Refining the Measurement of Factors Predicting Faculty Research Publications

doi:10.21203/rs.3.rs-2479240/v1

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Refining the Measurement of Factors Predicting Faculty Research Publications

https://doi.org/10.21203/rs.3.rs-2479240/v1

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Background: Research plays a large role in the professional expectations of faculty in all disciplines. In the health professions, faculty are expected to conduct research while caring for patients, educating learners, and carrying out major administrative roles. Given the difficulty in balancing these many responsibilities, it is sensible for academic institutional officers to seek to understand the factors that strongly relate to faculty research productivity, and to measure faculty members’ standing on those factors. The purpose of the study was to investigate the validity of the research productivity items from Bland and colleagues’ scale as predictors of publication counts among junior and mid-career faculty at the King Abdulaziz University Faculty of Dentistry (KAUFD).

Methods: This is an observational study that was conducted at KAUFD. A questionnaire modified from the Bland model was emailed to all full time assistant and associate professors. Two main sets of statistical analyses were run: exploratory factor analysis to investigate the internal structure of the scale and regression analysis to relate scale factors to counts of publications in peer-reviewed journals.

Results: Out of 106 faculty, 98 participated (92.5%). Faculty publication count in ISI-indexed journals from January 2013 to the survey time showed a Poisson distribution, with a mode of zero publications (44 participants) and a maximum of 14 publications. The exploratory factor analysis showed that factors 1-4 accounted for 46% of the variance (first factor alone explained 26% of the variance).

Conclusion: Our findings suggest a different factor structure between faculty input gathered via Bland and colleagues’ (2005) questionnaire and what the authors originally proposed. Institution- or department-specific validation of this measure is warranted to make reliable conclusions of any comparisons or intervention.

research

measurement

factors predicting

faculty research publications

Bland’s model

faculty productivity

Saudi Arabia.

This study was meant to investigate the validity of a model of the factors that influence academic health center faculty members’ research productivity. Research plays a large role in the professional expectations of faculty in all disciplines. In the health professions, faculty are expected to conduct research while caring for patients, educating learners, and carrying out major administrative roles. Given the difficulty in balancing these many responsibilities, it is sensible for academic institutional officers to seek to understand the factors that strongly relate to faculty research productivity [1–7], and to measure faculty members’ standing on those factors. Those factors would permit an institution to focus efforts on improving the conditions that have the greatest potential impact, either because they are strongly related to productivity, they are particularly ripe for improvement locally, or both [1–7].

Studies on faculty research productivity [3–7] recognize different characteristics that have an influence on faculty research productivity. These characteristics were grouped into explanatory models to recognize the major factors that affect research productivity.

One influential model of the factors that relate to research productivity was published by Carole Bland and colleagues [1]. Based on data from a 1999 survey of faculty, Bland and colleagues developed a theoretical model and associated survey instrument that categorized items as reflecting one of three major sets of factors: individual characteristics, institutional characteristics, and leadership characteristics. Individual characteristics or attributes relate to personal traits. They include motivation, early research socialization, competencies, working in simultaneous projects, orientation, content knowledge and autonomy and commitment work habits [8–14].

Institutional and departmental features or attributes include mentoring, availability of resources, productivity of colleagues, structure, policies, and the culture. Moreover, research productivity is regularly emphasized in the mission, the promotion and tenure structure of such institutions [2].

Leadership characteristics include the scholarly success and perceived positive orientation towards research of leaders at various levels of the institution (e.g., department heads, deans) [2]. According to Bland’s model, the maximum research productivity is achieved when a faculty member has specific individual characteristics, and works in a highly conducive research institution that is led by a leader with essential leadership abilities [2].

While Bland and colleagues’ model implies that all factors are at least somewhat important, there is a debate as to the relative importance of particular factors. For instance, in work pre-dating Bland and colleagues’, Brocato and Mavis [3] found that individual characteristics were more highly associated with research productivity compared to institutional and departmental characteristics. However, Bland et al. [1] stated that institutional features are the most powerful set of factors. In considering how to apply past scholarship in this area going forward, it is worthwhile to continue to investigate the relative strength by which particular factors relate to research productivity.

