Tag: Depression

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Technology-Enhanced Peer Support for Depression in Older Adults: Single-Arm Mixed Methods Feasibility Study

<strong>Background:</strong> Depression in late life is often compounded by social isolation and barriers to care. There is limited study of technology-enhanced peer support for depression among older adults. <strong>Objective:</strong> This study aimed to assess the feasibility and acceptability of a technology-enhanced peer support intervention to decrease depression among older adults. <strong>Methods:</strong> We used a mixed methods pilot study among adults aged 50 years and older with depression who received a peer support intervention called Peers+. The intervention consisted of 8 weekly video chats and unidirectional texts focused on increasing depression self-care and coping. Data obtained from screening, baseline, postintervention, and 3-month follow-up were used in the analysis to assess preliminary outcomes of the intervention. Mixed effects longitudinal models were used to assess change in depression, and qualitative data were collected and analyzed to identify key themes related to participant experiences. <strong>Results:</strong> A total of 34 older adults with a mean age of 67 (SD 9.57) years participated in the study, and 82.4% (28/34) of participants finished all 8 intervention meetings. Depressive symptoms declined over the course of the study of 35 weeks (<i>F</i><sub>1, 88.8</sub>=26.0; <i>β</i>=–.14, 95% CI –0.20 to 0.09; <i>P</i>&lt;.001). Emotional well-being (<i>β</i>=.48, 95% CI 0.26-0.70; <i>P</i>&lt;.001), social functioning (<i>β</i>=.71, 95% CI 0.33-1.09; <i>P</i>&lt;.001), self-efficacy (<i>β</i>=2.29, 95% CI 0.83-3.75; <i>P</i>&lt;.001), and coping (<i>β</i>=2.90, 95% CI 0.24-5.55; <i>P</i>&lt;.001) improved throughout the study period. Participants perceived supportive texts as reinforcing trust between peer coaches, using coping strategies, increasing social connection, and providing accountability for improving self-care. Peer coaches and older adults needed technology support for participation in the study. <strong>Conclusions:</strong> This study demonstrated the feasibility and acceptability of a peer support intervention enhanced by video chats and texts, delivered by older adult peer coaches to an ethnically diverse group of older adults with depression. Study findings indicate that ongoing and accessible technology support contributed to older adult participation and engagement.
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Augmented reality-based fine arts education experiences and adolescents’ perceived reduction in depressive symptoms: a self-report study of associations with psychological resilience, rumination, and emotional regulation

As depressive symptoms among adolescents continue to rise, increasing attention has been directed toward educational contexts that may support psychological well-being. Augmented reality, characterized by immersive, interactive, and multisensory affordances, has been increasingly incorporated into fine arts education. However, it remains insufficiently understood how adolescents’ perceived AR-based fine arts education experiences are associated with psychological resilience, emotional regulation, perceived reduction in rumination, and perceived reduction in depressive symptoms. Using post-course self-report questionnaire data from 518 Chinese adolescents, this study tested a cross-sectional associational model with structural equation modeling, without making causal or clinical claims. The empirical results indicate that adolescents’ perceived AR-based fine arts education experiences were positively associated with self-reported perceived reduction in depressive symptoms. Additionally, these experiences were positively associated with self-reported psychological resilience and perceived reduction in rumination. Self-reported psychological resilience and perceived reduction in rumination were positively associated with self-reported emotional regulation, and this regulation was positively associated with self-reported perceived reduction in depressive symptoms. These findings support a correlational psychological model linking perceived AR-based fine arts education experiences with adolescents’ self-reported psychological perceptions and perceived reduction in depressive symptoms. Theoretically, this study contributes to the literature on arts education, educational technology, and adolescent mental health. Practically, the findings suggest that immersive art-learning environments may be perceived by adolescents as supportive contexts for psychological resources. The innovation of this study lies in reframing AR-based fine arts education experiences as psychologically meaningful educational experiences associated with adolescents’ self-reported psychological perceptions
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Disrupted self-referential processing and empathy-based interventions in mental disorders: neural mechanisms, cognitive biases, and therapeutic integration

