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How to Write a Psychology Research Paper

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

 James Lacy, MLS, is a fact-checker and researcher.

Are you working on a psychology research paper this semester? Whether or not this is your first research paper, the entire process can seem a bit overwhelming at first. But, knowing where to start the research process can make things easier and less stressful.

While it can feel very intimidating, a research paper can initially be very intimidating, but it is not quite as scary if you break it down into more manageable steps. The following tips will help you break down the process into steps so it is easier to research and write your paper.

Decide What Kind of Paper You Are Going to Write

Before you begin, you should find out the type of paper your instructor expects you to write. There are a few common types of psychology papers that you might encounter.

Original Research or Lab Report

A report or empirical paper details research you conducted on your own. This is the type of paper you would write if your instructor had you perform your own psychology experiment. This type of paper follows a format similar to an APA format lab report. It includes a title page, abstract , introduction, method section, results section, discussion section, and references.

Literature Review

The second type of paper is a literature review that summarizes research conducted by other people on a particular topic. If you are writing a psychology research paper in this form, your instructor might specify the length it needs to be or the number of studies you need to cite. Student are often required to cite between 5 and 20 studies in their literature reviews and they are usually between 8 and 20 pages in length.

The format and sections of a literature review usually include an introduction, body, and discussion/implications/conclusions.

Literature reviews often begin by introducing the research question before narrowing the focus to the specific studies cited in the paper. Each cited study should be described in considerable detail. You should evaluate and compare the studies you cite and then offer your discussion of the implications of the findings.

Select an Idea for Your Research Paper

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Once you have figured out the type of research paper you are going to write, it is time to choose a good topic . In many cases, your instructor may assign you a subject, or at least specify an overall theme on which to focus.

As you are selecting your topic, try to avoid general or overly broad subjects. For example, instead of writing a research paper on the general subject of attachment , you might instead focus your research on how insecure attachment styles in early childhood impact romantic attachments later in life.

Narrowing your topic will make writing your paper easier because it allows you to focus your research, develop your thesis, and fully explore pertinent findings.

Develop an Effective Research Strategy

As you find references for your psychology paper, take careful notes on the information you use and start developing a bibliography. If you stay organized and cite your sources throughout the writing process, you will not be left searching for an important bit of information you cannot seem to track back to the source.

So, as you do your research, make careful notes about each reference including the article title, authors, journal source, and what the article was about. 

Write an Outline

You might be tempted to immediately dive into writing, but developing a strong framework can save a lot of time, hassle, and frustration. It can also help you spot potential problems with flow and structure.

If you outline the paper right off the bat, you will have a better idea of how one idea flows into the next and how your research supports your overall hypothesis .

You should start the outline with the three most fundamental sections: the introduction, the body, and the conclusion. Then, start creating subsections based on your literature review. The more detailed your outline, the easier it will be to write your paper.

Draft, Revise, and Edit

Once you are confident in your outline, it is time to begin writing. Remember to follow APA format as you write your paper and include in-text citations for any materials you reference. Make sure to cite any information in the body of your paper in your reference section at the end of your document.

Writing a psychology research paper can be intimidating at first, but breaking the process into a series of smaller steps makes it more manageable. Be sure to start early by deciding on a substantial topic, doing your research, and creating a good outline . Doing these supporting steps ahead of time make it much easier to actually write the paper when the time comes.

• Beins, BC & Beins, A. Effective Writing in Psychology: Papers, Posters, and Presentation. New York: Blackwell Publishing; 2011.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Tips for Writing Your Best Psychology Research Paper

A checklist of do's and don'ts for students to write papers people want to read..

Posted July 17, 2022 | Reviewed by Tyler Woods

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• Scientific writing is non-intuitive in many ways.
• When it comes to writing psychology research reports, a primary goal should be clear communication.
• Here is a list of tips to help behavioral scientists, at all levels, to best communicate ideas regarding psychological research findings.

When it comes to reading academic research reports in the behavioral sciences, I'm no different than anyone else. I often find myself thinking "what is the point?" Reading academic papers is not always rainbows, balloons, and unicorns.

As a teacher and researcher, I regularly provide commentary on student research papers, with the primary goal of helping students best express complex ideas. Based on this experience, here is something of a checklist of issues to think about when writing a psychology research report.

Write as you speak.

So often, I read student papers that sound much more like someone trying to sound smart than like someone trying to communicate ideas. You made it into college—you're likely plenty smart. Don't worry about using big words.

The point of summarizing your research is to present it to others so that they understand what you are saying.

One way to achieve this outcome is simply to write as you speak. When you speak to others, you are trying to get them to understand something. This same goal is true when you are writing a scientific research report. Sure, avoid informalities, slang, and profanity in scientific writing—but beyond that, I suggest that you simply write how you speak.

Never copy and paste so much as a letter from another source.

In this day and age, it is common for students to copy and paste content from others' papers into their own. From there, students will often edit, modify, etc. Regarding this practice, I say this: Never do that! Not only does this practice have you dancing dangerously on the edge of plagiarism, but it is just a poor way to communicate.