It is also worthwhile to further investigate the validity with which Bland and colleagues’ instrument measures the intended constructs, i.e., the overarching factors proposed in their model. Bland and colleagues’ manuscript details a confirmatory factor analysis of their survey items’ fit to their theoretical model. However, it was arguably premature to run a confirmatory analysis, since no exploratory factor analysis had been run to see what patterns might emerge in the data contrary to their presuppositions, nor did they compare whether their theorized model fit better than any of many other possible models (e.g., a single-dimension model; a model collapsing “institutional” with “leadership” items together). As Lee Cronbach [15] stated, “a proposition deserves some degree of trust only when it is survived serious attempts to falsify it.” Secondly, Bland and colleagues reported an analysis of the specific factors that best-predicted research productivity in their sample; however, they seem to have built that model by entering every item from a very large survey into a regression as potential predictors, retaining only the most strongly associated items. This approach is interesting descriptively, but risks capitalizing on chance relationships while failing to take advantage of the presumptive value of building a multi-item scale: that sets of items may better reflect underlying factors than any one item. In short, their work lays an excellent foundation, and additional studies are needed to test and build upon their theoretical and empirical work.

This research aimed to examine the internal validity of the research productivity items from Bland and colleagues’ model, and to explore whether it correlates with research productivity in our faculty.

Participants

This is an observational study that was conducted at King Abdulaziz University Faculty of Dentistry (KAUFD). It was approved by the KAUFD IRB (Proposal No. 020 − 15). The sampled population included all assistant and associate professors working at KAUFD during the research period, excluding any newly-appointed faculty or faculty who had been working for less than one academic year, for a sampled N = 106.

Methods

A pilot study of the questionnaire was performed to enhance validity. An initial questionnaire using all items from Bland and colleagues’ instrument was distributed to ten faculty members to gauge readability and elicit their feedback about the questionnaire. This initial questionnaire assessed faculty productivity factors in teaching, research, and patient care. After several reminders, seven pilot participants responded. Pilot test participants indicated that the questionnaire was easy to understand; however, it was very long. We then kept research productivity questions only, omitting the sections on teaching and clinical productivity. No pilot data are included in the main results described below.

Participants were asked to rate each of the items from Bland and colleagues’ instrument on a five-point scale from 1 (“Strongly disagree”) and 5 (“Strongly agree”) [1–2]. These items each correspond to one of the Bland model’s purported three main characteristics (individual, institutional, or leadership). We then asked two multiple choice questions and one open-ended question regarding strategies faculty perceived would most facilitate research productivity. Next, participants completed two questions about their number of published articles in the past two years as well as the number of hours spent on research during a typical week. Finally, participants were asked to indicate their age, nationality, gender, rank, departmental type (clinical vs. not), and qualifications, and were invited to share any general comments in an open-ended field.

Data collection Procedure

The primary investigator (LB) attended one of each department’s meetings at KAUFD and gave a brief presentation to encourage faculty to participate. Confidentiality was maintained by not reporting any demographic data that could identify respondents. The questionnaire was emailed to all eligible participants, and after several reminders, out of 106 faculty members, 98 participants responded, for a response rate was 92.5%.

Descriptive statistics

Out of 106 eligible and contacted participants, 98 responded (92.5%). 40.8% were males and 59.2% were females. The majority were of Saudi nationality (76.5%), with the remainder of Egyptian nationality. 71.4% of the participants were working in clinical departments and 28.6% worked in non-clinical departments. 69.4% of them were assistant professors and 30.6% were associate professors. Faculty publication counts in ISI-indexed journals from January 2013 through the time of survey response showed a Poisson distribution, with a mode at zero publications (44 participants) and a maximum of 14 publications. Total publication counts for all accepted peer-reviewed publications, ISI-indexed or not, were similarly distributed (mode of zero publications, 34 participants; maximum of 22 publications). ISI-index publication count and total publications were highly correlated (Spearman’s rho = 0.72, p < .001); for all subsequent analyses, we used total publication counts as the main outcome variable.

Research productivity factor scale item descriptive statistics are shown in Table 1. Responses on each of the 53 items were generally normally distributed, and participants used all scale points from “strongly disagree” to “strongly agree”. Two items had notably small standard deviations, each showing a ceiling effect of markedly high perceptions (perceived writing skills, M = 4.2, SD = 0.78; perceived computer skills, M = 4.2, SD = 0.84). For five items, twelve or more respondents marked “N/A” (“not applicable”); four items referred to a “division”, of which many participants were not part, while the remaining item was: “a large portion of my academic department’s faculty can be considered to be a significant external ‘grant getter’”. Three additional items featured 19–22 “don’t know” answers, each referring to the existence of an institutionally- or school-defined research vision.

