Tag: pubmed

Psychiatr Rehabil J. 2026 Jul 6. doi: 10.1037/prj0000686. Online ahead of print.

ABSTRACT

OBJECTIVE: As mental health systems worldwide shift toward supporting personal recovery, valid tools are needed to evaluate and guide service transformation. The Recovery Self-Assessment Scale (RSA-R) is the leading patient-reported measure of recovery-oriented care. This study aimed to adapt the RSA-R to the French context and assess its psychometric properties.

METHODS: The RSA-R was translated and administered online to 169 adults with serious mental illness. Exploratory factor analyses were conducted to assess the structural validity of the French RSA-R French Recovery Self-Assessment-Revised (RSAR-Fr), and internal consistency statistics were computed. Multiple linear regression analysis tested the RSAR-Fr association with a measure of personal recovery (the French Questionnaire about the Process of Recovery). Items were mapped onto an established framework of recovery-oriented care to assess content validity.

RESULTS: Exploratory factor analyses supported a concise three-factor model: The person-centered, organizational engagement, and social inclusion dimensions accounted for 46.3% of the variance, with excellent internal consistencies (McDonald’s ω values ranging from .92 to .94). Hypotheses for construct validity were not verified, as RSAR-Fr subscales did not significantly predict personal recovery. Expert review supported content validity, confirming the items’ relevance and comprehensiveness.

CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: The RSAR-Fr demonstrated adequate psychometric properties, addressing known concerns regarding the scale’s dimensionality. Despite sample limitations and the absence of test-retest data, these findings highlight the utility of the RSAR-Fr in measuring recovery-oriented care from the perspective of service users. Routine use of the RSAR-Fr may strengthen the recognition of lived experience within services and support improvements in recovery-oriented practices. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PMID:42406462 | DOI:10.1037/prj0000686

Psychol Methods. 2026 Jul 6. doi: 10.1037/met0000841. Online ahead of print.

ABSTRACT

Selective reporting bias arises when findings from primary research studies are incompletely reported and where the likelihood that a result is reported depends on the magnitude or statistical significance of the effect. When applied to selectively reported data, conventional meta-analytic models can produce systematically biased parameter estimates. Various statistical methods have been proposed for dealing with selective reporting in univariate meta-analysis, where each primary study contributes a single effect size estimate. However, fewer methods have been developed for handling selective reporting and publication bias in meta-analysis with dependent effect sizes, which are a common feature of meta-analyses in psychology. In this tutorial, we provide a guide for how to investigate potential selective reporting in meta-analyses of dependent effects, focusing on diagnosis and correction of selection reporting bias. We review several recently developed methods including a regression-based adjustment technique, a step-function selection model, and a sensitivity analysis approach. We demonstrate the implementation of these methods in the R statistical environment using data from two recent meta-analyses as examples. We discuss the application and interpretation of the methods, highlighting their strengths and limitations. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PMID:42406458 | DOI:10.1037/met0000841

Psychol Methods. 2026 Jul 6. doi: 10.1037/met0000850. Online ahead of print.

ABSTRACT

Understanding variability is a key focus in many areas of psychological research, with growing interest in modeling individual- and group-level variability. Although multilevel models such as heterogeneous variance models (HVMs) and Mixed-Effects Location-Scale models have been used to capture these dynamics, they typically rely on linear assumptions and restrict temporal changes in variability to a single level. Recent calls for nonlinear approaches in psychology highlight the need for more flexible models that can better account for complex, dynamic processes. This article introduces the use of Gaussian processes (GPs) within the framework of HVMs to address these limitations. By incorporating GPs in HVMs, we allow for the modeling of nonlinear variability across multiple levels, including temporal dynamics at both the individual and group levels. We demonstrate the benefits of this approach in two empirical applications. Our findings show that using GPs provides an improved model fit compared with traditional linear methods and highlight the utility of GPs in variance modeling, offering new possibilities for studying dynamic and emergent processes in psychological and social science research. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PMID:42406457 | DOI:10.1037/met0000850

Am Psychol. 2026 Jul-Aug;81(5):714-715. doi: 10.1037/amp0001751.

ABSTRACT

Presents a summary report of journal operations from 2025. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PMID:42406449 | DOI:10.1037/amp0001751

J Couns Psychol. 2026 Jul 6. doi: 10.1037/cou0000876. Online ahead of print.

