Psychiatric research and clinical practice最新文献

{"title":"Co‐Locating Obstetrics and Addiction Medicine Clinics to Improve Attendance in Services for Pregnant People with Opioid Use Disorder","authors":"Cara A. Poland, Julia M. Shadur, Morgan Cinader, J. Felton","doi":"10.1176/appi.prcp.20230033","DOIUrl":"https://doi.org/10.1176/appi.prcp.20230033","url":null,"abstract":"","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":"2 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138585660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving the Management of Maternal Mental Health with Digital Health Care","authors":"Constance Guille, Natalie Henrich, Alison K. Brinson, Hannah R. Jahnke","doi":"10.1176/appi.prcp.20230035","DOIUrl":"https://doi.org/10.1176/appi.prcp.20230035","url":null,"abstract":"Digital health solutions have the potential to improve maternal mental health care. The objective of this study is to determine if utilization of a digital health platform, Maven, is associated with improved management of mental health among peripartum people with a history of mental health disorders and determine which components of utilization associate with maternal mental health outcomes.Participants in this retrospective cohort analysis (n = 1561) accessed Maven as an employer‐sponsored health benefit and enrolled during their pregnancy and delivered from January 2020 through September 2022. Participants completed health surveys at enrollment, including history of a mood disorder, and post‐delivery. Maven includes online articles, asynchronous and synchronous virtual classes, app‐based mental health screenings, access to allied health professional and maternity care providers via messaging and telehealth appointments. Quantile g–computation was used to estimate the effects of multi‐utilization exposures on reports of postpartum depression (PPD) and management of mental health.Multi‐utilization exposure mixture models demonstrated that increasing use of digital resources by one quartile is associated with an increased odds of reporting that Maven helped users manage their mental health (aOR: 12.58 [95% CI: 6.74, 23.48]) and was not associated with self‐reported incidence of PPD (aOR: 1.30 [95% CI: 0.52, 3.27]). Care advocate appointments, provider messages, and article reads were positively associated with improved mental health management.Digital health platforms, such as Maven, may play an important role in managing maternal mental health conditions among pregnant and postpartum people at high risk for PPD.","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139212208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing Challenges in Residential Facilities: Promoting Human Rights and Recovery While Pursuing Functional Autonomy","authors":"Alessandra Martinelli, Elisa Dal Corso, Tecla Pozzan, Doriana Cristofalo, Chiara Bonetto, Mirella Ruggeri","doi":"10.1176/appi.prcp.20230034","DOIUrl":"https://doi.org/10.1176/appi.prcp.20230034","url":null,"abstract":"Objective Italian residential facilities (RFs) aim to promote human rights and recovery for individuals with severe mental disorders. Italian RFs can be distinguished into five main types: high‐intensity rehabilitation (RF1), medium‐intensity rehabilitation (RF2), medium‐level support (RF3.1), high‐level support (RF3.2), low‐level support (RF3.3). This study aimed to assess the effectiveness of Italian RFs in achieving functional autonomy while upholding human rights and recovery. Methods Data on socio‐demographics, clinical information, patient and staff assessments of functional autonomy, types of interventions, and RF performance in various domains were collected in a pilot study with a cross‐sectional design. Descriptive and inferential analyses were conducted. Results Twelve RFs and 113 patients participated, with varying proportions in each RF type. RF1 patients were the oldest (p < 0.001) with the lowest functional autonomy (p < 0.001), while RF2 patients were the youngest (p < 0.001) with the lowest hospitalization rate (p < 0.001). RF3.1 patients had the highest employment rate (p = 0.024), while RF3.2 had the lowest employment rate (p = 0.024) and the longest service contact (p < 0.001). RF3.3 users had the highest functional autonomy (p < 0.001). The highest functional autonomy was in self‐care which received the highest focus in objectives and interventions. Patients rated their functional autonomy higher than professionals (p < 0.001). RFs excelled in the “human rights” and “social interface” domains but performed poorly in “recovery‐based practice,” with RF1 having the lowest performance and RF3.3 the highest. Conclusions This pilot study suggests that Italian RFs generally aligne with their mission and human rights principles, but personalizing interventions and implementing recovery‐oriented practices face challenges.","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":"8 24","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135390968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Use of Holographic Memory Resolution® to Improve the Physical and Biopsychosocial Symptoms of Chronic Pain: A Feasibility, Mixed Methods Study","authors":"Mary D. Gaddy, Brent Baum, Becky Kiesow, Nicholas C. Coombs, Emily R. Beamon, Yvonne Mullowney, Geoffrey C. Williams, Jeannine