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Nevin Manimala Statistics

Influence of psychological capital on core competency for new nurses

PLoS One. 2023 Aug 10;18(8):e0289105. doi: 10.1371/journal.pone.0289105. eCollection 2023.

ABSTRACT

BACKGROUND: The development of core competency is crucial for the success of new nurses, enabling them to deliver high-quality care. Psychological capital (PsyCap), encompassing self-efficacy, optimism, hope, and resilience, significantly influences individuals’ abilities and achievements across various professions. However, limited research has specifically examined the impact of PsyCap on the core competency of new nurses. This study aims to bridge this gap by investigating the relationship between PsyCap and core competency development in new nurses, providing valuable strategic insights for improving PsyCap and promoting core competence acquisition.

METHODS: 142 new nurses were chosen for the investigation using a convenient cluster sampling method. The questionnaire included components on socio-demographic characteristics, the Competency Inventory for Registered Nurses (CIRN), and the PsyCap Questionnaire-24 (PCQ-24). The t-test, One-Way ANOVA, Pearson correlation analysis and hierarchical multiple regression were used for statistical analysis.

RESULT: The number of valid questionnaires was 138, and the effective return rate was 97.2%. The overall mean score for core competencies was 171.01 (SD 25.34), and the PsyCap score was 104.76(SD 13.71). The PsyCap of new nurses was highly correlated with core competency, with a correlation coefficient of r = 0.7, p < 0.01. Self-efficacy of PsyCap is a significant independent predictor of core competency (adjust R2 = 0.49).

CONCLUSION: Self-efficacy in PsyCap is an important predictor of new nurses’ core competency. Nursing managers should pay sufficient attention to the cultivation and development of new nurses’ PsyCap, with particular emphasis on enhancing self-efficacy to improve their core competency.

PMID:37561799 | DOI:10.1371/journal.pone.0289105

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Nevin Manimala Statistics

YouTube Videos on Nutrition and Dental Caries: Content Analysis

JMIR Infodemiology. 2023 Aug 10;3:e40003. doi: 10.2196/40003.

ABSTRACT

BACKGROUND: Dental caries is the most common health condition worldwide, and nutrition and dental caries have a strong interconnected relationship. Foods and eating behaviors can be both harmful (eg, sugar) and healthful (eg, meal spacing) for dental caries. YouTube is a popular source for the public to access information. To date, there is no information available on the nutrition and dental caries content of easily accessible YouTube videos.

OBJECTIVE: This study aimed to analyze the content of YouTube videos on nutrition and dental caries.

METHODS: In total, 6 YouTube searches were conducted using keywords related to nutrition and dental caries. The first 20 videos were selected from each search. Video content was scored (17 possible points; higher scores were associated with more topics covered) by 2 individuals based on the inclusion of information regarding various foods and eating behaviors that impact dental caries risk. For each video, information on video characteristics (ie, view count, length, number of likes, number of dislikes, and video age) was captured. Videos were divided into 2 groups by view rate (views/day); differences in scores and types of nutrition messages between groups were determined using nonparametric statistics.

RESULTS: In total, 42 videos were included. Most videos were posted by or featured oral health professionals (24/42, 57%). The mean score was 4.9 (SD 3.4) out of 17 points. Videos with >30 views/day (high view rate; 20/42, 48% videos) had a trend toward a lower score (mean 4.0, SD 3.7) than videos with ≤30 views/day (low view rate; 22/42, 52%; mean 5.8, SD 3.0; P=.06), but this result was not statistically significant. Sugar was the most consistently mentioned topic in the videos (31/42, 74%). No other topics were mentioned in more than 50% of videos. Low-view rate videos were more likely to mention messaging on acidic foods and beverages (P=.04), water (P=.09), and frequency of sugar intake (P=.047) than high-view rate videos.

CONCLUSIONS: Overall, the analyzed videos had low scores for nutritional and dental caries content. This study provides insights into the messaging available on nutrition and dental caries for the public and guidance on how to make improvements in this area.

