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Nevin Manimala Statistics

The Impact of an Online Educational Intervention on Attitudes of Primary Care Clinicians Toward Managing Patients With Substance Use Disorders

J Addict Nurs. 2024 Jan-Mar 01;35(1):22-27. doi: 10.1097/JAN.0000000000000563.

ABSTRACT

BACKGROUND: Negative attitudes of primary care clinicians toward patients with substance use disorders affect the quality and delivery of care in this highly marginalized patient population.

PURPOSE: This project aimed to improve negative attitudes of primary care clinicians toward managing patients with substance use disorders.

METHODS: A pretest-and-posttest design, employing multidimensional online educational interventions, was implemented from June to August 2020. The participants (n = 18) were recruited from a pool of 70 primary care clinicians at two community primary care agencies. The Affect Scale for Substance Users and 15-item Opening Minds Scale for Health Care Providers were administered before, immediately after, and 30 days after the intervention.

RESULTS: There were statistically significant reductions in the immediate postintervention and 30-day postintervention mean scores in the Affect Scale for Substance Users and the disclosure and help-seeking subscale when compared with those of preintervention. The change in attitudes was maintained at 30-day postintervention.

CONCLUSIONS: The project findings support conducting and evaluating future educational programs for substance use disorder management among primary care clinicians. Because of the heterogeneity of the participants and the small sample size, the project results have limited generalizability. Overall, this project is among one of the few aimed at substance use disorder management among primary care clinicians.

PMID:38574105 | DOI:10.1097/JAN.0000000000000563

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Nevin Manimala Statistics

Associations Between Cognitive Function and Muscle Quality Among Community-Dwelling Older Adults: A Cross-Sectional Study

Exp Aging Res. 2024 Apr 4:1-12. doi: 10.1080/0361073X.2024.2334645. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate whether muscle quality is related to cognitive function in older adults living in the community.

METHODS: The participants were 40 community-dwelling older adults without a diagnosis of dementia (mean age, 78.85 ± 6.40 years; 31 women). The dependent variable was the score on the mild cognitive impairment (MCI) index of the Japanese version of the Neurobehavioral Cognitive Status Examination Five (range: 0-6; higher scores indicate MCI or possible dementia).

RESULTS: Multiple regression with Bayesian statistics was performed for analysis of muscle quality, as indicated by echo intensity (EI), with skeletal muscle mass index, gait speed, physical activity level, age, and sex as covariates. EI was significantly associated with the MCI index (expected a posterior = 0.04 [95% Bayesian confidence interval: 0.01, 0.07], t = 2.47, β = 0.41, p = 0.019).

CONCLUSIONS: The results suggest that EI may be related to the cognitive function of older adults living in the community. Future studies should examine whether focusing on EI can help prevent cognitive decline among older adults..

PMID:38574102 | DOI:10.1080/0361073X.2024.2334645

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Nevin Manimala Statistics

Histological assessment of microtia cartilage, a potential source of autograft tissue in ear reconstruction

J Anat. 2024 Apr 4. doi: 10.1111/joa.14044. Online ahead of print.

ABSTRACT

Cartilage is a strong and flexible connective tissue that has many forms and functions in our body. While cartilage exhibits some forms of limited repair, for the most part, it is not particularly regenerative. Thus, in situations where patients require cartilage reconstruction, surgeons may use autografts to replace missing or damaged tissue. Cartilage tissues from different regions of the body exhibit histological differences and are in limited supply. Thus, it is important to characterize these differences to determine the most appropriate autograft source. In the case of microtia, a congenital deformity where the pinna is underdeveloped, reconstruction commonly utilizes cartilage sourced from a patient’s own costal cartilage. This presents a potential morbidity risk. In this study, we evaluate the histological characteristics of microtia cartilage compared with normal auricular and costal cartilage obtained from human patients undergoing surgical resection. Histochemistry was used to evaluate cellularity, lipid content, and ECM content. Using a Bayesian statistical approach, we determined that while costal cartilage is the standard tissue donor, the microanatomy of microtia cartilage more closely reflects normal auricular cartilage than costal cartilage. Therefore, microtia cartilage may serve as an additional reservoir for cartilage during reconstruction.