When it comes to summarizing ideas from past researchers, your best bet is to read their work to the point that you really understand it and then to write your ideas out as if you are describing the ideas to a friend or family member. Doing so will ensure that your voice comes through.

Only summarize parts of past research that are relevant to your own research.

Sometimes, students feel that they have to summarize everything that they find in a relevant article connected with their research. Not so.

Imagine that you are writing a paper about how academic self-esteem (belief in oneself in academic contexts) relates to academic success (e.g., grade point average).

Now suppose that in your review of past work on this topic, you find a paper that summarizes five different studies that another researcher conducted on this topic. Imagine that one of the five studies examined the relationship between general self-esteem and academic self-esteem. Now imagine that this particular issue is unrelated to your own study. In this case, it would be a mistake to elaborate on this particular feature of this past work in detail.

Sometimes it feels like a student describing irrelevant details of others' work is intentionally trying to add length to their paper. Honestly, don't ever do that! Only include content that is relevant to your point. If there is a part of a prior paper that is not related to the point of your work, don't include it.

Avoid writing superfluous details about past studies (sample sizes, specific statistical findings, and ancillary findings) that do not relate to your own work.

Here's something that students often do not know. When very in-the-weeds details about a prior study make it into your paper, it comes across as a rookie mistake.

Such details often include the sample size from a prior study (e.g., "In Smith and Johnson's (2019) study, 632 young adult participants from a large, midwestern university were studied..."). Honestly, no one cares! In your own research report, describe your sample in detail—but not such details of past work.

Describing samples of other studies in detail in your own paper automatically puts the reader in zone-out mode.

This same rule applies to statistical findings from past studies. Suppose that Smith and Johnson found that high academic self-esteem corresponded to high GPAs in a sample of students from a community college. That's all you need to say! If you go on and describe the r-value and the p-value and the N of that prior research, you are once again inviting your reader to go into zone-out mode.

Include a brief summary at the end of your Introduction that includes clearly specified hypotheses.

The whole point of your Introduction is to get the reader to see the problem that you are studying and to see the value of studying that problem. A strong way to communicate all of this is to make sure to specify your hypotheses (or predictions) clearly in a section that completes your Introduction. Summarizing your specific predictions in detail in this section helps to provide a bridge between your Introduction and your Methods sections.

Make sure that each variable in your study is described in your Introduction so that the reader knows why it is included.

When a variable shows up in your Methods section that was not introduced in the Introduction, the reader will automatically be confused. The reader may think, "Wait, what? The intro didn't say anything about this variable. I have no idea what the relevance is here!" Each variable included in your Methods section should be described in some detail in your Introduction section—especially as it relates to the main predictions of your study.

Include sub-sections in your Introduction to help guide your reader to your broader points.

Reading scientific papers is not easy. One way to help make your presentation easier on your reader is by including sub-sections in your Introduction. APA style fully allows you to include as many sub-sections as you want in your Introduction.

You can create sections for each variable that you study in your project. You can create sections that describe past work related to the topic, etc. A sub-section will usually have between two and five paragraphs, just as a rule of thumb. Doing this will help in making your ideas clear to your reader.

Refer to hypotheses in words and not by some arbitrary numbers.

Near the end of the Introduction, as noted above, it is best practice to demarcate your specific hypotheses. Sometimes, a researcher will describe these in numbered form (e.g., Hypothesis 1: We predict that high levels of academic self-esteem will be positively related to cumulative grade point average . Hypothesis 2...).

In the hypothesis section of your Introduction, it is fine to number your hypotheses in this way. That said, later in your paper, it is not good practice to refer to your hypotheses by number. For instance, in your results section, you can imagine saying something like, "Hypothesis 1 was supported by a correlation."

By the time I get to the Results section, I usually don't recall which particular prediction comprised "Hypothesis 1." It's best practice to refer to your hypotheses in terms of the actual, relevant content. You could call it "the hypothesis suggesting that academic self-esteem is positively related to GPA." Such an approach will make it so that your reader is not flipping back to a prior section.

In your Methods section, describe each measuring instrument in detail and include academic citations that point to the full scale when appropriate.

In your Methods section, it is best practice to describe each measure in enough detail so that your audience has a solid idea as to how the measuring instrument works.

For instance, if you use a published scale of general self-esteem in your study, you should not only provide the full academic citation to this scale, but you should also give one example item (e.g., "Here is an example item: 'Generally speaking, I like myself.'") and you should describe the measuring system in sufficient detail (e.g., are the items on a 1-5 Likert scale, anchored with Strong Disagree and Strongly Agree? If so, say that.). This basic process should be used for each measuring instrument included in your study.

Never end your paper with a limitation of your work.

Life is hard enough and there are endless critics out there. It is appropriate to describe limitations to your work in your Discussion section, but it is not great practice to end your paper with limitations of your work. That could leave the reader with something we call the recency effect —where they primarily remember the final information that was presented. You don't want your reader to walk away thinking that the main point of your work is that you had a small sample size in your research, for instance. Your ending should bring the paper full circle and focus on the value of your work as well as potential implications.

Bottom Line

In my work as a psychology professor, I both produce psychological research reports and I read and comment on many student papers that summarize research. In my efforts to help students hone their skills in this realm, I recently published a book: Own Your Psychology Major (Geher, 2019) , which helps guide students on various facets of the field of psychology, including the presentation of research findings.

