Correlates of Reflection-Impulsivity in Kindergarten Males: Intelligence, Socioeconomic Status, Race, Fathers' Absence, and Teachers' Ratings

1980 ◽  
Vol 47 (3_suppl) ◽  
pp. 1187-1191 ◽  
Author(s):  
Trina Plakosh Smith ◽  
Sheila C. Ribordy
Keyword(s):  
Socioeconomic Status ◽  
Cognitive Style ◽  
Socioeconomic Groups ◽  
Matching Familiar Figures Test ◽  
Reflection Impulsivity

72 kindergarten males were assessed for reflection-impulsivity with the Matching Familiar Figures test. Cognitive style on this test was examined in relation to intelligence, socioeconomic status, race, fathers' absence, and teachers' ratings of impulsivity. Significant findings included boys whose fathers were absent from the home made more errors on the test than boys whose fathers were present in the home. Teachers rated more intelligent boys as more impulsive, and these teachers' ratings were positively correlated with errors but not latencies. No significant differences in cognitive style were found for race or socioeconomic groups.

Relationship between Reflection-Impulsivity and Problem Solving

1976 ◽  
Vol 42 (1) ◽  
pp. 67-73 ◽  
Author(s):  
Gary A. Klein ◽  
Robert N. Blockovich ◽  
Pepi S. Buchalter ◽  
Linda Huyghe
Keyword(s):  
Problem Solving ◽  
Cognitive Style ◽  
Evaluation Criteria ◽  
Correct Order ◽  
Word Sequence ◽  
Matching Familiar Figures Test ◽  
Problem Solving Task ◽  
Reflection Impulsivity ◽  
Familiar Objects

Performance of 88 children categorized as reflective or impulsive was compared on convergent and divergent problem-solving tasks. The matching familiar-figures test was administered along with tests for determining the correct order of a word sequence, and for listing unusual uses for familiar objects. Reflective children ( n = 33) made significantly fewer errors on the convergent problem-solving task than impulsive children ( n = 33), but there was no effect of cognitive style on the divergent problem-solving task. Reflective-impulsive performance was discussed in terms of evaluation criteria for selecting responses.

scholarly journals Changes in cannabis use according to socioeconomic status among Finnish adolescents from 2000 to 2015

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Noora Knaappila ◽  
Mauri Marttunen ◽  
Sari Fröjd ◽  
Nina Lindberg ◽  
Riittakerttu Kaltiala
Keyword(s):  
Socioeconomic Status ◽  
Parental Education ◽  
Population Based ◽  
Cannabis Use ◽  
Chi Square ◽  
Socioeconomic Groups ◽  
Parental Unemployment ◽  
The Usa ◽  
Chi Square Test ◽  
School Survey

Abstract Background Despite reduced sanctions and more permissive attitudes toward cannabis use in the USA and Europe, the prevalences of adolescent cannabis use have remained rather stable in the twenty-first century. However, whether trends in adolescent cannabis use differ between socioeconomic groups is not known. The aim of this study was to examine trends in cannabis use according to socioeconomic status among Finnish adolescents from 2000 to 2015. Methods A population-based school survey was conducted biennially among 14–16-year-old Finns between 2000 and 2015 (n = 761,278). Distributions for any and frequent cannabis use over time according to socioeconomic adversities were calculated using crosstabs and chi-square test. Associations between any and frequent cannabis use, time, and socioeconomic adversities were studied using binomial logistic regression results shown by odds ratios with 95% confidence intervals. Results At the overall level, the prevalences of lifetime and frequent cannabis use varied only slightly between 2000 and 2015. Cannabis use was associated with socioeconomic adversities (parental unemployment in the past year, low parental education, and not living with both parents). The differences in any and frequent cannabis use between socioeconomic groups increased significantly over the study period. Conclusions Although the overall changes in the prevalence of adolescent cannabis use were modest, cannabis use increased markedly among adolescents with the most socioeconomic adversities. Socioeconomic adversities should be considered in the prevention of adolescent cannabis use.