PMID:38574100 | DOI:10.1111/joa.14044

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Nevin Manimala Statistics

Implementation of Learning Management Systems (LMS) in higher education systems through bipolar complex hesitant fuzzy Aczel-Alsina power aggregation operators: A case review for China

PLoS One. 2024 Apr 4;19(4):e0300317. doi: 10.1371/journal.pone.0300317. eCollection 2024.

ABSTRACT

A learning management system (LMS) is a web-based application or software platform computed to facilitate the development, tracking, management, reporting, and delivery of education and training programs. Many valuable and dominant factors are working behind the Learning Management System (LMS), but no one can find which factor is most important and valuable for LMS during COVID-19 among the following five alternatives, called Improved Accessibility, Blended Learning, Collaboration and Communications, Assessment and Evaluation, and Administrative Efficiency. For this, first, we derive the techniques of bipolar complex hesitant fuzzy (BCHF) sets, and then we evaluate some flexible operational laws, called Algebraic operational laws and Aczel-Alsina operational laws. Secondly, using the above techniques, we elaborate the technique of BCHF Aczel-Alsina power averaging (BCHFAAPA), BCHF Aczel-Alsina power weighted averaging (BCHFAAPWA), BCHF Aczel-Alsina power geometric (BCHFAAPG), and BCHF Aczel-Alsina power weighted geometric (BCHFAAPWG) operators. Some basic properties are also investigated for each proposed operator. Further, to evaluate the problem concerning LMS, we compute the multi-attribute decision-making (MADM) techniques for invented operators. Finally, we select some prevailing operators and try to compare their ranking results with our proposed results to enhance the worth and capability of the invented theory.

PMID:38574096 | DOI:10.1371/journal.pone.0300317

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Nevin Manimala Statistics

Under-utilisation of noncommunicable disease screening and healthy lifestyle promotion centres: A cross-sectional study from Sri Lanka

PLoS One. 2024 Apr 4;19(4):e0301510. doi: 10.1371/journal.pone.0301510. eCollection 2024.

ABSTRACT

BACKGROUND: Healthy Lifestyle Centres (HLCs) are state-owned, free-of-charge facilities that screen for major noncommunicable disease risks and promote healthy lifestyles among adults older than 35 years in Sri Lanka. The key challenge to their effectiveness is their underutilisation. This study aimed to describe the underutilisation and determine the factors associated, as a precedent of a bigger project that designed and implemented an intervention for its improvement.

METHODS: Data derived from a community-based cross-sectional study conducted among 1727 adults (aged 35 to 65 years) recruited using a multi-stage cluster sampling method from two districts (Gampaha and Kalutara) in Sri Lanka. A prior qualitative study was used to identify potential factors to develop the questionnaire which is published separately. Data were obtained using an interviewer-administered questionnaire and analysed using inferential statistics.

RESULTS: Forty-two percent (n = 726, 95% CI: 39.7-44.4) had a satisfactory level of awareness on HLCs even though utilisation was only 11.3% (n = 195, 95% CI: 9.80-12.8). Utilisation was significantly associated with 14 factors. The five factors with the highest Odds Ratios (OR) were perceiving screening as useful (OR = 10.2, 95% CI: 4.04-23.4), perceiving as susceptible to NCDs (OR = 6.78, 95% CI: 2.79-16.42) and the presence of peer support for screening and a healthy lifestyle (OR = 3.12, 95% CI: 1.54-6.34), belonging to the second (OR = 3.69, 95% CI: 1.53-8.89) and third lowest (OR = 2.84, 95% CI: 1.02-7.94) household income categories and a higher level of knowledge on HLCs (OR = 1.31, 95% CI: 1.24-1.38). When considering non-utilisation, being a male (OR = 0.18, 95% CI: 0.05-0.52), belonging to an extended family (OR = 0.43, 95% CI: 0.21-0.88), residing within 1-2 km (OR = 0.29, 95% CI: 0.14-0.63) or more than 3 km of the HLC (OR = 0.14, 95% CI: 0.04-0.53), having a higher self-assessed health score (OR = 0.97, 95% CI: 0.95-0.99) and low perceived accessibility to HLCs (OR = 0.12, 95% CI: 0.04-0.36) were significantly associated.

