what motivates you to do a research

Being a researcher: inspiration & curiosity to providing solutions

By Mohamed Boudjelal

The factors marking the similarities between a scientist, sportsperson and a politician are their ability to produce results, cut to the chase, lead and follow what inspired them the most. The characteristic that distinguishes the scientist from the rest, is the eagerness to discover how a certain phenomenon came about, and what is its purpose. The scientist aims to implement the gained knowledge to benefit humankind, living organisms and the universe in health, wealth, culture and sustainability. To reach this end, a scientist needs to acquire and possess certain qualities, skills and behavior regardless of his/her discipline. Based on my own experience working with successful scientists in the USA, Europe and Middle East, this short article summarizes what these qualities are.

1-        Working by inspiration not by the hours

The modern life has organized the human daily living ritual in such that most of us work very defined hours ranging from 32-40 hours a week. However, those who have left their marks in the history books, worked well beyond this schedule whether they were scientists, artists, sportspersons, politicians, writers and the like. They all shared one common quality: working by inspiration and not by the hours.  When working at or simply visiting research institutions around the world such as Harvard, MIT, MaxPlank, Karolinska, Imperial college, Welcome trust, SGC in UK and many others, one commonality that attracts your attention is this work ethic. Whether you show up during the day, the night, weekdays, weekends and holidays, there’s someone always there working to make their vision a reality. Adding to this is that there’s a noticeable level of satisfaction and enjoyment derived from such passion. The aspect that drives this motivation to work in the odd hours, is the discovery they are chasing. They get immersed in what they are doing and when a discovery is made, they don’t hesitate to call for a meeting at that exact moment whether it’s the night or a holiday to discuss it. True scientists simply enjoy working on something unique and undiscovered to make a difference in life. This does not mean, scientists do not have life beyond the lab walls. They share moments with their families and close friends. They strive to see their discoveries translated into practical changes in human development. In that regard, becoming a truly inspirational scientist, is to ignore the hours and work with inspiration. This lets you fall in love with your job, derive satisfaction and reward of what you are doing.

2-        Eagerness to be the first to know and discover

Curiosity is an intrinsic human feature; without it our life conditions would not develop and improve. It drives every person to work on the unknown, the hidden and undiscovered. The scientist uses the quality of curiosity to ask crucial questions; how a phenomenon came about and what is the benefit for mankind and how to replicate it for human use. They become satisfied when something new is discovered and no one has described it. This is in the same sense to when an athlete breaks a world record, or a politician when solving a complicated matter to stop a war. It is this unique point of being the first to the finish line that self-motivates scientists to keep going in comparison to other industries that rely on following patterns in the markets or repeating already known knowledge. It is the key characteristic the scientist must have and develop to become a true researcher who will be able discover and develop projects that impact lives positively.

3 – Thinkers out of the box

Dreaming is essential not only to human psychology, but also to humanity’s development. It can range from insignificant fragments of imagination, to concepts which alter the course of history. From a scientific perspective, such dreams often result from a drive, whether it is to understand how disease develops, or how to cure it. As scientists we have always dreamed, even speculative ideas, if at all feasible, must be explored. For example, the idea of one day having the ability to manufacture an organ in vitro to then be transplanted; or the concept of in vitro fertilization and birthing a child without a father, or even conquering space. All these aspects were no more than an impossibility for centuries, but through scientific curiosity, and abstract thinking, these dreams are now reality. Scientists must have the ability to imagine solutions beyond what is available. To enable such creativity and imagination, a scientist must keep updated on their specialty, and expose themselves to diverse thinking approaches by travelling and working worldwide. In this line, many of us have been educated in the West, and hence our way of thinking, tactic and approach to solve a scientific question is very similar. On the other hand, scientists and researchers from the East and Middle East, see through a different lens and approach problems from a different perspective. Having experience working with scientists from different cultures would challenge our methods of working and enforce new skills, providing new solutions to discover new matters. Moreover, especially in the age of information, we can easily translate non-English works to any language enabling us to further expose ourselves to other ways of thinking. Imagination and dreams are a key success of scientists, without it, we will not discover and develop new things.

4 –   Storyteller of real-life events, all are data based

Like writers and politicians, scientists tell stories based on facts and data. Unfortunately, on many occasions, the data obtained is often from experimental work, which may be surprising in such it is to the opposite of what was theorised. In such cases, most conclude that the data is negative and repeat experiments must be arranged. In other words, we avoid going deeper into those so-called negative data to understand the root cause; in reality, many times it is down to either having made a mistake in our experimental work or the data is pointing to different discovery. In this regard, no data can be deemed negative and as scientist we must ensure that what is obtained, either positive or negative, is reproducible, can be repeated, and then try to understand the message through it.

In most cases when we test a newly developed drug, it fails to show any efficacy in humans and we stop any further testing. We conclude that that drug does not work, while in vitro and even within animals it regularly produces the desired results. We halt at this stage and move on to other drugs to test.

As a scientific community, we did not come up with an approach to overcome this challenge as it is already very costly to bring a drug up to this point of testing. The negative data in this case is telling us that the disease we want to cure is different physiologically than we originally thought. One of the most important things a scientist never does, is to create or manipulate data that experiments never produce, otherwise called data fabrication to support the wanted conclusion. It is acceptable to not publish all generated data especially those that cannot yet be explained, but a true and trusted scientist never introduces data to the scientific community without guaranteeing its reproduction.  In sum a scientist must be a non-biased storyteller, based on real and reproducible data to keep their integrity and reputation.

5- Driven by the positive contribution to the whole humanity

Scientists are driven by humanity’s big picture in such that they want to contribute positively for the wellbeing of humankind and the universe. The hard work, ingenuity, curiosity and imagination must translate into the scientist’s self-satisfaction such as the discovery of chemotherapy, insulin, antibiotics, stem cells etc. Nowadays the tools available for us to try answering deeper questions and challenges are attracting the brilliant to consider science. All the impactful technology, processes and understanding began through individual discoveries in the laboratory with its application only starting after. A scientist’s role within society can often be underappreciated, but without them, humanity cannot challenge themselves to progress.

Through these 5 pillars, a scientist can achieve a professional satisfaction with a balanced family life and above all being a positive contributor to human kind and universe.

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Of the Many Reasons to Love Research

I am constantly asked why I do research and what it is I like about it. For me, it’s more than just gaining experience or improving my resume, it’s every reason— whether good or bad, frustrating or exciting, mundane or extraordinary. There are plenty of reasons to love and to do research, here are a few that come to mind:

• Research makes a difference . There is nothing cooler than knowing that you are contributing to the discovery or development of something that can make a difference in people’s lives or a change in the world! Every contribution matters!
• Research introduces you to great people! Not only does working in research give you the opportunity to work alongside incredible faculty mentors, research also provides the opportunity to work with a mentor and lab group that may serve as guides, counselors, and as friends outside of lab! Shout out to the Mitragotri Group!
• Research is applicable. One really cool thing about research is that it transcends beyond what is taught in the classroom and enables you to apply all that you know or have been taught and apply that knowledge into what you are learning and doing in lab.
• Research can help you!  As mentioned above, research can enhance both your professional and academic credentials for future graduate/professional school or for career advancement. It can also help support applications for internships, scholarships, and other awards!
• Research opens doors. Participating in research can afford the opportunity to go present your work at professional conferences, to meet other researchers like yourself, and to participate in great events. Research can also aid in networking and in making contacts early into your career! (Check out Lunch with Faculty every quarter!)
• Research changes the pace . Unlike with practice set exercises or protocol lab experiments with predetermined solutions and expected results, research has you come up with the experiments but also has you come up with the answer. Research makes you think differently by engaging you in the creation of new knowledge.
• Research is challenging. Sometimes, experiments don’t go as well as planned or give you unexpected results. And that’s okay! In these cases, you’re given the opportunity to question you process, make changes, and to think beyond. Research stretches your mind, and challenges and tests you to think of new ideas, new reasons, and new possibilities.
• Research is the future. It’s exciting to be a part of an adventure that will change the face of the future. Research is constantly pushing the frontiers of knowledge, and it’s crazy to think that the theory, the process, or the discovery you make today may determine how the world is structured tomorrow.
• Research doesn’t stop . Every study and every project in the world of research not only provides insights, answers, and details, it poses new questions. And even in the case where answers may be inconclusive, it still puts into consideration what it would take to solidify those answers.
• Research changes you. Somewhere along the way, research helps build traits and characteristics like independent thinking, resilience, communication, and creativity. Research can help mold you into the person you’d like to be while also changing all that you do, value, and hope to achieve!

Whether you’re in research or interested in research, what excites you? Why do you do research? And why do you love it?

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Reflecting on your interests and motivations, by claire fresher, peer research ambassador.

When getting started in research, it’s important to think about what motivates you and what is going to drive your passion for research. Do you love the process of finding solutions and answering questions? Is it a competitive drive to create something new? Are you naturally curious and enjoy learning new things? Do you thrive off having goals, deadlines, and objectives to achieve?

As college students, we are all motivated to complete our degree. What drives the motivation to go beyond our academic comfort zone and pursue research? Research takes work, and you want to make sure you’re doing something you are proud of and are learning about a topic that you want to talk with others about. Recognizing how research motivates you is a great place to begin your research journey.

What motivated me to get involved in research? I wanted to learn more about specific aspects of engineering outside of what my peers and I were learning in classes. I knew that I was interested in mechanical engineering, but I wanted to see how mechanical engineering overlaps with the biomedical engineering field to research how diseases work. I pursued this because I knew that it was something I was genuinely interested in and that interest would motivate me to learn more. When I was looking at different labs on campus that aligned with my interests, I considered what they were offering and how that aligned with my motivations. In one lab in particular, I would have the opportunity to work alongside another undergraduate student and in collaboration with graduate students and post-doc researchers. I thrive when working in a group and I am motivated by others, which made this opportunity a match with what I know about my work ethic and myself.

As you look for opportunities, make sure you spend time reflecting on what motivates you and what you want to get out of an experience. Being honest with yourself about what type of opportunity you’re seeking, and being able to weigh the pros and cons of different opportunities will help you decide what will be best for you.

Claire is a senior majoring in mechanical engineering and minoring in mathematics. Click here to learn more about Claire.

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Research Article

When research is me-search: How researchers’ motivation to pursue a topic affects laypeople’s trust in science

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources

Roles Conceptualization, Supervision, Writing – review & editing

• Marlene Sophie Altenmüller, 
• Leonie Lucia Lange, 
• Mario Gollwitzer

• Published: July 9, 2021
• https://doi.org/10.1371/journal.pone.0253911
• Peer Review
• Reader Comments

Research is often fueled by researchers’ scientific, but also their personal interests: Sometimes, researchers decide to pursue a specific research question because the answer to that question is idiosyncratically relevant for themselves: Such “me-search” may not only affect the quality of research, but also how it is perceived by the general public. In two studies ( N = 621), we investigate the circumstances under which learning about a researcher’s “me-search” increases or decreases laypeople’s ascriptions of trustworthiness and credibility to the respective researcher. Results suggest that participants’ own preexisting attitudes towards the research topic moderate the effects of “me-search” substantially: When participants hold favorable attitudes towards the research topic (i.e., LGBTQ or veganism), “me-searchers” were perceived as more trustworthy and their research was perceived as more credible. This pattern was reversed when participants held unfavorable attitudes towards the research topic. Study 2 furthermore shows that trustworthiness and credibility perceptions generalize to evaluations of the entire field of research. Implications for future research and practice are discussed.

Citation: Altenmüller MS, Lange LL, Gollwitzer M (2021) When research is me-search: How researchers’ motivation to pursue a topic affects laypeople’s trust in science. PLoS ONE 16(7): e0253911. https://doi.org/10.1371/journal.pone.0253911

Editor: Lynn Jayne Frewer, Newcastle University, School of Natural and Environmental Sciences, UNITED KINGDOM

Received: December 4, 2020; Accepted: June 15, 2021; Published: July 9, 2021

Copyright: © 2021 Altenmüller 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.

Data Availability: We provided all materials, the anonymized data and analyses, and supplementary materials online at the Open Science Framework via the following link: https://osf.io/phfq3/ .

Funding: The author(s) received no specific funding for this work.

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

Introduction

“Being a scientist is, at the most fundamental level, about being able to study what’s exciting to you”, says Jeremy Yoder, a gay man studying experiences of queer individuals in science [ 1 ]. Like Yoder, many researchers are passionate about their research and dedicated to their field. After all, they are free to choose research questions they deem important and are interested in. Freedom of science and research secures the independence of the academic from the political and other spheres. In return, researchers are expected to be neutral and objective and make their research process transparent to guarantee that this freedom is not exploited for personal gains.

Just as people differ in what they are interested in in their personal lives, researchers differ in what they find more or less fascinating and worth studying. Such fascination can have multiple causes and is often rooted in a perceived personal connection to a topic. For instance, Sir Isaac Newton allegedly became interested in gravity after an apple fell on his head [ 2 ]. A specific type of personal connection exists when researchers study a phenomenon because they are directly (negatively) affected by that phenomenon. In 1996, Harvard alumni and neuroanatomist Jill Bolte Taylor suffered a rare form of stroke that made her undergo major brain surgery, affected her personal and academic life tremendously, and eventually awakened her interest in studying the plasticity of the brain [ 3 ]. In 2006, she published an award-winning book covering her research and her personal story that led her to pursue this path. The Jill Bolte Taylor case is, thus, a prototypical example for such “me-search”: researchers studying a phenomenon out of a particular personal affection by (or connection to) this phenomenon. “Me-search” thus means pursuing a scientific question when the answer to that question is idiosyncratically relevant for the individual researcher (as opposed to when the answer is relevant per se).

Being directly affected by a phenomenon provides researchers studying it with a high degree of expertise and motivation: Jill Bolte Taylor, for instance, claims to bring a deep personal understanding and compassion to her research and work with patients [ 4 , 5 ]. That said, being personally affected may also come at the cost of losing one’s scientific impartiality and neutrality for the subject: Jill Bolte Taylor was criticized for being overly simplistic in her scientific claims and mixing them with esoteric ideas, and for pushing her own agenda (i.e., selling her story) by dramatizing her own experiences [ 4 – 7 ].

