neighborhood contexts during the middle school years, which has been described elsewhere (Hughes et al., 2008). The analytic sample consisted of 387 ado- lescents who identified as Black (n − 149; 38.5%). Dominican American (n − 114; 29.5%), and Chinese American (n =124; 32.0%; see Supporting Information for exclusionary criteria). Table 1 presents the demo- graphic characteristics for each ethnic-racial group by sex, maternal education, school, and immigrant status. There were no differences in the gender composition of adolescents from the three ethnic-racial groups, z(2)-247, p = ns. Relative to Black and Dominican American youth, Chinese American youth were more likely to come from households with mothers who were less well educated, F(2, 388)-9.38, p<.001. Black and Dominican American youth in the sample were represented at all six schools, and Chinese American youth were represented at three of the six schools. Black youth were significantly more likely to identify as native-origin (third generation) than were their Dominican American and Chinese American peers, (2)=165.74, p<.001. Procedure The procedure for the present study is described in detail elsewhere (Hughes et al., 2008). Principal investigators first identified public middle schools in which at least three of the four ethnic-racial Table 1 Demographic Characteristics in Percent of the Analytic sample (n-387) Presented by Ethnicity-Race Demographic characteris Black Dominican Chinese tics (n-149) (n-114) (n-124) Gender %Girls %Boys Schools (diversity score) %School 1 (0.74) %School 2 (0.69) %School 3 (0.44) %School 4 (0.33) %School 5 (0.70) %School 6 (0.50) Materal education % Less than high school %High school %Some college %Bachelors or beyond Generation status %Native-origin %Immigrant-origin 56.4 43.6 20 45.0 25.5 9.4 10.7 7.4 4.0 23.5 19.5 53.0 66.4 33.6 ******** **** ** 50.0 50.0 0.9 36.8 5.3 8.8 19.3 28.9 11.4 24.6 14.0 50.0 6.1 93.9 52.4 15.3 8.1 0.0 75.8 0.8 0.0 177 34.7 10.5 37.1 4.8 95.2 Ethnic-Racial Identity and Discrimination elll groups initially targeted for the larger study (ie., Black, Dominican American, Chinese American, and White) constituted 20% or more of the student population. Each of the six schools we initially approached agreed to participate in the study and all had a sixth-through-eighth-grade structure. We recruited students in all non-English as a second language sixth grade classrooms at the first assess- ment. For the seventh and eighth grade assess- ments, we permitted non-participating students to enter the study. Research assistants distributed and collected consent forms for a 2- to 3-week period in students' homeroom classes. The principal investi- gators provided students with a small non-mone- tary incentive for their participation. Overall, 77% of recruited adolescents returned parental consent forms and 78% of those had affirmative parental consent. We administered surveys in the spring of sixth, seventh, and eighth grades during two class periods that the school principal and teachers deemed appropriate. We collected data from two cohorts of adolescents; Cohort 1 was recruited in 2005 when students were sixth graders (n = 188), and Cohort 2 included adolescents recruited as sixth graders in 2006 (n – 199). Measures Ethnic-Racial Identity Exploration We used a four-item measure, derived from the Multigroup Ethnic Identity Measure (MEIM; Phin- ney, 1992), to assess ethnic-racial identity explo- ration. Adolescents indicated the extent to which they questioned or sought information about their ethnicity-race using a 5-point Likert scale (e.g., "In order to learn more about my ethnic/racial back- ground, I have often talked to other people about my ethnic/racial group"; 1- strongly disagree, 5-strongly agree). Internal consistency/reliability of the four-item measure was adequate across the three waves of study for each ethnic-racial group (time-range Black = 66-84; ime-range Domini- can = .69-75; imerange Chinese - 70-81). A con- firmatory factor analysis of the four items across the three waves indicated configural invariance as indicated by the acceptable fit indices, comparative fit index (CFI) 97; root mean square error of approximation (RMSEA) - .04, 90% CI 1.03, .06]. A chi-square difference test indicated that constraining the factor loadings to be equivalent across time did not diminish model fit, indicating metric invariance, Ax (6) 10.18, p=ns. We assessed exploration using an observed mean score across the four items, el12 Del Toro, Hughes, and Way which were coded such that higher values indicated Ax(4)-5.97, p=ns. The resulting measure was an more exploration. observed mean score of the three items, which were coded such that higher values indicated positive evaluations toward one's ethnic-racial group. Ethnic-Racial Identity Commitment We assessed commitment using a four-item mea- sure derived from the MEIM identity achievement subscale, which assessed ethnic-racial identity com- mitment and affirmation (Phinney, 1992). We omit- ted the three affirmation items from the original seven-item achievement measure because they were redundant with items that assessed private regard (e.g., "I am happy that I am a member of the eth- nic/racial group I belong