Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Longitudinal research could systematically capture the change of the target variable and thus is more convincing than cross-sectional research. It is popular in the fields of social sciences such as psychology, management, statistics, sociology, etc. The present study reviews the methodology study and model development for analyzing longitudinal data in China’s mainland. We aim to retrospect the methods used, the main research questions, and the popular research domains in longitudinal models. The target publications ranged from 1st Jan. 2001 to 31st Dec. 2020 in CNKI core collections in the relative domains, and finally, 75 articles met our selecting criterion. Results also indicated that the research topic widely includes latent growth model, multilevel modeling, autoregression, cross-lagged model, missing data, etc. Among these research topics, latent growth model ranked as the first. Typically, the latent growth model and experience sampling method were favored in the field of psychology. There are mainly four research questions retrieved from the publications. The first research question is to compare the mean difference, which is less popular. The second research question is to examine the reciprocal relationship between variables. It often uses the cross-lag model and the causal model to reveal the autoregressive and cross-lagged relationships within and between variables. The third research question is to depict growth trajectory with individual differences. It uses the latent growth model (LGM) and multilevel model (MLM) as the main methods to show a growth trajectory from the between-person perspective, as well as the individual difference included. The last one is to explore the dynamic changes. This research question does not focus on the general tendency of change but on the fluctuation between different time points. It usually uses autoregression with its extensions, MLM, time-varying effect model, and some newly developed models such as the dynamic structural equation model. The recent 20 years' publication broadens the domains of longitudinal models, such as the extension of the shape and pattern of growth, the combination of latent class analysis leading to growth mixture model and latent transition analysis. The causal effect, longitudinal mediation and moderation models are also introduced to reveal the relationship between variables. Meanwhile, models depicting growth trajectory with individual differences combines with models examining reciprocal relationships, thus they were extended and integrated to random intercept cross-lagged model, latent variable autoregressive latent trajectory, as well as general cross lagged model. Furthermore, research design becomes more complex; the intensive longitudinal data was introduced and thus the models were according developed, such as MLM, time-varying effect model, dynamic structural equation model, group iterative multiple model estimation, and so forth. Particularly, missing data issue is also hot discussed in the field. To summarize, methodology study for analyzing longitudinal data in China’s mainland has made fruitful development on the above topics and are in an advanced position all over the world. However, when comparing to the international scope, publications in China’s mainland are limited in narrow range. Many topics need to keep up with the international pace, which is a direction that Chinese scholars need to make efforts. Another future direction is to learn from other disciplines to promote the development of interdisciplinary.
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： When conducting the multivariate longitudinal studies, reciprocal relationship and latent trajectory are two of the focusing issues. The reciprocal relationship is often examined by a cross-lagged model that could build autoregressive influence and the multivariate influence between target variables, while the latent trajectory is usually defined by a latent growth model that explores the growth pattern simultaneously with individual difference. These two kinds of models are easily built under the SEM framework, at the same time could be flexibly combined by other research questions, such as the measurement error, the random factor, as well as the combination of the above issues. Such a combination yields a more complex model definition exploring the longitudinal relations, such as factor cross-lagged model, random-intercept cross-lagged model, trait-state-error model, autoregressive trajectory model, latent change score model, etc. In the study, we built a unified framework to analyze the above series of models according to the variance decomposition. First, the between-person difference was built by the latent trajectory often modeled as the latent growth. Second, the within-person difference was further decomposed as the within-person carry-over and the reciprocal relations between variables, which is the key question in the cross-lagged model series. Finally, the measurement error could be added to increase the measuring accuracy, where the trait-state-error model usually answers such a question. Since the research question of interest could be easily drawn from any above components, in summary, a “factor latent curve model with structured reciprocals” model was built as an extension and unified framework including all the components discussed above. We also used an empirical dataset to compare the above models. The data was driven from the Early Childhood Longitudinal Survey-Kindergarten (ECLS-K) project. There were 21,049 participants selected from 6 waves of measures from kindergarten to Grade 8. Reading and mathematics abilities IRT scores were used calibrated on the same scale. We first decided on the shape of the growth trajectory, where a series of alternative models indicated that the piecewise growth model best fit the data. Followed, longitudinal models suggested in our unified framework were adopted, i.e., (random intercept) cross-lagged model, trait-state-error model, latent growth model, (latent variable) autoregressive latent trajectory model, as well as (factor) latent curve model with structured residuals/reciprocals. Results indicated that the trait-state-error model best described the data. It showed that after controlling for the between-person difference (the trait factor—reading and mathematics ability), individually carry-over effects were significantly influential typically for students in the early elementary years. The significant reciprocal effect between reading and mathematics was also obtained showing these two domains of subjects influenced one another. Finally, we summarized how the results could be interpreted and offered suggestions on model selection for the researchers.