ABSTRACT

Measurement-based care has been shown to be an efficacious way to improve therapy outcomes. The use of advanced statistical approaches may assist in optimizing the feedback therapists receive. That is, algorithms developed within measurement-based care programs enhance their performance in predicting therapy outcomes. In this proof-of-concept article, we analyzed data from 9,591 clients who were treated at university counseling centers and completed the Behavioral Health Measure on a reoccurring basis. The sample included male and female clients of diverse ethnicities. We utilized two AI-derived approaches: ant colony optimization algorithm to derive a content-valid item subset that maximized the prediction of clinically significant change status, followed by logistic Lasso regression to identify the most influential item-level predictors. Early in treatment (i.e., the first three to five sessions), Behavioral Health Measure items were tested to determine which were the best predictors of therapy outcomes. The results demonstrated that five items, including self-esteem, general anxiety, substance use, cognitive attention, and overall work/school life purpose, were strong predictors of outcomes over the course of early treatment. These findings suggest that measurement-based care platforms or programs might benefit from more detailed attention to specific signals or patterns in the data that assist therapists and clients monitoring treatment progress. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PMID:42406433 | DOI:10.1037/cou0000876

J Occup Health Psychol. 2026 Jul 6. doi: 10.1037/ocp0000437. Online ahead of print.

ABSTRACT

The present study builds on conservation of resources theory and the concept of the recovery paradox (Hobfoll, 1989; Sonnentag, 2018) and responds to repeated calls to (a) study recovery processes over midterm time frames of weeks and (b) investigate directions of effects in recovery-well-being relations. Doing so, we employed the recovery activity characteristics approach, a dimensional framework for examining the underlying attributes of recovery activities (physical, social, creative, mental, spiritual, virtual, and outdoor dimensions) and examined the reciprocal lagged relationships between recovery activities and two indicators of employee well-being-emotional exhaustion and work engagement. We use preregistered data from 333 participants answering weekly surveys over an 8-week period to explore how recovery dimensions influence and are influenced by emotional exhaustion and work engagement using a random intercept cross-lagged panel model. Across dimensions, we found little evidence for consistent week-to-week lagged effects between recovery activities and well-being in either direction. One association indicated that higher-than-usual engagement in creative activities was followed by higher work engagement the subsequent week; however, given the number of statistical tests conducted, this finding may reflect a chance result and therefore requires independent replication. Overall, the findings suggest that recovery processes may be temporally bounded, with limited support for delayed within-person carryover effects across working weeks. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PMID:42406432 | DOI:10.1037/ocp0000437

JAMA Netw Open. 2026 Jul 1;9(7):e2621592. doi: 10.1001/jamanetworkopen.2026.21592.

ABSTRACT

IMPORTANCE: Transcranial pulse stimulation is a novel noninvasive brain stimulation technique with preliminary evidence of antidepressant effects; however, its efficacy has not been tested in a double-blind, sham-controlled randomized clinical trial.

OBJECTIVE: To examine the antidepressant efficacy of transcranial pulse stimulation for major depressive disorder.

DESIGN, SETTING, AND PARTICIPANTS: This 2-arm, parallel-design, double-blind, sham-controlled randomized clinical trial was conducted between June 1, 2023, and October 31, 2025, at the Hong Kong Polytechnic University. Patients with major depressive disorder and a Hamilton Depression Rating Scale score of 14 or higher were convenience sampled and enrolled.

INTERVENTIONS: Participants were randomized 1:1 to receive 12 sessions (1000 pulses per session) of active or sham transcranial pulse stimulation targeting the left dorsolateral prefrontal cortex during 4 weeks.

MAIN OUTCOMES AND MEASURES: Change in Montgomery-Åsberg Depression Rating Scale score (range, 0 [no depression] to 60 [severe depression], with a change of at least 6 indicating minimal change and 12 or more indicating substantial change) after 12 treatment sessions.

RESULTS: This modified intention-to-treat analysis included 80 participants (mean [SD] age, 35.6 [11.7] years; mean [SD] years of education, 15.5 [3.3]; 53 females), with 74 completing treatment and 6 withdrawing (2 from sham due to adverse effects); 40 participants were randomized to the active group and 40 to the sham group. The active group demonstrated a statistically significantly greater reduction in Montgomery-Åsberg Depression Rating Scale scores than the sham group (mean difference, -4.19; 95% CI, -8.33 to -0.04; P = .048; Hedges g = 0.45). Resting-state functional magnetic resonance imaging analyses found that, compared with the sham stimulation, active stimulation significantly enhanced functional connectivity within the left dorsolateral prefrontal cortex (mean difference, 0.11; 95% CI, 0.03-0.19; P = .009); between the left dorsolateral prefrontal cortex and left orbitofrontal, superior medial prefrontal, and pregenual anterior cingulate cortices (mean difference, 0.11; 95% CI, 0.05-0.17; P < .001); and between the left dorsolateral prefrontal cortex and posterior cingulate cortex and bilateral precuneus and calcarine cortex (mean difference, 0.08; 95% CI, 0.01-0.16; P = .02).