M. Brant","doi":"10.1176/appi.prcp.20230028","DOIUrl":"https://doi.org/10.1176/appi.prcp.20230028","url":null,"abstract":"Objective Holographic Memory Resolution® (HMR®), a mind‐based therapy, has been used for decades as a nonpharmacologic intervention for trauma imprinting to alleviate depression, anxiety, pain, and post‐traumatic stress disorder (PTSD). No clinical studies were found examining the use of HMR®. This study examined the feasibility and preliminary efficacy of administering HMR® to individuals experiencing chronic pain and related biopsychosocial symptoms. Methods A feasibility, mixed‐methods study was conducted between October 2021 and July 2022 and included four HMR® sessions over 1–12 weeks. A convenience sample was comprised of 60 adults suffering from chronic physical or emotional pain of 4+ (0–10 scale) over 6+ months at two clinics in the U.S. Baseline and subsequent surveys after sessions 2, 3, and 4 assessed symptom response. Symptoms were longitudinally measured via self‐report of depression, anxiety, somatic symptom burden, PTSD, and vitality. Results 73% completed all four sessions, demonstrating feasibility. Ages ranged from 19 to 80 years, 85% were female, and 87% were Caucasian. 52% reported high risk for toxic stress. Four symptoms decreased significantly: depression (p = 0.05), anxiety (p = 0.03), symptom burden (p < 0.01) and PTSD symptoms (p = 0.01); vitality improved. Conclusions HMR® may be a feasible intervention to address chronic pain and accompanying biopsychosocial symptoms; a randomized controlled trial is the next step to measure efficacy. Unlike other mind‐based therapies, HMR® participants use their own internal language for identification and resolution of the pain. The trauma imprinting can then be gently addressed, and the memory‐based components of pain resolved or reduced, which empowers participants to improve their well‐being. Trial registration ClinicalTrials.gov Identifier: NCT05001399.","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135016062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of Two Diagnostic Assessments for Opioid and Stimulant Use Disorder for Use by Non-Clinicians.","authors":"Angela Di Paola, David Farabee, Sandra A Springer","doi":"10.1176/appi.prcp.20230022","DOIUrl":"10.1176/appi.prcp.20230022","url":null,"abstract":"<p><strong>Objective: </strong>The United States is in the fourth wave of the opioid epidemic marked by the increase in fentanyl and co-occurring stimulant use related overdose deaths. Measures are needed to quickly diagnose opioid and stimulant use disorders, yet current traditional diagnostic assessments pose barriers to providing rapid diagnoses.</p><p><strong>Methods: </strong>This study aimed to (1) validate an updated version of the Rapid Opioid Dependence Screen (RODS) from DSM-IV criteria for opioid dependence to the now DSM-5 moderate-to-severe opioid use disorder, the Rapid Opioid Use Disorder Assessment (ROUDA); and (2) create and validate the Rapid Stimulant Use Disorder Assessment to DSM-5 stimulant use disorder (RSUDA) when compared to the substance use disorder module from the DSM-5 version of the Mini International Neuropsychiatric Interview.</p><p><strong>Results: </strong>One-hundred and fifty adults completed study assessments, 122 reported opioid misuse and 140 reported stimulant misuse within their lifetime. The ROUDA had a sensitivity of 82.5% (95% confidence interval [CI] 75.7, 89.2), specificity of 100.0% (95% CI: 100, 100), and strong internal consistency <i>α</i> = 0.94. The RSUDA had similarly high sensitivity (83.8%, 95% CI: 77.7, 89.9), specificity (91.4%, 95% CI: 86.8, 96.1), and internal consistency <i>α</i> = 0.87. The ROUDA and RSUDA are efficient and valid measures that can be administered in various settings by non-clinical staff to rapidly diagnose opioid and stimulant use disorders and allow for immediate treatment and harm reduction interventions.</p><p><strong>Conclusions: </strong>The ROUDA and RSUDA are efficient and valid measures that can be administered by non-clinicians to rapidly diagnose opioid and stimulant use disorders.</p>","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":"5 3","pages":"78-83"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/f1/70/RCP2-5-78.PMC10499189.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10271442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Affecting Antidepressant Response Trajectories: A Veterans Affairs Augmentation and Switching Treatments for Improving Depression Outcomes Trial Report.","authors":"Paul B Hicks, Varadan Sevilimedu, Gary R Johnson, Ilanit R Tal, Peijun Chen, Lori L Davis, Julia E Vertrees, Sidney Zisook, Somaia Mohamed","doi":"10.1176/appi.prcp.20230017","DOIUrl":"10.1176/appi.prcp.20230017","url":null,"abstract":"<p><strong>Background: </strong>In this secondary analysis of the VA Augmentation and Switching Treatments for Improving Depression Outcomes (VAST-D) study we used antidepressant response trajectories to assess the association of treatment and multiple clinical/demographic factors with the probability of response.