Prevalence of Mental Disorders by Socioeconomic Status in Australia: A Cross-Sectional Epidemiological Study

2020 ◽  
pp. 089011712096865
Author(s):  
Rubayyat Hashmi ◽  
Khorshed Alam ◽  
Jeff Gow ◽  
Sonja March
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Socioeconomic Status ◽  
Mental Disorders ◽  
National Health Survey ◽  
Cross Sectional ◽  
Lower Odds ◽  
Socioeconomic Groups ◽  
Income Groups ◽  
Weighted Prevalence

Purpose: To present the prevalence of 3 broad categories of mental disorder (anxiety-related, affective and other disorders) by socioeconomic status and examine the associated socioeconomic risk factors of mental disorders in Australia. Design: A population-based, cross-sectional national health survey on mental health and its risk factors across Australia. Setting: National Health Survey (NHS), 2017-2018 conducted by the Australian Bureau of Statistics (ABS) Participants: Under aged: 4,945 persons, Adult: 16,370 persons and total: 21,315 persons Measures: Patient-reported mental disorder outcomes Analysis: Weighted prevalence rates by socioeconomic status (equivalised household income, education qualifications, Socio-Economic Index for Areas (SEIFA) scores, labor force status and industry sector where the adult respondent had their main job) were estimated using cross-tabulation. Logistic regression utilizing subsamples of underage and adult age groups were analyzed to test the association between socioeconomic status and mental disorders. Results: Anxiety-related disorders were the most common type of disorders with a weighted prevalence rate of 20.04% (95% CI: 18.49-21.69) for the poorest, 13.85% (95% CI: 12.48-15.35) for the richest and 16.34% (95% CI: 15.7-17) overall. The weighted prevalence rate for mood/affective disorders were 20.19% (95% CI: 18.63-21.84) for the poorest, 9.96% (95% CI: 8.79-11.27) for the richest, and 13.57% (95% CI: 12.99-14.17) overall. Other mental disorders prevalence were for the poorest: 9.07% (95% CI: 7.91-10.39), the richest: 3.83% (95% CI: 3.14-4.66), and overall: 5.93% (95% CI: 5.53-6.36). These patterns are also reflected if all mental disorders were aggregated with the poorest: 30.97% (95% CI: 29.15-32.86), the richest: 19.59% (95% CI: 18.02-21.26), and overall: 23.93% (95% CI: 23.19-24.69). The underage logistic regression model showed significant lower odds for the middle (AOR: 0.75, 95% CI: 0.53 -1.04, p < 0.1), rich (AOR: 0.71, 95% CI: 0.5-0.99, p < 0.05) and richest (AOR: 0.6, 95% CI: 0.41-0.89, p < 0.01) income groups. Similarly, in the adult logistic model, there were significant lower odds for middle (AOR: 0.84, 95% CI: 0.72-0.98, p < 0.05), rich (AOR: 0.73, 95% CI: 0.62-0.86, p < 0.01) and richest (AOR: 0.76, 95% CI: 0.63-0.91, p < 0.01) income groups. Conclusion: The prevalence of mental disorders in Australia varied significantly across socioeconomic groups. Knowledge of different mental health needs in different socioeconomic groups can assist in framing evidence-based health promotion and improve the targeting of health resource allocation strategies.