People often find the process of scientific writing a bit non-intuitive. Following the tips above can help behavioral scientists at all levels communicate their ideas clearly, with the goal of having their ideas heard. Ultimately, this is the goal of all writing, including scientific writing.

Geher, G. (2019). Own Your Psychology Major! A Guide to Student Success. Washington, DC: American Psychological Association.

Glenn Geher, Ph.D. , is professor of psychology at the State University of New York at New Paltz. He is founding director of the campus’ Evolutionary Studies (EvoS) program.

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Psychological Science , the flagship journal of the Association for Psychological Science, is the leading peer-reviewed journal publishing empirical research spanning the entire spectrum of the science of psychology. The journal publishes high quality research articles of general interest and on important topics spanning the entire spectrum of the science of psychology. Replication studies are welcome and evaluated on the same criteria as novel studies. Articles are published in OnlineFirst before they are assigned to an issue. This journal is a member of the Committee on Publication Ethics (COPE) .

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Peer-reviewed

Research Article

Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression

Affiliations Department of Psychology, University of Gothenburg, Gothenburg, Sweden, Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden

Affiliation Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden

Affiliations Department of Psychology, University of Gothenburg, Gothenburg, Sweden, Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden, Department of Psychology, Education and Sport Science, Linneaus University, Kalmar, Sweden

* E-mail: [email protected]

Affiliations Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden, Center for Ethics, Law, and Mental Health (CELAM), University of Gothenburg, Gothenburg, Sweden, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

• Ali Al Nima, 
• Patricia Rosenberg, 
• Trevor Archer, 
• Danilo Garcia

• Published: September 9, 2013
• https://doi.org/10.1371/journal.pone.0073265
• Reader Comments

23 Sep 2013: Nima AA, Rosenberg P, Archer T, Garcia D (2013) Correction: Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression. PLOS ONE 8(9): 10.1371/annotation/49e2c5c8-e8a8-4011-80fc-02c6724b2acc. https://doi.org/10.1371/annotation/49e2c5c8-e8a8-4011-80fc-02c6724b2acc View correction

Mediation analysis investigates whether a variable (i.e., mediator) changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of different variables on depression. The purpose of this study was to assess the mediating and moderating effects of anxiety, stress, positive affect, and negative affect on depression.

Two hundred and two university students (males  = 93, females  = 113) completed questionnaires assessing anxiety, stress, self-esteem, positive and negative affect, and depression. Mediation and moderation analyses were conducted using techniques based on standard multiple regression and hierarchical regression analyses.

Main Findings

The results indicated that (i) anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii) that stress partially mediated the effects of anxiety and positive affect upon depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and between positive affect and negative affect upon depression.

The study highlights different research questions that can be investigated depending on whether researchers decide to use the same variables as mediators and/or moderators.

Citation: Nima AA, Rosenberg P, Archer T, Garcia D (2013) Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression. PLoS ONE 8(9): e73265. https://doi.org/10.1371/journal.pone.0073265

Editor: Ben J. Harrison, The University of Melbourne, Australia

Received: February 21, 2013; Accepted: July 22, 2013; Published: September 9, 2013

Copyright: © 2013 Nima et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors have no support or funding to report.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Mediation refers to the covariance relationships among three variables: an independent variable (1), an assumed mediating variable (2), and a dependent variable (3). Mediation analysis investigates whether the mediating variable accounts for a significant amount of the shared variance between the independent and the dependent variables–the mediator changes in regard to the independent variable, in turn, affecting the dependent one [1] , [2] . On the other hand, moderation refers to the examination of the statistical interaction between independent variables in predicting a dependent variable [1] , [3] . In contrast to the mediator, the moderator is not expected to be correlated with both the independent and the dependent variable–Baron and Kenny [1] actually recommend that it is best if the moderator is not correlated with the independent variable and if the moderator is relatively stable, like a demographic variable (e.g., gender, socio-economic status) or a personality trait (e.g., affectivity).

Although both types of analysis lead to different conclusions [3] and the distinction between statistical procedures is part of the current literature [2] , there is still confusion about the use of moderation and mediation analyses using data pertaining to the prediction of depression. There are, for example, contradictions among studies that investigate mediating and moderating effects of anxiety, stress, self-esteem, and affect on depression. Depression, anxiety and stress are suggested to influence individuals' social relations and activities, work, and studies, as well as compromising decision-making and coping strategies [4] , [5] , [6] . Successfully coping with anxiety, depressiveness, and stressful situations may contribute to high levels of self-esteem and self-confidence, in addition increasing well-being, and psychological and physical health [6] . Thus, it is important to disentangle how these variables are related to each other. However, while some researchers perform mediation analysis with some of the variables mentioned here, other researchers conduct moderation analysis with the same variables. Seldom are both moderation and mediation performed on the same dataset. Before disentangling mediation and moderation effects on depression in the current literature, we briefly present the methodology behind the analysis performed in this study.