While some criticized Jill Bolte Taylor heavily, the general public does not seem to have a problem with her research as “me-search”. Her book is currently translated into 30 languages, and thousands of people visit her talks and keynote addresses [ 4 – 6 ]. Does that suggest that the general public tends to turn a blind eye on conflicts of interest that may arise from a researchers’ personal affection by their research object? While the Jill Bolte Taylor case seems to suggest so, research on science communication and public understanding of science has shown that people are highly sensitive to potential conflicts of interest arising from researchers’ personal involvement: perceiving researchers as pursuing an “agenda” for personal reasons is a major factor predicting people’s loss of trust in researchers and science [ 8 – 11 ]. On the other hand, people may see personal (“autoethnographic”) experiences of researchers personally affected by their topic as valuable and laudable ‒ it may imply that “they know what they’re talking about” [ 12 – 14 ]. Similarly, revealing a personal interest or even passion for a particular research topic (e.g., due to being personally affected) could also overcome the stereotypical perception of scientists as distant “nerds in the ivory tower” [ 15 , 16 ]: researchers who openly disclose the idiosyncratic relevance of their research topic may appear more approachable, more likeable, and more trustworthy [ 17 – 19 ].

Thus, the public’s reaction to “me-search” seems to be ambivalent and contingent on certain boundary conditions. Thus, the question we are going to address in this article is whether and when ‒ that is, under which circumstances ‒ a researcher’s personal affection by a research topic (“me-search”) positively vs. negatively impacts public perceptions regarding the trustworthiness of the respective researcher (and the entire research area in general) and the extent to which this researcher’s findings are perceived as credible .

Perceivers’ motivated stance as a moderating variable

This potentially ambivalent perception of “research as me-search” can be understood from a motivated reasoning [ 20 ] perspective: Laypeople receive and process information in a manner biased towards their own beliefs, expectations, or hopes. This also applies to the reception of scientific information [ 21 , 22 ]: For example, laypeople are more likely to dismiss scientific evidence if it is inconsistent with their beliefs [ 23 , 24 ] or if it threatens important (moral) values [ 25 , 26 ] or their social identity, respectively [ 27 – 29 ].

However, identity-related and attitudinal motivated science reception might differ in their underlying mechanisms. For identity-related motivated science reception, biased perception of information, which is relevant to a social identity, is driven by a defense motivation to protect this positive social identity [ 30 ]. Thus, identity-threating scientific information is countered by identity-protection efforts, such as discrediting the findings and the source. These efforts will be more pronounced among strongly identified individuals [ 27 – 29 ]. For attitudinal motivated science reception, however, the mechanism might function as a broader perception filter. When confronted with new scientific information about the respective attitude object, the perceptual focus will be directed at clues helping to uphold prior attitudes (i.e., confirmation bias [ 31 ]): Potentially attitude-inconsistent information is attenuated, while potentially attitude-consistent information is accentuated. The ambivalent nature of “me-search” might allow to be easily bend in such a motivated manner and, thus, lead to biased perceptions of a researcher either way: when the findings are in line with one’s prior beliefs, being personally affected may be considered an asset–the respective researcher is perceived as more trustworthy and his/her findings as more credible (compared to no idiosyncratic relevance). However, when the findings are inconsistent with one’s prior beliefs, idiosyncratic relevance may be considered a flaw–the respective research is perceived as biased, untrustworthy, and less competent, and his/her findings are likely perceived as less credible than when idiosyncratic relevance is absent.

Prior research on motivated science reception mainly focused on laypeople’s reactions towards specific scientific findings: after learning about the outcome of a particular study, participants dismiss the research (and devalue the researcher) if these outcomes are consistent vs. inconsistent with their prior beliefs [ 23 – 25 , 27 – 29 ]. However, people might be prone to motivated science reception even before results are known, judging researchers proverbially just by their cover (e.g., by biographical data, personal and scientific interests and motivations). People who hold positive attitudes towards a certain research topic might perceive “me-searchers” as more trustworthy and anticipate their results to be more credible (before knowing the specific outcomes). By contrast, people who hold negative attitudes towards a certain research topic they might trust “me-searchers” less and expect their findings to be less credible.

Additionally, motivated reception processes can be extended over and above the specific information under scrutiny and lead to questioning the scientific method in itself–a phenomenon termed the “scientific impotence excuse” [ 32 ]. In line with that, critical evaluations of specific researchers and their findings are sometimes generalized to the entire field of research [ 27 ]. Thus, the fact that a researcher engages in “me-search” might be interpreted in a way that fits best to one’s preexisting convictions and may generalize to the entire field of research.

The present research

In two studies, laypeople read alleged research proposals concerning potentially polarizing research topics (i.e., LGBTQ issues and veganism) which were submitted by researchers who disclosed being either personally affected or not affected by the respective topic. We investigated whether ( Study 1 ) and when (i.e., moderated by preexisting positive attitudes towards the respective research topic, Studies 1 and 2) such “me-search” information increased or decreased laypeople’s perceptions regarding these researchers’ epistemic trustworthiness and the anticipated credibility of their future scientific findings. Of note, we use the term “credibility” to differentiate evidence-related trust/credibility from person-related trust/credibility (i.e. “trustworthiness”). Further, we test whether one researcher’s “me-search” impacts the evaluation of the entire respective field ( Study 2 ).

For both studies in this paper, we report how we determined our sample size, all data exclusions (if any), all manipulations, and all measures [ 33 ]. All materials, the anonymized data, and analyses are available online at the Open Science Framework (OSF; see https://osf.io/phfq3/ ). Before starting the respective study, informed consent was obtained. Participants read a GDPR-consistent data protection and privacy disclosure declaration specifically designed for the present study. Only participants who gave their consent could start the respective survey. According to German laws and ethical regulations for psychological research [ 34 ], gathering IRB approval is not necessary if (i) the data are fully anonymized, (ii) the study does not involve deception, (iii) participants’ rights (e.g., voluntary participation, the right to withdraw their data, etc.) are fully preserved, and (iv) participating in the study is unlikely to cause harm, stress, or negative affect. The present studies met all of these criteria; therefore, no IRB approval had to be obtained.

In our first study, we conducted an online experiment investigating the main effect of a researcher’s disclosure of being personally affected vs. not affected by their research on their trustworthiness and the credibility of their future research. Further, we tested whether laypeople’s preexisting attitudes towards the research topic moderate this effect.

Four-hundred and eleven German participants were recruited via mailing lists and social networks. Ninety-seven participants had to be excluded due to pre-specified criteria: Sixty-seven participants failed the manipulation check; 25 participants failed the pre-specified time criteria (viewing the manipulation stimulus less than 30sec, taking less than 3min or more than 20min for participation); 5 participants had apparently implausible response patterns (e.g., “straight-lining;” identical responses on every single item on more than one questionnaire page in a row). Eighty-five further participants failed the attention check. Excluding them did not change the overall results, so, for the sake of statistical power, we did not exclude these 85 cases. The final sample consisted of N = 314 participants. We conducted sensitivity analyses using G*Power [ 35 ] for determining which effect sizes can detected with this sample in a moderated (multiple) regression analysis: At α = 0.05 and with a power of 80%, small-to-medium effects (f 2 ≥0.03) can be detected with this sample. Participants were mostly female (74% female, 25% male, 2% other) and their age ranged between 16 and 68 years ( M = 26.79; SD = 10.18). Most participants were currently studying at a university (71%; working: 21%; unemployed or other: 8%). Participants who were currently studying or already had a university degree (93%) came from a variety of disciplines (law, economics, and social sciences: 49%; humanities: 16%; mathematics and natural sciences: 14%; medicine and life sciences: 11%; engineering: 4%).

Materials and procedure.

After obtaining informed consent, we asked participants to imagine they were browsing the website of a research institute and came across a short proposal for a new research project by a researcher named Dr. Lohr (no gender was indicated for greater generalizability and avoiding possible gender confounds). Next, participants read the beginning of the alleged proposal of a planned research project for which Dr. Lohr was allegedly applying for external funding. The text briefly introduced the planned project (i.e., investigating social reactions to queer employees at the workplace) and a statement of Dr. Lohr explaining why they were interested in conducting this project. Participants were randomly allocated to two groups. In the “not personally affected” condition, Dr. Lohr wrote:

“ I am interested in investigating this research topic in more detail not only out of scientific reasons but also because I–as someone who does not identify as homosexual and is not affected by my own research–really think we need more evidence-based knowledge about queer topics which we can implement in everyday life .”

In the “personally affected” condition, Dr. Lohr wrote:

“ I am interested in investigating this research topic in more detail not only out of scientific reasons but also because I–as someone who identifies as homosexual and is affected by my own research–really think we need more evidence-based knowledge about queer topics which we can implement in everyday life .”

We added a definition for the word “queer” below the proposal: “ Queer is a term used as self-description by people who do not identify as heterosexual and/or who do not identify with the gender assigned at birth . The term is often used as umbrella term for LGBTQ (lesbian , gay , bisexual , trans and queer) and describes all people who identify as queer .” After completing an attention check question (see pre-registration), we measured participants’ trust in Dr. Lohr with the Muenster Epistemic Trustworthiness Inventory (METI; [ 36 ]), which was constructed for measuring trust in experts encountered online. It consists of 14 opposite adjective pairs measuring an overall trustworthiness score (Cronbach’s α = .95) as well as the sub-dimensions expertise (e.g., competent–incompetent, Cronbach’s α = .92) and integrity/benevolence (e.g., honest–dishonest, Cronbach’s α = .93) on 6-point bipolar Likert scales. Factor analyses (see Appendix A in the supplementary materials, https://osf.io/phfq3/ ) suggest that a two-factor model (with expertise and integrity/benevolence) fit the data better than a three-factor model (as suggested by [ 36 ]), corroborating the idea of a cognitive-rational dimension and an affective dimension of trustworthiness [ 37 ]. Next, participants rated the extent to which they found Dr. Lohr’s research credible on a 6-point Likert scale ranging from 1 = “not at all” to 6 = “very much” (6 items, e.g., “I think Dr. Lohr’s future findings will be credible;” “I will be critical of Dr. Lohr’s research results” (reverse-coded); Cronbach’s α = .84).

Next, we measured participants’ own positive attitudes towards LGBTQ issues—the moderator variable in our design—with eleven statements developed from research on sympathy, group attitudes, and allyship [ 38 , 39 ] rated on a 6-point Likert scale ranging from “not at all” to “very much” (e.g., “I think that LGBTQ-related topics receive more attention than necessary” (reverse-coded); “I am open to learning more about concerns raised by LGBTQ people;” Cronbach’s α = .93). Next, we conducted a manipulation check by asking participants to indicate whether Dr. Lohr disclosed being personally affected by their research (“Dr. Lohr stated being personally affected;” “Dr. Lohr stated not being personally affected;” “Dr. Lohr did not say anything about being affected or not”).

Finally, we measured demographic variables (age, gender, occupation, academic discipline) and control variables: general perceptions of researchers’ neutrality (self-developed 6-point bipolar scale with 4 adjective-pairs, e.g. subjective–objective, and 6 distractor pairs, e.g. introverted–extraverted, Cronbach’s α = .81) and Public Engagement with Science (PES) with two measures adapted from a survey by the BBVA Foundation [ 40 ]: a 5-item scale measuring PES frequency (e.g., “How often do you read news about science?” 5-point Likert scale ranging from 0 =“never” to 5 =“almost daily,” Cronbach’s α = .78) and a multiple choice question measuring 15 potential PES experiences during the last 12 months (e.g., “I know someone who does scientific research;” “I visited a science museum”). Participants had the opportunity to participate in a lottery and sign up for more information and were debriefed.

Our randomized groups did not differ in regard to general perception of neutrality in science ( p = .924) or PES (PES frequency, p = .709; PES experiences, p = .533). Table 1 summarizes all means, standard deviations, correlations and internal consistencies of the measured variables.

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https://doi.org/10.1371/journal.pone.0253911.t001

Main effect of being personally affected.

First, we tested the main effect of the researcher’s disclosure of being personally affected on epistemic trustworthiness and credibility of future findings. Laypeople trusted Dr. Lohr significantly more in the “personally affected” condition ( M = 4.92, SD = 0.75) than in the “not personally affected” condition ( M = 4.66, SD = 0.81), t (312) = 2.93, p = .004, d = 0.33, 95% CI d [0.11; 0.56]. For credibility, the difference between the “personally affected” condition ( M = 4.15, SD = 0.96) and the “not personally affected” condition ( M = 4.04, SD = 0.86) was not significant, t (312) = 1.02, p = .306, d = 0.12, 95% CI d [-0.11; 0.34]. Further exploring the two dimensions of epistemic trustworthiness, Dr. Lohr was perceived as higher on integrity/benevolence, t (312) = 3.19, p = .002, d = 0.36, 95% CI d [0.14; 0.59], and on expertise, t (312) = 2.17, p = .030, d = 0.25, 95% CI d [0.02; 0.47] when disclosing being personally affected.

Moderation by pre-existing attitudes.

Second, we tested whether the effect of being personally affected by the research topic on trustworthiness was moderated by participants’ pre-existing attitudes towards LGBTQ issues. Using standardized linear regression, we again found a main effect of condition on trustworthiness, beta = 0.15, p = .004, 95% CI beta [0.05, 0.26]. There was a significant main effect of participants’ pre-existing attitudes, beta = 0.30, p < .001, 95% CI beta [0.20, 0.40] and the condition × attitudes interaction effect was significant, beta = 0.19, p < .001, 95% CI beta [0.08, 0.29], increasing the amount of explained variance in trustworthiness by 3% to R 2 adj = .14. Table 2 summarizes the results. Fig 1A displays the interaction effect and standardized simple slopes analysis further qualifies it: Participants with more positive attitudes towards LGBTQ issues (+1 SD above sample mean) trusted Dr. Lohr more when the researcher was personally affected vs. not affected, beta = 0.34, p < .001, 95% CI beta [0.20, 0.49]. For participants with less positive attitudes towards LGBTQ issues (-1 SD below sample mean), this effect appears to be reversed, yet the simple slope was not significant, beta = -0.03, p = .646, 95% CI B [-0.18, 0.11]. The same pattern of interaction effects emerged for both, integrity/benevolence ( p = .009, total R 2 adj = .14) and expertise ( p < .001, total R 2 adj = .10); full analyses are reported in Appendix B (see https://osf.io/phfq3/ ).

