Annual Review of Asian American Psychology, 2014

Abstract

This 2014 review of Asian American psychology is the sixth review in the series. It includes 316 articles that met the inclusion criteria established by the past five annual reviews. Featured articles were derived from three sources: 137 were generated via the search term “Asian American” in PyscINFO, 111 were generated via a search for specific Asian American ethnic groups, and 32 were generated via author searches of articles that met the inclusion criteria. The top primary topic was health and health-related behaviors, the most frequently employed study design was cross-sectional, and the most studied Asian American ethnic group was Chinese. This year’s review includes information on the target population of the primary topic, the age range and developmental period of participants, and whether the study design was cross-sectional or longitudinal. It also identifies top authors and journals contributing to the 2014 annual review. These new features reveal that the most common target population of the primary topic was youths; studies most commonly included emerging adults ages 18–25; cross-sectional study design was employed more often than longitudinal design; the top contributor to the 2014 review was Stephen Chen, who authored the highest number of papers included; and the Asian American Journal of Psychology generated the highest number of publications for this review.

The annual review of Asian American psychology facilitates a comprehensive, year-to-year understanding of the field by summarizing the major research topics and methodology used in Asian American psychology. Comparison of multiple annual reviews reveals past, current, and emerging trends. Illuminating these trends can be informative for new and experienced scholars alike, who can utilize the reviews to synthesize past and current research. This will help them identify emerging trends in order to plan future research that will make a meaningful contribution to scholarship on Asian American psychology. The present annual review uses the format established by the past five annual reviews, with the addition of new features for future annual reviews to consider. Like past reviews, the current issue presents major trends by primary topic, methodological design, and participant characteristics (e.g., average age and ethnicity). This review contributes a developmental perspective by including age range and developmental period in our categorization of participants, and by considering cross-sectional versus longitudinal study designs. We are also the first to recognize the top authors and journal outlets in this year’s review.

The 2014 review of Asian American psychology includes 316 articles, more than were included in any of the past five annual reviews. A confluence of factors has contributed to the growth of scholarship on Asian American psychology. First, there is the size of the population: Asian Americans represent 5.6% of the United States population; of all racial groups in the United States, Asian Americans are the fastest-growing (Hoeffel, Rastogi, Kim, & Shahid, 2012). In fact, the Asian American population is growing four times faster than the general U.S. population, at a rate of 43% (Hoeffel et al., 2012). Second, scholars working in this field tend to be prolific, as evidenced by how many have contributed at least three first-authored papers to this year’s review: Stephen H. Chen, Su Yeong Kim, Anh B. Nguyen, Scott K. Okamoto, Pallav Pokhrel, Thanh V. Tran, and Y. Joel Wong. Relatedly, there is an infusion of new scholars entering the field. For example, Assistant Professor Bum Jung Kim contributed two first-authored papers to this year’s review. Third, there are now professional organizations in many social science disciplines that facilitate scholarship on Asian American psychology, such as the Society for Research in Child Development’s Asian Caucus. Founded in 2007, the Asian Caucus represents developmental scholars whose mission is to advance research on Asian American children, youth, and families in the United States and Canada.

There are six journals that contributed a significant number of articles to this year’s review. The Asian American Journal of Psychology contributed the most, with 33 articles featured in this year’s review. Its strong impact factor of 1.405, along with its ranking as the second highest out of 15 ethnic journals from the Institute for Scientific Information (ISI) (Thomson Reuters, 2015), suggests that the journal is now established and will continue to publish important scholarship on Asian American psychology. This review includes eleven articles from Cultural Diversity and Ethnic Minority Psychology, seven articles from the Journal of Cross-Cultural Gerontology, seven articles from Race and Social Problems, six articles from Maternal and Child Health Journal, and six articles from Substance Use and Misuse. The large number of articles from Race and Social Problems and Substance Use and Misuse can be attributed to special issues with thematic content of particular relevance for Asian American psychology, as described below.

There were four notable special issues that contributed a significant number of articles to this annual review of Asian American psychology. The Asian American Journal of Psychology published two of these special issues. The first is on Culture and Prevention (R. M. Lee & Lau, 2014), including both basic research (e.g., examining the correlates of language brokering, Y. Shen, Kim, Wang, & Chao, 2014) and applied research (e.g., evaluating the cultural adaptation of an existing parenting prevention program, Zhou, Chen, Cookston, & Wolchik, 2014). The second is on Asian American Health Disparities (Saw & Song, 2014), focusing on varied topics, such as inpatient psychiatric care (J. E. Kim, Saw, Zane, & Murphy, 2014) and quality of life among Asian American youths (Fradkin et al., 2014). Race and Social Problems published a special issue on Asian Americans (Y. Choi, 2014), examining the invisibility of Asian Americans in the discourse on racial and social problems because of their depiction in popular culture as model minorities. For example, Ling, Okazaki, Tu, and Kim (2014) describe challenges faced by undocumented families or urban low-income Asian Americans. The final special issue to furnish articles for the present review is on Culture and Substance Use (Unger, 2014) in the journal Substance Use and Misuse; it has papers examining a range of topics, such as acculturative stress (S.-Y. Park, Anastas, Shibusawa, & Nguyen, 2014) and service utilization of substance abuse treatment programs in Asian Americans (Yu, Warner, Haverly, & Lambert-Wacey, 2014).

In the present paper, which is the sixth in a series of annual reviews of Asian American psychology, we have adhered to the methodology created by B. S. K. Kim, Wong, and Maffini (2010) in the initial review, as all of the authors who followed this first review have done so. Yeh, Yoo, and Lizarraga (2013) added a search for empirical articles on Native Hawaiian and Pacific Islanders, and the next review by Wei, Carrera, and Li (2014) did so as well. Therefore, in the interest of comparability across past and future annual reviews, the current review includes a search on Hawaiian and Pacific Islanders, an important social group to include because of their unique history of colonization and marginalization in the United States (Pokhrel & Herzog, 2014). The present review selected eight primary topics to code for target population of the primary topic (e.g., youths and women). We also describe data analytic methods when reviewing the articles in order to provide more in-depth coverage of the specific statistical or qualitative strategy used in each paper.

Previous annual reviews in this series have typically been led by authors in the field of counseling psychology (Juan, Lee, & Bates, 2012; B. S. K. Kim et al., 2010; Wei et al., 2014; Yeh et al., 2013). The authors of the present review, on the other hand, represent the field of developmental psychology. As such, we have chosen to bring a developmental focus to this annual review. For example, we indicate whether study designs were cross-sectional or longitudinal for quantitative studies designated as correlational in their design. In addition, for participant characteristics, we have enhanced the protocol established by B. S. K. Kim et al.’s (2010) first annual review by adding age range and developmental period in addition to average age of participants.

Method

Initial Search

We followed the search methods used by previous reviews (Juan et al., 2012; B. S. K. Kim et al., 2010; Okazaki, Kassem, & Tan, 2011; Wei et al., 2014; Yeh et al., 2013). We used EBSCO PsycINFO to conduct our initial search for articles to include. We typed “Asian American” into the “All Text” search field and “2014” into the “Year of Publication” search field, and limited the search to include only “Peer Reviewed” results. The “All Fields” category that was used in past reviews (Juan et al., 2012; Wei et al., 2014; Yeh et al., 2013) was not available to us through the EBSCO PsycINFO engine provided by our university. Our initial search yielded 321 articles, which is similar to the 332 articles yielded by Yeh et al.’s (2013) search; however, this was significantly fewer than the initial searches conducted in other reviews using the term “Asian American,” which yielded anywhere from 890 (Juan et al., 2012) to 1067 (Wei et al., 2014) results. To address the paucity of articles found in our initial search, we employed a tactic similar to those used by Juan et al. (2012), Yeh et al. (2013) and Wei et al. (2014) and made our search more comprehensive by using the ethnicities listed in Wei et al.’s (2014) review to find additional articles. After searching for each ethnicity individually, we found an additional 2087 unique articles. We also conducted author searches via EBSCO PsycINFO using the names of authors whose articles were included in this review, similarly to Juan et al.’s (2012) and Yeh et al.’s (2013) method for finding additional articles. These author searches yielded an additional 1412 unique articles. Each month between June 2014 and April 2015, we employed these three techniques to search for articles. Additionally, we received a bibliography of the articles compiled from a search conducted on February 20, 2015 via OvidSP’s PsycINFO from the American Psychological Association, using the search term “Asian American” and limiting the results to articles published in 2014 that were peer reviewed. This search was conducted per Wei’s (2014) finding that OvidSP’s PsycINFO search engine produced the most results compared to other search engines. This search yielded 546 unique results when we compared this bibliography with our existing library of articles. Any articles that we received after May 2015 did not receive consideration for inclusion in the present review. In total, we reviewed 4,366 articles.

Inclusion in Review

After coding the amassed articles, we identified 316 articles meeting the criteria for inclusion. Among these, 187 articles were found in two or more of the searches we conducted, 61 were found exclusively from our ethnicity searches, 36 were found exclusively from our PsycINFO OvidSP search using the term “Asian American,” 32 were included based on our author searches alone, and none were exclusive to our EBSCO PsycINFO Asian American search. Of the four searches we conducted, the ethnicity searches contributed the largest portion of the articles (248 of the 316 articles that met our inclusion criteria), irrespective of any other search. Had we searched for the term “Asian American” using EBSCO PsycINFO alone, we would have amassed 137 articles.

To facilitate comparison with the five previously published annual reviews, we have used the same inclusion criteria: (a) publication in a peer-reviewed journal, (b) report on an empirical study, and (c) a focus on Asian American/Pacific Islanders (AAPI). As in previous reviews, participants were considered Asian American if they were Pacific Islanders, Native Hawaiians, and/or “individuals of East, Southeast, and/or South Asian descent living in the United States (including Asian internationals and sojourners living in the United States)” (B. S. K. Kim et al., 2010, p. 228). Furthermore, we considered an article only if “(a) the majority of its participants were at least in one AAPI group, (b) it included at least one research question focusing exclusively on AAPIs, or (c) it included at least one research question comparing an AAPI group with another racial/ethnic group” (B. S. K. Kim et al., 2010, p. 299). Per Juan et al. (2012, p. 198), we expanded on criterion “c” by including only papers “that made direct comparisons of Asian Americans to another racial/ethnic group in the hypotheses and/or research questions” asked. For this reason, we excluded papers that “(a) used ethnicity as a control variable, (b) were interested in 'racial/ethnic differences' without specifically identifying Asian Americans as a group of interest in the hypotheses or research questions, or (c) aggregated Asian Americans with other non-Asian ethnic minorities” (Juan et al., 2012, p. 198). Additionally, per Okazaki et al. (2011) and all subsequent reviews, we excluded articles on Asians residing in Canada, articles in non-English language journals and theoretical papers. Articles that were published in print or through advanced online publication in 2014 were included in this review.

Coding Procedure and Summaries

The coding team comprised of four undergraduate research assistants and a coauthor. Coders were provided with an electronic coding sheet, where the questions were based on the inclusion criteria used in past reviews. A sample of 63 articles was assigned to the coding team to determine the degree of agreement on whether or not each article met the inclusion criteria. After checking the coders’ responses, results indicated that the coders reached 76.51% agreement for this initial sample. The first author and the coders then discussed the sample to clarify the inclusion and exclusion criteria by referring to past reviews’ organization and coding of similar articles to come to a resolution on contested articles. Once consensus was reached on those articles, the other articles continued to be coded as they amassed. During the process of coding the rest of the articles, coders reached an agreement anywhere from 93.02% to 100% of the time. Whenever consensus was not reached, all coders met with the authors of the paper and discussed the articles until a resolution was reached.

Once consensus was reached about which articles should be included in the review, the selected 316 articles were coded until agreement was reached by the entire team on all aspects of the coding. When coding for primary topic, for example, consensus ranged from 91.49% at the lowest to 99.37% at the highest; the coding team then discussed discrepancies until a 100% resolution was met. Following resolution of the discrepancies of the articles' coding, we categorized them into five domains: (a) topic area, (b) research design, (c) participant characteristics, (d) target population of the primary topic, and (e) age range/developmental period; these are found in Tables 1, 2, 3, 4 and 5, respectively. Congruent with the methodology of previous reviews, we assigned each article a primary topic “…based on the article’s conceptual model, research questions and hypotheses, results, and discussion” (Wei et al., 2014, p. 270). We used the same topic areas reported in Wei et al.’s (2014) review, which were accumulated from past reviews; however, we changed the “Measurement” topic introduced in Wei et al.’s (2014) review to “Measurement and methodology,” and we added a new topic called “Cognition,” which is derived from Wei et al.’s (2014) cognitive processing subtopic under “Miscellaneous.” Similar to Yeh et al.’s (2013) and Wei et al.’s (2014) reviews, we coded solely for the primary topic (rather than coding for both a primary and a secondary topic, which was the approach utilized in Okazaki et al.’s (2011) and Juan et al.’s (2012) reviews). However, we did code specifically for target population of the primary topic, which represented eight out of the 26 primary topics in Table 4, to report the specific population studied, as distinct from the primary topic. Over the span of the past five reviews, articles categorized by population have waned in number because the primary topic is often coded based on a more predominant theme within the paper. For example, in Qiao et al.’s (2014) article studying the relationship between quality of diet and the incident risk of diabetes in postmenopausal women, the primary topic was coded as health and health-related behavior, while the target population of the study was women (Qiao et al., 2014). We felt these were distinct topical areas, so we included an additional table for articles that studied a specific population. In some cases, the primary topic was still coded based on the target population of the study, but we felt it appropriate to make a conceptual distinction between primary topic and target population for this review in order to maintain the integrity of each category.

Table 1.

Topic Areas and Number of Articles Within Each Topic Across Annual Reviews

	n
Topic	2009	2010	2011	2012	2013	2014	2014 Articles by Topic
Health and health-related behaviors	37	88 (86)	63 (51)	70	85	85	7, 8, 12, 13, 14, 18, 20, 21, 22, 30, 32, 36, 43, 53, 55, 60, 66, 76, 80, 81, 82, 83, 84, 94, 95, 96, 99, 100, 109, 111, 114, 115, 122, 138, 140, 145, 146, 151, 173, 179, 190, 193, 198, 200, 203, 205, 207, 208, 210, 217, 218, 219, 227, 228, 229, 230, 232, 237, 239, 241, 242, 243, 246, 250, 251, 254, 255, 256, 262, 264, 267, 269, 270, 271, 274, 275, 278, 279, 281, 284, 292, 298, 311, 313, 315
Counseling and clinical issues	14	24 (20)	16 (11)	19	16	29	4, 9, 15, 37, 39, 72, 77, 92, 98, 102, 104, 135, 139, 160, 161, 163, 167, 174, 188, 216, 222, 231, 240, 296, 303, 304, 305, 314, 316
Psychopathology	27	49 (44)	36 (26)	11	18	23	10, 24, 35, 38, 41, 75, 88, 89,, 126, 133, 149, 171, 172, 194, 199, 206, 215, 226, 248, 287, 295, 306
Racism and discrimination	8	32 (24)	14 (13)	15	19	20	26, 44, 46, 48, 61, 69, 97, 108, 123, 132, 152, 212, 223, 224, 260, 263, 277, 285, 300, 309
Measurement and methodologya	-	-	-	-	12	18	52, 65, 79, 86, 91, 113, 119, 120, 131, 137, 143, 154, 202, 245, 247, 257, 282, 294
Acculturation and enculturation	31	21 (8)	16 (10)	18	11	16	27, 40, 59, 74, 101, 103, 110, 118, 141, 142, 150, 211, 236, 261, 280, 291
Cognitionb	-	-	-	-	-	16	29, 47, 70, 78, 106, 116, 127, 148, 180, 189, 201, 234, 253, 288, 290, 293
Stress and coping	8	4 (2)	14 (8)	3	11	16	11, 25, 42, 45, 124, 136, 157, 162, 170, 185, 191, 209, 221, 235, 252, 297
Families	34	27 (19)	21 (15)	18	24	15	1, 3, 19, 28, 67, 105, 117, 129, 155, 159, 183, 184, 195, 204, 259
Identity	15	17 (10)	9 (6)	8	13	15	2, 16, 31, 33, 50, 54, 68, 144, 175, 181, 197, 225, 249, 265, 273
Older Adults	2	16 (0)	15 (10)	13	5	11	17, 56, 57, 125, 177, 178, 186, 220, 268, 272, 307
Personality	5	-	-	1	0	11	23, 51, 62, 73, 107, 130, 147, 168, 192, 283, 301
Educational Experiences	20	21 (17)	12 (9)	9	11	8	34, 49, 58, 85, 90, 128, 165, 299
Career	5	6 (5)	2 (2)	2	5	6	112, 121, 196, 244, 258, 302
Violence	9	4 (0)	5 (4)	1	4	5	6, 63, 164, 176, 276, 312
Interpersonal Relationships	11	7 (5)	10 (8)	8	1	4	153, 158, 169, 187, 286
Spirituality	1	1 (0)	4 (4)	0	6	4	5, 87, 156, 310
Immigrants and refugees	35	10 (2)	16 (6)	24	5	3	71, 213, 308
LGBTQ	3	3 (2)	5 (3)	0	8	3	214, 238, 266
Media	-	-	-	2	0	3	93, 182, 233
Adoptees	1	4 (4)	2 (2)	0	0	1	166
Women	28	11 (1)	15 (1)	5	2	1	289
Youths	38	13 (6)	12 (4)	13	4	1	64
Men and masculinity	5	7 (0)	4 (1)	0	1	0
Miscellaneous	-	3 (3)	10 (10)	7	10	0
Politics	1	3 (3)	0 (0)	1	0	0

Note. LGBTQ = Lesbian, Gay, Bisexual, Transgender, Queer. Numbers in parenthesis represent the number of articles in which the topic was the primary focus of the study. Total ns for 2009, 2010, 2011, 2012, 2013, and 2014 are 134, 261, 204, 248, 271, and 316, respectively.

^aIndicates that the topic name was different compared to past reviews.

^bIndicates a topic created this year.

Table 2.

