Background
Major Depressive disorder (MDD) is one of the most prevalent mental disorders. With at least 350 million people suffering from this disorder worldwide, it is considered the leading cause of disability, in terms of total years lost due to disability [
1]. Cost-of-illness (COI) studies demonstrate a substantial increase of direct (i.e., medical and non-medical costs) and indirect costs (i.e., due to productivity losses and premature death) caused by depression, leading to a high economic burden for all nations [
2].
According to the WHO mhGAP Intervention Guide [
3], health care for depression preferably consists of a combination of basic psychosocial support with antidepressant medication or psychotherapy, including cognitive behavioral therapy (CBT), interpersonal psychotherapy (IPT) or problem-solving treatment. Although psychopharmalogical and psychotherapeutic interventions are both considered effective in the treatment of MDD (e.g., [
4]), less than half of the patients show response and remission to psychotherapy [
5] and the majority of patients fail to show remission after a first treatment with standard antidepressant medication [
6,
7]. Moreover, depression is characterized by high recurrence rates [
8], with up to 85 % of the recovered patients experiencing a new episode during 15 years follow-up (for a prospective study, see [
9]), and a substantial increase in risk of recurrence with each successive episode [
10].
These rather low response and remission rates, as well as the highly recurrent nature of the disorder indicate, that the underlying factors maintaining depression and predisposing individuals to repeatedly develop new episodes, are not very well understood, yet. In the past years, depression research has therefore extensively focused on the identification of potential vulnerability factors for this disorder [
8,
11]. One such cognitive vulnerability factor is a bias in the attentional processing of emotional information [
12,
13]. Cognitive theories of depression [
14,
15] postulate that information processing in depression is guided by negative schemata, which results in a selective attention for negative, schema-congruent stimuli in the environment. This so-called negative attentional bias is assumed to contribute to both development and maintenance of the disorder.
Indeed, a substantial amount of studies support that, compared to healthy individuals, the depressed show heightened attention for negative compared to positive or neutral information (for a meta-analysis, see [
16]), especially when assessed with the dot-probe task [
17]. More specifically, the bias in depression appears to operate at a later stage of information processing, as indicated by longer maintained attention on negative stimuli (for eye-tracking studies, see [
18‐
21]) and a difficulty to disengage attention from negative information [
22]. However, not only the processing of negative stimuli is impaired in depression. Next to this negative attentional bias, depressed individuals also lack a positive attentional bias, characterized by longer sustained attention to positive than to neutral or negative stimuli, which is usually found in healthy individuals [
20,
21,
23].
Both, the presence of negative as well as the lack of positive attentional biases, have been suggested to play an important role in mood regulation. Whereas a positive attentional bias has been associated with a more adaptive emotion regulation under stress [
24] and increased resilience [
25], the impaired attentional disengagement from negative information has been linked to the ineffective use of emotion-regulation strategies in response to stress [
26,
27]. The latter in turn is supposed to lead to prolonged processing of negative information, such as during rumination and hence, to sustained negative affect. Sanchez and colleagues [
22] recently provided support for this assumption by showing that in depressed patients, specifically the delayed disengagement from negative stimuli predicts lower recovery from negative mood in response to a stressor.
Based on above-mentioned findings, researches in this field have started to investigate attention bias modification (ABM) paradigms, to alter attentional bias and to examine its causal effects on symptoms in emotional disorders with, so far, main focus on anxious populations [
28]. Up to date only a handful of studies have been conducted in depressed samples. Most of these studies made use of the dot-probe task [
17] with increased stimulus presentation times (e.g., [
29,
30]) to allow for a more elaborate processing of the materials and hence tapping into the attentional bias in depression, which is operating at a later stage of information processing [
31].
