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Nevin Manimala Statistics

Application of Andersen’s behavioural model of health services use: a scoping review with a focus on qualitative health services research

BMJ Open. 2021 May 5;11(5):e045018. doi: 10.1136/bmjopen-2020-045018.

ABSTRACT

INTRODUCTION: Qualitative methods have become integral in health services research, and Andersen’s behavioural model of health services use (BMHSU) is one of the most commonly employed models of health service utilisation. The model focuses on three core factors to explain healthcare utilisation: predisposing, enabling and need factors. A recent overview of the application of the BMHSU is lacking, particularly regarding its application in qualitative research. Therefore, we provide (1) a descriptive overview of the application of the BMHSU in health services research in general and (2) a qualitative synthesis on the (un)suitability of the model in qualitative health services research.

METHODS: We searched five databases from March to April 2019, and in April 2020. For inclusion, each study had to focus on individuals ≥18 years of age and to cite the BMHSU, a modified version of the model, or the three core factors that constitute the model, regardless of study design, or publication type. We used MS Excel to perform descriptive statistics, and applied MAXQDA 2020 as part of a qualitative content analysis.

RESULTS: From a total of 6319 results, we identified 1879 publications dealing with the BMSHU. The main methodological approach was quantitative (89%). More than half of the studies are based on the BMHSU from 1995. 77 studies employed a qualitative design, the BMHSU was applied to justify the theoretical background (62%), structure the data collection (40%) and perform data coding (78%). Various publications highlight the usefulness of the BMHSU for qualitative data, while others criticise the model for several reasons (eg, its lack of cultural or psychosocial factors).

CONCLUSIONS: The application of different and older models of healthcare utilisation hinders comparative health services research. Future research should consider quantitative or qualitative study designs and account for the most current and comprehensive model of the BMHSU.

PMID:33952550 | DOI:10.1136/bmjopen-2020-045018

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Nevin Manimala Statistics

Face-to-face panel meetings versus remote evaluation of fellowship applications: simulation study at the Swiss National Science Foundation

BMJ Open. 2021 May 5;11(5):e047386. doi: 10.1136/bmjopen-2020-047386.

ABSTRACT

OBJECTIVES: To trial a simplified, time and cost-saving method for remote evaluation of fellowship applications and compare this with existing panel review processes by analysing concordance between funding decisions, and the use of a lottery-based decision method for proposals of similar quality.

DESIGN: The study involved 134 junior fellowship proposals for postdoctoral research (‘Postdoc.Mobility’). The official method used two panel reviewers who independently scored the application, followed by triage and discussion of selected applications in a panel. Very competitive/uncompetitive proposals were directly funded/rejected without discussion. The simplified procedure used the scores of the two panel members, with or without the score of an additional, third expert. Both methods could further use a lottery to decide on applications of similar quality close to the funding threshold. The same funding rate was applied, and the agreement between the two methods analysed.

SETTING: Swiss National Science Foundation (SNSF).

PARTICIPANTS: Postdoc.Mobility panel reviewers and additional expert reviewers.

PRIMARY OUTCOME MEASURE: Per cent agreement between the simplified and official evaluation method with 95% CIs.

RESULTS: The simplified procedure based on three reviews agreed in 80.6% (95% CI: 73.9% to 87.3%) of applicants with the official funding outcome. The agreement was 86.6% (95% CI: 80.6% to 91.8%) when using the two reviews of the panel members. The agreement between the two methods was lower for the group of applications discussed in the panel (64.2% and 73.1%, respectively), and higher for directly funded/rejected applications (range: 96.7%-100%). The lottery was used in 8 (6.0%) of 134 applications (official method), 19 (14.2%) applications (simplified, three reviewers) and 23 (17.2%) applications (simplified, two reviewers). With the simplified procedure, evaluation costs could have been halved and 31 hours of meeting time saved for the two 2019 calls.

CONCLUSION: Agreement between the two methods was high. The simplified procedure could represent a viable evaluation method for the Postdoc.Mobility early career instrument at the SNSF.

