scholarly journals The Effect of Seriousness and Device Use on Data Quality

2019 ◽  
Vol 38 (6) ◽  
pp. 720-738
Author(s):  
Anne-Roos Verbree ◽  
Vera Toepoel ◽  
Dominique Perada
Keyword(s):  
Data Quality ◽  
Demographic Characteristics ◽  
Self Report ◽  
Data Consistency ◽  
Future Research ◽  
Multiple Indicators ◽  
Multiple Data ◽  
Gender And Age ◽  
Device Use

Nonserious, inattentive, or careless respondents pose a threat to the validity of self-report research. The current study uses data from the Growth from Knowledge Online Panel in which respondents are representative of the Dutch population in education, gender, and age over 15 years ( N = 5,077). By doing regression analyses, we investigated whether self-reported seriousness and motivation are predictive of data quality, as measured using multiple indicators (i.e., nonsubstantial values, speeding, internal data consistency, nondifferentiation, response effects). Device group and demographic characteristics (i.e., education, gender, age) were also included in these analyses to see whether they predict data quality. Moreover, it was examined whether self-reported seriousness differed by device group and demographic characteristics. The results show that self-reported seriousness and motivation significantly predict multiple data quality indicators. Data quality seems similar for different device users, although smartphone users showed less speeding. Demographic characteristics explain little of the variance in data quality. Of those, education seems to be the most consistent predictor of data quality, where lower educated respondents show lower data quality. Effect sizes for all analyses were in the small to medium range. The present study shows that self-reported seriousness can be used in online attitude survey research to detect careless respondents. Future research should clarify the nature of this relationship, for example, regarding longer surveys and different wordings of seriousness checks.

The Relationship Between Interoception and Metacognition

2016 ◽  
Vol 30 (2) ◽  
pp. 76-86 ◽  
Author(s):  
Judith Meessen ◽  
Verena Mainz ◽  
Siegfried Gauggel ◽  
Eftychia Volz-Sidiropoulou ◽  
Stefan Sütterlin ◽  
...  
Keyword(s):  
Memory Performance ◽  
Memory Task ◽  
Demographic Characteristics ◽  
Metacognitive Awareness ◽  
Interoceptive Awareness ◽  
Future Research ◽  
Heartbeat Perception ◽  
Interoceptive Accuracy ◽  
The Relationship

Abstract. Recently, Garfinkel and Critchley (2013) proposed to distinguish between three facets of interoception: interoceptive sensibility, interoceptive accuracy, and interoceptive awareness. This pilot study investigated how these facets interrelate to each other and whether interoceptive awareness is related to the metacognitive awareness of memory performance. A sample of 24 healthy students completed a heartbeat perception task (HPT) and a memory task. Judgments of confidence were requested for each task. Participants filled in questionnaires assessing interoceptive sensibility, depression, anxiety, and socio-demographic characteristics. The three facets of interoception were found to be uncorrelated and interoceptive awareness was not related to metacognitive awareness of memory performance. Whereas memory performance was significantly related to metamemory awareness, interoceptive accuracy (HPT) and interoceptive awareness were not correlated. Results suggest that future research on interoception should assess all facets of interoception in order to capture the multifaceted quality of the construct.

scholarly journals Occupational groups and its physical and mental health correlates: results from the Singapore Mental Health Study 2016

2021 ◽  
Author(s):  
Rajeswari Sambasivam ◽  
Anitha Jeyagurunathan ◽  
Edimansyah Abdin ◽  
Saleha Shafie ◽  
Sherilyn Chang ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Mental Health ◽  
Work Productivity ◽  
Demographic Characteristics ◽  
Self Report ◽  
World Health ◽  
Physical Disorder ◽  
Occupational Groups ◽  
Physical Disorders

