression, MADRS – Montgomery‐Åsberg Depression Rating Scale, BDI – Beck Depression Inventory, SDQ – Symptoms of Depression Questionnaire, QIDS – Quick Inventory of Depressive Symptoms, CES‐D – Center for Epidemiological Studies ‐ Depression
There are studies suggesting that the frequency of some depressive symptoms may be different in relationship to gender, with anger attacks, aggression, irritability and risk taking behaviors being more frequent in males than in females 29 . A self‐report rating scale aimed to assess depression in males, the Masculine Depression Scale (MDS) 30 , has indeed been developed.
Contrary to primary psychosis, in the case of depression there is no clustering of symptoms into psychopathological dimensions that is largely agreed upon by the research and clinical communities. The ICD‐11 subdivides the listed depressive symptoms into three clusters (affective, cognitive‐behavioral and neurovegetative), but provides no empirical support for this clustering, which is just aimed at facilitating the recollection of symptoms by clinicians 31 . However, there have been several attempts to propose and validate clusters of depressive symptoms that may be clinically useful.
Uher et al 32 proposed a model comprising three dimensions based on factor analysis: observed mood (including depressed mood and anxiety), cognitive (including pessimism and reduced interest‐activity) and neurovegetative (comprising problems with sleep and appetite). Another exploratory factor analysis 33 reported a general depressive symptom factor, and four further factors reflecting vegetative symptoms, cognitive symptoms (hopelessness/suicidal ideation), weight/appetite symptoms, and symptoms of agitation and anxiety. A more recent analysis 11 reported three clusters: core emotional symptoms, sleep symptoms, and “atypical” symptoms (including psychomotor agitation, psychomotor slowing, suicidal ideation, hypochondriasis and reduced libido).
Attempts have been made to relate either individual depressive symptoms or clusters of symptoms to a preferential response to various antidepressant drugs or to antidepressant medication vs. specific psychotherapies.
Antidepressant medication in general has been found to be more effective in treating core emotional and sleep symptoms than “atypical” symptoms as defined above 11 , with high‐dose duloxetine being superior to escitalopram in treating both emotional and “atypical” symptoms 11 . A score of at least 7 on the HAM‐D anxiety/somatization factor has been associated with a worse response to antidepressant medication in general 34 , but venlafaxine has been found to be superior to fluoxetine in depressed patients with a HAM‐D psychic anxiety score of at least 2 35 . An interest‐activity symptom cluster including low interest, reduced activity, indecisiveness and lack of enjoyment has been associated with a decreased response to antidepressant medication, with no significant difference between response to citalopram and nortriptyline 36 .
Observed mood and cognitive symptoms have been found to improve more with escitalopram than with nortriptyline, while neurovegetative symptoms showed the opposite pattern 37 . Trazodone, mirtazapine and agomelatine have been reported to be particularly effective on subjective and objective measures of sleep 38 . Five HAM‐D items (depressed mood, feelings of guilt, suicidal thoughts, psychic anxiety, and general somatic symptoms) have been found in an individual patient data meta‐analysis to show larger improvements with antidepressant medication compared to cognitive behavioral psychotherapy 12 .
Overall, some evidence seems to support the notion that the symptom profile, beyond the diagnosis of depression, may have value in predicting the response to specific antidepressants or to antidepressant medication vs. specific psychotherapies. However, this evidence is at present preliminary. Individual clinical trials have usually focused on the equivalence rather than the differences between the various treatments, and secondary analyses of databases using innovative techniques11, 12 are just starting to emerge.
Most research evidence to date has been collected using the HAM‐D, but the suitability of this rating scale (originally developed to evaluate hospitalized severely depressed patients) for populations of outpatients has been questioned 32 . There is a need for a tool covering the whole range of depressive symptoms, beyond the lists provided by current diagnostic systems, and probing the presence of these symptoms using multiple questions. The identification of meaningful clusters of symptoms, once again beyond the DSM‐5 and ICD‐11 lists, should be encouraged. The exploration of the relationships of individual symptoms or validated clusters of symptoms to the response to different treatments for depression should be identified as a research priority, requiring large patient samples (i.e., pooling results from different studies using the same assessment instruments) and innovative approaches to data analysis15, 39, 40.
Self‐administered questionnaires may be more suitable than the HAM‐D for use in routine clinical practice and for inclusion in decision support tools. A good example is the Symptoms of Depression Questionnaire (SDQ) 41 , a 44‐item validated instrument that covers anxiety, several somatic symptoms, anger attacks, irritability, and lack of reactivity of mood, in addition to the depressive symptoms listed in the DSM‐5 and ICD‐11. Factor analysis has led to the identification of five subscales of this tool: the first including low mood, lassitude and cognitive impairment; the second anxiety, agitation, irritability and anger; the third suicide‐related items; the fourth sleep problems; and the fifth changes in appetite and weight 41 .
The assessment of suicidality is an integral part of the evaluation of a patient with a diagnosis of depression, both in research and in clinical settings. A meta‐analysis of 57 studies of more than 23,000 patients with depression found a lifetime rate of suicide attempt of 31% 42 . Suicidal ideation and suicide attempts are among the strongest predictors of completed suicide 43 , although the positive predictive value of any risk factor or risk algorithm is not high. For the assessment of suicide risk, the Columbia‐Suicide Severity Rating Scale (C‐SSRS) 44 is a validated tool requiring specific training. The 7‐item Concise Health Risk Tracking Self‐Report (CHRT‐SR) 45 is an alternative possibly more suitable for use in routine clinical practice.
All patients presenting with depression should be screened for bipolar disorder. There are two screening self‐report instruments – the Mood Disorders Questionnaire (MDQ) 46 and the Mood Swings Questionnaire (MSQ) 47 – with high and comparable discriminatory capacity, that can be considered for use in clinical practice.
CLINICAL SUBTYPES
The existence of clinical subtypes of depression has been proposed and discussed for many decades. Clinicians have long endorsed the notion that there are two core subtypes: the melancholic/endogenous/vital/autonomous vs. the non‐melancholic/reactive/neurotic/situational. The traditional view has been that the former depressions arise from biological perturbations, while the latter are linked to situational factors, often in the context of personality pathology. Although this view has been mostly dismissed in the post‐DSM‐III era, the melancholic subtype of depression has been retained by diagnostic systems.
Various definitions of melancholia have been put forward over the years 48 . Some have been based solely on the presence of particular symptoms, such as pervasive anhedonia and psychomotor slowing. Others have focused on a combination of the presence of characteristic symptoms and the absence of features thought to characterize neurotic depression, such as precipitating events and personality disorders. No definition has emerged as more reliable or valid than the others.
The DSM‐5 7 defines the specifier “with melancholic features” by the presence of either loss of pleasure in all or almost all activities, or lack of reactivity to usually pleasurable stimuli, plus at least three of the following: a distinct quality of depressed mood (characterized by profound despondency, despair and/or moroseness, or by empty mood), worsening of depression in the morning, early‐morning awakening, marked psychomotor agitation or retardation, significant anorexia or weight loss, and excessive or inappropriate guilt. The ICD‐11 definition 8 is similar, but distinct quality of depressed mood and excessive or inappropriate guilt are not included.
The distinction between melancholic and non‐melancholic depression can be assisted by the clinician‐rated Sydney Melancholia Prototype Index, which has positive and negative predictive values of 0.90 and 0.88, respectively 49 . The current approach of the DSM‐5 and ICD‐11 to consider melancholia as a specifier to the diagnosis of depression rather than a distinct disease entity seems to be supported by the observation that, in several patients with recurrent depression, some episodes are melancholic and some others are not 50 .
The evidence on the treatment validity of melancholic subtyping of depression is not robust. This subtyping has been better in predicting non‐response to placebo than response to active medication 51 . Early research suggested that patients with melancholia respond less well to psychotherapy 52 . Some more recent research, however, has failed to demonstrate that melancholic subtyping predicts or moderates the response to cognitive behavioral psychotherapy 53 . Some studies have suggested that patients with melancholia respond better to tricyclic antidepressants than to selective serotonin reuptake inhibitors (SSRIs) and are particularly responsive to electroconvulsive therapy54, 55, but the former differential response has not been consistently confirmed 56 .
Among treatment guidelines, only those of the Royal Australian and New Zealand College of Psychiatrists 57 and the American Psychiatric Association 6 make qualified suggestions that biological interventions may be superior for melancholia. Overall, there is a clear disconnect between the rich history of descriptions of this subtype of depression and the modern‐day empirical treatment literature based on official diagnostic criteria. Addressing this disconnect represents a clear unmet need of significant clinical relevance.
A second widely accepted subtype is psychotic depression, defined by the presence of delusions or hallucinations during the depressive episode, and the lack of persistence of psychotic symptoms outside of the period of depression. In patients with recurrent episodes of depression, the psychotic features tend to recur, but there are several patients with recurrent depression in which some episodes are psychotic and some others are not 58 , again supporting the DSM‐5 and ICD‐11 approach of regarding psychotic features as a specifier to the diagnosis of depression rather than considering psychotic depression as a distinct disease entity.
Psychotic features in depressed patients are associated with increased suicidality, particularly during the acute episode, increased mortality from physical causes, and a poorer outcome 58 . A Cochrane Library review concluded that combination treatment with an antidepressant and an antipsychotic is superior to monotherapy with either agent alone or placebo in psychotic depression 59 , and this is currently a widely shared notion.
Because of these treatment implications, it is important for clinicians to recognize psychotic symptoms in depressed patients. In research settings, these symptoms are assessed with semi‐structured interviews such as the Structured Clinical Interview for DSM‐5 (SCID‐5) 60 . The psychosis subscale of the self‐report Psychiatric Diagnostic Screening Questionnaire (PDSQ) 61 may be a reasonable alternative in clinical contexts. As emphasized in the ICD‐11 8 , the boundary between psychotic symptoms and persistent depressive ruminations or sustained preoccupations is not always clear.