Mediation and moderation

Baron and Kenny [1] postulated several criteria for the analysis of a mediating effect: a significant correlation between the independent and the dependent variable, the independent variable must be significantly associated with the mediator, the mediator predicts the dependent variable even when the independent variable is controlled for, and the correlation between the independent and the dependent variable must be eliminated or reduced when the mediator is controlled for. All the criteria is then tested using the Sobel test which shows whether indirect effects are significant or not [1] , [7] . A complete mediating effect occurs when the correlation between the independent and the dependent variable are eliminated when the mediator is controlled for [8] . Analyses of mediation can, for example, help researchers to move beyond answering if high levels of stress lead to high levels of depression. With mediation analysis researchers might instead answer how stress is related to depression.

In contrast to mediation, moderation investigates the unique conditions under which two variables are related [3] . The third variable here, the moderator, is not an intermediate variable in the causal sequence from the independent to the dependent variable. For the analysis of moderation effects, the relation between the independent and dependent variable must be different at different levels of the moderator [3] . Moderators are included in the statistical analysis as an interaction term [1] . When analyzing moderating effects the variables should first be centered (i.e., calculating the mean to become 0 and the standard deviation to become 1) in order to avoid problems with multi-colinearity [8] . Moderating effects can be calculated using multiple hierarchical linear regressions whereby main effects are presented in the first step and interactions in the second step [1] . Analysis of moderation, for example, helps researchers to answer when or under which conditions stress is related to depression.

Mediation and moderation effects on depression

Cognitive vulnerability models suggest that maladaptive self-schema mirroring helplessness and low self-esteem explain the development and maintenance of depression (for a review see [9] ). These cognitive vulnerability factors become activated by negative life events or negative moods [10] and are suggested to interact with environmental stressors to increase risk for depression and other emotional disorders [11] , [10] . In this line of thinking, the experience of stress, low self-esteem, and negative emotions can cause depression, but also be used to explain how (i.e., mediation) and under which conditions (i.e., moderation) specific variables influence depression.

Using mediational analyses to investigate how cognitive therapy intervations reduced depression, researchers have showed that the intervention reduced anxiety, which in turn was responsible for 91% of the reduction in depression [12] . In the same study, reductions in depression, by the intervention, accounted only for 6% of the reduction in anxiety. Thus, anxiety seems to affect depression more than depression affects anxiety and, together with stress, is both a cause of and a powerful mediator influencing depression (See also [13] ). Indeed, there are positive relationships between depression, anxiety and stress in different cultures [14] . Moreover, while some studies show that stress (independent variable) increases anxiety (mediator), which in turn increased depression (dependent variable) [14] , other studies show that stress (moderator) interacts with maladaptive self-schemata (dependent variable) to increase depression (independent variable) [15] , [16] .

The present study

In order to illustrate how mediation and moderation can be used to address different research questions we first focus our attention to anxiety and stress as mediators of different variables that earlier have been shown to be related to depression. Secondly, we use all variables to find which of these variables moderate the effects on depression.

The specific aims of the present study were:

• To investigate if anxiety mediated the effect of stress, self-esteem, and affect on depression.
• To investigate if stress mediated the effects of anxiety, self-esteem, and affect on depression.
• To examine moderation effects between anxiety, stress, self-esteem, and affect on depression.

Ethics statement

This research protocol was approved by the Ethics Committee of the University of Gothenburg and written informed consent was obtained from all the study participants.

Participants

The present study was based upon a sample of 206 participants (males  = 93, females  = 113). All the participants were first year students in different disciplines at two universities in South Sweden. The mean age for the male students was 25.93 years ( SD  = 6.66), and 25.30 years ( SD  = 5.83) for the female students.

In total, 206 questionnaires were distributed to the students. Together 202 questionnaires were responded to leaving a total dropout of 1.94%. This dropout concerned three sections that the participants chose not to respond to at all, and one section that was completed incorrectly. None of these four questionnaires was included in the analyses.

Instruments

Hospital anxiety and depression scale [17] ..

The Swedish translation of this instrument [18] was used to measure anxiety and depression. The instrument consists of 14 statements (7 of which measure depression and 7 measure anxiety) to which participants are asked to respond grade of agreement on a Likert scale (0 to 3). The utility, reliability and validity of the instrument has been shown in multiple studies (e.g., [19] ).

Perceived Stress Scale [20] .

The Swedish version [21] of this instrument was used to measures individuals' experience of stress. The instrument consist of 14 statements to which participants rate on a Likert scale (0 =  never , 4 =  very often ). High values indicate that the individual expresses a high degree of stress.

Rosenberg's Self-Esteem Scale [22] .

The Rosenberg's Self-Esteem Scale (Swedish version by Lindwall [23] ) consists of 10 statements focusing on general feelings toward the self. Participants are asked to report grade of agreement in a four-point Likert scale (1 =  agree not at all, 4 =  agree completely ). This is the most widely used instrument for estimation of self-esteem with high levels of reliability and validity (e.g., [24] , [25] ).

Positive Affect and Negative Affect Schedule [26] .