Table 1

Faculty productivity questionnaire item descriptive statistics.
Item	N	Mean	Std. Dev.
I have access to adequate resources to conduct my research projects such as secretarial support	95	1.89	1.09
I have access to adequate resources to conduct my research projects such as research assistants	95	1.94	1.16
I have been (or was when I was a junior faculty member) formally assigned an advisor or mentor within my academic department who provide me with valuable guidance in research	94	2.00	1.41
At least weekly, I have substantive uninterrupted conversations with important colleagues about research in my university	98	2.13	1.08
I have (or had when I was a junior faculty member) an “unassigned” mentor(s) either in this department or in other departments/schools/organizations who provide me with valuable guidance in research	93	2.24	1.34
I am a member of a research group in the university	98	2.31	1.13
At least weekly, I have substantive uninterrupted conversations with important colleagues about research in my school	98	2.35	1.12
I have access to adequate resources to conduct my research projects such as data analyses and technical support	94	2.37	1.27
I have adequate time to conduct research projects	98	2.44	1.22
At least weekly, I have substantive uninterrupted conversations with important colleagues about research in my discipline	98	2.44	1.22
I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my dean	98	2.44	1.24
At least weekly, I have substantive uninterrupted conversations with important colleagues about research in my department	98	2.46	1.27
I am a member of a research group in the division	68	2.49	1.26
I have space that is well equipped for me to conduct my research	97	2.49	1.28
I am a member of a research group in the school	98	2.51	1.27
At least weekly, I have substantive uninterrupted conversations with important colleagues about research in my division	86	2.51	1.22
I am a member of a research group in the discipline	97	2.58	1.28
My department has systematic and fair mechanisms for non-monetarily recognizing and celebrating achievements (e.g. putting in department newsletter, “toasting” at faculty meetings) in research	98	2.60	1.13
I am a member of a research group in the department	98	2.70	1.38
My school leadership keeps us on track by clearly emphasizing our core missions of research.	97	2.75	1.20
My academic department provides me with, or I have from external or other sources, adequate support to travel to research-based conferences	96	2.76	1.37
I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my division head	60	2.77	1.24
I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my department head	98	2.81	1.28
My department has a communication system that allows me to be informed in a timely fashion and adequately about major issues, important events, and upcoming concerns regarding research.	98	2.85	1.25
A large portion of my academic department’s faculty can be considered to be a significant external grant “getter”	83	2.92	1.07
I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my colleagues outside my department	98	2.92	1.24
It is clear to me how my school’s vision and goals are or can be related to the university’s vision and goals.	77	2.95	1.20
I believe I am up-to-date in grant getting skills for my area (e.g., identifying your funding sources, contacting funding agency personnel, preparing grants, using research reviews)	96	2.99	1.12
KAUFD (school) has a commonly held research vision for what we want to look like in the next five years.	79	3.03	1.21
I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my department colleagues	98	3.09	1.28
I have a well-developed network of colleagues with whom I discuss research projects outside my department/within Univ	98	3.13	1.23
I have excellent opportunities at KAUFD to pursue my interests in research	97	3.14	1.25
I have a well-developed network of colleagues with whom I discuss research projects outside the university	98	3.19	1.26
There is a high expectation in my department, school, and/or university to conduct research that is externally funded	96	3.21	1.01
I have access to adequate resources to conduct my research projects such as computers and library materials	96	3.24	1.27
I have a well-developed network of colleagues with whom I discuss research projects within my academic department	98	3.26	1.27
My department leadership (e.g., department head, senior faculty) make clear the expected ethical standards and practices in research	98	3.27	1.23
I feel appreciated and valued by my local colleagues (dept/school/univ) for my work in research	93	3.27	1.09
My division leader is highly regarded for her/his: (mark NA if your department has no divisions) research	50	3.36	1.14
I have a well-defined plan for achieving my research career goals	98	3.38	.99
KAU has a commonly held research vision for what we want to look like in the next five years.	76	3.38	1.20
My department head is highly regarded for his/her research	95	3.39	1.17
The number of faculty in my department is large enough to accomplish our goals in research	96	3.41	1.17
A large portion of my academic department’s faculty can be considered to be productive in research	92	3.41	1.06
My department head is very supportive of my efforts in research	92	3.67	1.21
There is a high expectation in my department, school, and/or university for faculty to be productive in research	98	3.71	1.02
The skills, expertise, and experience of the faculty in my department are appropriate to accomplish our goals in research	95	3.74	1.12
I have a clear picture of where I want to be in my research career in five to seven years	98	3.77	.99
I fully understand the research expectations for promotion in the appointment I hold (e.g., tenure track, Full-time clinical scholar).	98	3.83	1.01
I believe I am up-to-date in research skills for my area (e.g., statistics, research design, data collection, laboratory procedure)	97	3.84	1.03
I stay very “up-to-date” on the current literature in my research interest area(s)	97	3.94	.96
I would describe myself as being internally driven to conduct research	95	4.00	.93
I believe I am up-to-date in writing skills	97	4.22	.78
I believe I am up-to-date in computer skills	96	4.22	.84
Note. Items are based off of those originally published in Bland et al. (2005).

