© 2013 Cengage Learning

Outline  Types of Cross-Cultural Research  Method validation studies  Indigenous cultural studies  Cross-cultural comparisons  Types of Cross-Cultural Comparisons  Exploratory vs. hypothesis testing  Contextual factors  Structure vs. level oriented  Individual vs. ecological (cultural) level

Outline (cont'd.)  Designing Cross-Cultural Comparative Research  Getting the right research question  Designs that establish linkages between culture and individual mental processes and behaviors  Bias and equivalence  Conceptual bias  Method bias  Measurement bias  Response bias  Interpretational bias

T YPES OF C ROSS -C ULTURAL R ESEARCH

Method Validation Studies  Validity: how accurately does tool measure what it is supposed to measure?  Reliability: how consistent is measurement?  Cannot take scale or measure developed and validated in one culture and use it in another  Cross-cultural validation studies:  Tests equivalence of psychological measures  Important to conduct before cross-cultural comparisons

Indigenous Cultural Studies  Rich descriptions of complex theoretical models of culture  Predict and explain cultural differences  Psychological processes and behavior can be understood within cultural milieu  To understand behavior requires in-depth analysis of cultural systems  Roots in anthropology

Cross-Cultural Comparisons  Compare cultures on some psychological variable of interest  Serve as backbone of cross-cultural research  Most prevalent type of cross-cultural study  Different types of cross-cultural studies are prominent at different times  Own set of methodological issues have an impact on quality

T YPES OF C ROSS -C ULTURAL C OMPARISONS

Exploratory vs. Hypothesis Testing  Exploratory studies: examine existence of cross- cultural similarities and differences  Hypothesis-testing: examine why cultural differences may exist  Strength of exploratory studies: broad scope for identifying similarities and differences  Weakness of exploratory studies: limited capability to address causes of differences  Hypothesis-testing leads to more substantial contributions to theory development

Contextual Factors  Characteristics of participants or their cultures  Involves any variable that can explain observed cross-cultural differences  Enhances validity and helps rule out influence of biases and inequivalence  Evaluation of contextual factor influence can help to (dis)confirm their role in accounting for cultural differences observed  Hypothesis testing studies generally need to include contextual variables

Structure vs. Level Oriented  Structure: comparisons of constructs, structures, or relationships with other constructs  Level oriented: comparisons of scores  Structure-oriented studies focus on relationships among variables  Attempt to identify similarities and differences in these relations across cultures  Level-oriented studies ask whether people of different cultures have different mean levels of different variables

Individual vs. Ecological (Cultural) Level  Individual-level studies: individual participants provide data and are unit of analysis  Ecological- or cultural-level studies: countries or cultures are units of analysis  Most-well-known ecological-level study of culture is Hofstede's seminal work  Multi-level studies: use data from at least two levels  Statistical techniques examine relationship of data

D ESIGNING C ROSS -C ULTURAL C OMPARATIVE R ESEARCH

Getting the Right Research Question  Research design starts with comprehensive knowledge of literature  Understanding why study is to be conducted leads to questions about how to conduct it  Major challenge: how to isolate source of cultural differences  Identify active cultural (vs. noncultural) ingredients that produce those differences  Researchers need to pay attention to many theoretical and empirical issues

Designs that Establish Linkages between Culture and Individual Mental Processes and Behaviors  Unpackaging studies  Includes measurement of a variable  Assesses contents of culture thought to produce differences of the variable  Utilizes context variables  Individual-level measures of culture  Assess variable on individual level thought to be product of culture  Individualism versus collectivism

Designs that Establish Linkages between Culture and Individual Mental Processes and Behaviors (cont'd.)  Self-construal scales  Measures independence and interdependence on individual level  Personality  Cultural differences may be a product of different levels of personality traits in each culture  Cultural practices  Includes child-rearing practices, nature of interpersonal relationships, or cultural worldviews

Designs that Establish Linkages between Culture and Individual Mental Processes and Behaviors (cont'd.)  Experiments  Studies in which researchers create conditions to establish cause-effect relationships  Priming studies  Experimentally manipulating mindsets of participants and measuring resulting changes in behavior  Behavioral studies  Manipulations of environments and observation of changes in behavior as function of environments

B IAS AND E QUIVALENCE

Bias and Equivalence  Bias: differences that do not have exactly the same meaning within and across cultures  Equivalence: similarity in conceptual meaning and empirical method between cultures  Bias refers to a state of non-equivalence, and equivalence refers to a state of no bias  If bias exists in cross-cultural comparative study, comparison loses its meaning  Important to understand many aspects of studies that may be culturally biased

Method Bias  Sampling bias  Are samples appropriate representatives of culture?  Linguistic bias  Are research protocols semantically equivalent across languages?  Procedural bias  Are procedures, environments, and settings equivalent across cultures?

Measurement Bias  Degree to which measures used to collect data in different cultures are equally valid and reliable  Linguistic equivalence alone does not guarantee measurement equivalence  Different cultures may conceptually define a construct differently and/or measure it differently  Psychometric equivalence  Measurement equivalence is on a statistical level  Factor analysis  Creates groups of items on a questionnaire

Response Bias  Systematic tendency to respond in certain way to items or scales  If response biases exist, it is very difficult to compare data between cultures  Socially desirable responding: tendency to give answers that make oneself look good  Acquiescence bias: tendency to agree rather than disagree with items on questionnaires  Extreme response bias: tendency to use ends of scale regardless of item content

Response Bias (cont'd.)  Reference group effect: people make implicit social comparisons with others when making ratings on scales  In past, response biases viewed as methodological artifacts that need to be controlled  Today, growing view that response bias is important part of cultural influence on data

Interpretational Bias  Analyzing data  Researchers often use inferential statistics  Statistics compare differences observed between groups to differences occurring due to chance  “Proof by negation of the opposite“  In past, “statistically significant” results were interpreted as meaningful  Statistical differences between means does not give indication of meaningfulness

Dealing with Nonequivalent Data  Poortinga (1989):  Preclude comparison  Reduce the nonequivalence in the data  Interpret the nonequivalence  Ignore the nonequivalence

Interpreting Findings  Culture can bias ways researchers interpret their findings  Data from hypothesis-testing are correlational  Cultural attribution fallacies: claim that between- group differences are cultural without empirical justification  Linkage studies address this problem