Meta-analysis of the changes in correlations between depression instruments used in longitudinal studies

The effectiveness of self-guided interventions in adults with depressive symptoms: a systematic review and meta-analysis

BACKGROUND

Despite promising scalability and accessibility, evidence on the efficacy of self-guided interventions for adult depression is inconclusive. This study investigated their effectiveness and acceptability, considering diverse delivery formats and support levels.

METHODS

We systematically searched PubMed, PsycINFO, Embase, and Cochrane Library until 1st January 2024. Included were randomised controlled trials comparing self-guided interventions with a control condition for adult depression. Two independent researchers extracted data. Effect sizes were pooled using random-effects models, with post-intervention depressive severity compared with control conditions as the primary outcome. Study validity was evaluated using Cochrane Risk of Bias 2.0. This study was pre-registered with OSF (https://osf.io/rd43v).

FINDINGS

We identified 92 studies (111 interventions vs. control comparisons) with 16,706 participants (mean age: 18.78-74.41 years). Compared to controls, self-guided interventions were moderately effective at post-assessment (g = 0.53, 95% CI: 0.45-0.61; I2 = 79.17%) and six to twelve months post-randomisation follow-up (g = 0.32, 95% CI: 0.16-0.48; I2 = 79.19%). Trials with initial human screening (g = 0.59) and interventions delivered in computer programs (g = 1.04) had the significantly largest effect sizes. No differences in treatment effects were observed across support levels, therapy types, commercial availability, or the presence of online discussion forums. Self-guided interventions were less acceptable than control conditions (RR = 0.92, p < 0.001). Most studies showed a moderate to high risk of bias (n = 80).

INTERPRETATION

Existing trials on self-guided interventions are at high risk of bias, potentially overestimating treatment effects. Despite lower acceptability compared to controls, self-guided interventions are moderately effective in treating adult depression, regardless of support levels and online discussion features.

FUNDING

None.

Assessment of suicidality in trials of psychological interventions for depression: a meta-analysis

BACKGROUND

Psychological interventions that are efficacious as treatments for depression could indirectly affect suicide-related outcomes. We examined suicidal thoughts and behaviours as eligibility criteria, outcomes, and adverse events across trials of psychotherapy for depression.

METHODS

We used a publicly available meta-analytic database developed through systematic searches (updated as of May 1, 2023) to identify randomised controlled trials in which a psychological intervention for depression was compared with an inactive or non-specific control condition in adults with depression and in which any suicide-related outcomes were reported. We also identified studies in which suicide risk was an exclusion criterion. We excluded inpatient studies and trials of unguided digital interventions or collaborative care that included a psychological component. Pairs of reviewers worked independently to select studies and extract data. In a random-effects meta-analysis with robust variance estimation, we assessed the effect of the psychological intervention on suicide outcomes in trials in which suicide was explicitly assessed as an outcome with clinical scales with established psychometric properties. Risk of bias was assessed with the Cochrane risk-of-bias tool (version 2).

FINDINGS

Of the 469 randomised trials we identified in which a psychological intervention was compared with an inactive control in people with depression, 251 excluded people judged at risk of suicide. Any assessment of suicide was included in only 45 trials, 12 of which assessed suicidal ideation or risk as an outcome. These 12 trials included 3930 participants, 2795 (71%) of whom were female and 1135 (29%) of whom were male; data for age and ethnicity were not consistently reported. Psychological interventions for depression were associated with a small reduction in suicidal ideation and risk in 11 trials (one trial reported only follow-up data) after the intervention (standardised mean difference -0·31 [95% CI -0·60 to -0·03]) but not at follow-up (-0·49 [-1·31 to 0·32]). Suicide-related adverse events were reported in 25 trials, and suicide-related serious adverse events (eg, suicide attempts, deaths by suicide) were reported in 13 trials. Heterogeneity was substantial across all analyses, and prediction intervals crossed zero.

INTERPRETATION

Trials of psychological interventions for depression rarely report assessments of suicide. Psychological interventions might reduce suicidal ideation in patients with depression, but more randomised controlled trials are required to clarify this effect. Monitoring and reporting of suicide-related adverse events should be improved in trials of psychological interventions for depression, and future trials should incorporate outcomes related to suicidal thoughts or behaviours.

FUNDING

None.

TRANSLATION

For the Spanish translation of the abstract see Supplementary Materials section.

