PSYCHOTHERAPY AND PSYCHOSOMATICS心理治疗与心身医学
PSYCHOTHERAPY AND PSYCHOSOMATICS(英文缩写 PSYCHOTHER PSYCHOSOM),ISSN 0033-3190,eISSN 1423-0348,中文译名:心理治疗与心身医学 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-11-01 至 2026-10-31，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 25.617 | Q1 |
| 2022 | 22.800 | Q1 |
| 2023 | 16.300 | Q1 |
| 2024 | 17.400 | Q1 |
| 2025 | 9.000 | Q1 |
PSYCHOTHERAPY AND PSYCHOSOMATICS 最新收录文献
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1. Treatment Expectation across Open-Label Placebo and Pharmacological Contexts: A Randomized Clinical Trial in Chronic Low Back Pain.
PMID:日期:2026-10-01Introduction Chronic low back pain (CLBP) markedly reduces quality of life and remains difficult to treat. Increasing opioid prescriptions highlight the need for effective innovative approaches. This randomized controlled trial aims to investigate whether social observational learning augments analgesic or open-label placebo treatment through treatment expectation modulation in CLBP patients. Methods One hundred thirty patients with CLBP were randomized into a 2 × 2 fully balanced placebo design plus a natural history (NH) control group. Patients received a 3-week treatment with novamine sulfone (analgesic) or open-label placebos (OLP), with follow-up at 3 months. Expectations were manipulated before treatment, using a positive social observational learning video (SoL) or a neutral control video (neutral). Pain intensity (numeric rating scale, NRS 0-10) was the primary outcome. Secondary outcomes included treatment expectations and functional capacity. Results Pain intensity decreased significantly over time in all treatment groups (p < .001), with the smallest reduction in NH. Pain reduction in OLP + SoL and in analgesic + neutral was significantly greater than NH (p < .05). Expectation manipulation produced significant group differences in expected pain relief (p < .05). Higher expected pain relief predicted greater pain reduction after 3 weeks and 3 months (both p < .001). Functional capacity improved over time (p < .001) without consistent group differences. Conclusion Open-label placebos combined with social observational learning produced clinically meaningful analgesia that did not significantly differ from active medication. Treatment expectation represents a key mechanism underlying pain relief in CLBP and calls for further investigation.
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2. Digital rehabilitation using immersive Virtual Reality for Post-COVID fatigue: a double-blind randomized controlled trial.
PMID:日期:2026-09-29Background Post-COVID fatigue is a common and disabling condition with few proven treatments. Immersive virtual reality (VR) exercise therapy may offer a novel rehabilitation approach. We evaluated its efficacy and safety. Methods In this single-center, double-blind, parallel-group trial, German adults meeting WHO criteria for Post-COVID syndrome, with moderate-to-severe fatigue (Fatigue Severity Scale [FSS] ≥36) and no comorbidities better explaining fatigue were randomly assigned (1:1) to a supervised VR exercise therapy or to a supervised conventional exercise therapy. Both interventions comprised 12 sessions of 45min over 6 weeks. The primary endpoint was change in FSS from baseline to post-intervention, analyzed in the intention-to-treat population (DRKS00032059), follow-ups took place after 3 and 12 months post-treatment. Findings Between March 2023, and May 2024, 100 participants were randomized (1:1) to a VR exercise group (VR-EG); or a conventional exercise group (Con-EG). Fatigue severity improved in both groups (VR-EG -8·29; Con. EG -5·27), with no significant between-group difference (mean difference 3·03; 95% CI -1·02 to 7·06). Only the VR-EG exceeded the established minimal important difference (≥6·3 points). Symptom worsening was less frequent with VR-EG than with Con-EG (9% vs 22%). Patient Global Impression of Change ratings favored VR-EG (overall improvement: 76·7% vs 56·5%). Improvements were sustained at 3 and 12 months. Adverse events were mild and transient. Interpretation Immersive VR exercise therapy did not significantly outperform an active comparator on the primary endpoint. However, the VR-EG reached the minimal important difference for fatigue at the group level, showed fewer cases of symptom worsening, and reported more favorable global improvement. Considering the limited treatment options available for Post-COVID fatigue, these findings indicate a promising clinical signal warranting confirmation in larger, multicenter trials.
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4. The Future of Artificial Intelligence and Emerging Technologies in Mental Health: Prospects, Challenges, and a Roadmap for Personalized Treatment.