In a first study, Wells and Beevers [
29] showed that a dot-probe training designed at decreasing a negative attentional bias, reduces depressive symptoms in dysphoric students, from baseline to two weeks follow-up, compared to a placebo ABM training, with the group differences being mediated by a change in attentional bias. In a comparable study, a subclinical sample of adolescents with mild to severe symptoms of depression, completed either eight sessions of active, word based-ABM, placebo ABM or assessment-only [
32]. Compared to placebo and no-training control group, depressive symptoms reduced significantly in the active group and this decrease was maintained during three months follow-up. These effects were mediated by a decrease in rumination, which was again mediated by a change in attentional bias. Promising results were also found by Browning and colleagues [
33], who provided remitted depressed patients 14 days of dot-probe training (two sessions per day) towards positive and away from negative pictures or words. The researchers report an increase in positive attentional bias after the picture-based (but not after the word-based) ABM, as well as reductions in depressive symptoms and cortisol wakening response up to 4 weeks post-training. No such changes were found in the placebo ABM group.
To the best of our knowledge, so far, only two randomized controlled trials (RCTs) have been conducted in samples of currently, clinically depressed individuals. The first study, by Baert and colleagues [
34], made use of a different training paradigm than the dot-probe. By means of a spatial curing task, they trained dysphoric individuals’ and clinically depressed patients’ attention away from negative towards positive words. However, no changes in bias were found and symptom improvements appeared only in the dysphoric group. More encouraging findings come from a just recently conducted RCT, investigating effects of a dot-probe based ABM in currently depressed (MDD) patients [
35]. Compared to four weeks placebo ABM, the same amount of active ABM successfully reduced a negative attentional bias and increased resting-state connectivity within a neural circuit associated with attentional control over emotional information. Although symptom reduction did not differ across groups, only in the active training group, change in negative attentional bias was associated with symptom improvement, supporting the notion that negative attentional bias maintains the disorder. The decrease of symptoms in the placebo group by contrast, seemed to be related to improved control over spatial attention.
Despite these somewhat mixed results and limited number of studies, above-mentioned research suggests, that ABM might be of therapeutic value for depression and may have the potential to increase response and remission rates, achieved by usual care (UC). Considering the growing acknowledgement of the importance of self-help interventions as adjunct to regular health care in depression [
36] and promising findings from numerous studies on the effectiveness of computer-therapy for this disorder (for a meta-analysis, see [
37,
38]), the idea would be very appealing to add ABM as internet-based intervention to existing treatment services. As ABM consists of a rather simple and straightforward computer task and thus needs no or minimal assistance of a clinician, it may flexibly be incorporated into patients’ everyday life, being accessible 24 h a day, on every day of the week. Moreover, the training can be followed at home, in a familiar environment and is not associated with any travel time and costs. Due to these advantages, ABM may be provided to patients not only parallel to UC, but would also be accessible during waiting period for treatment. ABM thus might offer patients and effective, acceptable and budgetary affordable intervention to start with immediately after being referred to mental health care and bridge the, due to insufficient treatment capacitates in the health care system, often unacceptable long time between referral and start of treatment (i.e., up to 90 days or more;[
39]). Next to the potential therapeutic effects, the addition of ABM on top of regular treatment may have favorable economic impacts through reducing the number of sessions of outpatient care by accelerating speed of recovery. This in turn may reduce down-stream costs and may further positively affect return-to-work and productivity.
Before introducing ABM in treatment programs of depression though, more RCTs are required which address limitations of previous studies. First and most importantly, research needs to investigate the effectiveness of a dot-probe based ABM training in clinical practice. Although at least one RCT has been conducted in a sample of individuals diagnosed with clinical depression [
35], the potential of implementing dot-probe based ABM in a specialized clinical health care (and home) setting has not been tested, yet. Second, the long-term effectiveness of ABM still needs to be investigated. Research suggests, that ABM effects may only become apparent over time, when the newly acquainted cognitive processing style is repeatedly deployed in emotional daily-life situations [
17,
29,
40]. The previously conducted ABM studies in depressed samples, however, contained either no follow-up [
34], or follow-up measures between 2 and 4 weeks [
29,
33,
35]. Only one study included follow-up measures at 7 months [
32]. If the goal is, to ultimately apply ABM in clinical settings, it is of importance to examine symptom changes across a much longer period of time, in order to see how stable the changes are and whether ABM is associated with higher response and remission rates and, ideally a reduction in relapse percentages. Third, samples sizes of previous studies are rather small, varying between 14 and 29 participants per group [
29,
30,
32‐
34]. Given the supposedly rather small effects of ABM [
28,
41], it has been claimed that ABM research should strive for larger sample sizes, to increase the confidence regarding effect size estimates [
28,
35,
41].
