scholarly journals Arguing in Favor of Revising the Simulator Sickness Questionnaire Factor Structure When Assessing Side Effects Induced by Immersions in Virtual Reality

2021 ◽  
Vol 12 ◽  
Author(s):  
Stéphane Bouchard ◽  
Maxine Berthiaume ◽  
Geneviève Robillard ◽  
Hélène Forget ◽  
Camille Daudelin-Peltier ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Factor Analysis ◽  
Side Effects ◽  
Factor Structure ◽  
Factor Model ◽  
Latent Structure ◽  
Simulator Sickness ◽  
Negative Side ◽  
Simulator Sickness Questionnaire ◽  
Negative Side Effects

Two issues are increasingly of interest in the scientific literature regarding unwanted virtual reality (VR) induced side effects: (1) whether the latent structure of the Simulator Sickness Questionnaire (SSQ) is comprised of two or three factors, and (2) if the SSQ measures symptoms of anxiety that can be misattributed to unwanted negative side effects induced by immersions in VR. Study 1 was conducted with a sample of 876 participants. A confirmatory factor analysis clearly supported a two-factor model composed of nausea and oculomotor symptoms instead of the 3-factor structure observed in simulators. To tease-out symptoms of anxiety from unwanted negative side effects induced by immersions in VR, Study 2 was conducted with 88 participants who were administered the Trier Stress Social Test in groups without being immersed in VR. A Spearman correlation showed that 11 out of 16 side effects correlated significantly with anxiety. A factor analysis revealed that items measuring general discomfort, difficulty concentrating, sweating, nausea, and vertigo loaded significantly on the anxiety factor comprised of items from the State-Trait Anxiety Inventory. Finally, a multiple regression indicated that the items measuring general discomfort and difficulty concentrating significantly predicted increases in anxiety. The overall results support the notion that side effects associated with immersions in VR consist mostly of a nausea and an oculomotor latent structure and that a few items are confounding anxiety and cybersickness. The data support the suggestion to revise the scoring procedures of the Simulator Sickness Questionnaire when using this instrument with immersions in VR.

Factorial Structure of the Therapist Adherence Measure-Revised (TAM-R) Within Multisystemic Therapy

2020 ◽  
Vol 36 (2) ◽  
pp. 427-431
Author(s):  
Aurelie M. C. Lange ◽  
Marc J. M. H. Delsing ◽  
Ron H. J. Scholte ◽  
Rachel E. A. van der Rijken
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Multisystemic Therapy ◽  
Model Fit ◽  
Validity And Reliability ◽  
Adherence Measure ◽  
Therapist Adherence ◽  
Confirmatory Factor ◽  
The Us

Abstract. The Therapist Adherence Measure (TAM-R) is a central assessment within the quality-assurance system of Multisystemic Therapy (MST). Studies into the validity and reliability of the TAM in the US have found varying numbers of latent factors. The current study aimed to reexamine its factor structure using two independent samples of families participating in MST in the Netherlands. The factor structure was explored using an Exploratory Factor Analysis (EFA) in Sample 1 ( N = 580). This resulted in a two-factor solution. The factors were labeled “therapist adherence” and “client–therapist alliance.” Four cross-loading items were dropped. Reliability of the resulting factors was good. This two-factor model showed good model fit in a subsequent Confirmatory Factor Analysis (CFA) in Sample 2 ( N = 723). The current finding of an alliance component corroborates previous studies and fits with the focus of the MST treatment model on creating engagement.

An investigation into the factor structure of the Cognitive Therapy Scale – Revised (CTS-R) in a CBT training sample

2021 ◽  
pp. 1-11
Author(s):  
Sarah Beale ◽  
Silia Vitoratou ◽  
Sheena Liness
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Therapy ◽  
Exploratory Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Single Factor ◽  
Behaviour Therapy ◽  
Cognitive Behaviour ◽  
Confirmatory Factor

Abstract Background: Effective monitoring of cognitive behaviour therapy (CBT) competence depends on psychometrically robust assessment methods. While the UK Cognitive Therapy Scale – Revised (CTS-R; Blackburn et al., 2001) has become a widely used competence measure in CBT training, practice and research, its underlying factor structure has never been investigated. Aims: This study aimed to present the first investigation into the factor structure of the CTS-R based on a large sample of postgraduate CBT trainee recordings. Method: Trainees (n = 382) provided 746 mid-treatment audio recordings for depression (n = 373) and anxiety (n = 373) cases scored on the CTS-R by expert markers. Tapes were split into two equal samples counterbalanced by diagnosis and with one tape per trainee. Exploratory factor analysis was conducted. The suggested factor structure and a widely used theoretical two-factor model were tested with confirmatory factor analysis. Measurement invariance was assessed by diagnostic group (depression versus anxiety). Results: Exploratory factor analysis suggested a single-factor solution (98.68% explained variance), which was supported by confirmatory factor analysis. All 12 CTS-R items were found to contribute to this single factor. The univariate model demonstrated full metric invariance and partial scalar invariance by diagnosis, with one item (item 10 – Conceptual Integration) demonstrating scalar non-invariance. Conclusions: Findings indicate that the CTS-R is a robust homogenous measure and do not support division into the widely used theoretical generic versus CBT-specific competency subscales. Investigation into the CTS-R factor structure in other populations is warranted.