Linear regression plots for the interaction effect of attitudes × condition on epistemic trustworthiness (Fig 1A) and credibility (Fig 1B) with 95% confidence intervals: Participants’ attitudes towards the research topic moderated how a researcher’s disclosure of being personally affected (vs. being not personally affected) by one’s own research was perceived.

https://doi.org/10.1371/journal.pone.0253911.g001

https://doi.org/10.1371/journal.pone.0253911.t002

Regarding our second dependent variable, credibility, we found no main effect of condition, beta = 0.04, p = .456, 95% CI beta [-0.06, 0.13]. However, there was a significant main effect of participants’ pre-existing attitudes, beta = 0.48, p < .001 95% CI beta [0.39, 0.58]: Participants with more positive attitudes anticipated a higher credibility of future research findings in this condition than participants with less positive attitudes. Similar to epistemic trustworthiness, there was a significant condition × attitudes interaction effect, beta = 0.21, p < .001, 95% CI beta [0.12, 0.31], increasing the amount of explained variance in credibility by 4% to R 2 adj = .26. Table 2 summarizes the results. Fig 1B displays this interaction effect: Again, participants with more positive attitudes towards LGBTQ issues (+1 SD above sample mean) anticipated Dr. Lohr’s future research findings to be more credible when the researcher was personally affected vs. not affected, beta = 0.25, p < .001, 95% CI beta [0.12, 0.38]. However, for participants with more negative attitudes (-1 SD below sample mean) this effect was significantly reversed: They rated the future research as less credible when the researcher was personally affected vs. not affected, beta = -0.18, p = .009, 95% CI B [-0.31, -0.04].

Results from Study 1 suggest that LGBTQ researchers are perceived as more trustworthy and their future findings as more credible when they disclose being personally affected by their research topic (i.e., being queer themselves), but only if perceivers hold positive attitudes towards LGBTQ issues. By contrast, holding less favorable attitudes towards LGBTQ issues lead to more skeptical reactions towards personally affected vs. unaffected researchers. This finding shows that learning about a researcher’s personal affection by their research can, indeed, go both ways, as suggested by our theoretical reasoning. On a more general level, our research suggests that public reactions towards “me-search” is a matter of pre-existing attitudes, and, thus, a case of motivated science reception [ 21 , 22 ].

There are some limitations to this first study: As most people in our sample held rather positive attitudes towards the LGBTQ community ( M = 4.93, SD = 1.02; on a scale from 1 to 6), predicted values on trustworthiness and credibility at the lower end of the attitude spectrum are probably less reliable. Also, we did not control for participants’ own identification as belonging to the LGBTQ community. Thus, we cannot differentiate clearly between attitudinal and identity-related effects, which is important because attitudes and identity concerns have a psychologically distinguishable impact on motivated science reception [ 27 , 28 ]. Additionally, replicating our results in a different domain is necessary to be able to generalize our findings. Another question of generalizability that is left unanswered is how such individual experiences with one personally affected researcher might impact laypeople’s perception of the entire field. This calls for more research on the double-edged nature of the moderating effect of preexisting attitudes.

In our preregistered second study (see https://osf.io/c9r4e ), we aimed to replicate our findings in a more diverse sample and with a different research topic that has the potential of polarizing participants even more strongly. We used the same design as in Study 1, but changed the proposed research topic to perceptions of vegans and introduced a vegan vs. non-vegan researcher. Again, we hypothesized that laypeople’s attitudes towards veganism moderate the effects on trustworthiness as well as credibility of future research. Additionally, we tested whether the effect of one researcher being personally affected by their own research generalizes to the broader perception of their entire field. Furthermore, we also explored whether the moderation by attitudes towards veganism prevailed when controlling for self-identification as being vegan (not included in preregistration).

We conducted an a-priori power analysis using G*Power [ 35 ] for detecting the hypothesized interaction effect in a moderated multiple regression analysis ( f 2 = 0.04, based on Study 1, with 1- β = 0.90 and α = 0.05, which resulted in a total sample of N = 265. Anticipating exclusions (see specified criteria) of comparable size as in the previous study, we aimed for a sample of at least 350 participants.

We collected data from 364 participants via mailing lists and social media. Fifty-seven participants had to be excluded due to our preregistered criteria (see https://osf.io/c9r4e ): one participant was younger than 16 years, 31 failed the manipulation check, 10 took less than 20sec viewing the proposal, 12 took less than 3min or more than 20min for participation, 3 had apparently implausible patters of response (i.e., “straight-lining;” identical responses on every single item on more than one questionnaire page in a row). The final sample consisted of N = 307 participants (76% female, 23% male, 1 other) who were between 18 and 79 years old ( M = 33.55, SD = 13.92). Approximately half of the sample (50%) was currently studying at a university, further 40% were working and 10% not working, one person was currently in training. Eighty-five percent were currently studying or already held a university degree (social sciences: 49%, humanities: 17%, natural sciences: 14%, life sciences: 8%, engineering: 6% and other 6%). Most participants did not consider themselves as vegans (89%).

We used the same materials and procedure as in Study 1 (see OSF for full materials: https://osf.io/phfq3/ ). However, we changed the research topic to “perceptions of vegans”. Participants were randomly assigned to two conditions. In the “not personally affected” condition, the researcher Dr. Lohr wrote:

“ I was interested in investigating this research questions not only out of scientific reasons but because , as someone who is not living as a vegan and , thus , not personally affected by my own research , I think we have a need for more evidence-based knowledge regarding the social embedding of vegan lifestyles , which we can acknowledge in everyday life .”

“… because , as someone who is living as a vegan and , thus , personally affected by my own research , I think we have a need for more evidence-based knowledge regarding the social embedding of vegan lifestyles , which we can acknowledge in everyday life . ”

As dependent variables, we again used the 14-item METI [ 36 ] to measure epistemic trustworthiness, but we expanded the measure for credibility of future research by adding one more item (“I would express skepticism towards Dr. Lohr’s future findings”) to better capture the behavioral aspects of credibility (now: 7 items; Cronbach’s α = .86). We also added a measure of participants’ evaluation of the entire field (not the specific researcher) as a third dependent variable. This 12-item scale was adapted from a related study [ 28 ] (e.g., “I think researchers who do research on that topic sometimes lack competence,” “I think it is difficult to apply results from this line of research to reality;” 6-point Likert scale ranging from 1 = “not at all” to 6 = “very much;” Cronbach’s α = .85). Next, participants’ attitudes towards veganism (i.e., the moderator variable) were measured with a 14-item scale adapted from the attitude measure in Study 1 by changing and adding items (e.g., “I think veganism is exaggerated” (reverse-coded) and “I can imagine being a vegan myself;” 6-point Likert scale ranging from 1 = “not at all” to 6 = “very much;” Cronbach’s α = .95).

To reduce exclusions after data collection, participants could proceed only if they answered all attention checks correctly (4 items; multiple choice). We added self-identification as vegan as a control variable (“Do you presently consider yourself a vegan?” yes/no); and an open-ended question about participants’ opinion regarding the researcher being personally affected to explore how laypeople rationalize their opinion. These responses were later coded for valence (positive, negative, mixed, or neutral) and content (deductive and inductive coding) by two raters blind to the specific research question (see Appendix C in the supplementary materials, https://osf.io/phfq3/ ; interrater reliability for valence, Cohen’s κ = .86, p < .01; and for content, Cohen’s κ = .74, p < .01). Again, the questionnaire closed with a sign-up for a lottery and more information as well as a debriefing.

Our randomized groups did not differ in regard to PES (PES frequency, p = .147; PES experiences, p = .101). However, they did differ significantly in regard to the general perception of neutrality in science ( p = .049). Possible implications are addressed in the Discussion. Table 3 summarizes all means, standard deviations, correlations and internal consistencies. In the following, we report our findings for all three dependent variables (trustworthiness, credibility, evaluation of the entire field), consecutively.

https://doi.org/10.1371/journal.pone.0253911.t003

Trustworthiness.

First, we ran the standardized regression model for epistemic trustworthiness. There was neither a significant main effect of condition on epistemic trustworthiness, beta = 0.04, p = .482, 95% CI beta [-0.07, 0.15] nor a significant main effect of attitudes towards veganism, beta = 0.07, p = .205, 95% CI beta [-0.04, 0.18]. However, the hypothesized condition × attitudes interaction effect was significant, beta = 0.22, p < .001, 95% CI beta [0.11, 0.34], increasing the amount of explained variance in trustworthiness by 4% to R 2 adj = .05. Table 4 summarizes the results. Fig 2A and standardized simple slopes analyses show that participants with more positive attitudes towards veganism (+1 SD above sample mean) trusted Dr. Lohr more when personally affected vs. not affected, beta = 0.26, p = .001, 95% CI beta [0.11, 0.42]. This conditional effect was reversed for participants with more negative attitudes (-1 SD below sample mean), who trusted Dr. Lohr less when personally affected vs. not affected, beta = -0.19, p = .020, 95% CI beta [-0.34, -0.03]. The interaction effect remained significant when controlling for participants’ self-identification as being vegan ( p < .001, total R 2 adj = .06). In secondary analyses, we explored the effects on the two facets of epistemic trustworthiness, separately. The same pattern of interaction effects emerged for both integrity/benevolence ( p < .001, total R 2 adj = .08) and expertise ( p = .005, total R 2 adj = .02); full analyses are reported in Appendix D in the supplementary materials (see https://osf.io/phfq3/ ).

Linear regression plots for the interaction effect of attitudes × condition on epistemic trustworthiness (Fig 2A), credibility (Fig 2B) and critical evaluation of the entire field (Fig 2C) with 95% confidence intervals: Participants’ attitudes towards the research topic moderated how a researcher’s disclosure of being personally affected (vs. being not personally affected) by one’s own research was perceived.

https://doi.org/10.1371/journal.pone.0253911.g002

https://doi.org/10.1371/journal.pone.0253911.t004

Credibility.

On credibility, there was no significant main effect of condition, beta = -.07, p = .146, 95% CI beta [-0.17, 0.03] but a significant main effect of attitudes towards veganism, beta = .35, p < .001, 95% CI beta [0.25, 0.45]. As predicted, the condition × attitudes interaction effect was also significant for credibility, beta = 0.25, p < .001, 95% CI beta [0.15, 0.35], increasing the amount of explained variance in credibility by 6% to R 2 adj = .21. Table 4 summarizes these results. Fig 2B and standardized simple slope analyses qualify the interaction effect: In line with the results for trustworthiness, participants with more positive attitudes (+1 SD above sample mean) anticipated Dr. Lohr’s future findings to be more credible when personally affected vs not affected, beta = 0.18, p = .016, 95% CI beta [0.03, 0.32], while the conditional effect for participants with more negative attitudes (-1 SD below sample mean) changed its sign, beta = -0.32, SE ( B ) = 0.14, p < .001, 95% CI beta [-0.47, -0.18]. As before, the interaction effect remained significant when controlling for self-identification as being vegan ( p < .001, total R 2 adj = .21).

Evaluation of the field.

Third, we investigated whether this moderation effect generalizes to the evaluation of the entire field of veganism research. There was no significant main effect of condition, beta = -.00, p = .989, 95% CI beta [-0.10, 0.10] but a significant main effect of attitudes, beta = -.41, p < .001, 95% CI beta [-0.51, -0.31]. Again, we found the hypothesized condition × attitude interaction effect, beta = -.27, p < .001, 95% CI beta [-0.37, -0.18], increasing the amount of explained variance in critical evaluation by 7% to R 2 adj = .27. Again, Table 4 summarizes these results and Fig 2C and standardized simple slopes analyses further qualify the interaction effect: Participants with more positive attitudes towards veganism (+1 SD above sample mean) were less critical of research on veganism when Dr. Lohr was personally affected vs. not affected, beta = -0.28, p < .001, 95% CI beta [-0.41, -0.14]. By contrast, this conditional effect was reversed for participants with more negative attitudes towards veganism (-1 SD below sample mean), beta = 0.27, p < .001, 95% CI beta [0.14, 0.41]. This interaction effect also remained significant when controlling for self-identification as being vegan ( p < .001, total R 2 adj = .28).

Participants’ opinion.

Overall, participants who responded to the open-ended question expressed mostly negative opinions about the researcher being personally affected by his own research (negative: 48%, neutral: 21%, positive: 17%, and mixed: 14%). The most frequently mentioned (negative) remark was that a “me-searcher” might be biased towards their research (60%; e.g., “ By introducing himself as being affected , I fear he cannot evaluate the results of his research objectively ”). The second most frequently mentioned remark was that such idiosyncratic relevance is irrelevant (24%; e.g., “ It wouldn’t make a difference ”). Positive remarks were mentioned less frequently: Participants ascribed more motivation (11%; e.g. “ I think interest , also personal interest , is an important prerequisite for determined research ”) or knowledge about the topic (8%; e.g. “ Very good , most likely , he thus is knowledgeable about the subject matter and can conduct the study in a more purposeful manner ”) to the “me-searcher”, or recognized the transparency (7%; e.g., “ The main thing is transparency . People are always biased , perhaps even unconsciously ”; for more details, see Appendix C in the supplementary materials: https://osf.io/phfq3/ ).

In Study 2, we replicated the moderation effect of preexisting attitudes on the effect of a researcher disclosing being personally affected (vs. not affected) by their own research on participants’ epistemic trustworthiness and credibility ascriptions regarding the research and researcher’s future findings. Further, we showed that this effect generalizes to the evaluation of the entire research area. Here, positive attitudes towards veganism determined how learning about an openly vegan researcher impacted participants’ perceptions of trustworthiness and credibility as well as the evaluation of the entire field of veganism research compared to learning about a non-vegan (i.e., non-affected) researcher. Participants who held more positive attitudes towards veganism reported more trust, higher anticipated credibility of future findings, and a less critical evaluation of the field when confronted with a vegan researcher. Conversely, for participants with less positive attitudes this effect was reversed. The moderation by positive attitudes towards veganism persisted when controlling for participants’ self-identification as vegans. Overall, the interaction effects observed in Study 2 explained similar amounts of variance as in Study 1 (epistemic trustworthiness: 3% vs. 4%, and credibility: 4% vs. 6%). Further, qualitative analyses revealed that most participants reported negative–or, at least, mixed–perceptions of a “me-searcher” (e.g., “me-searchers” may be biased, but also highly motivation and knowledgeable), which corroborated our theoretical prediction that “me-search” may be a double-edged sword. Interestingly, these qualitative findings seem somewhat contradictory to the quantitative findings, according to which there was no main effect of researchers’ idiosyncratic affection by their research topic.