CONCLUSION: In conclusion, underutilisation of HLCs is a result of multiple factors operating at different levels. Therefore, interventions aiming to improve HLC utilisation should be complex and multifaceted designs based on these factors rather than merely improving knowledge.

PMID:38574085 | DOI:10.1371/journal.pone.0301510

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Nevin Manimala Statistics

Improving accuracy of vascular access quality classification in hemodialysis patients using deep learning with K highest score feature selection

J Int Med Res. 2024 Apr;52(4):3000605241232519. doi: 10.1177/03000605241232519.

ABSTRACT

OBJECTIVE: To develop and evaluate a novel feature selection technique, using photoplethysmography (PPG) sensors, for enhancing the performance of deep learning models in classifying vascular access quality in hemodialysis patients.

METHODS: This cross-sectional study involved creating a novel feature selection method based on SelectKBest principles, specifically designed to optimize deep learning models for PPG sensor data, in hemodialysis patients. The method effectiveness was assessed by comparing the performance of multiple deep learning models using the feature selection approach versus complete feature set. The model with the highest accuracy was then trained and tested using a 70:30 approach, respectively, with the full dataset and the SelectKBest dataset. Performance results were compared using Student’s paired t-test.

RESULTS: Data from 398 hemodialysis patients were included. The 1-dimensional convolutional neural network (CNN1D) displayed the highest accuracy among different models. Implementation of the SelectKBest-based feature selection technique resulted in a statistically significant improvement in the CNN1D model’s performance, achieving an accuracy of 92.05% (with feature selection) versus 90.79% (with full feature set).

CONCLUSION: These findings suggest that the newly developed feature selection approach might aid in accurately predicting vascular access quality in hemodialysis patients. This advancement may contribute to the development of reliable diagnostic tools for identifying vascular complications, such as stenosis, potentially improving patient outcomes and their quality of life.

PMID:38573764 | DOI:10.1177/03000605241232519

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Nevin Manimala Statistics

A Novel Digital Health Platform With Health Coaches to Optimize Surgical Patients: Feasibility Study at a Large Academic Health System

JMIR Perioper Med. 2024 Apr 4;7:e52125. doi: 10.2196/52125.

ABSTRACT

BACKGROUND: Pip is a novel digital health platform (DHP) that combines human health coaches (HCs) and technology with patient-facing content. This combination has not been studied in perioperative surgical optimization.

OBJECTIVE: This study’s aim was to test the feasibility of the Pip platform for deploying perioperative, digital, patient-facing optimization guidelines to elective surgical patients, assisted by an HC, at predefined intervals in the perioperative journey.

METHODS: We conducted an institutional review board-approved, descriptive, prospective feasibility study of patients scheduled for elective surgery and invited to enroll in Pip from 2.5 to 4 weeks preoperatively through 4 weeks postoperatively at an academic medical center between November 22, 2022, and March 27, 2023. Descriptive primary end points were patient-reported outcomes, including patient satisfaction and engagement, and Pip HC evaluations. Secondary end points included mean or median length of stay (LOS), readmission at 7 and 30 days, and emergency department use within 30 days. Secondary end points were compared between patients who received Pip versus patients who did not receive Pip using stabilized inverse probability of treatment weighting.