Study Design and Number of Articles Within Each Topic Across Annual Reviews

	n
Study Design	2009	2010	2011	2012	2013	2014	2014 Articles
Quantitative-Correlational	96	182	148	71*	179	201
Cross-Sectionala	-	-	-	-	-	169	4, 5, 8, 9, 10, 15, 18, 19, 20, 22, 23, 24, 26, 27, 28, 29, 30, 32, 33, 36, 37, 38, 39, 41, 42, 43, 46, 47, 48, 50, 52, 55, 56, 58, 59, 61, 63, 64, 66, 71, 72, 74, 77, 80, 83, 86, 87, 88, 89, 91, 93, 97, 98, 99, 103, 105, 109, 110, 113, 119, 120, 121, 122, 123, 125, 126, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 144, 145, 147, 149, 150, 153, 157, 158, 159, 160, 161, 162, 163, 166, 167, 168, 169, 170, 173, 174, 175, 176, 179, 183, 184, 185, 186, 190, 191, 192, 194, 198, 199, 201, 203, 205, 206, 208, 209, 210, 212, 213, 214, 218, 219, 222, 226, 227, 229, 230, 232, 233, 236, 237, 238, 239, 240, 241, 242, 243, 245, 248, 249, 250, 254, 255, 256, 258, 261, 269, 270, 275, 276, 278, 279, 280, 281, 286, 287, 292, 294, 295, 297, 300, 301, 306, 309, 310, 311, 312, 313, 315
Longitudinala	-	-	-	-	-	32	12, 13, 14, 40, 51, 53, 68, 73, 90, 94, 102, 107, 114, 115, 118, 124, 141, 142, 143, 193, 195, 202, 211, 223, 231, 246, 251, 257, 259, 265, 288, 298
Qualitative	32	46	41	17*	55	65	1, 2, 3, 7, 11, 17, 21, 25, 34, 44, 45, 49, 57, 62, 65, 75, 84, 85, 96, 101, 104, 112, 117, 128, 146, 151, 154, 155, 156, 165, 171, 177, 178, 180, 181, 187, 188, 196, 197, 204, 207, 216, 220, 221, 224, 244, 252, 262, 263, 264, 266, 268, 271, 272, 273, 274, 282, 284, 285, 289, 290, 299, 302, 303, 308
Quantitative: True or Quasi-Experimental	13	22	5	12*	30	37	6, 31, 35, 54, 60, 61, 69, 70, 76, 78, 79, 100, 106, 111, 116, 129, 148, 152, 175, 182, 189, 200, 215, 217, 234, 253, 260, 267, 277, 283, 291, 296, 307, 314
Mixed Methods	n/a	11	10	5*	8	17	16, 67, 81, 82, 92, 95, 108, 127, 164, 225, 228, 235, 247, 293, 304, 305, 316
Otherb	-	-	-	-	-	1	172

Note. Total ns for 2009, 2010, 2011, 2012, 2013, and 2014 are 134, 261, 204, 89*, 271, and 316, respectively.

^*These numbers were summed up for three topic areas (Health and health-related behaviors, Immigrants and refugees, and Racism and discrimination)

^aThese categories are new for this year's review.

^bMeta-Analysis

Table 3.

Participant Characteristics and Number of Articles Within Each Topic Across Annual Reviews

	n
Type of Sample	2009	2010	2011	2012	2013	2014	2014 Articles
Non-College	105	197	155	n/a	215	246	1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 21, 24, 25, 27, 28, 29, 30, 33, 34, 35, 36, 37, 38, 40, 41, 42, 43, 45, 46, 47, 48, 49, 50, 52, 53, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 74, 75, 76, 79, 80, 81, 82, 83, 84, 86, 87, 88, 90, 92, 93, 94, 95, 96, 98, 99, 100, 101, 102, 103, 104, 105, 107, 109, 110, 111, 112, 113, 114, 115, 116, 118, 119, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 136, 137, 138, 141, 142, 143, 146, 151, 153, 154, 155, 156, 157, 159, 162, 163, 164, 165, 166, 170, 171, 172, 173, 174, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 188, 189, 190, 191, 195, 196, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 212, 213, 214, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 235, 236, 237, 238, 239, 242, 245, 246, 247, 248, 249, 250, 251, 252, 253, 255, 256, 257, 259, 261, 262, 263, 264, 265, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 278, 279, 280, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 295, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 310, 311, 312, 313, 315, 316
College	41	64	49	n/a	59	79	1, 2, 14, 19, 20, 22, 23, 26, 31, 32, 33, 39, 44, 51, 54, 61, 69, 77, 78, 85, 89, 91, 97, 106, 108, 117, 119, 120, 121, 122, 123, 127, 128, 130, 139, 140, 144, 145, 147, 148, 149, 150, 152, 158, 160, 161, 167, 168, 169, 175, 176, 177, 182, 187, 192, 193, 194, 197, 198, 199, 211, 215, 233, 234, 240, 241, 243, 244, 254, 258, 260, 262, 266, 277, 281, 294, 296, 309, 314
Average Age
Less Than or Equal to 17 Years Old	40	56	32	7*	51	67	1, 4, 6, 9, 10, 15, 16, 27, 28, 29, 34, 40, 43, 46, 47, 49, 52, 53, 58, 60, 64, 66, 67, 68, 70, 72, 73, 84, 90, 92, 104, 105, 107, 116, 118, 124, 127, 142, 143, 155, 157, 159, 166, 180, 181, 183, 184, 195, 201, 202, 223, 228, 229, 230, 231, 239, 259, 265, 273, 274, 288, 290, 293, 298, 299, 301, 305
18–25 Years Old	48	76	54	9*	58	102	1, 2, 14, 19, 20, 22, 23, 26, 31, 32, 36, 37, 39, 44, 50, 51, 54, 61, 69, 75, 77, 85, 89, 91, 94, 95, 96, 97, 104, 108, 117, 119, 120, 121, 122, 128, 130, 138, 139, 140, 144, 145, 147, 148, 149, 150, 152, 161, 165, 167, 168, 169, 172, 174, 175, 176, 180, 182, 187, 188, 189, 192, 193, 194, 196, 197, 198, 199, 200, 204, 210, 211, 215, 222, 225, 226, 231, 234, 240, 243, 244, 247, 248, 253, 254, 258, 260, 264, 266, 271, 275, 277, 281, 282, 283, 289, 293, 294, 298, 306, 309, 314
26–64 Years Old	42	132	60	78*	119	162	3, 5, 7, 8, 12, 17, 18, 21, 24, 25, 26, 28, 30, 33, 36, 37, 38, 40, 41, 42, 45, 47, 48, 50, 55, 59, 60, 61, 62, 63, 65, 71, 74, 76, 78, 79, 80, 81, 82, 83, 86, 87, 88, 93, 98, 99, 100, 101, 104, 105, 106, 109, 110, 111, 113, 114, 115, 119, 123, 129, 131, 132, 133, 134, 135, 137, 138, 141, 146, 151, 153, 154, 156, 160, 165, 171, 172, 173, 174, 177, 180, 185, 188, 189, 190, 191, 192, 195, 196, 200, 201, 205, 206, 207, 208, 209, 210, 212, 214, 216, 217, 218, 219, 221, 222, 224, 225, 226, 227, 231, 232, 233, 236, 237, 238, 241, 242, 245, 246, 247, 248, 249, 250, 252, 255, 256, 257, 261, 262, 263, 264, 267, 269, 271, 274, 275, 276, 278, 279, 282, 284, 286, 287, 289, 291, 292, 293, 295, 296, 297, 298, 300, 302, 303, 304, 308, 310, 311, 312, 313, 315, 316
Greater Than or Equal to 65 Years Old	2	18	13	8*	15	45	13, 17, 24, 37, 50, 56, 57, 100, 102, 103, 104, 109, 115, 125, 126, 136, 162, 163, 164, 170, 172, 178, 180, 186, 188, 203, 210, 213, 220, 222, 226, 231, 235, 247, 248, 251, 252, 270, 271, 272, 278, 280, 293, 307, 308
Other (Not provided or available)	-	-	47	5*	32	8	11, 35, 112, 139, 158, 179, 268, 285
Race/Ethnicity
Chinese	68	59	74	17*	97	143	4, 5, 10, 12, 16, 24, 26, 27, 28, 29, 30, 32, 33, 35, 37, 39, 41, 42, 44, 50, 55, 56, 59, 60, 63, 68, 70, 71, 73, 74, 75, 77, 83, 85, 88, 89, 91, 96, 98, 104, 106, 109, 111, 113, 114, 120, 121, 124, 128, 134, 135, 137, 138, 139, 140, 141, 142, 143, 147, 148, 153, 158, 159, 165, 167, 168, 171, 173, 174, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 192, 193, 194, 195, 196, 198, 199, 201, 209, 210, 211, 212, 220, 222, 223, 225, 226, 229, 230, 234, 236, 242, 243, 244, 245, 249, 250, 254, 255, 256, 257, 258, 259, 262, 265, 267, 270, 271, 273, 275, 279, 281, 283, 284, 288, 290, 291, 293, 294, 295, 296, 298, 299, 301, 303, 304, 306, 308, 314, 316
Asian American	43	120	86	37*	137	126	4, 5, 6, 9, 10, 12, 14, 15, 18, 19, 22, 23, 26, 31, 32, 33, 36, 37, 39, 41, 42, 43, 44, 46, 48, 51, 52, 53, 54, 60, 61, 63, 64, 67, 68, 69, 72, 73, 74, 75, 77, 85, 87, 88, 89, 90, 91, 92, 97, 98, 99, 108, 111, 113, 115, 118, 119, 121, 122, 124, 128, 131, 132, 135, 137, 139, 140, 148, 149, 150, 152, 158, 169, 171, 172, 174, 175, 183, 188, 190, 194, 196, 198, 199, 208, 209, 210, 212, 213, 214, 215, 222, 224, 226, 237, 238, 240, 242, 243, 244, 246, 249, 254, 255, 258, 260, 262, 265, 273, 275, 276, 277, 281, 283, 286, 294, 295, 298, 300, 301, 309, 311, 313, 314, 316, 144, 225
Korean	36	63	59	17*	76	111	4, 5, 10, 12, 32, 33, 38, 39, 40, 47, 60, 63, 68, 70, 71, 73, 74, 75, 77, 78, 79, 83, 85, 88, 89, 91, 93, 94, 95, 96, 102, 103, 106, 107, 110, 111, 117, 120, 125, 126, 127, 128, 129, 135, 137, 139, 140, 147, 148, 155, 158, 160, 161, 162, 163, 164, 166, 167, 168, 170, 171, 173, 176, 177, 178, 185, 188, 189, 191, 193, 198, 199, 200, 209, 210, 211, 212, 225, 227, 233, 234, 235, 242, 243, 244, 249, 251, 254, 257, 258, 259, 261, 262, 263, 265, 266, 269, 275, 279, 281, 283, 294, 295, 296, 297, 298, 301, 307, 310, 314, 315
Filipino	31	27	34	8*	57	80	4, 5, 6, 10, 12, 30, 32, 33, 37, 39, 41, 42, 44, 45, 54, 60, 63, 65, 68, 70, 77, 83, 86, 88, 89, 90, 91, 96, 97, 98, 100, 104, 109, 113, 114, 121, 133, 135, 137, 139, 140, 156, 171, 174, 183, 190, 196, 198, 199, 209, 210, 212, 222, 225, 226, 229, 230, 231, 236, 242, 243, 244, 248, 249, 254, 255, 256, 257, 258, 262, 265, 279, 281, 283, 287, 294, 295, 298, 301, 316
Vietnamese	31	37	49	12*	54	79	4, 5, 10, 26, 30, 32, 37, 39, 41, 42, 58, 60, 63, 68, 70, 71, 73, 74, 75, 77, 85, 88, 91, 96, 98, 111, 113, 121, 124, 135, 137, 138, 139, 140, 157, 158, 165, 168, 171, 173, 174, 183, 197, 198, 199, 200, 206, 209, 210, 216, 217, 218, 219, 221, 222, 225, 226, 236, 244, 250, 255, 257, 258, 262, 265, 273, 275, 278, 279, 280, 281, 283, 284, 294, 295, 296, 298, 301, 314
Japanese	24	28	26	2*	44	61	4, 5, 10, 12, 13, 30, 32, 33, 39, 47, 60, 63, 68, 74, 77, 83, 91, 96, 101, 109, 114, 121, 135, 136, 137, 139, 158, 168, 171, 177, 187, 194, 196, 201, 209, 210, 212, 229, 231, 234, 242, 243, 244, 248, 249, 252, 253, 256, 258, 262, 265, 279, 281, 282, 283, 285, 294, 295, 298, 301, 314
Other Asians	-	37	-	2*	11	49	2, 4, 5, 6, 19, 29, 32, 41, 42, 54, 63, 70, 74, 83, 86, 88, 89, 90, 98, 109, 113, 137, 140, 154, 174, 177, 183, 190, 198, 199, 209, 212, 222, 226, 231, 244, 248, 250, 254, 255, 256, 276, 281, 294, 295, 296, 301, 306, 316
Asian Indian	19	14	24	5*	36	41	2, 4, 5, 7, 32, 39, 60, 62, 63, 74, 75, 80, 88, 89, 91, 96, 105, 120, 137, 139, 140, 145, 167, 168, 190, 196, 198, 199, 203, 207, 210, 212, 258, 262, 268, 281, 294, 295, 296, 298, 312
Pacific Islander	-	-	-	8*	30	35	4, 6, 10, 14, 15, 19, 26, 30, 36, 39, 43, 53, 64, 83, 109, 114, 115, 128, 154, 210, 215, 225, 229, 230, 231, 237, 238, 243, 254, 256, 262, 276, 281, 286, 298
Hawaiian	-	-	-	5*	13	27	6, 14, 15, 17, 36, 64, 83, 84, 109, 130, 154, 201, 202, 210, 228, 229, 230, 231, 241, 242, 243, 248, 256, 276, 282, 292, 298
Cambodian	8	13	12	7*	18	26	4, 30, 34, 39, 57, 73, 88, 96, 124, 137, 138, 139, 140, 183, 197, 199, 200, 225, 232, 239, 244, 250, 258, 262, 265, 274
Hmong	6	7	12	2*	24	24	8, 20, 66, 68, 116, 124, 137, 146, 151, 181, 183, 197, 200, 204, 205, 220, 225, 244, 250, 258, 264, 265, 289, 302
Taiwanese	12	3	3	0*	18	21	29, 32, 39, 71, 96, 121, 137, 139, 148, 168, 171, 187, 192, 196, 244, 258, 262, 272, 281, 306, 316
Bi or Multi Racial	2	1	6	0*	18	20	4, 26, 32, 44, 68, 75, 91, 104, 124, 139, 197, 230, 254, 258, 262, 265, 276, 281, 298, 305
South Asian	-	-	-	-	-	13	2, 7, 68, 80, 90, 124, 203, 244, 254, 257, 265, 276, 279
Pakistani	9	3	3	0*	12	12	2, 7, 39, 73, 80, 96, 137, 168, 198, 199, 203, 258
Thai	2	2	5	1*	11	12	25, 32, 39, 60, 68, 96, 137, 244, 250, 258, 262, 265
Laotian/Mien	6	7	6	0*	12	11	30, 68, 96, 124, 137, 183, 197, 225, 244, 250, 265
Samoan	-	-	-	0*	10	10	11, 21, 76, 81, 83, 154, 229, 247, 282, 305
Malaysian	1	-	0	0*	4	9	30, 39, 60, 73, 137, 168, 179, 258, 262
Bangladeshi	4	2	0	0*	4	8	1, 3, 7, 39, 73, 137, 168, 258
Indonesian	2	-	0	-	0	5	30, 96, 137, 168, 258
Muslim	-	-	-	-	1	5	2, 80, 112, 123, 224
Burmese	-	-	-	-	1	4	39, 137, 30, 49
Montagnard	-	-	-	-	3	3	68, 124, 265
Singaporean	-	-	-	-	1	3	39, 137, 168
Sri Lankan	4	-	1	0*	1	3	2, 137, 262
Bengali	-	-	-	-	1	2	2, 73
Marshallese	-	-	-	-	1	2	86, 154
Nepalese	-	-	1	0*	4	2	39, 73
Bhutanese	-	-	-	-	1	1	82
Cham	-	-	-	-	1	1	82
Okinawan	-	-	-	-	1	0
Taidam	-	-	-	-	1	0
Uzbek	-	-	-	-	1	0

Note. Total ns for 2009, 2010, 2011, 2012, 2013, and 2014 are 134, 261, 204, 89*, 271, and 316, respectively.

"Average" age refers to mean age when this number was available. For articles that did not provide a mean, median, or mode age, "not available" was coded.

^*These numbers were summed up for three topic areas (Health and health-related behaviors, Immigrants and refugees, and Racism and discrimination).

Table 4.

Target Population of the Primary Topic

Topic	n	2014 Articles
Youths	45	4, 6, 9, 10, 15, 29, 34, 43, 46, 47, 52, 53, 58, 64*, 66, 68, 70, 72, 73, 84, 90, 92, 107, 116, 118, 124, 155, 157, 183, 184, 188, 202, 223, 228, 229, 230, 239, 259, 265, 273, 288, 290, 299, 301, 305
Immigrants and refugees	39	1, 3, 7, 11, 27, 28, 30, 42, 45, 49, 57, 59, 62, 65, 71*, 82, 102, 125, 128, 153, 159, 173, 174, 179, 203, 206, 235, 236, 244, 245, 252, 272, 274, 279, 297, 303, 304, 306, 308*
Women	38	18, 22, 23, 32, 33, 36, 69, 75, 79, 80, 81, 83, 99, 101, 138, 146, 149, 150, 156, 194, 198, 208, 217, 218, 219, 246, 248, 250, 254, 260, 262, 264, 269, 287, 289*, 302, 315, 316
Older Adults	18	13, 17*, 24, 56*, 103, 126, 162, 163, 164, 170, 178, 186*, 213, 220*, 270, 278, 280, 307*
Families	17	35, 40, 60, 67*, 105*, 129*, 141, 142, 143, 185, 195*, 196, 201, 205, 207, 268, 284
Men and masculinity	5	91, 122, 221, 238, 266
Adoptees	2	16, 166*
LGBTQ	2	214*, 276

Note. LGBTQ = Lesbian, Gay, Bisexual, Transgender, Queer. This table is a new feature of this review.

^*Indicates that the Primary Topic in Table 1 and the Target Population of the Primary Topic are the same

Table 5.

