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Does Interest Fit Between Student and Study Program Lead to Better Outcomes? A Meta-Analysis of Vocational Interest Congruence as Predictor for Academic Success
... This is reinforced by the results of interviews with chemistry subject teachers, who stated that most students experience difficulties in understanding chemistry calculations, Such as stoichiometry, redox, reaction rates, mole concept, Kinetics, Thermodynamics, Acid-Base and pH. Vries et al., (2024) research reveals that interest is a positive predictor of academic achievement, persistence in subjects, and satisfaction with study outcomes. The interest in learning also affects the difficulties students face in mastering chemistry material. ...
Chemistry is often considered a difficult subject for learners due to its abstract concepts and complex terminology. This can lead to difficulties in understanding the material and a decrease in students' interest in studying chemistry. The aim of this research is to describe and explain the factors of difficulty understanding in solving chemistry material experienced by students. The research method used is descriptive qualitative. The results show that 62.3% of students experience slight difficulty and 37.7% experience moderate difficulty in understanding chemistry material. The interest in learning chemistry of class XII MIA students is categorized as sufficient with a percentage of 46.68%. Factors causing difficulties in understanding chemistry material include a lack of understanding of mathematical concepts, the predominance of lecture methods, limited learning media, and the suboptimal use of chemistry laboratories. The conclusion of this research provides an overview that the factors causing difficulties in understanding chemistry material affect students' interest in learning. Therefore, these findings can be used as evaluation material to improve the quality of chemistry education in schools.
According to the congruence hypothesis, job and study satisfaction will be higher when individual interests and the respective environment (both conceptualised according to Holland’s RIASEC model) are congruent. As our target group were teacher students, all participants who did not intend to become a teacher or did not meet other inclusion criteria (e.g., no missing data on relevant variables) were removed from the sample, resulting in a final sample of N = 1171. Teacher students completed questionnaires on their vocational interests and their satisfaction with course content. To obtain an assessment of the environment (study majors), N = 166 lecturers were asked to rate their courses with respect to Holland’s RIASEC model. As previous findings have indicated that conclusions are influenced by the congruence measure that is used, we applied two different approaches. First, we computed the profile correlation between the individual interest profile and the environmental profile for each individual to measure congruence. Profile correlation scores were then correlated with satisfaction with course content scores. This correlation was significant ( r = .21, p < .001), offering support for the congruence hypothesis. Second, Response Surface Analysis (RSA) was used to predict satisfaction with course content scores from the individual interest and environmental assessment variables and their interaction separately for each interest dimension. Results showed that the relationships between these three constructs were complex, but evidence for the congruence hypothesis could not be found. This makes this study the first study to investigate this hypothesis using RSA methodology.
Grounding on Holland’s RIASEC model of vocational interests and the respective assumptions on person-environment fit (congruence), this paper focuses on how congruence is related to study outcomes, especially students’ persistence, performance, and satisfaction. The paper distinguishes the measure of congruence with respect to social congruence (SOC) (interest fit with the study mates) and aspirational congruence (ASP) (interest fit with the occupation aspired) and also distinguishes the effects of congruence for gender and six different study areas including Science, Technology, Engineering, Mathematics (STEM), medicine, economics, education, and languages. The paper analyses 10,226 university freshmen of the German National Educational Panel Study (NEPS) and follows them longitudinally with respect to their study outcomes. The results show that students’ persistence was more related to SOC than to ASP, especially for male students. Furthermore, SOC was particularly important for students in STEM areas. Regarding performance, however, ASP was more important. Here, we notably found correlations for STEM subjects with a balanced proportion of female students. Regarding satisfaction, mainly marginal correlations could be found. The results indicate conceptual differences between social and aspirational congruence as well as specific effects for gender and study area. While research might take this into account by specifically developing their models for different study areas, career counseling may reflect on the different significance of the interest-based person-environment fit for different study areas. Initiatives for raising young people’s participation in STEM should therefore specifically focus on students that have high chances to develop interest profiles that are congruent to STEM rather than students who show profiles which already indicate a low congruence.