In Study 2, one caveat is that the groups differed significantly in regard to participants’ general expectations of neutrality in science. Participants who read about the personally affected researcher had weaker expectations of neutrality; yet, when added to the regression model as a control, the pattern of results remained unchanged (see Appendix E in the supplementary materials, https://osf.io/phfq3/ ). Further, as a second caveat, we show that participants generalized their perceptions to the overall field of veganism research. However, this research area might be considered quite narrow and, thus, future research should investigate how far such generalization processes stretch out to perceptions of broader areas of research (e.g., health psychology).

General discussion

In two studies, we show that laypeople’s perception of researchers who disclose being personally affected by their own research can be positive as well as negative: The effect of such “me-search” was moderated by laypeople’s preexisting attitudes. Queer or vegan researchers were perceived as more trustworthy and their future findings were anticipated to be more credible when participants had positive, sympathizing attitudes towards the related research object (i.e., LGBTQ community or veganism). When participants’ attitudes were less positive, this pattern reversed. In Study 2, we extended our research from individualized perceptions of single researchers and their findings to evaluations of the entire field of research. Participants who were confronted with a personally affected researcher seemed to consider this person a representative example and generalized their judgment to their evaluation of the entire (though here quite narrow) research area.

We explored epistemic trustworthiness in more detail in both studies, namely the cognitive-rational facet of expertise and the affective facet of integrity/benevolence: Both were impacted by researchers’ disclosure of being personally affected, although effect sizes for expertise were descriptively smaller than for integrity/benevolence. This points to “me-search”–when received positively–possibly adding to the perception of competence-related aspects like a deeper knowledge of a phenomenon (e.g., via anecdotal insights) [ 12 – 14 ] and, even more so, warmth-related aspects like seeming more sincere, benevolent, transparent and, thus, approachable [ 15 , 16 , 41 ]. Disclosing such personal interest in a scientific endeavor might be able to bridge the stereotypical perception of cold and distant “science nerds” by revealing passionate, human and, thus, more relatable side of a researcher. When received negatively, however, “me-search” might be regarded as harboring vested interests, which casts doubts on a researcher’s neutrality and objectivity [ 8 – 11 , 42 ].

In general, the main models tested here explained between 5% and 28% of variance which may not appear impressive at first glance. However, our studies posed a very strict test of the effects of “me-search” by only using a subtle manipulation sparse in information followed by measures of very specific perceptions which might have contributed to an understatement of the real-world impact.

“Me-search” neither automatically sparks trust nor mistrust in laypeople, even if their explicit opinions seem rather negative. In line with assumptions from motivated science reception [ 22 , 43 ], our findings suggests that the ambivalence of the fact that a researcher is personally affected can be seized as an opportunity to interpret the situation in a manner that best fits to preexisting attitudes: Researchers, their findings and even their entire field of research are evaluated–even before learning about specific findings–based on prior attitudes towards the research topic. We show in Study 2 that the moderation effect of participants’ positive attitudes towards the respective research topic (i.e., veganism) prevails when controlling for self-identification with the topic (i.e., being a vegan). This suggests that, indeed, in motivated reasoning attitudinal and identity-related processes can be differentiated: Here, social identity protection could be ruled out as alternative explanation for the effects of pre-existing attitudes. Noteworthily, we demonstrate that motivated science reception already operates when the results are not (yet) known. This points towards a perceptual filter made up of pre-existing attitudes that is activated when confronted with scientific information and leads to biased pre-judgments: Ambivalent cues (i.e., “me-search”) are prematurely interpreted in line with prior attitudes without actually knowing whether the new scientific information will be attitude-consistent or inconsistent (when, later, results are reported).

Future research

Future research on the motivated reception of “me-search” should focus on three open questions. First, while we consider it a strength of our studies that the results of the proposed research project were not yet known, it might be interesting to see how being personally affected or not interacts with the perceived direction of the communicated scientific results (e.g. supporting vs. opposing a certain position): To what extent can the first, premature evaluation of a “me-searching” researcher be adapted if the actual results are inconsistent with this pre-judgment?

Second, the investigation of what specific characteristics of “me-search” are instrumentalized by benevolent or skeptical perceivers might not only provide practical tips on how to handle being personally affected (e.g., in science communication) but also important theoretical insights on the building blocks of trust in science and researchers (see discussion above regarding the effects on the facets of epistemic trustworthiness). As one example, knowing that a qualitative level of knowledge is highly valued could further research on the trust-benefit of enriching statistical evidence with anecdotal and narrative elements [ 44 , 45 ]. As second example, we argue that researchers’ self-disclosure of being personally affected by their research might signal transparency and, thus, improve the perception of the trust facets integrity and benevolence. Yet, even the disclosure of not being personally affected could have such an effect on a researcher’s reputation and, at the same time, it might be less ecologically valid (as, presumably, it is rather unusual to explicitly state to not be affected by something). Introducing a control group without any information about a researcher’s relation towards their research object might bring light to this.

Third, we demonstrated the moderation effect of preexisting attitudes for two research areas (i.e., LGBTQ and veganism) and in different populations. Yet, further research should investigate whether this effect will hold up for other areas, more diverse samples and different kinds of “me-search”, as well. For example, in some research fields being personally affected by the research might be perceived as more morally charged than in others and, thus, having stronger polarizing effects [ 46 ]: While, in veganism-research, “me-search” might be grounded in an ideological choice (e.g., thinking its morally wrong to consume animal products and, thus, being vegan), having a stroke and, following, studying stroke-related brain plasticity is likely perceived as less ideological. Also, different scientific methods (typically) used in a field might impact the perceptions of “me-search” depending on how prone for subjectivity these methods are perceived to be (e.g., qualitative “me-search” like autoethnographic analyses might be perceived more critically than when using seemingly objective, quantitative methods like physiological measures). Further, researchers who are not directly personally affected by their research but “merely” interested in something for personal reasons (e.g., being highly empathetic towards queer concerns without identifying as queer) might not profit from disclosure of such personal motivations: Such researchers might be perceived as impostors [ 47 ] lacking the expertise stemming from directly firsthand experiences.

Practical implications

Finally, for the applied perspective on public engagement with science, it should again be noted, that motivated reasoning processes are activated even before specific results are presented (e.g. before hearing a talk or reading about a study). This might be important, as judgments are quickly formed and remembered [ 48 , 49 ] and, therefore, the first impression of a researcher might set the tone for further interactions and, particularly, for the acceptance and implementation of their findings. This emphasizes the importance of researchers knowing their audience (and their attitudes) when engaging in science communication.

Of course, there are also ethical considerations concerning “me-search”: Researchers should always declare any conflict of interests when conducting research [ 50 , 51 ]. Failing to disclose being personally affected by one’s own research might backfire severely on researchers’ reputation–especially concerning their trustworthiness and the credibility of their findings–and in particular, when this information is disclosed by someone else and not themselves. At least for achieving positive reputational effects, it seems researchers need to freely initiate the disclosure of limitations and problems themselves [ 41 , 52 ]. A possible solution for reaping all the benefits and protecting against the potential harms of engaging in “me-search” might be to actively seek out mixed research teams. Including affected as well as non-affected individuals in research projects might be worth considering from the stance of the public’s trust in science: It enables deep, even personal insights to the studied phenomenon, while still securing balanced perspectives and impartiality.

Neuroanatomist Jill Bolte Taylor became famous for turning her “stroke of fate” into productive and well-selling “me-search”. Yet, she was praised as well as heavily criticized for mixing her personal and scientific motivations: When research is also “me-search”, it can be perceived positively as well as negatively depending on laypeople’s preexisting attitudes towards the research object. Researchers who disclose being personally affected by their own research can benefit from this disclosure in terms of trustworthiness and credibility when it is perceived by laypeople with positive attitudes; however, for audiences with more negative attitudes this effect is reversed and disclosure can be harmful. One experience with a personally affected researcher might be enough to impact the evaluation of the whole field. Thus, openly acknowledging “me-search” in one’s research is an ambivalent matter and its communicative framing as well as the targeted audience should be well considered.

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We asked 6 scientists what inspired them to pursue a career in science. Here’s what they said

Deputy Chief of Staff, The Conversation

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As you read this, scientists the world over are rushing to find out more about the COVID-19 Omicron variant.

Indeed, if there’s anything the pandemic has made clear, it’s that the importance of scientific research can’t be understated in today’s world.

As we embark on a new year, hopefully with more progress on the COVID-19 front, we asked six authors of The Conversation to reflect on what first sparked their interest in science.

Read more: Hit hard by the pandemic, researchers expect its impacts to linger for years

Cathy Foley

Australia’s Chief Scientist

It was my brothers’ high-school textbooks, I kid you not! I loved poring over the Harry Messel textbooks as a 10- or 11-year-old. They were beautifully illustrated, with nature drawings and detailed experiments set out in a visual format. And I’ll never forget the photo of a dissected rat.

Then when I got to years 11 and 12 at school, the six-volume Harvard Project Physics sold me completely. It has a strong historical narrative, which is unusual in a science textbook and really worked for me.

I still have both sets of textbooks on the bookshelf in my home office. But even though I wanted to be a scientist from a young age, I didn’t know it was open to me so I didn’t dare express it. That final step only came in third-year experimental physics, when I discovered new properties of liquid crystals no one had found before. There was no going back.

Bronwyn Carlson

Professor of Indigenous Studies and Director of The Centre for Global Indigenous Futures, Macquarie University

In 2008 I made my first Facebook post. I was in the middle of a PhD, conducting interviews with Aboriginal people about their identity and involvement in the Aboriginal community. Several spoke about how they expressed their Aboriginality on Facebook, by sharing images and forming connections.

This piqued my interest; Facebook was still new, having opened to the public just two years prior. I hadn’t considered issues of identity or community in these still-novel digital settings. Back then, people tended to separate life into the offline “real” world and the online “virtual” world – which by implication was not “real”.

I became interested in whether being Aboriginal online attracted the same sort of scrutiny as Aboriginal people regularly experienced offline. It turned out those with Facebook profiles experienced high levels of surveillance around their identity. I guess regardless of being online or offline, being Indigenous can attract violent behaviour from settlers.

Postdoctoral Research Fellow at the Centre for Astrophysics and Supercomputing, Swinburne University of Technology

I have always been curious about the world and universe we live in. As a child I remember catching my poor mum off-guard, at 7.30am mind you, with the questions: “why do we exist?” and “What was there before the universe?”

It was a lot for 8-year-old me to be contemplating. But after watching all the Discovery Channel, National Geographic and History Channel documentaries I could possibly get my hands on, my mind was constantly in awe of such questions.

I genuinely can’t remember a time I haven’t been fascinated with the wonders of life. Learning physics in high school was the pinnacle of me beginning to understand why the universe is the way it is. This passion led me to where I am today – an astrophysicist and data scientist trying to make sense of the universe (and other things) via observations and data analysis.

Russell D.C. Bicknell

Postdoctoral Researcher in Palaeobiology, University of New England

When I was about five years old, my father showed me the fossil of an extinct animal called a trilobite: ancient organisms that lived within even older oceans. They evolved long before the dinosaurs, and had gone extinct just before the first of the giant vertebrates (animals that have a backbone).

In doing so, my father had introduced me to the record of organisms that were no longer alive – and furthermore, that people who studied these animals are called palaeontologists. From this point on, I was motivated to understand more about these extinct groups.

This led me down the road of studying evolution, ultimately resulting in me becoming an evolutionary palaeontologist. Now, rather true to my childhood origins, I regularly study trilobites and am interested in documenting many different aspects of arthropod evolution.

Jenny Graves

Distinguished Professor of Genetics and Vice-Chancellor’s Fellow, La Trobe University

I was a scientist for 20 years before I defined myself as “a scientist”. I was many things: harried lecturer, canny grant-seeker, cynical academic, chameleon mother and wife of shire president.

The event that stopped everything, and focused my attention on science, was a near-fatal brain bleed when I was 50 – followed by life-saving neurosurgery and an 18-month recuperation. During my rehabilitation, a kind visitor remarked comfortingly, “Now you have the space to decide what you really want to do with your life!”

I was overwhelmed by the realisation that what I really wanted to do was at the core of what I had been doing for 20 years: science! Just more, and better, with commitment and immersion.

Yvonne Wong

Associate Professor of Physics, University of New South Wales

The American physicist Sidney Coleman once said:

The career of a young theoretical physicist consists of treating the harmonic oscillator in ever-increasing levels of abstraction.

My journey into theoretical physics indeed began with a harmonic oscillator: the pendulum. Specifically, the formula relating the period of a pendulum’s swing ( T ) to its length ( l ) and gravity ( g ), which I found in a textbook at the age of about 15:

T  = 2π√( l / g )

I was always good at maths. I also liked the idea that a set of universal principles governs all natural phenomena. But to see the latter expressed in terms of the former so cleanly was an epiphany.

I spent many hours pondering the 2π and the square root. More obsessions followed, from plucked violin strings to nuclear fission.

But what sealed it in the end was Douglas Giancoli’s textbook Physics: Principles with Applications , which I came across at about age 16. The last two chapters were on “Elementary Particles” and “Astrophysics and Cosmology”. The rest is history.

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• How to Answer “What...

How to Answer “What Motivates You?” - With Examples

11 min read · Updated on October 26, 2023

Knowing how to explain what motivates you tells an interviewer that you not only can do the job - you'll enjoy it, too

When a recruiter or hiring manager asks, “What motivates you?” it sounds like a simple-enough question and one that should be easy to answer - but this is another one of those open-ended questions that need a bit of preparation to answer effectively and keep you in the running for the job.