Factor structure

Research productivity factor scale: exploratory factor analysis

After excluding the eight items mentioned above with considerable missing-ness due to “N/A” or “don’t know” responses, we conducted an exploratory factor analysis using principal axis factoring. We included factors with an eigenvalue greater than 1.0 initially, using an oblique (“promax”) rotation, which allows factors to be correlated with each other.

The initial extraction showed a strong first factor that explained 26% of the variance. Examining the scree plot, it appears that factors 2–4 explain smaller additional amounts of variance, and starting with factor 5, the eigenvalues are not much greater than what would be expected from random variance. Factors 1–4 accounted for 46% of the variance. We thus reran the factor analysis, constraining it to extract four factors.

Examining the pattern matrix for the four-factor solution (see Table 2), 16 items load onto the first factor most strongly. These items tended to refer to the quality of one’s department, leading us to name this factor “Departmental Environment”; example items include “My department head is very supportive of my efforts in research” (loading = .739) and “I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my department colleagues” (loading = .866).

Table 2

Pattern matrix, four-factor exploratory factor analysis solution for faculty productivity questionnaire items
Item	Factor				Original Bland theoretical factor
Item	1	2	3	4	Original Bland theoretical factor
I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my department head	.930				Leadership
I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my department colleagues	.866				Institutional
My department has systematic and fair mechanisms for non-monetarily recognizing and celebrating achievements (e.g. putting in department newsletter, “toasting” at faculty meetings) in research	.762				Institutional
My department leadership (e.g., department head, senior faculty) make clear the expected ethical standards and practices in research	.743				Institutional
My department head is very supportive of my efforts in research	.739				Leadership
A large portion of my academic department’s faculty can be considered to be productive in research	.720				Institutional
I have a well-developed network of colleagues with whom I discuss research projects within my academic department	.702				Institutional
My department head is highly regarded for his/her research	.700				Leadership
I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my dean	.635	.300			Leadership
I get constructive feedback, guidance, and suggestions that help my efforts to perform research from my colleagues outside my department	.612			− .355	Institutional
The skills, expertise, and experience of the faculty in my department are appropriate to accomplish our goals in research	.558				Institutional
I have excellent opportunities at KAUFD to pursue my interests in research	.536				Institutional
My department has a communication system that allows me to be informed in a timely fashion and adequately about major issues, important events, and upcoming concerns regarding research.	.534				Institutional
My school leadership keeps us on track by clearly emphasizing our core missions of research.	.500				Institutional
At least weekly, I have substantive uninterrupted conversations with important colleagues about research in my department	.467	.319			Institutional
I am a member of a research group in the department	.385				Institutional & Individual
At least weekly, I have substantive uninterrupted conversations with important colleagues about research in my university		.859			Individual
At least weekly, I have substantive uninterrupted conversations with important colleagues about research in my discipline		.809			Individual
At least weekly, I have substantive uninterrupted conversations with important colleagues about research in my school	.349	.589			Institutional & Individual
I am a member of a research group in the discipline		.585			Individual
I am a member of a research group in the university		.535			Individual
I have a well-developed network of colleagues with whom I discuss research projects outside my department/within Univ		.477			Individual
I stay very “up-to-date” on the current literature in my research interest area(s)		.454			Individual
I would describe myself as being internally driven to conduct research		.380	.365		Individual
I am a member of a research group in the school		.371			Institutional & Individual
I believe I am up-to-date in research skills for my area (e.g., statistics, research design, data collection, laboratory procedure)			.685		Individual
I believe I am up-to-date in computer skills			.656		Individual
I believe I am up-to-date in writing skills			.642		Individual
I believe I am up-to-date in grant getting skills for my area (e.g., identifying your funding sources, contacting funding agency personnel, preparing grants, using research reviews)			.535		Individual
I have a well-defined plan for achieving my research career goals			.499	.319	Individual
There is a high expectation in my department, school, and/or university for faculty to be productive in research	.415		.488		Institutional
I have a well-developed network of colleagues with whom I discuss research projects outside the university		.396	.467		Individual
There is a high expectation in my department, school, and/or university to conduct research that is externally funded	.357		.445		Institutional & Individual
I have a clear picture of where I want to be in my research career in five to seven years			.388		Individual
I fully understand the research expectations for promotion in the appointment I hold (e.g., tenure track, Full-time clinical scholar).			.383		Institutional & Individual
I feel appreciated and valued by my local colleagues (dept/school/univ) for my work in research			.329		Institutional
I have access to adequate resources to conduct my research projects such as data analyses and technical support				.769	Institutional
I have access to adequate resources to conduct my research projects such as secretarial support	.379			.668	Institutional
I have access to adequate resources to conduct my research projects such as computers and library materials				.637	Institutional
I have access to adequate resources to conduct my research projects such as research assistants	.426			.544	Institutional
I have space that is well equipped for me to conduct my research				.416	Institutional
My academic department provides me with, or I have from external or other sources, adequate support to travel to research-based conferences					Institutional
I have adequate time to conduct research projects					Institutional
The number of faculty in my department is large enough to accomplish our goals in research					Institutional
I have been (or was when I was a junior faculty member) formally assigned an advisor or mentor within my academic department who provide me with valuable guidance in research					Institutional & Leadership
I have (or had when I was a junior faculty member) an “unassigned” mentor(s) either in this department or in other departments/schools/organizations who provide me with valuable guidance in research					Institutional & Leadership??
Note. Factor extraction method was principal axis factoring. Factor rotation method was promax with Kaiser normalization. Items are based off of those originally published in Bland et al. (2005).