RESULTS: A total of 283 patients were invited, of whom 172 (60.8%) enrolled in Pip. Of these, 80.2% (138/172) patients had ≥1 HC session and proceeded to surgery, and 70.3% (97/138) of the enrolled patients engaged with Pip postoperatively. The mean engagement began 27 days before surgery. Pip demonstrated an 82% weekly engagement rate with HCs. Patients attended an average of 6.7 HC sessions. Of those patients that completed surveys (95/138, 68.8%), high satisfaction scores were recorded (mean 4.8/5; n=95). Patients strongly agreed that HCs helped them throughout the perioperative process (mean 4.97/5; n=33). The average net promoter score was 9.7 out of 10. A total of 268 patients in the non-Pip group and 128 patients in the Pip group had appropriate overlapping distributions of stabilized inverse probability of treatment weighting for the analytic sample. The Pip cohort was associated with LOS reduction when compared to the non-Pip cohort (mean 2.4 vs 3.1 days; median 1.9, IQR 1.0-3.1 vs median 3.0, IQR 1.1-3.9 days; mean ratio 0.76; 95% CI 0.62-0.93; P=.009). The Pip cohort experienced a 49% lower risk of 7-day readmission (relative risk [RR] 0.51, 95% CI 0.11-2.31; P=.38) and a 17% lower risk of 30-day readmission (RR 0.83, 95% CI 0.30-2.31; P=.73), though these did not reach statistical significance. Both cohorts had similar 30-day emergency department returns (RR 1.06, 95% CI 0.56-2.01, P=.85).

CONCLUSIONS: Pip is a novel mobile DHP combining human HCs and perioperative optimization content that is feasible to engage patients in their perioperative journey and is associated with reduced hospital LOS. Further studies assessing the impact on clinical and patient-reported outcomes from the use of Pip or similar DHPs HC combinations during the perioperative journey are required.

PMID:38573737 | DOI:10.2196/52125

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Nevin Manimala Statistics

Rapid assessment of public interest in drought and its likely drivers in South Africa

J Emerg Manag. 2024 Special Issue on Climate Change and Sustainability in Emergency Management;22(7):101-112. doi: 10.5055/jem.0834.

ABSTRACT

The monthly search volumes for drought were extracted from Google® for South Africa using the Keywordsevery-where.com plugin from January 2004 until June 2022. To identify the potential qualitative drivers for such public interest the following data extracted by the plugin were investigated and analysed: the drought-related keywords, the long-tail keywords similar to drought, and the “people also searched for category” from the South African users. The Google Trends monthly score was extracted for South Africa and the Eastern Cape Province, and specific local municipalities/towns/cities in the province. The aim was to assess the relative significance of the drought interest in comparison to public interest in other search terms. The results of the Kruskal-Wallis analyses of variance by ranks showed that there was a statistically significant difference between individual values of the monthly search volumes for drought in South Africa, as a function of time of data extraction (5 percent level of significance; p-value ≤ 4.7 × 10-14). The monthly search volumes increased with time, which is based on the results of the Mann-Kendall test at a 5 percent level of significance (p-value ≤ 0.0092). Analyses of the Google Trends scores indicate that the relative interest in drought in South Africa and the Eastern Cape Province increased with time between January 2004 and June 2022 (the Mann-Kendall test at a 5 percent level of significance; p-value = 0.0011). The population’s searches for drought were relatively low when compared to other search terms on Google. Drought adaptation of the South African community could be considered a driver of the Google searches for drought, but it is a marginal topic compared to other topics in Google searches. It might be necessary to increase this significance by investigating the “Google-search patterns for droughts” in the areas of Tshikaro, Mafusini, Cofimvaba, and Nxotsheni in the Eastern Cape Province of South Africa.

PMID:38573733 | DOI:10.5055/jem.0834

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Nevin Manimala Statistics

Grief-focused cognitive behavioral therapies for prolonged grief symptoms: A systematic review and meta-analysis

J Consult Clin Psychol. 2024 Apr;92(4):236-248. doi: 10.1037/ccp0000884.

