Background Non-Suicidal Self-Injury (NSSI) refers to deliberate and repeated acts of damaging one's own body tissue without suicidal intent. It has have become a serious public health problem in the world. This study is to set a meta-analysis for exploring effectiveness of acupuncture combined with psychotherapy compared to antidepressant in treatment of adolescent depressive patients. Methods Chinese and English literature related to treatment with combination of acupuncture and psychotherapy compared to antidepressant for adolescent patients with depression in China were searched. The comments, letters, reviews, and case reports were excluded. The index of depression, anxiety, and effectiveness in patients with was synthesized and discussed. Result A total of three studies were included, in which their studying type is acupuncture combined with psychotherapy compared to antidepressant in treatment of depressive patients. The lower score of anxiety and depression were found in combined acupuncture with psychotherapy compared to antidepressant in the end of treatment in adolescent depressive patients. It is found that higher rate of efficacy in combined acupuncture with psychotherapy compared to antidepressant in the end of treatment in adolescent depressive patients. Conclusion The severity of anxiety and depression was significantly lower and higher effective rate in adolescent depressive patients with combination of acupuncture and psychotherapy than antidepressant after treatment. These results fully demonstrate the important role of complying with treatment guideline, in which non-pharmacotherapy was first choice.
Urszula Kaczmarska, Michał Jakub Cioch, J. Nowak
et al.
Introduction Depression is one of the most common mental illnesses. Over the course of a lifetime, several percent of the adult population suffers from depression. There are many treatments for depression like pharmacotherapy and psychotherapy. In this article, we wanted to focus on the effectiveness of ketamine in treating depression. Aim of study The study aimed to summarize the available knowledge on the use of ketamine in the treatment of depression. The epidemiology, etiology, side effects, and treatment methods, were summarized and described. Materials and method The literature available in the PubMed database was reviewed using the following keywords: “Ketamine”,” Depression”, and “Antidepressants”. Conclusion Without a doubt, ketamine has proven to be a new advocate for mental health research and therapeutics. After over half a century without novel targets for MDD (Major Depressive Disorder) treatment, the observation of ketamine’s rapid antidepressant effects in treatment-resistant depression has become a promising field that could represent a breakthrough in the understanding of MDD, and the possibility of reducing some of the major personal and global burden that depression is responsible for. It seems imminent then that a new era of different acting antidepressant strategies is upon us, and it is our responsibility to make a critical analysis of the potential benefits and harm inherent to novel therapeutics.
Sleep is an indispensable physiological function regulated by circadian rhythms, which influence the biological pathways and overall health of the body. Sleep is crucial for the maintenance and restoration of bodily systems, and disturbances can lead to various sleep disorders, which can impair both mental and physical health. Treatment options for these disorders encompass lifestyle modifications, psychotherapy, medications, and therapies such as light therapy and surgery. Not only sleep deprivation has a significant impact on essential organs, but it also influences various types of stem cells in the body. In this review, we explore the connection between sleep and various types of stem cells, highlighting how circadian rhythms regulate stem cell activities that are vital for tissue regeneration and homeostasis. Disruptions in sleep can hinder stem cell self-renewal, homing, proliferation, function, and differentiation, thereby affecting tissue regeneration and overall health. We also discuss how transplantation of stem cells and their products may help improve sleep disorders, how sleep quality affects stem cell behavior, and the implications for stem cell therapies. Notably, while certain stem cell transplantations can disrupt sleep, enhancing sleep quality may improve the efficacy of these therapies. Finally, stem cells can be utilized to model sleep disorders, offering valuable insights into their underlying mechanisms.
Schizophrenia and other chronic psychotic disorders are notoriously difficult to treat and full remission is unfortunately not the norm. In this article, we will review advances in treatment as follows: 1) conceptual advances in understanding, quantifying, and targeting cognitive symptoms, which are pervasive through the lifespan; 2) advancements in targeting metabolic and motor effects of antipsychotic medications with vesicular monoamine transporter (VMAT) inhibitors and compounds such as samidorphan, and newer antipsychotics with varied neurotransmitter targets, including cholinergic modulation, glutamatergic tone, lesser known receptor systems such as glycine transporters, and trace amine-associated receptor 1 (TAAR1) agents; 3) enhanced delivery mechanisms leading to quarterly and biyearly long-acting injectables; and 4) digital therapeutics, a set of apps and wearables meant to enhance care for psychotic disorders by utilizing well-established psychotherapy treatment principles; packaged in smartphone applications, the interventions can be delivered in a private customized manner that bypasses access issues and supports microbehavioral experiments to target negative and cognitive symptoms. [ Psychiatr Ann . 2025;55(1):e8–e13.]