</p><p><strong>Methods: </strong>Using data from VAST-D, a multi-site, randomized, single-blind trial with parallel-assignment to one of three treatment interventions in 1522 Veterans whose major depressive disorder was unresponsive to at least one antidepressant trial, we evaluated response patterns using group-based trajectory modeling (GBTM). A weighted multinomial logistic regression analysis with backward elimination and additional exploratory analyses were performed to evaluate the association of multiple clinical/demographic factors with the probability of inclusion into specific trajectories. Additional exploratory analyses were used to identify factors associated with trajectory group membership that could have been missed in the primary analysis.</p><p><strong>Results: </strong>GBTM showed the best fit for depression symptom change was comprised of six trajectories, with some trajectories demonstrating minimal improvement and others showing a high probability of remission. High baseline depression and anxiety severity scores decreased, and early improvement increased, the likelihood of inclusion into the most responsive trajectory in both the GBTM and exploratory analyses.</p><p><strong>Conclusion: </strong>While multiple factors influence responsiveness, the probability of inclusion into a specific depression symptom trajectory is most strongly influenced by three factors: baseline depression, baseline anxiety, and the presence of early improvement.</p>","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":" ","pages":"131-143"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698706/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45209978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Associated with Depressive and Anxiety Symptom Trajectories Across Pregnancy and Postpartum in Selective Serotonin Reuptake Inhibitor-Treated Individuals.","authors":"Jessica L W Mayer, Amy Yang, Katherine L Wisner, Catherine S Stika, Jacqueline K Gollan","doi":"10.1176/appi.prcp.20230010","DOIUrl":"10.1176/appi.prcp.20230010","url":null,"abstract":"<p><strong>Objective: </strong>The primary purpose of this article is to identify factors that are associated with worsening mood and anxiety trajectories across the perinatal period among pregnant individuals receiving treatment with a selective-serotonin reupdate inhibitor.</p><p><strong>Methods: </strong>This secondary analysis of primary data from the original article, Trajectories of Depressive and Anxiety Symptoms Across Pregnancy and Postpartum in Selective Serotonin Reuptake Inhibitor-Treated Women, explores if number of lifetime episodes of depression as characterized in the Mini-International Neuropsychiatric Interview, elevated maternal adverse childhood experiences (ACE) score, or specific obstetric or neonatal factors from the Peripartum Events Scale (PES) were associated with membership in trajectory groups with the highest symptom burden.</p><p><strong>Results: </strong>No difference in ACE scores or obstetric or neonatal factors were associated with membership in the trajectory groups using Wilcoxon rank sum tests and bi-variable logistic regression. The trajectory group with the highest anxiety symptom burden experienced more lifetime episodes of depression compared to other groups (odds ratio = 1.17, 95% confidence intervals, 1.02-1.34, <i>p</i> = 0.03).</p><p><strong>Conclusions: </strong>Congruent with other studies, we found a high prevalence of co-occurring mood and anxiety symptoms and that past episodes of depression remain an important historical risk factor for perinatal symptom burden. This reinforces that past experiences of depression increase not only the risk of future symptoms but also higher symptom burden during antidepressant treatment.</p>","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":" ","pages":"144-147"},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698702/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49170708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simple and Objective Evaluation Items for the Prognosis and Mortality of Delirium in Real-World Clinical Practice: A Preliminary Retrospective Study.","authors":"Yuzuru Shibuya, Ryota Kobayashi, Takuma Numazawa, Toyoki Toyoshima, Hiroshi Hayashi, Toshimasa Sone, Daichi Morioka, Akihito Suzuki, Shinobu Kawakatsu","doi":"10.1176/appi.prcp.20230006","DOIUrl":"10.1176/appi.prcp.20230006","url":null,"abstract":"<p><strong>Objective: </strong>Identifying factors associated with poor outcomes in patients with delirium is important for predicting prognosis. This retrospective study developed an easy and objective cognitive function measurement scale that can predict the prognosis and mortality related to delirium.</p><p><strong>Methods: </strong>Fifty-five patients aged ≥65 years and diagnosed with delirium were included. Objective data regarding attention and orientation related to time and place were extracted from their medical records during the first consultation, and in total, six points were evaluated. The patients were categorized into high and low cognitive function (LCF) groups. The severity at the first visit and 1-week post-treatment was evaluated using the Clinical Global Impressions-Severity scale. Outcomes (survival or death) at 6 months from the initial visit were evaluated by reviewing medical records.</p><p><strong>Results: </strong>Although the Clinical Global Impressions-Severity score at the first visit was not significantly different between the two groups, 1 week after treatment, it was significantly lower in the high cognitive function (HCF) group than in the LCF group. Regarding the outcome (survival or death) after 6 months, the LCF group had significantly higher mortality than the HCF group. A multivariate logistic regression analysis revealed the same result (OR = 17.049, 95% CI = 2.415-120.373, <i>p</i> = 0.004).