The Family Affluence Scale as a Measure of National Wealth: Validation of an Adolescent Self-Report Measure

2006 ◽  
Vol 78 (3) ◽  
pp. 473-487 ◽  
Author(s):  
William Boyce ◽  
Torbjorn Torsheim ◽  
Candace Currie ◽  
Alessio Zambon
Keyword(s):  
Self Report ◽  
Family Affluence Scale ◽  
Family Affluence ◽  
National Wealth ◽  
The Family ◽  
Report Measure

scholarly journals Does the family affluence scale reflect actual parental earned income, level of education and occupational status? A validation study using register data in Sweden

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maria Corell ◽  
Yun Chen ◽  
Peter Friberg ◽  
Max Petzold ◽  
Petra Löfstedt
Keyword(s):  
Educational Level ◽  
Occupational Status ◽  
Income Level ◽  
High Income ◽  
Register Data ◽  
Family Affluence Scale ◽  
Earned Income ◽  
Family Affluence ◽  
Level Of Education ◽  
The Family

Abstract Aim To examine the external validity of the Family Affluence Scale (FAS) among adolescents in Sweden by using register data for parental earned income, level of education and occupational status. Methods Data from the baseline (2015–2019) of the Study of Adolescence Resilience and Stress (STARS), comprising 2283 13-year-olds in the region of Västra Götaland, were used. The FAS III consists of six items: unshared bedroom, car ownership, computer/tablet ownership, dishwasher, number of bathrooms and number of holidays abroad. Register data regarding earned income, educational level and occupational status from Statistics Sweden (2014–2018) were linked to adolescents. In total, survey data were available for 2280 adolescents, and register data were available for 2258 mothers and 2204 fathers. Results Total parental earned income was moderately correlated with adolescents’ scoring on FAS (0.31 < r < 0.48, p < 0.001), depending on examination year. The low FAS group mainly comprised low-income households, and the high FAS group mainly comprised high-income households. Correlations between mothers’ and fathers’ educational level and adolescents’ scoring on FAS were low (r = 0.19 and r = 0.21, respectively, p < 0.001). FAS was higher among adolescents whose parents were working, but the correlation between parents’ occupational status and FAS was low (r = 0.22, p < 0.001). Conclusions The FAS can mainly identify low- and high-income households in Sweden. It may be used as an alternative measure of parental earned income in studies using self-reported socioeconomic status among adolescents.

scholarly journals FAMILY AFFLUENCE RELATIONSHIP TO SPORTS SPECIALIZATION IN YOUTH ATHLETES

2020 ◽  
Vol 8 (4_suppl3) ◽  
pp. 2325967120S0022
Author(s):  
Gregory A. Walker ◽  
Aubrey Armento ◽  
Katherine S. Dahab ◽  
Aaron J. Provance ◽  
Julie C. Wilson ◽  
...  
Keyword(s):  
Sports Medicine ◽  
The United States ◽  
Cross Sectional Study ◽  
Specific Information ◽  
Family Affluence Scale ◽  
Cross Sectional ◽  
Family Affluence ◽  
Youth Athletes ◽  
Patient Reported ◽  
The Family

Background: Specializing in a single sport while excluding others, also known as sports specialization, is increasing in prevalence in the United States. The effect of socioeconomic status (SES) on rates of sports specialization has been previously described in the specialty clinic setting using zip code as a surrogate for SES. Patient-reported family affluence, a validated surrogate for SES, may provide more specific information about how family SES is associated with sport specialization. Purpose/Hypothesis: Our purpose was to examine the association between patient-reported SES and sport specialization level. We hypothesized that athletes who reported higher levels of sports specialization would report greater family affluence. Methods: We conducted a cross-sectional study of youth athletes undergoing a pre-participation evaluation. During the assessment, participants specified their level of sport specialization on a 3-point scale described originally by Jayanthi and colleagues. Participants also completed the Family Affluence Scale, a 6-item scale which is a valid correlate of parental income. We compared family affluence among the sport specialization groups (low/medium/high) using ANOVA with Tukey post-hoc comparisons. We then constructed a multivariable linear regression model to assess the association between family affluence and sport specialization level while controlling for potential confounding variables. Results: A total of 195 youth athletes participated in the study. The majority (52%) reported low levels of sport specialization, 33% reported medium sport specialization, and 15% reported high sport specialization. The sport specialization groups were similar in age, proportion of females, and time spent training in their sport (Table 1). A significantly larger proportion of highly specialized athletes were varsity athletes compared to the low specialization group (Table 1). The high sport specialization group reported significantly greater family affluence than the low sport specialization group (Figure 1). After covariate adjustment, higher levels of sport specialization remained significantly associated with greater reported family affluence (Table 2). Conclusion: In our population of youth athletes, high sports specialization was associated with greater family affluence. Additionally, we found a significantly higher proportion of varsity level athletes in the high sports specialization groups. This study extends previous studies identifying greater sports specialization levels among those with higher SES. By using the Family Affluence Scale and sampling from a large and diverse population during a pre-participation evaluation, our findings reflect accurate patient-level associations. Examining SES and sports specialization affords the sports medicine community an opportunity to better identify and monitor populations who are likely to specialize in a single sport during high school. [Table: see text][Figure: see text][Table: see text]