This article argues that clinicians and researchers must apply the same evidence-based medicine (EBM) hierarchy to digital health interventions that they use for traditional treatments. When comparing interventions for the same clinical indication, evidentiary standards should not change based on delivery method - whether pharmacotherapy, psychotherapy, or digital therapeutics. The manuscript outlines the spectrum of digital health tools (Digital Health, Digital Medicine, and Digital Therapeutics) and examines the rigorous FDA approval process for digital therapeutics, which requires Phase III randomized controlled trials comparable to pharmaceutical standards. Using substance use disorder treatment as a concrete example, the article demonstrates the “evidence gap” between FDA-approved digital therapeutics with robust clinical trial data and unvalidated commercial apps that rely on testimonials or no published research. The framework extends to emerging artificial intelligence applications in therapeutic spaces. Finally, the article addresses systemic implementation barriers - including reimbursement uncertainty, limited provider awareness, and clinical workflow integration challenges - and practical considerations clinicians face when selecting digital tools, including cost-access trade-offs, engagement metrics, and professional liability concerns.
Eric Wang, Samuel Schmidgall, Paul F. Jaeger
et al.
Therapeutic development is a costly and high-risk endeavor that is often plagued by high failure rates. To address this, we introduce TxGemma, a suite of efficient, generalist large language models (LLMs) capable of therapeutic property prediction as well as interactive reasoning and explainability. Unlike task-specific models, TxGemma synthesizes information from diverse sources, enabling broad application across the therapeutic development pipeline. The suite includes 2B, 9B, and 27B parameter models, fine-tuned from Gemma-2 on a comprehensive dataset of small molecules, proteins, nucleic acids, diseases, and cell lines. Across 66 therapeutic development tasks, TxGemma achieved superior or comparable performance to the state-of-the-art generalist model on 64 (superior on 45), and against state-of-the-art specialist models on 50 (superior on 26). Fine-tuning TxGemma models on therapeutic downstream tasks, such as clinical trial adverse event prediction, requires less training data than fine-tuning base LLMs, making TxGemma suitable for data-limited applications. Beyond these predictive capabilities, TxGemma features conversational models that bridge the gap between general LLMs and specialized property predictors. These allow scientists to interact in natural language, provide mechanistic reasoning for predictions based on molecular structure, and engage in scientific discussions. Building on this, we further introduce Agentic-Tx, a generalist therapeutic agentic system powered by Gemini 2.5 that reasons, acts, manages diverse workflows, and acquires external domain knowledge. Agentic-Tx surpasses prior leading models on the Humanity's Last Exam benchmark (Chemistry & Biology) with 52.3% relative improvement over o3-mini (high) and 26.7% over o3-mini (high) on GPQA (Chemistry) and excels with improvements of 6.3% (ChemBench-Preference) and 2.4% (ChemBench-Mini) over o3-mini (high).
The increasing demand for mental health services has led to the rise of AI-driven mental health chatbots, though challenges related to privacy, data collection, and expertise persist. Motivational Interviewing (MI) is gaining attention as a theoretical basis for boosting expertise in the development of these chatbots. However, existing datasets are showing limitations for training chatbots, leading to a substantial demand for publicly available resources in the field of MI and psychotherapy. These challenges are even more pronounced in non-English languages, where they receive less attention. In this paper, we propose a novel framework that simulates MI sessions enriched with the expertise of professional therapists. We train an MI forecaster model that mimics the behavioral choices of professional therapists and employ Large Language Models (LLMs) to generate utterances through prompt engineering. Then, we present KMI, the first synthetic dataset theoretically grounded in MI, containing 1,000 high-quality Korean Motivational Interviewing dialogues. Through an extensive expert evaluation of the generated dataset and the dialogue model trained on it, we demonstrate the quality, expertise, and practicality of KMI. We also introduce novel metrics derived from MI theory in order to evaluate dialogues from the perspective of MI.