This is a widely applied instrument for measuring individuals' self-reported mood and feelings. The Swedish version has been used among participants of different ages and occupations (e.g., [27] , [28] , [29] ). The instrument consists of 20 adjectives, 10 positive affect (e.g., proud, strong) and 10 negative affect (e.g., afraid, irritable). The adjectives are rated on a five-point Likert scale (1 =  not at all , 5 =  very much ). The instrument is a reliable, valid, and effective self-report instrument for estimating these two important and independent aspects of mood [26] .

Questionnaires were distributed to the participants on several different locations within the university, including the library and lecture halls. Participants were asked to complete the questionnaire after being informed about the purpose and duration (10–15 minutes) of the study. Participants were also ensured complete anonymity and informed that they could end their participation whenever they liked.

Correlational analysis

Depression showed positive, significant relationships with anxiety, stress and negative affect. Table 1 presents the correlation coefficients, mean values and standard deviations ( sd ), as well as Cronbach ' s α for all the variables in the study.

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https://doi.org/10.1371/journal.pone.0073265.t001

Mediation analysis

Regression analyses were performed in order to investigate if anxiety mediated the effect of stress, self-esteem, and affect on depression (aim 1). The first regression showed that stress ( B  = .03, 95% CI [.02,.05], β = .36, t  = 4.32, p <.001), self-esteem ( B  = −.03, 95% CI [−.05, −.01], β = −.24, t  = −3.20, p <.001), and positive affect ( B  = −.02, 95% CI [−.05, −.01], β = −.19, t  = −2.93, p  = .004) had each an unique effect on depression. Surprisingly, negative affect did not predict depression ( p  = 0.77) and was therefore removed from the mediation model, thus not included in further analysis.

The second regression tested whether stress, self-esteem and positive affect uniquely predicted the mediator (i.e., anxiety). Stress was found to be positively associated ( B  = .21, 95% CI [.15,.27], β = .47, t  = 7.35, p <.001), whereas self-esteem was negatively associated ( B  = −.29, 95% CI [−.38, −.21], β = −.42, t  = −6.48, p <.001) to anxiety. Positive affect, however, was not associated to anxiety ( p  = .50) and was therefore removed from further analysis.

A hierarchical regression analysis using depression as the outcome variable was performed using stress and self-esteem as predictors in the first step, and anxiety as predictor in the second step. This analysis allows the examination of whether stress and self-esteem predict depression and if this relation is weaken in the presence of anxiety as the mediator. The result indicated that, in the first step, both stress ( B  = .04, 95% CI [.03,.05], β = .45, t  = 6.43, p <.001) and self-esteem ( B  = .04, 95% CI [.03,.05], β = .45, t  = 6.43, p <.001) predicted depression. When anxiety (i.e., the mediator) was controlled for predictability was reduced somewhat but was still significant for stress ( B  = .03, 95% CI [.02,.04], β = .33, t  = 4.29, p <.001) and for self-esteem ( B  = −.03, 95% CI [−.05, −.01], β = −.20, t  = −2.62, p  = .009). Anxiety, as a mediator, predicted depression even when both stress and self-esteem were controlled for ( B  = .05, 95% CI [.02,.08], β = .26, t  = 3.17, p  = .002). Anxiety improved the prediction of depression over-and-above the independent variables (i.e., stress and self-esteem) (Δ R 2  = .03, F (1, 198) = 10.06, p  = .002). See Table 2 for the details.

https://doi.org/10.1371/journal.pone.0073265.t002

A Sobel test was conducted to test the mediating criteria and to assess whether indirect effects were significant or not. The result showed that the complete pathway from stress (independent variable) to anxiety (mediator) to depression (dependent variable) was significant ( z  = 2.89, p  = .003). The complete pathway from self-esteem (independent variable) to anxiety (mediator) to depression (dependent variable) was also significant ( z  = 2.82, p  = .004). Thus, indicating that anxiety partially mediates the effects of both stress and self-esteem on depression. This result may indicate also that both stress and self-esteem contribute directly to explain the variation in depression and indirectly via experienced level of anxiety (see Figure 1 ).

Changes in Beta weights when the mediator is present are highlighted in red.

https://doi.org/10.1371/journal.pone.0073265.g001

For the second aim, regression analyses were performed in order to test if stress mediated the effect of anxiety, self-esteem, and affect on depression. The first regression showed that anxiety ( B  = .07, 95% CI [.04,.10], β = .37, t  = 4.57, p <.001), self-esteem ( B  = −.02, 95% CI [−.05, −.01], β = −.18, t  = −2.23, p  = .03), and positive affect ( B  = −.03, 95% CI [−.04, −.02], β = −.27, t  = −4.35, p <.001) predicted depression independently of each other. Negative affect did not predict depression ( p  = 0.74) and was therefore removed from further analysis.

The second regression investigated if anxiety, self-esteem and positive affect uniquely predicted the mediator (i.e., stress). Stress was positively associated to anxiety ( B  = 1.01, 95% CI [.75, 1.30], β = .46, t  = 7.35, p <.001), negatively associated to self-esteem ( B  = −.30, 95% CI [−.50, −.01], β = −.19, t  = −2.90, p  = .004), and a negatively associated to positive affect ( B  = −.33, 95% CI [−.46, −.20], β = −.27, t  = −5.02, p <.001).