PMID:日期:2026-09-18Artificial intelligence (AI), alongside emerging digital and neurotechnologies, is increasingly incorporated into mental health care, psychosomatic medicine, and psychotherapy. However, the clinical value of these tools cannot be judged by technical performance alone. These fields are characterized by diagnostic heterogeneity, reliance on language-based and self-reported information, complex biopsychosocial pathways, and substantial interindividual variability in treatment response. Clinically meaningful progress therefore requires integrating technological progress and biological markers with patients' lived experience, personal history, and social context to catalyze person-centered precision assessment, decision-making and intervention. This review examines how AI and emerging technologies may contribute to mental health care across diagnostic assessment, biomarker development, treatment selection, personalized neuromodulation, adaptive interventions, and conversational agents. We argue that AI should support and improve, not replace, clinical assessments and care by integrating complex biopsychosocial data into precision person-centered decision making and intervention. Realizing this potential will require careful attention to clinical validation, safety, equity, commodification and governance. The clinical value of AI and emerging technologies will depend on their responsible integration into context-sensitive, person-centered mental health care. AI has the potential to strengthen diagnostic assessment, inform treatment selection, and expand therapeutic options while preserving the centrality of the human therapeutic alliance. Successful implementation requires combining computational precision with clinical judgment, ethical oversight, and demonstrated clinical benefit to improve clinical outcomes and quality of life.
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6. Menstrual Cycle Informed Psychotherapy: Preliminary findings in Women with Spider Phobia.
PMID:日期:2026-09-05Anxiety disorders are the most frequent mental disorders worldwide. Although exposure therapy is the gold-standard treatment for anxiety disorders, almost half of patients fail to achieve sufficient improvements. While much has been learned about for whom psychotherapy works and why, far less is understood about when it works. Emerging evidence indicates that estradiol and progesterone may affect fear extinction, yet studies examining the effects of menstrual cycle phase on exposure therapy outcomes remain lacking. This study is the first to investigate to what extent biologically informed menstrual cycle phase affects exposure therapy outcomes in women with spider phobia. N=45 women with spider phobia in 1) the early to mid-follicular phase, 2) the mid-luteal phase, or 3) using hormonal contraceptives (HC), participated in a group-based exposure therapy. Symptoms were assessed at baseline, one-week post-therapy, and at 12-14 weeks follow-up, using the Spider Phobia Questionnaire (SPQ), the Fear of Spiders Questionnaire (FSQ), and a behavioral approach test (BAT). Both phobic fear and avoidance behavior improved significantly over time. Although improvement did not differ between menstrual cycle groups, higher progesterone levels on the day of exposure therapy were associated with less improvement in behavioral avoidance. The present findings provide preliminary evidence that ovarian hormones on the day of exposure therapy may affect exposure-based outcomes, particularly reductions in behavioral avoidance. More research in larger samples is needed to further investigate menstrual cycle phase effects in exposure-based treatment. If replicated, the findings would attest to the potential of bio-rhythm informed psychotherapy.
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7. Examining the Contribution of Childhood Maltreatment to the Sex Gap in Depression: Insights from the German National Cohort (NAKO).
PMID:日期:2026-08-31Childhood maltreatment is a major risk factor for depression and may contribute to sex differences in depression prevalence. We examined sex-specific associations between childhood maltreatment and depression and estimated the proportion of depression cases attributable to maltreatment subtypes. We analyzed baseline data from 159,045 participants (49.4% female; aged 19-72) in the German National Cohort (NAKO). Childhood maltreatment was assessed via the Childhood Trauma Screener; depression was assessed via self-reported physician's diagnosis and MINI classification (lifetime) and the PHQ-9 (current). Associations, including sex interactions, were modeled using binary logistic regressions. Disparity decomposition analyses and sex-stratified population attributable fractions (PAFs) quantified the contribution of childhood maltreatment to depression. Childhood maltreatment was associated with increased odds of lifetime (OR = 2.45 [2.38, 2.53]; OR = 2.30 [2.18, 2.43]) and current depression (OR = 2.90 [2.79, 3.02], all p < 0.001). Sex interactions were observed for physician's diagnosis: physical abuse (p = 0.024) and neglect (p < 0.001) had stronger associations in females (OR = 2.74 [2.59, 2.90]; OR = 1.36 [1.28, 1.44]) than males (OR = 2.36 [2.21, 2.52]; OR = 1.08 [1.00, 1.16]), whereas sexual abuse (p = 0.003) showed stronger associations in males (OR = 3.23 [2.91, 3.57]) than females (OR = 2.61 [2.48, 2.75]). Overall, childhood maltreatment accounted for 21.2-26.2% of lifetime and 33.4% of current depression. Population attributable fractions were higher in females than males for lifetime (24.5-28.5% vs. 16.0-20.9%) and current depression (36.1% vs. 28.4%). Emotional subtypes contributed the highest PAFs (up to 10.2%). Childhood maltreatment contributed 19.2-22.4% to the association between sex and depression. Childhood maltreatment accounts for a substantial proportion of depression in both sexes, with stronger overall associations in females. Sex-specific prevention may help reduce depression prevalence.
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8. Back to gut feelings. Latent class analysis of daily perceived health variations identifies later responses to antidepressant treatment.