Abstract Purpose The physical and mental wellbeing of an individual is impacted by the type occupation one does. This study aims to establish the prevalence of mental and physical disorders, the association of occupational groups and health-related quality of life, and the extent of work-loss and work-cut back in past 30 days among the employed in the Singapore resident population. Methods Data from a population-based, epidemiological survey of a representative sample of Singapore citizens and permanent residents aged 18 years and above were used. Lifetime diagnosis of select mental disorders was established using the World Health Organization’s Composite International Diagnostic Interview version 3.0 (WHO-CIDI 3.0). Data on nicotine dependence, work productivity, quality of life and socio-demographics were obtained via self-report. Ten major occupational groups based on the Singapore Standard Occupational Classification were included in the analysis. Results The sample comprised 4021 employed individuals who were predominantly males (54.7%) and aged 35–49 years (35.4%). ‘Service and sales workers’ (22.6%), ‘Professionals’ (17.3%) and ‘Legislators, senior officials and managers’ (16.4%) were the three largest occupational groups. Socio-demographic characteristics differed significantly (p < 0.001) across all occupational groups. Lifetime prevalence of mood disorders among the employed was 8.4% and the most prevalent physical disorder was chronic pain (18.9%). No significant differences were observed in work productivity loss across the occupational groups. Conclusions The disparities in the socio-demographic characteristics and prevalence of mental and physical disorders across occupational categories provide policymakers with vital information to pilot effective interventions that can improve the psychosocial and physical conditions at work.

Big Data Quality for Data Mining in Business Intelligence Applications

2021 ◽  
pp. 64-91
Author(s):  
Arun Thotapalli Sundararaman
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Quality ◽  
Business Intelligence ◽  
Future Research ◽  
Quality Factors ◽  
Data Volume ◽  
Mining Algorithms ◽  
Data Mining Application

Study of data quality for data mining application has always been a complex topic; in the recent years, this topic has gained further complexity with the advent of big data as the source for data mining and business intelligence (BI) applications. In a big data environment, data is consumed in various states and various forms serving as input for data mining, and this is the main source of added complexity. These new complexities and challenges arise from the underlying dimensions of big data (volume, variety, velocity, and value) together with the ability to consume data at various stages of transition from raw data to standardized datasets. These have created a need for expanding the traditional data quality (DQ) factors into BDQ (big data quality) factors besides the need for new BDQ assessment and measurement frameworks for data mining and BI applications. However, very limited advancement has been made in research and industry in the topic of BDQ and their relevance and criticality for data mining and BI applications. Data quality in data mining refers to the quality of the patterns or results of the models built using mining algorithms. DQ for data mining in business intelligence applications should be aligned with the objectives of the BI application. Objective measures, training/modeling approaches, and subjective measures are three major approaches that exist to measure DQ for data mining. However, there is no agreement yet on definitions or measurements or interpretations of DQ for data mining. Defining the factors of DQ for data mining and their measurement for a BI system has been one of the major challenges for researchers as well as practitioners. This chapter provides an overview of existing research in the area of BDQ definitions and measurement for data mining for BI, analyzes the gaps therein, and provides a direction for future research and practice in this area.

scholarly journals El impacto de la valoración de la importancia en la evaluación de la calidad de vida en adolescentes chilenos

2015 ◽  
Vol 14 (2) ◽  
pp. 723
Author(s):  
Alfonso Urzúa ◽  
Alejandra Caqueo-Urízar ◽  
María Fernanda Bravo ◽  
Karen Carvajal ◽  
Claudio Vera
Keyword(s):  
Quality Of Life ◽  
Self Report ◽  
State Universities ◽  
Quantitative Methodology ◽  
The North ◽  
Calidad De Vida ◽  
Gender And Age ◽  
The Impact ◽  
The City