Aim and hypotheses
The present study aims to address above-mentioned limitations by means of an adequately powered, randomized, double-blind, placebo-controlled trial, alongside an economic evaluation, investigating the long-term effectiveness and cost-effectiveness of a dot-probe based ABM training, as self-help intervention for clinical depression in a specialized health care setting. One hundred twenty six patients who are diagnosed with MDD and are registered for specialized ambulatory treatment at the mental health care institute Pro Persona in the Netherlands, are randomized into either a positivity training (PT) group (ABM towards positive and away from negative stimuli) or a sham (i.e., placebo) training (ST) group, as control condition (continuous attentional bias assessment). Patients complete eight training sessions (of which seven at home via internet) during a period of two weeks. Changes in attentional bias are assessed from pre- to post-assessment, whereas effects on clinical symptoms are additionally assessed one, six and 12 months after training.
In line with previous research on ABM in depression, we predict that the PT group shows a stronger decrease in negative attentional bias and therefore a stronger decrease in depressive symptoms over time, than the ST group. As already suggested by findings of Wells and Beevers [
29] and Beevers and colleagues [
35], training effects on depressive symptoms are thus expected to be mediated by an decrease in negative attentional bias. Recent research by Yang and colleagues [
32] however suggests, that the ABM effect on depressive symptoms is not directly mediated by change in bias. Instead, a change in bias appears to mediate a change in rumination, which in turn directly mediates the reduction of symptoms. Therefore, we additionally explore the effects of ABM on rumination and it’s mediating role in the effects of ABM on depression.
Although previous research suggests that a negative attentional bias is associated with the use of less effective emotion regulation strategies [
26,
42] and hence lower mood recovery from stress [
22], research has not tested the causal effects of modifying attentional bias on stress responses in depressed samples, yet. Whereas ABM effects on symptoms are assumed to manifest themselves over a longer period of time (see for instance, [
23,
33]), effects on mood reactivity and recovery from stress should be visible shortly after the training already. Hence, the present study also includes a stressful speech task at post-assessment, as a more sensitive measure of the potential therapeutic effects. In line with findings of Sanchez and colleagues [
22], it is hypothesized that the PT group shows a higher mood recovery from the stressor than the ST group. Moreover, effects on general levels of resilience over time are measured.
In addition to the effects on depressive symptomatology, rumination and stress responses, this study further extends previous findings by investigating transference effects to other cognitive processes, including attentional bias for verbal emotional information and quality of positive mental imagery, known to be impaired in depression [
43]. Furthermore, a measure of cognitive control is included, as previous research suggests that depression is also associated with a lack of inhibitory control over negative information [
27] and that ABM can increase activity in neural networks associated with attentional control [
35]. Importantly, some previous studies found that sham-training control conditions may lead to comparable changes in symptoms as the active ABM condition, possibly due to the above-mentioned increase in cognitive control, resulting from the contingency-based learning procedure [
30,
44‐
46]. These effects have mainly been observed in socially anxious populations, whereas most studies in depressed samples found active ABM to be more effective than sham ABM [
29,
32‐
34]. Nevertheless, we have to consider the possibility that both groups may show indistinguishable, significant clinical improvements. If this is the case, it will be important to investigate the role of (changes in) cognitive control in the therapeutic effects of the training. At the same time, previous research also suggests that ABM training effects may depend on levels of attentional control (i.e., higher attentional control is associated with stronger training effects; [
47]). Therefore, our measure of cognitive control will also be used to explore whether it predicts our training effects on bias.