While there might be many things that motivate you, your answer must be crafted to align with the specific position you're after and the company hiring you to do it.

Why do interviewers ask “What motivates you?”

This question is similar to asking  “What makes you unique?” It's meant to discover whether or not you're the right fit for the job and, more importantly, if you'll fit within that company's particular workplace  culture and goals.

It provides insight into how and why you're motivated to be a successful employee, as well as what fulfills you in your job or career, which in turn offers some additional insight into your personality and approach to work. All these things - plus your skills and experience - help the interviewer to determine whether you're the best person to hire.

It is important to remember that employers who ask what motivates you are not asking you why you've decided to pursue your career options or apply for their open position. They are simply trying to figure out your motivations and drive to do a great job, achieve your mission, and contribute to your employer's success.

“What drives you?” and other ways this question is asked

Some interviewers won't ask this specific question. You need to recognize it when it's asked in different ways, so you can still provide the answers they're after. Instead of “what motivates you?” you might hear:

What inspires you?

What drives you to meet challenges?

What excites you about your job (or about working in general)?

What drives you to be successful?

What makes you want to get up every day for work?

How to prepare an answer to “What motivates you?” 

As with all interview preparation, begin by researching the company in detail. The more you know about the company (and the position), the more you can tailor your answer to match the company's needs. Try to learn about the employer's mission and values, as that can be critical in framing your answers.

In most cases, the hiring manager is asking this in the context of your work life, not your personal life. Most importantly, don't start off with the obvious answer of “a good salary” or “excellent benefits.” It's a given that these things are generally part of everyone's motivation for taking a job and, for the right candidate, these discussions come later in the hiring process.

Possible motivations to focus on as you develop your answer

Taking on or overcoming challenges

Developing new skills

Working with others

Working independently

Having little (or more frequent) direct supervision

Being part of, or leading, a team

Teaching or mentoring others

Creating new processes or improving existing ones

Learning new things

Being innovative or creative

Having challenging goals and deadlines

Aligning your answer with the position you're seeking

As we noted, it's important to know as much as possible about the employer and the job you're seeking, so that you can tailor your response to align with the position. For example, if you're seeking a job dealing with data and analysis, you should try to include those concerns in your answer. You can find an example of this type of data-focused answer in our sample answer section below.

One way to ensure that your answer aligns with the position is to review the job description. Figure out which responsibilities seem to inspire you and build your answer around those duties. Remember to be honest with yourself as you do this, since your response will be more believable if it truly conveys your motivations.

It's also important to not stray too far from that alignment. If the job you're seeking requires a great deal of collaboration with others, then you shouldn't respond by talking about how much you love studying spreadsheets by yourself in a corner office.

Other factors to consider as you create an answer

Consider your strengths . Generally, what motivates someone is also what they're good at, so your answer can highlight skills as well as motivation.

Reflect on the past. Think back to one of your best days at work. Why was it such a good day? What were you doing? Who were you working with? What made you happiest?

Use actual examples. Sharing a specific example from your current job or a previous position means backing up your motivation with the skills that will also make you successful in the job. This often makes a recruiter sit up and take notice.

Keep it short - or as short as possible . Be sure your answer isn't too long or rambling. Keep it as short as possible while still getting across what motivates you the most.

Stay positive. Don't frame your answers using negative examples about you or about others. Share the things you enjoy doing and show how they've helped you to be an excellent employee in all your jobs.

Be honest. Hopefully, you're applying for a position that you really do feel is a good fit for your skills and abilities, as well as for what drives you to be successful. That said, it's important to be honest about your motivation for a job, or it's quite possible you won't have the job for long once your employer discovers you're not a great fit. For example, being motivated by leading a team and consistently interacting with others is not the same as being fulfilled by working mostly on your own crunching numbers or researching data. Neither is good or bad. It's just a question of which one is best for you and that specific role.

Use the STAR method . Describe your motivation examples around S ituations, T asks, A ctions, and R esults. The benefit of this method is that it can show how your motivation ultimately benefited your past company or could benefit a future one. What's more, you end up telling a story rather than just rattling off an answer. That approach can make you sound more interesting and make the interviewer more interested in you.

Practice. Share your answer with a family member or friend and get their feedback. Practicing will help you to answer confidently and concisely.

If you're interviewing for your first full-time job, talk about what motivated you while working in an internship or volunteer role. The outcome should be the same: to convey what's meaningful to you in a job and help the company to see that you'll be a motivated employee who's a good fit for their role.

Sample answers to “What motivates you?”

As you develop your answers, consider the things that attracted you to your current career or specific job. Think about why this kind of work feels right for you and how you've become even more talented over time.

Hopefully, you'll discover more about why you're after any specific position and, in turn, be able to clearly communicate that to the hiring manager or recruiter. Here are some examples to get you started:

Example of someone motivated by learning and skill development

“Learning new skills really motivates me. It's so satisfying to see myself improve as I gain more knowledge about a job or market sector. In my last job, I consistently signed up for training or courses that would grow my skill set, paying for some out of my own pocket. I really believe that ongoing learning makes you more innovative and valuable in the workplace.”

Example for someone motivated by a desire to solve problems

“ I've been coding since middle school, when I was first exposed to it. My mom is a Software Developer and helped me whenever I needed it. Coding has been “it” for me ever since and I've become an expert in Java and C++. I think about coding from the minute I wake up until I go to sleep. Solving problems with code is what challenges me, motivates me, and drives me to be successful. ”

Example for someone who loves organizing projects and activities

“ I'm addicted to planning! Being organized at work and at home drives me to make sure I have enough time to achieve my goals and give my best in all I do. It ensures that I don't overtask myself, so I can focus on doing quality work and not get burned out by working long hours on any one project. Good time management helps me to maintain consistently excellent standards.”

Example for someone who's motivated by serving others

“ Providing outstanding customer service is what drives me. I worked as a Mobile Sales Associate for a local credit union. The days were hectic with solving customer issues and answering questions. I worked hard to understand their queries and explain the how and why of our processes and operations. It really motivated me and upped my confidence whenever customers gave me a great review and a high rating.”

Example for a team player or leader

“I was a Team Lead in my last position, managing a team of 10. Our task was to improve outcomes, so the team had to work efficiently and deliver consistently accurate results. I made it my goal to streamline the team's processes and be more productive with less “busy work.” Working with a team to complete tasks accurately and ahead of schedule was and is what drives me every day. I want to help any company I'm with to always meet their bottom line.” 

Example for someone who's driven by managing successful teams

“I've been responsible for directing software development teams and implementing repeatable processes for a variety of companies. My teams achieved 100% on-time product delivery for six straight months. The challenge of finishing the projects ahead of schedule and successfully managing teams to reach our goals is the kind of thing that's always motivated me.”

Example for a person who's driven to get results

“I'm motivated by results. I'm always excited when I have a tangible goal to meet and enough time to develop a sound strategy to accomplish it. In my current job, we have very aggressive quarterly and yearly goals. I was tasked to work with my manager and my team to create a month-by-month strategy to meet our quarter-end and year-end numbers. Accomplishing that was a great thrill and made me even more result oriented.”

Example for a person who's motivated by data

“I love numbers. Analyzing data and providing results really drives and motivates me. I love getting my hands on a spreadsheet to figure out what's driving the numbers and sharing my conclusions. In my current position, I generate our monthly sales analytics reports. Being able to provide this essential information is really motivating because the data from these reports helps the company to determine its sales goals for the upcoming months and clarifies how the organization will move forward, and I know I've made a big contribution to that.”

Proper preparation can help you approach your interview with greater confidence

Knowing what motivates you means you can clearly and confidently convey to an interviewer that you not only have the skills to do the job but that you will also fit well with the company's culture and values. As long as you've done your research and preparation, you'll conquer your fear of this particular interview question and be ready to promote yourself as the best candidate to hire.

Your motivators are simply what you love to do and, as the saying goes, “find something you love to do and you'll never work a day in your life.”

Learn how to ace every part of your interview with our  expert interview tips , and let our free resume review make your resume shine! This article was originally written by Lisa Tynan and has been updated by Ken Chase.

Recommended reading:

Ask Amanda: How Can I Be More Confident During Interviews?

5 Tricky Interview Questions and How to Handle Them

What to Say at an Interview: 5 Boring Interview Lines to Avoid

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As the need for highly trained scientists grows, a look at why people choose these careers.

What leads people to a career in science?

It’s an important question because the road to a successful career in science – as with technology, engineering and mathematics, the other STEM fields – can be challenging, often requiring a Ph.D. or other postgraduate training. And once in their fields, there can be political and economic pressures with which to contend. The Bureau of Labor Statistics projects workforce shortfalls for many science fields, though the projected needs differ across the life, physical and natural sciences.

So, what draws people into these careers? Roughly one-third (32%) of working Ph.D. scientists said a main motivator for their career path was a lifelong interest in science and desire for intellectual challenge, according to the 2014 survey . 

Many of these scientists reported an interest and curiosity in science or the natural world starting in early childhood. For some 12% their curiosity was fostered by parents and other family members who brought them in contact with scientists and science labs, nature or science and technology museums. Others (27%) remembered effective mentoring and encouragement from teachers whether in elementary school, graduate school or somewhere in between. And some 17% talked about the importance of lab and field work, often at the high school and college levels, which spurred their interest in a science career.

Here are some of their stories:

In second grade, I read a scientific explanation of something I experienced every day. That flash of insight stimulated an intense curiosity of how things work. I knew from then on that I would be a scientist. – Molecular biologist, man, age 60

I’ve had a passion for science ever since I can remember, from age 4 or so. My second grade teacher was a big influence on building that passion. She was an amateur naturalist and taught us a lot about ecology and the natural world. In high school, I discovered my passion for molecular biology. I remember learning of the [Meseleson-Stahl] experiment in my AP Biology class, and I remember thinking, “Yes, this is exactly the kind of thing I want to understand.” – Microbiologist, woman, age 50

I found science interesting. Growing up, I had a chemistry set and telescope (later building my own), and because of these, read a lot about chemistry and astronomy. My father took me rock collecting and brought chemicals home for me to analyze. Those experiences led to a degree (BS and MS) in Physics and a Ph.D. and career in Geophysics . – Geophysicist, man, age 65

My father is a physicist. When I was young (I probably was 4 or 5), we would go to his building after dinner and run around the corridors and labs. I remember one of the grad students tipping a [vacuum flask] of [liquid nitrogen] to create a fog cloud – very impressive. – Materials Scientist, woman, age 49

My interest in science was first piqued as a seven-year-old observing a full moon through the telescope of a friend. A couple of years later, my interest in space and the possibility of space exploration was promoted by the start of the manned launches into space in the early 1960s, and in a written essay in fourth or fifth grade I even expressed interest in science as one of three possible career paths …. – Medical Physicist, man, age 63

My entire childhood was steeped in experiences in the natural world and in scientific observation/experimentation. Both my parents are scientists. One memory that stands out in particular is of a canoe trip to the boundary waters in northern Minnesota when I was about 12, where I saw carnivorous plants in the wild for the first time – beautiful, huge, floating mats of pitcher plants …. – Ecologist, woman, age 35

While many scientists mentioned childhood experiences facilitated by their families, some 6% said science media was particularly influential in their career path. These scientists mentioned a range of media including books such as Microbe Hunters; magazines such as National Geographic and Scientific American; TV programming on PBS and commercial stations such as NOVA, Carl Sagan’s Cosmos, Mr. Wizard and Bill Nye the Science Guy.

One scientist noted:

When I was a child, my exposure through media of what science was and what scientists did influenced my career decisions. My grade school education in science was very poor, which increased the importance of the media exposure. – Biotechnologist, woman, age 54

Scientists’ reflections often touched on multiple themes; some emphasized their curiosity about the world and others emphasized the role of people in their lives who fostered their interests. As one scientist put it: “I love puzzles and to me, science is the ultimate puzzle.”

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How to Stay Motivated in Research

Motivation is an enthusiastic desire or willingness to continue making progress in a particular role, or to work towards a particular goal. Staying motivated can be difficult for researchers. Failed experiments, negative results and lack of useable data can leave researchers feeling discouraged. The lengthy time gap between starting a research project and the resulting publication can wear down enthusiasm.

“Persevere!”, people say. But perseverance without motivation is often short-lived. Without motivation, work can leave you feeling unsatisfied and uninspired. Don’t let that happen. Here are some tips for staying motivated to keep working towards your goals:

Remember Why You Do Research

It’s hard to stay motivated when you’ve lost sight of your end goal; a common occurrence in research when all the other stresses and strains of daily lab-life weigh you down. Why did you get into research in the first place? Perhaps you hoped to make a real difference through your research. Young scientists often start out with the ambition to find a cure or unearth a discovery that can change the world, unaware of how difficult the path to a breakthrough truly is. Remind yourself why you are working on your research project, and that everything you do and every step you take is important and serves a purpose.

Keep Up with Recent Discoveries

You'll see the progress being made in the field and be reminded of how your research project can fit in as a piece of the puzzle. You may be inspired from seeing your project with a “big picture" perspective and gain the motivation to keep it moving forward. Keep current with your field with our 20 weekly Science Newsletters. Subscribe Now >

Take Small Steps and Reward Yourself

Research is a long journey to the end result. Waiting for reward in the ultimate goal, such as a publication, can be tiresome. Don’t wait until a major accomplishment to reward yourself. Set smaller milestones within your journey and celebrate reaching them. This will make the process itself motivating. If your goal is to finish writing your thesis, reward yourself for writing every 10 pages. If your goal is to publish a paper on your project, celebrate each complete set of data you obtain.

Expect Imperfection

Nothing hinders motivation more than realizing you can’t reach your goals. Sometimes this is because you’ve set unattainable goals or unrealistic expectations. You’ve probably read amazing publications, each telling a story of immaculately planned experiments that resulted in an almost perfect series of figures comprised of high quality data. What you didn’t see in those publications is how the authors got there—the failed experiments, the mistakes, and the hypotheses that led nowhere. The truth is researchers encounter failed experiments, non-statistically significant results, or conflicting data more often than they would like to admit. This is the reality of research. Expecting that some things will not go perfectly as planned can prepare you to adapt to your situation, prevent you from getting discouraged, and help you stay motivated.