While self-report of overall quality of life has been widely examined, there are no studies that explore the impact of the relative importance people give to the various categories of their quality of life. Therefore, with a quantitative methodology and a co-relational transverse design, we analyze differences in the assessment when the importance given to each category is evaluated. Participants were 530 students from the city of Antofagasta in the North of Chile, aged between 15 and 18 years. They were from subsidized, public secondary schools and private and state universities in the city who were assessed using the KIDSCREEN-27 questionnaire. Results: Differences were found in the assessment of categories when results were analyzed based on gender and age and when incorporating an assessment of importance. Even when the results were not conclusive, there was evidence of a need to incorporate an importance variable when assessing quality of life.

scholarly journals The Abbreviated Psychopathy Measure (APM): Two Pilot Studies of a Brief Measure of Psychopathy Traits

2018 ◽  
Vol 10 (2) ◽  
pp. 41 ◽  
Author(s):  
Robert Semel
Keyword(s):  
Construct Validity ◽  
Internal Consistency ◽  
Self Report ◽  
Future Research ◽  
Normal Range ◽  
Pilot Studies ◽  
Personality Variables ◽  
High Internal Consistency ◽  
Highly Correlated

Two studies were undertaken to examine preliminary construct validity of a newly developed, abbreviated measure of psychopathy.  The Abbreviated Psychopathy Measure (APM) is a 33-item inventory that is closely modeled on the Triarchic Psychopathy Measure (TriPM; Patrick, 2010), with a new and more parsimonious set of items.  Analyses in Study 1 ( = 126) found that the Boldness, Meanness, and Disinhibition scales of the APM had high internal consistency reliabilities and were highly correlated with their counterpart scales on the TriPM.  The APM Total score was very highly correlated with the TriPM Total score (r = .90).  Each of the APM scales was also significantly correlated with a measure of Antisocial Intent.  In Study 2 (N = 140), the APM was very highly correlated with the Total score of a 36-item version of the Levenson Self-Report Psychopathy Scales (LSRP; Levenson, Kiehl, &amp; Fitzpatrick, 1995). Additionally, the APM scales were associated differentially with normal range personality variables associated with psychopathy (e.g., Boldness was robustly associated with Extraversion, Meanness was highly and inversely associated with Agreeableness, Disinhibition was robustly and negatively associated with Conscientiousness).  The APM appeared to differ most significantly from the TriPM in that APM Boldness was moderately correlated with Meanness and Disinhibition.  APM Boldness may capture a more maladaptive quality of boldness relative to TriPM Boldness through a greater emphasis on low harm avoidance or fearlessness in comparison to TriPM Boldness.  The APM is potentially a promising brief measure of psychopathy; however, further study is needed to determine whether the moderately inter-correlated APM scales can distinguish among conceptually relevant constructs.  Directions for future research are discussed.

Initial Management of Low-Risk Pediatric Fever and Neutropenia: Efficacy and Safety, Costs, Quality-of-Life Considerations, and Preferences

2012 ◽  
pp. 570-574
Author(s):  
Lillian Sung
Keyword(s):  
Quality Of Life ◽  
Low Risk ◽  
Self Report ◽  
Future Research ◽  
Outpatient Management ◽  
Management Options ◽  
Initial Management ◽  
Parent Proxy Report ◽  
Meta Analyses

Overview: Initial management options for pediatric low-risk fever and neutropenia (FN) include outpatient compared with inpatient management and oral compared with intravenous therapy. Single-arm and randomized trials have been conducted in children. Meta-analyses provide support for the equivalence of outpatient and inpatient approaches. Outpatient oral management may be associated with a higher risk of readmission compared with outpatient intravenous management in children with FN, although other outcomes such as treatment failure and discontinuation of the regimen because of adverse effects were similar. Importantly, there have been no reported deaths among low-risk children treated as outpatients or with oral antibiotics. Costs, whether derived directly or through cost-effectiveness analysis, are consistently reduced when an outpatient approach is used. Quality of life (QoL) and preferences should be considered in order to evaluate different strategies, plan programs, and anticipate uptake of outpatient programs. Using parent-proxy report, child QoL is consistently higher with outpatient approaches, although research evaluating child self-report is limited. Preferences incorporate estimated QoL, but, in addition, factor in issues such as costs, fear, anxiety, and logistical issues. Only approximately 50% of parents prefer outpatient management. Future research should develop tools to facilitate outpatient care and to measure caregiver burden associated with this strategy. Additional work should also focus on eliciting child preferences for outpatient management. Finally, studies of effectiveness of an ambulatory approach in the real-world setting outside of clinical trials are important.