Finally, recent research strongly recommends adding questions regarding patients’ expectancies, to control for non-specific treatment effects of an intervention [
48]. It has been argued that, although active/sham control conditions are superior to waiting-list control groups in controlling for placebo effects, it is only possible to ascribe treatment effects to the intervention, if it can be proven that both, treatment and control group have the same expectations regarding improvement. To our knowledge, this is the first ABM study, which actively controls for possible placebo effects of an ABM training, by measuring participants expectations and the experienced credibility of the training.
Discussion
Despite the range of available, evidence-based treatment options for MDD, the rather low response and remission rates [
5‐
7] suggest that treatment for depression is not optimal, yet. Considering the increasing demand for mental health care, the associated costs and limited resources, adding easily accessible computerized interventions as adjunct to regular treatment services of depression, is an appealing and likely efficient option when aiming at treatment optimization.
ABM might have the potential to be provided as such a cost-effective intervention during waiting period for UC or next to the regular treatment sessions by bringing more patients into remission and by reducing face-to-face sessions, especially when being provided via internet. Although the number of ABM studies in depressed samples is still limited and findings are somewhat mixed [
34,
35], existing literature provides encouraging evidence that ABM may indeed decrease depressive symptoms in sub-clinically depressed [
29] and clinically depressed individuals [
29,
32,
35] and thus may have therapeutic value. Most of these previous studies have however limited their scope, by focusing on ABM effects on depressive symptoms and rumination in non-clinical samples, outside mental health care institutions. Moreover, only one RCT has been conducted so far, testing the long term effects on symptoms (i.e., up to seven month after training [
32]).
To the best of our knowledge this is the first RCT examining the long-term effectiveness and cost-effectiveness of an internet-based ABM intervention in clinically depressed patients, in a specialized mental health care setting. Based on the extensive literature showing that depression is characterized by heightened attention for negative information and a lack of attention for positive information [
86], we investigate whether a dot-probe based ABM training away from negative and towards positive pictures is therapeutically effective compared to a placebo (i.e., sham ABM) training. Moreover, it is tested whether ABM effects on symptoms are indeed mediated by a change in attentional bias, as suggested by earlier research [
29].
Next to the long-term effects on clinical symptoms of depression, the present study further aims at extending findings of previous studies, by investigating whether the training affects emotion regulation in response to stress and general levels of resilience. Regarding the mechanisms of symptom change, it is assumed that effects on symptoms manifest themselves over a longer period of time, after the bias has been repetitively deployed in stressful daily life situations [
17,
40]. Although there is evidence that the prolonged processing of negative information is related to impaired mood recovery after stress [
22], this is the first study examining the causal link between attentional bias and stress responses in depression.
Moreover a range of exploratory questions are addressed. To get more insight into mechanisms associated with symptom change, we additionally test the mediating role of rumination in ABM effects. Second, transference effects to attentional bias for verbal materials and to other cognitive measures, including cognitive control and prospective positive mental imagery are investigated. Third, the credibility of the training and related expectancies are measured and controlled for. The latter will not only provide insight into the role of placebo effects within ABM research, but may also give an indication of the acceptance of such a computerized training among patients.
Altogether, this study will enhance our understanding regarding the role of attentional bias in depression and the potential therapeutic effectiveness of ABM in this population. To our knowledge, this is the first study testing the cost-effectiveness of an ABM training in clinically depressed patients in a specialized mental health care setting. It thereby also provides insight into the combination of UC and ABM and whether adding such an internet-based intervention, requiring limited to no time of experienced clinicians, is indeed economically sensible. If the training shows the expected beneficial effects, this study will form an important step towards the implementation of ABM in clinical practice and the optimization of UC through computerized self-help trainings.