A further subtype of depression, introduced for the first time in the DSM‐5 but not included in the ICD‐11, is mixed depression. This subtype has been defined in varying ways in the literature 62 . The DSM‐5 requires the presence of at least three manic/hypomanic symptoms out of a list of seven (elevated, expansive mood; inflated self‐esteem or grandiosity; more talkative than usual or pressure to keep talking; flight of ideas or racing thoughts; increase in energy or goal‐directed activity; increased involvement in risky activities; and decreased need for sleep). This definition has been criticized because it does not include features that have been considered as typical of mixed depression, such as psychomotor agitation, irritability and distractibility 63 .
The presence of manic/hypomanic symptoms during a depressive episode is associated with a higher rate of anxiety and substance use disorders, increased suicidality, greater impairment in functioning, more frequent family history of bipolar disorder, and poorer response to treatment 62 . It has been suggested that patients with mixed features who are treated with antidepressants should be monitored closely because they are at greater risk for emergence of activation, hypomania and suicidality 64 . An expert panel of mood disorder researchers, while acknowledging the limited number of prospectively designed trials for depression with mixed features, recommended atypical antipsychotic medication as the first‐line treatment 65 .
The most commonly used clinician‐administered measure to evaluate manic/hypomanic symptoms in depressed patients is the Young Mania Rating Scale (YMRS) 66 . A self‐report questionnaire, the CUDOS‐M 67 , has been specifically designed to assess the DSM‐5 mixed features specifier to the diagnosis of depression.
The subtype of anxious depression has been introduced in the DSM‐5 through the specifier “with anxious distress”, and is also present in the ICD‐11 (“with prominent anxiety symptoms”). The DSM‐5 specifier requires the presence of at least two out of a list of five symptoms (feeling keyed up or tense, feeling unusually restless, difficulty concentrating because of worry, fear that something awful may happen, feeling that the individual might lose control of himself).
Patients with anxious depression are characterized by higher levels of suicidal ideation, poorer functioning, poorer health‐related quality of life, and greater chronicity 68 . Co‐occurring anxiety has been reported to be a predictor of a poor response to antidepressant treatment in general 33 or to specific antidepressants 69 , but these findings do not necessarily apply to anxious depression as defined in the DSM‐5 and ICD‐11, because alternative definitions of this depression subtype show only modest levels of concordance 70 . A self‐report questionnaire, the CUDOS‐A 71 , has been specifically designed to assess the DSM‐5 anxious distress specifier.
The concept of atypical depression gained prominence in the 1980s, when a group at Columbia University offered specific criteria focused on mood reactivity, sensitivity to rejection, extreme anergia, and the reverse vegetative features of increased appetite and increased sleep 72 . In controlled treatment trials, they found that patients meeting this subtype responded better to monoamine oxidase inhibitors (MAOIs) than to tricyclic antidepressants 72 . Based on their research, the atypical depression subtype of depression entered the DSM‐IV and was retained in the DSM‐5.
However, MAOIs are no longer widely used, and evidence that patients with atypical depression respond better to MAOIs than to the newer generation medications has been lacking 73 . Moreover, a recent meta‐analysis found that atypical depression did not predict or moderate the response to either cognitive behavioral therapy or antidepressant medication 53 . Indeed, this specifier is not included in the ICD‐11.
The subtype of seasonal depression is based on the lifetime pattern of depressive episodes. The most common pattern is autumn/winter onset, with spring/summer resolution. Characteristic symptoms of winter depression are hypersomnia, hyperphagia, and carbohydrate craving 7 . Consistent with the hypothesis that seasonal depression is the result of a reduction in daylight hours, some epidemiological studies have found that prevalence rates are increased in Northern latitudes, though the results have been mixed 74 .
Bright light therapy is an effective treatment for symptomatic seasonal depression 75 . The recurrent pattern of this subtype of depression provides a unique opportunity to examine preventive strategies. Three Cochrane Library reviews concluded that bupropion XL is effective in preventing seasonal recurrence, while the evidence is insufficient to recommend either psychotherapy or light therapy as preventive interventions76, 77, 78. The most frequently used screening scale for seasonal depression, the Seasonal Pattern Assessment Questionnaire 79 , has been criticized for being overly inclusive. The Seasonal Health Questionnaire appears to be a more valid screening tool 80 .
Overall, treatment guidelines do not identify, or are equivocal in recommending, preferred first‐line treatments for most subtypes of depression, though there are some important exceptions. The American Psychiatric Association 6 , the Royal Australian and New Zealand College of Psychiatrists 57 , and the Canadian Network for Mood and Anxiety Treatments (CANMAT) 38 all recommend combined antidepressant and anti‐psychotic medication or electroconvulsive therapy as first‐line treatments for psychotic depression. The UK National Institute for Health and Care Excellence (NICE) guidelines 5 explicitly state that clinicians should not vary treatment strategies by depressive subtype, though elsewhere they specify that augmentation with an antipsychotic should be considered in patients with psychotic symptoms. The Australian and New Zealand as well as the American guidelines indicate that biological interventions may be preferred for melancholia, and that light therapy is a first‐line treatment for winter depression, though antidepressant medication is also effective6, 57.
Little research has examined the impact of clinical subtypes of depression on treatment decision‐making in routine clinical practice. A survey of the factors influencing psychiatrists' choice of pharmacological treatment found that melancholic and atypical features were rarely the basis for selecting one medication over another, and that anxiety was the most commonly endorsed feature for selecting a particular medication 81 . This study, however, was limited to the question of how medications are selected, and did not assess other types of treatment decision‐making such as referral for psychotherapy, electroconvulsive therapy, or light therapy.
In conclusion, several subtypes of depression have been identified. The most clinically relevant of these subtypes is psychotic depression, as there is consistent evidence that it requires a specific treatment approach. The melancholic subtype retains clinical appeal, but the evidence supporting its differential response to treatment is not consistent. The treatment implications of the anxious and mixed subtypes of depression remain insufficiently studied, whereas the atypical subtype seems to be less clinically relevant today than it was some decades ago. Overall, this is a research area that requires more systematic attention as part of the current effort to personalize the management of depression.
SEVERITY
While research has not been entirely consistent, the severity of depression has been associated with health‐related quality of life, functional impairment, suicidality, longitudinal course, and response to treatment 82 . There are no biomarkers of depression that characterize disorder severity. Thus, researchers and clinicians base their severity ratings on the clinical features of the disorder. Almost all research on severity depends on depression symptom scales.
In the DSM‐5 7 , depression is classified as mild, moderate or severe based on the number of symptoms, the level of distress caused by the intensity of the symptoms, and the degree of impairment in social and occupational functioning. The definition of functional impairment is limited to social or occupational functioning and does not include other potentially important areas of functioning, such as self‐care, parenting or schooling. Mild depression is specified when “few, if any, symptoms in excess of those required to make the diagnosis are present, the intensity of the symptoms is distressing but manageable, and the symptoms result in minor impairment in social or occupational functioning”. Severe depression is specified when “the number of symptoms is substantially in excess of that required to make the diagnosis, the intensity of the symptoms is seriously distressing and unmanageable, and the symptoms markedly interfere with social and occupational functioning”. The DSM‐5 does not explicitly define moderate depression other than to say that the number of symptoms, their intensity, and/or functional impairment are between mild and severe.
The ICD‐11 description of mild, moderate and severe depression is more detailed 8 . Mild depression requires that none of the symptoms are intense, and there is some difficulty in personal, family, social, educational, occupational or other important areas of functioning. Moderate depression is defined by a marked intensity of several symptoms or a large number of less severe symptoms, and a considerable difficulty in functioning. Severe depression requires that many or most symptoms are present to a marked degree or some symptoms to an intense degree, and there is a complete or near‐complete inability to function in some domain. As with the DSM‐5, there are potential problems with the logic of these definitions. For example, how should we classify a patient with symptoms of moderate intensity who is unable to work? Such a patient would meet the impairment threshold for severe depression, but not the symptom threshold.
Despite potential problems in applying the DSM‐5 and ICD‐11 definitions, both of them have more intuitive appeal to clinicians than severity classification based on depression symptom scales, because they consider the degree of impairment as co‐equal to symptom level. However, there is almost no research on the DSM and ICD definitions. It is also noteworthy that neither DSM‐5 nor ICD‐11 consider suicidality in their definitions of severity. This contrasts with many physical illnesses, whereby severity refers to the likelihood of imminent or distal mortality, or to prognosis or future course.
The DSM and ICD definitions of depression severity have not been used in treatment studies. In almost all these studies, severity has been evaluated by the total score on a symptom rating scale, usually the HAM‐D or the MADRS. Of note, adding up item scores to yield a total score as a measure of overall depression severity assumes that all symptoms are equal indicators of severity, an assumption which is not empirically supported.
According to current treatment guidelines, depression severity is an important consideration in treatment decision‐making. For example, the NICE guidelines 5 discourage the use of antidepressant medications as the initial treatment option for mild depression, whereas they recommend it, along with empirically supported psychotherapies, for moderate and severe depression. The third edition of the American Psychiatric Association's guidelines 6 recommends either psychotherapy or pharmacotherapy for mild and moderate depression, and pharmacotherapy (with or without psychotherapy) for severe depression.
If clinicians are to follow treatment guidelines and base initial treatment selection on the severity of depression, then it is important to have a consistent method of determining that severity. Based on a review of the available evidence, the following severity ranges have been suggested for the 17‐item HAM‐D: 0‐7 for no depression, 8‐16 for mild depression, 17‐23 for moderate depression, and >24 for severe depression 82 .
However, a rating scale such as the 17‐item HAM‐D takes too much time to administer to be suitable for use in routine clinical practice. A 6‐item version of this scale, which is purported to assess the core features of depression, has been found to be superior to the full‐length scale at detecting differences between active drug and placebo 83 . This version of the scale might be more suitable for clinical use. However, cutoff scores to demarcate categories of severity on this version are not established.
In clinical practice, it is more likely that self‐administered questionnaires will be used to quantify the severity of depressive symptoms. Self‐report scales that assess the symptoms of depression and are available for clinical use at no cost include the Clinically Useful Depression Outcome Scale (CUDOS) 84 , the QIDS 24 , the Patient Health Questionnaire‐9 (PHQ‐9) 85 , and the 8‐item PROMIS Depression Short Form (www.dsm5.org). However, there is a marked disparity among these tools in the classification of depressed patients into severity groups, making their use to guide treatment selection problematic 86 .