Self-referential processing (SRP), the mental activity of linking experiences and stimuli to the self, is fundamental to shaping identity, regulating affect, and navigating complex social environments. Disruptions in SRP are increasingly recognized as a transdiagnostic hallmark across psychiatric disorders, including schizophrenia spectrum disorders, major depressive disorder, and anxiety disorders. Such disruptions often manifest as distorted self-perception, negative cognitive-affective biases, and dysfunctional connectivity within key neural networks, particularly the default mode network (DMN) and the medial prefrontal cortex (mPFC). Emerging evidence reveals a dynamic bidirectional relationship between SRP and empathy. Impairments in self-processing may hinder the capacity to accurately infer others’ emotional and cognitive states, while deficits in empathic attunement may reinforce maladaptive self-focus. This interplay contributes to social withdrawal, interpersonal dysfunction, and emotional dysregulation across diagnostic boundaries. Recent therapeutic advances suggest that interventions targeting the interface between SRP and empathy may effectively modulate shared neurocognitive mechanisms. Such interventions include metacognitive therapy, mindfulness-based interventions, and psychedelic-assisted psychotherapy. These therapeutic approaches show preliminary but promising evidence for reducing maladaptive self-focused attention, enhancing emotion regulation, and improving social functioning. This review synthesizes empirical evidence regarding the neural underpinnings of SRP, delineates disorder-specific alterations in self-referential processing, and examines the bidirectional interplay between SRP and empathic functioning. We further outline a conceptual framework for empathy-based interventions targeting SRP dysfunction and propose future directions for precision psychiatry research. Emphasis is placed on developing personalized, mechanism-driven therapeutic strategies informed by computational modeling, transdiagnostic biomarker identification, and digital therapeutic platforms.
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Biomarkers Could Help in Antidepressant Choice

Antidepression treatment based on a person’s individual biomarkers could help determine which of the world’s most popular medications to use, a clinical trial suggests.

The SMART Trial to Predict Anhedonia Response to Antidepressant Treatment results suggest that behavioral, brain, and clinical data could together determine the optimal antidepressant to choose before a person starts treatment.

There were no significant primary endpoint differences in depression outcomes between participants who received bupropion or sertraline based on biomarkers identified in the prior Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study.

But people negative for biomarkers with both drugs had significantly worse depression symptom trajectories than those who had at least one positive biomarker, regardless of the drug they received.

Response rates among participants with both biomarkers were almost double that of those without any biomarkers, with those who had at least one biomarker having an intermediate response.

“Our results suggest that we could boost response rate by using two sets of biomarkers previously identified in the EMBARC study, making an important contribution to advancing the goals of precision psychiatry,” reported Peter Zhukovsky, PhD, from Harvard Medical School, and co-workers in Nature Mental Health.

“Ultimately, we strongly hope these advances will enable personalized treatment guidance to accelerate and boost antidepressant benefits.”

Treatment for depression is often still trial and error, with symptoms improving in only half the people taking an antidepressant. This could be due to treatments not being chosen based on people’s individual characteristics.

Finding markers that predict response to different antidepressants could therefore provide patients and clinicians with valuable information to guide treatment choice.

The trial was among the first to investigate how treatment could be guided using clinical information such as responses to questionnaires, behavioral information such as performance in computerized tasks, and brain data such as magnetic resonance imaging (MRI) scans.

It was carried out as part of the Wellcome Leap Multi-Channel Psych Program effort to double the number of people who respond to the first treatment they try for depression via the integration of multimodal biomarkers.

Firstly, the researchers investigated biomarker models that predicted response to the selective serotonin reuptake inhibitor (SSRI) sertraline or the norepinephrine-dopamine reuptake inhibitor bupropion using the EMBARC study.

The treatment-assignment algorithm that was developed generated two marker-based indications for each patient—one for bupropion and sertraline—with the predictive model achieving a cross-validated area under the curve of 0.86 and 0.66, respectively.

The team then examined whether antidepressant response could be boosted using their created biomarker combination of a functional MRI imaging marker, reward learning and sensitivity, cognitive control, the clinical variables of depression severity and neuroticism, and the demographic variable of employment status.

After analyzing these biomarkers among participants, who had major depressive disorder, the group was randomly assigned to receive a full 8-week course of an SSRI or non-SSRI.

The primary outcome was the change in depression severity from pretreatment baseline to eight weeks after the start of treatment, with no significant differences in treatment outcomes for those assigned a drug consistent versus inconsistent with their biomarkers.

This, the researchers say was possibly due to the limited power to detect moderate effects.

However, significant differences emerged in symptom reduction trajectories for those with positive markers for both medications, with a response rate of 71.4% compared with 65.4% for those with a positive biomarker for either drug and 42.9% for those with two negative markers.

The authors concluded: “We found that, relative to patients with two negative markers, those with one or two markers were characterized by significantly larger reduction in depressive symptoms, showing that biomarker-guided treatment selection can boost efficacy for two of the most widely prescribed antidepressants around the world.”

The post Biomarkers Could Help in Antidepressant Choice appeared first on Inside Precision Medicine.

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Oral and Sublingual Ketamine

Conditions: Major Depression Severe

Interventions: Drug: 75 mg of oral ketamine; Drug: Sublingual ketamine 75 mg

Sponsors: Western University, Canada

Not yet recruiting
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Pregnenolone for Cannabis Use Disorder and Depression

Conditions: Cannabis Use Disorder; Major Depressive Disorder (MDD)

Interventions: Drug: Pregnenolone

Sponsors: University of Texas Southwestern Medical Center; National Institute on Drug Abuse (NIDA); The University of Texas at Dallas

Not yet recruiting