PMID:33952554 | DOI:10.1136/bmjopen-2020-047386

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Nevin Manimala Statistics

Self-management for patients on ventricular assist device support: a national, multicentre study: protocol for a 3-phase study

BMJ Open. 2021 May 5;11(5):e044374. doi: 10.1136/bmjopen-2020-044374.

ABSTRACT

INTRODUCTION: Self-management (SM) may facilitate patient participation and involvement to become active and knowledgeable partners in the care of complex chronic conditions such as ventricular assist device (VAD) therapy. The ‘SM model for patients on VAD support’ will serve to distinguish between SM components, and will guide the development, implementation and evaluation of an evidence-based curriculum.

METHODS AND ANALYSIS: This is a 3-phase, multicentre study. In phase 1, a prevalence study will be performed. Phase 2 aims to develop an evidence-based, interprofessional curriculum for SM support for VAD patients. In phase 3, a non-blinded block-randomised controlled trial (RCT), allocation ratio 1:1, intervention group superiority, with an unblinded multifacetted intervention with assessments before (T1) and after (T2) the intervention, and two follow-up assessments at three (T3), and 12 (T4) months after VAD implantation, will be performed. The curriculum guides the intervention in the RCT. Patient recruitment will consider centre-related volume: power analyses require 384 patients for phase 1, and 142 patients for phase 3.

ETHICS AND DISSEMINATION: Ethical considerations will be continuously taken into account and approved by the institutional review boards. Central ethical review board approval has been obtained by the Albert-Ludwigs University Freiburg. This study will be performed in concordance with the Declaration of Helsinki and the European data protection law. Publications will exclusively report aggregated data and will be distributed in the scientific community, and patient support groups. Report languages will be German and English.

TRIAL REGISTRATION NUMBERS: NCT04234230 and NCT04526964; Pre-results.

PMID:33952544 | DOI:10.1136/bmjopen-2020-044374

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Nevin Manimala Statistics

Psychosocial determinants of quit motivation in older smokers from deprived backgrounds: a cross-sectional survey

BMJ Open. 2021 May 5;11(5):e044815. doi: 10.1136/bmjopen-2020-044815.

ABSTRACT

OBJECTIVES: To identify psychosocial determinants of quit motivation in older deprived smokers. The evidence may be used to optimise smoking cessation interventions for the target population.

DESIGN: Cross-sectional survey using online recruitment methods including Facebook-targeted advertising.

SETTING: UK, 2019.

PARTICIPANTS: Current smokers aged 50 years or older and from a socioeconomically deprived background.

MAIN OUTCOME MEASURES: Measures included motivation to stop smoking, smoking history, perceived social support, self-efficacy for quitting, self-exempting beliefs and lung cancer risk perception. Multivariable regression was used to analyse factors associated with quit motivation.

RESULTS: Of a total 578 individuals who consented to take part, 278 (48.1%) did not meet the inclusion criteria. Of the 300 eligible participants, most were recruited using Facebook (94.0%), were aged 50-64 years (83.7%) and women (85.7%). Most participants were renting from a housing association (72.0%) and had low education (61.0%). Higher motivation to quit was statistically significantly associated with a higher intensity of previous quit attempts (p=0.03), higher quit confidence (p=0.01), higher smoking self-efficacy (p=0.01), a lower risk-minimising beliefs score (p=0.01) and using traditional nicotine replacement therapy (NRT) when trying to stop smoking or cut down (p<0.001).

CONCLUSION: Older smokers from deprived backgrounds face complex barriers to quitting smoking. Interventions are needed to increase self-efficacy for quitting, modify risk-minimising beliefs and target elements of previous quit attempts (ie, the use of NRT) that are associated with motivation to stop smoking.

PMID:33952547 | DOI:10.1136/bmjopen-2020-044815

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Nevin Manimala Statistics

Identification of novel cardiovascular disease associated metabolites using untargeted metabolomics

Biol Chem. 2021 Jan 20;402(6):749-757. doi: 10.1515/hsz-2020-0331. Print 2021 May 26.