So, overall, while treatment guidelines emphasize depression severity as a key consideration in treatment decision‐making, there is no agreement about how this severity should be assessed in ordinary clinical practice. Reaching this agreement represents today a major unmet need.
Approximately a decade ago, two analyses of the US Food and Drug Administration (FDA) database found that drug‐placebo differences were largest in antidepressant trials with the highest mean baseline severity on the HAM‐D, whereas the differences in the trials with lower mean baseline scores were modest and clinically insignificant87, 88. More recently, large pooled analyses of patient level data from published and unpublished studies have found that antidepressants are effective across a range of severity9, 89. However, these studies do not include patients across the full range of symptom severity, because they require a minimum score on a symptom severity scale for study entry. Thus, the lower bound of symptom severity associated with antidepressant efficacy has not been established. Nonetheless, at the present time, it is reasonable to conclude that the efficacy of antidepressants is not limited to the small group of patients who score highest on symptom severity scales.
Regarding the impact of severity on the efficacy of psychotherapies for depression, a meta‐analysis of 132 controlled studies of various types of psychotherapy found that higher mean baseline symptom scores did not predict poorer response 10 . More recently, an individual patient data meta‐analysis 90 of pooled data from 16 studies compared antidepressants and cognitive behavioral therapy: severity was not associated with differential treatment outcome.
The results of these more recent analyses are thus not consistent with clinical lore and current treatment guidelines which recommend medication as the first line treatment for severe depression. However, interpretation of these data must be tempered by the recognition that studies often truncate the range of severity included. More studies of psychotherapy than pharmacotherapy of depression limit the upper range of severity 91 . Thus, the most severely depressed patients may not have been included in at least some controlled psychotherapy treatment studies. Furthermore, the above studies are based on scales assessing symptom severity without consideration of the degree of functional impairment.
The use of scales assessing symptom severity to monitor the course of treatment is supported by research demonstrating that measuring outcome in clinical practice results in improved outcome92, 93. However, which scales should be used in routine clinical practice for this purpose currently remains uncertain. For practical reasons, self‐administered questionnaires may be more suitable.
NEUROCOGNITION
Cognitive deficits are a core dimension of the depressive syndrome and have been identified in both first‐ and multiple‐episode patient populations 94 . They may be antecedent to the formal diagnosis of depression and persist during “asymptomatic” states 95 . Their magnitude (i.e., expressed as effect sizes) ranges from small to large and is clinically relevant 96 . Moreover, it has been empirically shown that a significant degree of psychosocial impairment and reduction of workplace productivity in adults with depression is mediated directly by cognitive impairment 97 .
Neurocognition may be disaggregated into executive functions, attention/concentration, learning/memory, and processing speed 98 . Executive functions can be further subdivided into the planning, initiation, sequencing, monitoring and inhibition of thoughts, moods and behavior 99 .
Replicated evidence indicates that cognitive deficits may be progressive in patients with depression especially in the subdomain of learning/memory 100 . This observation aligns with a separate body of evidence documenting volumetric reduction in memory substrates (e.g., hippocampus) in adults with depression 101 . Conceptually, the progression of cognitive deficits in subpopulations of patients may provide an explanatory framework for the attenuated response to antidepressants in cohorts of adults with depression later in the illness trajectory 102 .
The prevalence, persistence, as well as the mediational effect of cognitive deficits on quality of life, psychosocial and workplace function, as well as response to treatment, suggests the need for systematic screening and measurement of neurocognition in adults presenting with clinically relevant depressive symptoms. The lack of a significant correlation between self‐ and objectively‐measured cognitive functioning in depression indicates that the exclusive reliance on self‐reported cognitive functions will insufficiently characterize the magnitude and complexity of cognitive disturbances in affected individuals 98 .
Conventional rating instruments of depressive symptoms – such as the PHQ‐9 and the QIDS – rely on patient self‐report, contain relatively few items assessing cognition and, importantly, do not fully capture the ecological manifestations of cognition in an affected individual's everyday life. Consequently, it is recommended that adults with depression be specifically asked about the presence of cognitive deficits and their impact on their quality of life and psychosocial/workplace functioning. It is also suggested to supplement the clinical assessment with a validated, reliable and sensitive objective measure suitable for use in ordinary practice 103 .
Most cognition assessment tools are too time‐consuming for clinical use and many require professional interpretation, often with cost. The THINC‐integrated tool (THINC‐it) is an instrument with satisfactory psychometric properties whose administration is feasible in routine practice 104 . It has been validated both as a screening tool for cognitive impairment in depression and as a measure to detect change in cognition with treatment. It evaluates executive functions, information processing speed, attention/concentration, learning/memory, as well as self‐reported cognitive functions. It is free of charge and downloadable to a smart device, and takes approximately 5‐8 min to complete.
The presence of cognitive impairment in a patient with depression has significant implications for the formulation of the management plan. Psychotropic drugs that are known to interfere with cognitive functions should be discontinued. These include antidepressants with anticholinergic activity (e.g., tricyclic antidepressants), antipsychotics with significant anti‐histamine properties, and benzodiazepines98. Moreover, recreational substances (e.g., cannabis) that interfere with cognition should be avoided. Improving sleep quality would also be expected to ameliorate cognitive functions in depressed patients. Treating both psychiatric (e.g., alcohol misuse) and medical (e.g., diabetes mellitus, obesity) comorbid states should be prioritized as part of a “cognitive preserving” approach to managing depression 105 .
Treatments specifically targeting cognitive functioning in depression have been hitherto insufficiently evaluated. Cognitive remediation has been found to improve attentional capacity in adults with depression, but its benefit across other domains of cognitive functioning awaits further documentation106, 107. Aerobic exercise shows some promise in preserving and improving cognitive functions in adults with age‐related cognitive decline, but its efficacy in improving cognition in adults with depression remains just a testable hypothesis 108 . Neurostimulation (e.g., repetitive transcranial magnetic stimulation) may also improve subdomains of cognition in individuals with depression independent of mood symptoms 109 .
Available evidence suggests that the antidepressants vortioxetine and duloxetine may have direct and independent effects on cognitive functions. Vortioxetine has been reported to improve executive functions, attention, learning/memory and processing speed 110 , while duloxetine has been found to have a favorable impact on learning/memory 111 . Psychostimulants, anti‐inflammatory agents, and possibly ketamine may be pro‐cognitive in select individuals 98 .
New technologies, such as ecological momentary assessment, may help in the assessment of neurocognition in patients with depression, by providing a more precise characterization of an individual's cognitive abilities in real time across different environments 112 .
FUNCTIONING AND QUALITY OF LIFE
When defining the depressive syndrome, classification systems go beyond symptoms and require that these symptoms “cause clinically significant distress or impairment in social, occupational, or other important areas of functioning” (DSM‐5) 7 or “result in significant impairment in personal, family, social, educational, occupational, or other important areas of functioning” (ICD‐11) 8 .
Since these functional aspects are not well defined, the clinician is left with hesitancy as to how to assess them. A study in primary care in which physicians were asked to include patients with major depression showed that 95% of the included patients had, as requested, at least five of the nine DSM depressive symptoms, but that only 72% met the criterion of at least moderate impairment in occupational, social or family functioning 113 . Assessing functioning appropriately could therefore improve diagnostic accuracy.
The growing interest in functioning and in quality of life (QOL) goes hand in hand with the recent emphasis on shared decision‐making, where the patient and the physician should agree upon the treatment goals. In fact, in depression, the main patient expectations are restoration of positive emotions, functioning and meaningfulness of life rather than merely symptom relief, far away from what is usually assessed in randomized controlled trials114, 115.
Numerous scales and questionnaires have been proposed for the assessment of functioning and QOL (over one thousand QOL scales have been published), but they are rarely used by clinicians. They are often overly comprehensive and therefore only suitable for use in research settings, or they are a mix of symptoms and functioning, or they contain some items or subscales (i.e., self‐care, mobility) which make them useful in a very severe patient population but not in the majority of outpatients.
Another problem is that some scales make it difficult to differentiate between impaired functioning caused by the depressive disorder and the problems causing or maintaining the disorder: for example, impairment in occupational functioning caused by the depressive mood state versus difficulties and conflicts at work leading to or maintaining the depressive mood state.
The concept of QOL is even more confusing. The relevant literature differentiates between objective and subjective QOL 116 . Objective QOL refers to a functionalist approach: the ability to perform roles that are considered normal for people (i.e., occupational, social, family life), aiming for an optimal level of functioning defined externally by society. Subjective QOL refers to a needs‐based approach: the ability and capacity to satisfy one's needs (physical, emotional or social), which involves a personal cognitive‐emotional appraisal and mediates between objective indices (living conditions, symptoms and side effects) and personal expectations and aspirations 117 .
The latter comes close to the concept of “life satisfaction”, which is influenced by the excess of negative affect and lack of positive affect in depression 117 . Satisfaction with one's life implies a contentment with or acceptance of one's life circumstances, or the fulfilment of one's wishes and needs for one's life as a whole 117 . It comes also close to the concept of eudaimonic well‐being: a sense of having meaning and purpose in one's life, considered very important from the patients' perspective 115 .
Among the various scales available for the assessment of functioning and QOL, we do not recommend the Global Assessment of Functioning (GAF) 118 , because it reflects too closely symptom severity, nor the 36‐item Short Form Survey (SF‐36) 119 , which mixes symptoms and functioning. Some very well‐developed scales – such as the World Health Organization (WHO) Disability Assessment Schedule 120 (36‐item WHODAS 2.0), the International Classification of Functioning (ICF) 121 , the WHO Model Disability Survey (MDS) 122 , and the Quality of Life Enjoyment and Satisfaction Questionnaire (Q‐LES‐Q) 123 – may be too comprehensive to be used in daily practice. Even the 12‐item version of the WHODAS 2.0 is not well suited for the majority of depressed outpatients, due to the inclusion of items such as “washing your whole body” and “getting dressed” that are likely to be not relevant.
More suitable for routine practice may be one tool for assessing both functioning and life satisfaction and two tools for assessing life satisfaction.