Impact of the fear of catching COVID-19 on mental health in undergraduate students: A Predictive Model for anxiety, depression, and insomnia

Most studies only describe mental health indicators (anxiety, depression, insomnia, and stress) and the risk factors associated with these indicators during the pandemic (sex, student status, and specific physical symptoms). However, no explanatory studies have been found that assess the impact of variables associated with COVID-19. Against this background, the objective of the study was to evaluate the impact of the fear of catching COVID-19 on the level of anxiety, depression, and insomnia in 947 university students of both sexes (41.6% males and 58.4% females) between the ages of 18 and 35 (M = 21.6; SD = 3.4). The Fear of catching COVID-19 Scale, the Generalized Anxiety Disorder Scale (GAD-7), the Patient Health Questionnaire (PHQ-9), and the Insomnia Severity Index (ISI) were used to measure the variables. The results of the study show that the fear of catching COVID-19 significantly influences the level of anxiety (β = .52; p < .01), insomnia (β = .44; p<.01), and depression (β = .50; p < .01) experienced by university students (χ2 = 2075.93; df = 371; p = .000; RMSEA = .070 [CI 90% .067-.073]; SRMR = .055; CFI = .95; TLI = .94). The descriptive results show that a notable percentage of university students present significant symptoms of anxiety (23%), depression (24%), and insomnia (32.9%). It is concluded that the fear of catching COVID-19 is a serious health problem since it influences the appearance of anxiety, depression and insomnia symptoms.

The applicability of the Beck Depression Inventory and Hamilton Depression Scale in the automatic recognition of depression based on speech signal processing

Depression is a growing problem worldwide, impacting on an increasing number of patients, and also affecting health systems and the global economy. The most common diagnostical rating scales of depression are self-reported or clinician-administered, which differ in the symptoms that they are sampling. Speech is a promising biomarker in the diagnostical assessment of depression, due to non-invasiveness and cost and time efficiency. In our study, we try to achieve a more accurate, sensitive model for determining depression based on speech processing. Regression and classification models were also developed using a machine learning method. During the research, we had access to a large speech database that includes speech samples from depressed and healthy subjects. The database contains the Beck Depression Inventory (BDI) score of each subject and the Hamilton Rating Scale for Depression (HAMD) score of 20% of the subjects. This fact provided an opportunity to compare the usefulness of BDI and HAMD for training models of automatic recognition of depression based on speech signal processing. We found that the estimated values of the acoustic model trained on BDI scores are closer to HAMD assessment than to the BDI scores, and the partial application of HAMD scores instead of BDI scores in training improves the accuracy of automatic recognition of depression.

Are existing self-ratings of acute manic symptoms in adults reliable and valid?-A systematic review

BACKGROUND

Depression research historically uses both self- and clinician ratings of symptoms with significant and substantial correlations. It is often assumed that manic patients lack insight and cannot accurately report their symptoms. This delayed the development of self-rating scales for mania, but several scales now exist and are used in research. Our objective is to systematically review the literature to identify existing self-ratings of symptoms of (hypo)mania and to evaluate their psychometric properties.

METHODS

PubMed, Web of Knowledge, and Ovid were searched up until June 2018 using the keywords: "(hypo)mania," "self-report," and "mood disorder" to identify papers which included data on the validity and reliability of self-rating scales for (hypo)mania in samples including patients with bipolar disorder.

RESULTS

We identified 55 papers reporting on 16 different self-rating scales claiming to assess (hypo)manic symptoms or states. This included single item scales, but also some with over 40 items. Three of the scales, the Internal State Scale (ISS), Altman Self-Rating Mania Scale (ASRM), and Self-Report Manic Inventory (SRMI), provided data about reliability and/or validity in more than three independent studies. Validity was mostly assessed by comparing group means from individuals in different mood states and sometimes by correlation to clinician ratings of mania.

CONCLUSIONS

ASRM, ISS, and SRMI are promising self-rating tools for (hypo)mania to be used in clinical contexts. Future studies are, however, needed to further validate these measures; for example, their associations between each other and sensitivity to change, especially if they are meant to be outcome measures in studies.

An Automated Mobile Mood Tracking Technology (Mood 24/7): Validation Study

BACKGROUND

Electronic tracking has been utilized for a variety of health conditions. Previous studies have shown that there is higher adherence to electronic methods vs paper-and-pencil tracking modalities. Electronic tracking also ensures that there are no back-filled entries, where patients have-to appear compliant-entered their responses retrospectively just before their visits with their health care provider. On the basis of the recognition of an unmet need for a Web-based automated platform to track psychiatric outcomes, Johns Hopkins University partnered with Health Central (a subsidiary of Remedy Health Media LLC) to develop Mood 24/7, an electronic, mobile, automated, SMS-based mood tracker. This is a pilot study to validate the use of Mood 24/7 in anticipation of clinical trials to demonstrate the therapeutic benefit on patients' health outcomes of utilizing digital mood-tracking technology.

OBJECTIVE

Mood 24/7 is an electronic mood-monitoring platform developed to accurately and efficiently track mood over time through automated daily SMS texts or emails. This study was designed to assess the accuracy and validity of Mood 24/7 in an outpatient psychiatric setting.