Interest inventories are widely used for career and organizational decision-making. Though it is widely assumed that interest fit predicts job satisfaction, previous meta-analyses reported non- significant relations between interest fit and job satisfaction. However, past meta-analyses were limited by several critical issues, including low statistical power and inconsistent inclusion criteria. In this updated meta-analysis, we systematically reviewed the link between interest fit and job satisfaction across 105 studies (k = 194, N = 39,602). Results revealed a statistically significant, positive relation between interest fit and overall job satisfaction that was slightly lower than expected (ρ = .19, [95% CI: .16, .21]). Yet moderation analyses revealed the strength of the relation was notably stronger for satisfaction facets capturing how people evaluate their career choice in general. Overall, these results suggest a need to reconceptualize the applied importance of vocational interests. Although we report clear evidence that interest fit predicts job satisfaction, interest fit is more strongly related to performance outcomes and satisfaction with one’s overall career path. We conclude by presenting a series of recommendations for improving the use of interest assessments in career and organizational settings.
In ecological meta‐analyses, nonindependence among observed effect sizes from the same source paper is common. If not accounted for, nonindependence can seriously undermine inferences. We compared the performance of four meta‐analysis methods that attempt to address such nonindependence and the standard random‐effect model that ignores nonindependence. We simulated data with various types of within‐paper nonindependence, and assessed the standard deviation of the estimated mean effect size and Type I error rate of each method. Although all four methods performed substantially better than the standard random‐effects model that assumes independence, there were differences in performance among the methods. A two‐step method that first summarizes the multiple observed effect sizes per paper using a weighted mean and then analyzes the reduced data in a standard random‐effects model, and a robust variance estimation method performed consistently well. A hierarchical model with both random paper and study effects gave precise estimates but had a higher Type I error rates, possibly reflecting limitations of currently available meta‐analysis software. Overall, we advocate the use of the two‐step method with a weighted paper mean and the robust variance estimation method as reliable ways to handle within‐paper nonindependence in ecological meta‐analyses.
Vocational interests have a rich history throughout the last century of psychological research, playing an influential role in fields such as personality, development, education, counseling, and organizational psychology. Yet interest measures are typically developed with the goal of matching people to careers, and there has never been a quantitative review of interests and career choice. The present meta-analysis examines the validity of interest inventories for predicting educational choices and occupational membership. This analysis of predictive hit rates incorporates almost 100 years of research investigating the accuracy of interest inventories. Using a binomial-normal meta-analytic model, the present analysis found that measured interests attain an estimated overall hit rate of 50.8% for predicting career choice. Because of the vast amount of career choice possibilities, this effect size conveys a significant degree of predictive accuracy. We also tested several potential moderators to address historical debates surrounding interest measurement. In particular, accuracy was moderated by year of publication, interest inventory, type of interest inventory scale, type of career choice outcome, and hit rate calculation method. Finally, the present study reintroduces base rates into the evaluation of predictive accuracy. We demonstrate the importance of taking base rates into account by comparing interest category hit rates and employment rates within those categories. Overall, the results of this study demonstrate that interest inventories possess considerable validity for predicting career choice, supporting their use in research, education, and work contexts. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Despite a major increase in the range and number of software offerings now available to help researchers produce evidence syntheses, there is currently no generic tool for producing figures to display and explore the risk‐of‐bias assessments that routinely take place as part of systematic review. However, tools such as the R programming environment and Shiny (an R package for building interactive web apps) have made it straightforward to produce new tools to help in producing evidence syntheses. We present a new tool, robvis (Risk‐Of‐Bias VISualization), available as an R package and web app, which facilitates rapid production of publication‐quality risk‐of‐bias assessment figures. We present a timeline of the tool’s development and its key functionality.
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Holland’s theory of vocational choice is a powerful framework for studying academic environments and student development in college. This study tests Holland’s third proposition that students flourish in academic environments (i.e., majors) that are congruent with their personality types. In addition, we examine the extent to which student characteristics influence person-environment fit. Findings indicated that student characteristics and personality type were significantly related to person-environment fit. Moreover, person-environment fit is positively related to self-reported grades. However, person-environment was not significantly related to either perceived learning gains or satisfaction with college.
This study aimed at developing and validating a new instrument to facilitate late adolescents and young adults to choose a higher education major. For the main study, the sample consisted of 6,215 late adolescents and young adults ( M age = 19.50, SD = 1.89, 42.3% female). After rational scale construction based on the RIASEC model of Holland (1997) , several statistical analyses were conducted. In four studies, structural validity, internal consistency, and construct validity were examined. Our analyses showed that adequate structural validity, internal consistency, and construct validity were established. A 7-factor structure was found, in which the investigative domain split into two subscales. The overall results suggested that the new instrument is reliable and valid as an orientation instrument in applied settings in secondary and higher education.