Age Range and Developmental Period of Participants Within Each Article

Age and Developmental Period	n	2014 Articles
Infants & Toddlers (Age 0–35 Months, 0–2 Years)	2	47, 116
Early Childhood (Age 36–59 Months, 3–4 Years)	4	10, 92, 116, 195
Middle Childhood (Age 5–9 Years)	15	9, 27, 28, 29, 43, 49, 70, 90, 118, 159, 180, 195, 288, 290, 301
Adolescence (Age 10–17 Years)	61	1, 4, 6, 9, 15, 16, 34, 40, 43, 46, 52, 53, 58, 60, 64, 66, 67, 68, 70, 72, 73, 84, 86, 90, 96, 104, 105, 107, 124, 127, 142, 143, 155, 157, 166, 180, 181, 182, 183, 184, 201, 202, 212, 223, 224, 228, 229, 230, 231, 239, 259, 265, 273, 274, 293, 298, 299, 301, 305, 306, 314
Emerging Adults (Age 18–25 Years)	164	1, 2, 4, 5, 14, 18, 19, 20, 22, 23, 26, 31, 32, 36, 37, 39, 41, 44, 50, 51, 54, 61, 63, 69, 74, 75, 77, 78, 79, 81, 82, 83, 85, 86, 88, 89, 91, 94, 95, 96, 97, 104, 106, 108, 110, 114, 117, 119, 120, 121, 122, 123, 127, 128, 130, 131, 132, 133, 134, 135, 138, 139, 140, 144, 145, 146, 147, 148, 149, 150, 151, 152, 154, 158, 160, 161, 165, 167, 168, 169, 173, 174, 175, 176, 177, 180, 182, 187, 188, 189, 190, 191, 192, 193, 194, 196, 197, 198, 199, 200, 201, 204, 209, 210, 211, 212, 214, 215, 217, 218, 222, 224, 225, 226, 231, 232, 233, 234, 238, 240, 241, 243, 244, 247, 248, 249, 250, 253, 254, 256, 258, 260, 262, 263, 264, 266, 269, 271, 274, 275, 276, 277, 279, 281, 282, 283, 284, 286, 289, 292, 293, 294, 295, 296, 297, 298, 302, 303, 306, 309, 310, 311, 313, 314
Early Adulthood (Age 26–39 Years)	159	3, 5, 7, 12, 18, 19, 20, 21, 26, 28, 30, 32, 33, 36, 37, 38, 39, 40, 41, 42, 45, 47, 48, 50, 60, 61, 62, 63, 65, 71, 74, 75, 77, 78, 79, 81, 82, 83, 86, 88, 96, 98, 100, 104, 105, 106, 108, 110, 111, 113, 114, 119, 120, 123, 129, 130, 131, 132, 133, 134, 135, 137, 138, 140, 145, 146, 151, 152, 153, 154, 160, 161, 165, 167, 168, 169, 171, 173, 174, 177, 180, 182, 185, 187, 188, 189, 190, 191, 192, 195, 196, 199, 200, 201, 205, 207, 208, 209, 210, 212, 214, 216, 217, 218, 219, 222, 224, 225, 226, 231, 232, 233, 237, 238, 241, 242, 243, 247, 248, 249, 250, 255, 256, 257, 261, 262, 263, 264, 268, 269, 271, 274, 275, 276, 279, 282, 283, 284, 286, 289, 291, 292, 293, 294, 295, 296, 297, 298, 300, 302, 303, 308, 310, 311, 312, 313, 314, 315, 316
Middle-Aged Adults (Age 40–64 Years)	156	3, 5, 7, 8, 12, 17, 18, 21, 24, 25, 28, 30, 32, 37, 38, 39, 40, 41, 42, 45, 50, 55, 57, 59, 60, 62, 63, 65, 71, 74, 76, 79, 80, 82, 86, 87, 88, 93, 98, 99, 100, 101, 103, 104, 105, 109, 110, 111, 113, 114, 115, 119, 120, 123, 131, 132, 133, 134, 135, 136, 137, 138, 140, 141, 146, 151, 153, 154, 156, 160, 164, 167, 168, 169, 171, 173, 174, 177, 178, 180, 182, 185, 186, 188, 190, 191, 201, 203, 205, 206, 208, 209, 210, 212, 216, 217, 218, 219, 220, 221, 222, 224, 226, 227, 231, 232, 233, 235, 236, 237, 238, 242, 245, 246, 247, 248, 250, 251, 252, 256, 257, 261, 263, 264, 267, 268, 269, 270, 271, 274, 275, 276, 278, 279, 282, 284, 286, 287, 291, 292, 293, 295, 296, 297, 300, 302, 303, 304, 307, 308, 310, 311, 312, 313, 315, 316
Older Adults (Age 65 Years and Older)	100	5, 7, 8, 13, 17, 18, 21, 24, 25, 37, 38, 41, 50, 56, 57, 63, 65, 74, 76, 87, 88, 100, 101, 102, 103, 104, 109, 110, 114, 115, 125, 126, 131, 133, 134, 136, 151, 153, 162, 163, 164, 170, 177, 178, 180, 182, 185, 186, 188, 190, 201, 203, 205, 206, 208, 210, 213, 217, 218, 220, 221, 222, 224, 226, 227, 231, 232, 235, 237, 245, 246, 247, 248, 250, 251, 252, 256, 257, 267, 268, 270, 271, 272, 274, 278, 279, 280, 284, 286, 287, 292, 293, 295, 297, 300, 304, 307, 308, 310, 311
Other or Not Provided	8	11, 35, 112, 139, 172, 179, 188, 285

Note. This table is a new feature of this review.

The undergraduate research assistants on the coding team and a coauthor also coded independently for study design (see Table 2) and participant characteristics (i.e., racial and ethnic groups, age, and college or non-college students; see Table 3), which included the same categories used in past reviews, with a few additions. In this year’s review, correlational design is divided into two subcategories in the study design table: cross-sectional and longitudinal design. This feature allowed us to organize and discuss the articles with the developmental approach we adopted for this review. In Table 3, we organized the articles based on each study’s participant characteristics. We have maintained consistency with the organizational conventions of past reviews, and have included all the categories used in past reviews. However, we added an age range category in Table 5 because this review employs a developmental focus. Given that human development occurs throughout the lifespan, participants’ developmental period is coded as belonging to one of eight developmental periods (see Table 5). Childhood is divided into four periods: Infants and Toddlers (0–2 years; Lightfoot, Cole, & Sheila, 2012), Early Childhood (3–4 years; Lightfoot et al., 2012), Middle Childhood (5–9 years; Lightfoot et al., 2012), and Adolescence (10–17 years; Steinberg, 2013). Adulthood is divided into four periods: Emerging adults (18–25 years; Arnett, 2000), Early Adulthood (26–39 years), Middle-Aged Adults (40–64 years; Spitze & Logan, 1990), and Older Adults (65 and older; Whitbourne & Sliwinski, 2012). In order to maintain the integrity of the developmental periods represented, we revised the age categories to avoid overlaps or gaps. For example, we created the “Early Adulthood” category for those aged 26–39 to represent the period between Emerging Adults and Middle-Aged Adults. In addition, the upper and lower age ranges representing “Middle Childhood” have been variously defined by developmental scholars; we chose the age range of 5–9 years to avoid overlap with “Early Childhood” and “Adolescence.”

The study design and participant characteristics categories were not mutually exclusive. For example, a single study might have two groups of participants with different age ranges, such as a parent and child sample. In this case, we would code for both groups represented. Additionally, an article might report on multiple studies, each with a different study design. Therefore, the total number of cited articles in these sections exceeds the total number of articles included in this review.

Results

As in past years, health and health-related topics continues to persist as the most frequent primary topic (27%) out of the 26 primary topics in this 2014 review; these are presented in Table 1. The “correlational: cross-sectional” research method was the most commonly employed study design (55%) out of the six study designs represented in this review (see Table 2). Of the participant characteristics (see Table 3), Chinese were the most studied ethnic group (15%) out of the 35 ethnicities categorized in this review, 26–64 year olds were the most common age group (41%) out of the five categories represented, and studies were more likely to utilize non-college participants (as opposed to college participants) at 76%. Based on our coding for target population of the primary topic, youths were the most studied target population (26%) out of eight categories (see Table 4). Additionally, the most commonly represented developmental period in the articles was emerging adulthood (ages 18–25) at 24% out of nine categories (see Table 5). Consistent with past reviews, in this section, we organized the primary topics alphabetically. For each topic, we first provided a summary of study content, methodology, and type of data analysis used; we then discussed one study as an example. The criteria for choosing the example were as follows: whenever possible, we chose a developmentally focused study (e.g., a study with a longitudinal design); otherwise, we chose studies that exemplify the scholarship on the focal topic or that used innovative research methodology.

Primary Topic Summaries

Acculturation and enculturation

We identified 16 articles on this topic. These articles covered three subtopics that were consistent with those in Wei et al.’s (2014) review, the impact of acculturation on life experiences (n = 12), acculturative stress (n = 3), and acculturation process (n = 1; Iwasaki & Brown, 2014). Most studies focused on adults (n = 11; e.g., Weber, Hsu, & Sparks, 2014), with a few focusing on children (S. H. Chen, M. Hua, et al., 2014; H. S. Kang, Haddad, Chen, & Greenberger, 2014) or adolescents (Y. Choi, Tan, Yasui, & Pekelnicky, 2014; S. Y. Kim, Wang, Chen, Shen, & Hou, 2014). Most studies used quantitative designs, such as correlational designs including cross-sectional (n = 9; e.g., S. H. Chen, M. Hua, et al., 2014) and longitudinal designs (n = 5; e.g., H. S. Kang et al., 2014), as well as experimental designs (Weber et al., 2014). One study used qualitative design (Iwasaki & Brown, 2014). Analytical methods involved structural equation modeling (n = 8; e.g., S. H. Chen, M. Hua, et al., 2014), regression (n = 4; e.g., C. Y. Fang, Ross, Pathak, Godwin, & Tseng, 2014), analysis of variance (Weber et al., 2014), cluster analysis (Shin & Lach, 2014), and generalized estimating equation (GEE; H. S. Kang et al., 2014).

For the impact of acculturation on life experiences, studies examined the associations between various measures of acculturation – for instance, English proficiency (e.g., H. S. Kang et al., 2014), cultural orientations (e.g., S. H. Chen, M. Hua, et al., 2014; S. Y. Kim, Shen, Huang, Wang, & Orozco-Lapray, 2014), and acculturation profiles (e.g., S. Y. Kim, Y. Wang, Q. Chen, et al., 2014) – and various outcomes such as socioemotional and behavioral well-being (Y. Choi et al., 2014; Jang, Roh, & Chiriboga, 2014; Murray et al., 2014), health (Shin & Lach, 2014; T. V. Tran, T.-N. Nguyen, & K. T. Chan, 2014), academic outcomes (S. Y. Kim, Y. Wang, Q. Chen, et al., 2014), and consumer behaviors (Ha, Hums, & Greenwell, 2014; Jun, Ham, & Park, 2014; Weber et al., 2014). For example, S. Y. Kim et al. (2014) investigated parents’ and adolescents’ acculturation profiles and adolescents’ academic trajectories from 8^th to 12^th grade in Chinese American families. They found that a) adolescents with a Chinese-oriented father showed faster decline in grade point average, b) Chinese-oriented adolescents had lower initial scores in English language arts (ELA), and c) adolescents who were more American-oriented than their parents had the highest initial scores in ELA, whereas adolescents who were more Chinese-oriented than their parents had the lowest initial scores in ELA.

For acculturative stress, studies examined the influence of acculturative stress on alcohol use (S.-Y. Park et al., 2014), inflammation (C. Y. Fang et al., 2014), and eating disorder symptoms (Kroon Van Diest, Tartakovsky, Stachon, Pettit, & Perez, 2014). For example, Park et al. (2014) found that acculturative stress was positively associated with alcohol use, but only for Vietnamese immigrants, and not for Chinese and Filipino immigrants in the United States, which may be because Vietnamese immigrants have less prior exposure to the American culture and a relatively short history of immigration. The results underscored the importance of considering the heterogeneity of Asian Americans in research on alcohol use.

Adoptees

One article primarily focused on adoptees. It examined whether ethnic identity moderates the influence of racial discrimination on adjustment among transracially, transnationally adopted Korean American adolescents (J. P. Lee, Lee, Hu, & Kim, 2014). They found that ethnic pride exacerbated the effect of discrimination on externalizing problems; engagement with one’s ethnic group exacerbated the effect of discrimination on substance use; and clarity regarding the meaning and importance of one's ethnic group had no moderating effect on the association between discrimination and negative outcomes.

Career

We identified six articles focusing on career-related experiences among Asian Americans. These studies focused on either college students (e.g., Poon, 2014) or Asian American adults in the workforce (e.g., A. Yang, 2014). The majority of these articles used qualitative designs (interview or case study, n = 4; e.g., Ma, Desai, George, San Filippo, & Varon, 2014). Two studies used quantitative-correlational designs (cross-sectional, Keller & Brown, 2014; F. C. Shen, Liao, Abraham, & Weng, 2014), analyzing data with regression (Keller & Brown, 2014) or path analyses (F. C. Shen et al., 2014).

These articles investigated factors (e.g., parental pressure and support) related to Asian Americans’ career choices (Keller & Brown, 2014; Poon, 2014; F. C. Shen et al., 2014), management of family conflict regarding career choices (Ma et al., 2014), obstacles to leadership positions for Muslim Americans in the legal field (Kadi, 2014), and career development of Hmong American women (A. Yang, 2014). For example, Ma et al. (2014) investigated how Asian American young adults manage family conflicts regarding their career decisions. Results demonstrated that when young adults’ career choices were disapproved of by parents, they sought advice from friends and relatives. They adopted various strategies to earn parents’ approval: for example, educating parents about their chosen career, seeking honors, and compromising between personal desires and parental expectations.

Cognition

We identified 16 articles focusing on cognition. This primary topic is similar to the subtopic cognitive processing under miscellaneous in last year’s annual review (Wei et al., 2014). Given the large number of articles focusing on this topic, we created a new category for them. These studies covered two subtopics, cognitive processes (n = 8) and linguistics and language learning (n = 8). These studies covered various developmental periods, including infants (e.g., Cote & Bornstein, 2014), children (e.g., Kan, 2014), adolescents (e.g., McArdle, Hamagami, Bautista, et al., 2014), and adults (e.g., Kitayama & Park, 2014). Most studies used quantitative designs, such as experimental (n = 8; e.g., J. Park & Kitayama, 2014) and correlational designs including cross-sectional (n = 3; e.g., McArdle, Hamagami, Bautista, et al., 2014) and longitudinal designs (Uchikoshi, 2014). Other studies used qualitative designs (interview; Leung, 2014; Wang, Capous, Koh, & Hou, 2014) or mixed methods (C. E. Kim & Pyun, 2014; A. W.-m. Wong & Hall-Lew, 2014). The primary analytical method employed by most studies was analysis of variance and/or regression (n = 13; e.g., J. Park & Kitayama, 2014), with one study using multilevel structural equation modeling (McArdle, Hamagami, Bautista, et al., 2014) and one study using individual growth modeling (Uchikoshi, 2014).

For cognitive processes, studies examined various factors (e.g., English proficiency, culture, ethnicity, age, and sex) associated with cognitive processes (e.g., spatial performance and episodic thinking; S. H. Chen, Zhou, Uchikoshi, & Bunge, 2014; Gross, 2014; McArdle, Hamagami, Bautista, et al., 2014; Sakamoto & Spiers, 2014; Wang et al., 2014) and neural correlates of cognitive processes (H. Han, Glover, & Jeong, 2014; Kitayama & Park, 2014; J. Park & Kitayama, 2014). For example, Gross et al. (2014) examined own-ethnicity bias in face recognition (i.e., the tendency to better recognize people of one's own ethnicity) among four ethnic groups of children: Asian, Black, Hispanic, and White. They found own-ethnicity bias for Hispanic and White children but not for Asian and Black children. They discussed two potential mechanisms of such a bias: a) face recognition is better for ethnic faces that are seen more often; b) face recognition biases are related to children’s attitudes toward ethnic groups.

For linguistics and language learning, studies covered areas such as bilingual children’s language learning experiences (Cote & Bornstein, 2014; Kan, 2014; Uchikoshi, 2014), Asian Americans’ heritage language development (C. E. Kim & Pyun, 2014; Leung, 2014), and English pronunciation (Jin & Liu, 2014; Liu, Jin, & Chen, 2014; A. W.-m. Wong & Hall-Lew, 2014). For example, Uchikoshi (2014) investigated Spanish-speaking and Cantonese-speaking English language learners’ vocabulary development of first language (Spanish or Cantonese) and second language (English) from kindergarten to second grade. They found that Cantonese-speaking children had higher English expressive vocabulary scores compared to Spanish-speaking children throughout the three years, whereas Spanish-speaking children had steeper growth rates in first-language vocabulary than did Cantonese-speaking children.

Counseling and clinical issues

We identified 29 articles that primarily focused on counseling and clinical issues. We continued using Wei’s (2014) categories, but given the larger number of articles for this topic area published in 2014 compared to 2013, we divided one category, help seeking and service utilization (Wei et al., 2014), into two: help-seeking attitudes (n = 11; e.g., P. Y. Kim & Lee, 2014) and service utilization (n = 12; e.g., Anyon, Ong, & Whitaker, 2014), while keeping the category of culturally competent interventions (n = 7; e.g., Huang et al., 2014).

For help-seeking attitudes, studies investigated Asian American participants’ help-seeking attitudes or mental illness stigma with a focus on within-group variance or between-group differences (e.g., comparing Asian Americans to European Americans or Latinos). The majority of the studies relied on data obtained from samples of college students (n = 9; N.-Y. Choi & Miller, 2014; Hampton & Sharp, 2014; P. Y. Kim & Lee, 2014; E.-J. Lee, Chan, Ditchman, & Feigon, 2014; E.-J. Lee, Ditchman, Fong, Piper, & Feigon, 2014; J.-y. Lee, 2014; Pedersen & Paves, 2014; Y. J. Wong, Wang, & Maffini, 2014; Zane & Ku, 2014), and the remaining one study focused on emerging to middle-aged adults (L. H. Yang, Chen, et al., 2014). Most studies used quantitative designs – either experimental designs (n = 2; Y. J. Wong, Wang, et al., 2014; Zane & Ku, 2014) or correlational: cross-sectional designs, using analytical methods such as regression, path analysis, or analysis of variance (n = 7; e.g., N.-Y. Choi & Miller, 2014) – while only one study used a qualitative design (interviews; L. H. Yang, Chen, et al., 2014).

Here, we discuss the results of one representative study in this category. Y. J. Wong et al. (2014) conducted an experimental study with 465 Asian international college students who were randomly assigned to report their levels of emotional self-control and humility during three different types of interactions: with their families of origin, peers from their country of origin, or American peers. Emotional self-control was negatively related to help-seeking attitudes only during interactions with members of their country of origin. On the other hand, humility was negatively associated with help-seeking attitudes only during interactions with nonfamily members. In sum, this study revealed complex relations among emotional self-control, humility, and help-seeking attitudes.

With respect to service utilization, studies investigated parity or disparity of mental health service use among multiple racial/ethnic groups, including Asian Americans (n = 8; Anyon et al., 2014; Bear, Finer, Guo, & Lau, 2014; Brice et al., 2014; H. Cho, Kim, & Velez-Ortiz, 2014; S. Guo, Kataoka, Bear, & Lau, 2014; J. E. Kim et al., 2014; S. Lee, Laiewski, & Choi, 2014; Ona et al., 2014), or among multiple Asian ethnic groups (Ihara, Chae, Cummings, & Lee, 2014; D. Nguyen & Bornheimer, 2014); or they studied the extent of mental health service utilization among a specific Asian American ethnic group (H. B. Lee, Han, Huh, Kim, & Kim, 2014; Ngo, Gibbons, Scire, & Le, 2014). Four studies focused on adolescents’ mental health service use (e.g., school-based mental health service use; Anyon et al., 2014; Bear et al., 2014; Brice et al., 2014; S. Guo et al., 2014), and the other studies focused on the service use of adults in different periods of adulthood (n = 7; e.g., J. E. Kim et al., 2014). All studies used cross-sectional designs and quantitative methods (e.g., analysis of variance, multiple regression, and logistic regression). For example, H. B. Lee et al. (2014) assessed 630 Korean American elders in Korean churches for clinical depression and dementia. Of those participants with clinical depression or with thoughts of death or self-injury, 17% reported utilizing mental health services, whereas only 7.3% of those with probable dementia reported receiving any treatment. Furthermore, the authors identified significant sociodemographic and mental health predictors (years of U.S. residency, mental health service needs, and self-rated mental health) for Korean American elders’ mental health service utilization.

For culturally competent interventions, three studies applied extant intervention programs designed for mainstream populations to evaluate whether they could feasibly be used with Asian American participants (Huang et al., 2014; L. H. Yang, Lai, et al., 2014; Zhou et al., 2014). Two studies developed culturally competent interventions specifically designed for a certain Asian American ethnic population (Jang, Chiriboga, et al., 2014; Yeh, Borrero, et al., 2014). Other studies used qualitative data obtained from interviews and focus groups involving individuals from the target population, family members, community members, and service providers to identify mental health needs and intervention strategies specific to Asian Americans (Javier et al., 2014; Ling et al., 2014). The intervention programs highlighted the mental health needs of Asian American populations at different developmental periods, as well as those of their family members, from early childhood (Huang et al., 2014), to children/adolescents or mothers with children/adolescents (Javier et al., 2014; Ling et al., 2014; Yeh, Borrero, et al., 2014; Zhou et al., 2014), to caregivers (mother or spouse) of adult patients with mental health disorders (L. H. Yang, Lai, et al., 2014), and to older adults (Jang, Chiriboga, et al., 2014). With respect to the qualitative studies (Javier et al., 2014; Ling et al., 2014), even though the majority of participants were adults (e.g., service providers), the main population of interest was Asian American adolescents and young adults, whose psychosocial needs were the focus of this study.