The tool for assessing both functioning and life satisfaction is taken from the Leuven Affect and Pleasure Scale (LAPS) 124 . Four items are considered: “I can think clearly, I can focus well. I can make decisions and my memory is good”; “I can function well (occupational, social and family life)”, “I feel my life is meaningful”, “I feel happy”. For each item, the respondent is asked “To what extent did you experience this during the past week?”. The ratings are: “0 (not at all)”, “1 to 3 (a little bit)”, “4 to 6 (moderately)”, “7 to 9 (quite a bit)”, and “10 (very much)”.
A first tool for assessing life satisfaction is based on the Organisation for Economic Co‐operation and Development (OECD) guidelines 125 . Two items are considered: “Overall, how satisfied are you with life as a whole these days?”; “Overall, to what extent do you feel the things you do in your life are worthwhile?”. The rating is from “0 (not at all satisfied)” to “10 (completely satisfied)”.
A second tool for assessing life satisfaction is based on the finding that the subscale “Inner experiences” from the Quality of Life Self‐Assessment Inventory (QLS‐100) 126 is the most impaired in patients with depression 127 . The subscale includes five items: “Feeling at ease”, “Being pleased with life”, “Sense of fulfilment”, “Being of use” and “Being understood by others”. The rating on each item can be “Satisfactory” or “Unsatisfactory”.
A routine assessment of these aspects of functioning/QOL/life satisfaction in clinical practice is important for multiple reasons. First, it can improve diagnostic accuracy: in defining depression, both the DSM‐5 and ICD‐11 go beyond symptoms, and assessing functioning can reduce the number of false positive diagnoses 113 . Second, shared decision‐making and patient‐centered care have gradually become integrated in medicine, where “what matters to you” has become as important as “what is the matter”: concordance on the treatment goals (what does the physician as well as the patient expect from treatment) has been shown to result in better outcomes six months later, at both the symptom and the QOL level128, 129, 130. Third, medicine is about curing and caring: although cure is the ultimate goal of treatment, many patients can achieve a meaningful QOL and an acceptable level of life satisfaction despite (residual) symptoms.
CLINICAL STAGING
Clinical staging indicates where a person stands along the continuum of the course of depression 131 . Furthermore, it takes into consideration the response of the disorder to specific therapies, with particular reference to treatment resistance 132 .
A staging model of depression was first presented in 1993 131 and updated twenty years later 132 (see Table 3).
Table 3.
Clinical staging of depression
| STAGE 1 | Prodromal phase
|
| STAGE 2 | First depressive episode |
| STAGE 3 | Residual phase
|
| STAGE 4 |
|
| STAGE 5 | Chronic depressive episode (i.e., episode lasting at least two years without interruptions) |
This staging is a modification of that proposed by Cosci and Fava 132
The prodromal phase (stage 1) is characterized by either aspecific symptoms (generalized anxiety, irritability, sleep disorders) with mild functional change or decline (stage 1a), or subthreshold depressive symptoms (stage 1b). There is a large inter‐individual variability in this prodromal phase; however, for a specific patient, different depressive episodes tend to share a similar prodromal symptomatology.
At stage 2, the patient presents the first depressive episode. Then a residual phase (stage 3) may occur. This phase may be marked by aspecific symptoms (sleep disturbance, generalized anxiety, irritability, anorexia, impaired libido) (stage 3a), or by residual depressive symptoms (depressed mood, guilt, hopelessness) (stage 3b), or by the occurrence of dysthymia (a mild chronic depressive syndrome) (stage 3c).
Residual symptoms are a strong predictor of relapse 132 . Certain prodromal symptoms may be overshadowed by the acute manifestation of the disorder, but persist as residual symptoms and progress to become prodromes of relapse. A model for relating prodromal and residual symptomatology, based on the so‐called rollback phenomenon, has been proposed 133 : as the ‐episode remits, it progressively recapitulates, in reverse order, many of the symptoms that were seen during the time it developed. The rollback phenomenon has been substantiated in depression 132 .
Stage 4 is characterized by recurrent depression or by double depression (i.e., depressive episodes superimposed on dysthymia). The link between dysthymia and relapse of depressive episodes has been widely confirmed 134 . At stage 5, the patient has a chronic depressive episode (i.e., an episode lasting at least two years without interruptions).
This longitudinal view of depression entails two important clinical implications. First, let us consider a patient who currently presents with depressive symptoms that are not sufficient to formulate the diagnosis of a depressive episode. Staging allows to determine whether such symptoms are a residual symptomatology of a previous episode (thus indicating a high risk of relapse) or can be viewed as manifestations of mild or subthreshold depression.
A second implication is concerned with treatment planning. Staging allows selection of a specific treatment geared to the phase of development of depressive disorder 135 . In particular, the sequential model is an intensive, two‐step approach, where one type of treatment (i.e., psychotherapy) is employed to address symptoms which another type of treatment (i.e., pharmacotherapy) has been unable to improve 136 . The sequential model has been found to prevent depressive relapse in a number of ran‐domized controlled trials135, 136. Furthermore, chronicity (stage 5) has been reported to be a predictor of a better response to the combination of pharmacotherapy and psychotherapy vs. either treatment alone 137 .
Different methods to stage degree of treatment resistance in patients with depression have been suggested.
In the five‐stage model 138 , patients are classified according to the number and classes of antidepressants that failed to produce a response, with staging moving from more common to less common treatments. Thus, for instance, stage I is characterized by failure of at least one adequate trial of one major class of antidepressants.
A second model is the European approach 139 . Stage A represents no response to one adequate antidepressant trial lasting 6‐8 weeks. Treatment‐refractory depression (stage B) is defined by the failure of two or more adequate trials of different antidepressants given in adequate dosages for a period of at least 12‐16 weeks, but no longer than one year. Chronic resistant depression (stage C) is marked by failure of several antidepressant trials, including augmentation strategies, lasting one year or more.
The Massachusetts General Hospital model 140 considers both the number of failed trials and the intensity of each trial, without assumptions on the hierarchy of antidepressant classes. This model generates a score reflecting the degree of treatment resistance and ranging from 0 to 5.
Finally, the Maudsley Staging Method 141 incorporates, in addition to the number of failed treatment trials, factors considered to be closely related to the depressive disorder itself, such as duration and severity, as well as the use of augmentation or electroconvulsive therapy. The stage of treatment resistance is represented as a single score ranging from 3 to 15.
An attempt to integrate the four models is proposed in Table 4, which also includes psychotherapeutic approaches 135 . Stage 0 is defined by no history of failure to respond to a therapeutic trial. Stages 1 to 3 are characterized by failure of one, two or at least three adequate therapeutic trials of a specified duration. Stage 4 is defined by the failure of three or more adequate trials, with at least one involving augmentation/combination or electroconvulsive therapy. In this model, the expression “therapeutic” means either psychopharmacological therapy or psychotherapy.
Table 4.
Staging of depression according to levels of treatment resistance
| STAGE 0 | No history of failure to respond to a therapeutic trial |
| STAGE 1 | Failure of one adequate therapeutic trial (duration: 6‐8 weeks for medication; 36 weeks‐1 year for psychotherapy) |
| STAGE 2 | Failure of two adequate therapeutic trials (duration of each trial: 12‐16 weeks for medication; 36 weeks‐1 year for psychotherapy) |
| STAGE 3 | Failure of three or more adequate therapeutic trials (duration of each trial: 12‐16 weeks for medication; 36 weeks‐1 year for psychotherapy) |
| STAGE 4 | Failure of three or more adequate trials, with at least one involving augmentation/combination or electroconvulsive therapy (duration of each trial: at least 3 months) |
This staging is a modification of that proposed by Cosci and Fava 132
In summary, staging allows to characterize a patient with a diagnosis of depression with respect to both the phase of the development of the disorder and its response to specific therapies, and can therefore be useful in clinical practice.
PERSONALITY TRAITS
Personality traits should be routinely assessed in a person with a diagnosis of depression. These traits, particularly neuroticism, may have provided a dispositional vulnerability for the onset of the depression, and additional traits may impact on how the patient responds to treatment. However, the assessment of personality traits while the person is clinically depressed can often be problematic, as the depressed mood will influence the patient's self‐description.
The predominant model for the description of personality structure is the Five Factor Model (FFM) 142 , consisting of the five broad domains of neuroticism, extraversion (vs. introversion), openness (or conventionality vs. unconventionality), agreeableness (vs. antagonism), and conscientiousness (or constraint vs. disinhibition).
Neuroticism is particularly important as a precursor for major depressive episodes, as it concerns the disposition to experience negative affects, including sadness as well as anger and anxiety 143 . Persons with elevated levels of neuroticism respond poorly to environmental stress, interpret ordinary situations as threatening, and can experience minor frustrations as hopelessly overwhelming 144 . A clinician may need to treat the patient's personality to the extent that the current depression is secondary to the neuroticism. There is now a manualized psychotherapy for the treatment of neuroticism 145 . Techniques that help reduce neuroticism include cognitive therapy, exposure, and mindfulness145, 146.
Personality traits can also impact treatment. Persons who are highly conscientious are more likely to adhere to demanding treatment regimens, whereas persons who are low in conscientiousness (i.e., disinhibited or lax) are more likely to drop out. Persons who are high in openness will be more receptive to exploratory insight; persons who are extraverted are more likely to be comfortable and active within group therapy; and persons who are antagonistic are likely to be disruptive within inpatient settings and oppositional or argumentative within individual therapeutic sessions, whereas persons who are agreeable are more likely to be compliant 147 . There are empirically supported strategies to treat maladaptive traits: for example, goal planning to increase conscientiousness, social skills training to decrease detachment, and cognitive restructuring to decrease antagonism 146 .
There has been a study reporting that depressed patients with higher scores on neuroticism are more likely to respond to pharmacotherapy than to cognitive behavioral psychotherapy, suggesting a potential usefulness of treatment sequencing (i.e., initial treatment with medication and subsequent introduction of psychotherapy when the patient is better able to benefit from cognitive behavioral strategies) 148 .
The maladaptive trait models included in the Section III of the DSM‐5 (negative affectivity, detachment, disinhibition, antagonism and psychoticism) and in the ICD‐11 (negative affectivity, detachment, disinhibition, dissocial and anankastia) are aligned conceptually and empirically with the FFM. For example, ICD‐11 negative affectivity aligns with FFM neuroticism, detachment with introversion, dissocial with antagonism, anankastia with conscientiousness, and disinhibition with low conscientiousness 149 .