ABSTRACT

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality around the world. Early diagnosis of CVD could provide the opportunity for sensible management and better clinical outcome along with the prevention of further progression of the disease. In the current study, we used an untargeted metabolomic approach to identify possible metabolite(s) that associate well with the CVD and could serve either as therapeutic target or disease-associated metabolite. We identified 26 rationally adjusted unique metabolites that were differentially present in the serum of CVD patients compared with healthy individuals, among them 15 were found to be statistically significant. Out of these metabolites, we identified some novel metabolites like UDP-l-rhamnose and N1-acetylspermidine that have not been reported to be linked with CVD directly. Further, we also found that some metabolites like ethanolamide, solanidine, dimethylarginine, N-acetyl-l-tyrosine, can act as a discriminator of CVD. Metabolites integrating pathway enrichment analysis showed enrichment of various important metabolic pathways like histidine metabolism, methyl histidine metabolism, carnitine synthesis, along with arginine and proline metabolism in CVD patients. Our study provides a great opportunity to understand the pathophysiological role and impact of the identified unique metabolites and can be extrapolated as specific CVD specific metabolites.

PMID:33951765 | DOI:10.1515/hsz-2020-0331

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Nevin Manimala Statistics

Psychopathologic Profiles and Clusters in Tertiary Clinic Referred Patients with Adult Attention Deficit Hyperactivity Disorder: A Person-Centered Analysis

Psychiatry Investig. 2021 Apr;18(4):304-311. doi: 10.30773/pi.2020.0331. Epub 2021 Apr 25.

ABSTRACT

OBJECTIVE: Adult attention deficit hyperactivity disorder (ADHD) has a heterogeneous clinical presentation with patients showing very frequent emotional problems. In the present study, patients with adult ADHD were subtyped based on their psychopathology using a person-centered approach.

METHODS: In the present chart review study, detailed findings of psychological evaluation conducted as part of routine care were utilized. A total of 77 subjects with adult ADHD were included in the analysis. Detailed ADHD symptoms, psychiatric comorbid Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnoses, and severity of mood and anxiety symptoms were evaluated in the person-centered analysis.

RESULTS: Three clusters were generated using clustering analysis. DSM comorbid conditions did not significantly impact the clustering. Cluster 1 consisted of ADHD combined presentation (ADHD-C) with less mood symptoms, cluster 2 of ADHD predominantly inattentive presentation and cluster 3 of ADHD-C with significant mood symptoms. Patients in cluster 3 had adulthood functional impairment more frequently compared with patients in cluster 1. Patients in cluster 3 showed recurrent thoughts of death and suicidal ideation more frequently compared with patients in cluster 1.

CONCLUSION: Further studies are needed to confirm the relationships observed in the present study.

PMID:33951777 | DOI:10.30773/pi.2020.0331

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Nevin Manimala Statistics

R and nlmixr as a gateway between statistics and pharmacometrics

CPT Pharmacometrics Syst Pharmacol. 2021 Apr;10(4):283-285. doi: 10.1002/psp4.12618.

NO ABSTRACT

PMID:33951757 | DOI:10.1002/psp4.12618

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Nevin Manimala Statistics

The effect of Chlorella vulgaris on obesity related metabolic disorders: a systematic review of randomized controlled trials

J Complement Integr Med. 2021 May 5. doi: 10.1515/jcim-2021-0024. Online ahead of print.

ABSTRACT

OBJECTIVES: Chlorella vulgaris (CV) as a unicellular algae is a dietary supplement with beneficial nutritious content, used for decades in some countries. Positive effects for CV supplementation on metabolic parameters has been established in animal and human studies. However there is a gap for this results summary for a definite conclusion announce. This systematic review aimed to summarize the effects of CV on body weight, lipid profile, and blood glucose.