A hierarchical regression analysis using depression as the outcome and anxiety, self-esteem, and positive affect as the predictors in the first step, and stress as the predictor in the second step, allowed the examination of whether anxiety, self-esteem and positive affect predicted depression and if this association would weaken when stress (i.e., the mediator) was present. In the first step of the regression anxiety ( B  = .07, 95% CI [.05,.10], β = .38, t  = 5.31, p  = .02), self-esteem ( B  = −.03, 95% CI [−.05, −.01], β = −.18, t  = −2.41, p  = .02), and positive affect ( B  = −.03, 95% CI [−.04, −.02], β = −.27, t  = −4.36, p <.001) significantly explained depression. When stress (i.e., the mediator) was controlled for, predictability was reduced somewhat but was still significant for anxiety ( B  = .05, 95% CI [.02,.08], β = .05, t  = 4.29, p <.001) and for positive affect ( B  = −.02, 95% CI [−.04, −.01], β = −.20, t  = −3.16, p  = .002), whereas self-esteem did not reach significance ( p < = .08). In the second step, the mediator (i.e., stress) predicted depression even when anxiety, self-esteem, and positive affect were controlled for ( B  = .02, 95% CI [.08,.04], β = .25, t  = 3.07, p  = .002). Stress improved the prediction of depression over-and-above the independent variables (i.e., anxiety, self-esteem and positive affect) (Δ R 2  = .02, F (1, 197)  = 9.40, p  = .002). See Table 3 for the details.

https://doi.org/10.1371/journal.pone.0073265.t003

Furthermore, the Sobel test indicated that the complete pathways from the independent variables (anxiety: z  = 2.81, p  = .004; self-esteem: z  =  2.05, p  = .04; positive affect: z  = 2.58, p <.01) to the mediator (i.e., stress), to the outcome (i.e., depression) were significant. These specific results might be explained on the basis that stress partially mediated the effects of both anxiety and positive affect on depression while stress completely mediated the effects of self-esteem on depression. In other words, anxiety and positive affect contributed directly to explain the variation in depression and indirectly via the experienced level of stress. Self-esteem contributed only indirectly via the experienced level of stress to explain the variation in depression. In other words, stress effects on depression originate from “its own power” and explained more of the variation in depression than self-esteem (see Figure 2 ).

https://doi.org/10.1371/journal.pone.0073265.g002

Moderation analysis

Multiple linear regression analyses were used in order to examine moderation effects between anxiety, stress, self-esteem and affect on depression. The analysis indicated that about 52% of the variation in the dependent variable (i.e., depression) could be explained by the main effects and the interaction effects ( R 2  = .55, adjusted R 2  = .51, F (55, 186)  = 14.87, p <.001). When the variables (dependent and independent) were standardized, both the standardized regression coefficients beta (β) and the unstandardized regression coefficients beta (B) became the same value with regard to the main effects. Three of the main effects were significant and contributed uniquely to high levels of depression: anxiety ( B  = .26, t  = 3.12, p  = .002), stress ( B  = .25, t  = 2.86, p  = .005), and self-esteem ( B  = −.17, t  = −2.17, p  = .03). The main effect of positive affect was also significant and contributed to low levels of depression ( B  = −.16, t  = −2.027, p  = .02) (see Figure 3 ). Furthermore, the results indicated that two moderator effects were significant. These were the interaction between stress and negative affect ( B  = −.28, β = −.39, t  = −2.36, p  = .02) (see Figure 4 ) and the interaction between positive affect and negative affect ( B  = −.21, β = −.29, t  = −2.30, p  = .02) ( Figure 5 ).

https://doi.org/10.1371/journal.pone.0073265.g003

Low stress and low negative affect leads to lower levels of depression compared to high stress and high negative affect.

https://doi.org/10.1371/journal.pone.0073265.g004

High positive affect and low negative affect lead to lower levels of depression compared to low positive affect and high negative affect.

https://doi.org/10.1371/journal.pone.0073265.g005

The results in the present study show that (i) anxiety partially mediated the effects of both stress and self-esteem on depression, (ii) that stress partially mediated the effects of anxiety and positive affect on depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and positive affect and negative affect on depression.

Mediating effects

The study suggests that anxiety contributes directly to explaining the variance in depression while stress and self-esteem might contribute directly to explaining the variance in depression and indirectly by increasing feelings of anxiety. Indeed, individuals who experience stress over a long period of time are susceptible to increased anxiety and depression [30] , [31] and previous research shows that high self-esteem seems to buffer against anxiety and depression [32] , [33] . The study also showed that stress partially mediated the effects of both anxiety and positive affect on depression and that stress completely mediated the effects of self-esteem on depression. Anxiety and positive affect contributed directly to explain the variation in depression and indirectly to the experienced level of stress. Self-esteem contributed only indirectly via the experienced level of stress to explain the variation in depression, i.e. stress affects depression on the basis of ‘its own power’ and explains much more of the variation in depressive experiences than self-esteem. In general, individuals who experience low anxiety and frequently experience positive affect seem to experience low stress, which might reduce their levels of depression. Academic stress, for instance, may increase the risk for experiencing depression among students [34] . Although self-esteem did not emerged as an important variable here, under circumstances in which difficulties in life become chronic, some researchers suggest that low self-esteem facilitates the experience of stress [35] .