PMID:日期:2026-08-28Major depressive disorder (MDD) is a prevalent and disabling condition, yet predicting individual response to antidepressants remains difficult. Traditional symptom-based assessments, typically conducted weeks apart, may miss early and dynamic changes. Daily self-reported measures of wellbeing dimensions, particularly via simple tools such as visual analog scales (VAS), could provide ecologically valid and patient-centered markers of early treatment response. This study aimed to identify distinct early trajectories of self-rated health during antidepressant initiation and examine their associations with baseline clinical characteristics and outcomes at 6-8 weeks. In this multicentre naturalistic study, 1536 outpatients with MDD initiating agomelatine monotherapy were recruited across 388 community psychiatry centers. The primary outcome was daily self-rated health during the first 14 days, assessed using the EuroQol VAS. Latent class analysis identified distinct trajectories of self-rated health evolution, with model selection based on Akaike and Bayesian information criteria (AIC/BIC), entropy, and clinical interpretability. A five-class solution was retained, including persistently high or low trajectories, stable intermediate patterns, and one subgroup showing marked early improvement despite low baseline values. Trajectories were associated with baseline clinical severity and different symptomatic and functional outcomes at 6-8 weeks. Patients with rapid early improvement had the highest remission rates, whereas those with severe baseline symptoms and limited early improvement had the poorest outcomes. These findings support the clinical utility of early wellbeing trajectories for personalized monitoring during antidepressant treatment.
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9. The impact of Trauma-Focused Cognitive Behaviour Therapy for psychosis on post-traumatic stress symptoms in daily life: ESM outcomes of the STAR Trial.
PMID:日期:2026-08-27People with psychosis have high rates of post-traumatic stress-disorder (PTSD). The STAR (Study of Trauma And Recovery) randomised controlled trial found that a Trauma-Focused therapy integrated with Cognitive Behaviour Therapy for psychosis (TF-CBTp) added to Treatment-As-Usual (TAU) reduced PTSD symptoms in people with psychosis compared to TAU only. We hypothesized that TF-CBTp would also reduce PTSD symptoms in daily life, using Experience Sampling Methodology (ESM), which would be associated with improvements on a clinical measure of PTSD. Participants were adults with PTSD and schizophrenia-spectrum diagnoses, a subsample of the STAR trial (N=153; TF-CBTp+TAU=73, TAU=80). Participants completed ESM assessments of intrusive memories, hyperarousal, dissociation, avoidance and negative trauma-related cognitions through a smartphone app multiple times daily over six days, at baseline and 9-months post-randomisation (end-of-therapy). No between-group differences were found in ESM measures of momentary PTSD symptoms at 9-months. Significant timepoint×therapy interactions indicated greater decrease over time in hyperarousal, negative cognitions, and avoidance, and in variability of intrusive memories, in TF-CBTp+TAU compared to TAU. ESM measures at 9-months were significantly associated with improvements on the Clinician-Administered PTSD Scale for DSM-5. While findings are tentatively in favour of TF-CBTp, the robust reductions in PTSD symptoms found in the STAR trial using retrospective outcome measures were not fully replicated with ESM, suggesting these methodologies may be capturing different features of symptom expression and processes of therapeutic change. Including both approaches in future research could provide a fuller picture of therapy effects on 'in-the-moment' versus reflective reports of experiences.
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10. Baseline prediction of two-year prevention and remission of anxiety, depression, and eating disorders in college students receiving a digital guided self-help intervention: derivation and external validation of a machine learning algorithm across 26 population-based cohorts.
PMID:日期:2026-08-24We examined whether machine learning identified baseline variables that predicted two-year prevention and remission from anxiety, depression, and eating disorders following digital cognitive-behavioral therapy guided self-help (D-CBTgsh). Undergraduates at risk for or meeting criteria for anxiety, depression, and eating disorders who were randomized to population-based screening and D-CBTgsh were examined. A five-step hybrid feature selection strategy reduced 863 baseline questionnaire items to 37 spanning demographics, mental health problems, treatment motivation, and treatment targets. Five supervised machine learning algorithms were trained and tested using nested cross-validation among students from 13 U.S. colleges (n = 1472) to discriminate who did versus did not achieve two-year prevention and remission of all anxiety, depression, and eating disorders. External validation was conducted in a separate set of 13 U.S. colleges (n = 823). When externally validated, random forest outperformed all models in discriminative power, calibration, and clinical utility. Predictors of no disorders at two years included lower levels of behavioral avoidance, generalized anxiety interference, social fear, social anxiety interference, depressed mood, fear of observation, number of worry topics, perseverative thinking, and binge eating, along with higher feelings of calm/peacefulness, perceived need for treatment, and intention to seek help. Demographic predictors of no disorders were being male at birth, fewer financial difficulties, and a lower current body mass index. This predictive algorithm, using 37 single items, developed a scalable self-report measure that could be readily adopted by college campuses to help optimize and scale service delivery across campuses.