Each student faces the challenge of choosing a study program that matches his or her vocational interest. A good person-environment fit (PE fit) between student and study program influences study success and persistence, prerequisites to obtaining the desired degree. But which criterion should be used when presenting advice sets of study options to orient students toward study programs that match their vocational interests? And how long should such a list of study options be? Moving beyond existing, non-evidence-based approaches, present study sets out to develop an empirical advice set engine (EASE) to optimize the process of matching future students to fitting study options. Compared to existing, non-evidence-based alternatives, EASE shows a better balance between the number and PE fit of the options presented. EASE may be a promising way to rethink how student PE fit information can be used in student orientation and higher education research.
The extent to which a good person-environment (PE) interest fit between student and study program leads to better study results in higher education is an ongoing debate wherein the role of the study program environment has remained inadequately studied. Unanswered questions include: how diverse study programs are in the interests of their student populations, and how this program interest diversity influences study results, in comparison to individual PE fit? The present study addressed these questions in students (N = 4,635) enrolled in open-access university education. In such an open access system, students are allowed to make study choices without prior limitations based on previous achievement or high stakes testing. Starting from the homogeneity assumption applied to this open access setting, we propose several hypotheses regarding program interest diversity, motivation, student-program interest fit, and study results. Furthermore, we applied a method of measuring interest diversity based on an existing measure of correlational person-environment fit. Results indicated that interest diversity in an open access study environment was low across study programs. Results also showed the variance present in program interest diversity was linked to autonomous and controlled motivation in the programs’ student populations. Finally, program interest diversity better explained study results than individual student fit with their program of choice. Indeed, program interest diversity explained up to 44% of the variance in the average program’s study results while individual student-program fit hardly predicted study success at all. Educational policy makers should therefore be aware of the importance of both interest fit and interest diversity during the process of study orientation.
The relation between the degree of interest congruence (i.e., person–environment fit in interest domain) and career satisfaction has been inconsistent and generally low across studies. Interest congruence is typically measured at the broadband general interest level, bound within Holland’s Realistic, Investigative, Artistic, Social, Enterprising, and Conventional (RIASEC) framework, and largely based on the match of the high-point interest codes between persons and environments. Using two cross-cultural college samples, we reexamined the congruence–satisfaction relation with a refined congruence index by using narrowband basic interest measures and considering the entire basic interest profiles. As a comparison, we used three additional congruence indices based on the entire general interest RIASEC profiles or the high-point RIASEC codes. Findings showed stronger congruence–satisfaction relations when the basic interest measure and/or complete interest profiles were used to generate interest congruence indices. Implications for research and career practice are discussed.
The main objective of the present study was to explore the role of the forces in the context external to the setting of a specific vocational setting (i.e., an academic major in a university) in the congruence–satisfaction relationship. Four hundred and fifty-three Chinese university students responded to the Career Personality Styles Inventory, the revised Contextual Supports and Barriers Scale, and the Academic Major Satisfaction Scale. Results indicated that the congruence between individual vocational interests and their academic majors (for brevity, congruence) and two types of external forces (external barriers and support from social relations) were significant predictors of students’ satisfaction with their academic majors. In comparison, the predictive power of external forces for students’ satisfaction with their academic majors was far beyond that of congruence. Moreover, external barriers were a marginally significant moderator in the relationship between congruence and satisfaction. Implications and limitations of the findings are discussed.
Background
Systematic reviews (SRs) are an important source of information about healthcare interventions. A key component of a well-conducted SR is a comprehensive literature search. There is limited evidence on the contribution of non-English reports, unpublished studies, and dissertations and their impact on results of meta-analyses. Methods
Our sample included SRs from three Cochrane Review Groups: Acute Respiratory Infections (ARI), Infectious Diseases (ID), Developmental Psychosocial and Learning Problems (DPLP) (n = 129). Outcomes included: 1) proportion of reviews that searched for and included each study type; 2) proportion of relevant studies represented by each study type; and 3) impact on results and conclusions of the primary meta-analysis for each study type. ResultsMost SRs searched for non-English studies; however, these were included in only 12% of reviews and represented less than 5% of included studies. There was a change in results in only four reviews (total sample = 129); in two cases the change did not have an impact on the statistical or clinical significance of results. Most SRs searched for unpublished studies but the majority did not include these (only 6%) and they represented 2% of included studies. In most cases the impact of including unpublished studies was small; a substantial impact was observed in one case that relied solely on unpublished data. Few reviews in ARI (9%) and ID (3%) searched for dissertations compared to 65% in DPLP. Overall, dissertations were included in only nine SRs and represented less than 2% of included studies. In the majority of cases the change in results was negligible or small; in the case where a large change was noted, the estimate was more conservative without dissertations. Conclusions
The majority of SRs searched for non-English and unpublished studies; however, these represented a small proportion of included studies and rarely impacted the results and conclusions of the review. Inclusion of these study types may have an impact in situations where there are few relevant studies, or where there are questionable vested interests in the published literature. We found substantial variation in whether SRs searched for dissertations; in most reviews that included dissertations, these had little impact on results.
