The Computer-Vision Symptom Scale (CVSS17): Development and Initial Validation

Purpose.: To develop a questionnaire (in Spanish) to measure computer-related visual and ocular symptoms (CRVOS). Methods.: A pilot questionnaire was created by consulting the literature, clinicians, and video display terminal (VDT) workers. The replies of 636 subjects completing the questionnaire were assessed using the Rasch model and conventional statistics to generate a new scale, designated the Computer-Vision Symptom Scale (CVSS17). Validity and reliability were determined by Rasch fit statistics, principal components analysis (PCA), person separation, differential item functioning (DIF), and item–person targeting. To assess construct validity, the CVSS17 was correlated with a Rasch-based visual discomfort scale (VDS) in 163 VDT workers, this group completed the CVSS17 twice in order to assess test-retest reliability (two-way single-measure intraclass correlation coefficient [ICC] and their 95% confidence intervals, and the coefficient of repeatability [COR]). Results.: The CVSS17 contains 17 items exploring 15 different symptoms. These items showed good reliability and internal consistency (mean square infit and outfit 0.88–1.17, eigenvalue for the first residual PCA component 1.37, person separation 2.85, and no DIF). Pearson's correlation with VDS scores was 0.60 (P < 0.001). Intraclass correlation coefficient for test–retest reliability was 0.849 (95% confidence interval [CI], 0.800–0.887), and COR was 8.14. Conclusions.: The Rasch-based linear-scale CVSS17 emerged as a useful tool to quantify CRVOS in computer workers

Intraexaminer repeatability and agreement in stereoacuity measurements made in young adults

·AIM: To determine the repeatability and agreement of stereoacuity measurements made using some of the most widely used clinical tests: Frisby, TNO, Randot and Titmus. ·METHODS: Stereoacuity was measured in two different sessions separated by a time interval of at least 24h but no longer than 1wk in 74 subjects of mean age 20.6y using the four methods. The study participants were divided into two groups: subjects with normal binocular vision and subjects with abnormal binocular vision. ·RESULTS: Best repeatability was shown by the Frisby and Titmus [coefficient of repeatability (COR): 依13 and 依12s arc respectively] in the subjects with normal binocular vision though a clear ceiling effect was noted. In the subjects with abnormal binocular vision, best repeatability was shown by the Frisby (COR: 依69s arc) and Randot (COR: 依72s arc). In both groups, the TNO test showed poorest agreement with the other tests. ·CONCLUSION: Therepeatabilityof stereoacuitymeasures was low in subjects with poor binocular vision yet fairly good in subjects with normal binocular vision with the exception of the TNO test. The reduced agreement detected between the tests indicates they cannot be used interchangeably

Deep-learning based detection for cyber-attacks in IoT networks: A distributed attack detection framework

The widespread use of smart devices and the numerous security weaknesses of networks has dramatically increased the number of cyber-attacks in the internet of things (IoT). Detecting and classifying malicious traffic is key to ensure the security of those systems. This paper implements a distributed framework based on deep learning (DL) to prevent many different sources of vulnerability at once, all under the same protection system. Two different DL models are evaluated: feed forward neural network and long short-term memory. The models are evaluated with two different datasets (i.e.NSL-KDD and BoT-IoT) in terms of performance and identification of different kinds of attacks. The results demonstrate that the proposed distributed framework is effective in the detection of several types of cyber-attacks, achieving an accuracy up to 99.95% across the different setups.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work is partially supported by the Spanish Ministry of Science and Innovation under contract PID2021-124463OB-IOO, by the Generalitat de Catalunya under grants 2017SGR962, 2021SGR00326, and by the DRAC (IU16-011591), the HORIZON Vitamin-V (101093062) and the HORIZON-AG PHOENI2X (101070586) projects.Peer ReviewedPostprint (published version

Complemento audiovisual para el aprendizaje de procedimientos clínicos optométricos de visión binocular no estrábica

El resultado de este proyecto consta de 35 vídeotutoriales de exploración a pacientes, que complementan el aprendizaje de procedimientos clínicos relacionados con la visión binocular no estrábica. Sirven como guía previa a la realización de las prácticas y de complemento para el estudio de los procedimientos

Symptoms associated with reading from a smartphone in conditions of light and dark

Asthenopia symptoms were investigated in visually-normal subjects without computer-related vision symptoms after prolonged reading from: smartphone versus hardcopy under photopic conditions, and smartphone in conditions of ambient versus dark room illumination. After reading from the smartphone, total symptom scores and nine out of ten questionnaire symptoms were significantly worse than for the hardcopy (“blurred vision while viewing the text, “blurred distance vision after the task”, “difficulty in refocusing from one distance to another”, “irritated or burning eyes”, “dry eyes”, “eyestrain”, “tired eyes”, “sensitivity to bright lights” and “eye discomfort”). Mean total symptom scores and scores for “irritated or burning eyes” and “dry eyes” were significantly higher for the dark versus photopic conditions. In conclusion, prolonged smartphone reading could cause worse asthenopic symptoms than reading from a hardcopy under similar conditions. Symptoms could be even worse when reading from a smartphone in the dark