Given that these traits are maladaptive variants of the FFM, one can infer their likely impact on the treatment of depression. For example, the same implications for treatment apply to ICD‐11 negative affectivity, detachment, dissocial and disinhibition that occur for FFM neuroticism, introversion, antagonism and low conscientiousness, respectively. The DSM‐5 and ICD‐11 trait models do not include adaptive personality strengths (e.g., extraversion and conscientiousness) and so will not indicate how positive personality traits can facilitate treatment response.
Personality disorder syndromes, such as borderline and antisocial personality disorders, are constellations of maladaptive personality traits and can therefore impact on treatment. Patients with borderline disorder may form intense relationships with their therapist, sometimes leading to violation of professional boundaries; patients with dependent disorder may become overly attached and reliant; patients with histrionic disorder may be overly flirtatious and provocative; patients with narcissistic disorder may be critical and devaluing; and patients with antisocial disorder may be deceptive, disruptive and oppositional. Cognitive behavioral, dialectical, schema, and psychodynamic therapies are efficacious for personality disorders 150 . Pharmacotherapy can also be effective for borderline personality disorder, but the treatment will have to be maintained.
The co‐occurrence of a diagnosis of personality disorder with that of depression has been found to be associated with a better response to a combination of pharmacotherapy and psychotherapy than to pharmacotherapy alone 151 . In patients with avoidant personality disorder, cognitive behavior psychotherapy has been reported to be superior to interpersonal psychotherapy 152 .
There are many alternative measures for the assessment of FFM personality traits, the DSM‐5 and ICD‐11 maladaptive trait models, and the personality disorder syndromes. The predominant and most well validated self‐report measure of the FFM is the NEO Personality Inventory ‐ Revised (NEO PI‐R) 153 . This is a 240‐item self‐report commercially published measure. A closely comparable (and freely available) measure is the International Personality Item Pool ‐ NEO (IPIP‐NEO) 154 . Both the NEO PI‐R and IPIP‐NEO, though, are relatively long. There are several abbreviated measures, including the Five Factor Model Rating Form (FFMRF) 155 and the Big Five Inventory‐2 156 . The FFMRF is a one‐page rating form that can be completed as a self‐report measure or as a clinician assessment tool.
There is only one instrument for the assessment of the DSM‐5 trait model: the Personality Inventory for DSM‐5 (PID‐5) 157 , freely available online from the American Psychiatric Association. The Personality Inventory for ICD‐11 (PiCD) 158 was developed to assess the ICD‐11 trait model. The PID‐5 can also be used to assess the ICD‐11 trait model, but its coverage for anankastia is more limited than in the PiCD.
There are also many alternative measures of the personality disorder syndromes. The most commonly used is the freely available Personality Diagnostic Questionnaire‐4 (PDQ‐4) 159 , consisting of 99 items. Other possible measures have potential limitations, such as being relatively expensive, lengthy and/or lacking in full coverage.
One of the most well‐recognized problems in the self‐report assessment of personality is the potential impact of clinical depression on a person's self‐image and self‐description 160 . Persons will provide inordinately negative self‐descriptions when they are clinically depressed. Clinicians should focus their interview assessment of personality on the patient's life prior to the onset of the depression.
ANTECEDENT AND CONCOMITANT PSYCHIATRIC CONDITIONS
While there are multiple antecedent psychiatric conditions over‐represented in persons with depression, the list is somewhat elastic depending on source material.
A representative study 161 reported that adult depression was increased in those who had had anxiety conditions (i.e., generalized anxiety, separation anxiety), disruptive states (e.g., conduct disorder, oppositional defiant disorder) and substance‐related disorders in childhood or adolescence. Such narrow lists most commonly reflect a limited set of candidate conditions being studied by the researchers.
In contrast, the DSM‐5 7 states that “essentially all major nonmood disorders increase the risk of an individual developing depression”, before noting that “substance use, anxiety, and borderline personality disorder are among the most common of these”. The manual also points out that depression developing against the background of another mental disorder often follows a more refractory course.
The number of antecedent conditions is also likely to be related to how depression is defined, in that there may be a small set of antecedent conditions experienced by those who develop melancholic depression and a broad set if depression is defined at a low threshold of severity.
Multiple mechanisms for such associations can be postulated and should be contemplated, as they have the potential to shape management models. First, the conditions may have independent status. Second, having a psychiatric condition can be depressogenic per se. Third, those with “acting‐out” conditions (e.g., conduct disorder) or who have substance use conditions are more likely to be expelled from school, lose their job or experience divorce, with such secondary social factors being depressogenic. Fourth, some antecedent conditions may operate via a biological conduit (for example, alcohol excess and some illicit drugs can be distinctly depressogenic). Fifth, a “staging model” may be operative, in which the clinical phenotype is linked to the extent of disease progression. For instance, there may be a prodromal phase in the development of depression, marked by “increased aggression and augmented anxiety” 131 .
Turning to concomitant conditions (and it is perhaps important to note that “comorbid” strictly means coterminous and excludes antecedent conditions), virtually all psychiatric disorders can be associated with depression. The most common ones are anxiety states, with patients reporting the onset of, or an increase in, generalized anxiety, panic attacks or social anxiety during depressive episodes, and with such conditions generally returning to their premorbid status when recovery from depression occurs.
In terms of mechanisms, concomitant psychiatric states may again reflect chance, or the pathoplastic impact of a stressor (e.g., a traumatic event might cause depression, a set of anxiety disorders including post‐traumatic stress disorder, and illicit substance use). Furthermore, the concomitant presentation may reflect a common genetic determinant providing a pleiotropic risk. A high genetic correlation between anxiety and major depression has been indeed documented 162 , although those two might be conjoined by genetically determined neuroticism.
In terms of tools for diagnostic assistance and clarification, the SCID‐5 60 provides a guidance to the clinician, but its administration takes about 90 min and requires considerable training. Thus, clinicians are more likely to rely on taking a comprehensive clinical history from patients (and optimally from relatives as corroborative witnesses) to determine what conditions have diagnostic status, and their onset, ranking and current standing.
The DSM‐5 has a patient‐ or informant‐rating “cross‐cutting” symptom measure, best viewed as a screening measure for potential more detailed inquiries. While principally designed to assess symptoms in the two previous weeks and prospectively, its 12 probe questions for adults capture several salient domains (i.e., anxiety, psychosis, obsessive‐compulsive disorder, personality functioning, and substance use), so allowing retrospective applicability 7 .
The PDSQ 61 is a screening instrument covering multiple psychiatric disorders, including mood, anxiety, substance abuse, eating and somatoform disorders. Tools focusing on specific disorders, to be used when their presence is suspected, are the Generalized Anxiety Disorder 7‐item scale (GAD‐7) 163 , the Penn State Worry Questionnaire 164 , the Liebowitz Social Anxiety Scale 165 , the Yale‐Brown Obsessive‐Compulsive Scale (Y‐BOCS) 166 , the PID‐5 157 , the Posttraumatic Stress Diagnostic Scale (PDS) 167 , the Conners Adult ADHD Rating Scales (CAARS) 168 , the Alcohol Use Disorders Identification Test (AUDIT) 169 , and the Drug Abuse Screening Test (DAST‐10) 170 .
In persons with depression, identifying other conditions should help shaping management. If the two conditions are judged to be independent, then both are likely to require condition‐specific treatments. If interdependent, five principal models come into play.
First, a sequential model. For example, for a patient with depression and a borderline personality disorder, stabilizing the depression might be the initial priority before addressing the other condition.
Second, a hierarchically‐weighted model. A single treatment may address a higher‐order factor and thus ameliorate downstream concomitant conditions. For example, an SSRI and/or cognitive behavioral therapy may be of benefit for comorbid states of depression and anxiety, or depression and obsessive‐compulsive disorder.
Third, a severity‐weighted model. Treatment of a primary depressive episode might correct any secondary conditions or consequences. For example, if anxiety has emerged only with onset of a severe melancholic depressive episode, then treating the primary state is the optimal model, with the hypothesis being that, on its recovery, there will be no residual anxiety requiring treatment or, if present, it will become more responsive to treatment.
Four, a “motivational bypass” model. For example, an individual with an acting‐out personality style leading to brief explosive depressive states may have no motivation to attend psychotherapy or to take medication (which, moreover, may involve a risk for overdose), but be prepared to engage in an anger management program.
Fifth, a risk management model. For example, if an individual with depression has a primary conduct disorder and/or is under the influence of an illicit substance, then hospitalization and other salient strategies for ensuring the patient's and/or relatives' safety may be the immediate priority.
The reality of depression being associated with multiple antecedent and concomitant conditions challenges the clinician to contemplate a range of causal and treatment models, and to avoid seeking a parsimonious single diagnosis.
The scientific data base informs us about candidate conditions, but their detection relies on diagnostic skills and tools, while management invokes the therapeutic “art” of determining the relevant explanatory model and then providing a management model that “fits” with the putative linking mechanisms.
PHYSICAL COMORBIDITIES
Compelling evidence indicates that the depressive syndrome is highly associated with physical comorbidities, particularly cardiometabolic diseases 171 . A variety of factors, including unhealthy lifestyles and the use of antidepressants, increase the risk of physical complications/disorders in people with this condition 172 . In clinical practice, however, such comorbidities are routinely overlooked 173 .
The poor clinical management of these comorbidities drastically reduces life expectancy, and increases the personal, social and economic burden of depression across the lifespan 174 . Improving the management of physical health conditions in people with depression, with the aim of decreasing morbidity and premature mortality, is therefore essential.
Approximately one third of people with a diagnosis of depression has metabolic syndrome 175 , characterized by the simultaneous occurrence of several metabolic abnormalities (abdominal obesity, glucose intolerance or insulin resistance, dyslipidemia and hypertension). Meta‐analytic data show that, compared with the general population, people with depression have a 1.6 times higher risk of developing this syndrome 175 .
As the individual components of metabolic syndrome are critical in predicting the morbidity and mortality of cardiovascular disease, type 2 diabetes mellitus, cancer and other related diseases, they should be checked at baseline and measured regularly thereafter 176 .