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Motivation is an important non-cognitive factor affecting students’ academic achievement. Despite motivation is generally considered conducive to learning, researchers have long recognized the necessity to differentiate various kinds of motivation in that not all of them are desirable. There is not much dispute on the benefits of intrinsic motivation on academic achievement. In contrast, extrinsic motivation which has been believed to be undesirable since the seventies, was considered more recently by some researchers to be positive and indispensable under certain circumstances. The present research postulated the "motivation continuum" to resolve the discrepancies from the two directions. In the first direction, the popular theories related to motivation were united under one grand theory. We used the motivation continuum based on the self-determination theory to connect different related theories, including, the interest theory, the goal theory, the expectancy-value theory, the self-worth theory, the reinforcement theory, the social cognitive theory. Each of these theories could help to explain one or more types of motivation on the continuum, from the intrinsic end to the extrinsic end. In the second direction, we summarized these theories and their applications by analyzing how the motivation structure influenced the outcomes. In brief, there are at least four main perspectives on the structure and effects of intrinsic and extrinsic motivation. Intrinsic and extrinsic motivations are antagonistic to the unidimensional structure believers in that intrinsic motivation enhances performance while extrinsic motivation reduces it. To those believing in a multiple-dimensional structure, these two motivations are additive in that both can facilitate performance and work independently. Recently, more complex structures have been proposed to integrate both the unidimensional and multiple-dimensional hypotheses. The third perspective is a semi-radex structure with a general factor reflecting all types of motivations and specific factors representing various sub-domains. This semi-radex structure leads to a bi-factor model: it extracts it extracts an autonomy element added to the controlling end of the “self-determination factor” while still allows each sub-domain to have a unique influence. In the fourth perspective, the multiplicative model postulates that the two types of motivation work interdependently in an interactive way in that the effect of extrinsic motivation would vary with the level of intrinsic motivation, and vice versa. In the present research, we summarized the pros and cons of different theories in the motivation continuum model. We also reviewed different perspectives of various motivational structure hypotheses and their corresponding applications. The motivation continuum could be extended and applied to different situations such as in the different measures and perspectives of motivation, different outcomes and their nuanced effects, and different contexts. For context, we have specific interest in the Chinese culture and its related research findings. As the structure of motivation remains topics of great concern, in-depth analyses on the structure of the motivation continuum would facilitate researchers’ application of different theories in the appropriate context.
Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： In our complex social environments, life situations are ever-changing. When dealing with these changes, there is no one-size-fits-all response or regulatory strategy suitable for all situations. Emotion regulation flexibility (ERF)—a framework for understanding individual differences in adaptive responding to ever-changing life contexts—emphasizes that individuals can flexibly deploy and adjust emotion regulation strategies according to specific characteristics of stressful situations in daily life. To achieve regulatory efficacy, it is important that one can utilize a balanced profile of ER strategies and select strategies that fit well with particular stressful situations. Specifically, using multiple ER strategies in daily life, rather than relying on only single-strategies, would indicate higher ERF. Additionally, based on leading models of strategy-situation fit, certain ER strategies are more appropriate for high versus low intensity stressful events. For instance, distraction involves with shielding oneself from negative stimuli and replacing them with irrelevant things, which may have a greater regulatory effect in high-intensity negative situations. Conversely, strategies such as reappraisal, which involves the processing of negative situations through deep cognitive change, may be more effective in lower-intensity negative situations and as a cornerstone of longer-term ER. We used the experience-sampling method (ESM) to quantify individual’s ERF; more specifically we assess participants for 1) having more or less balanced ER strategy profiles and 2) showing greater strategy-situation fit, in regard to the use of distraction versus reappraisal in the regulation of high-intensity versus low-intensity negative life events. To test the adaptive value of ERF on negative emotions and mental health, we investigated the influence of ERF on depressive and anxiety symptoms in two samples. We hypothesized that individuals with a more balanced profile of ER strategy use and a great level of strategy-situation fit would have higher levels of mental health, indicated by low levels of anxiety and depressive feelings. In sample 1, two hundred eight college students finished the ESM procedure (2859 beeps). Intensity of negative situations was measured by self-reported negative feelings for the time points where participants reported an adverse event. Simultaneously, we assessed participants’ use of two ER strategies (i.e., distraction and reappraisal). Considering the negative impact of COVID-19 on people’s daily life, we collected another sample (sample 2, 3462 beeps) with one hundred people who lived in Hubei Province, where Wuhan was in lockdown during the severe phase of COVID-19 (March 7-13, 2020). We measured intensity of negative situations (by averaging individuals’ negative feelings), as well as the use of two ER strategies at corresponding time points. After completing the ESM procedure, the participants were asked to fill out a series of emotional health questionnaires, including Beck Depression Inventory-II, Beck Anxiety Inventory and Spielberger State Anxiety Scale. Multilevel models were used to fit the covariation between the use of distraction versus reappraisal ER strategies and the intensity of negative events. Additionally, we used multiple level regression models to test whether high level of strategy-situation fit would result in lower negative feelings. To test whether a single-strategy preference would lead to higher levels of anxiety and depressive feelings compared to a multiple-strategy preference, latent profile analyses (LPA) was used. Results from the LPA indicated that individuals with preferences for rumination and express suppression reported higher levels depression and anxiety than individuals with a multi-strategy preference. In the multilevel models, results of the two independent samples both suggested individuals who were more inclined to use a higher level of distraction in response to high-intensity negative situations (e.g., adverse events or during COVID-19) and use higher levels of reappraisal during low-intensity situations (i.e., high level of ERF) reported lower levels of anxiety and depressive feelings. On the converse, individuals who tended to use more distraction in low intensity situations and more reappraisal in high intensity situations, (i.e., those showing lower ERF) reported a higher level of negative feelings. Together, our findings revealed a negative relationship between ERF and mental health problems in two samples, suggesting that having balanced ER profiles and flexibly deploying strategies in specific life contexts may have adaptive value in facilitating positive mental health. This work deepens our understanding of the interaction between ER strategies and situational demands, paving the way for future intervention research to help alleviate negative emotions associated with affective disorders or the experience of major traumatic events (such as epidemics, earthquakes, etc.).