to"). Thus, the items cap- tured the construct of commitment only (e.g., "I have a strong sense of belonging to my own eth- nic/racial group"). Students rated each item on a 5- point Likert scale (1 strongly disagree, 5-strongly agree). The internal consistency/reliability was ade- quate across the three waves of study for each eth- nic-racial group (merange Black - 83-85; ime range Dominican = 88-89; time-range Chi- nese - 77-85). A confirmatory factor analysis of these items across the three assessments indicated configural invariance, CFI .98; RMSEA .06, 90% CI [.04, 07]. A chi-square difference test indicated metric invariance, as constraining the factor load- ings to be equivalent across time did not result in a significant decrement in model fit, Ax²(6) - 6.44, p= ns. The measure was a unit-weighted mean score across the four items, which were coded such that higher values indicated higher commitment. Private Regard We used the private regard subscale of the Mul- tidimensional Inventory of Black Identity (MIBI)- Teen (Scottham, Sellers, & Nguyên 2008) which consisted of three items, with minor revisions such that references to "Black" were re-worded as refer- ences to "my ethnic/racial group." Students rated items on a 5-point Likert scale (eg, "I feel good about people from my ethnic/racial group"; 1-strongly disagree, 5-strongly agree). The internal consistency/reliability was acceptable across the three assessments for each ethnic-racial group (time range Black-76-78; imerange Domini- can = 81-85; time range Chinese - .79-87). A con- firmatory factor analysis indicated configural invariance across the three assessments, CFI- .99; RMSEA - .04, 90% CI [.02, .06]. A chi-square differ- ence test indicated metric invariance as factor load- ings constrained to be equivalent across time did not result in a significant decrement in model fit, Public Regard We assessed public regard using three items from the MIBI-Teen (Scottham et al., 2008). Adoles- cents indicated the extent to which they felt others value their group on a 5-point Likert scale (e.g., "A lot of people don't expect my ethnic/racial group to do well in life"; 1- strongly disagree, 5- strongly agree). The internal consistency was adequate across the three waves of the study and across the three ethnic-racial groups (me-range Black - 76-87; ime range Dominican - 74-0.86; imerange Chi- nese - 79-85). Fit indices from a confirmatory fac- tor analysis met the criteria for configural invariance across the three assessments, CFI = .99; RMSEA = .02, 90% CI [.00, .04]. A chi-square differ- ence test indicated metric invariance, as constrain- ing the factor loadings to be equivalent across time did not result in a significant decrement in model fit, Az(4)-1.67, p=ns. The resulting measure was a unit-weighted average of the three items, which were coded such that higher values indicated ado- lescents' perceived positive evaluations of others toward one's ethnic-racial group. Ethnic-Racial Discrimination Items assessing perceived ethnic-racial discrimi- nation were adapted from measures used in prior studies (Greene, Way, & Pahl, 2006; Hughes, Del Toro, Harding, Way, & Rarick, 2016; Hughes & Johnson, 2001; Williams, Neighbors, & Jackson, 2003). Adolescents responded to items that assessed varied manifestations of covert and overt discrimi- nation. We used the term covert discrimination to refer to perceptions that one has been the target of often unconscious negative attitudes and stereo- types pertaining to one's ethnic-racial group (e.g. others seeming uncomfortable around or afraid of you because of race or ethnicity), whereas we use the term overt discrimination to refer to instances of concrete and visible discrimination (e.g., name call- ing, bullying). The wording of items explicitly spec- ified the source of ethnic-racial discrimination (peers, adults in school, adults outside of school), but items regarding different sources appeared in separate parts of the survey. The measure of dis- crimination from adults in school had substantial missing data in sixth grade as well as a low mean
Who were the participants and what were the measures? What was the research design?
Research design refers to the structured plan or blueprint that researchers follow to investigate a specific research question or hypothesis. It encompasses the overall strategy for collecting, analysing, and interpreting data. The choice of research design depends on the nature of the research question and the goals of the study. Researchers use samples because it is often impractical or impossible to study an entire population. Sampling methods are employed to ensure that the selected sample is representative and provides reliable information about the population. The size and characteristics of the sample are crucial for the generalizability of research findings to a broader population. Measures in research refer to the tools, instruments, or methods used to collect data on variables of interest. These measures can be surveys, questionnaires, observations, physiological tests, or any other means of data collection. Measures are essential because they allow researchers to quantify and analyse variables systematically.
Step by step
Solved in 3 steps