Family Affluence Relationship to Sports Specialization in Youth Athletes

2020 ◽  
Vol 60 (1) ◽  
pp. 50-55
Author(s):  
Gregory A. Walker ◽  
Corrine N. Seehusen ◽  
Aubrey Armento ◽  
Aaron J. Provance ◽  
Julie C. Wilson ◽  
...  
Keyword(s):  
High School ◽  
Covariate Adjustment ◽  
Family Affluence Scale ◽  
Cross Sectional ◽  
Family Affluence ◽  
Youth Athletes ◽  
The Family ◽  
Youth Athlete ◽  
The Relationship ◽  
Group Family

Our objective was to examine the association between participant-reported family affluence and sport specialization level. We conducted a cross-sectional investigation of adolescent athletes. Specifically, participants completed a level of sport specialization (low/moderate/high) questionnaire and the Family Affluence Scale. The majority (52%) of the 195 youth athlete participants reported low, 33% reported moderate, and 15% reported high sport specialization. Sport specialization groups were similar in age (mean = 15.3 ± 1.6 years), proportion of females (49%), and time spent training (mean = 11.9 ± 5.0 hours per week). The high sport specialization group reported significantly greater family affluence than the low sport specialization group (Family Affluence Scale = 10.4 ± 1.7 vs 9.2 ± 1.9; P = .005). After covariate adjustment, higher levels of sport specialization remained significantly associated with greater family affluence (β = 0.48, 95% confidence interval = 0.11-0.86). Understanding the relationship between family affluence and sports specialization affords an opportunity to better identify and monitor populations likely to specialize in a single sport during high school.

Dimensionality and Reliability Assessment of the Pain Patient Profile Questionnaire

2008 ◽  
Vol 24 (1) ◽  
pp. 22-26 ◽  
Author(s):  
Brian E. McGuire ◽  
Michael J. Hogan ◽  
Todd G. Morrison
Keyword(s):  
Self Report ◽  
Pain Patient ◽  
Fit Indices ◽  
Depression And Anxiety ◽  
Oblique Rotation ◽  
Pain Experience ◽  
Patient Profile ◽  
Adequate Representation ◽  
Pain Patients ◽  
Report Measure

Abstract. Objective: To factor analyze the Pain Patient Profile questionnaire (P3; Tollison & Langley, 1995 ), a self-report measure of emotional distress in respondents with chronic pain. Method: An unweighted least squares factor analysis with oblique rotation was conducted on the P3 scores of 160 pain patients to look for evidence of three distinct factors (i.e., Depression, Anxiety, and Somatization). Results: Fit indices suggested that three distinct factors, accounting for 32.1%, 7.0%, and 5.5% of the shared variance, provided an adequate representation of the data. However, inspection of item groupings revealed that this structure did not map onto the Depression, Anxiety, and Somatization division purportedly represented by the P3. Further, when the analysis was re-run, eliminating items that failed to meet salience criteria, a two-factor solution emerged, with Factor 1 representing a mixture of Depression and Anxiety items and Factor 2 denoting Somatization. Each of these factors correlated significantly with a subsample's assessment of pain intensity. Conclusion: Results were not congruent with the P3's suggested tripartite model of pain experience and indicate that modifications to the scale may be required.

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