scholarly journals Adolescents’ adoption of COVID-19 preventive measures during the first months of the pandemic: what led to early adoption?

2021 ◽  
Vol 41 (12) ◽  
Author(s):  
Claude Bacque Dion ◽  
Richard Bélanger ◽  
Scott T. Leatherdale ◽  
Slim Haddad
Keyword(s):  
Structural Equation ◽  
Structural Equation Models ◽  
Preventive Measures ◽  
Anxiety Level ◽  
Perception Of Risk ◽  
Related Factors ◽  
Early Adopters ◽  
Preventive Practices ◽  
Early Adoption ◽  
Study Participants

Introduction The objectives of this study were to explore the extent to which adolescents adopted COVID-19 preventive measures in the first few months of the pandemic and to understand their adoption by looking at interconnected adoption-related factors and determining the strength of these factors, particularly among subgroups not expected to be early adopters. Methods Analyses focus on data collected during Spring 2020 from 29 eastern Quebec secondary schools that participated in the COMPASS study. Participants (n = 6052) self-reported their knowledge, perception of risk and preventive practices to do with the COVID-19 pandemic. Data were analyzed using structural equation models based on gender and anxiety level. Results The majority of respondents reported adopting the recommended COVID-19 preventive measures. The results showed three paths leading to adolescents’ adoption of these measures: pandemic knowledge; perception of risk related to COVID-19; and, in particular, discussions with relatives about preventive measures and what to do in case of infection. Conclusion While most of the adolescent participants in this study appeared to comply with COVID-19 preventive measures, factors such as discussions with relatives emerge as elements to foster in order to improve adolescents’ adoption of preventive measures.

scholarly journals Awareness, Perceived Risk and Preventive Practice on Coronavirus Disease (COVID-19) among Cancer Patient in Bir Hospital, Kathmandu

2021 ◽  
Vol 23 (2) ◽  
pp. 139-145
Author(s):  
Roshani Gautam ◽  
Bishnu Dutta Paudel ◽  
Rejina Shrestha ◽  
Bhagawaty Kalikotay
Keyword(s):  
Cancer Patients ◽  
Perceived Risk ◽  
Preventive Measures ◽  
Sampling Technique ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Preventive Practice ◽  
Preventive Practices ◽  
Socio Demographic Factors ◽  
Study Participants

People with cancer are at high risk for coronavirus infection because of immunosuppressive nature of disease itself and adverse effect of treatment. Knowledge and adoption of preventive practice is critical to control the outbreak of infectious disease in vulnerable populations. Hence, this study aimed to identify the awareness, perceived risk and preventive practices regarding coronavirus disease among people with cancer. Methods: A descriptive cross-sectional study was conducted among 83 cancer patients in Bir Hospital. Total enumeration sampling technique was used to collect data for two weeks and interview schedule was used. Data was analyzed in SPSS version 16, descriptive and inferential statistics was calculated. Out of 83 participants, mean score of knowledge was 37.33±7.5 and 76% of study participants had adequate awareness (>75% of total score) and the mean practice score was 24.6±2.88. None of the study participants were practicing preventive measures as per guidelines of government. The study found that level of awareness was significantly associated with the age of the participants (p=0.04). However, other socio-demographic factors were not associated with awareness. The study concluded that people with cancer had adequate awareness but had inadequate practices on preventive measures as per the guidelines of the Ministry of Health and Population and WHO, which should be mandatory to contain disease outbreak. Therefore, there is an urgent need to focus on the adoption of preventive behaviors for cancer patients.

scholarly journals Validation and Measurement Invariance of the Scale of Positive and Negative Experience (SPANE) in a Spanish General Sample

2020 ◽  
Vol 17 (22) ◽  
pp. 8359
Author(s):  
Begoña Espejo ◽  
Irene Checa ◽  
Jaime Perales-Puchalt ◽  
Juan Francisco Lisón
Keyword(s):  
Negative Affect ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Temporal Stability ◽  
Well Being ◽  
Correlated Errors ◽  
Related Factors ◽  
Cross Sectional ◽  
Negative Experience

Well-being has been measured based on different perspectives in positive psychology. However, it is necessary to measure affects and emotions correctly and to explore the independence of positive and negative affect. This cross-sectional study adapts and validates the Scale of Positive and Negative Experience (SPANE) with a non-probabilistic sample of 821 Spanish adults. A confirmatory factor analysis confirmed two related factors with two correlated errors. The average variance extracted was 0.502 for negative affect (SPANE-N) and 0.588 for positive affect (SPANE-P). The composite reliability was 0.791 for SPANE-N and 0.858 for SPANE-P. Measurement invariance analysis showed evidence of scalar invariance. Item-total corrected polyserial correlations showed values between 0.47 and 0.76. The path analysis used to test temporal stability, and the structural equation models used to test convergent and concurrent validity with other well-being measures, showed good fit. All path coefficients were statistically significant and over 0.480. For the validity models, the magnitude of the correlations was large and in the expected direction. The Spanish version of the SPANE show good psychometric properties. Future studies of emotional well-being in Spain can benefit from the use of this scale, and new studies must test cross-cultural invariance.