We highlight one study as an example of culturally competent interventions. Zhou et al. (2014) conducted a pilot study with 10 recently divorced or separated Asian American mothers to evaluate the cultural adaptation of the New Beginnings Parent Program (NBP), a psychoeducational program originally designed to help children from divorced, predominantly European American families. Results of the pilot study showed that the overall themes of the NBP as originally designed were acceptable for use with divorced/separated Asian American parents, and that the program was engaging to this group. Major themes of the participants’ reported experiences included overall satisfaction with the program, challenges faced by divorced Asian American families, and the “cultural fit” of parenting skills taught in NBP with Asian American families. Authors further identified areas of NBP that were in need of culturally sensitive adaptation (e.g., parenting skills less familiar to Asian American families and culturally salient challenges, such as parent-child gaps in acculturation).

Educational experiences

We identified eight articles primarily focused on the educational experiences of Asian Americans. Similar to Wei et al.’s (2014) and Juan et al.’s (2012) reviews, our review groups articles based on their topical similarity, rather than by grade levels, as in Okazaki et al.’s (2011) review. Articles published in 2014 in this topic area could generally be divided into three categories: academic success and barriers (n = 5; Duong, Schwartz, & McCarty, 2014; Henfield, Woo, Lin, & Rausch, 2014; Hsin & Xie, 2014; E. Kim, 2014; J. Lee & Zhou, 2014), language-related educational experiences (n = 2; Croce, 2014; M.-H. Wu, Lee, & Leung, 2014), and educator-student relationship (n = 1; Chhuon, 2014). Six articles used qualitative designs to analyze Asian American students’ educational experiences (interviews or observation; Chhuon, 2014; Croce, 2014; Henfield et al., 2014; E. Kim, 2014; J. Lee & Zhou, 2014; M.-H. Wu et al., 2014). In addition, two articles had quantitative-correlational designs (one cross-sectional: Duong et al., 2014; one longitudinal: Hsin & Xie, 2014) and used analytical methods such as analysis of variance and multiple regression to identify predictors of achievement gap between Asian American students and students of other ethnicities (e.g., Caucasian or Mexican-American students).

We highlight one longitudinal study on academic success and barriers. Hsin and Xie (2014) analyzed data from two nationally representative student samples and compared the educational trajectories (K-12) of Asian American students and White students. They found that Asian American students’ educational advantage could be explained by their greater academic effort, which could further be attributed to (a) cultural differences in educational beliefs and (b) immigration status.

Families

We identified 15 articles that focused on family experiences among Asian Americans. As in previous reviews (Juan et al., 2012; B. S. K. Kim et al., 2010; Okazaki et al., 2011; Wei et al., 2014), parenting practices and family relationships continued to be the main focus of studies on families (n = 13). Consistent with B. S. K. Kim et al. (2010), we also identified a subtopic on language issues (n = 2). Most studies focused on children (n = 4; e.g., E. H. Lee et al., 2014) and adolescents (n = 8; e.g., Fu & Markus, 2014), with a few focusing on adults (n = 3; e.g., Campos, Ullman, Aguilera, & Dunkel Schetter, 2014). Studies employed quantitative-experimental designs (E. Kim et al., 2014), quantitative-correlational designs including cross-sectional (n = 6; e.g., E. H. Lee et al., 2014) and longitudinal designs (Luo, Tamis-LeMonda, Kuchirko, F. Ng, & Liang, 2014; Y. Shen et al., 2014), qualitative designs (interview, n = 5; e.g., Meschke & Juang, 2014), and mixed methods (Fu & Markus, 2014). Data analyses used mainly structural equation modeling (n = 6; e.g., Campos et al., 2014) and analysis of variance (Jensen & Dost-Gözkan, 2014; Luo et al., 2014).

For parenting practices and family relationships, studies examined antecedents and consequences of parenting (Alam, 2014; S. H. Chen, Zhou, Main, & Lee, 2014; Fu & Markus, 2014; E. H. Lee et al., 2014; Liew, Kwok, Chang, Chang, & Yeh, 2014), parent-child relationships (Amin & Ingman, 2014; Jensen & Dost-Gözkan, 2014; Y. Li, 2014; Meschke & Juang, 2014), and family values (Campos et al., 2014; H. Kang & Larson, 2014). One study evaluated the effectiveness of a parent training program in promoting effective parenting (E. Kim et al., 2014). As an example of studies in this topical area, E. H. Lee et al. (2014) found that the concentration of Asians in the neighborhood positively related to authoritarian parenting, which in turn linked to children's higher externalizing and internalizing problems. Meanwhile, neighborhood economic disadvantage was positively associated with children's externalizing problems, which in turn negatively related to authoritative parenting. The results underlined the importance of considering multiple pathways in the relations among neighborhood, parenting, and child adjustment.

With respect to language issues, studies examined how Asian American adolescents’ language brokering experiences related to their well-being (Kwon, 2014; Y. Shen et al., 2014). For example, Y. Shen et al. (2014) analyzed a two-wave longitudinal data set to reveal a negative indirect effect from language brokering for the mother to externalizing problems in Chinese American and Korean American adolescents through perceived maternal sacrifice and respect for the mother. This indirect effect was more evident when the level of open communication was lower.

Health and health-related behaviors

Similar to previous annual reviews (Juan et al., 2012; B. S. K. Kim et al., 2010; Okazaki et al., 2011; Wei et al., 2014; Yeh et al., 2013), health and health-related behaviors was the most frequently studied topic in 2014. A total of 85 articles focused primarily on this topic. As was the case with all of the previous reviews (Juan et al., 2012; B. S. K. Kim et al., 2010; Okazaki et al., 2011; Wei et al., 2014; Yeh et al., 2013), two subtopics continued to draw scholarly attention: cancer screening and management (n = 15; e.g., K. E. Kim, Chandrasekar, & Lam, 2014) and substance use (n = 26; e.g., S. S. Kim, Lee, Kiang, Kalman, & Ziedonis, 2014). We used Yeh et al.’s (2013) and Wei et al.’s (2014) label of viruses: hepatitis B virus (HBV), human immunodeficiency virus (HIV), and human papillomavirus (HPV) to categorize virus-related articles (n = 7; e.g., Tokes et al., 2014). Other articles fell under Wei et al.’s (2014) categories of eating and weight-related issues (n = 18; e.g., Cachelin, Thompson, & Phimphasone, 2014), healthcare beliefs, practices, and utilization (n = 7; e.g., K. M. Oh, Zhou, Kreps, & Kim, 2014), dementia (n = 6; e.g., Diamond & Woo, 2014), and cardiovascular disease (n = 1; Suh, Barksdale, & Logan, 2014). We found three articles that fit the label of sexual behaviors (n = 3; e.g., K. A. King, Vidourek, & Singh, 2014) included in three of the previous reviews (Juan et al., 2012; B. S. K. Kim et al., 2010; Okazaki et al., 2011). We changed the label of maternal and/or women’s health used in a previous annual review by Juan et al. (2012) to maternal and perinatal health because the articles on this topic dealt with the health of both mothers and babies before, during, and after birth. Two articles fell under this category (n = 2; e.g., Chihara et al., 2014). Below, we review these subtopics in alphabetical order.

Cancer screening and management

Studies reviewed under this category typically focused on breast and/or cervical cancer (n = 10; Hasnain, Menon, Ferrans, & Szalacha, 2014; Haworth, Margalit, Ross, Nepal, & Soliman, 2014; K. E. Kim et al., 2014; Kue, Zukoski, Keon, & Thorburn, 2014; Monnat, 2014; A. B. Nguyen & Belgrave, 2014; A. B. Nguyen & Clark, 2014; A. B. Nguyen, Clark, & Belgrave, 2014; Robison et al., 2014; Sparks, 2014) and colorectal cancer (n = 3; Menon, Szalacha, Prabhughate, & Kue, 2014; Ryu, Crespi, & Maxwell, 2014; Strong et al., 2014). Two articles did not specify a particular type of cancer (Im, Chang, & Chee, 2014; Leng & Gany, 2014). One of these articles investigated the quality of life of cancer survivors (Im et al., 2014), and the other one focused on the use of traditional Chinese medicine among cancer patients (Leng & Gany, 2014). Cervical cancer screening was an important issue for both young and middle aged women; breast cancer screening was focused more on the middle aged. Colorectal cancer screening was a health issue for a relatively late life stage (50 and older). Most studies had quantitative-correlational designs, using analytical methods such as regression, structural equation modeling, or latent class analysis to identify predictors, mechanisms, or heterogeneity in cancer screening attitudes and behaviors (n = 11; e.g., K. E. Kim et al., 2014; Menon et al., 2014; Strong et al., 2014). Among studies with quantitative-correlational designs, only one study used a longitudinal design (Ryu et al., 2014). Some studies used qualitative designs, including interviews or focus groups to investigate the participants’ cancer screening attitudes, experiences, and specific barriers to cancer screening (Haworth et al., 2014; Kue et al., 2014; Sparks, 2014). One study used experimental design (intervention) to identify factors that can promote cancer screening in Asian American communities (A. B. Nguyen & Belgrave, 2014).

As an example of the subtopic cancer screening and management, we describe findings from one study in detail. Kim, Chandrasekar, and Lam (2014) used data from a local health assessment survey of three foreign-born Asian subgroups in Chicago (Chinese, Vietnamese, and Cambodian) and found that their overall screening rates (48% and 49% for breast and cervical cancer, respectively) were much lower than the national averages for the general population (72% and 83%, respectively). They also found some socio-demographic variables differentially related to screening rates for breast cancer (e.g., English proficiency) and cervical cancer (e.g., marital status). Their results highlighted the heterogeneity of Asian Americans and suggested potential directions for future research, policy, and targeted interventions.

Dementia

Six studies were found to focus on dementia, or more specifically, Alzheimer’s disease (Borenstein et al., 2014; Diamond & Woo, 2014; Kally, Cherry, Howland, & Villarruel, 2014; Kally, Cote, et al., 2014; F. Sun, Gao, Shen, & Burnette, 2014; F. Sun, Mutlu, & Coon, 2014). Studies either focused on middle-aged (e.g., Diamond & Woo, 2014) or older adults (e.g., F. Sun, Gao, et al., 2014). Three of the studies had quantitative-correlational designs, and used analytical methods such as multivariate regression or Cox proportional hazards regression to identify correlates of dementia/Alzheimer’s disease literacy or incidence rates (Borenstein et al., 2014; Diamond & Woo, 2014; F. Sun, Gao, et al., 2014). One of these three articles used a longitudinal design (Borenstein et al., 2014). The remaining studies utilized either quantitative-experimental designs (Kally, Cherry, et al., 2014; Kally, Cote, et al., 2014) or a qualitative design (focus groups; F. Sun, Mutlu, et al., 2014).

We highlight one longitudinal study, which was the first to identify incidence rates for dementia in the Japanese American population in Seattle, WA (Borenstein et al., 2014). Since the beginning of the study in 1992–1994 and at the follow-ups every two years (1994–2001), a total of 173 incident cases of dementia were found, with the overall rate being 14.4 per 1,000 per year. The rates were also found to roughly double every five years for dementia and Alzheimer’s disease. Using Cox regression, analyses for correlates of dementia showed that sex was not significantly related to incidence rates of dementia, although incidence rates were slightly higher for women than for men. In addition, an inverse association with years of education and a strong positive association with Apolipoprotein-ε4 were found for all dementias.

Eating and weight-related issues

This category was previously labeled dietary habits and obesity prevention (Juan et al., 2012; B. S. K. Kim et al., 2010; Okazaki et al., 2011) or dietary habits, obesity, and diabetes (Yeh et al., 2013). We continued using Wei et al.’s (2014) label eating and weight-related issues to categorize a broad range of eating and weight-related health issues, including maternal feeding (n = 2; Cachelin et al., 2014; Momin, Chung, & Olson, 2014), nutrition and dietary habits (n = 3; H. V. Chung et al., 2014; Tiedje et al., 2014; S. S. Yi, Ruff, Jung, & Waddell, 2014), body mass and obesity (n = 3; Cassel, Braun, Ka’opua, Soa, & Nigg, 2014; Franzen-Castle & Smith, 2014; Y. Park et al., 2014), body image and eating disorders (n = 6; Chang, Yu, & Kahle, 2014; H.-L. Cheng, 2014; de Guzman & Nishina, 2014; Kelly, Cotter, Tanofsky-Kraff, & Mazzeo, 2014; Masuda, Le, & Cohen, 2014; Smart & Tsong, 2014), and diabetes (n = 4; Inouye, Matsuura, Li, Castro, & Leake, 2014; Qiao et al., 2014; T. Tran, Allen, Nguyen, Lee, & Chan, 2014; T. V. Tran, T.-N. Nguyen, & K. Chan, 2014). Eating and weight-related issues emerged as important health issues in different developmental periods throughout the entire life span: from maternal feeding and child nutrition (Cachelin et al., 2014; H. V. Chung et al., 2014; Momin et al., 2014); to dietary habits, obesity and body dissatisfaction during puberty/adolescence (de Guzman & Nishina, 2014; Franzen-Castle & Smith, 2014; Tiedje et al., 2014); to body image, compulsive exercise (in males), and eating disorders among young adults (H.-L. Cheng, 2014; Kelly et al., 2014; Masuda, Le, et al., 2014); and to diabetes in middle aged and older adults (T. Tran et al., 2014). The majority of studies used quantitative-correlational designs (n = 13; e.g., Chang, Yu, & Kahle, 2014), including two longitudinal studies (de Guzman & Nishina, 2014; Qiao et al., 2014), whereas one study used a quantitative-experimental design (intervention; Inouye et al., 2014) and four studies used qualitative designs (narratives, interviews, and focus groups; Cassel et al., 2014; Momin et al., 2014; Smart & Tsong, 2014; Tiedje et al., 2014).

As an example, a study of undergraduate men from diverse racial/ethnic backgrounds found that Asian American men had more body image concerns relative to their White and Black peers, and that compulsive exercise was a particular problem among Asian American men with binge eating habits (Kelly et al., 2014). Results suggested that the desire to achieve a muscular body type may put Asian American men at elevated risk for disordered eating symptoms and compulsive exercise.

Healthcare beliefs, practices, and utilization

In this year’s review, we continue using Wei et al.’s (2014) category to cover healthcare-related topics (n = 7), including health literacy (Sentell, Zhang, Davis, Baker, & Braun, 2014), health beliefs (i.e., health locus of control, Carpenter-Aeby, Xiong, & Aeby, 2014), health information seeking behaviors (K. M. Oh et al., 2014), healthcare access (S. Lee, Choi, & Jung, 2014), medication adherence (Juarez, Tan, Davis, & Mau, 2014), and healthcare utilization (Hamid et al., 2014; Hawley et al., 2014). Participants in these studies were distributed across a wide range of developmental periods, from emerging adulthood to older adulthood. All studies had quantitative designs, the majority of which were correlational: cross-sectional designs using analytical methods such as logistic regressions, analyses of variance, t-tests, etc. (n = 6; e.g., K. M. Oh et al., 2014; Sentell et al., 2014), while one study used an experimental design (intervention; Hamid et al., 2014).

In their study on the influence of immigration status on Korean American adults’ health information seeking behaviors, K. M. Oh et al. (2014) found that Korean Americans were three times more likely than native Koreans residing in South Korea to trust health information from newspapers or magazines and eleven times more likely to read the health sections of newspapers and magazines, but were three times less likely to look for health information from TV. The authors called for more reliable and valid health information from printed Korean language magazines or newspapers, so as to increase awareness and screening behaviors among Korean Americans.

Maternal and perinatal health

Two studies fell under this category; both used correlational: cross-sectional designs to investigate breastfeeding behaviors and gestational weight gain of new mothers residing in Hawaii (Chihara et al., 2014; Hayes et al., 2014). The first study (Hayes et al., 2014) found racial/ethnic disparity in exclusive breastfeeding among Asian/Native Hawaiian/Pacific Islander mothers (lower than 40%) compared to White mothers (50%). The second study (Chihara et al., 2014) found an association between gestational weight gain and infant birthweight, such that women with excessive weight gain during pregnancy were more likely to deliver a high birthweight infant, whereas those with inadequate weight gain were more likely to deliver a low birthweight infant.

Sexual behaviors

For the 2014 review, we found three articles (K. A. King et al., 2014; Meschke & Peter, 2014; Trinh, Ward, Day, Thomas, & Levin, 2014) related to Asian American adolescents’ and emerging adults’ sexual behaviors (compared to only one article for the years 2009–2011 and no articles for 2012 or 2013). These studies used correlational: cross-sectional designs and applied analytical methods such as chi-square tests or regressions. For example, based on surveys of 312 Asian American college students (ages 17 to 22) from diverse ethnic backgrounds, Trinh et al. (2014) examined sexual socialization of their parents and peers, and found that sexual communications from peers exceeded those from parents for most types of sexual messages; women received more conservative messages than did men; and peer communication was more closely related to risky sexual behaviors than was parent communication, especially in the case of acceptance of casual sex.

Substance use

A total of 26 articles were on substance use, suggesting that this area continued to be one of the most active areas of research in the field of Asian American psychology. Articles mainly centered on alcohol use (n = 11; Banerjee et al., 2014; Blanco et al., 2014; Jimi Huh, Heesung Shin, et al., 2014; Jimi Huh, Thing, Abramova, Sami, & Unger, 2014; Lo, Cheng, & Howell, 2014; Mukherjea, Wackowski, Lee, & Delnevo, 2014; Pagano, Lee, & Sin, 2014; Pokhrel, Little, Fagan, Kawamoto, & Herzog, 2014; Pokhrel, Little, Fagan, Muranaka, & Herzog, 2014; Tsang et al., 2014; Williams & Nigg, 2014) and drug/nonmedical stimulant use, resistance, and treatment (n = 3; Bart, Lenz, Straka, & Brundage, 2014; Okamoto, Pel, Helm, & Valdez, 2014; L.-T. Wu, Swartz, Brady, Blazer, & Hoyle, 2014). Other articles studied substance use more generally, covering cigarettes, alcohol, marijuana, or “hard” drugs (n = 8; L. Fang & Schinke, 2014; Helm, Okamoto, Kaliades, & Giroux, 2014; Okamoto, Helm, et al., 2014; Okamoto, Kulis, Helm, Edwards, & Giroux, 2014; Pedersen et al., 2014; Pokhrel & Herzog, 2014; Savage & Mezuk, 2014; Yu et al., 2014). Substance use emerged as an important health issue across a wide range of developmental periods, including adolescence (e.g., Helm et al., 2014; Okamoto, Kulis, et al., 2014), emerging adulthood (e.g., Jimi Huh, Heesung Shin, et al., 2014; Luczak et al., 2014) and all other periods of adulthood (e.g., Mukherjea et al., 2014; Tsang et al., 2014). The majority of studies used quantitative-correlational designs with analytical methods such as analysis of variance, linear or logistic regression, and structural equation modeling (n = 15; e.g., Mukherjea et al., 2014). Among the correlational studies, six used longitudinal designs (n = 6; Bart et al., 2014; Blanco et al., 2014; Boyd, Corbin, & Fromme, 2014; Jimi Huh, Heesung Shin, et al., 2014; Luczak et al., 2014; L.-T. Wu et al., 2014), and the rest used cross-sectional designs. Other studies used quantitative-experimental designs (n = 1; L. Fang & Schinke, 2014), qualitative designs using methods such as interviews and focus groups (n = 4; Banerjee et al., 2014; Helm et al., 2014; Hunt, Moloney, & Fazio, 2014; Tsang et al., 2014) and mixed-method designs (n = 1; Jimi Huh, James Paul Thing, et al., 2014).