scholarly journals A systematic review of the latent structure of the Center for Epidemiologic Studies Depression Scale (CES-D) amongst adolescents

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Joanna M. Blodgett ◽  
Chantelle C. Lachance ◽  
Brendon Stubbs ◽  
Melissa Co ◽  
Yu-Tzu Wu ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Cultural Differences ◽  
Factor Structure ◽  
English Language ◽  
Depression Scale ◽  
Epidemiologic Studies ◽  
Latent Structure ◽  
Future Research ◽  
Primary Analysis ◽  
The Usa

Abstract Background The Centre for Epidemiologic Studies Depression Scale (CES-D) is a commonly used psychometric scale of depression. A four-factor structure (depressed affect, positive affect, somatic symptoms, and interpersonal difficulties) was initially identified in an American sample aged 18 to 65. Despite emerging evidence, a latent structure has not been established in adolescents. This review aimed to investigate the factor structure of the CES-D in adolescents. Methods We searched Web of Science, PsychINFO and Scopus and included peer-reviewed, original studies assessing the factor structure of the 20-item CES-D in adolescents aged ≤18. Two independent researchers screened results and extracted data. Results Thirteen studies met the inclusion criteria and were primarily from school-based samples in the USA or Asia. Studies that conducted confirmatory factor analysis (CFA; n = 9) reported a four-factor structure consistent with the original factor structure; these studies were primarily USA-based. Conversely, studies that conducted exploratory factor analysis (EFA) reported distinct two or three factor structures (n = 4) and were primarily based in Asia. Limitations Studies in a non-English language and those that included individuals aged > 18 years were excluded. Ethnic or cultural differences as well as different analytical methods impacted generalisability of results. The use of CFA as the primary analysis may have biased towards a four-factor structure. Conclusions A four-factor CES-D structure was an appropriate fit for adolescents in Western countries; further research is required to determine the fit in in Asian countries. This has important implications for clinical use of the scale. Future research should consider how cultural differences shape the experience of depression in adolescents.

scholarly journals Acceptance and Intake of COVID-19 Vaccines among Older Germans

2021 ◽  
Vol 10 (7) ◽  
pp. 1388
Author(s):  
Marta Malesza ◽  
Erich Wittmann
Keyword(s):  
Side Effects ◽  
Long Term Effects ◽  
Negative Side ◽  
Factors Influencing ◽  
Vaccination Acceptance ◽  
Negative Side Effects

The main aim of this study was to investigate the various factors influencing COVID-19 vaccination acceptance and actual intake among older Germans aged over 75 years old (n = 1037). We found that the intention to get vaccinated or intake of the COVID-19 vaccine were positively related to the perceptions of becoming infected, perceptions of the severity of the potential long-term effects, the vaccine’s efficacy, and the benefits of vaccination. Meanwhile, the intention to get the vaccine or vaccine intake were decreased by perceptions of the negative side-effects and the general impediments to vaccination.

Exploring the Factor Structure of the Job Demands-Resources Measure With Patient Violence on Direct Care Workers in the Home Setting

2017 ◽  
Vol 25 (2) ◽  
pp. 257-274 ◽  
Author(s):  
Ha Do Byon ◽  
Donna Harrington ◽  
Carla L. Storr ◽  
Jane Lipscomb
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Job Demands ◽  
Direct Care ◽  
Direct Care Workers ◽  
Home Setting ◽  
Patient Violence ◽  
Measurement Framework ◽  
Care Workers

Background and Purpose: Workplace violence research in health care settings using the Job Demands-Resources (JD-R) framework is hindered by the lack of comprehensive examination of the factor structure of the JD-R measure when it includes patient violence. Is patient violence a component of job demands or its own factor as an occupational outcome? Method: Exploratory factor analysis and confirmatory factor analysis were conducted using a sample of direct care workers in the home setting (n = 961). Results: The overall 2-construct JD-R structure persisted. Patient violence was not identified as a separate factor from job demands; rather, two demand factors emerged: violence/emotional and workload/physical demands. Conclusions: Although the three-factor model fits the data, the two-factor model with patient violence being a component of job demands is a parsimonious and effective measurement framework.