PMID:37561564 | DOI:10.2196/40003

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Nevin Manimala Statistics

Patient and Public Acceptance of Digital Technologies in Health Care: Protocol for a Discrete Choice Experiment

JMIR Res Protoc. 2023 Aug 10;12:e46056. doi: 10.2196/46056.

ABSTRACT

BACKGROUND: Strokes pose a particular challenge to the health care system. Although stroke-related mortality has declined in recent decades, the absolute number of new strokes (incidence), stroke deaths, and survivors of stroke has increased. With the increasing need of neurorehabilitation and the decreasing number of professionals, innovations are needed to ensure adequate care. Digital technologies are increasingly used to meet patients’ unfilled needs during their patient journey. Patients must adhere to unfamiliar digital technologies to engage in health interventions. Therefore, the acceptance of the benefits and burdens of digital technologies in health interventions is a key factor in implementing these innovations.

OBJECTIVE: This study aims to describe the development of a discrete choice experiment (DCE) to weigh criteria that impact patient and public acceptance. Secondary study objectives are a benefit-burden assessment (estimation of the maximum acceptable burden of technical features and therapy-related characteristics for the patient or individual, eg, no human contact), overall comparison (assessment of the relative importance of attributes for comparing digital technologies), and adherence (identification of key attributes that influence patient adherence). The exploratory objectives include heterogeneity assessment and subgroup analysis. The methodological aims are to investigate the use of DCE.

METHODS: To obtain information on the criteria impacting acceptance, a DCE will be conducted including 7 attributes based on formative qualitative research. Patients with stroke (experimental group) and the general population (control group) are surveyed. The final instrument includes 6 best-best choice tasks in partial design. The experimental design is a fractional-factorial efficient Bayesian design (D-error). A conditional logit regression model and mixed logistic regression models will be used for analysis. To consider the heterogeneity of subgroups, a latent class analysis and an analysis of heteroscedasticity will be performed.

RESULTS: The literature review, qualitative preliminary study, survey development, and pretesting were completed. Data collection and analysis will be completed in the last quarter of 2023.

CONCLUSIONS: Our results will inform decision makers about patients’ and publics’ acceptance of digital technologies used in innovative interventions. The patient preference information will improve decisions regarding the development, adoption, and pricing of innovative interventions. The behavioral changes in the choice of digital intervention alternatives are observable and can therefore be statistically analyzed. They can be translated into preferences, which define the value. This study will investigate the influences on the acceptance of digital interventions and thus support decisions and future research.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46056.

PMID:37561559 | DOI:10.2196/46056

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Nevin Manimala Statistics

Assessing Vulnerability to Surges in Suicide-Related Tweets Using Japan Census Data: Case-Only Study

JMIR Form Res. 2023 Aug 10;7:e47798. doi: 10.2196/47798.

ABSTRACT

BACKGROUND: As the use of social media becomes more widespread, its impact on health cannot be ignored. However, limited research has been conducted on the relationship between social media and suicide. Little is known about individuals’ vulnerable to suicide, especially when social media suicide information is extremely prevalent.

OBJECTIVE: This study aims to identify the characteristics underlying individuals’ vulnerability to suicide brought about by an increase in suicide-related tweets, thereby contributing to public health.

METHODS: A case-only design was used to investigate vulnerability to suicide using individual data of people who died by suicide and tweet data from January 1, 2011, through December 31, 2014. Mortality data were obtained from Japanese government statistics, and tweet data were provided by a commercial service. Tweet data identified the days when suicide-related tweets surged, and the date-keyed merging was performed by considering 3 and 7 lag days. For the merged data set for analysis, the logistic regression model was fitted with one of the personal characteristics of interest as a dependent variable and the dichotomous exposure variable. This analysis was performed to estimate the interaction between the surges in suicide-related tweets and personal characteristics of the suicide victims as case-only odds ratios (ORs) with 95% CIs. For the sensitivity analysis, unexpected deaths other than suicide were considered.