Although large language models (LLMs) hold significant promise in psychotherapy, their direct application in patient-facing scenarios raises ethical and safety concerns. Therefore, this work shifts towards developing an LLM as a supervisor to train real therapists. In addition to the privacy of clinical therapist training data, a fundamental contradiction complicates the training of therapeutic behaviors: clear feedback standards are necessary to ensure a controlled training system, yet there is no absolute "gold standard" for appropriate therapeutic behaviors in practice. In contrast, many common therapeutic mistakes are universal and identifiable, making them effective triggers for targeted feedback that can serve as clearer evidence. Motivated by this, we create a novel therapist-training paradigm: (1) guidelines for mistaken behaviors and targeted correction strategies are first established as standards; (2) a human-in-the-loop dialogue-feedback dataset is then constructed, where a mistake-prone agent intentionally makes standard mistakes during interviews naturally, and a supervisor agent locates and identifies mistakes and provides targeted feedback; (3) after fine-tuning on this dataset, the final supervisor model is provided for real therapist training. The detailed experimental results of automated, human and downstream assessments demonstrate that models fine-tuned on our dataset MATE, can provide high-quality feedback according to the clinical guideline, showing significant potential for the therapist training scenario.
Saar Draznin Shiran, Boris Boltyansky, Alexandra Zhuravleva
et al.
Background. Chronic pain afflicts 20 % of the global population. A strictly biomedical mind-set leaves many sufferers chasing somatic cures and has fuelled the opioid crisis. The biopsychosocial model recognises pain subjective, multifactorial nature, yet uptake of psychosocial care remains low. We hypothesised that patients own pain narratives would predict their readiness to engage in psychotherapy. Methods. In a cross-sectional pilot, 24 chronic-pain patients recorded narrated pain stories on Painstory.science. Open questions probed perceived pain source, interference and influencing factors. Narratives were cleaned, embedded with a pretrained large-language model and entered into machine-learning classifiers that output ready/not ready probabilities. Results. The perception-domain model achieved 95.7 % accuracy (specificity = 0.80, sensitivity = 1.00, AUC = 0.90). The factors-influencing-pain model yielded 83.3 % accuracy (specificity = 0.60, sensitivity = 0.90, AUC = 0.75). Sentence count correlated with readiness for perception narratives (r = 0.54, p < .01) and factor narratives (r = 0.24, p < .05). Conclusion. Brief spoken pain narratives carry reliable signals of willingness to start psychosocial treatment. NLP-based screening could help clinicians match chronic-pain patients to appropriate interventions sooner, supporting a patient-centred biopsychosocial pathway.
Precision therapeutics require multimodal adaptive models that generate personalized treatment recommendations. We introduce TxAgent, an AI agent that leverages multi-step reasoning and real-time biomedical knowledge retrieval across a toolbox of 211 tools to analyze drug interactions, contraindications, and patient-specific treatment strategies. TxAgent evaluates how drugs interact at molecular, pharmacokinetic, and clinical levels, identifies contraindications based on patient comorbidities and concurrent medications, and tailors treatment strategies to individual patient characteristics. It retrieves and synthesizes evidence from multiple biomedical sources, assesses interactions between drugs and patient conditions, and refines treatment recommendations through iterative reasoning. It selects tools based on task objectives and executes structured function calls to solve therapeutic tasks that require clinical reasoning and cross-source validation. The ToolUniverse consolidates 211 tools from trusted sources, including all US FDA-approved drugs since 1939 and validated clinical insights from Open Targets. TxAgent outperforms leading LLMs, tool-use models, and reasoning agents across five new benchmarks: DrugPC, BrandPC, GenericPC, TreatmentPC, and DescriptionPC, covering 3,168 drug reasoning tasks and 456 personalized treatment scenarios. It achieves 92.1% accuracy in open-ended drug reasoning tasks, surpassing GPT-4o and outperforming DeepSeek-R1 (671B) in structured multi-step reasoning. TxAgent generalizes across drug name variants and descriptions. By integrating multi-step inference, real-time knowledge grounding, and tool-assisted decision-making, TxAgent ensures that treatment recommendations align with established clinical guidelines and real-world evidence, reducing the risk of adverse events and improving therapeutic decision-making.
This study aimed to investigate the effectiveness of narrative group therapy on resilience, functional disability, and psychological distress of patients with chronic schizophrenia. The current research method was quasi-experimental with pre-test, post-test, and follow-up with control and experimental groups. The population of the research included men aged 20 to 60 with chronic schizophrenia in Ardabil in 2023 who were hospitalized in treatment and rehabilitation centers for chronic psychotic patients, and their number was estimated to be around 250. Convenience sampling was used due to the impracticality of gathering patients from other centers for group therapy. One treatment and rehabilitation center for chronic patients was selected through this method based on the availability of the required sample size and the level of cooperation. After reviewing the psychological files and considering the inclusion criteria, 30 participants were selected and randomly divided into experimental (n=15) and control (n=15) groups. Both the control and experimental groups answered the Connor-Davidson Resilience Scale, the WHO Disability Assessment Schedule, and the Psychological Distress scale before, after, and one month after the intervention, and their data were compared with the use of descriptive statistics and analysis of variance with repeated measurements analyzed in SPSS22 software platform. The results showed that resilience, functional disability, and psychological distress (anxiety, stress, and depression) have a significant difference from the pre-test stage to the follow-up stage. Therefore, it can be concluded that narrative therapy leads to the improvement of resilience, functional disability, and psychological distress of chronic schizophrenia patients.