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2022 ◽  
Author(s):  
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Keyword(s):  
Weight Loss ◽  
United Kingdom ◽  
Side Effects ◽  
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Essential CBD Extract Gummies [Australia] AU Reviews – Hidden Negative Side Effects Or Real Benefits? v1

2021 ◽  
Author(s):  
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Keyword(s):  
Side Effects ◽  
Negative Side ◽  
Negative Side Effects ◽  
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scholarly journals Evaluation of the Factor Structure of the Adolescent Stress Questionnaire in Chinese Adolescents

2018 ◽  
Vol 122 (6) ◽  
pp. 2366-2395
Author(s):  
Tianpeng Ye ◽  
Naixue Cui ◽  
Wen Yang ◽  
Jianghong Liu
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Behavioral Problems ◽  
Romantic Relationship ◽  
Factor Model ◽  
Chinese Adolescents ◽  
School Students ◽  
Cross Cultural Differences ◽  
Distinct Factor ◽  
Adolescent Stress

This study evaluated the psychometric properties of the Chinese version of Adolescent Stress Questionnaire ( ASQ-CN) in a sample of Chinese middle school students ( N = 420; 52.14% boys and 47.86% girls). Iterated principal factor analysis and multiple-group principal components cluster analysis supported a six-factor model with 42 items out of 58 items in the ASQ-CN. The internal consistency was from .82 to .90. Girls reported lower stress levels in one subscale, Stress of romantic relationship, whereas no gender differences were found in the other five subscales. Compared with other studies of the ASQ in Westernized countries, the ASQ-CN showed a distinct factor structure that may be explained by cross-cultural differences. Scales constructed from factor analysis related negatively to measures of mindfulness and positively to a measure of behavioral problems, suggesting that they were valid for Chinese adolescent stress. The study did not support a higher order construct of the ASQ-CN. Altogether, our findings suggest that the ASQ-CN is adequate for assessing stressors in Chinese adolescents.

scholarly journals Empirical Approach to Developing an Optimal Socioeconomic Status Index for Health Surveillance

2022 ◽  
Author(s):  
Jordana LaFantasie ◽  
Francis Boscoe
Keyword(s):  
Socioeconomic Status ◽  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Health Surveillance ◽  
Cancer Surveillance ◽  
Income Poverty ◽  
One Dimensional ◽  
Indicator Variables ◽  
Statistical Consistency

The association between multi-dimensional deprivation and public health is well established, and many area-based indices have been developed to measure or account for socioeconomic status in health surveillance. The Yost Index, developed in 2001, has been adopted in the US for cancer surveillance and is based on the combination of two heavily weighted (household income, poverty) and five lightly weighted (rent, home value, employment, education and working class) indicator variables. Our objectives were to 1) update indicators and find a more parsimonious version of the Yost Index by examining potential models that included indicators with more balanced weights/influence and reduced redundancy and 2) test the statistical consistency of the factor upon which the Yost Index is based. Despite the usefulness of the Yost Index, a one-factor structure including all seven Yost indicator variables is not statistically reliable and should be replaced with a three-factor model to include the true variability of all seven indicator variables. To find a one-dimensional alternative, we conducted maximum likelihood exploratory factor analysis on a subset of all possible combinations of fourteen indicator variables to find well-fitted one-dimensional factor models and completed confirmatory factor analysis on the resulting models. One indicator combination (poverty, education, employment, public assistance) emerged as the most stable unidimensional model. This model is more robust to extremes in local cost of living conditions, is comprised of ACS variables that rarely require imputation by the end-user and is a more parsimonious solution than the Yost index with a true one-factor structure.

scholarly journals A Multi-Objective Approach to Mitigate Negative Side Effects

2020 ◽  
Author(s):  
Sandhya Saisubramanian ◽  
Ece Kamar ◽  
Shlomo Zilberstein
Keyword(s):  
Side Effects ◽  
Empirical Evaluation ◽  
Primary Objective ◽  
Maximum Deviation ◽  
Negative Side ◽  
Multi Objective ◽  
Markov Decision ◽  
Secondary Objective ◽  
Negative Side Effects ◽  
The Impact

Agents operating in unstructured environments often create negative side effects (NSE) that may not be easy to identify at design time. We examine how various forms of human feedback or autonomous exploration can be used to learn a penalty function associated with NSE during system deployment. We formulate the problem of mitigating the impact of NSE as a multi-objective Markov decision process with lexicographic reward preferences and slack. The slack denotes the maximum deviation from an optimal policy with respect to the agent's primary objective allowed in order to mitigate NSE as a secondary objective. Empirical evaluation of our approach shows that the proposed framework can successfully mitigate NSE and that different feedback mechanisms introduce different biases, which influence the identification of NSE.

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