Clinicians should monitor the weight of every patient at every visit. However, assessment of central/abdominal adiposity, by measuring waist circumference, has a stronger correlation with insulin resistance and better predicts future type 2 diabetes mellitus and cardiovascular diseases than total body weight or body mass index. This assessment can easily be done with a simple and inexpensive waist tape measure.
As the cost for measuring is low and hypertension is a risk factor for cardiovascular disease, blood pressure ought to be assessed routinely with an inflatable or digital blood pressure cuff. A checklist for accurate measurement is provided by the American College of Cardiology/American Heart Association (ACC/AHA) 177 . Importantly, at least two separate, independent measurements are required for the diagnosis of elevated blood pressure/hypertension. Moreover, the ACC/AHA guidelines recommend out‐of‐office measurements to confirm this diagnosis 177 .
Finger prick tests should be carried out to capture early cases of hyperglycemia at baseline and after three months, and then at least yearly. Ideally, blood glucose measurement should be conducted in the fasting state, because this is the most sensitive measurement for the detection of developing glucose abnormalities.
Lipid parameters, especially triglycerides and high density lipoprotein (HDL)‐cholesterol, should also be assessed at baseline and at 3 months, with 12‐monthly assessments thereafter. More frequent screening is unnecessary, unless in case of abnormal values. Fasting is not routinely required for the determination of a lipid profile.
The diagnosis of depression is a risk factor for cardiovascular disease 178 . According to a large‐scale meta‐analysis, depression increases the risk for coronary heart disease by 1.6‐2.5 times 179 . Identifying and managing modifiable cardiovascular risk factors in people with depression – such as smoking, an unhealthy diet, obesity, sedentary lifestyle, alcohol consumption, hypertension, diabetes mellitus, and dyslipidemia – will reduce their risk for premature morbidity/mortality180, 181.
People with depression are more likely to smoke and have significantly poorer diet quality than the general population. Around 60‐70% of them do not meet physical activity guidelines and are sedentary for 8.5 hours or more per day. Around 30% have or have had alcohol use disorder 173 .
Patients with high risk for cardiovascular disease can be identified by one of several “cardiovascular risk calculators”, including the WHO cardiovascular risk prediction charts, the Joint British Societies risk calculator (JBS3), and the Framingham risk score (FRS‐CVD), some of which are available online182, 183, 184. The WHO risk prediction charts, for example, quantify the 10‐year risk of a fatal or non‐fatal major cardiovascular event (i.e., myocardial infarction or stroke), according to age, gender, blood pressure, smoking status, total cholesterol and presence or absence of diabetes mellitus 183 . The value of such prediction is to help communicate risk, so that patients can receive advice (and treatment if necessary) appropriate to their risk level.
Depression is also a well‐acknowledged risk factor for diabetes mellitus 185 . Meta‐analytic data have found that the risk for type 2 diabetes mellitus is 1.5 times higher in people with a depressive syndrome, compared to the general population 185 . Clinicians who provide care to people with depression should understand the clinical features of diabetes mellitus and be able to identify potential life‐threatening episodes. The clinician should check whether patients have significant risk factors (family history, body mass index ≥25, waist circumference above critical values).
Physical comorbidities of depression have important implications for the formulation of the management plan. Patients should be taught about healthy lifestyles and receive psycho‐educational packages (e.g., nutrition education) and support (e.g., dietary support) to facilitate them. Training on smoking cessation is now freely available online (e.g., the e‐learning tool from the National Centre for Smoking Cessation and Training) 186 . Patients should be advised to engage in at least 30 min of moderately vigorous activity on most days of the week. The importance of consuming healthy food, such as fresh fruit and vegetables, fish, and lean meats in a balanced way, should be stressed by clinicians whenever possible 187 .
If lifestyle interventions do not succeed, medication may be indicated. First‐line pharmacological therapy for type 2 diabetes mellitus or pre‐diabetes is metformin monotherapy. For the pharmacological management of hypertension, any of the following medication classes can be used as first‐line treatment: thiazide diuretics, long‐acting calcium‐channel blockers, angiotensin‐converting enzyme inhibitors, and angiotensin II receptor antagonists. Statin therapy should be offered for primary prevention of cardiovascular disease if the 10‐year risk of developing cardiovascular disease is ≥10% 173 . In cases where physical comorbidities, such as hyperglycemia or hyperlipidemia, are secondary to antidepressant medication, dose reduction or switching to an antidepressant with a lower risk profile should be considered, if safe and feasible.
Preventing physical comorbidities of depression is a more efficient strategy than attempting to reverse them once they have developed 188 . The Diabetes Prevention Program is an example of a gold‐standard lifestyle intervention with a key focus on prevention 189 . Emerging evidence indicates that mHealth, i.e. the use of digital technology (such as smartphone apps and fitness trackers) in health care delivery, can play an important role in preventing those comorbidities. A comprehensive lifestyle assessment would inform patients of specific lifestyle changes they could make to protect their physical health. Unfortunately, no suitable digital tools are as yet available for clinicians to comprehensively assess lifestyle factors (e.g., exercise, diet, sleep) all at once 190 .
In summary, clinicians have a duty today to ensure that patients with depression are adequately evaluated with respect to their physical health, and are given access to evidence‐based lifestyle interventions from the start of treatment.
FAMILY HISTORY
Assessing the family history in a patient with depression can assist in refining the diagnosis and identifying management priorities, and it may have utility in clarifying possible comorbid conditions. It can also be of importance to some patients in advancing understanding of their condition.
A meta‐analysis of six twin studies quantified heritability of DSM‐defined major depression at 37%, with an apparently higher rate in women than men 191 . However, DSM‐defined major depression is likely to be a heterogeneous diagnosis, subsuming quite different depressive conditions, presumably with varying degrees of genetic contribution – including perhaps none. A higher concordance rate for DSM‐defined major depression has been reported in melancholic than in non‐melancholic co‐twins, with the risk for major depression in the melancholic subset also being higher in monozygotic than in dizygotic twins 192 .
Obtaining a family history of depression and/or bipolar disorder may weigh the likelihood of a melancholic condition in a patient with a diagnosis of depression (and may thus prioritize the use of antidepressant medications, in particular broad‐action ones). Any such probability is further advanced if a family member is reported as having been hospitalized or committed suicide, or if a relative received (and, especially, benefitted from) electroconvulsive therapy.
For patients with a unipolar melancholic pattern, a family history of bipolar disorder does not by itself argue for diagnostic revision (to bipolar status). Any history of a relative receiving an antidepressant medication is of limited utility in refining the depressive subtype, in light of the wide use of these drugs across quite varying depressive (and other) conditions in recent times.
In depressed patients with prominent comorbid anxiety, a family history of anxiety or of relatives being distinct “worriers” (and no distinct family history of depression) may weigh a diagnosis of a non‐melancholic depression and implicate anxiety as a highly likely predisposing factor. In such scenarios, management options include a sequential approach (i.e., treat the depression and then address the predisposing anxiety) or a transdiagnostic treatment model (e.g., prescribe an SSRI and/or initiate cognitive behavioral therapy) to address both conditions concurrently.
In depressed patients with certain hereditary‐weighted comorbid conditions (e.g., attention‐deficit/hyperactivity disorder, conduct disorder), the diagnostic probability of such disorders is advanced if there is a family history.
If a family history of a mood disorder is identified, then establishing medications that have been of benefit for a relative would appear theoretically useful in determining treatment choice for the patient. However, at the clinical level, such information does not seem to provide a distinct specificity “signal”, and there are only few studies documenting a high concordance of antidepressant response in members of the same family 193 . However, a family history of depression and/or bipolar disorder has been consistently shown to indicate a greater likelihood of responding to lithium augmentation in those with treatment‐resistant depression 194 .
Pursuing a family history is initially best addressed by seeking such information from the patient, but a false negative report is not uncommon as a consequence of the family “hiding” such information from the patient, most commonly reflecting stigma or cultural factors.
While a corroborative witness interview with one or more family members is generally wise for any initial assessment, it can be particularly important in such cases. One remains struck by the high frequency of a family member nominating a relative who was hospitalized for depression or committed suicide, or who even nominates himself/herself as having depression, when the patient has failed to report any family history.
Some instruments for the assessment of family history in patients with depression have been used for research purposes, such as the Diagnostic Interview for Genetic Studies 195 and the Family Informant Schedule and Criteria 196 , but they take several hours to complete for an average sized family. Brief screening instruments have also been proposed, such as the Family History Screen (FHS) 197 , which could be suitable for use in clinical settings. This screen is administered to a family informant, who reports about himself/herself and other biological relatives (parents, siblings and offspring). It takes about 5 to 20 min to administer, as each question is posed only once about all family members as a group.
The patient's concern about any role of genetic factors in contributing to his/her depressive condition allows a potentially therapeutic dialogue. For those with melancholia, information that its cause is likely to reflect genetic “hard wiring” (akin to developing a genetically determined physical disease such a type 1 diabetes) is often reassuring if they have previously judged their condition as reflecting a personality limitation, as well as advancing adherence to medication. For patients with a non‐melancholic depression, dialogue about genetic “causes” may concede weaker direct and even indirect genetic links (e.g., a family history of anxiety predisposing them to increased anxiety and, in turn, to depression) or may allow the clinician to formulate the greater salience of psychosocial as against genetic factors. Some patients are intrigued by studies demonstrating gene‐environment interactions, with such data allowing the clinician to inform them that depression should not be viewed as necessarily “all environmental” or “all genetic”.
Overall, a comprehensive family history can assist diagnostic clarification and so lead to prioritized management modalities. While gathering such background information, the clinician is also afforded the opportunity to become aware of and moderate any concerns from the patient of “passing on” his/her mood disorder and so strengthen the therapeutic alliance.
EARLY ENVIRONMENTAL EXPOSURES
There is a consistent and growing evidence base supporting an association between early childhood adversity and subsequent depression. A systematic review 198 , focusing on prospective cohort studies, calculated a pooled odds ratio between maltreatment in childhood and depression of 2.03, with population attributable fractions indicating that over one‐half of global depression cases are potentially attributable to self‐reported child‐hood maltreatment.