CONTENT: PRISMA guidelines were charted in this review. Subject search was performed in MEDLINE, ProQuest, PubMed, ISI web of sciences, Google scholar, Cochrane and Scopus databases for randomized clinical trials published in English languages, until December 2020, which assessed the effects of CV on metabolic syndrome related symptoms in clinical trials.

SUMMARY: Out of 4,821 records screened, after duplicate and irrelevant exclusion by title and abstract, 20 articles remained for full text screening. Finally a total of 12 articles met the study inclusion criteria and were assessed for study method and results.

OUTLOOK: The findings showed controversies in anthropometric, glycemic and lipid profile effects. CV may have beneficial effects on obesity-related metabolic disorders; however, collected studies lacked statistical power to reach a definite conclusion. More well-designed studies are required.

PROSPERO REGISTRATION NUMBER: CRD42019123683.

PMID:33951762 | DOI:10.1515/jcim-2021-0024

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Antipsychotics are related to psychometric conversion to psychosis in ultra-high-risk youth

Early Interv Psychiatry. 2021 May 5. doi: 10.1111/eip.13158. Online ahead of print.

ABSTRACT

BACKGROUND: The prescription of antipsychotics outside overt psychotic conditions remains controversial, especially in youth where it is relatively widespread. Furthermore, some studies seem to indicate that antipsychotic exposure in individuals at ultra-high-risk (UHR) for psychosis is associated with higher conversion rates. This study was set up to test whether the inter-current prescription of antipsychotics in UHR patients was related to the psychometric threshold for a diagnosis of psychosis.

METHODS: The 24-item Brief Psychiatric Rating Scale (BPRS) was used to quantify treatment response up to 2 years in 125 UHR participants. Standard psychometric criteria were used to quantify conversion to psychosis. Kaplan-Mayer and Cox proportional hazard survival analysis were applied to determine the impact of having or not received the prescription of an antipsychotic drug.

RESULTS: Over the study period 30 (24%) subjects received the prescription of an antipsychotic. In the sample, there were 31 participants (25%) who had reached the psychometric threshold for conversion to psychosis after 2 years of treatment. UHR people who received a prescription of antipsychotics during the first 2 years of treatment were statistically more likely to reach the psychometric threshold for conversion to psychosis on the BPRS: Hazard ratio = 3.03 (95%CI: 1.49-6.16); p = .003.

CONCLUSION: This finding supports the hypothesis that the prescription of antipsychotics within UHR cohorts is to be considered a red flag for higher incipient risk of conversion to psychosis.

PMID:33951751 | DOI:10.1111/eip.13158

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Nevin Manimala Statistics

Impact of study design and statistical model in pharmacogenetic studies with gene-treatment interaction

CPT Pharmacometrics Syst Pharmacol. 2021 Apr;10(4):340-349. doi: 10.1002/psp4.12624.

ABSTRACT

Gene-treatment interactions, just like drug-drug interactions, can have dramatic effects on a patient response and therefore influence the clinician decision at the patient’s bedside. Crossover designs, although they are known to decrease the number of subjects in drug-interaction studies, are seldom used in pharmacogenetic studies. We propose to evaluate, via realistic clinical trial simulations, to what extent crossover designs can help quantifying the gene-treatment interaction effect. We explored different scenarios of crossover and parallel design studies comparing two symptom-modifying treatments in a chronic and stable disease accounting for the impact of a one gene and one gene-treatment interaction. We varied the number of subjects, the between and within subject variabilities, the gene polymorphism frequency and the effect sizes of the treatment, gene, and gene-treatment interaction. Each simulated dataset was analyzed using three models: (i) estimating only the treatment effect, (ii) estimating the treatment and the gene effects, and (iii) estimating the treatment, the gene, and the gene-treatment interaction effects. We showed how ignoring the gene-treatment interaction results in the wrong treatment effect estimates. We also highlighted how crossover studies are more powerful to detect a treatment effect in the presence of a gene-treatment interaction and more often lead to correct treatment attribution.

PMID:33951752 | DOI:10.1002/psp4.12624