Having a well-embodied sustainable state which has impenetrable security is considered the emblem of advanced civilization. Apart from all the indisputable elements of a sustainable state, security plays the role of the founding stone. This study aims to pursue the contribution of historical religious harmony in Bangladesh, practiced by the mass people, in strengthening the state security. Data was collected through particular scientific research methodologies of the descriptive method to analyze the possible answers of arising queries, historical method to explore historical background of the subject and the comparative method to detect the perfect stakeholders for establishing religious harmony in Bangladesh to strengthen the state security. The study explored that Bangladesh, since its creation, has assumed different characteristics from any other countries all over the world & religious harmony played a pivotal role in creating Bangladesh as an independent and sustainable state on the global map. It identified that despite not being the ruling party, religious parties have been contributing more to securing religious harmony than the conventional parties. The study tracked out a plethora of confidential conspiracies driven by different wings to annihilate the historical heritage to prove Bangladesh as a fragile state. This research concluded that utilizing the heritage of religious harmony will pave the eternal way to keep this state as an unassailable secured country.
This non-systematic exploratory review examined the literature regarding spiritual care in the voluntary assisted dying (VAD) environment, ultimately establishing a holistic theoretical framework for care. Drawing on previously established conceptualisations of spirituality, two dimensions of VAD care were identified: internal spiritual concerns and relational spiritual concerns. Care for internal spiritual issues in the VAD environment involves establishing internal congruence within a patient and exploring the existential meaning the VAD experience holds for them. Family members can be a crucial psychosocial–spiritual support, which often leads to their involvement in treatment, thereby creating potential relational spiritual concerns; however, VAD itself can create interpersonal challenges that diminish familial support. A patient’s philosophical, religious or spiritual community and relevant spiritual leaders also provide highly beneficial significant patient relationships that can be challenged by the VAD environment. Therefore, spiritual care practitioners must support these significant relationships of family and community to optimise patient wellbeing by managing relational spiritual concerns while also addressing patients’ internal spiritual concerns. This places the spiritual care practitioner in a nexus of patient relationships, internal concerns, and community systems.
Psychedelic science is growing at a rapid pace, and as evidence accrues, we will most likely see authorization of the use of substances such as psilocybin and MDMA augmenting the effects of psychotherapy in the coming years. Lykos therapeutics (previously called MAPS PBC) recently filed a New Drug Application to the FDA in the US and expects to be able to offer MDMA as a prescribable drug in the treatment of PTSD before the end of 2024 (Lykos Therapeutics, 2024). Several large psilocybin studies are underway and stakeholders aim for a New Drug Application in the coming years (Kozak, Johnson & Aaronson, 2023; Compass pathways, 2022). Psychedelic-assisted psychotherapy shares a number of features with ISTDP. One is that it seeks to unleash the “inner healing intelligence” of the patient similarly to how we in ISTDP aim to help free the patient’s UTA (Mithoefer, 2017; Martling, 2023). Another one is that we optimize the therapeutic setting in order for “breakthrough experiences” to happen (Grof, 1980; Davanloo, 1995). In this article, we’ll get to meet two prominent ISTDP therapists, Reiko Ikemoto-Joseph and Allen Kalpin, who have taken an interest in psychedelic-assisted therapy and are currently working with ketamine-assisted psychotherapy (KAP). I interviewed the two of them in order to provide first-person perspectives on this topic in more detail.
