Mindfulness-based interventions for people diagnosed with a current episode of an anxiety or depressive disorder: a meta-analysis of randomised controlled trials

Objective Mindfulness-based interventions (MBIs) can reduce risk of depressive relapse for people with a history of recurrent depression who are currently well. However, the cognitive, affective and motivational features of depression and anxiety might render MBIs ineffective for people experiencing current symptoms. This paper presents a meta-analysis of randomised controlled trials (RCTs) of MBIs where participants met diagnostic criteria for a current episode of an anxiety or depressive disorder. Method Post-intervention between-group Hedges g effect sizes were calculated using a random effects model. Moderator analyses of primary diagnosis, intervention type and control condition were conducted and publication bias was assessed. Results Twelve studies met inclusion criteria (n = 578). There were significant post-intervention between-group benefits of MBIs relative to control conditions on primary symptom severity (Hedges g = −0.59, 95% CI = −0.12 to −1.06). Effects were demonstrated for depressive symptom severity (Hedges g = −0.73, 95% CI = −0.09 to −1.36), but not for anxiety symptom severity (Hedges g = −0.55, 95% CI = 0.09 to −1.18), for RCTs with an inactive control (Hedges g = −1.03, 95% CI = −0.40 to −1.66), but not where there was an active control (Hedges g = 0.03, 95% CI = 0.54 to −0.48) and effects were found for MBCT (Hedges g = −0.39, 95% CI = −0.15 to −0.63) but not for MBSR (Hedges g = −0.75, 95% CI = 0.31 to −1.81). Conclusions This is the first meta-analysis of RCTs of MBIs where all studies included only participants who were diagnosed with a current episode of a depressive or anxiety disorder. Effects of MBIs on primary symptom severity were found for people with a current depressive disorder and it is recommended that MBIs might be considered as an intervention for this population

Categorical differentiation of the unipolar and bipolar disorders

There has been a longstanding debate as to whether the bipolar disorders differ categorically or dimensionally, with some dimensional or spectrum models including unipolar depressive disorders within a bipolar spectrum model. We analysed manic/hypomanic symptom data in samples of clinically diagnosed bipolar I, bipolar II and unipolar patients, employing latent class analyses to determine if separate classes could be identified. Mixture analyses were also undertaken to determine if a unimodal, bimodal or a trimodal pattern was present. For both a refined 15-item set and an extended 30-item set of manic/hypomanic symptoms, our latent class analyses favoured three-class solutions, while mixture analyses identified trimodal distributions of scores. Findings argue for a categorical distinction between unipolar and bipolar disorders, as well as between bipolar I and bipolar II disorders. Future research should aim to consolidate these results in larger samples, particularly given that the size of the unipolar group in this study was a salient limitation

The bipolar disorders: A case for their categorically distinct status based on symptom profiles

Background: It is unclear whether the bipolar disorders (i.e. BP-I/BP-II) differ dimensionally or categorically. This study sought to clarify this issue. Methods: We recruited 165 patients, of which 69 and 96 had clinician-assigned diagnoses of BP-I and BP-II respectively. Their psychiatrists completed a data sheet seeking information on clinical variables about each patient, while the patients completed a different data sheet and scored a questionnaire assessing the prevalence and severity of 96 candidate manic/hypomanic symptoms. Results: We conducted a series of analyses examining a set (and two sub-sets) of fifteen symptoms that were significantly more likely to be reported by the clinically diagnosed BP-I patients. Latent class analyses favoured two-class solutions, while mixture analyses demonstrated bimodality, thus arguing for a BP-I/BP-II categorical distinction. Statistically defined BP-I class members were more likely when manic to have experienced psychotic features and over-valued ideas. They were also more likely to have been hospitalised, and to have been younger when they received their bipolar diagnosis and first experienced a depressive or manic episode. Limitations: The lack of agreement between some patients and managing clinicians in judging the presence of psychotic features could have compromised some analyses. It is also unclear whether some symptoms (e.g. grandiosity, noting mystical events) were capturing formal psychotic features or not. Conclusions: Findings replicate our earlier study in providing evidence to support the modelling of BP-I and BP-II as categorically discrete conditions. This should advance research into aetiological factors and determining optimal (presumably differing) treatments for the two conditions

Differentiating mania/hypomania from happiness using a machine learning analytic approach.

Background: This study aimed to improve the accuracy of bipolar disorder diagnoses by identifying symptoms that help to distinguish mania/hypomania in bipolar disorders from general ‘happiness’ in those with unipolar depression. Methods: An international sample of 165 bipolar and 29 unipolar depression patients (as diagnosed by their clinician) were recruited. All participants were required to rate a set of 96 symptoms with regards to whether they typified their experiences of manic/hypomanic states (for bipolar patients) or when they were ‘happy’ (unipolar patients). A machine learning paradigm (prediction rule ensembles; PREs) was used to derive rule ensembles that identified which of the 94 non-psychotic symptoms and their combinations best predicted clinically-allocated diagnoses. Results: The PREs were highly accurate at predicting clinician bipolar and unipolar diagnoses (92% and 91% respectively). A total of 20 items were identified from the analyses, which were all highly discriminating across the two conditions. When compared to a classificatory approach insensitive to the weightings of the items, the ensembles were of comparable accuracy in their discriminatory capacity despite the unbalanced sample. This illustrates the potential for PREs to supersede traditional classificatory approaches. Limitations: There were considerably less unipolar than bipolar patients in the sample, which limited the overall accuracy of the PREs. Conclusions: The consideration of symptoms outlined in this study should assist clinicians in distinguishing between bipolar and unipolar disorders. Future research will seek to further refine and validate these symptoms in a larger and more balanced sample