Nine items loaded on the second factor most strongly, which we named “Networking outside of the department”, including items such as “at least weekly, I have uninterrupted substantive conversations with important colleagues about research in my discipline” (loading = .809). Eleven items loaded on the third factor; we named this factor “Individual research orientation & skill”, including items such as “I believe I am up to date in computer skills” (loading = .656). Finally, five items load on the fourth factor, which we named “Research resources”. An example item is “I have access to adequate resources to conduct my research projects, such as secretarial support” (loading = .668). For each person, we computed their factor score on each of the four factors, to be used as predictor variables in the regression model to predict the outcome of interest in the study, number of peer-reviewed publications. Five items did not load on any factors, two of which referred to having mentors, one to have adequate time for research, one to the departmental faculty roster size being adequate for research, and one to support for research conference travel. We elected to create a distinct variable, “Mentoring rating”, that was the average of the two mentoring-related items for subsequent analysis.

Simple relationships of publication predictors with total publication counts

For dichotomous variables (gender, nationality, clinical vs. non-clinical department, and assistant vs. associate rank) as predictors of total publication counts, Mann-Whitney U tests were significant for two of the four predictors: nationality (p = .002; Saudi median publication count = 2, Egyptian = 4) and rank (p = .001; assistant professor median publication count = 2, associate professor median publication count = 5).

For continuous variables (age in years, hours per week devoted to research, the four research productivity factor scale factor scores, and mentoring rating) as predictors of total publication counts, Spearman’s rho correlations were significant for four of the seven predictors: age in years (rho = .34, p = .001), hours per week devoted to research (rho = .35, p < .001), “Networking outside of department” factor score (rho = .24, p = .047), and “Individual research orientation and skill” factor score (rho = .38, p = .001).

Final generalized linear model predicting total publication counts

Significant simple predictors of total publication count from above were entered as predictors in a generalized linear model, with a Poisson distribution and a log link function. Data for 69 participants were retained after omitting participants with missing values on any predictors. Three of six predictors were statistically significant in the model: age in years (B = .029, p = .017), research hours (B = .063, p < .001), and “Individual research orientation and skill” factor score (B = .403, p < .001).

Universities are judged according to the amount and quality of their published research and scientific innovations and discoveries, making it essential to understand how to best support such productivity. We investigated the factor structure and predictive power of Bland and colleagues’ previously-established questionnaire on factors that may predict research productivity. We found that, when using exploratory rather than confirmatory analysis methods, the items did not tend to adhere according to the authors’ theoretical model, but rather sorted into a four-factor solution, where several items corresponded to factors not in the original model. This result was in agreement with Bland et al. [2]. However, they did not change the model based on their results and they suggested that they need further studies from different schools to support their results [2]. Furthermore, we found that, within this institution, existing variance in research productivity was related mainly to differences in age, amount of time devoted to research, and item responses that fell under the “Individual research orientation and skill” factor score.