Among the substance-use-related articles, we highlight a short-term longitudinal study conducted with 22 Korean American emerging adults who were daily smokers (Jimi Huh, Heesung Shin, et al., 2014). Using a within-subject modeling approach, the researchers found that momentary negative moods and being with friends were two independent predictors of increased likelihood of smoking. They further found that the effects of momentary negative moods were only significant in the presence of friends. Given the strong influence of peer contexts and momentary negative affect, as well as the interaction between the two, to young smokers, the authors concluded their study by calling for more intervention efforts that take into account these two contexts.

Viruses: hepatitis B virus (HBV), immunodeficiency virus (HIV), and human papillomavirus (HPV)

Of the seven articles that focused on viruses, three were on HBV (Juon et al., 2014; Maxwell et al., 2014; Tokes et al., 2014), another three were on HIV (W.-T. Chen et al., 2014; P. A. L. King & Pate, 2014; Salud, Marshak, Natto, & Montgomery, 2014), and the remaining one was on HPV (Zhao, Huh, Murphy, Chatterjee, & Baezconde-Garbanati, 2014). All seven studies focused on adults, from emerging through middle-aged adult participants (ages 18–65). Two studies on HBV (Juon et al., 2014; Maxwell et al., 2014) used quantitative-experimental designs (intervention) to understand Asian American men’s and women’s perceptions and attitudes toward chronic hepatitis B treatment and to promote HBV screening. One study on HIV testing used a qualitative design (focus groups) to investigate perinatal HIV testing among racially/ethnically diverse women (P. A. L. King & Pate, 2014). The remaining articles all used cross-sectional, quantitative-correlational designs with analytical methods such as hierarchical Bayesian modeling, multiple regressions, and mediational path analysis to explore predictors or mechanisms of HBV screening, HIV testing, or HPV vaccination.

As an example, we describe one study that developed a liver cancer education program for Asian Americans (Chinese, Korean, and Vietnamese Americans; Juon et al., 2014). Using a cluster randomized controlled trial, participants who had not received hepatitis B-related education in the past five years received a 30-minute educational program, in contrast to those in the control group (n = 436), who received an educational brochure. The results of a 6-month follow-up telephone survey suggested that the odds of self-reported receipt of HBV screening were significantly higher for the intervention group than for the control group.

Identity

We identified 15 studies with a focus on identity. Consistent with previous reviews (Juan et al., 2012; Wei et al., 2014), these studies covered two subtopics, ethnic identity (n = 10) and general identity issues (n = 5). The majority of studies focused on the developmental periods of adolescence (n = 5; e.g., Brocious, 2014) and emerging adulthood (n = 8; e.g., Devos & Yokoyama, 2014). Most studies used quantitative designs – correlational designs, either cross-sectional (n = 4; e.g., Y.-H. Kim, Chiu, Cho, Au, & Kwak, 2014) or longitudinal (Gartner, Kiang, & Supple, 2014; Stein, Kiang, Supple, & Gonzalez, 2014), and experimental designs (n = 3; e.g., Y. Chen, Li, Liu, & Shih, 2014). These quantitative studies mainly employed analytical methods, such as regression (n = 7; e.g., Stein et al., 2014) and analysis of variance (n = 5; e.g., K. Cheng, Conley, & Ziegler, 2014). The rest used qualitative designs (interview or observation, n = 4; e.g., Ali, 2014) and mixed methods (Brocious, 2014; Ocampo, 2014).

For ethnic identity, articles investigated predictors and outcomes of ethnic identity (n = 8; K. Cheng et al., 2014; Cui, Fitzgerald, & Donovan, 2014; Devos & Yokoyama, 2014; Gartner et al., 2014; T. L. Lee, Wilton, & Kwan, 2014; Levy, 2014; Ocampo, 2014; Roberts, Cha, & Kim, 2014), the buffering role of ethnic identity in Asian American adolescents’ lives (Stein et al., 2014), and the effects of social justice-oriented youth programs on racial and ethnic identities for Asian American youth (Suyemoto, Day, & Schwartz, 2014). A two-wave longitudinal study demonstrated the moderating role of ethnic identity (belonging and exploration) on the effects of economic stress (but not perceived ethnic discrimination) on mental health outcomes (depressive symptoms and self-esteem) in a sample of Asian American adolescents from an emerging immigrant community (Stein et al., 2014). For general identity issues, studies covered various topics, such as the formation of a new group identity (Brocious, 2014; Maramba & Palmer, 2014), Muslim adolescents’ understanding of their identities (Ali, 2014), the similarities and differences between Asian and European American college students on their perspectives of the self (Y.-H. Kim et al., 2014), as well as the effect of priming natural identities (i.e., university identity and ethnic identity) on cooperative behaviors (Y. Chen et al., 2014). Using an experimental design, Y. Chen et al. (2014) found that participants displayed more cooperation when primed with a shared (university) identity than when primed with a non-shared (ethnic) identity.

Immigrants and refugees

Three articles primarily focused on immigrants and refugees. These studies covered the association between victimization, fear of crime, and acculturation (Grubb & Bouffard, 2014), Chinese immigrants’ experiences of the revised naturalization exam (Yep, Zhao, Wang, Pang, & Wang, 2014), and economic conditions among older Asian Americans (Nam, 2014). Two studies adopted a quantitative-correlational design (cross-sectional) with data analyses involving correlation, t-test, and regression (Grubb & Bouffard, 2014; Nam, 2014). The other study used a qualitative design (case study; Yep et al., 2014). Two studies focused on adults (Grubb & Bouffard, 2014; Yep et al., 2014), and one specifically focused on older adults (Nam, 2014). Nam et al. (2014) compared the economic statuses between native and immigrant Asian Americans, Whites, Blacks, and Hispanics aged 65 years old or older. They found a native-immigrant gap in economic status, such that native-born individuals had higher status than immigrants. This native-immigrant gap was larger among older Asian Americans than among other ethnic groups, suggesting that the public perception of economically successful immigrant Asians is not consistent with the economic reality experienced by older immigrant Asian Americans.

Interpersonal relationships

We identified five studies that focused primarily on interpersonal relationships. Four used a quantitative-correlational design (cross-sectional) and employed regression as their main analytical method, and one used qualitative methods (Y.-Y. Lin, 2014). These studies covered various areas of adult interpersonal relationships, including predictors of social anxiety (Lau, Wang, Fung, & Namikoshi, 2014), online dating preferences (Tsunokai, McGrath, & Kavanagh, 2014), gossip (J.-y. Lee & Pistole, 2014), and health outcomes of social relationships (C. M. L. Kwan et al., 2014). For example, C. M. L. Kwan et al. (2014) examined how social relationships relate to measures of Chinese Americans’ health and whether age moderates such associations. They found that more unresolved diabetes-specific family conflict and less general social support were related to more depressive symptoms across ages. In contrast, more emotional support was linked to better glucose regulation for midlife but not for older participants.

LGBTQ

We identified three articles primarily focused on LGBTQ. These studies examined various aspects of the lives of adult Asian gay men, such as dating preferences (Nehl et al., 2014), academic and social experiences (Strayhorn, 2014), and substance use and stigmatization (Paul, Boylan, Gregorich, Ayala, & Choi, 2014). Two studies used a quantitative-correlational design (cross-sectional) with analytical methods involving regression (Nehl et al., 2014) or generalized estimating equation (GEE; Paul et al., 2014). One study used qualitative design (interview; Strayhorn, 2014). For example, Nehl et al. (2014) investigated the dating preferences of Asian American gay men and whether nativity and acculturation related to their preferences. They found that the majority (over 60%) had no clear racial/ethnic dating preference, 17.1% preferred dating White men, and over 20% preferred Asian men. Participants who had a higher ethnic orientation and were U.S.-born were more likely to prefer dating Asian men.

Measurement and methodology

In this year’s review, we changed Wei et al.’s (2014) category of “measurement” to “measurement and methodology,” not only so as to group articles on instrument development and/or validation, but also in order to include articles that focused on research methodologies, which were discussed under the “miscellaneous” category in Wei et al.’s (2014) review. In total, 18 articles fell under this category, with 15 focused on measurement and four focused on research methodology. Articles on measurement covered a wide range of research topics, including health and health-related behaviors (substance use; e.g., Dawson, Sotelo, Roesch, & Klonoff, 2014; Herzog et al., 2014; Quinn et al., 2014; cancer screening; e.g., H.-R. Han, Huh, Kim, Kim, & Nguyen, 2014; medication adherence; e.g., Qi & Resnick, 2014; healthcare beliefs and practices; e.g., Seo, Chung, & Shumway, 2014), psychopathology (expression of depression; e.g., Kalibatseva, Leong, & Ham, 2014; J. M. Kim & López, 2014), racism and discrimination (everyday discrimination; e.g., G. Kim, Sellbom, & Ford, 2014), families (language brokering; e.g., S. Y. Kim, Y. Wang, S. R. Weaver, et al., 2014), career (vocational interest; e.g., Kantamneni, 2014), interpersonal relationships (interpersonal shame; e.g., Y. J. Wong, Kim, Nguyen, Cheng, & Saw, 2014), personality (universal-diverse orientation; e.g., Kegel & DeBlaere, 2014), and men and masculinity (masculine norms; e.g., Hsu & Iwamoto, 2014). The majority of the measurement articles focused on the development, validation, or invariance testing of quantitative rating scales, but one study developed a bilingual version of a semi-structured interview assessment of drug/alcohol dependence for American Samoans (Quinn et al., 2014).

We introduce a study that examined the differential expression of depression in Asian Americans and European Americans using data from the National Latino and Asian American Study with an item response theory differential item functioning (IRT DIF) analysis (Kalibatseva et al., 2014). This study found that European American participants endorsed affective symptoms (e.g., “cried more often” or “feeling depressed”) more often than Asian Americans, and that given equal levels of depression, Asian Americans were more likely to endorse appetite changes and feeling worthless than were European Americans.

For research methodology, the use of qualitative participatory research approaches for “hard-to-reach” Asian/Pacific Islander populations was advocated; such approaches included community-based participatory research (CBPR; P. P. Kwan et al., 2014), participatory action research (PAR; Francisco, 2014), and critical indigenous pedagogy of place (CIPP; Trinidad, 2014). In addition, one quantitative-correlational analytical method – longitudinal dynamic analysis (McArdle, Hamagami, Chang, & Hishinuma, 2014) – was introduced; this method could be used for determining the (causal) direction of the relation between two variables for large datasets, such as the Hawaiian High Schools Health Survey (HHSHS). As an example of articles focused on measurement or methodology, we introduce one qualitative study. By discussing the migrant experiences of Filipinos and describing a participatory action research (PAR) project conducted with Filipino domestic workers in New York City, Francisco (2014) advocated the use of PAR methodology and principles for immigrant communities. Specifically, she advocated the use of kuwentohan, or talk story in Tagalog, as well as theater, as forms of participatory data collection and analytical method. She further argued that PAR could have political potential, in that it could help migrant workers to understand their own individual stories as part of a larger shared story.

Media

There were three articles with a focus on media. They used quantitative designs, including correlational: cross-sectional (Jisu Huh, Delorme, Reid, & Kim, 2014; H. S. Park et al., 2014) and experimental designs (C. Li, 2014). These studies examined the influence of media on adults’ attitudes toward certain products or groups of people (Jisu Huh et al., 2014; C. Li, 2014; H. S. Park et al., 2014). For example, C. Li et al. (2014) examined how the use of Facebook and Renren (a Chinese networking site similar to Facebook) influences Chinese consumers' attitudes toward product packages with different cultural symbols (American cultural symbols or Chinese cultural symbols, or both, or neither). They found that social media use was associated with participants’ preference of packages, such that more intensive Renren usage related to more favorable attitudes toward packages displaying Chinese cultural symbols.

Older adults

We identified 11 articles focusing primarily on issues faced by older adults. Most studies adopted qualitative designs (interview or focus group, n = 7; e.g., K. C.-Y. Sun, 2014). The rest used quantitative designs, including correlational designs (cross-sectional, n = 3; e.g., Dong, Chang, Wong, Wong, & Simon, 2014) and experimental designs (intervention; Yeom & Fleury, 2014). The primary quantitative analytical methods were regression (Dong et al., 2014; S. Lin, Liu, & Jang, 2014), structural equation modeling (B. J. Kim, 2014) and analysis of variance (Yeom & Fleury, 2014).

These studies covered four areas: a) correlates of Asian older adults’ depressive symptoms (Dong et al., 2014; S. Lin et al., 2014) and quality of life (B. J. Kim, 2014); b) older adults’ perceptions of aging, including the onset of old age (Dubus, 2014), the definition of successful aging (A. L. Nguyen & Seal, 2014), and making arrangements for elder care (Browne et al., 2014; Sudha, 2014; K. C.-Y. Sun, 2014); c) elder mistreatment (Y.-S. Lee, Kaplan, & Perez-Stable, 2014; Y.-S. Lee, Moon, & Gomez, 2014); and d) the effectiveness of an intervention program for improving older adults’ mobility (Yeom & Fleury, 2014). We highlight an intervention study that aimed to promote physical activity targeting mobility in older Korean adults (Yeom & Fleury, 2014). Results indicated that a Motivational Physical Activity Intervention program was effective at promoting older adults’ physical activity, walking endurance and flexibility. The effectiveness of this program may be due to increased social resources, self-efficacy, motivational appraisal, and self-regulation for physical activity.

Personality

We identified 11 articles on personality. These studies covered various developmental periods, including childhood (Xu & Krieg, 2014), adolescence (Gupta, Rogers-Sirin, Okazaki, Ryce, & Sirin, 2014; Jo & Bouffard, 2014), emerging adulthood (n = 6; e.g., D’Lima, Winsler, & Kitsantas, 2014), and early adulthood (Fishman, Raval, Daga, & Raj, 2014; Tsai et al., 2014). Studies used quantitative-correlational designs, some cross-sectional (n = 6; e.g., Xu & Krieg, 2014) and some longitudinal (n = 3; e.g., Jo & Bouffard, 2014); also represented were quantitative-experimental (Tsai et al., 2014) and qualitative designs (i.e., interview; Fishman et al., 2014). Analytical methods included regression (n = 3; e.g., Xu & Krieg, 2014), analysis of variance (n = 4; e.g., Kitayama et al., 2014), hierarchical linear modeling (Gupta et al., 2014), growth mixture modeling (Jo & Bouffard, 2014), and structural equation modeling (E. J. Kim, Berger, Kim, & Kim, 2014; J.-y. Lee & Ciftci, 2014).

These articles examined correlates of various measures of personality such as shyness (Xu & Krieg, 2014), independent versus interdependent social orientation (Kitayama et al., 2014), collective self-esteem (Gupta et al., 2014), self-enhancement and self-improvement (E. J. Kim et al., 2014; Tsai et al., 2014), meta-emotion philosophy (Fishman et al., 2014), self-control (Jo & Bouffard, 2014), academic self-efficacy (Lowinger, He, Lin, & Chang, 2014), extrinsic and intrinsic motivation (D’Lima et al., 2014), perfectionism (Chang, Yu, & Lin, 2014), and multicultural personality (J.-y. Lee & Ciftci, 2014). We highlight a 3-wave longitudinal study examining the role of ethnic collective self-esteem and American collective self-esteem on anxious-depressed symptoms from 10^th to 12^th grade in Asian American and Latino adolescents (Gupta et al., 2014). This study found that for both ethnic groups, anxious-depressed symptoms first decreased between 10^th and 11^th grade and then increased over time. For Asian American adolescents, both ethnic and American collective self-esteem were negatively associated with anxious-depressed symptoms, whereas for Latino adolescents, ethnic collective self-esteem was not related to anxious-depressed symptoms, but American collective self-esteem was positively related to anxious-depressed symptoms.

Psychopathology

We identified 23 articles that focused on psychopathology among Asian Americans. As in the annual review for 2013, depression was again the most frequently studied topic (n = 7; e.g., Lund, Chan, & Liang, 2014), followed by suicidality (n = 4; e.g., Hahm, Gonyea, Chiao, & Koritsanszky, 2014), and other forms of psychopathology and distress, including anxiety disorder (n =3; Horng & Coles, 2014; L. O. Lee & Prescott, 2014; Nelson, Bishop, Sarapas, Kittles, & Shankman, 2014), lifetime psychiatric disorders (n = 2; Hong, Walton, Tamaki, & Sabin, 2014; H. Y. Oh & DeVylder, 2014), trauma/Post Traumatic Stress Disorder (PTSD, n = 2; Koo, Nguyen, Gilmore, Blayney, & Kaysen, 2014; Mollica et al., 2014), Autistic Spectrum Disorder (n = 2; Becerra et al., 2014; Chiang, 2014), gambling (n = 2; I. Kim, Kim, & Nochajski, 2014; J. Kim, Ahlgren, & Bernhard, 2014), and schizophrenia (K. K. Lee, Yamada, Kim, & Dinh, 2014).

Depression or depressive symptoms were occasionally studied alongside anxiety and somatization (Masuda, Mandavia, & Tully, 2014; Tuason, Ancheta, & Battie, 2014; Yeh, Liao, et al., 2014). Articles either explored racial/ethnic disparities in the prevalence of depression/anxiety/somatization and identified predictors of this difference (e.g., European Americans versus Asian Americans, n = 2; Chao et al., 2014; Lund et al., 2014) or focused on exploring the risk and protective factors of depression/anxiety/somatization for a single sample (e.g., pan-Asian Americans from diverse ethnic backgrounds or a single Asian ethnic group, such as Chinese Americans, n = 5; S. Cho, Park, Bernstein, Roh, & Jeon, 2014; Masuda, Mandavia, et al., 2014; Remigio-Baker, Hayes, & Reyes-Salvail, 2014; Tuason et al., 2014; Yeh, Liao, et al., 2014). Depression/anxiety/somatization was studied across different developmental periods of the life course: adolescence to emerging adulthood (Lund et al., 2014; Yeh, Liao, et al., 2014), emerging adulthood to middle adulthood (Masuda, Mandavia, et al., 2014; Tuason et al., 2014), older adulthood (Chao et al., 2014), or all of the above in the same study (S. Cho et al., 2014; Remigio-Baker et al., 2014). All studies utilized quantitative: cross-sectional designs and adopted analytical methods such as analysis of variance, multiple regression or logistic regression, and structural equation modeling. For example, Remigio-Baker et al. (2014) studied the association between the count and type of adverse childhood events (household dysfunction: physical, verbal, and sexual abuse) and current depressive symptoms among women aged 18–99 residing in Hawaii. They found that the number of adverse childhood events, as well as having experienced each type of adverse childhood event (vs. not having experienced it), positively predicted having current depressive symptoms, net of the effects of current smoking status and binge drinking.