Clinical correlates of complicated grief among individuals with acute coronary syndromes

OBJECTIVE: The study aimed at exploring bereavement and complicated grief (CG) symptoms among subjects without a history of coronary heart disease (CHD) at the time of a first acute coronary syndrome (ACS) and to evaluate the relationship of CG symptoms and ACS. METHOD: Overall, 149 subjects with ACS (namely, acute myocardial infarct with or without ST-segment elevation or unstable angina), with no previous history of CHD, admitted to three cardiac intensive care units were included and evaluated by the Structured Clinical Interview for Complicated Grief (SCI-CG), Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, and the 36-item Short-Form Health Survey (MOS-SF-36). RESULTS: Of the total sample of 149 subjects with ACS, 118 (79.2%) met criteria for DSM-5 persistent complex bereavement disorder. Among these, subjects who lost a partner, child, or sibling were older (P=0.008), less likely to be working (P=0.032), and more likely to be suffering from hypertension (P=0.021), returned higher scores on the SCI-CG (P=0.001) and developed the index ACS more frequently between 12 and 48 months after the death than those who lost a parent or another relative (P≤0.0001). The occurrence of ACS 12-48 months (P=0.019) after the loss was positively correlated with SCI-CG scores. An inverse relationship with SCI-CG scores was observed for patients who experienced ACS more than 48 months after the loss (P=0.005). The SCI-CG scores significantly predicted lower scores on the "general health" domain of MOS-SF-36 (P=0.030), as well as lower scores on "emotional well-being" domain (P=0.010). CONCLUSION: A great proportion of subjects with ACS report the loss of a loved one. Among these, the loss of a close relative and the severity of CG symptoms are associated with poorer health status. Our data corroborate previous data indicating a strong relationship between CG symptoms and severe cardiac problems

Impact of a mobile phone and web program on symptom and functional outcomes for people with mild-to-moderate depression, anxiety and stress: a randomised controlled trial.

Background Mobile phone-based psychological interventions enable real time self-monitoring and self-management, and large-scale dissemination. However, few studies have focused on mild-to-moderate symptoms where public health need is greatest, and none have targeted work and social functioning. This study reports outcomes of a CONSORT-compliant randomised controlled trial (RCT) to evaluate the efficacy of myCompass, a self-guided psychological treatment delivered via mobile phone and computer, designed to reduce mild-to-moderate depression, anxiety and stress, and improve work and social functioning. Method Community-based volunteers with mild-to-moderate depression, anxiety and/or stress (N= 720) were randomly assigned to the myCompass program, an attention control intervention, or to a waitlist condition for seven weeks. The interventions were fully automated, without any human input or guidance. Participants’ symptoms and functioning were assessed at baseline, post-intervention and 3-month follow-up, using the Depression, Anxiety and Stress Scale and the Work and Social Adjustment Scale. Results Retention rates at post-intervention and follow-up for the study sample were 72.1% (n= 449) and 48.6% (n= 350) respectively. The myCompass group showed significantly greater improvement in symptoms of depression, anxiety and stress and in work and social functioning relative to both control conditions at the end of the 7-week intervention phase (between-group effect sizes ranged from d= .22 to d= .55 based on the observed means). Symptom scores remained at near normal levels at 3-month follow-up. Participants in the attention control condition showed gradual symptom improvement during the post-intervention phase and their scores did not differ from the myCompass group at 3-month follow-up. Conclusions The myCompass program is an effective public health program, facilitating rapid improvements in symptoms and in work and social functioning for individuals with mild-to-moderate mental health problems

Effects of mental health self-efficacy on outcomes of a mobile phone and web intervention for mild-to-moderate depression, anxiety and stress: secondary analysis of a randomised controlled trial.

Background: Online psychotherapy is clinically effective yet why, how, and for whom the effects are greatest remain largely unknown. In the present study, we examined whether mental health self-efficacy (MHSE), a construct derived from Bandura’s Social Learning Theory (SLT), influenced symptom and functional outcomes of a new mobile phone and web-based psychotherapy intervention for people with mild-to-moderate depression, anxiety and stress. Methods: STUDY I: Data from 49 people with symptoms of depression, anxiety and/or stress in the mild-to-moderate range were used to examine the reliability and construct validity of a new measure of MHSE, the Mental Health Self-efficacy Scale (MHSES). STUDY II: We conducted a secondary analysis of data from a recently completed randomised controlled trial (N = 720) to evaluate whether MHSE effected post-intervention outcomes, as measured by the Depression, Anxiety and Stress Scales (DASS) and Work and Social Adjustment Scale (WSAS), for people with symptoms in the mild-to-moderate range. Results: STUDY I: The data established that the MHSES comprised a unitary factor, with acceptable internal reliability (Cronbach’s alpha = .89) and construct validity. STUDY II: The intervention group showed significantly greater improvement in MHSE at post-intervention relative to the control conditions (p’s < = .000). MHSE mediated the effects of the intervention on anxiety and stress symptoms. Furthermore, people with low pre-treatment MHSE reported the greatest post-intervention gains in depression, anxiety and overall distress. No effects were found for MHSE on work and social functioning. Conclusion: Mental health self-efficacy influences symptom outcomes of a self-guided mobile phone and web-based psychotherapeutic intervention and may itself be a worthwhile target to increase the effectiveness and efficiency of online treatment programs