Subjects: Psychology >> Cognitive Psychology submitted time 2022-08-01
Abstract： In our complex social environments, life situations are ever-changing. When dealing with these changes, there is no one-size-fits-all response or regulatory strategy suitable for all situations. Emotion regulation flexibility (ERF)—a framework for understanding individual differences in adaptive responding to ever-changing life contexts—emphasizes that individuals can flexibly deploy and adjust emotion regulation strategies according to specific characteristics of stressful situations in daily life. To achieve regulatory efficacy, it is important that one can utilize a balanced profile of ER strategies and select strategies that fit well with particular stressful situations. Specifically, using multiple ER strategies in daily life, rather than relying on only single-strategies, would indicate higher ERF. Additionally, based on leading models of strategy-situation fit, certain ER strategies are more appropriate for high versus low intensity stressful events. For instance, distraction involves with shielding oneself from negative stimuli and replacing them with irrelevant things, which may have a greater regulatory effect in high-intensity negative situations. Conversely, strategies such as reappraisal, which involves the processing of negative situations through deep cognitive change, may be more effective in lower-intensity negative situations and as a cornerstone of longer-term ER. We used the experience-sampling method (ESM) to quantify individual’s ERF; more specifically we assess participants for 1) having more or less balanced ER strategy profiles and 2) showing greater strategy-situation fit, in regard to the use of distraction versus reappraisal in the regulation of high-intensity versus low-intensity negative life events. To test the adaptive value of ERF on negative emotions and mental health, we investigated the influence of ERF on depressive and anxiety symptoms in two samples. We hypothesized that individuals with a more balanced profile of ER strategy use and a great level of strategy-situation fit would have higher levels of mental health, indicated by low levels of anxiety and depressive feelings. In sample 1, two hundred eight college students finished the ESM procedure (2859 beeps). Intensity of negative situations was measured by self-reported negative feelings for the time points where participants reported an adverse event. Simultaneously, we assessed participants’ use of two ER strategies (i.e., distraction and reappraisal). Considering the negative impact of COVID-19 on people’s daily life, we collected another sample (sample 2, 3462 beeps) with one hundred people who lived in Hubei Province, where Wuhan was in lockdown during the severe phase of COVID-19 (March 7-13, 2020). We measured intensity of negative situations (by averaging individuals’ negative feelings), as well as the use of two ER strategies at corresponding time points. After completing the ESM procedure, the participants were asked to fill out a series of emotional health questionnaires, including Beck Depression Inventory-II, Beck Anxiety Inventory and Spielberg State Anxiety Scale. Multilevel models were used to fit the covariation between the use of distraction versus reappraisal ER strategies and the intensity of negative events. Additionally, we used multiple level regression models to test whether high level of strategy-situation fit would result in lower negative feelings. To test whether a single-strategy preference would lead to higher levels of anxiety and depressive feelings compared to a multiple-strategy preference, latent profile analyses (LPA) was used. Results from the LPA indicated that individuals with preferences for rumination and express suppression reported higher levels depression and anxiety than individuals with a multi-strategy preference. In the multilevel models, results of the two independent samples both suggested individuals who were more inclined to use a higher level of distraction in response to high-intensity negative situations (e.g., adverse events or during COVID-19) and use higher levels of reappraisal during low-intensity situations (i.e., high level of ERF) reported lower levels of anxiety and depressive feelings. On the converse, individuals who tended to use more distraction in low intensity situations and more reappraisal in high intensity situations, (i.e., those showing lower ERF) reported a higher level of negative feelings. Together, our findings revealed a negative relationship between ERF and mental health problems in two samples, suggesting that having balanced ER profiles and flexibly deploying strategies in specific life contexts may have adaptive value in facilitating positive mental health. This work deepens our understanding of the interaction between ER strategies and situational demands, paving the way for future intervention research to help alleviate negative emotions associated with affective disorders or the experience of major traumatic events (such as epidemics, earthquakes, etc.).
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Statistics in Psychology submitted time 2021-04-30
Abstract： Abstract: When conducting the multivariate longitudinal studies, reciprocal relationship and latent trajectory are two of the focusing issues. These two issues could be flexibly combined by other research questions, such as the measurement error, the random factor, as well as the combination of the above topics. Such a combination yields a more complex model definition exploring the longitudinal relations, such as factor cross-lagged model, random-intercept cross-lagged model, trait-state-error model, autoregressive trajectory model, etc. In the study, a factor latent curve model with structured reciprocals model was built as an extension and unified framework including all the components discussed above. The empirical dataset, Early Childhood Longitudinal Survey-Kindergarten (ECLS-K), was used as an illustrating example. Results indicated that the trait-state-error model best described the data. Finally, we summarized how the results could be interpreted and offered suggestions on model selection for the researchers. "
Peer Review Status:Awaiting Review
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