RESULTS: During the study period, there were 159,490 suicides and 115,072 unexpected deaths, and the number of suicide-related tweets was 2,804,999. Following the 3-day lag of a highly tweeted day, there were significant interactions for those who were aged 40 years or younger (OR 1.09, 95% CI 1.03-1.15), male (OR 1.12, 95% CI 1.07-1.18), divorced (OR 1.11, 95% CI 1.03 1.19), unemployed (OR 1.12, 95% CI 1.02-1.22), and living in urban areas (OR 1.26, 95% CI 1.17 1.35). By contrast, widowed individuals had significantly lower interactions (OR 0.83, 95% CI 0.77-0.89). Except for unemployment, significant relationships were also observed for the 7-day lag. For the sensitivity analysis, no significant interactions were observed for other unexpected deaths in the 3-day lag, and only the widowed had a significantly larger interaction than those who were married (OR 1.08, 95% CI 1.02-1.15) in the 7-day lag.

CONCLUSIONS: This study revealed the interactions of personal characteristics associated with susceptibility to suicide-related tweets. In addition, a few significant relationships were observed in the sensitivity analysis, suggesting that such an interaction is specific to suicide deaths. In other words, individuals with these characteristics, such as being young, male, unemployed, and divorced, may be vulnerable to surges in suicide-related tweets. Thus, minimizing public health strain by identifying people who are vulnerable and susceptible to a surge in suicide-related information on the internet is necessary.

PMID:37561553 | DOI:10.2196/47798

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Nevin Manimala Statistics

Student and Faculty Perspectives on the Usefulness and Usability of a Digital Health Educational Tool to Teach Standardized Assessment of Persons After Stroke: Mixed Methods Study

JMIR Med Educ. 2023 Aug 10;9:e44361. doi: 10.2196/44361.

ABSTRACT

BACKGROUND: The VSTEP Examination Suite is a collection of evidence-based standardized assessments for persons after stroke. It was developed by an interdisciplinary team in collaboration with clinician users. It consists of 5 standardized assessments: 2 performance-based tests using the Kinect camera (Microsoft Corp) to collect kinematics (5-Time Sit-to-Stand and 4-Square Test); 2 additional performance-based tests (10-Meter Walk Test and 6-Minute Walk Test); and 1 patient-reported outcome measure, the Activities-Specific Balance Confidence Scale.

OBJECTIVE: This study aimed to describe the development of the VSTEP Examination Suite and its evaluation as an educational tool by physical therapy students and faculty to determine its usefulness and usability.

METHODS: A total of 6 students from a Doctor of Physical Therapy program in the United States and 6 faculty members who teach standardized assessments in different physical therapy programs from the United States and Israel were recruited by convenience sampling to participate in the study. They interacted with the system using a talk-aloud procedure either in pairs or individually. The transcripts of the sessions were coded deductively (by 3 investigators) with a priori categories of usability and usefulness, and comments were labeled as negative or positive. The frequencies of the deductive themes of usefulness and usability were tested for differences between faculty and students using a Wilcoxon rank sum test. A second round of inductive coding was performed by 3 investigators guided by theories of technology adoption, clinical reasoning, and education.

RESULTS: The faculty members’ and students’ positive useful comments ranged from 83% (10/12) to 100%. There were no significant differences in usefulness comments between students and faculty. Regarding usability, faculty and students had the lowest frequency of positive comments for the 10-Meter Walk Test (5/10, 50%). Students also reported a high frequency of negative comments on the 4-Square Test (9/21, 43%). Students had a statistically significantly higher number of negative usability comments compared with faculty (W=5.7; P=.02), specifically for the 5-Time Sit-to-Stand (W=5.3; P=.02). Themes emerged related to variable knowledge about the standardized tests, value as a teaching and learning tool, technology being consistent with clinical reasoning in addition to ensuring reliability, expert-to-novice clinical reasoning (students), and usability.

CONCLUSIONS: The VSTEP Examination Suite was found to be useful by both faculty and students. Reasons for perceived usefulness had some overlap, but there were also differences based on role and experience. Usability testing revealed opportunities for technology refinement. The development of the technology by interdisciplinary teams and testing with multiple types of users may increase adoption.