Suicidality was studied among samples of Asian Americans from one or more ethnic groups. Participants of these studies were at various periods of adulthood, from emerging adulthood/early adulthood (Hahm et al., 2014) to older adulthood (B. J. Kim & Ahn, 2014), or all developmental periods of adulthood within a single study (Chu, Chi, Chen, & Leino, 2014; Y. J. Wong, Vaughan, Liu, & Chang, 2014). Studies used qualitative (interview, Hahm et al., 2014) or quantitative: cross-sectional designs and employed analytical methods such as multiple regression or logistic regression and latent class analysis (Chu et al., 2014; B. J. Kim & Ahn, 2014; Y. J. Wong, Vaughan, et al., 2014) to explore risk factors for suicidal behaviors. For example, using data from the National Latino and Asian American Study, Chu et al. (2014) classified 191 Asian American adults aged 18–82 with a history of serious suicidal ideation or suicide attempts into two subtypes: 48% in a “psychiatric” subtype and 52% in a “nonpsychiatric” subtype. Whereas the “psychiatric” subtype was characterized by a history of psychopathology, such as depressive or bipolar disorders, the “nonpsychiatric” subtype was mainly characterized by sociocultural risk factors (discrimination, family conflict, and low acculturation), medical problems, and limited functioning. Further, findings indicated that the “nonpsychiatric” subtype was less likely than the “psychiatric” subtype to seek help. These results highlighted the heterogeneity of ethnic minority groups in terms of suicidality.

Racism and discrimination

We identified 20 articles for this topic area. Similar to studies in previous annual reviews (Juan et al., 2012; Wei et al., 2014), studies in 2014 focused on the subtopics of model minority myths or stereotypes (n = 9) and the impact of racism on life experiences (n = 10). One study focused on a new subtopic, family communication on discrimination (Juang & Syed, 2014). Most studies targeted emerging adults (n = 11; e.g., Kushins, 2014) or adults (n = 8; e.g., Kushins, 2014), with only two studies focusing on adolescents (Cooc & Gee, 2014; Niwa, Way, & Hughes, 2014). Most studies used quantitative designs, such as experimental (n = 4; e.g., Gibson, Losee, & Vitiello, 2014) and correlational designs, among which were cross-sectional (n = 10; e.g., I. Kim, 2014) and longitudinal designs (Niwa et al., 2014). Others used qualitative designs (interview or focus groups, n = 4; e.g., J. Y. Chung, 2014) or mixed methods (Juang & Syed, 2014). Analytical methods involved regression (n = 6; e.g., Khan, 2014), analysis of variance (n = 5; e.g., Shih, Wout, & Hambarchyan, 2014), structural equation modeling (Festekjian, Tram, Murray, Sy, & Huynh, 2014; I. Kim, 2014), and group-mixture modeling (Niwa et al., 2014).

For model minority myths and stereotypes, studies covered three areas: a) race/ethnicity differences on perceptions of the police (Y. Wu, 2014), perceptions of leadership (Festekjian et al., 2014), and employment discrimination (Covarrubias & Liou, 2014; Kushins, 2014); b) Muslim Americans’ experiences post-9/11, such as perceptions of stigma (Khan, 2014) and experiences of ethnic prejudice (North et al., 2014); and c) Asian Americans’ attitudes or reaction to racial discrimination (Son, 2014), perpetual foreigner stereotype (Tsuda, 2014), and exceptionalizing stereotype (i.e., being treated as an outlier of Asian Americans, A. G. T. T. Tran & Lee, 2014). A. G. T. T. Tran and Lee (2014) found that participants evaluated their partner, the interaction, and future interaction less favorably when they were told by their partner, “You speak English well for an Asian” (high racially loaded condition, exceptionalizing stereotype) than when they were told, “You speak English well” (low racially loaded condition) or, “Nice talking to you” (control condition).

For the impact of racism on life experiences, studies examined the association between discrimination and individual outcomes (A. C.-C. Chen, Szalacha, & Menon, 2014; J. Y. Chung, 2014; Huynh, Devos, & Goldberg, 2014; I. Kim, 2014; Nadal, Wong, Sriken, Griffin, & Fujii-Doe, 2014; Niwa et al., 2014; Yeung & Johnston, 2014), national trends regarding Asian Americans’ school victimization (Cooc & Gee, 2014), and whether ethnic or gender stereotype influences female Asian college students’ academic performance (Gibson et al., 2014; Shih et al., 2014). We highlight a longitudinal study examining developmental patterns of ethnic-racial discrimination from two sources (adults and peers) and its consequences in Chinese, Dominican, and African American sixth to eighth graders (Niwa et al., 2014). Using a semiparametric mixture model, the study revealed two developmental patterns for adult discrimination (moderate-stable and low-stable) and three developmental patterns for peer discrimination (high-decreasing, moderate-decreasing, and low-decreasing). Those classified into the low-stable or low-decreasing groups tended to be better adjusted at eighth grade.

Spirituality

We found four articles on spirituality. As in last year’s review (Wei et al., 2014), these articles mainly focused on the effect of religion and spirituality on physical and mental health outcomes (Appel, Ai, Huang, & Nicdao, 2014; Hodge, Sun, & Wolosin, 2014; Lagman, Yoo, Levine, Donnell, & Lim, 2014; G.-H. H. Yi & Bjorck, 2014). Most studies used quantitative-correlational designs (cross-sectional), with one study using a qualitative design (interview; Lagman et al., 2014). Studies generally focused on adults, with one specifically focusing on older adults (Hodge et al., 2014). Hodge et al. (2014) tested a model of spiritual care for older hospitalized Asians. They found that the relationship between participants’ perceptions of how well hospital staff addressed their spiritual needs and their overall satisfaction with the services provided during hospitalization were mediated by responsiveness and skills of nurses and physicians, accommodation for visitors and staff members’ attitudes toward visitors, as well as the admission and discharge process (e.g., speed and attitude).

Stress and coping

For the 2014 review, we identified 16 articles related to stress and coping. Two subtopics were consistent with those in Wei et al.’s (2014) review, coping in the context of health-related problems (n = 2) and coping strategies (n = 2). We also identified two new subtopics: coping in the context of trauma (n = 4) and general stress and coping issues (n = 8). Most studies focused on adults (n = 9; e.g., Mossakowski & Zhang, 2014), while two studies focused on adolescents (Kiang & Buchanan, 2014; Lam, Alvarado, & Lee, 2014) and three studies focused on older adults (e.g., K. H. Lee & GlenMaye, 2014). Most studies adopted quantitative-correlational designs, most of which were cross-sectional (n = 9; e.g., Mossakowski & Zhang, 2014) and one of which was longitudinal (Kiang & Buchanan, 2014); the rest used qualitative designs (interview or case study, n = 5; e.g., Connor & Miller, 2014) and mixed methods (S. K. Park, Stotts, Douglas, Donesky-Cuenco, & Carrieri-Kohlman, 2014). Analytical methods mainly included regression (n = 5; e.g., H. Chung & Epstein, 2014), analysis of variance (n = 3; e.g., Logan, Barksdale, & Chien, 2014), structural equation modeling (J. H. J. Kim, Nagata, & Akiyama, 2014), and hierarchical linear modeling (Kiang & Buchanan, 2014).

The two articles in the category of coping in the context of health-related problems highlighted specific coping strategies for certain diseases, including asthma or chronic obstructive pulmonary disease (S. K. Park et al., 2014) and breast cancer (Lim, 2014). The two articles about coping strategies examined whether gender, ethnicity (H. Lee & Mason, 2014) and collective self-esteem (Lam et al., 2014) related to coping strategies. For example, H. Lee and Mason (2014) found that Korean Americans (vs. Caucasians) scored higher on problem-focused, emotion-focused, and avoidant coping strategies; women (vs. men) utilized more planning, religion, and denial coping strategies.

For coping in the context of trauma, studies covered people’s reactions following a tsunami in American Samoa (Binder, Baker, Mayer, & O'Donnell, 2014), the death of a husband (Saito, 2014), incarceration experiences (C. M. Nguyen et al., 2014), and government redress for their unjust incarceration during World War II (J. H. J. Kim et al., 2014). J. H. J. Kim et al. (2014) examined predictors of second-generation Japanese-American older adults’ reactions to government redress for their unjust incarceration during World War II. They demonstrated that belief in a just world and two dimensions of locus of control (internal and powerful others) related to greater relief of suffering and more positive effects of redress.

With respect to general stress and coping issues, studies examined individual adjustment consequences of various types of stress (e.g., daily stress and occupational stress; Connor & Miller, 2014; Kiang & Buchanan, 2014), and moderators of the effect of stress (e.g., social support; H. Chung & Epstein, 2014; Logan et al., 2014; Mossakowski & Zhang, 2014), as well as coping resources (Chatrung, Sorajjakool, & Amnatsatsue, 2014; K. H. Lee & GlenMaye, 2014; Woo, Lee, & Hong, 2014). For example, in a daily-diary study, Kiang and Buchanan (2014) examined the relationship between stress in three domains (i.e., family, school, and peers) and well-being (happiness, distress, and anxiety) among Asian American 9^th to 10^th graders. Hierarchical linear modeling demonstrated bidirectional relationships between stress and well-being in the same day but not across days.

Violence

We identified six articles with a focus on violence. These articles covered areas of child maltreatment (Y. Lee, Malley-Morrison, Jang, & Watson, 2014), sexual and/or emotional and physical violence (Baker, Naai, Mitchell, & Trecker, 2014; Foynes, Platt, Hall, & Freyd, 2014), intimate partner violence among men who have sex with men (A. Tran et al., 2014), Asian Indians (Yoshihama, Blazevski, & Bybee, 2014) and the elderly (H. Y. Lee et al., 2014). Study designs included mixed methods (H. Y. Lee et al., 2014), experimental (intervention; Baker et al., 2014), and correlational designs (Foynes et al., 2014; Y. Lee et al., 2014; A. Tran et al., 2014; Yoshihama et al., 2014). Data analytical methods used were analysis of variance (e.g., Y. Lee et al., 2014) and logistic regression (e.g., Foynes et al., 2014). We highlight one mixed-methods study (H. Y. Lee et al., 2014) conducted with two cohorts of Korean elders (immigrants in the U.S. and Korea-based). For both cohorts, when presented with a vignette that depicted a hypothetical scenario of intimate partner violence, participants showed low recognition of intimate partner violence and low help-seeking intention. The authors further conducted qualitative content analysis to identify reasons for not seeking help (e.g., “keeping family problems inside”) and quantitative multivariate analysis to identify predictors of help-seeking intention (i.e., perceiving the vignette as elder mistreatment for both cohorts, and being female and showing lower adherence to traditional values for the immigrant cohort).

Women

One article focused on the general well-being of Asian American women. Vang and Her (2014) interviewed 12 Hmong American women and studied their teenage marriages. They found that, as these Hmong women acculturated, they questioned the legitimacy of the traditional Hmong practice of teenage marriage. After identifying family socialization processes and individual perspectives linked with teenage marriage for Hmong American women, the authors called for more practice, policy, and research interventions aimed at better educating and helping Hmong women with their decisions about early marriage.

Youth

One article focused on youth rather than other topic areas. Fradkin et al. (2014) examined whether Asian American youth experienced disparities in general quality of life (e.g., physical, emotional, social, school, etc.) compared to Hispanic, African American, and White youth. They found that Asian American youth experienced lower status than White youth (but not Hispanic or African American youth) for three out of 10 quality of life measures (e.g., self-worth, physical and social well-being), controlling for socioeconomic differences.

Top Authors and Journals

This year, we recognize the most prolific authors contributing to Asian American scholarship. Table 6 lists 25 authors who have two or more first author publications in this review, along with their current department, the primary topics of their 2014 published articles, the study designs employed in their studies, the developmental period(s) studied, and the ethnicities of the participants represented in their articles. The top authors represented a variety of disciplines, including psychology, social work, medicine, public health, epidemiology, human development, and education. The primary topics studied by these prolific authors match the primary topic frequencies among the articles in this year’s review, with health and health-related behaviors being the most studied area, followed by counseling and clinical issues. Stephen H. Chen had the most publications included, with five articles represented in the 2014 review. Among the top authors whose number of citations and impact points (acquired from Research Gate) and h-index scores (acquired from Google Scholar profiles) were available, Shinobu Kitayama had the highest overall score in all three areas.

Table 6.

Top Authors for the 2014 Annual Review of Asian American Psychology

Author Name	Current Department	Primary Topic of Published Articles	Study Design	Developmental Period	Ethnicities Studied	Articles
Chen, Stephen H.	Psychology, Wellesley College	Counseling and clinical issues, Families, Acculturation and enculturation, Cognition	Mixed methods, Correlational: Cross-Sectional	Middle Childhood, Early Adulthood, Middle-Aged Adults	Other Asian, Taiwanese, Chinese, Filipino, Asian American	27, 28, 29, (159)*, (316)
Kim, Su Yeong	Human Development and Family Sciences, University of Texas at Austin	Acculturation and enculturation, Families, Measurement and methodology	Correlational: Longitudinal	Adolescence, Middle-Aged Adults	Chinese	141, 142, 143, (259)
Okamoto, Scott K.	Social Work, Hawaii Pacific University	Health and health-related behaviors	Mixed methods, Qualitative, Correlational: Cross-Sectional	Adolescence	Hawaiian, Samoan, Chinese, Filipino, Japanese, Pacific Islander	(84), 228, 229, 230
Pokhrel, Pallav	Cancer Prevention and Control, University of Hawaii Cancer Center	Health and health-related behaviors, Measurement and methodology	Correlational: Cross-Sectional	Adolescence, Emerging Adults, Early Adulthood, Middle-Aged Adults	Pacific Islander, Hawaiian, Chinese, Korean, Filipino, Japanese, Asian American, Other Asian, Marshallese, Cham	(86), 241, 242, 243
Nguyen, Anh B.	Division of Cancer Control and Population Sciences, The National Cancer Institute, Rockville, Maryland	Health and health-related behaviors	Experimental, Correlational: Cross-Sectional	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Vietnamese	217, 218, 219
Tran, Thanh V.	Social Work, Boston College	Health and health-related behaviors, Acculturation and enculturation	Correlational: Cross-Sectional	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Vietnamese, Chinese, Korean, Filipino, Japanese, South Asian	278, 279, 280
Wong, Y. Joel	Education, Indiana University Bloomington	Counseling and clinical issues, Measurement and methodology, Psychopathology	Experimental, Correlational: Cross-Sectional	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Chinese, Korean, Vietnamese, Other Asian, Asian Indian, Filipino, Japanese, Asian American	294, 295, 296
Huh, Jimi	Preventive Medicine, University of Southern California	Health and health-related behaviors	Correlational: Longitudinal, Mixed methods, Correlational: Cross-Sectional	Emerging Adults, Early Adulthood, Middle-Aged Adults	Korean	94, 95, (315)
Jang, Yuri	Social Work, University of Texas at Austin	Older Adults, Acculturation and enculturation, Counseling and clinical issues	Correlational: Cross-Sectional, Correlational: Longitudinal	Middle-Aged Adults, Early Adulthood, Older Adults	Chinese, Korean	102, 103, (186)
Kim, Bum Jung	Social Work, University of Hawaii at Manoa	Older Adults, Psychopathology	Qualitative, Correlational: Cross-Sectional	Middle-Aged Adults, Older Adults	Hawaiian, Korean	(17), 125, 126
Kim, Isok	Social Work, University at Buffalo	Counseling and clinical issues, Racism and discrimination, Psychopathology	Correlational: Cross-Sectional	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Filipino, Vietnamese, Asian American, Chinese, Asian American	(37), 132, 133
Kitayama, Shinobu	Psychology, University of Michigan	Cognition, Personality	Experimental, Correlational: Cross-Sectional	Emerging Adults	Taiwanese, Chinese, Korean, Asian American, Japanese, Other Asian	147, 148, (234)
Sun, Fei	Social Work, Arizona State University	Health and health-related behaviors, Spirituality	Correlational: Cross-Sectional, Qualitative	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Chinese, Asian American	(87), 270, 271
Chang, Edward C.	Psychology, University of Michigan	Health and health-related behaviors, Personality	Correlational: Cross-Sectional	Emerging Adults	Asian American	22, 23
Kally, Zina	Institute for Change, Partners in Care Foundation, San Fernando, California	Health and health-related behaviors	Correlational: Longitudinal	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Chinese, Filipino, Japanese, Pacific Islander, Asian American	114, 115
Lee, Eun-Jeong	Psychology, Illinois Institute of Technology	Counseling and clinical issues	Correlational: Cross Sectional	Emerging Adults, Early Adulthood	Korean	160, 161
Lee, Ji-yeon	Education, Hankuk University of Foreign Studies, South Korea	Personality, Counseling and clinical issues, Interpersonal relationships	Correlational: Cross-Sectional	Emerging Adults, Early Adulthood	Chinese, Korean, Vietnamese, Japanese, Asian Indian, Taiwanese, Pakistani, Malaysian, Bangladeshi, Indonesian, Singaporean, Asian American	167, 169
Lee, Sungkyu	Social Work, University of Tennessee	Counseling and clinical issues, Health and health-related behaviors	Correlational: Cross-Sectional	Emerging Adults, Early Adulthood, Middle-Aged Adults	Filipino, Vietnamese, Asian American, Chinese, Other Asian, Korean	173, 174
Lee, Yeon-Shim	Social Work, San Francisco State University	Older Adults	Qualitative	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Korean, Japanese, Other Asian, Chinese	177, 178
Masuda, Akihiko	Psychology, Georgia State University	Health and health-related behaviors, Psychopathology	Correlational: Cross-Sectional	Emerging Adults, Early Adulthood	Chinese, Korean, Filipino, Vietnamese, Asian American, Other Asian, Asian Indian, Pakistani, Cambodian	198, 199
McArdle, John J.	Psychology, University of Southern California	Measurement and methodology, Cognition	Correlational: Longitudinal, Cross-Sectional	Adolescence, Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Hawaiian, Chinese, Japanese	201, 202
Meschke, Laurie L.	Public Health, University of Tennessee	Families, Health and health-related behaviors	Qualitative, Correlational: Cross-Sectional	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Hmong	204, 205
Pedersen, Eric R.	RAND Corporation, Santa Monica, California	Health and health-related behaviors, Counseling and clinical issues	Correlational: Cross-Sectional	Adolescence, Emerging Adults	Cambodian, Asian American	239, 240
Yang, Lawrence H.	Epidemiology, Columbia University	Counseling and clinical issues	Mixed methods, Qualitative	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	Chinese	303, 304
Yeh, Christine J.	Counseling Psychology, University of San Francisco	Psychopathology, Counseling and clinical issues	Correlational: Cross-Sectional, Mixed methods	Adolescence, Emerging Adults	Chinese, Other Asian, Taiwanese, Bi or multi-racial, Samoan	305, 306

Note. This table is a new feature of this review. This table is ordered by number of publications contributed to this review.

^*Citations in parentheses are co-authored publications.

This year, a total of 192 journals are represented in this review. Of these journals, 39 had two or more publications included, representing 143 articles (see Table 7). The primary topics and developmental periods associated with these journals are also represented in this table. Among these journals, the range in impact factors was 0.309 at the lowest to 4.974 at the highest. Of the journals that published two or more articles included in this review, there were eight journals without an impact factor that were therefore excluded from Table 7. The Asian American Journal of Psychology has the most publications represented in this review, followed by Cultural Diversity and Ethnic Minority Psychology, the Maternal and Child Health Journal, and Substance Use & Misuse. The journals with the top five highest impact factors, in order from greatest to least, were the Journal of Abnormal Psychology, Developmental Psychology, Journal of General Internal Medicine, Drug and Alcohol Dependence, and the Journal of Counseling Psychology. Information about these top journals can guide scholars in deciding which journal to target when submitting an article relevant to Asian American psychology.