Specific questions continue to be explored, including associations of different types of early adversity with depression, causal mediators between early adversity and subsequent depression, and associations of early adversity with different features of depression 199 .
Early life adversity includes exposures to either abuse (sexual, physical or emotional) or neglect (physical or emotional). Emotional abuse and neglect may be particularly strongly associated with depression200, 201. Other parental factors, such as less warmth or over‐involvement, that are associated with depression in young people, may be more subtle 202 .
Timing of adversity may also be important, with increased vulnerability during particular developmental phases, although further work is needed to delineate such windows more precisely 203 .
Causal mediators between early adversity and subsequent depression involve gene‐environment interaction, and may lead to neurobiological changes (e.g., alterations in brain structures and connectivity, in neuroendocrine systems, and in inflammatory pathways) and cognitive‐affective changes (e.g., hypervigilance to threat, emotional dysregulation, low responsivity to reward) 204 . Causal mechanisms may differ across threat‐related and deprivation‐related adversity 205 . Importantly, some predictors of depression after childhood maltreatment, e.g., interpersonal relationships, may be modifiable 206 .
Early adversity has been associated with risk for depression onset, maintenance and recurrence. In addition, it has been related to an increased comorbidity of depression with other mental disorders, increased suicidality, and greater treatment refractoriness 199 . Population‐attributable risk proportions suggest that eradication of childhood adversities would lead to a 22.9% reduction in mood disorders, with a higher reduction in early onset than in later depression 207 .
Given this literature, assessing the history of childhood adversity is a crucial component of the comprehensive characterization of a patient with depression. However, a number of key issues must be kept in mind. First, reports of adversity are necessarily subjective, and there is the possibility of recall bias. Second, it is important to explore not only the events that occurred, but also key aspects of the subjective experience and meaning assigned. Third, personality and sociocultural background may influence both the experience and reporting of early adversity. Obtaining a history of childhood adversity that also includes a focus on coping and resilience may be useful in helping to address these issues.
The Childhood Experience of Care and Abuse (CECA) is a comprehensive interview measure for the assessment of childhood adversity 208 . Although it allows for detailed collection of information, it is time‐consuming to administer and requires interviewer training. Moreover, information on its clinical utility is limited.
Several shorter self‐report questionnaires have been used in research settings, and can be considered in clinical practice. These include a shorter self‐report questionnaire based on the CECA (CECA.Q) 209 , and the Childhood Trauma Questionnaire 210 . The short form of the Childhood Trauma Questionnaire has 28 items, assessing five domains of childhood adversity: emotional neglect, physical neglect, emotional abuse, physical abuse, and sexual abuse.
A number of measures are also available to assess the parenting patterns of early caregivers. The Young Parenting Inventory (YPI) has been used in schema therapy, and provides a useful way of assessing early parenting styles, and how these might be related to an individual's early maladaptive schemas 211 . The inventory has 72 items that retrospectively assess perceived parenting experiences in respect of each key caregiver. This measure is designed to be used in conjunction with the Young Schema Questionnaire (YSQ) 212 , which assesses 18 early maladaptive schemas.
The presence of early adversity may impact on treatment planning for depression in a number of ways. First, the presence of early adversity may be associated with premature treatment termination 213 , perhaps because of a weaker therapeutic alliance. This association may be present across psychotherapies; any particular therapy would therefore need to consider how best to address this issue, in accordance with its own theoretical framework.
Second, specific evidence‐based psychotherapies developed for patients with childhood adversity, such as trauma‐focused treatment for depression, can be considered in order to ensure more specific targeting of the impact of such adversity. However, such interventions have been developed only recently, and the evidence base for their efficacy remains preliminary 214 .
Third, the presence of early adversity may be associated with a decreased response to both pharmacotherapy and psychotherapy 215 . This does not impact choice of treatment per se, but rather indicates the need for robust management. Indeed, many patients with depression and early adversity respond well to pharmacotherapy and/or psychotherapy over time, and it is therefore key to encourage patients to stay in treatment216, 217.
RECENT ENVIRONMENTAL EXPOSURES
Environmental stressors can play a role in precipitating depression. The literature on this association has benefited from increasingly sophisticated study designs 218 , and has included work on a range of stressors, studies of stress appraisal, research on vulnerable populations, and gene‐environment interaction studies.
Stressors associated with depression include major life events (e.g., serious physical disease, natural disasters, intimate partner violence), chronic stressors (e.g., community violence, job insecurity, racial discrimination), and daily hassles. Other environmental factors reported to be associated with depression include negative aspects of the work environment 219 , increased social media and screen time220, 221, unfavorable living environments 222 , increased air and noise pollution223, 224, and higher ambient temperatures 225 .
Individual response to stressors differs, in part due to differences in stress appraisal. Causal factors relevant to stress appraisal are genetic as well as environmental (e.g., previous exposure to stressors). The relevance of stressors differs across the lifespan, in part due to what is considered most stressful at a particular developmental stage226, 227.
Populations with higher vulnerability to stressors include patients in long‐term care 228 , caregivers, postpartum women229, 230, individuals with a housing disadvantage 231 , immigrants and refugees 232 ; lesbian, gay, bisexual and transgender people; and other stigmatized individuals 233 . Among caregivers at particularly high risk are those taking care of children with intellectual and developmental disabilities, or family members with dementia 234 .
History of environmental exposures is therefore a crucial component of a comprehensive assessment in persons with depression, particularly those from vulnerable groups. Semi‐structured interview measures such as the Life Event and Difficulty Schedule (LEDS) 235 are mostly used in research settings. They involve questions to assess objective aspects of the severity of life events and chronic stressors, as well as the person's subjective experience of how threatening or disruptive they were.
A range of self‐rated checklist measures for assessing life events and chronic stressors may be suitable for use in clinical practice. These include the Psychiatric Epidemiology Research Interview (PERI) Life Events Scale (PERI‐LES) 236 , the List of Threatening Experiences (LTE) 237 , and the Questionnaire of Stressful Life Events (QSLE) 238 , each of which has been carefully validated by psychometric research.
The PERI‐LES lists 102 events, and has been widely used in epidemiological research. The LTE was specifically developed in order to be shorter; it assesses 12 recent life events that are associated with long‐term threat. The QSLE was developed to cover the lifespan; it assesses 18 life events that occur during childhood, adolescence and adulthood, noting the age at which they occurred and their impact. Thus, it may be a helpful clinical adjunct. Additional work to assess the clinical utility of such measures is warranted.
Targeted clinical questions regarding aspects of the work and neighborhood environment, including social media and screen time, may be useful as part of the clinical interview. There is also ongoing attention to the use of ecological momentary assessment to measure daily life stressors and responses. Although these are typically restricted to research settings, a range of apps can now be used by clinicians and patients to collect such information239, 240.
Mobile technologies have potential advantages over traditional diaries in several respects, including automating the process, allowing a more engaging experience, and providing real‐time feedback to patients and clinicians 241 . In research settings, self‐reports from ecological momentary assessment can be integrated with data from both embedded sensors and wearable biosensors. Few clinical studies have, however, focused on these technologies, and further work is needed to mould research approaches for clinical purposes239, 240.
A comprehensive clinical interview in a patient with depression should include a careful assessment of the patient's family and social networks, and the quality of relationships. The use of an interpersonal inventory is a key strategy in interpersonal therapy, but may be useful in ordinary clinical practice as well. The original Inventory of Interpersonal Problems comprised 127 items, but a number of shorter (e.g., 32‐item) versions are now available, and may be helpful in assessing interpersonal behaviors 242 .
The presence of environmental stressors may impact on treatment planning of depression in a number of ways. First, occurrence and perception of ongoing chronic stressors and daily hassles will inform the therapeutic work. In interpersonal therapy, the presence of interpersonal stressors is specifically targeted. In cognitive behavioral therapy, it may be noted that stressors and hassles trigger particular schemas or thoughts, which in turn lead to maladaptive emotions.
Second, for major stressors, trauma‐focused treatment for depression may be considered 214 . Depression, like post‐traumatic stress disorder, may be marked by intrusive and distressing memories of traumatic events, and these can then be targeted by trauma‐focused interventions. However, such interventions have been developed only recently, and the evidence base for their efficacy remains preliminary.
Third, while a relationship between severe and enduring environmental stressors and less robust responses to pharmacotherapy and psychotherapy may be hypothesized, many patients with depression and environmental stressors do respond well to pharmacotherapy and/or psychotherapy over time. The presence of ongoing severe environmental stressors does not impact choice of treatment, but rather highlights the need for rigorous management that includes a clear focus on addressing such stressors.
PROTECTIVE FACTORS/RESILIENCE
There is a growing body of work on factors that protect against the onset or continuation of depression. This work includes development of theoretical frameworks for conceptualizing different kinds of protective factors, exploration of causal pathways and mechanisms that mediate increased resilience, and investigation of protective factors and resilience in particularly vulnerable populations.
Protective factors against depression range from those involving the individual and his/her family to those pertaining to the larger community. They include being employed 243 , using positive coping strategies 244 , having closer family relationships 245 , residing where one's own ethnic density is higher 246 , and having more social interactions 247 .
Work on causal pathways and processes underlying resilience against depression is at a surprisingly early stage. Investigation of genetic and environmental factors is needed to delineate these pathways, which may involve specific cognitive‐affective processes, neuronal circuitry and molecular mechanisms. Some findings have clear clinical relevance: for example, work on mechanisms underlying the protective impact of healthy diet and weight218, 248, reduced substance use 249 , increased cardio‐respiratory fitness 250 , and positive work and living environment219, 222.
Importantly, there is a growing literature on the supports and “uplifts” associated with well‐being in particularly vulnerable populations, such as postpartum women 251 , caregivers 229 , and lesbian, gay, bisexual and transgender people 252 .
A comprehensive clinical interview in a patient with depression should include a history of protective factors and resilience against stressors. Nesse 253 has used the acronym SOCIAL to refer to key protective factors that should be addressed in such a history: Social resources, including friends, groups and social influence; Occupation, whether paid work or other social roles; Children and family, including relatives; Income and sources of material resources; Abilities, appearance, health, time, and other personal resources; and Love and sex in an intimate relationship.
