Patients with depressive disorders are especially prone to suicide risk. Among the clinical predictors of suicidality, those specifically related to depressive disorders have not been accurately detailed. Our aim was to conduct a systematic review and meta-analysis of studies reporting longitudinal predictors of suicidal ideation, suicide attempts and suicide death within depression, including diagnostic subtypes, symptoms, clinical course, and assessment scales. A systematic search of the literature between 2001 and 2022 identified 4422 references, among which 19 studies providing 45 different predictors of suicidality met the inclusion criteria. Random effects meta-analyses were performed for 22 predictors, three for suicidal ideation, eleven for suicide attempts and eight for suicide death. Heterogeneity and publication bias were inspected through I² tests and Egger’s tests respectively. Meta-analysis results showed that severity of hopelessness predicted suicidal ideation and suicide attempts. History of suicide attempts, suicidal ideation, severe depression, and psychotic symptoms predicted subsequent suicide attempts and suicide death. Time to full remission and sleep disturbances were also found as relevant predictors of future suicide behaviours. This review specifies which predictors of suicidality within the clinical features of depression will help clinicians and policy makers to better prevent suicide risk in patients with depressive disorders. Further longitudinal studies are needed to reliably assess the predictive ability of our results and to analyse other possible clinical predictors to prevent suicidality, especially with regard to suicidal ideation.

Background: Depression is a serious, disabling mental disorder that severely affects quality of life. Patients with depression often do not receive adequate treatment. App-based psychotherapy is considered to have great potential to treat depression owing to its reach and easy accessibility. Objective: We aim to analyze the impact of app-based psychological interventions for reducing depressive symptoms in people with depression. Methods: We conducted a systematic literature review and meta-analysis. We searched Medline, Embase, PsycINFO, Web of Science, and Cochrane Central Register of Controlled Trials from inception to December 23, 2020. We selected randomized controlled trials to examine the impact of app-based psychological interventions for reducing depressive symptoms in people with depression. Study selection, data extraction, and critical appraisal (using the Cochrane Risk of Bias tool for randomized studies and the ROBINS-I tool for nonrandomized studies) were conducted independently by 2 reviewers. Where possible, we pooled data using random effects meta-analyses to obtain estimates of the effect size of the intervention. We conducted post hoc meta-regression analyses to explore the factors associated with intervention success. Results: After screening 3468 unique references retrieved from bibliographic searches and assessing the eligibility of 79 full texts, we identified 12 trials (2859 participants) evaluating 14 different interventions. Of 14 trials, 7 (58%) were conducted in the United States; 3 (25%) trials, in Asia (Japan, South Korea, and China); 1 (8%) trial, in Australia; and 1 (8%) trial, in Germany. Of the 12 trials, 5 (42%) trials presented a low risk of bias. The mean duration of the interventions was 6.6 (SD 2.8) weeks. Two-thirds of the interventions were based on cognitive behavioral therapy alone or included it in combination with cognitive control therapy, positive psychology, brief behavioral activation, or mindfulness- and acceptance-based therapy. With no evidence of publication bias, a pooled analysis of 83% (10/12) of the trials and 86% (12/14) of the interventions showed that app-based interventions, compared with a control group receiving usual care or minimal intervention, produced a moderate reduction in depressive symptoms (standardized mean difference [SMD] −0.51, 95% CI −0.69 to −0.33; 2018/2859, 70.58% of the participants; I2=70%). Our meta-regression analyses indicated that there was a greater reduction in symptoms of depression (P=.04) in trials that included participants with moderate to severe depression (SMD −0.67, 95% CI −0.79 to −0.55), compared with trials with participants exhibiting mild to moderate depression (SMD −0.15, 95% CI −0.43 to −0.12). Conclusions: App-based interventions targeted at people with depression produce moderate reductions in the symptoms of depression. More methodologically robust trials are needed to confirm our findings, determine which intervention features are associated with greater improvements, and identify those populations most likely to benefit from this type of intervention. Trial Registration: PROSPERO CRD42019145689; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=145689