Table 7.

Top Journals for the 2014 Annual Review of Asian American Psychology

Journal Name	n	ISI Impact Factor For 2013	Primary Topic	Developmental Period	Article Citations
Asian American Journal of Psychology	33	1.405	Counseling and clinical Issues, Violence, Health and health-related behavior, Personality, Youths, Cognition, Psychopathology, Racism and discrimination, Acculturation and enculturation, Adoptees, Families, LGBTQ, Identity	Infants and Toddlers, Early Childhood, Middle Childhood, Adolescence, Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	4, 6, 18, 23, 60, 64, 70, 88, 92, 97, 101, 103, 104, 135, 141, 166, 184, 199, 211, 212, 214, 259, 260, 262, 265, 273, 287, 295, 305, 306, 314, 315, 316
Cultural Diversity and Ethnic Minority Psychology	11	1.755	Health and health-related behavior, Families, Personality, Measurement and methodology, Racism and discrimination, Stress and coping, Counseling and clinical issues, Identity	Middle Childhood, Adolescence, Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	19, 28, 73, 120, 132, 136, 139, 159, 219, 249, 283
Maternal and Child Health Journal	6	2.015	Health and health-related behavior, Psychopathology	Adolescence, Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	36, 66, 81, 83, 207, 248
Substance Use & Misuse	6	1.226	Health and health-related behavior, Acculturation and enculturation	Adolescence, Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	95, 96, 190, 232, 236, 313
Community Mental Health Journal	5	1.146	Counseling and clinical issues, Psychopathology	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	37, 38, 133, 161, 226
Ethnicity and Health	4	1.276	Health and health-related behavior, Families	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	151, 204, 246, 251
Journal of Counseling Psychology	4	2.955	Career, Counseling and clinical issues, Racism and discrimination, Measurement and methodology	Emerging Adults, Early Adulthood	39, 258, 277, 294
Addictive Behaviors	3	2.441	Health and health-related behavior	Adolescence, Emerging Adults, Early Adulthood, Middle-Aged Adults	239, 242, 243
American Journal of Health Behavior	3	1.137	Health and health-related behavior	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	109, 210, 241
Clinical Gerontologist: The Journal of Aging and Mental Health	3	0.660	Interpersonal relationships, Older Adults, Health and health-related behavior	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	153, 186, 271
Drug and Alcohol Dependence	3	3.278	Health and health-related behavior, Measurement and methodology	Adolescence, Emerging Adults, adults, Middle-Aged Adults, Older Adults	8, 86, 255
Journal of Career Development	3	0.846	Career	Emerging Adults, Early Adulthood, Middle-Aged Adults	121, 196, 302
Journal of College Student Development	3	0.355	Identity, Career, LGBTQ	Emerging Adults	197, 244, 266
Journal of Health Care for the Poor and Undeserved	3	0.902	Health and health-related behavior	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	173, 208, 217
Journal of Social Service Research	3	0.309	Families, Health and health-related behavior, Stress and coping	Adolescence, Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	183, 279, 297
Preventing Chronic Disease: Public Health Research, Practice, and Policy	3	1.956	Health and health-related behavior	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	111, 200, 284
Psychology of Men & Masculinity	3	1.823	Measurement and methodology, Health and health-related behavior, Stress and coping	Emerging Adults, Middle-Aged Adults, Older Adults	91, 122, 221
Aging and Mental Health	2	1.781	Psychopathology, Counseling and clinical issues	Older Adults	126,163
AIDS Care	2	2.194	Health and health-related behavior	Emerging Adults, Early Adulthood, Middle-Aged Adults	30, 254
Cancer Nursing	2	1.931	Health and health-related behavior	Middle-Aged Adults, Older Adults	203, 267
The Counseling Psychologist	2	1.696	Health and health-related behavior, Counseling and clinical issues	Emerging Adults, Early Adulthood, Middle-Aged Adults	32, 296
Developmental Psychology	2	3.782	Acculturation and enculturation, Stress and coping	Middle Childhood, Adolescence	27, 124
Ethnic and Racial Studies	2	0.888	Identity, Racism and discrimination	Emerging Adults, Early Adulthood	225, 285
Health Promotion Practice	2	0.55	Health and health-related behavior, Measurement and methodology	Adolescence, Middle-Aged Adults	154, 230
Infant and Child Development	2	1.162	Families, Personality	Early Childhood, Middle Childhood, Adolescence, Early Adulthood	195, 301
International Journal of Intercultural Relations	2	1.216	Stress and coping, Personality	Emerging Adults, Early Adulthood, Middle-Aged Adults	42, 168
Journal of Abnormal Psychology	2	4.974	Health and health-related behavior, Measurement and methodology	Emerging Adults, Early Adulthood, Middle-Aged Adults	137, 193
Journal of Adolescence	2	1.638	Racism and discrimination	Adolescence, Emerging Adults, Early Adulthood	46, 108
The Journal of Behavioral Health Services & Research	2	1.026	Health and health-related behavior, Counseling and clinical issues	Adolescence, Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	222, 228
Journal of Community Psychology	2	0.832	Stress and coping, Counseling and clinical issues	Emerging Adults, Early Adulthood	11, 160
Journal of General Internal Medicine	2	3.423	Health and health-related behavior	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	256, 275
Journal of Religion and Health	2	0.945	Stress and coping, Spirituality	Middle-Aged Adults, Older Adults	25, 156
Journal of Transcultural Nursing	2	0.830	Stress and coping, Acculturation and enculturation	Early Adulthood, Middle-Aged Adults, Older Adults	235, 261
Journal of Youth and Adolescence	2	2.312	Identity, Acculturation and enculturation	Adolescence	68, 142
Nicotine & Tobacco Research	2	2.805	Health and health-related behavior	Emerging Adults, Early Adulthood, Middle-Aged Adults	12, 94
Psychological Trauma: Theory, Research, Practice, and Policy	2	2.097	Violence, Psychopathology	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	63, 149
Qualitative Health Research	2	1.625	Health and health-related behavior, Personality	Early Adulthood, Middle-Aged Adults, Older Adults	21, 62
Social Science & Medicine	2	2.558	Health and health-related behavior, Counseling and clinical issues	Emerging Adults, Early Adulthood, Middle-Aged Adults, Older Adults	303, 311
Teachers College Record	2	0.722	Identity, Racism and discrimination	Adolescence, Early Adulthood	48, 181

Note. ISI = Institute for Scientific Information. This table is a new feature of this review. This table is ordered by number of publications contributed to this review. n = Number of articles published within each journal.

Discussion

This year’s review includes the largest number of articles published in an annual review to date at 316. The body of literature on Asian American psychology will continue to expand as the Asian American and Pacific Islander population gains increasing visibility and becomes more prominent in the United States. Indeed, the first-ever White House Summit on Asian American and Pacific Islanders was held recently in Washington D.C., on May 12, 2015 (www.ed.gov/edblogs/aapi). Here, in our discussion, we identify continuing content and methodological trends from past years, as well as new ones.

Content Trends

As in past reviews, health and health-related behaviors remained by far the most studied topic in 2014, particularly the subtopics of cancer screening and management and substance use. This continuing trend is most likely due to several factors: the leading cause of death for Asian American and Pacific Islanders is cancer (U.S. Census Bureau, 2013), there are numerous disciplines beyond psychology that address health-related issues (Juan et al., 2012), the priorities of agencies such as the National Institutes of Health mean that research on this topic gets funded more easily, and the Asian American community continues to advocate for research focused on the health of Asian Americans (Wei et al., 2014). Other frequently studied topics that were also prominent in reviews from past years were counseling and clinical issues, psychopathology, and racism and discrimination. Although health, disease, and negative life experiences are unquestionably meaningful targets of research, Wei et al. (2014) suggested in the last review that positive psychology is also an important topic to investigate. In other words, researchers should focus not only on challenges faced by Asian Americans, but also on the particular strengths of this community. Although we did not find studies of positive psychology to include in this year’s review, a forthcoming Asian American Journal of Psychology special issue is devoted to this important topic. Topics that were less common in this year's review compared to reviews from previous years include acculturation, immigration, refugees, and educational experiences. These decreasing trends may be an indication that the content areas in question are diversifying and that researchers are moving away from traditional topics to include a broader range of experiences relevant to the AAPI community. Nonetheless, as the AAPI population has the most foreign-born individuals of any ethnic group (Ramakrishnan & Ahmad, 2014), acculturation and other immigration-related issues will continue to be salient and therefore worth further study.

Our review has identified a few new trends, such as an emphasis on topics (e.g., cognition) that did not warrant a separate topic heading in previous reviews, an increasing recognition of and attention to heterogeneity within the AAPI population, and greater attention to measurement. In 2014, there were considerably more studies on cognition, personality, and measurement and methodology. In the cognition topic area, three out of the 16 studies focused on neural correlates of cognitive processes. President Obama declared 2013 as the year of the BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative (braininitiative.nih.gov); new fields of inquiry, such as cultural neuroscience (the study of the dynamic relations between culture, behavior, mind, brain, and genes) have also emerged within the last decade (e.g., Chiao, Cheon, Pornpattananangkul, Mrazek, & Blizinsky, 2013). We will no doubt see more studies on cognition with the AAPI population in the future.

Although many studies still use the pan-ethnic Asian American label, more attention to within-group variability of specific ethnicities is evident (e.g., Hawley et al., 2014). This year’s review also found more studies that included bicultural or multiracial Asian-heritage populations compared to past reviews (e.g., L.-T. Wu et al., 2014). This is an encouraging trend, reflecting the fact that from 2000 to 2010, the multiple-race “White and Asian” population increased by a remarkable 87% in the United States (Jones & Bullock, 2012). Continued attention to this population is warranted, as individuals in the U.S. are becoming less and less likely to be monocultural. As in previous reviews, articles in the present review gave the most attention to Chinese- and Korean-heritage populations. In the U.S., the largest Asian subpopulations are Chinese, Filipinos, Asian Indians, Vietnamese, Koreans, Native Hawaiian and Pacific Islanders, and Japanese (U.S. Census Bureau, 2015). B. S. K. Kim et al.’s initial 2010 review noted that the greatest disparity between number of studies and population size was evident for the Asian Indian group. In 2014, this disparity continued. Further, some subgroups in this understudied population, for example Bangladeshi Americans, have grown tremendously, increasing an astounding 177% from 2000 to 2010 (Ramakrishnan & Ahmad, 2014). As the demographics of the United States continue to change, researchers will need to closely consider these shifts and devote more attention to groups that have been studied less often. Because disparities among different Asian subgroups remain in many areas, such as educational attainment, household income, poverty rates, prevalence rates for diseases, and life expectancy (Ramakrishnan & Ahmad, 2014), specific attention to the great diversity among Asian subgroups will be necessary.

The first annual review (B. S. K. Kim et al., 2010) called for more research on older adults (65 years and older). It appears that this recommendation is slowly being fulfilled, as we are now seeing a substantial number of articles on older adults. The proportion of older adults in the U.S. population is growing, and is projected to reach 20% of the population in 2030, compared to 13% in 2010 (Ortman, Velkoff, & Hogan, 2014). Understanding aging, and focusing not only on challenges but also on positive developments of older adults, will be important for future scholars to address. Our review also shows that there is a clear lack of studies on infancy and the early childhood years. Because the early years are important in setting the stage for later developmental trajectories, we encourage researchers to pay greater attention to these earlier age groups. Perhaps this oversight reflects the historically non-developmental approach of Asian American psychology in general, and the fact that the Asian American Psychological Association (aapaonline.org) has a membership dominated by clinical and counseling psychologists. Relatedly, we also recommend moving towards more collaboration among AAPI researchers across disciplines and subdisciplines of psychology (such as developmental and counseling psychology). Combining diverse approaches to study the health and well-being of the AAPI community should lead to novel and more comprehensive insights.

Methodological Trends

Notably, we found a sufficient number of studies on measurement and methodology to warrant creating a separate topic for them in this review. Many instruments used with Asian American populations have been adapted from measures developed with other populations (e.g., racism and racial socialization measures, see Yeh et al., 2013 previous critique of the widely used Everyday Discrimination Scale). It is encouraging in this review to see new measures, such as the language brokering scale (S. Y. Kim, Y. Wang, S. R. Weaver, et al., 2014), developed specifically for Asian American populations. It is also encouraging to see more rigorous testing of quantitative rating scales to establish reliability and validity for use with Asian American populations (J. M. Kim & López, 2014). Wei et al.’s (2014) review identified a trend of more studies focusing on measurement invariance issues. In 2014, this trend continued.

As the previous five reviews also showed, there is a continued reliance on correlational study designs in the overwhelming majority of articles. And most correlational study designs were cross-sectional. Earlier reviews (Juan et al., 2012; B. S. K. Kim et al., 2010; Okazaki et al., 2011) encouraged more experimental research to add variety to the study designs used. We agree that the field should continue to expand and diversify research designs, especially if researchers aim to uncover causal relations and mechanisms among variables and phenomena of interest.

Wei et al.’s (2014) review suggested that future reviews code for cross-sectional versus longitudinal research designs. We adopted this suggestion and also included a developmental focus. By coding for participants’ developmental period, we were able to highlight the points in the lifespan that were targeted by studies most often (emerging and early adults) and least often (infancy and early childhood). It also became clear that there is a dearth of longitudinal studies. This research gap limits our understanding of stability and change in developmental pathways and trajectories.

Two other methodological gaps were clear. There were few papers that used person-centered approaches (e.g., latent class analysis, Chu et al., 2014) and only a handful that used mixed methods (combining qualitative and quantitative methods and data). Identifying patterns or configurations of individuals beyond the variable approach offers information that is person-specific, rather than a generalization that may not necessarily apply to any one individual. A longitudinal, person-centered approach (e.g., latent transition analysis) is especially useful for understanding how specific groups of individuals change across time. Designing a study with mixed methods is both a challenge to carry out and potentially of great benefit (Creswell & Clark, 2007). The use of mixed methods may be intuitively attractive for psychological studies with AAPI populations in newer areas such as positive psychology, religion and spiritually, or media.

Another continuing trend is that traditional analytical methods such as regression and analysis of variance were the most commonly used. More complex analytical methods, such as structural equation modeling, growth modeling, and generalized estimating equations, were less frequently employed. It will be important for researchers to keep pace with innovative analytic techniques that will allow for greater flexibility in answering research questions appropriately and adequately.

Finally, an area for consideration in future reviews is coding for the geographical location and community characteristics of areas from which samples were drawn. This would mean, of course, that researchers need to include information about the community context in their manuscripts. The AAPI population has traditionally concentrated in a few states (e.g., California, New York, Hawaii). Now, however, states such as Nevada, Arizona, North Dakota, North Carolina, and Georgia have seen a doubling in their Asian American communities (Ramakrishnan & Ahmad, 2014). Greater attention to these changing demographics may be especially relevant for certain topics and populations (e.g., ethnic and racial identity, LGBTQ issues). Each of these communities may offer variations in networks of support, institutional completeness, availability of cultural resources, and status and visibility of the Asian American community. These variations may have implications for the psychology of AAPI individuals. Thus, sampling from a range of diverse communities and documenting community characteristics will be essential in future studies.

Limitations and Future Directions

Throughout the process of writing this review, we encountered several situations that have informed our recommendations for future directions. Our greatest challenge was the disparity between the search results produced by EBSCO’s search engine for PsycINFO, which is the only search engine available at our university, and the search results produced by OvidSP’s PsycINFO. The fewer number of articles retrieved from PsychINFO using EBSCO, relative to the number retrieved by OvidSP, created a considerable obstacle during the production of this review. We echo Wei et al.’s (2014) recommendation that future authors of this annual review use OvidSP’s PsycINFO to conduct their initial search for articles.

For the sake of consistency, we firmly held to the inclusion criteria used by past reviews. This strategy aided in narrowing the focus to articles on Asian Americans, specifically; however, some articles in which the sample was largely made up of Asian Americans were excluded because they did not have a research question focusing specifically on Asian Americans. For example, Nadal, Griffin, Wong, Hamit, and Rasmus’ (2014) article regarding micro aggressions against minorities included a participant base in which the majority of participants identified as Asian American; however, we did not include it in the review, for reasons outlined by Juan et al.’s (2012) exclusion criteria.

While the inclusion criteria serve a purpose, there were a few articles that we felt challenged the parameters currently in place, leading us to wonder whether perhaps they need to be reconfigured. We came across several articles that were relevant to Asian Americans, even though they did not comprise the body of participants in the study (e.g., L. Guo & Harlow, 2014; Phua, 2014). In Phua’s (2014) article comparing consumer attitudes regarding advertisements that feature Asian American (versus Caucasian) spokesmodels, the participants evaluating the advertisements belonged to diverse ethnic groups. Even if the study participants are not exclusively (or even mostly) Asian American, articles of particular relevance to Asian Americans should be considered for inclusion in the future. A similar recommendation was also offered in Juan et al.’s (2012) and Wei et al.’s (2014) reviews.

Another limitation is the indexing of online publications on PsycINFO, which creates an overlap between articles for the present year in review and the following year in review. For example, we included Dong’s (2014) article in this review because it was published in print in 2014. However, Wei et al. (2014) also included it in their 2013 review because it was indexed as an advanced online publication for 2013. This shows that some articles published late in the year may be included in two consecutive annual reviews. To minimize this overlap, we excluded 24 advance publications we originally coded for 2014, because they were later published in print in 2015 (e.g, Wang, Koh, & Song, 2015). As of April 2015, there were 20 articles published online in 2014 that were awaiting publication in print. Between May and August of 2015, five of those 20 articles were published in print. As such, these articles are likely to overlap with the 2015 annual review. We recommend that coding teams of future reviews check to see whether online articles are published in print around April of the following year, and if so, exclude those articles. Additionally, some articles that get published late in the year were not considered for inclusion in this annual review because they were not indexed by EBSCO PsycINFO until after we had concluded our searches. For example Kim, Parton et al.’s (2014) paper was published in December 2014, but not indexed into the EBSCO PsycINFO database until May 2015. Additionally, between May 2015 and July 2015, we found three articles that were published in 2014 that would have been included in the annual review (Bell et al., 2014; Becerra, Herring, Marshak, & Banta, 2014; I. Kim & Kim, 2014). Given that we only found three additional articles, we recommend that future reviews forgo their searches for additional articles by April of the annual review’s publication.

Our next recommendation is that studies with Asian participants residing in Canada be included in future reviews. This recommendation is based on the definition of “Asian American” provided by the Asian American Journal of Psychology (AAJP) in their mission statement: “…Americans of Asian and Pacific Islander ancestry in the United States and Canada” (American Psychological Association, 2015). In L. Kim et al.’s (2014) study, contemporary parenting styles were analyzed among second-generation Korean-American parents residing in Canada and the United States. Due to the inclusion criteria currently in place, this article was excluded.

To be consistent with Wei et al.’s (2014) Asian American ethnicities, which are listed in Table 3, we included Muslims as an ethnicity during our search for articles, as outlined in the Method section. However, the Muslim faith is observed by many more ethnicities than just those of Asian descent, and is therefore more appropriately categorized as a religion than an ethnicity. The “Muslim” category emerged as a topic for discussion during the process of producing this review, most notably while coding for ethnicities. In general, the articles that included Muslim participants compared them with participants of different religions rather than with participants with different ethnicities, and some studies did not provide the ethnicities of the Muslim participants at all (e.g., Khan, 2014). Therefore, we recommend that Muslims no longer be included as a separate ethnicity in future reviews.