COGNITIVE IMPULSIVITY AND SOCIAL STATUS IN PREDELINQUENT PREADOLESCENT MALES

1979 ◽  
Vol 7 (2) ◽  
pp. 209-215
Author(s):  
David S. Glenwick ◽  
Roxanne G. F. Croft ◽  
Ralph Barocas ◽  
Harvey K. Black
Keyword(s):  
Social Status ◽  
Cognitive Style ◽  
Residential Setting ◽  
Cognitive Impulsivity ◽  
The Relationship ◽  
Matching Familiar Figures Test

The relationship between cognitive impulsivity, as measured by Kagan's Matching Familiar Figures Test (MFF), and interpersonal popularity was investigated in a sample of 42 “predelinquent” preadolescent boys in a residential setting. Predictions that the relationship would vary with the specific sociometric situations sampled were generally not confirmed. In fact, both the latency and errors dimensions of the MFF proved to have comparatively little association with social status, with age and intelligence demonstrating much stronger correlations with sociometric scores. Similarities to, and differences from, results with nondelinquent populations are discussed, as are implications for attempts at modifying cognitive style.

scholarly journals Leave No Child Behind: Using Data from 1.7 Million Children from 67 Developing Countries to Measure Inequality Within and Between Groups of Births and to Identify Left Behind Populations

2020 ◽  
Author(s):  
Antonio P. Ramos ◽  
Robert E. Weiss ◽  
Martin Flores
Keyword(s):  
Risk Factors ◽  
Socioeconomic Status ◽  
Mortality Risk ◽  
Rural Areas ◽  
Socioeconomic Group ◽  
Policy Makers ◽  
Socioeconomic Groups ◽  
Mortality Risks ◽  
Multiple Risk Factors ◽  
Left Behind

Background: Goal 3.2 from the Sustainable Development Goals (SDG) calls for reductions in national averages of Under-5 Mortality. However, it is well known that within countries these reductions can coexist with left behind populations that have mortality rates higher than national averages. To measure inequality in under-5 mortality and to identify left behind populations, mortality rates are often disaggregated by socioeconomic status within countries. While socioeconomic disparities are important, this approach does not quantify within group variability since births from the same socioeconomic group may have different mortality risks. This is the case because mortality risk depends on several risk factors and their interactions and births from the same socioeconomic group may have different risk factor combinations. Therefore mortality risk can be highly variable within socioeconomic groups. We develop a comprehensive approach using information from multiple risk factors simultaneously to measure inequality in mortality and to identify left behind populations. Methods: We use Demographic and Health Surveys (DHS) data on 1,691,039 births from 182 different surveys from 67 low and middle income countries, 51 of which had at least two surveys. We estimate mortality risk for each child in the data using a Bayesian hierarchical logistic regression model. We include commonly used risk factors for monitoring inequality in early life mortality for the SDG as well as their interactions. We quantify variability in mortality risk within and between socioeconomic groups and describe the highest risk sub-populations. Findings: For all countries there is more variability in mortality within socioe- conomic groups than between them. Within countries, socioeconomic membership usually explains less than 20% of the total variation in mortality risk. In contrast, country of birth explains 19% of the total variance in mortality risk. Targeting the 20% highest risk children based on our model better identifies under-5 deaths than targeting the 20% poorest. For all surveys, we report efficiency gains from 26% in Mali to 578% in Guyana. High risk births tend to be births from mothers who are in the lowest socioeconomic group, live in rural areas and/or have already experienced a prior death of a child. Interpretation: While important, differences in under-5 mortality across socioeconomic groups do not explain most of overall inequality in mortality risk because births from the same socioeconomic groups have different mortality risks. Similarly, policy makers can reach the highest risk children by targeting births based on several risk factors (socioeconomic status, residing in rural areas, having a previous death of a child and more) instead of using a single risk factor such as socioeconomic status. We suggest that researchers and policy makers monitor inequality in under-5 mortality us- ing multiple risk factors simultaneously, quantifying inequality as a function of several risk factors to identify left behind populations in need of policy interventions and to help monitor progress toward the SDG.

