ISSN 1671-3710
CN 11-4766/R

Advances in Psychological Science ›› 2023, Vol. 31 ›› Issue (2): 159-172.doi: 10.3724/SP.J.1042.2023.00159

• Research Method •     Next Articles

Examining societal change from the perspective of psychology: Research design and analytic techniques

CAI Huajian1,2(), ZHANG Mingyang3, BAO Han-Wu-Shuang1,2, ZHU Huijun1,2, YANG Ziyan1,2, CHENG Xi1,2, HUANG Zihang4, WANG Zixi1,2   

  1. 1CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
    2Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
    3School of Journalism and Communication, Tsinghua University, Beijing 100084, China
    4Centre for Mental Health Education, Chengdu University, Chengdu 611730, China
  • Received:2022-06-26 Online:2023-02-15 Published:2022-11-10
  • Contact: CAI Huajian


In recent years, impacts of societal changes on human culture and psychology have become a cutting-edge research area in cultural psychology. The research from the perspective of psychology mainly concerns psychological and behavioral changes as well as their potential drives, which often involves three kinds of effect, that is, age/maturation effect, period/time effect, and cohort/generation effect. Time effect refers to effects caused by socioecological changes in a certain period (e.g., the influences of modernization on Chinese people since 1980s). Age effect refers to development growth caused by individual maturation (e.g., developmental growth during a specific period). Cohort effect refers to effects associated with a specific born year (e.g., enduring effect of modernization on 1970 generation in China). Among these effects, time effect and cohort effect are related to socioecological change, whereas age effect usually constitutes a confounder.

In examining psychological changes as well as their drives, widely used research designs includes cross-time comparison, cross-generation comparison, and cross-region comparison (or historical reconstruction). By examining psychology and behaviors of people in different times, cross-time comparison allows researchers to infer how surveyed psychology and behaviors have changed with time. This examination usually involves cross-temporal analysis of published data, archive data and survey data. The survey data may be resulted from diverse designs, including cross-sequential design, longitudinal design, revolving panel design, total population design and retrospective panel design. These designs vary in difficulty of data collection.

Cross-generation comparison allows researchers to infer the changes of psychology and behaviors across time by examining differences across people born in different cohorts. The cohort can be decided based on special years (e.g., 1980s, 1990s and so on) or special events (e.g., China’s opening up and reform; China’s joining in WTO). In doing this, research can compare representative samples born in different cohorts. A special case is to compare grandparents, parents, and youngest generation within a family. Cross-generation comparison within a family also allows to examine similarities and dissimilarities of different generations.

Cross-regional comparison allows researchers to infer the changes of psychology and behavior by examining differences across regions at different modernization levels. A typical example is to infer psychological changes by comparing people from rural areas with those from urban areas. In this case, rural areas represent the past or tradition, whereas urbane areas represent current or modern time. Thus, rural-urban differences can be mapped onto tradition-modern differences.

In examining psychological changes as well as their drives, widely used data analysis methods includes classic correlation and regression analyses, and modern time series analysis. In exploring possible causal relationships, cross-lagged correlation analysis and Granger causal test are often used. In doing correlation and regression analysis, researchers usually use year or potential socioeconomic factors to predict targeted psychological outcomes, thereby inferring the psychological trends as well as their covariations with diverse socioecological factors. Cross-lagged correlation analysis allows us to infer the direction of the covariation. Granger causal test may provide further causality test while controlling for potential influences of autoregression. Vector autoregression has received increasing attention in recent years, which can be used to model multivariate time-series data. Despite salient advances in data analysis technique, how to decompose and estimate the age effect, period effect, and cohort effect is still a challenge. More studies are needed to tackle this issue.

In summary, we summarized the main research designs and data analysis techniques in studying culture, psychology, and behavior changes. It is notable that each design has specific pros and cons, researchers need to choose suitable design in terms of research question and data collection possibility. If possible, it is highly recommended to pursue convergent evidence by conducting multiple studies with diverse research designs.

Key words: social change, cultural change, time series analysis, Granger causality test, age effect, time effect, cohort effect

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