scholarly journals Mental Health and Time Management Behavior among Students During COVID-19 Pandemic: Towards Persuasive Technology Design

2021 ◽  
Author(s):  
Mona Alhasani ◽  
Ali Alkhawaji ◽  
Rita Orji
Keyword(s):  
Mental Health ◽  
Time Management ◽  
Perceived Control ◽  
Structural Equation ◽  
Large Scale ◽  
Structural Equation Models ◽  
Related Factors ◽  
Anxiety Levels ◽  
The Impact ◽  
Over Time

The study explored the impact of the COVID-19 pandemic on students' mental health in higher education while capturing their perceptions and attitudes towards time management. The aim was to examine relationships between stress, anxiety, and specific time management related factors. Considering possible differences between genders and degree levels, we developed five structural equation models (SEMs) to delineate these relationships. Results of a large-scale study of 502 participants show that students suffered from stress and two types of COVID-19-related anxiety: disease and consequences. Students' preference for organization was the only factor that significantly promoted their perceived control over time, which contributes to reducing stress, hence, anxiety. However, female students reported higher stress and anxiety levels than male students. Graduate students reported higher anxiety levels related to the consequences of the pandemic compared to undergrads. To promote students' preference for organization, we map the three categories of organization to corresponding persuasive strategies which could be used in the design of persuasive interventions. This creates an opportunity for developing technological interventions to improve students' perceived control over time, thus, reduce stress and anxiety.

scholarly journals A Study on the Perception Change of Passengers on Sustainable Air Transport Following COVID-19 Progress

2021 ◽  
Vol 13 (14) ◽  
pp. 8056
Author(s):  
Ki-Han Song ◽  
Solsaem Choi
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Preventive Measures ◽  
Group Analysis ◽  
Equation Model ◽  
Air Transport ◽  
Social Perceptions ◽  
Survey Period ◽  
Related Factors ◽  
Sanitary Conditions

We investigate whether air transport passengers changed their perceptions on the resumption of air transport use as the circumstances of the COVID-19 pandemic have changed. We surveyed 1200 Koreans, and then six months later re-surveyed 840 people among those who participated in the first survey. We built a structural equation model that was configured of five latent variables: COVID-19-related, self-isolation, destination condition, level of preventive measures in the airport/aircraft, and social perception. We performed paired sample t-test, multi-group analysis, and latent mean analysis for two divided groups, based on the survey period. We found that the perception structure on resuming air transportation use over time during the COVID-19 pandemic has not changed, though a significant change has occurred in the responses to the measured and latent variables. In particular, a high variation was found in the awareness of COVID-19-related factors and social perceptions, and we suggest continuous monitoring of the related factors to preemptively respond to the recovery of air transport demand. On the other hand, we propose proactive level setting and the maintaining of sanitary conditions of the destination and preventive measures in the airport/aircraft. We expect that this study will provide effective implications for the recovery of air transport demand during the COVID-19 pandemic.

Measuring the Big Five in Self-Report and Other Ratings

2000 ◽  
Vol 16 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Claudio Barbaranelli ◽  
Gian Vittorio Caprara
Keyword(s):  
Big Five ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Error Variance ◽  
The Self ◽  
Self Report ◽  
Sources Of Information ◽  
Third Person ◽  
Fit Indexes ◽  
Response Modes

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.

Collective Efficacy and Organizational Commitment in an Italian City Hall

2009 ◽  
Vol 14 (4) ◽  
pp. 363-371 ◽  
Author(s):  
Laura Borgogni ◽  
Silvia Dello Russo ◽  
Laura Petitta ◽  
Gary P. Latham
Keyword(s):  
Organizational Commitment ◽  
Collective Efficacy ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Practical Significance ◽  
City Hall ◽  
Italian City ◽  
Public Sector Managers ◽  
The Individual ◽  
Level Group

Employees (N = 170) of a City Hall in Italy were administered a questionnaire measuring collective efficacy (CE), perceptions of context (PoC), and organizational commitment (OC). Two facets of collective efficacy were identified, namely group and organizational. Structural equation models revealed that perceptions of top management display a stronger relationship with organizational collective efficacy, whereas employees’ perceptions of their colleagues and their direct superior are related to collective efficacy at the group level. Group collective efficacy had a stronger relationship with affective organizational commitment than did organizational collective efficacy. The theoretical significance of this study is in showing that CE is two-dimensional rather than unidimensional. The practical significance of this finding is that the PoC model provides a framework that public sector managers can use to increase the efficacy of the organization as a whole as well as the individual groups that compose it.

A Cautionary Note on Incremental Fit Indices Reported by LISREL

Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Null Model ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Fit Indices ◽  
Cautionary Note ◽  
Confirmatory Factor

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.

Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Equation Model ◽  
Model Fit ◽  
Model Specification ◽  
Simulation Design ◽  
Measurement Models ◽  
Fit Statistics ◽  
Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

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