Development of a tool to assess client-centered practice on a domestic violence hotline

2018 ◽  
Vol 19 (1) ◽  
pp. 102-120 ◽  
Author(s):  
Jessica Grossmann ◽  
Rachel Shor ◽  
Karen Schaefer ◽  
Lauren Bennett Cattaneo
Keyword(s):  
Domestic Violence ◽  
Assessment Tool ◽  
Research Evaluation ◽  
Self Report ◽  
Trauma Survivors ◽  
Future Research ◽  
Measurement Tools ◽  
Two Phases ◽  
Vantage Points

Summary Client-centered practice, also termed survivor-centered practice in the context of domestic violence, has broad support as a set of strategies for working effectively with trauma survivors. However, research, evaluation and staff training are limited by a lack of measurement tools. This paper describes the process of developing an index of hotline caller reactions to practitioners’ client-centered practices. Findings The project was a collaborative effort between academic researchers and practitioners working in a community agency. To generate and refine the items, researchers consulted the scholarly literature and agency materials, had discussions with practitioners, and coded a group of 25 recorded calls to the agency’s hotline. The resulting tool separates two phases of the hotline calls and identifies 23 client reactions to advocate behaviors that indicate the client-centeredness of the interaction. Application The collaborative nature of the process ensured that the final product included multiple vantage points on client-centered practice. The tool developed in this study, the Client-Centered Hotline Assessment Tool (C-CHAT), may be used for research, evaluation, and training. Future research could explore the generalizability and, consequently, predictive utility of the tool in outcomes of interest to practitioners. In evaluation, the tool allows agencies, in assessing client experience, to go beyond client self-report of general satisfaction, and to improve services in response. Finally, in training, the tool allows supervisors to assess the level of fidelity to the client-centered model, and to pinpoint particular aspects of interactions that suggest strengths or growth areas for staff, ultimately improving the quality of services.

Data Quality for Data Mining in Business Intelligence Applications

2015 ◽  
pp. 34-59
Author(s):  
Arun Thotapalli Sundararaman
Keyword(s):  
Data Mining ◽  
Data Quality ◽  
Business Intelligence ◽  
Objective Measures ◽  
Future Research ◽  
Subjective Measures ◽  
Research And Practice ◽  
Modeling Approaches ◽  
Mining Algorithms

Data Quality (DQ) in data mining refers to the quality of the patterns or results of the models built using mining algorithms. DQ for data mining in Business Intelligence (BI) applications should be aligned with the objectives of the BI application. Objective measures, training/modeling approaches, and subjective measures are three major approaches that exist to measure DQ for data mining. However, there is no agreement yet on definitions or measurements or interpretations of DQ for data mining. Defining the factors of DQ for data mining and their measurement for a BI System has been one of the major challenges for researchers as well as practitioners. This chapter provides an overview of existing research in the area of DQ definition and measurement for data mining for BI, analyzes the gaps therein, besides reviewing proposed solutions and providing a direction for future research and practice in this area.

scholarly journals Health-related quality of life in Iranian adolescents: a psychometric evaluation of the self-report form of the PedsQL 4.0 and an investigation of gender and age differences

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Habib Hadianfard ◽  
Behnaz Kiani ◽  
Mahla Azizzadeh Herozi ◽  
Fatemeh Mohajelin ◽  
John T. Mitchell
Keyword(s):  
Quality Of Life ◽  
Psychometric Properties ◽  
Internal Consistency ◽  
Convergent Validity ◽  
Age Effects ◽  
Self Report ◽  
Gender And Age ◽  
Pedsql 4.0 ◽  
Test Retest Reliability