This study investigates three methods to handle dependency among effect size estimates in meta-analysis arising from studies reporting multiple outcome measures taken on the same sample. The three-level approach is compared with the method of robust variance estimation, and with averaging effects within studies. A simulation study is performed, and the fixed and random effect estimates of the three methods are compared with each other. Both the robust variance estimation and three-level approach result in unbiased estimates of the fixed effects, corresponding standard errors and variances. Averaging effect sizes results in overestimated standard errors when the effect sizes within studies are truly independent. Although the robust variance and three-level approach are more complicated to use, they have the advantage that they do not require an estimate of the correlation between outcomes, and they still result in unbiased parameter estimates.
A new, Holland-based Interest Inventory is proposed, intended to facilitate the transition from secondary to tertiary education. Specific interest items were designed to grasp activities that are prevalent during tertiary studies, including an Academic-track-scale to assist in the choice between academic and vocational-oriented programs. Interest profile descriptions are complemented by a list of matching study programs. Data from 3,962 students were analyzed to evaluate the underlying circumplex structure, the criterion validity of the Academic-track-scale and the study program RIASEC codes. It is concluded that the assessment and feedback tools are promising instruments to facilitate the transition to tertiary education.
Despite their significance to both individuals and organizations, interests are often misunderstood, and their predictive power is often overlooked. In this article, we discuss the nature of interests, describe several key features of interests, and, contrary to the received knowledge of many, explain how interests can be used to predict career and educational choice, performance, and success. Finally, we discuss the continuity of interests across the life span and explain how evidence of stability supports conceptualizations of interests as being distinct dispositions rather than simply extensions or workplace instantiations of basic personality traits.
Using an expanded person-environment fit (P-E fit) model, we conducted 2 studies to test the combined effects of 2 individual difference factors, ability-demand fit and interest-vocation fit, in predicting college student choice of and persistence in the science, technology, engineering, and mathematics (STEM) fields. Analysis results based on data from 207,093 students entering 51 postsecondary institutions supported the hypothesized roles that academic ability and interest fit play in determining STEM field choice and persistence. Ability was found to moderate the effects of interest fit on the behavioral outcomes, thus expanding the P-E fit framework. We also found that gender moderates the effects of these individual difference predictors, such that the effects are weaker for females than for males in predicting STEM choice. For STEM persistence, the opposite effect was found: The relationship between ability and persistence is stronger for females than it is for males. As such, this research contributes to the resurging attention in the roles that individual difference factors play in organizational and educational research and the importance of integrating ability and interest constructs to fully understand college and career choice and persistence behaviors. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
A dozen literary reviews and two meta-analyses of congruence research, operationally defined using John Holland's (1959) theory, continue to reveal a mixture of significant and nonsignificant relations between congruence and a variety of work-related behaviors. Congruenceappears to be a sufficient, though not a necessary, condition for job satisfaction with correlations in the .25 range (5% of variance). Repeated and sometimes trenchant criticismof the design, methodology, and analyses employed in previous studies of congruencehas produced an improved array of research designs, including more longitudinal,moderator, and multidimensional designs, yet results using these designs have donelittle to clarify the central issues in the congruence model. The present review examines 66 published congruence studies from 1985 to 1999. Benchmark studies with improved methodologies are described. A paradigmatic shift in the next generation of congruenceresearch is recommended, with continued improvement and diversification of design and methodology drawing more heavily from person–environment psychology as well as a change in emphasis from correlational to experimental designs.