We recommend that future reviews maintain the distinction we have made between the primary topic and target population of the primary topic (Tables 1 and 4, respectively). We believe that this approach allows for a more multifaceted overview of the articles included. As both the primary topic and the population studied are important features of empirical studies, and because these are conceptually different from one another, we recommend that in the future, they continue to be coded for independently. We also recommend that the description of the studies in the Results section continue to highlight the statistical or data analytic strategies used. Lastly, we recommend retaining the top authors and top journals tables recognizing prolific scholars and top journals that contribute to each year’s review (Tables 6 and 7, respectively).

Despite the benefits of conducting author searches, it is a large undertaking to conduct them in a limited time frame. Of the 1,412 articles generated from the author search, only 2.27% of those articles made it into the final review, a much smaller proportion than any of our other searches. Because the payoff for this search is so low, we do not recommend that future authors of this review employ this particular search technique. Similarly, the searches we conducted based on the ethnicities listed in Table 3 yielded 2,087 articles, more than any of our other searches. Of these articles, only 5.32% were included in this review. For this reason, we recommend using the methodology outlined by Wei (2014) and Yeh (2013), searching only for the ethnicities Asian American, Pacific Islander, Hawaiian, and Samoan.

We suggest that scholars involved in producing future issues of this review begin to reassess the primary topic areas (see Table 1). As the field matures and begins to investigate new areas, such as culture and biology (a planned special issue for Cultural Diversity and Ethnic Minority Psychology) and cultural neuroscience (Kitayama et al., 2014; Kitayama & Park, 2014), and as the population of Asian Americans changes to become more multi-racial (Hoeffel et al., 2012), future annual reviews may consider revamping the present set of primary topics to keep up with the changing field of Asian American psychology.

Lastly, we recommend that the journal consider adopting a 5–10 year review perspective, in addition to publishing an annual review. While the Handbook of Asian American Psychology (2007) covers longer spans of scholarship on specific topics, it is not a peer-reviewed outlet. An additional 5–10 year review would allow examination of the broad changes taking place in the field, in addition to the smaller, more nuanced changes year to year. The suggested approach for this longer-term review is that it be topical in structure, and that the topics included be determined by emerging themes in the field, decade to decade. The Journal of Marriage and Family (2010) and the Journal of Research and Adolescence (2011) each produce a 10-year review with a structure similar to the one we recommend.

This series of annual reviews has seen a tremendous growth in the number of articles included over the past six years, growing from 134 articles identified in B. S. K. Kim et al.’s (2010) review to the 316 articles identified in the current review. There appears to be more consistency than change in terms of primary topic studied, participant characteristics, and study design of articles across the six years covered by these annual reviews. Supported by a diverse set of social science disciplines, such as social work, public health, and education, the scholarship on Asian American psychology is likely to grow in the future. This is an exciting period in the history of Asian American psychology, and we look forward to the continued progression and advancement of the field.

Appendix

List of 2014 Reviewed Articles

1. Alam

2. Ali

3. Amin & Ingman

4. Anyon, Ong, & Whitaker

5. Appel, Ai, Huang, & Nicdao

6. Baker, Naai, Mitchell, & Trecker

7. Banerjee,Ostroff, D’Agostino, Bari, Khera, Acharya,… Gany

8. Bart, Lenz, Straka, & Brundage

9. Bear, Finer, Guo, & Lau

10. Becerra, von Ehrestein, Heck, Olsen, Arah, Jeste,…Ritz

11. Binder, Baker, Mayer, & O'Donnell

12. Blanco, Nydegger, Sakuma, Tong, White & Trinidad

13. Borenstein, Wu, Bowen, McCormick, Uomoto, McCurry,… Larson

14. Boyd, Corbin, & Fromme

15. Brice, Masia Warner, Okazaki, Ma, Sanchez, Esseling,… Lynch

16. Brocious

17. Browne, Mokuau, Ka’opua, Kim, Higuchi & Braun

18. Cachelin, Thompson, & Phimphasone

19. Campos, Ullman, Aguilera, & Dunkel Schetter

20. Carpenter-Aeby, Xiong, & Aeby

21. Cassel, Braun, Ka’opua, Soa, & Nigg

22. Chang, Yu, & Kahle

23. Chang, Yu, & Lin

24. Chao, Matthews, Yokoyama, Lai, Ong, Tse,… Rosen

25. Chatrung, Sorajjakool, & Amnatsatsue

26. A. C.-C. Chen, Szalacha, & Menon

27. S. H. Chen, Hua, Zhou, Tao, Lee, Ly,… Main

28. S. H. Chen, Zhou, Main, & Lee

29. S. H. Chen, Zhou, Uchikoshi, & Bunge

30. W.-T. Chen, Guthrie, Shiu, Yang, Weng, Wang,… Luu

31. Y. Chen, Li, Liu, & Shih

32. H.-L. Cheng

33. K. Cheng, Conley, & Ziegler

34. Chhuon

35. Chiang

36. Chihara, Hayes, Chock, Fuddy, Rosenberg, & Handler

37. H. Cho, Kim, & Velez-Ortiz

38. S. Cho, Park, Bernstein, Roh, & Jeon

39. N.-Y. Choi & Miller

40. Y. Choi, Tan, Yasui, & Pekelnicky

41. Chu, Chi, Chen, & Leino

42. H. Chung & Epstein

43. H. V. Chung, Iverson, Lai, Saka, ul Anwar, & Nigg

44. J. Y. Chung

45. Connor & Miller

46. Cooc & Gee

47. Cote & Bornstein

48. Covarrubias & Liou

49. Croce

50. Cui, Fitzgerald, & Donovan

51. D’Lima, Winsler, & Kitsantas

52. Dawson, Sotelo, Roesch, & Klonoff

53. de Guzman & Nishina

54. Devos & Yokoyama

55. Diamond & Woo

56. Dong, Chang, Wong, Wong, & Simon

57. Dubus

58. Duong, Schwartz, & McCarty

59. C. Y. Fang, Ross, Pathak, Godwin, & Tseng

60. L. Fang & Schinke

61. Festekjian, Tram, Murray, Sy, & Huynh

62. Fishman, Raval, Daga, & Raj

63. Foynes, Platt, Hall, & Freyd

64. Fradkin, Wallander, Yamakawa, Schwebel, Chien, Le,…Schuster

65. Francisco

66. Franzen-Castle & Smith

67. Fu & Markus

68. Gartner, Kiang, & Supple

69. Gibson, Losee, & Vitiello

70. Gross

71. Grubb & Bouffard

72. S. Guo, Kataoka, Bear, & Lau

73. Gupta, Rogers-Sirin, Okazaki, Ryce, & Sirin

74. Ha, Hums, & Greenwell

75. Hahm, Gonyea, Chiao, & Koritsanszky

76. Hamid, Dunsiger, Seiden, Nu’usolia, Tuitele,DePue,…McGarvey

77. Hampton & Sharp

78. H. Han, Glover, & Jeong

79. H.-R. Han, Huh, Kim, Kim, & Nguyen

80. Hasnain, Menon, Ferrans, & Szalacha

81. Hawley, Brown, Nu’usolia, Ah-Ching, Muasau-Howard,& McGarvey

82. Haworth, Margalit, Ross, Nepal, & Soliman

83. Hayes, Mitchell, Donohoe-Mather, Zaha, Melcher, & Fuddy

84. Helm, Okamoto, Kaliades, & Giroux

85. Henfield, Woo, Lin, & Rausch

86. Herzog, Murphy, Little, Suguitan, Pokhrel, &Kawamoto

87. Hodge, Sun, & Wolosin

88. Hong, Walton, Tamaki, & Sabin

89. Horng & Coles

90. Hsin & Xie

91. Hsu & Iwamoto

92. Huang, Calzada, Kamboukos, Rhule, Sharma, Cheng,…Brotman

93. Jisu Huh, Delorme, Reid, & Kim

94. Jimi Huh, Shin, Leventhal, Spruijt-Metz, Abramova, Cerrada,…Dunton

95. Jimi Huh, Thing, Abramova, Sami, & Unger

96. Hunt, Moloney, & Fazio

97. Huynh, Devos, & Goldberg

98. Ihara, Chae, Cummings, & Lee

99. Im, Chang, & Chee

100. Inouye, Matsuura, Li, Castro, & Leake

101. Iwasaki & Brown

102. Jang, Chiriboga, Molinari, Roh, Park, Kwon,… Cha

103. Jang, Roh, & Chiriboga

104. Javier, Supan, Lansang, Beyer, Kubicek, & Palinkas

105. Jensen & Dost-Gözkan

106. Jin & Liu

107. Jo & Bouffard

108. Juang & Syed

109. Juarez, Tan, Davis, & Mau

110. Jun, Ham, & Park

111. Juon, Lee, Strong, Rimal, Kirk, & Bowie

112. Kadi

113. Kalibatseva, Leong, & Ham

114. Kally, Cherry, Howland, & Villarruel

115. Kally, Cote, Gonzalez, Villarruel, Cherry, Howland,…Hepburn

116. Kan

117. H. Kang & Larson

118. H. S. Kang, Haddad, Chen, & Greenberger

119. Kantamneni

120. Kegel & DeBlaere

121. Keller & Brown

122. Kelly, Cotter, Tanofsky-Kraff, & Mazzeo

123. Khan

124. Kiang & Buchanan

125. B. J. Kim

126. B. J. Kim & Ahn

127. C. E. Kim & Pyun

128. E. Kim

129. E. Kim, Cain, Boutain, Chun, Kim, & Im

130. E. J. Kim, Berger, Kim, & Kim

131. G. Kim, Sellbom, & Ford

132. I. Kim

133. I. Kim, Kim, & Nochajski

134. J. Kim, Ahlgren, & Bernhard

135. J. E. Kim, Saw, Zane, & Murphy

136. J. H. J. Kim, Nagata, & Akiyama

137. J. M. Kim & López

138. K. E. Kim, Chandrasekar, & Lam

139. P. Y. Kim & Lee

140. S. S. Kim, Lee, Kiang, Kalman, & Ziedonis

141. S. Y. Kim, Shen, Huang, Wang, & Orozco-Lapray

142. S. Y. Kim, Wang, Chen, Shen, & Hou

143. S. Y. Kim, Wang, Weaver, Shen, Wu-Seibold, & Liu

144. Y.-H. Kim, Chiu, Cho, Au, & Kwak

145. K. A. King, Vidourek, & Singh

146. P. A. L. King & Pate

147. Kitayama, King, Yoon, Tompson, Huff, & Liberzon

148. Kitayama & Park

149. Koo, Nguyen, Gilmore, Blayney, & Kaysen

150. Kroon Van Diest, Tartakovsky, Stachon, Pettit, & Perez

151. Kue, Zukoski, Keon, & Thorburn

152. Kushins

153. C. M. L. Kwan, Mullan, Chun, Kwong, Hsu, & Chesla

154. P. P. Kwan, Briand, Lee, Lepule, Pang, Sabado,…Palmer

155. Kwon

156. Lagman, Yoo, Levine, Donnell, & Lim

157. Lam, Alvarado, & Lee

158. Lau, Wang, Fung, & Namikoshi

159. E. H. Lee, Zhou, Ly, Main, Tao, & Chen

160. E.-J. Lee, Chan, Ditchman, & Feigon

161. E.-J. Lee, Ditchman, Fong, Piper, & Feigon

162. H. Lee & Mason

163. H. B. Lee, Han, Huh, Kim, & Kim

164. H. Y. Lee, Yoon, Yoon, Kwon, Park, Nam,…& Park

165. J. Lee & Zhou

166. J. P. Lee, Lee, Hu, & Kim

167. J.-y. Lee

168. J.-y. Lee & Ciftci

169. J.-y. Lee & Pistole

170. K. H. Lee & GlenMaye

171. K. K. Lee, Yamada, Kim, & Dinh

172. L. O. Lee & Prescott

173. S. Lee, Choi, & Jung

174. S. Lee, Laiewski, & Choi

175. T. L. Lee, Wilton, & Kwan

176. Y. Lee, Malley-Morrison, Jang, & Watson

177. Y.-S. Lee, Kaplan, & Perez-Stable

178. Y.-S. Lee, Moon, & Gomez

179. Leng & Gany

180. Leung

181. Levy

182. C. Li

183. Y. Li

184. Liew, Kwok, Chang, Chang, & Yeh

185. Lim

186. S. Lin, Liu, & Jang

187. Y.-Y. Lin

188. Ling, Okazaki, Tu, & Kim

189. Liu, Jin, & Chen

190. Lo, Cheng, & Howell

191. Logan, Barksdale, & Chien

192. Lowinger, He, Lin, & Chang

193. Luczak, Yarnell, Prescott, Myers, Liang, & Wall

194. Lund, Chan, & Liang

195. Luo, Tamis-LeMonda, Kuchirko, F. Ng, & Liang

196. Ma, Desai, George, San Filippo, & Varon

197. Maramba & Palmer

198. Masuda, Le, & Cohen

199. Masuda, Mandavia, & Tully

200. Maxwell, Bastani, Glenn, Taylor, Nguyen, Stewart,…Chen

201. McArdle, Hamagami, Bautista, Onoye, Hishinuma, Prescott,…Johnson

202. McArdle, Hamagami, Chang, & Hishinuma

203. Menon, Szalacha, Prabhughate, & Kue

204. Meschke & Juang

205. Meschke & Peter

206. Mollica, Chernoff, Megan Berthold, Lavelle, Lyoo, & Renshaw

207. Momin, Chung, & Olson

208. Monnat

209. Mossakowski & Zhang

210. Mukherjea, Wackowski, Lee, & Delnevo

211. Murray, Klonoff, Garcini, Ullman, Wall, & Myers

212. Nadal, Wong, Sriken, Griffin, & Fujii-Doe

213. Nam

214. Nehl, Talley, Ong, Takahashi, Yu, Nakayama,…Wong

215. Nelson, Bishop, Sarapas, Kittles, & Shankman

216. Ngo, Gibbons, Scire, & Le

217. Nguyen & Belgrave

218. Nguyen & Clark

219. Nguyen, Clark, & Belgrave

220. A. L. Nguyen & Seal

221. C. M. Nguyen, Liu, Phan, Pittsinger, Casper, & Alt

222. D. Nguyen & Bornheimer

223. Niwa, Way, & Hughes

224. North, Gordon, Kim, Wallace, Smith, Pfefferbaum…Pollio

225. Ocampo

226. H. Y. Oh & DeVylder

227. K. M. Oh, Zhou, Kreps, & Kim

228. Okamoto, Helm, Pel, McClain, Hill, & Hayashida

229. Okamoto, Kulis, Helm, Edwards, & Giroux

230. Okamoto, Pel, Helm, & Valdez

231. Ona, Onoye, Goebert, Hishinuma, Bumanglag, Takeshita,…Fukuda

232. Pagano, Lee, & Sin

233. H. S. Park, Lee, Choi, Lee, Ahn, & Park

234. J. Park & Kitayama

235. S. K. Park, Stotts, Douglas, Donesky-Cuenco, & Carrieri-Kohlman

236. S.-Y. Park, Anastas, Shibusawa, & Nguyen

237. Y. Park, Wang, Kitahara, Moore, de Gonzalez, Bernstein,…Willett

238. Paul, Boylan, Gregorich, Ayala, & Choi

239. Pedersen, Marshall, Schell, Wong, Berthold, & Hambarsoomian

240. Pedersen & Paves

241. Pokhrel & Herzog

242. Pokhrel, Little, Fagan, Kawamoto, & Herzog

243. Pokhrel, Little, Fagan, Muranaka, & Herzog

244. Poon

245. Qi & Resnick

246. Qiao, Tinker, Olendzki, Hébert, Balasubramanian, Rosal,…Ma

247. Quinn, Rosen, McGeary, Amoa, Kranzler, Francazio,…Swift

248. Remigio-Baker, Hayes, & Reyes-Salvail

249. Roberts, Cha, & Kim

250. Robison, Clark, Eng, Wu, Raker, Clark,… Dizon

251. Ryu, Crespi, & Maxwell

252. Saito

253. Sakamoto & Spiers

254. Salud, Marshak, Natto, & Montgomery

255. Savage & Mezuk

256. Sentell, Zhang, Davis, Baker, & Braun

257. Seo, Chung, & Shumway

258. F. C. Shen, Liao, Abraham, & Weng

259. Y. Shen, Kim, Wang, & Chao

260. Shih, Wout, & Hambarchyan

261. Shin & Lach

262. Smart & Tsong

263. Son

264. Sparks

265. Stein, Kiang, Supple, & Gonzalez

266. Strayhorn

267. Strong, Ji, Liang, Ma, Brown, & Wang

268. Sudha

269. Suh, Barksdale, & Logan

270. F. Sun, Gao, Shen, & Burnette

271. F. Sun, Mutlu, & Coon

272. K. C.-Y. Sun

273. Suyemoto, Day, & Schwartz

274. Tiedje, Wieland, Meiers, Mohamed, Formea, Ridgeway,…Sia

275. Tokes, Quadri, Cahill, Chiu, Ivanov, & Tang

276. A. Tran, Lin, Nehl, Talley, Dunkle, & Wong

277. A. G. T. T. Tran & Lee

278. T. Tran, Allen, Nguyen, Lee, & Chan

279. T. V. Tran, T.-N. Nguyen, & K. Chan

280. T. V. Tran, T.-N. Nguyen, & K. T. Chan

281. Trinh, Ward, Day, Thomas, & Levin

282. Trinidad

283. Tsai, Lau, Niles, Coello, Lieberman, Ko,…Stanton

284. Tsang, Tsoh, Wong, Le, Cheng, Nguyen,…Burke

285. Tsuda

286. Tsunokai, McGrath, & Kavanagh

287. Tuason, Ancheta, & Battie

288. Uchikoshi

289. Vang & Her

290. Wang, Capous, Koh, & Hou

291. Weber, Hsu, & Sparks

292. Williams & Nigg

293. A. W.-m. Wong & Hall-Lew

294. Y. J. Wong, Kim, Nguyen, Cheng, & Saw

295. Y. J. Wong, Vaughan, Liu, & Chang

296. Y. J. Wong, Wang, & Maffini

297. Woo, Lee, & Hong

298. L.-T. Wu, Swartz, Brady, Blazer, & Hoyle

299. M.-H. Wu, Lee, & Leung

300. Y. Wu

301. Xu & Krieg

302. A. Yang

303. L. H. Yang, Chen, Sia, Lam, Lam, Ngo,…Good

304. L. H. Yang, Lai, Tu, Luo, Wonpat-Borja, Jackson,…Dixon

305. Yeh, Borrero, Lusheck, Plascencia, Kiliona, Mase,…Tito

306. Yeh, Liao, Ma, Shea, Okubo, Kim,…Atkins

307. Yeom & Fleury

308. Yep, Zhao, Wang, Pang, & Wang

309. Yeung & Johnston

310. G.-H. H. Yi & Bjorck

311. S. S. Yi, Ruff, Jung, & Waddell

312. Yoshihama, Blazevski, & Bybee

313. Yu, Warner, Haverly, & Lambert-Wacey

314. Zane & Ku

315. Zhao, Huh, Murphy, Chatterjee, & Baezconde-Garbanati

316. Zhou, Chen, Cookston, & Wolchik