For each of these resources, several follow‐up questions may help the clinician to understand the person and his/her resources better. Thus, for example, are there secure ways to get sufficient amounts of this resource, how important is this resource to you, is there a gap between what you want and what you have, and what are the main things you are trying to do, get, or prevent in this area?
A number of self‐report measures of resilience have been developed for use in research settings 254 . The Connor‐Davidson Resilience Scale 255 may be of particular interest to clinicians, because it appears sensitive to change during treatment. A 10‐item version of this scale has been studied in a range of populations; these items reflect the ability to tolerate experiences such as change or personal problems 256 . The Brief Resilience Scale 257 is focused on the ability to bounce back from the stressors of life; it is a 6‐item scale that again could be considered for clinical use.
Self‐report measures of perceptions of social support, such as the Multidimensional Scale of Perceived Social Support (MSPSS) 258 , and perceptions of social rank, such as the McArthur Subjective Social Status Scale (MSSSS) 259 , may also be useful for assessing protective factors, although further work on clinical utility is needed. The MSPSS is a 12‐item self‐report measure of subjectively assessed social support from family, friends and significant others. The MSSSS is a two‐item visual scale of subjectively assessed social rank. The instrument comprises a drawing of two ladders on which people place themselves; the first assesses placement in society and the second evaluates placement in community.
Knowledge about protective factors may impact on the management plan for depression. Where protective factors are present, their maintenance can be encouraged, and conversely, where modifiable protective factors are absent, addressing this may be part of treatment targeting. There is, for example, a growing evidence base on the value of a healthy diet and of exercise in the management of depression 260 .
Treatments of depression that include a focus on enhancing resilience can be considered261, 262, 263. There is an increasing evidence base, for instance, on the value of mindfulness‐based cognitive therapy (MBCT) and acceptance and commitment therapy (ACT) in the management of depression, although further work is needed to determine which patients might benefit most from these therapies264, 265, 266.
DYSFUNCTIONAL COGNITIVE SCHEMAS
Depressed patients tend to have dysfunctional cognitive schemas characterized by themes of loss, failure, worthlessness and rejection, which lead to negative perceptions of themselves, the world and the future (the cognitive triad) and to negative information‐processing biases267, 268.
The formulation of dysfunctional cognitive schemas has paved the ground for the development of cognitive therapy 268 and subsequent psychotherapeutic refinements subsumed under the rubric of cognitive behavioral strategies 269 . Cognitive restructuring is a central part of this approach: schemas can be modified in the course of psychotherapy to achieve a functional role268, 269.
In addition to a life history interview and the use of a diary, inventories are available to identify dysfunctional cognitive schemas 269 . Both detailed questionnaires, such as the Dysfunctional Attitude Scale 270 , and brief checklists, such as the Schema Inventory 269 , have been developed and validated.
In people with depression, cognitive negative biases are frequently associated with impaired ability to use past memories to mitigate current mood states 271 . Attention has been drawn on cognitive schemas that in depression hinder balanced levels of psychological well‐being (i.e., environmental mastery, personal growth, purpose in life, autonomy, self‐acceptance, and positive relations with others) 272 . A widely used and validated self‐rating inventory, the Psychological Well‐Being Scales 273 , is geared to detecting such impairments.
Specific instruments for assessing euthymia (the presence of positive affects and psychological well‐being, i.e., balance and integration of psychic forces, a unifying outlook on life which guides actions and feelings, and resistance to stress) are also available272, 274. They include a brief self‐rating scale (the Euthymia Scale) and a Clinical Interview for Euthymia272, 274.
It is a common assumption that assessment of dysfunctional cognitive schemas in depression is only relevant to the performance of cognitive behavioral therapies 269 or well‐being enhancing psychotherapeutic strategies 272 . There is evidence to call such views in question.
In the setting of a depressive episode, exploration of cognitive biases may provide incremental information on challenging clinical issues such as suicidal ideation and mental pain267, 275, 276, and the weight of stressful environmental circumstances 277 . For instance, severe hopelessness and lack of purpose in life may increase suicidal risk267, 275. A patient who displays good symptom control with pharmacotherapy, but is exposed to major life events and has dysfunctional cognitive schemas, may be in need of additional psychotherapy.
Prospective studies have shown that more negatively biased self‐referential processing is associated with a worse clinical course 271 . Conversely, the presence of unaffected areas of psychological well‐being may predict a more favorable course 278 .
The importance of assessing dysfunctional cognitive schemas increases when patients have achieved improvement of their symptomatology with pharmacotherapy and/or psychotherapy. Negative schemas may remain present, even though at a latent level, after remission from a depressive episode 267 , and trigger negative automatic thoughts when they are activated by life events, leading to recurrences of illness.
Dysfunctional cognitive schemas have been reported to be pre‐dictive of the onset of a new depressive episode 279 . During the stage of remission, their assessment may suggest the use of cognitive behavioral therapies and/or well‐being enhancing psychotherapeutic strategies to improve residual symptomatology and thus long‐term outcome in depression 135 .
Furthermore, dysfunctional cognitive schemas (e.g., “no matter what I do, it will not work”, “I must always be in control”) are likely to affect individual attitudes to medication 280 . If a patient has problems with adherence to antidepressant drugs, this is a clinical area that is worth exploring. The Drug Attitude Inventory is a brief questionnaire 280 that may facilitate such exploration.
In summary, assessment of dysfunctional cognitive schemas during the acute manifestations of depressive disorder, and particularly after remission, may demarcate major differences relevant to prognosis and treatment among patients who otherwise seem to be deceptively similar since they share the same diagnosis.
DISCUSSION
This paper provides a systematic description of the salient domains that should be considered in the currently ongoing effort to personalize the management of depression. The assessment instruments that have been developed for the evaluation of these domains are reviewed, with a special attention to their suitability for use in routine clinical practice. The preliminary research evidence on the relevance of each domain to treatment decisions is summarized, and the main unmet needs that have to be addressed by further studies are emphasized. Where the available evidence provides indications about how the management of depression can already be personalized to some extent in the current situation of uncertainty, these indications are highlighted.
The aims of this endeavor are: a) to reinforce the currently re‐emerging interest in the personalization of the management of depression; b) to help in the identification of the variables to be considered when developing machine learning approaches or other complex prediction models in this area; c) to help in the selection of simple, preferentially self‐report assessment instruments that can be included in comprehensive questionnaires or batteries of measures to be tested in large observational studies; d) to support clinicians in their attempts to personalize treatment of depression even today, in the absence of standardized decision tools validated by research.
One could argue that most clinicians are aware that depression is a heterogeneous syndrome, and that some of them have developed their own criteria for the selection of the optimal antidepressant and/or psychotherapy in the individual patient. These criteria are usually based on their personal experience, their interaction with experienced colleagues, or papers or meeting presentations focusing on the mechanisms of action of antidepressants, which often represent a guidance for clinical decision‐making beyond the evidence provided by clinical trials 281 . So, the majority of clinicians are likely to welcome the ongoing effort to make the characterization of the individual patient who has received a diagnosis of depression more systematic. This will more probably happen if different levels and modalities of characterization are envisaged, taking into account different real‐world scenarios in terms of available resources, sociocultural context (including the needs of special populations such as ethnic minorities), organization of the health care system, and clinical traditions.
It is true that many clinicians do not like using formal assessment instruments in their ordinary practice, and that even formal diagnostic systems are not routinely used in clinical settings. However, our experience with the DSM‐III and its successors is very telling in this respect. Although these diagnostic manuals are not frequently used in routine practice, several elements of their description of individual mental disorders have actually been incorporated by most clinicians in their personal prototypes of these disorders, which has arguably made the reliability of psychiatric diagnosis, although far from optimal, certainly better than it was in the 1970s. Something similar may happen if decision support tools are developed for the personalization of management of depression and other psychiatric conditions: although these tools may be formally used only by a minority of clinicians, several of their elements may be incorporated by most clinicians in their characterization of individual patients, making this characterization more reliable and useful than it is today.
Regulatory agencies have encouraged in recent decades the documentation of the “equivalence” of any newly developed anti‐depressant medication to an already consolidated one, implicitly discouraging the search for the “differences” between those medications and consequently the pursuit of a matching between the characteristics of the individual depressed patients and the individual available interventions. Not surprisingly, in clinical trials, the characterization of the recruited depressed patients is often somewhat coarse, mostly limited to the administration of a depression rating scale. Comparisons between antidepressant medication and psychotherapies, and between different psychotherapeutic techniques, have suffered from the same limitation, thus generating a research evidence which seems to suggest that almost all treatments for depression, being “equivalent”, are interchangeable with each other. However, even in the presence of such a limited information from clinical trials, recent secondary analyses of available databases are documenting that there may indeed be clinical variables associated with the response to different antidepressant drugs, and or to antidepressant medication vs. specific psychotherapies11, 12. The present paper aims to encourage and support these developments, which clearly require large patient samples (i.e., pooling the results of different studies using the same assessment instruments) and the use of innovative strategies of data analysis.
Our review also indicates that the management of patients with a diagnosis of depression can be personalized even today, in several respects, beyond the choice of a given antidepressant medication or psychotherapy. Several sections of the paper, such as those on neurocognition and on physical comorbidities, highlight that the modern management of depression is becoming increasingly complex, and that some of its components may already be reliably personalized in routine clinical practice on the basis of the available research evidence.
We would like to emphasize once again that the focus of this paper on clinical variables does not mean that we are undervaluing the currently ongoing effort to identify biological markers that may help in the personalization of treatment of depression. There may be different views about the current status of this line of research, but we think that no biological marker is as yet ready for use in routine clinical practice. On the other hand, we do believe that a more precise clinical characterization of depressed patients, beyond the syndromal diagnosis, may significantly support the development of those markers, as well as the identification of more homogeneous subtypes of depression.
The endeavor reflected in this paper is obviously a work in progress. We welcome comments and additions from the field that may be considered in a future update of this publication.
ACKNOWLEDGEMENTS
Joshua R. Oltmanns (University of Kentucky, Lexington, KY, USA) contributed to the section on personality traits. Johan Detraux and Davy Vancampfort (University Psychiatric Centre KU Leuven, Kortenberg, Belgium) contributed to the section on physical comorbidities.
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