I would advise the next generation of scientists to stay curious and stay determined in their work. Science is not easy, and we often face experimental failures and make erroneous hypotheses. Be persistent and keep trying; when the going gets tough, do not lose sight of your initial motivation to do science. Stay firm in your belief that you can contribute to the scientific community and improve the lives of people through scientific innovations, novel discoveries, and development of improved treatments for diseases.

Look Beyond the Bench

You’ve heard the saying “don’t put all your eggs into one basket.” As a researcher, it’s tempting to put all your focus in one basket: what you do at the bench. The result may be negligence of other important aspects of your career such as their communication, networking, or writing skills. Realize that it’s not just what you do at the bench that matters. Adopt a more multifaceted view of your career. Taking ownership of your personal career growth will help you stay motivated during difficult moments when what you do at the bench isn’t working out. Regardless of what happens at the bench, you can still feel satisfied about the well-written review article you’ve just produced, or with the new connections you just formed at a networking event. These small wins beyond the bench can boost your motivation.

Read Seven Networking Tips for Scientists >

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We all have to stay motivated to continue making scientific progress. How can we help one another stay motivated?

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Research Motivation – Motivational factors for opting research

In this article, let us understand the research motivation or what are the key motivational factors for students who opt for research.

Research Motivation Reasons

The research motivation may be either due to one or more of the following reasons:

• The desire to get a research degree along with its significance.
• The desire to face challenges in solving the unsolved problems. For example, concern over practical problem initiates research.
• The desire to get the intellectual joy of doing some creative work.
• The desire to be finding solutions which service to society.
• The aspiration to get respectability.

However, this is not an exhaustive list of research motivation factors for people to undertake research studies.

Many more factors such as government directives, employment conditions, curiosity about new things, social thinking and awakening may as well motivate people to perform research operations.

Objectives of Research

The purpose of the research is to know the answers to questions through the application of scientific procedures.

The main aim is to find out the truth or to know the answer which has not be known yet.

Every research study has its own purpose, and research objectives can be classified into following broad groupings.

• To get familiar with a phenomenon or to achieve new insights into it (study with this object is termed as exploratory or formulative.
• To put accurately the characteristics of a particular individual, situation or a group (study with this object is known as descriptive research study).
• To determine the occurrence of which something happens or association with something else (study with this object is known as diagnostic research study).
• To test a hypothesis of a causal relationship between variables (the study is known as hypothesis-testing research studies).

Significance of Research

In the context of Hudson Maxim. Progress is possible with increased amounts of research.

Research instructs scientific and inductive thinking, and it promotes the development of logical habits of thinking and organization.

The increasingly sophisticated nature of business and government has focused their attention on the use of research in solving operational problems.

Nowadays, our economic system highly relies on the research to formulate the government policies.

For example, the budget of any country requires the analysis of people’s needs with expected expenditure required to meet those needs. In such conditions, research is heavily required to equate the cost of probable revenues to cover the cost of meeting people’s needs.

Research Process – Importance of knowing the process

Research methodology gives a student the necessary training in gathering material and arranging that information.

It also helps a student for participation in the field work whenever required.

It also trains in techniques for the collection of data which is appropriate to particular problems,

The research process also helps in the course of using statistics, questionnaires, controlled experimentation, recording evidence, sorting it out and interpreting it.

Importance of knowing the research methodology or how research is carried stems from the following considerations:

• The knowledge of methodology provides proper training especially to the new research worker and enables him to do better research.
• The methodology also helps the researcher to develop disciplined thinking or to observe the field objectively.
• Knowledge of how to do research will instruct the ability to estimate and use research results with reasonable confidence.
• Research methodology knowledge enables the consumers of research results to evaluate them and make rational decisions.

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Health care professionals’ motivation, their behaviors, and the quality of hospital care: A mixed-methods systematic review

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Supplemental digital content is available in the text.

Health care professionals’ work motivation is assumed to be crucial for the quality of hospital care, but it is unclear which type of motivation ought to be stimulated to improve quality. Motivation and similar concepts are aligned along a motivational continuum that ranges from (intrinsic) autonomous motivation to (extrinsic) controlled motivation to provide a framework for this mixed-methods systematic review.

This mixed-methods systematic review aims to link various types of health care professionals’ motivation directly and through their work-related behaviors to quality of care.

Six databases were searched from January 1990 to August 2016. Qualitative and quantitative studies were included if they reported on work motivation in relationship to work behavior and/or quality, and study participants were health care professionals working in hospitals in high-income countries. Study bias was evaluated using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields. The review protocol was registered in the PROSPERO database (CRD42016043284).

A total of 84 out of 6,525 unique records met the inclusion criteria. Results show that health care professionals’ autonomous motivation improves their quality perceptions and work-related behaviors. Controlled motivation inhibits voicing behavior, but when balanced with autonomous motivation, it stimulates core task and proactive behavior. Proactivity is associated with increased quality of care perceptions.

Practice Implications

To improve quality of care, policy makers and managers need to support health care professionals’ autonomous motivation and recognize and facilitate proactivity as an essential part of health care professionals’ jobs. Incentive-based quality improvements need to be complemented with aspects that stimulate autonomous motivation.

It is widely assumed that health care professionals’ work motivation is beneficial for the quality of patient care in hospitals ( Berenson & Rice, 2015 ; Franco, Bennett, & Kanfer, 2002 ). Health care professionals’ work motivation is increasingly being investigated, as scholars draw on the positive effects of motivation on performance that were observed in the organizational literature ( Cerasoli, Nicklin, & Ford, 2014 ; Kim, Kolb, & Kim, 2013 ). However, it is unclear whether these findings apply to the quality of patient care, as studies from the field of organizational research tend to focus on individual-level employee outcomes, such as performance or employee behavior, rather than on team or organizational outcomes ( Kim et al., 2013 ). In a complex system as health care, quality follows from the performance of many independent actors working together in a connected system, which means that performance at the individual level does not necessarily predict the outcomes of the system: quality of care (Griffin, Neal, & Parker, as cited in Gagné, 2014 ; Hollnagel, Wears, & Braithwaite, 2015 ).

The inability to determine whether and how health care professionals’ motivation affects patient care is problematic, because it hampers the development of effective motivation-based policies and interventions to boost care quality. Moreover, current motivational strategies may even have unintended consequences. For example, financial incentives, which are widely popular in health care ( Berenson & Rice, 2015 ; Flodgren et al., 2011 ), may improve performance on relatively simple tasks but at the same time hold the potential to “crowd out” intrinsic motivation, which determines the quality of performance on complex tasks ( Cerasoli et al., 2014 ). Therefore, more insight is needed in the relationships between health care professionals’ work motivation, their work behaviors, and the quality of care.

Previous attempts to integrate the literature on this topic were unsuccessful in linking health care professionals’ work motivation to the quality of hospital care. In an overview of reviews, Flodgren et al. (2011) concluded that there is some but limited evidence for the effectiveness of financial incentives in changing professional practice, but no evidence to support any effects on patient outcomes. Likewise, systematic reviews on nurses’ work engagement and physicians’ occupational well-being reported positive associations with work behaviors, but the link with care outcomes was understudied ( Keyko, Cummings, Yonge, & Wong, 2016 ; Scheepers, Boerebach, Arah, Heineman, & Lombarts, 2015 ).

This review aims to go beyond existing work to get more insight in the relationship between motivation and quality of care. To achieve this aim, we apply a broad approach by synthesizing the evidence from quantitative and qualitative studies on (a) the direct relationships between autonomous motivation, controlled motivation, and amotivation of all health care professionals involved in direct patient care in hospitals and the quality of hospital care, (b) the relationships between these types of work motivation and health care professionals’ core task and (c) proactive behaviors, and (d) the relationship between proactive behaviors and the quality of patient care in hospitals. To overcome a potential lack of evidence due to narrow conceptualizations of work motivation and work behavior as observed in previous reviews, we use extensive conceptualizations of these constructs by considering similar concepts, which we place within a theoretical framework to guide our systematic search for evidence and the synthesis of results. The theoretical framework and research questions are depicted in Figure ​ Figure1 1 and will be further explained subsequently.

Theoretical framework: motivational continuum and Research Questions (RQ) 1–4

Work motivation is defined as “a set of energetic forces originating within and beyond an individual’s being, which determines the form, direction, intensity and duration of work- related behavior” (Pinder, as cited in Gagné, 2014 , p. 38). According to the self-determination theory, various forms of work motivation exist on a continuum (Deci & Ryan, as cited in Gagné, 2014 ). This continuum ranges from autonomous motivation at the one end, through controlled motivation, to amotivation at the other end of the continuum . Autonomous motivation means that the reasons to engage in a behavior stem from within a person. From most autonomous to least autonomous, a behavior can be perceived as enjoyable or interesting in itself ( intrinsic motivation ), or as an integral part of oneself ( integrated regulation ), or the values underlying the behavior can be considered congruent with one’s personal goals and identity ( identified regulation ). Controlled motivation means that reasons to engage in a behavior stem from beyond a person. When driven by controlled motivation, a behavior is done because it has instrumental value; it helps to obtain a sense of self-worth or prevents one from feeling guilty ( introjected regulation ) or it leads to a separable outcome such as money or status ( external regulation ). Amotivation refers to not being motivated to engage in an activity (Deci & Ryan, as cited in Gagné, 2014 ).

From this perspective, we align several related constructs that refer to energetic forces that guide behavior with this motivational continuum to guide our review. From most to least autonomous, we consider work engagement (“a positive affective-motivational state of work related well-being”; Bakker et al., as cited in Kim et al., 2013 , p. 249), psychological empowerment (intrinsic task motivation due to finding the task meaningful and experiencing self-efficacy and a sense of impact; Thomas & Velthouse, as cited in Gagné, 2014 ), psychological ownership (being psychologically tied to an object as an extension of one’s identity, e.g., the organization, or the patient; Van Dyne & Pierce, 2004 ), affective commitment (“a force that binds an individual to a course of action relevant to one or more targets,” e.g., the job, organization or patient, based on values, personal involvement, and identity; Meyer & Herscovitch, as cited in Gagné, 2014 , p. 34), and finally job and work involvement (the importance of one’s job or work in general; Kanungo, as cited in Gagné, 2014 ).

At the controlled side of the continuum, we consider normative commitment (an attachment to a target based on a perceived obligation; Meyer & Herscovitch, as cited in Gagné, 2014 ) and continuance commitment (an attachment to a target based on a cost–benefit analysis of maintaining versus withdrawing from the commitment; Meyer & Herscovitch, as cited in Gagné, 2014 ).

Finally, a construct that is often used to predict behavior is behavioral intention , which refers to a willingness to exert effort to achieve something ( Ajzen, 1991 ). This construct can be interpreted as the absence of amotivation. To enhance readability, the concepts at the autonomous side of the continuum are referred to as autonomous motivation, and the concepts corresponding with the controlled side are referred to as controlled motivation. When relevant, specifications are given.

Quality of Care

The main aim of this review is to understand the impact of health care professionals’ work motivation on the quality of care. Quality of care encompasses more than just one type of outcome. Following the World Health Organization, quality is defined along six dimensions: effectiveness (congruent with current medical evidence and leads to improved health outcomes), efficiency (optimal and sustainable use of personnel and resources), accessibility (timeliness and skills and resources match the medical need), patient-centeredness (respects for individual needs and preferences of the patient), equitability (equality despite gender, ethnicity, or socioeconomic status), and safety (minimized risk and harm to patients; World Health Organization, 2006 ). This review aims to shed more light on Research Question 1: “How do autonomous motivation, controlled motivation, and amotivation relate to the six dimensions of quality of hospital care?”

Work Behaviors

Health care professionals’ actions within a hospital system are the core of patient care. For this reason, it is meaningful to consider health care professionals’ work behaviors as mediators between motivation and quality of care ( Franco et al., 2002 ).

Work behavior can be classified into two types, namely core task behavior and proactive behavior ( Kim et al., 2013 ; Van Dyne & Pierce, 2004 ). Core task behavior refers to the behaviors to fulfill formal task requirements (Crant, as cited in Gagné, 2014 ), which is similar to role prescribed (or in-role ) behavior (behavior that is recognized by the formal reward system and that is part of the job description; Borman & Motowidlo, as cited in Kim et al., 2013 ). Examples of core task behaviors are guideline adherence and compliance to organizational procedures and protocols ( Gagné, 2014 ). Studies using these concepts are included in our review in order to answer Research Question 2: “How do autonomous motivation, controlled motivation, and amotivation relate to health care professionals’ core task behaviors?”

Many core task behaviors are formalized in evidence-based guidelines and protocols, which are specific per discipline within the hospital and grounded in ample scientific evidence ( Greenhalgh, Howick, & Maskrey, 2014 ). Consequently, the relationship between core task behaviors and quality of care is too extensive for this review. Yet, it can be argued that, although there are exceptions, exerting these behaviors contributes to care quality.

Proactive behavior , the second type of behavior, refers to challenging current circumstances and taking initiative to create new ones and is also described as going beyond one’s job or task requirements ( Gagné, 2014 ). Similar concepts are extra-role behavior (positive and discretionary behavior that is not prescribed in formal job descriptions; Borman & Motowidlo, as cited in Kim et al., 2013 ) and organizational citizenship behavior , which refers “discretionary work behaviors that contribute to organizational well-being but are not part of formal job expectations” (Organ, as cited in Van Dyne & Pierce, 2004 , p. 446). Examples of proactive behaviors are engaging in quality improvements and voicing concerns or speaking up in unsafe clinical situations ( Gagné, 2014 ). We include these concepts in our review to determine their motivators, as Research Question 3 states: “How do autonomous, controlled, and amotivation relate to health care professionals’ proactive behaviors?”

Health care professionals’ proactive behaviors are indispensable for quality of care, as the complexity of the health care system can never be completely captured in guidelines and protocols ( Greenhalgh et al., 2014 ; Hollnagel et al., 2015 ). However, proactive behavior may have inconsistent contributions for each of the six dimensions of quality. For example, patient-centeredness is likely to increase when health care professionals “go the extra mile” for their patients, but this may diminish efficiency. Therefore, Research Question 4 states: “How do health care professionals’ proactive behaviors relate to outcomes on the six dimensions of quality of hospital care?”