Five levels of performance and two subscales identified in the computer-vision symptom scale (CVSS17) by Rasch, factor, and discriminant analysis

Purpose: To quantify the levels of performance (symptom severity) of the computer-vision symptom scale (CVSS17), confirm its bifactorial structure as detected in an exploratory factor analysis, and validate its factors as subscales. Methods: By partial credit model (PCM), we estimated CVSS17 measures and the standard error for every possible raw score, and used these data to determine the number of different performance levels in the CVSS17. In addition, through discriminant analysis, we checked that the scale's two main factors could classify subjects according to these determined levels of performance. Finally, a separate Rasch analysis was performed for each CVSS17 factor to assess their measurement properties when used as isolated scales. Results: We identified 5.8 different levels of performance. Discriminant functions obtained from sample data indicated that the scale's main factors correctly classified 98.4% of the cases. The main factors: Internal symptom factor (ISF) and external symptom factor (ESF) showed good measurement properties and can be considered as subscales. Conclusion: CVSS17 scores defined five different levels of performance. In addition, two main factors (ESF and ISF) were identified and these confirmed by discriminant analysis. These subscales served to assess either the visual or the ocular symptoms attributable to computer use

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Spanish Cross-Cultural Adaptation, Rasch Analysis and Validation of the Ocular Comfort Index (OCI) Questionnaire

The Ocular Comfort Index (OCI) assesses ocular surface irritation and grades the severity of dry eye disease. This study sought to adapt the OCI questionnaire into Spanish, and then to assess the psychometric performance and validity of the new adapted version (OCI-versión española, OCIVE). The questionnaire was translated, back translated, and then cross-culturally adapted for use with Spanish-speaking individuals. The OCIVE was completed by 450 participants, including 53 subjects that were diagnosed with dry eye disease. Through a Rasch analysis, the psychometric properties of item fit, targeting, person separation, reliability, and differential item functioning (DIF) were assessed. To test the convergent validity, we examined the correlation between the OCIVE and the Computer Vision Symptom Scale (CVSS17). Validity was tested in a subgroup of participants with and without dry eye, and test-retest repeatability was determined in a subset of 151 individuals. We also compared, via DIF, the performance of the OCIVE with that of the original OCI. Our Rasch analysis revealed a good model fit, high accuracy, good targeting, unidimensionality, and no DIF according to gender. The validity and repeatability were good. The OCIVE shows comparable psychometric properties to the original English version, making it a valid tool for measuring dry eye symptoms in Spanish adults

Spanish Cross-Cultural Adaptation and Rasch Analysis of the Convergence Insufficiency Symptom Survey (CISS)

Purpose: To culturally and linguistically adapt the Convergence Insufficiency Symptom Survey (CISS) to Spanish and assess the psychometric performance of the new version through Rasch analysis and classical test theory methods. Methods: The Spanish version of the CISS (CISSVE ) was completed by 449 subjects (9– 30 years old) from the general population. The validity and reliability of CISSVE were assessed through Rasch statistics (precision, targeting, item fit, unidimensionality, and differential item functioning). To test construct validity, we calculated the coefficients of correlation between the CISSVE and the Computer-Vision Symptom Scale (CVSS17) or Warwick–Edinburgh Mental Well-Being Scale (WEMWBS). We determined test–retest reliability in a subset of 229 subjects. We used differential item functioning (DIF) to compare the CISSSVE and the CISS after administering the CISS to 216 English children. Results: After applying exclusion criteria, the responses of 420 participants (mean age, 18.62 years; female, 54.95%) revealed good Rasch model fit, good precision (person separation = 2.33), and suboptimal targeting (–1.37). There was some evidence of multidimensionality, but disattenuated correlations between the Rasch dimension and a possible secondary dimension were high, suggesting they were measuring similar constructs. No item bias according to gender or age was detected. Spearman’s correlation was 0.34 (P < 0.001) for CISSVE –CVSS17 and non-significant for CISSVE –WEMWBS. The limits of agreement for test–retest reliability were 9.67 and –8.71. Rasch analysis results indicated no difference between CISS and CISSVE. Conclusions: According to our results, CISSVE is a valid and reliable tool for measuring the symptoms assessed by CISS in Spanish people 9 to 30 years of age. Translational Relevance: CISSVE can measure convergence insufficiency symptoms in Spanish-speaking subjects