Despite early claims that vocational interests could be used to distinguish successful workers and superior students from their peers, interest measures are generally ignored in the employee selection literature. Nevertheless, theoretical descriptions of vocational interests from vocational and educational psychology have proposed that interest constructs should be related to performance and persistence in work and academic settings. Moreover, on the basis of Holland's (1959, 1997) theoretical predictions, congruence indices, which quantify the degree of similarity or person-environment fit between individuals and their occupations, should be more strongly related to performance than interest scores alone. Using a comprehensive review of the interest literature that spans more than 60 years of research, a meta-analysis was conducted to examine the veracity of these claims. A literature search identified 60 studies and approximately 568 correlations that addressed the relationship between interests and performance. Results showed that interests are indeed related to performance and persistence in work and academic contexts. In addition, the correlations between congruence indices and performance were stronger than for interest scores alone. Thus, consistent with interest theory, the fit between individuals and their environment was more predictive of performance than interest alone.
© The Author(s) 2012.
Holland's (1985a) typology of persons and environments is outlined, and support for the theory as an explanation of stability and change in careers and work satisfaction is summarized. Studies show that people flourish in their work environment when there is a good fit between their personality type and the characteristics of the environment. Lack of congruence between personality and environment leads to dissatisfaction, unstable career paths, and lowered performance. The results of recent research designed to strengthen the explanatory power of Hollands's typology and link it to the Big Five personality factors is described. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
A theory of vocational choice is presented "in terms of the occupational environments, the person and his development, and the interactions of the person and the vocational environment." Research problems stemming from this theory are suggested and discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Polynomial regression is a proven method to calculate person-environment (PE) interest fit between the RIASEC (realistic, investigative, artistic, social, enterprising and conventional) interests of a student and the RIASEC profile of a study program. The method has shown much larger effects of PE interest fit on academic achievement than earlier approaches in literature. However, the polynomial regression method in its current form only focuses on establishing the regressed interest fit (RIF) of a population of students with their study environments, in order to observe how large the general impact of PE interest fit can become on academic achievement. The present study (N = 4407 across n = 22 study programs) further validates this method towards new applications by theoretically deriving two measures of RIF that only affect a single environment like a study program. Analyses show that the use of RIF for a single study environment results in an even stronger positive relation between PE interest fit and academic achievement of r = 0.36, compared to r = 0.25 for the original polynomial regression method. Analyses also show that RIF for one environment can be used to generate interpretable and reliable RIASEC environment profiles. In sum, RIF for a single (study) environment is a promising operationalization of PE interest fit which facilitate both empirical research as well as the practical application of interest fit in counseling settings.
Student fail rates in the first year of open access academic higher education can become dramatically high. The present study in Flanders, Belgium examines how performance on program-specific basic skillsets can identify students at risk at the start of their curriculum in 21 bachelor programs (N = 6,624), months before actually failing their exams or dropping out. Results identify up to 58% of the students prone to failure at relatively lower error rates while still adhering to the principles of higher education equity. In practice, institutions and counselors can use the methodology of this study to identify at-risk students and offer them reorientation and remediation trajectories, preventing failure. Future applications towards more restricted or selective international education systems are discussed.
The statistical synthesis of quantitative effects within primary studies via meta-analysis is an important analytical technique in the scientific toolkit of modern researchers. As with any scientific method or technique, knowledge of the weaknesses that might render findings limited or potentially erroneous as well as strategies by which to mitigate these biases is essential for high-quality scientific evidence. In this paper, we focus on one prevalent consideration for meta-analytical investigations, namely dependency among effects. We provide readers with a non-technical introduction to and overview of statistical solutions for handling dependent effects for their efforts to integrate evidence within primary studies. This goal is achieved via a series of seven reflective questions that scholars might consider when planning and executing a meta-analysis in which some degree of dependency among effect sizes from primary studies may exist. We also provide an example application of the recommendations with real-world data, including an analytical script that readers can adapt for their own purposes.
This chapter shows how the multiple regression used in primary studies can be applied to meta‐regression. It begins with the fixed‐effect model, which is simpler, and then moves on to the random‐effects model, which is generally more appropriate. Since the meaning of a summary effect size is different for fixed versus random effects, the null hypothesis being tested also differs. Both test a null hypothesis of no linear relationship between the covariates and the effect size. Under the random‐effects model that effect size is the mean of the true effect sizes for all studies with a given value of the covariates. If there is heterogeneity in true effects that is not explained by the covariates, then the random‐effects model is likely to be more appropriate.