</p><p><strong>Conclusion: </strong>A simple cognitive assessment of attention and orientation may help predict unfavorable outcomes, including mortality, in patients with delirium.</p>","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":" ","pages":"126-130"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45373479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exposure to Alcohol-Related Content on Social-Media.","authors":"Kathryn Janiuk, Nasim Maleki","doi":"10.1176/appi.prcp.20230009","DOIUrl":"10.1176/appi.prcp.20230009","url":null,"abstract":"<p><strong>Objective: </strong>Exposure to alcohol-related content is unavoidable on social media. In this study level of exposure to alcohol marketing content on Twitter and Instagram for those in recovery was examined, and the effectiveness of privacy settings to mitigate exposing content was assessed.</p><p><strong>Methods: </strong>Four fictitious accounts were created on Instagram and Twitter in a case-control design in Spring 2022. All accounts followed 19 alcohol brands, with two accounts (1 male, 1 female) following only alcohol brand accounts while the other two (1 male, 1 female) additionally followed recovery resources. Four weeks of data collection were done with default privacy and advertisement settings, followed by two additional weeks of data collection with advertisement and privacy settings for blocking alcohol content.</p><p><strong>Results: </strong>Privacy settings did not help with blocking the alcoholic brand-related photographic content on either platform, meaning that the accounts received the same amount of alcohol-related content from the accounts they were following with and without changing the privacy settings. However, Twitter algorithms were more effective in suppressing alcohol-related content for accounts following recovery resources and alcohol brands.</p><p><strong>Conclusions: </strong>These results suggest that risks of exposure to triggering/cueing photographic alcohol content may outweigh the benefits of social media for social connection if an individual is considering seeking recovery.</p>","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":"5 3","pages":"93-104"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/11/1f/RCP2-5-93.PMC10499190.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10271434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Machine Learning to Predict Antidepressant Treatment Outcome From Electronic Health Records.","authors":"Zhenxing Xu, Veer Vekaria, Fei Wang, Judith Cukor, Chang Su, Prakash Adekkanattu, Pascal Brandt, Guoqian Jiang, Richard C Kiefer, Yuan Luo, Luke V Rasmussen, Jie Xu, Yunyu Xiao, George Alexopoulos, Jyotishman Pathak","doi":"10.1176/appi.prcp.20220015","DOIUrl":"10.1176/appi.prcp.20220015","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate if a machine learning approach can accurately predict antidepressant treatment outcome using electronic health records (EHRs) from patients with depression.</p><p><strong>Method: </strong>This study examined 808 patients with depression at a New York City-based outpatient mental health clinic between June 13, 2016 and June 22, 2020. Antidepressant treatment outcome was defined based on trend in depression symptom severity over time and was categorized as either \"Recovering\" or \"Worsening\" (i.e., non-Recovering), measured by the slope of individual-level Patient Health Questionnaire-9 (PHQ-9) score trajectory spanning 6 months following treatment initiation. A patient was designated as \"Recovering\" if the slope is less than 0 and as \"Worsening\" if the slope was no less than 0. Multiple machine learning (ML) models including L2 norm regularized Logistic Regression, Naive Bayes, Random Forest, and Gradient Boosting Decision Tree (GBDT) were used to predict treatment outcome based on additional data from EHRs, including demographics and diagnoses. Shapley Additive Explanations were applied to identify the most important predictors.</p><p><strong>Results: </strong>The GBDT achieved the best results of predicting \"Recovering\" (AUC: 0.7654 ± 0.0227; precision: 0.6002 ± 0.0215; recall: 0.5131 ± 0.0336). When excluding patients with low PHQ-9 scores (<10) at baseline, the results of predicting \"Recovering\" (AUC: 0.7254 ± 0.0218; precision: 0.5392 ± 0.0437; recall: 0.4431 ± 0.0513) were obtained. Prior diagnosis of anxiety, psychotherapy, recurrent depression, and baseline depression symptom severity were strong predictors.</p><p><strong>Conclusions: </strong>The results demonstrate the potential utility of using ML in longitudinal EHRs to predict antidepressant treatment outcome. Our predictive tool holds the promise to accelerate personalized medical management in patients with psychiatric illnesses.</p>","PeriodicalId":74592,"journal":{"name":"Psychiatric research and clinical practice","volume":"1 1","pages":"118-125"},"PeriodicalIF":0.0,"publicationDate":"2023-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698704/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41626962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}