PMID:37561552 | DOI:10.2196/44361

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Nevin Manimala Statistics

How statistical correlations influence discourse-level processing: Clause type as a cue for discourse relations

J Exp Psychol Learn Mem Cogn. 2023 Aug 10. doi: 10.1037/xlm0001270. Online ahead of print.

ABSTRACT

Linguistic phenomena (e.g., words and syntactic structure) co-occur with a wide variety of meanings. These systematic correlations can help readers to interpret a text and create predictions about upcoming material. However, to what extent these correlations influence discourse processing is still unknown. We address this question by examining whether clause type serves as a cue for discourse relations. We found that the co-occurrence of gerund-free adjuncts and specific discourse relations found in natural language is also reflected in readers’ offline expectations for discourse relations. However, we also found that clause structure did not facilitate the online processing of these discourse relations, nor that readers have a preference for these relations in a paraphrase selection task. The present research extends previous research on discourse relation processing, which mostly focused on lexical cues, by examining the role of non-semantic cues. We show that readers are aware of correlations between clause structure and discourse relations in natural language, but that, unlike what has been found for lexical cues, this information does not seem to influence online processing and discourse interpretation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

PMID:37561516 | DOI:10.1037/xlm0001270

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Nevin Manimala Statistics

Genetic Correlations Among Corneal Biophysical Parameters and Anthropometric Traits

Transl Vis Sci Technol. 2023 Aug 1;12(8):8. doi: 10.1167/tvst.12.8.8.

ABSTRACT

PURPOSE: The genetic architecture of corneal dysfunction remains poorly understood. Epidemiological and clinical evidence suggests a relationship between corneal structural features and anthropometric measures. We used global and local genetic similarity analysis to identify genomic features that may underlie structural corneal dysfunction.

METHODS: We assembled genome-wide association study summary statistics for corneal features (central corneal thickness, corneal hysteresis [CH], corneal resistance factor [CRF], and the 3 mm index of keratometry) and anthropometric traits (body mass index, weight, and height) in Europeans. We calculated global genetic correlations (rg) between traits using linkage disequilibrium (LD) score regression and local genetic covariance using ρ-HESS, which partitions the genome and performs regression with LD regions. Finally, we identified genes located within regions of significant genetic covariance and analyzed patterns of tissue expression and pathway enrichment.

RESULTS: Global LD score regression revealed significant negative correlations between height and both CH (rg = -0.12; P = 2.0 × 10-7) and CRF (rg = -0.11; P = 6.9 × 10-7). Local analysis revealed 68 genomic regions exhibiting significant local genetic covariance between CRF and height, containing 2874 unique genes. Pathway analysis of genes in regions with significant local rg revealed enrichment among signaling pathways with known keratoconus associations, including cadherin and Wnt signaling, as well as enrichment of genes modulated by copper and zinc ions.

CONCLUSIONS: Corneal biophysical parameters and height share a common genomic architecture, which may facilitate identification of disease-associated genes and therapies for corneal ectasias.

TRANSLATIONAL RELEVANCE: Local genetic covariance analysis enables the identification of associated genes and therapeutic targets for corneal ectatic disease.

PMID:37561511 | DOI:10.1167/tvst.12.8.8

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Nevin Manimala Statistics

Equivalence testing to judge model fit: A Monte Carlo simulation

Psychol Methods. 2023 Aug 10. doi: 10.1037/met0000591. Online ahead of print.