METHODS

This pilot study involved a retrospective chart review for depressed outpatients (N=9) to compare their self-reported Mood 24/7 daily mood ratings with their psychiatrist's independent clinical mood assessment at the time of the patient's visit. Their mood ratings via Mood 24/7 were collected over 36 weeks. In addition, a mixed model analysis was applied to compare the weekly Montgomery-Åsberg Depression Rating Scale (MADRS) scores with Mood 24/7 scores over an average of 3 months.

RESULTS

A 97.2% (315/324) digital mood reporting adherence was found over 36 weeks, and a significant correlation (r=0.86, P<.001) was observed between patients' Mood 24/7 scores and their psychiatrist's blinded clinical assessment of the patient's mood when seen in the clinic. In addition, a significant concordance (intraclass correlation of 0.69, 95% CI 0.33-0.91, P<.001) was observed in the mixed model analysis of the clinician-administered MADRS vs Mood 24/7 scores over time.

CONCLUSIONS

Our chart review and mixed model analyses demonstrate that Mood 24/7 is a valid instrument for convenient, simple, noninvasive, and accurate longitudinal mood assessment in the outpatient clinical setting.

Hamilton scale and MADRS are interchangeable in meta-analyses but can disagree at trial level

BACKGROUND AND OBJECTIVE

Major depressive disorder is a multidimensional disease, in which demonstrating the efficacy of treatments is difficult. The Hamilton Rating Scale for Depression (HRSD) and the Montgomery-Asberg Depression Rating Scale (MADRS) cover different domains but are used interchangeably as primary measures of the outcome in trials and-with standardized measures-in meta-analyses. We aimed at understanding (i) whether the choice of the outcome measurement tool can influence the outcome of a trial, and if so, (ii) whether one systematically outperforms the other, and (iii) whether using standardized measures of the effect in meta-analysis is justified.

METHODS

Short-term randomized trials in patients with major depressive disorder that used both the scales were systematically searched and the results were collected. To quantify the differences in the results-both in terms of the standardized mean difference (SMD) and odds ratio (OR) for response-and their range, data were analyzed and plotted with the Bland-Altman method.

RESULTS

161 comparisons from 80 studies were included, involving a total of 18,189 patients. Neither of the two scales appears systematically more sensitive to the treatment effect than the other in terms of SMDs (P-value = 0.06, 95% CI -0.044 to 0.001) or ORs (P-value = 0.15, 95% CI -0.25 to 0.04). However, the variability of differences between the HRSD and MADRS largely depends on the number of patients included in the comparison.

CONCLUSION

No systematic differences between the two scales were found supporting the use of standardized measures in meta-analyses. However, the same trial may give very different results with either scale, especially in small trials. Further research is needed to understand the causes of this variability.

Are Measures of Character and Personality Distinct? Evidence From Observed-Score and True-Score Analyses

Two studies were conducted to investigate redundancy between the character strengths found in the VIA model of character and familiar personality facets. Study 1 used a community sample (N = 606) that completed a measure of character strengths, four personality inventories, and 17 criterion measures. The second study used Mechanical Turk workers (N = 498) who completed measures of the HEXACO and VIA models and 111 criterion variables. Analyses were conducted using both observed scores and true score estimates, evaluating both predictive and conceptual overlap. Eight of 24 VIA scales proved to be largely redundant with one HEXACO personality facet, but only one VIA scale (Appreciation of Beauty) was largely redundant with Five Factor facets. All strength scales except Spirituality overlapped substantially with at least one personality facet. The results suggest the VIA Classification variables are strongly related to commonly measured personality facets, but the two models are not redundant.

Deep brain stimulation to the medial forebrain bundle for depression- long-term outcomes and a novel data analysis strategy

BACKGROUND

Deep brain stimulation (DBS) of the supero-lateral branch of the medial forebrain bundle (slMFB) in treatment-resistant depression (TRD) is associated with acute antidepressant effects.

OBJECTIVE

Long-term clinical effects including changes in quality of life, side effects and cognition as well as long-term data covering four years are assessed.

METHODS

Eight TRD patients were treated with DBS bilateral to the slMFB. Primary outcome measure was a 50% reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) (response) and remission (MADRS <10) at 12 months compared to baseline. Secondary measures were anxiety, general functioning, quality of life, safety and cognition assessed for 4 years. Data is reported as conventional endpoint-analysis and as area under the curve (AUC) timeline analysis.

RESULTS

Six of eight patients (75%) were responders at 12 months, four patients reached remission. Long-term results revealed a stable effect up to four years. Antidepressant efficacy was also reflected in the global assessment of functioning. Main side effect was strabismus at higher stimulation currents. No change in cognition was identified. AUC analysis revealed a significant reduction in depression for 7/8 patients in most months.

CONCLUSIONS

Long-term results of slMFB-DBS suggest acute and sustained antidepressant effect; timeline analysis may be an alternative method reflecting patient's overall gain throughout the study. Being able to induce a rapid and robust antidepressant effect even in a small, sample of TRD patients without significant psychiatric comorbidity, render the slMFB an attractive target for future studies.