Gender. There was a significant difference between male and female faculty in research productivity. Male faculty were more productive. This is in agreement with previous studies which showed that male faculty tend to publish more than female faculty [4, 16–17]. However, when considered in a regression model with the other predictors, the association of gender with productivity became non-significant. This suggests that females may publish less due to having fewer hours for research, tending not to be at associate professor rank, and/or other reasons.

Age. There was a high correlation between research productivity and age. This finding is different than some of the previous studies which showed no association between age and research productivity [2, 18]. This could be explained that with age experience in research would increase. However, this too was non-significant when considered in context of the other predictors, suggesting that the effect of age may be better captured by other variables such as academic rank.

Rank. There was a significant difference between associate professor and assistant professor in research productivity. This finding is understandable and it is in agreement with previous studies [2, 4, 19]. Faculty with higher rank had more experience in research than lower rank. Moreover, faculty with higher rank had less teaching hours than lower rank. This might have allowed them to spend more time on their research and become more productive.

Research working hours. There was a high correlation between research productivity and number of research working hours. This is also, understandable. However, the total working hours had no correlation with the research productivity. It exclusively depends on the faculty and how much time they would devote for research.

Although, gender, age, rank, and research working hours were related to research productivity; only rank and research working hours were predictors of research productivity.

While these results suggest that the factor structure of this faculty productivity questionnaire may differ from that suggested by its original authors, we do not mean to suggest that this invalidates or even reduces the usefulness of the questionnaire for evaluating a school’s climate for research productivity, nor do we assert that our factor structure is necessarily more correct. Rather, we suggest that the questionnaire may be used more insightfully if we remain skeptical and curious about how items align, at least until a larger body of research has amassed and a consistent factor structure has emerged. That is, rather than assuming that items sensibly cohere within the original structure, institutions with large enough samples that administer this questionnaire should consider exploring the factor structure of their own data and the ways in which it does or does not align to the original model.

Based on this data, we do not suggest that only the significant correlates with productivity that emerged in this analysis are suitable for intervention for either our institution or others. Since this was a cross-sectional survey, it only speaks to how currently-perceived variability in any of these factors is related to productivity. In the studied institution, the institutional factors may be fairly similar for faculty in different departments. Therefore, productivity may be dependent only on the individual characteristics of the faculty, simply because there is limited variability in the other factors. As schools such as ours pursue different institutional initiatives, it would be possible to re-administer this survey and see if (1) the initiatives relate to changes in faculty members’ perception of the environment for research, and subsequently (2) if those changes in perception are also reflected in increased productivity.

Given that the study was conducted in a single institution, one may not expect these exact results to necessarily generalize more broadly. Study features that do support some generalizability of these findings include the use of previously-published items, sufficient sample size with excellent response rate, and multi-nationality faculty members (Saudis and non-Saudis) with international qualifications.

As academic health centers seek to measure and improve their support of faculty research, our study suggests that faculty input gathered via Bland and colleagues’ (2002) questionnaire may exhibit a factor structure different from that which the authors originally proposed. It will be valuable, as departments and institutions draw comparisons between themselves or between different time points (e.g., before vs. after an intervention to support research productivity), to continue to investigate the validity of this measure and to refine its interpretation and use to support more sound and insightful conclusions.

Ethics approval and consent to participate

This study was approved by the Research Ethics Committee at King Abdulaziz University, Faculty of Dentistry (Proposal No. 020-15). All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from each participant.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

Not applicable.

Authors' contributions

All authors contributed to the design of the study (LB, BE & ML). The data collection was done by LB and the descriptive analysis was done by LB & BE. The rest of the analysis was performed by ML. The manuscript writing was done by LB & ML. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

Author details

¹ Professor, Department of Endodontics, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia, [email protected]; [email protected]

²Professor of community medicine and public health, Vice dean of community service and environmental development, Faculty of Medicine, Damietta University, Egypt, [email protected]

³Director of Simulation Research, Assessment, & Outcomes, Zamierowski Institute for Experiential Learning, University of Kansas Medical Center and Health System, Kansas City, KS, USA, [email protected]

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No competing interests reported.

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Refining the Measurement of Factors Predicting Faculty Research Publications

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Abstract

Introduction

Methods

Participants

Methods

Data collection Procedure

Results

Descriptive statistics

Factor structure

Research productivity factor scale: exploratory factor analysis

Simple relationships of publication predictors with total publication counts

Final generalized linear model predicting total publication counts

Discussion

Conclusion

Declarations

References

Additional Declarations

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