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Suicide is a serious public health concern. Depression is the main gateway to suicidal behavior. The already established relationship between depression and suicidal risk should now focus on the investigation of more specific factors: recent studies have suggested an association between vulnerability to suicidal behavior and neurocognitive alterations, a nuclear symptom of depression. This project aims to identify alterations in the Executive Functions (EF) of patients suffering a first depressive episode that might constitute a risk factor for suicidal ideation, suicidal attempts and suicide, to allow for more adequate suicide prevention. Prospective longitudinal design involving two groups (first depressive episodes with and without alterations in their EF) and four repeated measures (0, 6, 12 and 24 months). The estimated minimum sample size is 216 subjects. The variables and measurement instruments will include socio-demographic variables, clinical variables (age of illness onset, family and personal antecedents, psychopathological and medical comorbidity, suicidal ideation, suicide attempts and completed suicides, severity of depression, including melancholic or atypical, remission of the depressive episode), and neuropsychological variables (EF and decision-making processes evaluated through the Cambridge Neuropsychological Test Automated Battery (CANTAB)). First and foremost, the identification of clinical and neuropsychological risk factors associated with suicidal behavior will open the possibility to prevent such behavior in patients with a first depressive episode in the context of clinical practice. Secondly, interventions aimed at cognitive impairment (in particular: EF) derived from the study may be incorporated into strategies for the prevention of suicidal behavior. Finally, impaired neurocognitive function (even in early stages) could become an identifiable endophenotype or “marker” in clinical and neurobiological studies about suicidal behavior in depressive patients.

Background: Primary care is a major access point for the initial treatment of depression, but the management of these patients is far from optimal. The lack of time in primary care is one of the major difficulties for the delivery of evidence-based psychotherapy. During the last decade, research has focused on the development of brief psychotherapy and cost-effective internet-based interventions mostly based on cognitive behavioral therapy (CBT). Very little research has focused on alternative methods of treatment for depression using CBT. Thus, there is a need for research into other therapeutic approaches. Objective: This study aimed to assess the effectiveness of 3 low-intensity, internet-based psychological interventions (healthy lifestyle psychoeducational program [HLP], focused program on positive affect promotion [PAPP], and brief intervention based on mindfulness [MP]) compared with a control condition (improved treatment as usual [iTAU]). Methods: A multicenter, 4-arm, parallel randomized controlled trial was conducted between March 2015 and March 2016, with a follow-up of 12 months. In total, 221 adults with mild or moderate major depression were recruited in primary care settings from 3 Spanish regions. Patients were randomly distributed to iTAU (n=57), HLP (n=54), PAPP (n=56), and MP (n=54). All patients received iTAU from their general practitioners. The main outcome was the Spanish version of the Patient Health Questionnaire-9 (PHQ-9) from pretreatment (time 1) to posttreatment (time 2) and up to 6 (time 3) and 12 (time 4) months’ follow-up. Secondary outcomes included the visual analog scale of the EuroQol, the Short-Form Health Survey (SF-12), the Positive and Negative Affect Schedule (PANAS), and the Pemberton Happiness Index (PHI). We conducted regression models to estimate outcome differences along study stages. Results: A moderate decrease was detected in PHQ-9 scores from HLP (β=–3.05; P=.01) and MP (β=–3.00; P=.01) compared with iTAU at posttreatment. There were significant differences between all intervention groups and iTAU in physical SF-12 scores at 6 months after treatment. Regarding well-being, MP and PAPP reported better PHI results than iTAU at 6 months post treatment. PAPP intervention significantly decreased PANAS negative affect scores compared with iTAU 12 months after treatment. Conclusions: The low-intensity, internet-based psychological interventions (HLP and MP) for the treatment of depression in primary care are more effective than iTAU at posttreatment. Moreover, all low-intensity psychological interventions are also effective in improving medium- and long-term quality of life. PAPP is effective for improving health-related quality of life, negative affect, and well-being in patients with depression. Nevertheless, it is important to examine possible reasons that could be implicated for PAPP not being effective in reducing depressive symptomatology; in addition, more research is still needed to assess the cost-effectiveness analysis of these interventions. Trial Registration: ISRCTN Registry ISRCTN82388279; http://www.isrctn.com/ISRCTN82388279 International Registered Report Identifier (IRRID): RR2-10.1186/s12888-015-0475-0