Socioeconomic status: the prime indicator of premature death in Australia

1993 ◽  
Vol 25 (4) ◽  
pp. 539-552 ◽  
Author(s):  
James S. Lawson ◽  
Deborah Black
Keyword(s):  
Socioeconomic Status ◽  
Heart Disease ◽  
Health Status ◽  
Premature Death ◽  
Social Classes ◽  
Important Indicator ◽  
Death Rates ◽  
Socioeconomic Groups ◽  
Premature Deaths ◽  
Socioeconomic Status And Health

SummaryThe link between socioeconomic status and health has long been recognised. This study of deaths among Australian men aged 15–59 years demonstrates that during the 20-year period, 1966–86 the number of premature deaths was dramatically reduced among all socioeconomic groups, primarily as a result of falls in death rates due to heart disease, stroke and trauma. However, the marked differences in death rates according to social class remain, to the extent that if men of all social classes had the same mortality experiences as professional and technical workers the overall death rates for Australian men would be reduced by 60%. Socioeconomic status is the most important indicator of health status among Australians.

scholarly journals Socioeconomic inequalities in the access to and quality of health care services

2014 ◽  
Vol 48 (6) ◽  
pp. 968-976 ◽  
Author(s):  
Bruno Pereira Nunes ◽  
Elaine Thumé ◽  
Elaine Tomasi ◽  
Suele Manjourany Silva Duro ◽  
Luiz Augusto Facchini
Keyword(s):  
Health Care ◽  
Socioeconomic Status ◽  
Health Care Services ◽  
Access To Health Services ◽  
Socioeconomic Groups ◽  
Care Services ◽  
Access To Health ◽  
To Receive ◽  
Use Of Health Care

OBJECTIVE To assess the inequalities in access, utilization, and quality of health care services according to the socioeconomic status. METHODS This population-based cross-sectional study evaluated 2,927 individuals aged ≥ 20 years living in Pelotas, RS, Southern Brazil, in 2012. The associations between socioeconomic indicators and the following outcomes were evaluated: lack of access to health services, utilization of services, waiting period (in days) for assistance, and waiting time (in hours) in lines. We used Poisson regression for the crude and adjusted analyses. RESULTS The lack of access to health services was reported by 6.5% of the individuals who sought health care. The prevalence of use of health care services in the 30 days prior to the interview was 29.3%. Of these, 26.4% waited five days or more to receive care and 32.1% waited at least an hour in lines. Approximately 50.0% of the health care services were funded through the Unified Health System. The use of health care services was similar across socioeconomic groups. The lack of access to health care services and waiting time in lines were higher among individuals of lower economic status, even after adjusting for health care needs. The waiting period to receive care was higher among those with higher socioeconomic status. CONCLUSIONS Although no differences were observed in the use of health care services across socioeconomic groups, inequalities were evident in the access to and quality of these services.

Is the Matching Familiar Figures Test a Measure of Cognitive Style?: A Warning for Users

1987 ◽  
Vol 64 (1) ◽  
pp. 59-74 ◽  
Author(s):  
Pedro Solís-Cámara R. ◽  
Pedro Solís-Cámara V.
Keyword(s):  
Fourth Graders ◽  
Evaluation Process ◽  
Total Sample ◽  
Random Response ◽  
Cognitive Response ◽  
Initial Errors ◽  
Median Split ◽  
Response Group ◽  
Matching Familiar Figures Test ◽  
Reflection Impulsivity

A probabilistic model of reflection-impulsivity as measured by the Matching Familiar Figures Test (MFFT) is presented and tested on 77 fourth graders. In testing the model two groups emerged, a random response group ( n = 22) and a cognitive response group ( n = 55), who use the evaluation process. Correlations among latencies, total errors, initial errors, school-scores, and IQs were compared for our total sample and the two groups. The correlation of MFFT latencies and errors disappeared for the random-response group and new correlations with errors appeared while the cognitive response group kept a statistically significant correlation of latencies with errors and no other error correlation was shown. This last group was classified by Kagan's median-split procedure showing that most reflective subjects kept their classification. Preliminary results suggest a reinterpretation of reflection-impulsivity literature, especially as related to the impulsive style.

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