Abstract Background Research on the psychometric properties of the Persian self-report form of the Pediatric Quality of Life Inventory Version 4.0 (PedsQL 4.0) in adolescents has several gaps (e.g., convergent validity) that limit its clinical application and therefore the cross-cultural impact of this measure. This study aimed at investigating the psychometric properties of the PedsQL 4.0 and the effects of gender and age on quality of life in Iranian adolescents. Method The PedsQL 4.0 was administered to 326 adolescents (12–17 years). A subsample of 115 adolescents completed the scale two weeks after the first assessment. Confirmatory Factor Analysis (CFA), correlation of the PedsQL 4.0 with the Weiss Functional Impairment Rating Scale-Self-report (WFIRS-S), and Item Response Theory (IRT) analysis were conducted to examine validity. Cronbach’s alpha, McDonald’s Omega, and Intra class correlation (ICC) were calculated as well to examine reliability. Gender and age effects were also evaluated. Results Internal consistency and test–retest reliability of the total PedsQL 4.0 scale was .92 and .87, respectively. The PedsQL 4.0 scores showed negative moderate to strong correlations with the WFIRS-S total scale. The four-factor model of the PedsQL 4.0 was not fully supported by the CFA—the root mean square error of approximation and the comparative fit index showed a mediocre and poor fit, respectively. IRT analysis indicated that all items of the PedsQL 4.0 fit with the scale and most of them showed good discrimination. The items and total scale provided more information in the lower levels of the latent trait. Males showed significantly higher scores than females in physical and emotional functioning, psychosocial health, and total scale. Adolescents with lower ages showed better quality of life than those with higher ages in all scores of the PedsQL 4.0. Conclusion The PedsQL 4.0 showed good psychometric properties with regard to internal consistency, test–retest reliability, and convergent validity in Iranian adolescents, which supports its use in clinical settings among Persian-speaking adolescents. However, factor structure according to our CFA indicates that future work should address how to improve fit. In addition, studies that include PedsQL 4.0 should consider gender and age effects were reported.

scholarly journals Improving Data Quality in Citizen Science Apps for Conservation Biology

2018 ◽  
Vol 2 ◽  
pp. e26665
Author(s):  
Alan Stenhouse ◽  
Philip Roetman ◽  
Frank Grützner ◽  
Tahlia Perry ◽  
Lian Pin Koh
Keyword(s):  
User Interface ◽  
Data Quality ◽  
Citizen Science ◽  
Rapid Development ◽  
Lessons Learned ◽  
Future Research ◽  
Population Census ◽  
Population Modelling ◽  
App Development

Field data collection by Citizen Scientists has been hugely assisted by the rapid development and spread of smart phones as well as apps that make use of the integrated technologies contained in these devices. We can improve the quality of the data by increasing utilisation of the device in-built sensors and improving the software user-interface. Improvements to data timeliness can be made by integrating directly with national and international biodiversity repositories, such as the Atlas of Living Australia (ALA). I will present two Citizen Science apps that we developed for the conservation of two of Australia’s iconic species – the koala and the echidna. First is the Koala Counter app used in the Great Koala Count 2 – a two-day Blitz-style population census. The aim was to improve both the recording of citizen science effort as well as to improve the recording of “absence” data which would improve population modelling. Our solution was to increase the transparent use of the phone sensors as well as providing an easy-to-use user interface. Second is the EchidnaCSI app – an observational tool for collecting sightings and samples of echidna. From a software developer’s perspective, I will provide details on multi-platform app development as well as collaboration and integration with the Australian national biodiversity repository – the Atlas of Living Australia. Preliminary analysis regarding data quality will be presented along with lessons learned and paths for future research. I also seek feedback and further ideas on possible enhancements or modifications that might usefully be made to improve these techniques.

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