Moderator effects/interaction effects

The present study showed that the interaction between stress and negative affect and between positive and negative affect influenced self-reported depression symptoms. Moderation effects between stress and negative affect imply that the students experiencing low levels of stress and low negative affect reported lower levels of depression than those who experience high levels of stress and high negative affect. This result confirms earlier findings that underline the strong positive association between negative affect and both stress and depression [36] , [37] . Nevertheless, negative affect by itself did not predicted depression. In this regard, it is important to point out that the absence of positive emotions is a better predictor of morbidity than the presence of negative emotions [38] , [39] . A modification to this statement, as illustrated by the results discussed next, could be that the presence of negative emotions in conjunction with the absence of positive emotions increases morbidity.

The moderating effects between positive and negative affect on the experience of depression imply that the students experiencing high levels of positive affect and low levels of negative affect reported lower levels of depression than those who experience low levels of positive affect and high levels of negative affect. This result fits previous observations indicating that different combinations of these affect dimensions are related to different measures of physical and mental health and well-being, such as, blood pressure, depression, quality of sleep, anxiety, life satisfaction, psychological well-being, and self-regulation [40] – [51] .

Limitations

The result indicated a relatively low mean value for depression ( M  = 3.69), perhaps because the studied population was university students. These might limit the generalization power of the results and might also explain why negative affect, commonly associated to depression, was not related to depression in the present study. Moreover, there is a potential influence of single source/single method variance on the findings, especially given the high correlation between all the variables under examination.

Conclusions

The present study highlights different results that could be arrived depending on whether researchers decide to use variables as mediators or moderators. For example, when using meditational analyses, anxiety and stress seem to be important factors that explain how the different variables used here influence depression–increases in anxiety and stress by any other factor seem to lead to increases in depression. In contrast, when moderation analyses were used, the interaction of stress and affect predicted depression and the interaction of both affectivity dimensions (i.e., positive and negative affect) also predicted depression–stress might increase depression under the condition that the individual is high in negative affectivity, in turn, negative affectivity might increase depression under the condition that the individual experiences low positive affectivity.

Acknowledgments

The authors would like to thank the reviewers for their openness and suggestions, which significantly improved the article.

Author Contributions

Conceived and designed the experiments: AAN TA. Performed the experiments: AAN. Analyzed the data: AAN DG. Contributed reagents/materials/analysis tools: AAN TA DG. Wrote the paper: AAN PR TA DG.

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Because altering computer code in any way (e.g., indents, line spacing, line breaks, page breaks) during the typesetting process could alter its meaning, we treat computer code differently from the rest of your article in our production process. To that end, we request separate files for computer code.

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We request that runnable source code be included as supplemental material to the article. For more information, visit Supplementing Your Article With Online Material .

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Use Word's insert table function when you create tables. Using spaces or tabs in your table will create problems when the table is typeset and may result in errors.

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List references in alphabetical order. Each listed reference should be cited in text, and each text citation should be listed in the References section.

Examples of basic reference formats:

Journal article

McCauley, S. M., & Christiansen, M. H. (2019). Language learning as language use: A cross-linguistic model of child language development. Psychological Review , 126 (1), 1–51. https://doi.org/10.1037/rev0000126

Authored book

Brown, L. S. (2018). Feminist therapy (2nd ed.). American Psychological Association. https://doi.org/10.1037/0000092-000

Chapter in an edited book

Balsam, K. F., Martell, C. R., Jones. K. P., & Safren, S. A. (2019). Affirmative cognitive behavior therapy with sexual and gender minority people. In G. Y. Iwamasa & P. A. Hays (Eds.), Culturally responsive cognitive behavior therapy: Practice and supervision (2nd ed., pp. 287–314). American Psychological Association. https://doi.org/10.1037/0000119-012

Data set citation

Alegria, M., Jackson, J. S., Kessler, R. C., & Takeuchi, D. (2016). Collaborative Psychiatric Epidemiology Surveys (CPES), 2001–2003 [Data set]. Inter-university Consortium for Political and Social Research. https://doi.org/10.3886/ICPSR20240.v8

Software/Code citation

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package.  Journal of Statistical Software , 36(3), 1–48. https://www.jstatsoft.org/v36/i03/

Wickham, H. et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4 (43), 1686, https://doi.org/10.21105/joss.01686

All secondary data and program code and other methods from other articles should be cited in the text and listed in the References section.

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The APA Ethics Office provides the full Ethical Principles of Psychologists and Code of Conduct electronically on its website in HTML, PDF, and Word format. You may also request a copy by emailing or calling the APA Ethics Office (202-336-5930). You may also read "Ethical Principles," December 1992, American Psychologist , Vol. 47, pp. 1597–1611.

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See APA’s Publishing Policies page for more information on publication policies, including information on author contributorship and responsibilities of authors, author name changes after publication, the use of generative artificial intelligence, funder information and conflict-of-interest disclosures, duplicate publication, data publication and reuse, and preprints.