CONCLUSIONS AND RELEVANCE: In this randomized clinical trial of transcranial pulse stimulation, the treatment was safe, well tolerated, and associated with antidepressant effects and modulation of multiple depression-relevant brain circuits. These findings provide a rationale for future studies to optimize therapeutic efficacy by increasing the number of treatment sessions and refining targeting strategies.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05551585.

PMID:42406402 | DOI:10.1001/jamanetworkopen.2026.21592

JAMA Netw Open. 2026 Jul 1;9(7):e2621713. doi: 10.1001/jamanetworkopen.2026.21713.

ABSTRACT

IMPORTANCE: Most diabetes care is managed in primary care settings, which represent a critical yet underutilized site for continuous glucose monitoring (CGM) adoption. Whether CGM initiation by primary care clinicians improves glycemic outcomes and reduces acute health care utilization remains understudied.

OBJECTIVE: To evaluate the association of primary care-initiated CGM with changes in hemoglobin A1c (HbA1c) levels and rates of hospitalizations and emergency department (ED) visits among adults with insulin-treated diabetes.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study was performed at 18 primary care clinics within Montefiore Medical Center, a large safety-net health system in the Bronx, New York. Adults 18 years or older with any insulin-treated diabetes who had at least 1 primary care visit between August 1, 2022, and August 1, 2025, were included. Patients were excluded if they were uninsured, if they had a CGM prescription in the prior 2 years, or if their first CGM during follow-up was prescribed outside primary care.

EXPOSURE: First CGM prescription by a primary care clinician.

MAIN OUTCOMES AND MEASURES: The primary outcomes were HbA1c level trajectories, which were analyzed using mixed-effects models, and hospitalizations and ED visits, which were analyzed using recurrent event frailty models.

RESULTS: The study included 8502 insulin-treated CGM-naive adult patients with diabetes (mean [SD] age, 62.3 [14.6] years; 4764 [56.0%] female; 3618 [42.6%] with Medicare and 2854 [33.6%] with Medicaid coverage). Of these, 2392 patients (28.1%) were prescribed CGM by primary care clinicians. Patients who initiated CGM were younger, more often English-speaking and commercially insured, and had higher baseline HbA1c levels and more microvascular complications. At 12 months, HbA1c levels decreased by 0.66 (95% CI, 0.57-0.75) percentage points (pp) in patients who initiated CGM vs 0.17 (95% CI, 0.08-0.27) pp in those who did not, with a between-group difference of -0.49 (95% CI -0.62 to -0.35) pp. CGM initiation was associated with lower risk of recurrent hospitalizations (hazard ratio, 0.87 [95% CI, 0.77-0.98]) and ED visits (hazard ratio, 0.82 [95% CI, 0.74-0.91]).

CONCLUSIONS AND RELEVANCE: In this cohort study of adults with insulin-treated diabetes, initiation of CGM by primary care clinicians was associated with clinically meaningful improvements in HbA1c and significant reductions in recurrent hospitalizations and ED visits. These findings support expanding CGM implementation in primary care settings as a scalable strategy to improve diabetes outcomes and reduce acute care utilization, particularly in underserved populations.

PMID:42406400 | DOI:10.1001/jamanetworkopen.2026.21713

JAMA Netw Open. 2026 Jul 1;9(7):e2621731. doi: 10.1001/jamanetworkopen.2026.21731.

ABSTRACT

IMPORTANCE: Postacute sequelae of SARS-CoV-2 infection include fatigue, respiratory symptoms, and cognitive dysfunction. However, the extent to which these symptoms contribute to increased health care utilization and spending among Medicare beneficiaries remains unclear.

OBJECTIVE: To quantify differences in postacute symptoms and health care utilization and spending between traditional Medicare beneficiaries with COVID-19 and matched control beneficiaries without COVID-19.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study used traditional Medicare claims from February 2020 through November 2022. Beneficiaries with a documented COVID-19 diagnosis were matched 1:5 to beneficiaries without COVID-19 based on demographic and clinical characteristics. Four variant-defined cohorts (original strain and Alpha, Delta, and Omicron variants) were analyzed. Follow-up extended through 40 weeks after diagnosis. Data were analyzed from February 2020 to November 2022.

MAIN OUTCOMES AND MEASURES: Diagnosis of 21 postacute COVID-19 symptoms, all-cause health care utilization, and Medicare spending were compared between those with COVID-19 and matched control beneficiaries using logistic and linear regression models adjusted for demographic and clinical covariates.