Theory and research suggest that vocational interests should predict individual behavior at work, in school, and during leisure time. However, more research is needed to understand the underlying mechanisms for these relationships. In the present study, we suggest that satisfaction and motivation are direct outcomes of vocational interest fit and mediate the relationship between interest fit and behavior. We test this mediation model in a seven-week longitudinal study examining the prediction of academic performance in a sample of 372 college students. Results indicated that vocational interest fit had direct effects on performance, citizenship behavior, counterproductive behavior, and intent to leave even after controlling for cognitive ability and conscientiousness. Both motivation and satisfaction also mediated the relationships with several of these outcomes. Finally, results also showed that an objective measure of interest fit was a better predictor of performance while a perceived fit measure was a stronger predictor of satisfaction. These results suggest that vocational interest fit may be useful for identifying individuals who are likely to be successful in school and help to clarify several of the underlying mechanisms for this relationship.
The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
Although interest congruence is a cornerstone of career counseling, little is known about the relative importance of different operationalization approaches to interest congruence (i.e., how to calculate interest congruence). Using a sample of U.S. employees ( n = 303), the current study comparatively examined four profile-based conceptual congruence approaches, namely Euclidean distance, angular agreement, profile deviance, and profile correlation, in terms of their predictions for job and life satisfaction, turnover intention, and perceived person–job fit. The results found that profile correlation demonstrated complete dominance (i.e., ubiquitously stronger predictive utility) over the other three congruence indices in predicting all four career outcomes. Therefore, the current study portrays profile correlation as a preferred operationalization approach to interest congruence and offers rich implications for congruence research and practice.
This study explored whether and to what extent vocational personality types based
on Holland (1994) correlate with and explain unique variance of academic success
among 117 undergraduate civil engineering students by using the Self-Directed
Search–Form R, 4th Edition. Findings indicated that the majority of participants’
1st-letter code was Realistic (39.3%), 2nd-letter code was Investigative (24.8%),
and 3rd-letter code was Social (21.4%), compared with Holland’s 3-letter codes for
civil engineering (Investigative, Realistic, Enterprising). The study also calculated
the degree of congruence between personality type and occupational environment.
For career counselors, the findings underscore the importance of using congruence
scores to predict engineering students’ academic performance.
The revised edition of the Handbook offers the only guide on how to conduct, report and maintain a Cochrane Review ? The second edition of The Cochrane Handbook for Systematic Reviews of Interventions contains essential guidance for preparing and maintaining Cochrane Reviews of the effects of health interventions. Designed to be an accessible resource, the Handbook will also be of interest to anyone undertaking systematic reviews of interventions outside Cochrane, and many of the principles and methods presented are appropriate for systematic reviews addressing research questions other than effects of interventions. This fully updated edition contains extensive new material on systematic review methods addressing a wide-range of topics including network meta-analysis, equity, complex interventions, narrative synthesis, and automation. Also new to this edition, integrated throughout the Handbook, is the set of standards Cochrane expects its reviews to meet. Written for review authors, editors, trainers and others with an interest in Cochrane Reviews, the second edition of The Cochrane Handbook for Systematic Reviews of Interventions continues to offer an invaluable resource for understanding the role of systematic reviews, critically appraising health research studies and conducting reviews.
Over the past four decades, psychometric meta-analysis (PMA) has emerged a key way that psychological disciplines build cumulative scientific knowledge. Despite the importance and popularity of PMA, software implementing the method has tended to be closed-source, inflexible, limited in terms of the psychometric corrections available, cumbersome to use for complex analyses, and/or costly. To overcome these limitations, we created the psychmeta R package: a free, open-source, comprehensive program for PMA.
Recent meta-analyses indicated that interest congruence can predict performance both at work and in school. Given these findings, the exclusion of interests from predictive models of performance has several potential consequences. In this study, we demonstrate that excluding vocational interests from models of performance has implications for the validity of the model as well as for understanding predictive bias in selection testing. Using a sample of 1449 students from a large university, we examined the validity and incremental validity of vocational interests for predicting academic performance above and beyond ACT scores, high school GPA, and other noncognitive predictors. Building on recent research, we also demonstrate that including vocational interests in the prediction model eliminates the predictive bias observed for ACT and HSGPA across men and women but not across racial/ethnic subgroups. The implications of these results for understanding performance and future research needs in the area of vocational interests are discussed.
The current study sought to determine if student employment was a significant moderator of the relationship between congruence with college major, academic major satisfaction, and academic major success. Correlation results suggested that student employment has a negative relationship with academic success as measured by grade point average. No study hypotheses were supported but regression analyses showed significant impact of cognitive influences on academic major satisfaction and academic major success. Clinicians are encouraged to aid students in planning the relationship between required work and educational responsibilities, as well as consider implications of negative career thinking on academic satisfaction and success.