In line with the broad approach of this review, a mixed-methods systematic review was conducted. Reviews can be mixed by including various types of studies, by applying mixed methods for the synthesis of studies, or by applying both theory building and theory testing modes of analysis ( Harden, 2010 ). This systematic review was mixed in the sense that we included qualitative, quantitative, and mixed-methods studies. This systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO, No. CRD42016043284) of the University of York. The data were managed using a PRISMA-based Excel workbook and ATLAS.ti, Version 8.3.2.

Sources and Search Strategy

An elaborate search string was entered into PubMed, PsycINFO, Business Source Premier, CINAHL, EMBASE, and Web of Science. Two librarians (from medical and social sciences departments) were consulted for the development of the search string, which combined three key themes: motivation/behavior (e.g., motivation OR engagement OR proactive behavior OR guideline adherence), health care professionals (e.g., nurse OR physician OR resident), and quality of care (e.g., effectiveness OR safety). The search was limited to studies published in an academic journal between January 1990 and August 2016 and written in the English language. The full search string is available from the first author on request.

The search string identified a large number of records, which included all relevant references obtained from related reviews. Consequently, it was considered appropriate to deviate from the research protocol by not performing a backward reference search.

Study Selection

To be eligible for inclusion in the systematic review, a paper had to match the following criteria: be an empirical quantitative or qualitative paper revealing information on at least one of the four research questions, study participants were health care professionals providing direct patient care, the study took place within a hospital setting and in a high-income country as classified by the World Bank ( The World Bank Group, 2016 ), because the availability of resources is an important factor influencing care quality in middle- and low-income countries ( Fritzen, 2007 ). Furthermore, the paper had to report on individual-level self-reported measures of work motivation, whereas the measures of health care professionals’ behaviors and quality of care could take place at either the individual or at the group level and could be either self-reported (e.g., self-reported behavior or perceived quality) or externally assessed (e.g., supervisor-assessed work behavior or outcomes derived from hospital systems).

The interrater agreement for a random selection of 10% of the screened records was unsatisfactory for both the title and abstract and full-text screening (around 0.5). Consequently, we deviated from the review protocol, which describes that the first author would screen the remaining papers. Instead, the complete title and abstract screening and the complete full-text screening were done by two independent reviewers. Inconsistencies were discussed until consensus was reached.

Risk of Bias, Data Extraction, and Synthesis of Results

The risk of bias was assessed using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers ( Kmet, Cook, & Lee, 2004 ), with quality assessment (QA) checklists for quantitative papers (14 items) and for qualitative papers (10 items). These instruments resulted in a QA score for each paper with a possible range from 0 to 1, with 1 being the highest score. Studies were included regardless of their QA score, which is used to determine the risk of bias across studies and to differentiate between findings from low-quality and high-quality studies (with QAs below and above average, respectively).

The data extraction concerned the research method, sample size, response rate, descriptive information about the participants, definitions, and operationalizations of the concepts and research findings. The QA and data extraction were performed by two independent reviewers for 41.67% ( n = 35) of the research papers, where disagreements were discussed until consensus was reached. The correlation between the QAs of the first author and the second reviewers was satisfactory ( r = .61, p < .001) and the correlation between the first authors’ initial QA and the consensus decision was high ( r = .89, p < .001). Therefore, it was considered appropriate to perform the risk assessment and data extraction of the remaining papers by the first author. The extracted data were entered into a spreadsheet and coded in ATLAS.ti to enable the narrative synthesis of results per research question. In the synthesis of results, we distinguished between findings based on quantitative or qualitative evidence. For mixed-methods studies, this categorization was based on the type of evidence about the research question presented.

The search resulted in the identification of 6,525 unique records, of which 84 records matched the inclusion criteria. A PRISMA flow diagram of the identification and selection of records is given in Figure ​ Figure2 2 .

PRISMA flow diagram of the literature search

Study Characteristics and Risk of Bias

The included records on quantitative findings ( n = 66) reported on four quasi-experimental studies, four time-lagged studies, four mixed-methods studies, six longitudinal studies, and 48 cross-sectional studies. Records reporting on qualitative findings ( n = 18) reported on three case studies and 15 interview studies. Of all included studies, 46 focused exclusively on nurses, 13 focused exclusively on physicians, and 25 studies had participants from multiple professions, including nurses, physicians, paraprofessionals, and physician assistants. Together, the studies included over 102,500 health care professionals.

The QA resulted in an overall mean score of 0.70 ( SD = 0.21), with M QAquantitative = 0.71 ( SD = 0.19) and M QAqualitative = 0.70 ( SD = 0.27). The QA across studies (available from the first author on request) demonstrated that a potential risk of bias of quantitative studies are the lack of control for confounding factors and the limited definition and/or operationalization of the concepts of interest. For qualitative studies, most frequently observed shortcomings were the lack of reflexivity, the ambiguity of the sampling strategy, and data collection and/or analysis.

Seventy-one of the studies reported on one of the research questions of this review, eight studies reported on two research questions, four studies reported on three research questions, and one study reported on all four research questions. An overview of the results is depicted in Table ​ Table1. 1 . For each research question, the findings based on quantitative evidence will be described first, followed by the qualitative findings, which deepen our understanding of the relationships of interest. In the conclusions for each research question, reflections are made upon the influence of the quality of the studies.

Overview of findings per research question (first author and year of publication of the reporting study)

Note. Qualitative evidence is depicted in italics. RQ = research question; OCB = organizational citizenship behavior.

a High-quality study.

b Externally assessed outcome.

Each finding (positive, negative, or no association) about Research Questions 1–4 is depicted in Table ​ Table1 1 and papers reporting multiple research findings are represented multiple times. Full references to the included studies are given in Supplemental Digital Content 1 ( http://links.lww.com/HCMR/A67 ). The full descriptions of the study characteristics and findings as depicted in Table ​ Table1 1 are available from the first author on request.

Motivation and Quality of Care

The first research question was investigated in 29 studies: 24 studies reported on quantitative evidence and 5 on qualitative evidence. The quantitative evidence showed that autonomous motivation, mostly investigated in terms of work engagement and empowerment, positively influenced overall perceptions of quality. Organizational commitment had mixed (positive and no) effects on perceived quality, and professional commitment was positively associated with three out of six patient-perceived quality indicators.

Autonomous motivation positively affected safety perceptions but had no association with the number of safety events. Work engagement was mostly positively associated with perceived safety, but one study reported no association. There was no effect of controlled motivation on perceived safety.

Autonomous motivation had mixed effects on perceived patient-centeredness, with some studies finding a positive association, one study finding no association and one study reporting a negative association. Controlled motivation was negatively associated with perceptions of patient-centeredness.

For the less investigated quality dimensions, behavioral intention was positively associated with perceptions of equitability. Autonomous motivation positively affected perceived effectiveness and efficiency of care. Furthermore, an otherwise unspecified sense of motivation was not associated with effectiveness, nor with accessibility of care.

The qualitative evidence also supported positive associations between autonomous motivation and perceptions of quality, safety, and patient-centeredness, whereas an absence of motivation was perceived to lead to poor quality of care. An interview study found that physicians’ motivation to provide patient-centered care results from a balance between autonomous reasons (values) and controlled reasons (their own agenda based on external factors such as resources and fear of uncertainty).

When merely considering the high-quality studies, there was a positive association between autonomous motivation and perceived quality and safety. Patient-centeredness was stimulated by a balance of autonomous and controlled motivation. The studies focusing on effectiveness, equitability, and efficiency perceptions and externally assessed quality were either of low quality or reported no effect. Therefore, the effect of motivation on these outcomes remains uncertain.

Motivation and Core Task Behavior

Of the 19 studies that reported on the second research question, quantitative evidence was presented in 15 studies, and four studies presented qualitative evidence. The quantitative findings were that autonomous motivation, most often investigated in terms of work engagement and organizational commitment, positively influenced self-reported core task behavior and guideline adherence. Mixed (positive and no) results were found for the relationship between autonomous motivation and externally assessed core task behavior. One study reported that the relationship between autonomous motivation and supervisor-assessed core task behavior was mediated by commitment to the supervisor. Whereas normative commitment had a positive association with core task behavior, continuance commitment had a negative association with core task behavior. Mixed effects were reported for behavioral intention and an otherwise unspecified sense of motivation in relationship to self-reported guideline adherence. Behavioral intention did not predict observed guideline adherence.

The qualitative evidence also supported positive associations between autonomous motivation and core task behaviors. Core task behavior was reported to result from a balance between autonomous and controlled motivation, in which controlled motivation contributed to as well as inhibited this type of behavior.

When merely considering the high-quality studies, autonomous motivation was positively associated with core task behavior. Moderately controlled motivation contributed to core task behavior, but motivation at the most controlled end of the continuum did not to contribute to and even inhibited core task behavior. As the studies on behavioral intention were of low quality, its effect remains unclear.

Motivation and Proactive Behavior

The third research question was investigated in 43 studies, of which 32 presented quantitative findings and 11 presented qualitative findings. The quantitative evidence generally showed a positive relationship between autonomous motivation and proactive behavior, but findings were mixed for identified regulation, involvement, and organizational commitment. Controlled motivation had no or a negative association with self-reported proactive behavior. Furthermore, controlled motivation, commitment to patients, and goal internalization did not affect externally assessed proactive behavior. For voicing behavior, it was found that, whereas autonomous motivation stimulated voicing behavior, this behavior was discouraged by extrinsic factors (e.g., colleagues’ approval and the fear of failure).

The qualitative findings supported the positive association between autonomous motivation and proactive behavior. Nevertheless, it was observed that even if health care professionals experience a sense of ownership or find quality improvement important, this autonomous motivation may exist without actual engagement in proactive behavior. Similar to the quantitative findings, autonomous and controlled reasons simultaneously stimulated proactive behavior, quality improvements, and voicing behavior. However, for voicing behavior, controlled motivation held the potential to overrule autonomous motivation to speak up, thereby preventing this type of behavior.

Overall, autonomous motivation was positively associated with proactive behaviors. The association between controlled motivation and proactive behavior was dependent on the type of proactive behavior; whereas controlled motivation, combined with autonomous motivation, stimulated quality improvements and possibly also proactivity, controlled motivation negatively affected voicing behavior. When merely considering the high-quality studies, the results do not change.

Proactive Behavior and Quality of Care

Of the 12 studies reporting on the fourth research question, nine reported on quantitative findings and three reported on qualitative findings. The quantitative results showed that proactive behavior positively influenced perceived quality and had mixed effects on externally assessed quality and safety. Proactive behavior even had a negative effect on safety when safety was operationalized in terms of a low number of reported incidents in the hospital system. Furthermore, although proactivity among nurses stimulated nurse compliance to screening, it had no influence on the actual effectiveness of care delivered by physicians. Regarding quality improvement projects, positive effects were found on care effectiveness and safety, except when the patients were vulnerable. Voicing behavior was not associated with quality perceptions.

The qualitative evidence resembled these findings. Patients as well as nurses perceive nurses’ proactivity as an indicator of high-quality care, and nurse-reported (but not externally assessed) proactivity was indeed associated with externally assessed safety outcomes. Furthermore, interventions to stimulate proactivity or quality improvements had generally positive effects on externally assessed safety and effectiveness, but when patients were vulnerable, quality improvements had less or no effect.

When merely considering the high-quality studies, there was a positive association between self-reported proactive behavior and self-reported quality. Proactive behavior had a positive association with externally assessed safety in terms of the absence of harm to patients, but it had no or even a negative association with externally assessed safety when this was operationalized as the number of incident reports. The studies reporting on externally assessed proactive behavior, voicing behavior, or evaluations of interventions were of low quality, which limits their reliability.

This review highlights the importance of autonomous motivation for health care professionals’ behaviors and the quality of care. We show that autonomous motivation is directly and positively associated with quality, safety, and patient-centeredness, whereas controlled motivation and amotivation are negatively associated with quality.

In addition, the findings of this review provide nuanced insights on the role of controlled motivation and incentives. Moderately controlled motivation is positively associated with core task performance, as observed in the organizational literature. In contrast with findings from the field of organizational studies, which support a positive effect of external regulation on performance ( Cerasoli et al., 2014 ), our findings show that motivation at the most controlled end of the continuum is not or negatively associated with health care professionals’ core task behaviors. This discrepancy might be due to differences between work motivation of health care professionals versus of employees from other types of organizations. In a study comparing the motivation of for-profit and not-for-profit employees (with the latter group including hospital employees as their organization has a social rather than a profit mission), not-for-profit employees had lower external regulations than employees working in organizations driven by monetary goals ( De Cooman, De Gieter, Pepermans, & Jegers, 2011 ). Furthermore, studies among medical students indicate that they choose their profession out of intrinsic and identified motivation rather than extrinsic motivation ( Berenson & Rice, 2015 ), and they maintain this high level of intrinsic motivation throughout their career ( Berenson & Rice, 2015 ; Scheepers et al., 2015 ). Because of this high level of intrinsic motivation and low level of external regulation, health care professionals might not be very susceptible for extrinsic motivators. This would also provide an explanation for the finding that providing incentives does not stimulate proactive behaviors and quality improvement, unless this is combined with autonomous reasons to act. These observations challenge the emphasis on incentivizing (e.g., financial incentives) and penalizing (e.g., public reporting) as a means to extrinsically motivate health care professionals to improve quality and potentially explain why these methods have not reached their anticipated success ( Berenson & Rice, 2015 ; Flodgren et al., 2011 ; Franco et al., 2002 ).

Furthermore, our review sheds further light on the role of proactive behavior in the health care setting. Our findings show that proactive behavior generally contributes to effectiveness, but only when the treatment is under the direct control of the proactive health care professional. In addition, proactive behavior contributes to safety, but not if safety is operationalized as the number of reported incidents. We argue that the number of reported incidents is probably not a valid measure of patient safety, which is confirmed by our finding that autonomous reasons contribute to voicing, but that this motivation can be overruled by controlled reasons to act, such as social reprimands. We state that the number of reported incidents reflects the safety culture or the learning potential of an organization; if there is a supportive safety culture, health care workers are more willing to act proactively and voice incidents ( Ancarani, Di Mauro, & Giammanco, 2017 ). This could also explain the observed positive relationship between proactive behavior and reported incidents. Considering this point, we conclude that proactive behavior contributes to the quality and safety of care.