Pathological fear and anxiety are highly debilitating and, despite considerable advances in psychotherapy and pharmacotherapy they remain insufficiently treated in many patients with PTSD, phobias, panic and other anxiety disorders. Increasing preclinical and clinical evidence indicates that pharmacological treatments including cognitive enhancers, when given as adjuncts to psychotherapeutic approaches [cognitive behavioral therapy including extinction-based exposure therapy] enhance treatment efficacy, while using anxiolytics such as benzodiazepines as adjuncts can undermine long-term treatment success. The purpose of this review is to outline the literature showing how pharmacological interventions targeting neurotransmitter systems including serotonin, dopamine, noradrenaline, histamine, glutamate, GABA, cannabinoids, neuropeptides (oxytocin, neuropeptides Y and S, opioids) and other targets (neurotrophins BDNF and FGF2, glucocorticoids, L-type-calcium channels, epigenetic modifications) as well as their downstream signaling pathways, can augment fear extinction and strengthen extinction memory persistently in preclinical models. Particularly promising approaches are discussed in regard to their effects on specific aspects of fear extinction namely, acquisition, consolidation and retrieval, including long-term protection from return of fear (relapse) phenomena like spontaneous recovery, reinstatement and renewal of fear. We also highlight the promising translational value of the preclinial research and the clinical potential of targeting certain neurochemical systems with, for example d-cycloserine, yohimbine, cortisol, and L-DOPA. The current body of research reveals important new insights into the neurobiology and neurochemistry of fear extinction and holds significant promise for pharmacologically-augmented psychotherapy as an improved approach to treat trauma and anxiety-related disorders in a more efficient and persistent way promoting enhanced symptom remission and recovery.
Digital immersive technologies have become increasingly prominent in clinical research and practice, including medical communication and technical education, serious games for health, psychotherapy, and interfaces for neurorehabilitation. The worldwide enthusiasm for digital health and digital therapeutics has prompted the development and testing of numerous applications and interaction methods. Nevertheless, the lack of consistency in the approaches and the peculiarity of the constructed environments contribute to an increasing disparity between the eagerness for new immersive designs and the long-term clinical adoption of these technologies. Several challenges emerge in aligning the different priorities of virtual environment designers and clinicians. This article seeks to examine the utilization and mechanics of medical immersive interfaces based on extended reality and highlight specific design challenges. The transfer of skills from virtual to clinical environments is often confounded by perceptual and attractiveness factors. We argue that a multidisciplinary approach to development and testing, along with a comprehensive acknowledgement of the shared mechanisms that underlie immersive training, are essential for the sustainable integration of extended reality into clinical settings. The present review discusses the application of a multilevel sensory framework to extended reality design, with the aim of developing brain-centered immersive interfaces tailored for therapeutic and educational purposes. Such a framework must include broader design questions, such as the integration of digital technologies into psychosocial care models, clinical validation, and related ethical concerns. We propose that efforts to bridge the virtual gap should include mixed methodologies and neurodesign approaches, integrating user behavioral and physiological feedback into iterative design phases.
The authors discuss the two broad domains of affect-focused and exposure-focused psychotherapies, defining the characteristics and potential advantages and disadvantages of each. The two domains differ in their theoretical approaches, structures, and techniques. Exposure-focused therapies have come to dominate research and practice, leading to the relative neglect of affect-focused therapies. When the two approaches have been examined in well-conducted clinical trials, they generally appear to be equally beneficial for treating common mood, anxiety, and trauma disorders, although further research may better define differential therapeutics. The authors argue for better training in affect awareness and tolerance across psychotherapies and use a brief case vignette to illustrate several aspects of these different approaches.
Kenneth Shinozuka, B. Tabaac, Alejandro Arenas
et al.
Background: After becoming notorious for its use as a party drug in the 1980s, 3,4-methylenedioxy-methampetamine (MDMA), also known by its street names “molly” and “ecstasy,” has emerged as a powerful treatment for post-traumatic stress disorder (PTSD). Areas of Uncertainty: There are extensive data about the risk profile of MDMA. However, the literature is significantly biased. Animal models demonstrating neurotoxic or adverse effects used doses well beyond the range that would be expected in humans (up to 40 mg/kg in rats compared with roughly 1–2 mg/kg in humans). Furthermore, human samples often comprise recreational users who took other substances in addition to MDMA, in uncontrolled settings. Therapeutic Advances: Phase III clinical trials led by the Multidisciplinary Association for Psychedelic Studies (MAPS) have shown that MDMA-assisted psychotherapy has an effect size of d = 0.7–0.91, up to 2–3 times higher than the effect sizes of existing antidepressant treatments. 67%–71% of patients who undergo MDMA-assisted psychotherapy no longer meet the diagnostic criteria for PTSD within 18 weeks. We also describe other promising applications of MDMA-assisted psychotherapy for treating alcohol use disorder, social anxiety, and other psychiatric conditions. Limitations: Thus far, almost all clinical trials on MDMA have been sponsored by a single organization, MAPS. More work is needed to determine whether MDMA-assisted therapy is more effective than existing nonpharmacological treatments such as cognitive behavioral therapy. Conclusions: Phase III trials suggest that MDMA is superior to antidepressant medications for treating PTSD. Now that MAPS has officially requested the Food and Drug Administration to approve MDMA as a treatment for PTSD, legal MDMA-assisted therapy may become available as soon as 2024.