Decisions regarding college majors have the potential to affect a person's overall academic performance and long-term career success. With Holland's () trait-and-factor theory serving as a foundation, the authors examined relationships between person–environment fit, college major satisfaction, and grade point average of undergraduate students (N = 99). Results revealed that student–major congruence and academic major satisfaction were both significant predictors of grade point average. © 2017 by the American Counseling Association. All rights reserved.
Recently, there has been a growing interest in the study and use of vocational interests for predicting workplace behavior. The renewed attention to this topic is at least partially due to two recent meta-analyses (Nye, Su, Rounds, & Drasgow, 2012; Van Iddekinge, Roth, Putka, & Lanivich, 2011a) demonstrating the validity of interests for predicting job performance. Both studies came to the conclusion that interests predict performance but their results differed with respect to the validity of interest congruence. Although the congruence (or match) between an individual's interests and his or her work is particularly important for theories of vocational interest, there is some debate in the literature about the validity and utility of interest congruence for predicting work outcomes and the varying results reported in the two recent meta-analyses do little to resolve this issue. Therefore, the goal of the present study was to address these differences and the broader debate about interest congruence by conducting a more comprehensive meta-analysis of the validity of interest congruence for predicting job performance. An analysis of 92 studies and 1858 correlations suggested that interest congruence is a stronger predictor of performance outcomes than interest scores alone, with baseline correlations of 0.32 and 0.16, respectively. These results are discussed in the context of the broader person-environment fit literature and the implications for the interest literature and personnel selection research are discussed.
Various factors have shown to relate to different forms of career commitment (i.e., affective, continuance, and normative commitment). Commitment has been associated with intent to remain within a profession or organization, suggesting that commitment is an important component of career retention. Correspondingly, commitment to one’s academic major may also provide information about university retention. The current study examined fit (e.g., objective and subjective), attitudes (e.g., organizational commitment, satisfaction, involvement, and intention to quit), and demographic (e.g., semesters in major) factors that have been previously related to career commitment to investigate the construct of major commitment of undergraduate students (N = 303). Using canonical correlation analysis, several significant relationships were found with approximately 69% and 67% of the shared variance between the three forms of major commitment and other variables for Black and White students, respectively, being explained.
Understanding the degree to which students’ interests and achievement fit with educational environmental rewards and requirements can help universities retain students, while assisting students in finding fulfilling academic majors and careers. We examined the effect of various interest-major congruence indices and American College Testing (ACT) achievement indicators on biology and chemistry students’ success and retention using archival university data from a Historically Black College/University. Results indicated that the specific congruence index utilized alters the statistical impact of achievement indicators on retention and success. Additionally, while the predictors of success and retention differed between biology and chemistry majors, math and English ACT scores impacted success and retention for both biology and chemistry majors, highlighting the utility of assessing skill areas beyond math for students majoring in both biology and chemistry. Career counselors and advisors should consider students’ majors and the utility of exploration tools when providing guidance to college students.
There is a growing interest in policy research on student completion and non-continuation and bodies such as the European Commission and OECD are focusing on the subject. There is also increasing national interest in the issue in many countries and they are looking to each other for input on effective policies. However, there are significant social, economic and educational differences between national systems across Europe, making this a very challenging project. The aim of this article is to study challenges and complexities in researching student non-completion of higher educqtion programmes in Europe. We use the case of two contrasting countries — England and Norway — to help to identify some of the differences, challenges and complexities that are relevant when creating an approach for analysis that can be used more widely to explore ‘non-completion’ across different countries in Europe and beyond.
The use of control variables plays a central role in organizational research due to practical difficulties associated with the implementation of experimental and quasi-experimental designs. As such, we conducted an in-depth review and content analysis of what variables and why such variables are controlled for in ten of the most popular research domains (task performance, organizational citizenship behaviors, turnover, job satisfaction, organizational commitment, employee burnout, personality, leader-member exchange, organizational justice, and affect) in organizational behavior/human resource management (OB/HRM) and applied psychology. Specifically, we examined 580 articles published from 2003 to 2012 in AMJ, ASQ, JAP, JOM, and PPsyc. Results indicate that, across research domains with clearly distinct theoretical bases, the overwhelming majority of the more than 3,500 controls identified in our review converge around the same simple demographic factors (i.e., gender, age, tenure), very little effort is made to explain why and how controls relate to focal variables of interest, and control variable practices have not changed much over the past decade. To address these results, we offer best-practice recommendations in the form of a sequence of questions and subsequent steps that can be followed to make decisions on the appropriateness of including a specific control variable within a particular theoretical framework, research domain, and empirical study. Our recommendations can be used by authors as well as journal editors and reviewers to improve the transparency and appropriateness of practices regarding control variable usage.