The key policy priority to improve quality of care is to stimulate health care professionals’ autonomous work motivation. Although our review confirms that controlled motivation has its positive sides ( Cerasoli et al., 2014 ), it negatively affects quality perceptions and voicing behavior. Therefore, current efforts to extrinsically motivate health care professionals to improve specific quality outcomes by incentivizing or penalizing need to be revised. It is recommended that these incentive-based interventions are complemented with aspects to simultaneously stimulate autonomous motivation, such as alignment with health care professionals’ drives and values, autonomy, supportive supervision, appreciation, respect and good interpersonal relationships, and growth opportunities ( Berenson & Rice, 2015 ; Keyko et al., 2016 ).

Furthermore, as we observed that motivation based on normative considerations predicts core task behavior well, we suggest that, to increase compliance for specific core task behaviors, such as hand hygiene, one might want to appeal on health care professionals’ sense of professionalism; the internalized professional norms and values to act in the interest of the patient. Health care leaders can set the norm by engaging in exemplary behaviors ( Ancarani et al., 2017 ; Berenson & Rice, 2015 ; Franco et al., 2002 ).

The next recommendation is to facilitate health care professionals’ proactive behaviors. In uncertain contexts, systems awareness, organizational learning, and continuous quality improvement are essential, and acting proactively is “part of the job” (Griffin et al., as cited in Gagné, 2014 ; Hollnagel et al., 2015 ). It is increasingly recognized that establishing quality and safety is no longer merely “avoiding that something goes wrong,” rather, it is “ensuring that as many things as possible go right” ( Hollnagel et al., 2015 ) by acting proactively and raising concerns. In line with this thinking, we state that, to unleash the learning potential of health care organizations and to improve the quality of care, proactive behavior needs to be recognized as a fundamental part of health care professionals’ job requirements and needs to be appreciated and facilitated accordingly, for example, by allocating resources (e.g., time, equipment, training) for quality improvements, normalizing voicing behavior, and establishing a shame- and blame-free environment for raising concerns, learning, and improvement ( Ancarani et al., 2017 ).

This review focused on the hospital setting, and our recommendations might apply beyond this setting as well. Care provision takes place within the clinical microsystem (the team of health care professionals caring for a patient; Fulop & Ramsay, 2019 ), and as these can be found in several settings such as primary care clinics, mental health care, and chronic care, we assume that our findings and recommendations translate to those settings as well. However, the extent to which our research translates to other health care systems outside high-income countries may be limited, as Fritzen (2007) stated that in low- and middle-income countries, there is “often a disjunction between formal responsibilities and the requisite resources to meet minimum specific standards.” In other words, the availability of resources, which varies per system, affects the extent to which health care professionals are able to act upon their motivation to provide and improve care.

It is important to note that achieving high-quality provision in hospitals is complex and influenced by intertwined factors from the organizational context and the broader environmental context. These factors include organizational characteristics (e.g., size, scale, structure, information systems, leadership, and culture) and broader environmental characteristics such as governance, regulation, and finance of the health care system ( Fulop & Ramsay, 2019 ). These factors should be aligned to provide health care workers with the resources, including autonomous motivation, for high-quality care delivery.

Limitations and Future Research

The results of this review need be interpreted in consideration of its limitations. First, the alignment of the motivational concepts along the self-determination theory continuum may reflect an overly simplistic view of these concepts, and the list of aligned concepts might not have been exhaustive. The generalizability of this approach may therefore be limited when investigating other, but related, concepts (e.g., altruism). In addition, some studies may have been overlooked due to publication bias, not incorporating gray literature and because the search string was not exhaustive. Furthermore, we observed a suboptimal interrater agreement regarding the inclusion of the studies, which we resolved by performing the screening of all abstracts and full-text records by two independent reviewers. Future researchers might prevent this issue by stating the inclusion and exclusion criteria more explicitly, especially for ambiguously described studies (e.g., include, unless it is completely clear that an exclusion criterion applies). In addition, the extensive QA, which included questions concerning the risk of bias, may not have completely eliminated the potential influence of bias. Regarding all research questions, it is noted that most studies use self-reported measures of behavior or quality, and therefore, the evidence for the effect of motivation on externally assessed behavior and quality is limited. Finally, most studies based their conclusions on correlations or regression analyses. In the absence of sufficient longitudinal or (quasi-)experimental studies, we cannot unambiguously determine the causality of the relationships we studied.

These limitations should be addressed in future work, as well as the following recommendations. This review shows that autonomous and controlled motivation might influence behavior simultaneously. Building on studies about motivational or commitment profiles (e.g., Gagné, 2014 ), future (quasi-)experimental studies might aim at getting a better understanding of the “right” balance between extrinsic rewards and autonomous motivation for the provision of high-quality care. To conclude, it is strongly recommended that future studies incorporate objective and valid measures to study health care professionals’ motivation, behaviors, and the (externally assessed) quality of care dimensions.

To improve quality of care, policy makers and managers need to support health care professionals’ autonomously motivation and facilitate them to act proactively and “go the extra mile” for their patients. Combining autonomous and controlled motivation holds the potential to boost quality of care, but more insight is needed into how to balance these types of motivation in such a way that it does not thwart voicing behaviors.

Supplementary Material

Acknowledgments.

We would like to express our gratitude to our student assistants Rick Overwijk and Marcel Schmidt for their help in the screening phases of this review. We are thankful to Helena VonVille for providing us with the Excel workbooks and advise. We are grateful to the University Medical Center Groningen and the University of Groningen as the submitted work was undertaken as part of a PhD program funded by these two institutions.

The authors have disclosed that they have no significant relationship with, or financial interest in, any commercial companies pertaining to this article.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s web site ( www.hcmrjournal.com ).

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Global Cognition

7 ways to improve your motivation to study (backed by science).

by Winston Sieck updated September 18, 2021

Just about everyone who has ever been in school knows what it feels like to sit in front of the computer, staring at a blank screen. Hoping their term paper would write itself.

Or tried reading a textbook only to find that they have read the same paragraph ten times and still don’t know what they read.

Or decided they would rather clean the clutter out from under their bed than study in the first place.

Bottom line, studying can be kind of a drag. When you have a hundred other things you would rather do and an overwhelming amount of work to do, it is hard to get started and even harder to finish.

Fortunately, there are some simple, scientifically proven ways you can find your motivation and keep it.

What is Motivation to Study?

Motivation comes from a Latin word that literally means “to move.” But what causes someone to be motivated to study has been a hot topic in the world of science.

Researchers believe that your motivation to study can either come from inside you or outside of you. You can be motivated by an internal drive to learn as much possible. Or, you might be motivated to study by an external reward like a good grade, or a great job, or someone promising you a car.

Recently, researchers have discovered that your motivation to study is rooted in lots of factors, many of which we have control over. Rory Lazowski of James Madison University and Chris Hulleman of the University of Virginia analyzed more than 70 studies into what motivates students in schools. They published their paper , “Motivation Interventions in Education: A Meta-Analytic Review, in the journal Review of Educational Research .

Lazowski and Hulleman found that a number of ways to improve motivation consistently yield positive results. Here, I describe seven of the techniques that you can most readily use on your own to power through your own study barriers, and move your learning forward.

1. Set Clear Goals

You may think to yourself, “My goal is to graduate and get a good job and be rich.” While that’s a fine ambition, by itself it probably won’t help you in school day-to-day.

In order to improve your motivation to study, your goals have to be a little closer to home. In fact, setting clear academic goals has been scientifically linked to higher grade point averages than students who set vague goals, like, “I’ll just do the best I can.”

Set a goal to earn an “A” on a particular test in a particular subject. Or, decide to learn everything you can about a concept because it will help you in the real world. Set a deadline for homework that will force you to finish a task before it is due so you can review it before handing it in. Whatever the goal is, be sure it is specific, relevant, and timely.

2. Don’t Just Shoot For Performance, Go For Mastery

There is nothing more frustrating than studying hard for a test only to get a grade that is less than what you were expecting. At that point, lots of students throw their hands in the air and say, “If this is what happens when I study, why study?”

Resist that urge.

The grades you receive on a test are examples of performance goals. If you set a goal to get an “A”, and stop there, you may only study the things that you think will be on the test, but not necessarily the things that will give you mastery of the concept.

Students who consistently strive for mastery , really learning what they are studying, almost always see their grades improve as a result.

Mastery goals also help with your motivation to study. If you want to learn everything there is to know, you are less likely to put off starting that process.

3. Take Responsibility for Your Learning

It’s tempting to blame your grades on other people. The teacher doesn’t like you. They never taught what you were tested on. Your homework assignment doesn’t apply. When you blame others for your performance, you are more likely to do poorly on tests, assignments and projects.

Taking responsibility for your own learning can make a world of difference when it comes to getting yourself motivated to study. Recognizing that you are in charge of what you learn can help you start studying, but it can also keep you going when other distractions threaten to take your attention away.

Next time you are tempted to stop in the middle of an assignment and do something else, pause. Take a breath. Then, say out loud, “No one is going to learn this for me.” You might be surprised at how hearing those words affect your focus.

4. Adopt a Growth Mindset

Some people still believe that you’re either born smart (or not). And there’s not much you can do about it. However, research has shown that successful people tend to believe that intelligence is something you build up over your life. These folks have a growth mindset.

When your intelligence is challenged by hard assignments or difficult concepts, people with a growth mindset tend to think, “I don’t know this yet, but if I work hard, I will learn it.”

Researchers found that believing your brain can get stronger when you tackle hard things not only improves your mastery of what you are learning, it also improves your grades and increases your motivation to study.

The next time you are faced by a blank screen or hard textbook chapter remember, “I don’t know this yet, but if I work hard, I will learn it.”

5. Find the Relevance

If you ever want to annoy your math teacher, tell them algebra has no relevance in the real world. Alternatively, try to figure out how what you are studying relates to your life. Studies have shown that high school students who were asked to write down how their subject matter related to their everyday life saw a significant jump in their GPA.

Before you start studying, try jotting down a few ways this information will come in handy in the future. Making this connection will help you see value in what you are doing and get you started on an assignment or topic.

Sometimes, the connection between what you are learning and how it applies to your life is not easy to see. Try searching the web for applications of your topic to help you see the real-life relevance of what you are learning.

6. Imagine Your Future Self

Imagine what your life will be like in 10 years. Are you successful? Do you have a great career that you love? Are you living in the best city in the world?

Now, imagine how you are going to get there.

Some people automatically connect the school work they are doing now with getting into a good college or training program that will lead to their desired future. Other students have difficulty making that connection.

Having the ability to imagine your future self is a skill that has been shown to improve motivation to study. It has also been linked to higher grades, lower cases of truancy and fewer discipline problems in school.

Next time you are faced with a particularly daunting assignment, close your eyes and picture what you want your life to be like. Then, recognize that in order to have the life you want, you have to do the assignment in front of you.

7. Reaffirm Your Personal Values

What do you value most? What are the two or three most important qualities you can possibly develop? Do you strive to be honest in everything you do? Do you value kindness? Is success the most important value in your life?

Taking a few minutes now and again to reaffirm your values by writing in a journal or meditating about them can help you focus your efforts in other areas of your life.

If you value family over everything, your ability to take care of your family will motivate you to study and do well in school. If you value honesty, you will never feel inclined to cheat on a test, but will work hard to study.

Ultimately, finding the motivation to study is less about going on a treasure hunt and more about changing the way you think about learning. Even implementing a few of these seven tips can help you stay focused and keep going.

Image Credit: PublicDomainPictures

Lazowski, R. A., & Hulleman, C. S. (2016). Motivation interventions in education: A meta-analytic review. Review of Educational research , 86(2), 602-640. DOI: 10.3102/0034654315617832

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About Winston Sieck

Dr. Winston Sieck is a cognitive psychologist working to advance the development of thinking skills. He is founder and president of Global Cognition, and director of Thinker Academy .

Reader Interactions

October 2, 2018 at 4:59 pm

Thanks for sharing this post. I plan to share it with my students this week. We’re implementing some growth mindset and mindfulness practices this year. This will be a good reinforcement of some of those ideas and will provide some new insight as well. I think it will be well-received. I’ve been pleasantly surprised at how open they’ve been to these ideas so far. Thanks again.

October 2, 2018 at 5:24 pm

That’s great, Tony. Excellent to hear the success you’re having with these ideas in your class. Thanks for stopping by..

October 25, 2021 at 12:51 pm

Thanks for posting this . I felt it after reading it and I think that if I prepare it today tomarow will be good . From this I’ll stay motivated .

October 2, 2018 at 6:54 pm

Thank greatly for this post. I’m studying at college at 45yrs ,sometimes want to give up studying but you came along with this great post. Great assurance and encouragement for young and old students alike.

Will have to share with my students as well,

kind regards,

clotilda Claudia Harry Solomon islands.

October 2, 2018 at 7:14 pm

Yep, we all need a little motivation boost at any age. Way to keep learning, Clotilda.

November 16, 2018 at 12:08 am

Thanks for providing a resource for our children to grow in knowledge. Seems that no matter what the age, we all struggle with these issues.

November 17, 2018 at 4:39 pm

No doubt, Michael! Managing motivation is a life-long skill we can teach our kids. Good to see you here – thanks for stopping by..

October 6, 2020 at 4:23 am

Thank you so much for motivating, the point you are mentioned such as set goal and go for mastery, be responsibility for learning, etc. all these points are really very helpful and they are very useful for study thank you so much for sharing

February 3, 2021 at 5:18 am

Thank you! Without following all of these steps, it’s hard to have any significant academic success, I think. It helps me not to lose motivation with step-by-step planning: I divide the global goal into several small short-term goals and achieving even minimal results makes me happy and motivates me to try harder. Of course, there are also bad periods, when I feel exhausted and overwhelmed. But a little rest allows me to get back on track.

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