RESULTS: The cohort study included 937 077 Medicare beneficiaries with COVID-19 and 4 808 573 matched control beneficiaries without COVID-19 (3 109 789 females [54.1%]), with most beneficiaries (4 880 497 [84.9%]) aged 65 years or older. During the acute phase of infection (diagnosis week), beneficiaries with COVID-19 were 41.71 (95% CI, 41.62-41.91) percentage points more likely to receive at least 1 postacute symptom diagnosis than control beneficiaries. This difference declined to 5.22 (95% CI, 5.11-5.32) percentage points during weeks 1 to 12 and to 1.94 (95% CI, 1.81-2.05) percentage points during weeks 13 to 40. Medicare spending was $7933.13 higher (95% CI, $7904.12-$7962.14) in the acute phase, decreasing to $232.31 (95% CI, $230.11-$234.14) per week in weeks 1 to 12 and to $28.21 (95% CI, $27.11-$30.13) per week in weeks 13 to 40. Differences in health care utilization followed a similar pattern, decreasing to 0.05 (95% CI, 0.05-0.06) visits per week in weeks 1 to 12 and to 0.03 (95% CI, 0.02-0.03) visits per week in weeks 13 to 40.

CONCLUSIONS AND RELEVANCE: In this cohort study of traditional Medicare beneficiaries across major COVID-19 variants, postacute symptom diagnoses and health care utilization and spending were substantially higher in the acute phase of COVID-19 but diminished over time, approaching levels observed in matched control beneficiaries without COVID-19 by 3 months after infection. These findings suggest limited long-term excess health care utilization or spending attributable to COVID-19 infection among older adults.

PMID:42406399 | DOI:10.1001/jamanetworkopen.2026.21731

JAMA Netw Open. 2026 Jul 1;9(7):e2621741. doi: 10.1001/jamanetworkopen.2026.21741.

ABSTRACT

IMPORTANCE: Metastatic prostate cancer (PC) incidence has increased in US men, partly due to changes in prostate-specific antigen (PSA) screening recommendations. However, few studies have examined contemporary PSA screening practices in large US health care systems.

OBJECTIVE: To describe and examine contemporary PSA testing practices associated with metastatic PC incidence.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study included veterans within the Veterans Health Administration that received a prostate needle biopsy (PNB) between January 2015 and December 2023 with follow-up through 2024, excluding those with a history of PC. Data were analyzed between July 1, 2023, and November 6, 2025.

EXPOSURES: PSA tests were retrieved from the VA Corporate Data Warehouse and categorized by age at first VA PSA (<50, 50-59, and ≥60 years) and by longest interval between consecutive VA PSA tests in the 5 years before PNB (≤24 vs >24 months). Clinical, laboratory, pathological, demographic, and census block group-level socioeconomic status data were obtained from the VA Multi-OMICS Analysis Platform for Prostate Cancer database.

MAIN OUTCOMES AND MEASURES: Multivariable Cox models estimated hazard ratios (HRs) from time of first VA PSA to first PNB, evaluated risk of metastatic (regional or distant) vs localized PC or benign diagnosis, and adjusted for sociodemographic and clinical covariates.

RESULTS: There were 103 067 participants of whom 20 233 (19.6%) were younger than 50 years at first PSA, 31 546 (30.6%) were non-Hispanic Black, 58 264 (56.5%) were non-Hispanic White, and 13 277 (12.9%) had other race or ethnicity. Of all participants, 22 190 (21.5%) had a first PSA value of 1 ng/mL or less, 52 939 (51.4%) had a screening interval of 24 months or less, and 3773 (3.7%) were diagnosed with metastatic PC at time of PNB. Compared with men aged younger than 50 years at first PSA, those aged 50 to 59 years (adjusted HR [aHR], 1.27; 95% CI, 1.24-1.29) and 60 years or older (aHR, 2.37; 95% CI, 2.33-2.42) had higher risk of metastatic PC. Men with longer screening intervals had higher risk of metastatic PC (aHR, 1.14; 95% CI, 1.13-1.16). Men aged younger than 50 years with shorter screening intervals had lower rates of metastatic PC (adjusted risk ratio, 0.10; 95% CI, 0.09-0.12) compared with men aged 60 years or older with longer screening intervals.

CONCLUSIONS AND RELEVANCE: In this cohort study, few veterans had the most favorable combinations of screening factors in relation to metastatic PC, suggesting potential for further screening optimization.

PMID:42406398 | DOI:10.1001/jamanetworkopen.2026.21741