The Research

To measure perceived discrimination, I assessed participants’ past experience with racial discrimination by presenting them with five questions. These measures were adapted from the past experience with racial discrimination questionnaire in Branscombe et al. (1999) to be more relevant to COVID. For example, “I have felt worried that others might be suspicious of me if I wear a mask in public because of my race or ethnicity” and “I feel like I am personally a victim of societal COVID-19 discrimination because of my race”. This was measured on a Likert-type scale (1 = strongly disagree, 5 = strongly agree) where higher numbers corresponded to stronger perceived discrimination. Internal consistency was high (a = 0.854).

I assessed multigroup ethnic identity using Jean Phinney’s Multigroup Ethnic Identity Measure (Phinney, 1992). This is a 12-item measure includes items such as “I have a clear sense of my ethnic background and what it means for me” and “I think a lot about how my life will be affected by my ethnic group membership”.  MEIM was measured on a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree) with higher numbers indicating greater identification with Asian Americans. Internal consistency was high (a = 0.866).

Adoptee identity was assessed using the Adoptee Identity Questionnaire (AIQ). This measure consists of multi-sentence descriptions of the four adoptive identity types. Each short paragraph contains a series of statements that look at the depth of adoptive identity exploration, degree of positive and negative affect regarding adoptive identity, and the extent of adoptive identity salience associated with that type (Donahue, 2008). Respondents rated each description according to how well it describes them on a 7-point Likert-type scale (1 = not at all, 4 = somewhat, 7 = very much). The final question asked them which paragraph best characterizes their adoptive identity into one of four groups: integrated, limited, unexamined, and unsettled. For the purposes of this study, this measure was solely used for categorization purposes. Participants were placed into the four groups based on the response they chose and the previous responses were not factored into the current analyses. Because of this, the limited group was not included in the data analysis as the sample size was small (n = 3).

personal well-being

I assessed personal well-being using two measures, similar to that of Branscombe et al. (1999). The first measure was the Rosenberg Self-Esteem (RSE) Inventory (1979), which is a 10-item scale to measure self-esteem and is a self-reported measure. Participants responded to the measure using a Likert-type scale (1 = strongly disagree, 5 = strongly agree). Statements included “All in all, I am inclined to think that I am a failure” and “I feel that I have a number of good qualities”. The negative self-esteem questions were reverse-scored so that higher numbers indicated higher self-esteem. Branscombe et al. (1999) also measured personal well-being by asking about frequency of experiencing various negative emotions by presenting participants with a list of emotional states. Following their style, I presented participants with ten emotional states, both positive and negative. The emotions presented are as followed: happiness, sadness, satisfaction, helplessness, uselessness, content, lifeless, depressed, anger, and hopeful. These ratings ranged from 1 (experienced not at all) to 7 (experience all the time). The negative emotional states were also reverse scored such that higher numbers indicated higher self-esteem. Internal consistency was high (a = 0.927).

collective well-being

To measure collective well-being, I followed a similar procedure as Branscombe et al. (1999) and used the Collective Self-Esteem (CSE) Scale (Luhtanen & Crocker, 1992). For the purposes of this study, I used all four subscales. I chose to include the Public subscale because the participants’ views of how others perceive their group memberships are relevant to the hypothesis concerning well-being. Furthermore, I chose to include the Identity subscale because of the intersection of adoptee and Asian American identities. Participants indicated their level of agreement with each statement on a Likert-type scale from 1 (strongly disagree) to 5 (strongly agree). The necessary responses were reverse-scored so that higher scores indicated higher levels of collective self-esteem. Internal consistency was high (a = 0.719). Personal well-being and collective self-esteem measures were analyzed together to create the psychological well-being measure.