Variance between studies in a meta-analysis will exist. This heterogeneity may be from clinical, methodological or statistical origin. The latter is quantified by the I(2) statistic. We investigated, using simulated studies, the accuracy of I(2) in the assessment of heterogeneity and the effects of heterogeneity on the predictive value of meta-analyses. The relevance of quantifying I(2) was determined based on the likely presence of heterogeneity between studies (low, high or unknown) and the calculated I(2) (low or high). Findings were illustrated by published meta-analyses of Selective Digestive Decontamination and weaning protocols. As expected, I(2) increases and the likelihood to draw correct inferences from a meta-analysis decreases with increasing heterogeneity. With low levels of heterogeneity the I(2) value appears not predictive for the accuracy of the meta-analysis result. With high levels of heterogeneity even meta-analyses with low I(2) values have low predictive values Most commonly the level of heterogeneity in a meta-analysis will be unknown. In these scenarios I(2) determination may help to identify estimates with low predictive values (high I(2) ). In this situation the results of a meta-analysis will be unreliable. With low I(2) values and unknown levels of heterogeneity predictive values of pooled estimates may range extensively, and findings should be interpreted with caution. In conclusion, quantifying statistical heterogeneity, through I(2) -statistics, is only helpful when the amount of clinical heterogeneity is unknown and I(2) is high. Objective methods to quantify the levels of clinical and methodological heterogeneity are urgently needed to allow reliable determination of the accuracy of meta-analyses. This article is protected by copyright. All rights reserved.
Career development gains new meaning in the context of employability demands in a knowledge economy. In this context, increased mobility, a dynamic work environment, and an increased level of career support from employers are seen as characteristics of a modern career. All of these characteristics put emphasis on individual and self-management in career development. This article presents the results of an empirical study that addressed the general question as to which competencies employees need to possess to realize career self-management. In a survey of 1,579 employees (51% response) in 16 Dutch companies, 6 career factors and competencies of career self-management prove to be relevant for career development: career development ability, reflection on capacities, reflection on motives, work exploration, career control, and networking. Among the explanatory variables that are considered, mobility perspective and career support at work and private life appear to be associated most strongly (statistical significance at .01) with career competencies.
This study proposed that precollege students’ standardized mathematics achievement score and the congruence between their occupational interests and engineering tasks would predict their second-year retention in college and the stability of their major. Binary response models were used to predict second-year major status (i.e., continue, transfer major, or dropout). High mathematics achievement was predictive of retention on campus and within the engineering major. Interest congruence predicted likelihood of staying on campus. A trend was also detected (p < .07) between the Mathematics Achievement · Interest Congruence interaction effect. These findings reinforce the importance of examining both achievement and interest congruence factors when understanding the retention of engineering majors. Future research needs to replicate and extend this model to other majors and institutions to more fully understand the major choice and college retention processes.
This article first presents research that compares 10 extant measures of interest congruence, derived from Holland′s (1985a) theory of career choice, for their underlying distribution characteristics and their abilities to discriminate among subtle but important differences in person-environment congruence. Using simulated data, we show that (a) none of the three-letter code measures are sensitive to differences among persons across the entire possible range of congruence scores, and (b) with one exception (Kwak & Pulvino, 1982), they are incapable of making fine distinctions among persons with like, but out of order, three-letter person and environment codes. In a second study, we present a new measure of interest congruence that retains the advantages of the Kwak and Pulvino measure, but is easier to calculate. Results are discussed in terms of how users can choose among measures, and needed areas for future research on the new measure and on congruence measurement in general.
Performed a meta-analysis of 27 studies reporting a relation between interest congruence and job or academic satisfaction. The overall mean congruence-satisfaction correlation was not significant. An examination of type of congruence measure, gender, Holland type, and academic vs job setting showed no significant moderating effects. Surprisingly, a breakdown by quality of the measurements used in the study indicate that the methodologically weaker studies yielded the strongest satisfaction-congruence relations. Results reinforce the importance of considering occupational fit as more than the match between interests and the occupational environment. (PsycINFO Database Record (c) 2012 APA, all rights reserved)