ABSTRACT

Decades of published methodological research have shown the chi-square test of model fit performs inconsistently and unreliably as a determinant of structural equation model (SEM) fit. Likewise, SEM indices of model fit, such as comparative fit index (CFI) and root-mean-square error of approximation (RMSEA) also perform inconsistently and unreliably. Despite rather unreliable ways to statistically assess model fit, researchers commonly rely on these methods for lack of a suitable inferential alternative. Marcoulides and Yuan (2017) have proposed the first inferential test of SEM fit in many years: an equivalence test adaptation of the RMSEA and CFI indices (i.e., RMSEAt and CFIt). However, the ability of this equivalence testing approach to accurately judge acceptable and unacceptable model fit has not been empirically tested. This fully crossed Monte Carlo simulation evaluated the accuracy of equivalence testing combining many of the same independent variable (IV) conditions used in previous fit index simulation studies, including sample size (N = 100-1,000), model specification (correctly specified or misspecified), model type (confirmatory factor analysis [CFA], path analysis, or SEM), number of variables analyzed (low or high), data distribution (normal or skewed), and missing data (none, 10%, or 25%). Results show equivalence testing performs rather inconsistently and unreliably across IV conditions, with acceptable or unacceptable RMSEAt and CFIt model fit index values often being contingent on complex interactions among conditions. Proportional z-tests and logistic regression analyses indicated that equivalence tests of model fit are problematic under multiple conditions, especially those where models are mildly misspecified. Recommendations for researchers are offered, but with the provision that they be used with caution until more research and development is available. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

PMID:37561492 | DOI:10.1037/met0000591

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Nevin Manimala Statistics

Mixture multilevel vector-autoregressive modeling

Psychol Methods. 2023 Aug 10. doi: 10.1037/met0000551. Online ahead of print.

ABSTRACT

With the rising popularity of intensive longitudinal research, the modeling techniques for such data are increasingly focused on individual differences. Here we present mixture multilevel vector-autoregressive modeling, which extends multilevel vector-autoregressive modeling by including a mixture, to identify individuals with similar traits and dynamic processes. This exploratory model identifies mixture components, where each component refers to individuals with similarities in means (expressing traits), autoregressions, and cross-regressions (expressing dynamics), while allowing for some interindividual differences in these attributes. Key issues in modeling are discussed, where the issue of centering predictors is examined in a small simulation study. The proposed model is validated in a simulation study and used to analyze the affective data from the COGITO study. These data consist of samples for two different age groups of over 100 individuals each who were measured for about 100 days. We demonstrate the advantage of exploratory identifying mixture components by analyzing these heterogeneous samples jointly. The model identifies three distinct components, and we provide an interpretation for each component motivated by developmental psychology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

PMID:37561488 | DOI:10.1037/met0000551

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Nevin Manimala Statistics

How often does homelessness precede criminal arrest in veterans? Results from the U.S. survey of prison inmates

Am J Orthopsychiatry. 2023 Aug 10. doi: 10.1037/ort0000693. Online ahead of print.

ABSTRACT

Research has shown links between homelessness and criminal legal involvement in military veterans. The present study aimed to determine the magnitude and directionality of this association by investigating the incidence of, and factors associated with, homelessness preceding criminal arrest among veterans. Data on incarcerated veterans (N = 1,602) were analyzed from the 2016 Survey of Prison Inmates conducted by the U.S. Bureau of Justice Statistics. In this survey, 27% of incarcerated veterans reported homelessness 12 months before criminal arrest. In multivariable logistic regression analyses, higher odds of experiencing homelessness preceding criminal arrest were associated with younger age, non-White race, substance use disorder (with or without serious mental illness [SMI]), history of previous arrests, parental history of incarceration, and history of homelessness before age 18. These factors were found to be the same for nonveterans, as were rates of homelessness before arrest. However, incarcerated veterans were more likely to have mental disorders, including SMI, posttraumatic stress disorder (PTSD), and personality disorders. In contrast, incarcerated nonveterans were more likely to have a criminal history, including past arrests, parental incarceration, and juvenile detention. Although policymakers may be aware that some veterans they serve are at risk of criminal legal involvement, these national data reveal the magnitude and directionality of this problem: more than one in four incarcerated veterans experienced homelessness before criminal arrest. Identifying characteristics of veterans who experienced homelessness before criminal arrest directly informs service providers of demographic, historical, and clinical factors to evaluate and address to prevent criminal legal involvement. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

PMID:37561476 | DOI:10.1037/ort0000693