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Elena L. Grigorenko, PhD University of Houston, United States

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John R. Anderson, PhD Carnegie Mellon University, United States

Marjan Bakker, PhD University of Tilburg, Netherlands

Deanna Barch, PhD Washington University, United States

Jennifer A. Bartz, PhD McGIll University, Canada

Denny Borsboom, PhD University of Amsterdam, Holland

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Chi-yue Chiu, PhD The Chinese University of Hong Kong, Hong Kong

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APA endorses the Transparency and Openness Promotion (TOP) Guidelines by a community working group in conjunction with the Center for Open Science ( Nosek et al. 2015 ). The TOP Guidelines cover eight fundamental aspects of research planning and reporting that can be followed by journals and authors at three levels of compliance.

• Level 1: Disclosure—The article must disclose whether or not the materials are posted to a trusted repository.
• Level 2: Requirement—The article must share materials via a trusted repository when legally and ethically permitted (or disclose the legal and/or ethical restriction when not permitted).
• Level 3: Verification—A third party must verify that the standard is met.

As of August 1, 2021, empirical research, including meta-analyses, submitted to Psychological Review must, at a minimum, meet Level 1 (Disclosure) for all eight aspects of research planning and reporting. Authors should include a subsection in their methods description titled “Transparency and openness.” This subsection should detail the efforts the authors have made to comply with the TOP guidelines.

The list below summarizes the minimal TOP requirements of the journal. Please refer to the Center for Open Science TOP guidelines for details, and contact the editor (Elena L. Grigorenko, PhD) with any further questions. APA recommends sharing data, materials, and code via trusted repositories (e.g., APA’s repository on the Open Science Framework (OSF)), and we encourage investigators to preregister their studies and analysis plans prior to conducting the research. Trusted repositories adhere to policies that make data discoverable, accessible, usable, and preserved for the long term. Trusted repositories also assign unique and persistent identifiers. There are many available preregistration forms (e.g., the APA Preregistration for Quantitative Research in Psychology template, ClinicalTrials.gov , or other preregistration templates available via OSF ). Completed preregistration forms should be posted on a publicly accessible registry system (e.g., OSF , ClinicalTrials.gov, or other trial registries in the WHO Registry Network).

A list of participating journals is also available from APA.

The following list presents seven fundamental aspects of research planning and reporting, the TOP level required by Psychological Review , and a brief description of the journal's policy. (The journal also publishes replications if they are relevant to and/or embedded in new or enhanced theories.)

• Citation: Level 1, Disclosure—All data, program code, and other methods developed by others should be cited in the text and listed in the references section.
• Data Transparency: Level 1, Disclosure—Article states whether the raw and/or processed data on which study conclusions are based are posted to a trusted repository and, if so, how to access them.
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More information on this journal’s reporting standards is listed under the submission guidelines tab .

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Who Am I? An Effectual Perspective on the Impact of Psychological Capital on the Internationalization of Academic Spin-Offs

35 Pages Posted: 26 Jun 2024

Mariluz Fernández-Alles

Universidad de Cádiz

Juan Pablo Diánez-González

Dara hernandez-roque, mercedes villanueva-flores.

The literature applying effectual logic to entrepreneurial activity is extensive. However, there needs to be more research focused on the analysis of international entrepreneurship in the specific context of academic spin-offs (ASOs). Prior research has mainly analyzed the effect of human capital (what the entrepreneur knows) and relational capital (who they know) on internationalization.  There is, however, limited research that has focused on psychological capital (PsyCap) (who they are). Therefore, it seems appropriate to investigate whether the PsyCap of entrepreneurs impacts their firms' internationalization. It would also be interesting to analyze the timing and speed of withdrawal from foreign markets, and how the PsyCap changes over time, due to the entrepreneur's experiences and decisions. For this reason, the objective of this paper is twofold. First, to analyze whether there are differences in the PsyCap of the academic entrepreneur, between domestic ASOs (DASOs) and international ASOs (IASOs). Second, to identify differences in the PsyCap of entrepreneurs' pre-, and, post- internationalization in IASOs with different internationalization patterns. The results of hierarchical cluster analysis, analysis of variance (ANOVA), and post-hoc tests conclude, first, that there are no differences in the PsyCap of academic entrepreneurs in DASOs and IASOs, except for optimism, which is more prominent for IASOs. Second, internationalization increases the PsyCap of academic entrepreneurs in all internationalization patterns, except in ASOs which follows a non-linear pattern, with PsyCap being more prominent in the Born Global (BG) model.

Keywords: Effectual theory, Psychological capital, Academic spin-offs, Internationalization

Suggested Citation: Suggested Citation

Universidad de Cádiz ( email )

Dara hernandez-roque (contact author), do you have a job opening that you would like to promote on ssrn, paper statistics, related ejournals, entrepreneurship & economics ejournal.

Subscribe to this fee journal for more curated articles on this topic

Entrepreneurship & the Social Sciences eJournal

• DOI: 10.35316/psycomedia.2023.v3i1.9-15
• Corpus ID: 268771592

Rasa syukur dan psychologycal well- being pedagang pasar tradisional

• Nur Alifa , Aisyatin Kamila
• Published in PSYCOMEDIA : Jurnal Psikologi 31 December 2023
• PSYCOMEDIA : Jurnal Psikologi

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