ABSTRACT

BACKGROUND: Studies suggest that cognitive behavioral therapies (CBTs) may be efficacious in reducing symptoms of prolonged grief disorder (PGD), but no comprehensive overview and pooled estimate of CBTs’ effect on PGD in adulthood exist. We conducted a systematic review and meta-analysis of randomized controlled trials.

METHOD: Studies were selected independently by two researchers based on a systematic literature search in Pubmed, APA PsycInfo, Web of Science, and Embase. Meta-analyses provided pooled effect sizes for the effects of CBTs on PGD symptoms and secondary outcomes. We explored potential moderators of effect, risk of bias of included studies, and evaluated the quality of the meta-analytical evidence through the Grading of Recommendations, Assessment, Development, and Evaluation system.

RESULTS: The meta-analysis included 22 studies of 2,602 bereaved adults (averaged study Mage = 49 years). CBTs had a statistically significant medium effect on PGD symptoms at postintervention (K = 22, g = 0.65, 95% CI [0.49, 0.81]), and a large effect at follow-up (K = 7, g = 0.90, 95% CI [0.37, 1.43]). Statistically significant small-to-medium effects were found at postintervention on posttraumatic stress symptoms (K = 10, g = 0.74, 95% CI [0.49, 0.98]), depression (K = 19, g = 0.53, 95% CI [0.36, 0.71]), and anxiety (K = 9, g = 0.35, 95% CI [0.22, 0.49]). The effects on PGD remained unchanged when adjusted for possible outliers. None of the moderator analyses reached statistical significance.

CONCLUSION: This review suggests that CBTs are efficacious in reducing PGD symptoms in adulthood. Generalization of findings should be done with caution due to considerable inconsistency and indirectness of meta-analytic evidence. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

PMID:38573714 | DOI:10.1037/ccp0000884

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Statins Do Not Significantly Affect Oxidative Nitrosative Stress Biomarkers in the PREVENT Randomized Clinical Trial

Clin Cancer Res. 2024 Apr 4. doi: 10.1158/1078-0432.CCR-23-3952. Online ahead of print.

ABSTRACT

PURPOSE: Preventing Anthracycline Cardiovascular Toxicity with Statins (PREVENT) (NCT01988571) randomized breast cancer or lymphoma patients receiving anthracyclines to atorvastatin 40 mg daily or placebo. We evaluated the effects of atorvastatin on oxidative and nitrosative stress biomarkers, and explored whether these biomarkers could explain the lack of effect of atorvastatin on LVEF in PREVENT.

PATIENTS AND METHODS: Blood samples were collected and cardiac magnetic resonance imaging was performed prior to doxorubicin initiation and at 6 and 24 months. Thirteen biomarkers (arginine-nitric oxide metabolites, paraoxonase-1 [PON-1] activity, and myeloperoxidase) were measured. Dimensionality reduction using principal component analysis was used to define biomarker clusters. Linear mixed-effects models determined the changes in biomarkers over time according to treatment group. Mediation analysis determined if biomarker clusters explained the lack of effect of atorvastatin on LVEF.

RESULTS: Among 202 participants with available biomarkers, median age was 53 years; 86.6% had breast cancer; median LVEF was 62%. Cluster 1 levels, reflecting arginine methylation metabolites, were lower over time with atorvastatin, although this was not statistically significant (p=0.081); cluster 2 levels, reflecting PON-1 activity, were significantly lower with atorvastatin (p=0.024). There were no significant changes in other biomarker clusters (p>0.05). Biomarker clusters did not mediate an effect of atorvastatin on LVEF (p>0.05) Conclusions: Atorvastatin demonstrated very modest effects on oxidative/nitrosative stress biomarkers in this low cardiovascular risk population. Our findings provide potential mechanistic insight into the lack of effect of atorvastatin on LVEF in the PREVENT trial.

PMID:38573708 | DOI:10.1158/1078-0432.CCR-23-3952