Knowledge Dissemination of Intimate Partner Violence Intervention Studies Measured Using Alternative Metrics: Results From a Scoping Review

Abstract

Alternative metrics measure the number of online mentions that an academic paper receives, including mentions in social media and online news outlets. It is important to monitor and measure dispersion of intimate partner violence (IPV) victim intervention research so that we can improve our knowledge translation and exchange (KTE) processes improving utilization of study findings. The objective of this study is to describe the dissemination of published IPV victim intervention studies and to explore which study characteristics are associated with a greater number of alternative metric mentions and conventional citations. As part of a larger scoping review, we conducted a literature search to identify IPV intervention studies. Outcomes included znumber of alternative metric mentions and conventional citations. Fifty-nine studies were included in this study. The median number of alternative metric mentions was six, and the median number of conventional citations was two. Forty-one percent of the studies (24/59) had no alternative metric mentions, and 27% (16/59) had no conventional citations. Longer time since publication was significantly associated with a greater number of mentions and citations, as were systematic reviews and randomized controlled trial designs. The majority of IPV studies receive little to no online attention or citations in academic journals, indicating a need for the field to focus on implementing strong knowledge dissemination plans. The papers receiving the most alternative metric mentions and conventional citations were also the more rigorous study designs, indicating a need to focus on study quality. We recommend using alternative metrics in conjunction with conventional metrics to evaluate the full dissemination of IPV research.

Keywords

intimate partner violence research methodology scoping review alternative metrics

Introduction

As with many fields, the volume of intimate partner violence (IPV) intervention literature is steadily growing. With that growth comes a need to effectively disseminate the findings of these IPV intervention studies to maximize uptake and use of that information by clinicians, researchers, advocacy organizations, policymakers, and other stakeholders. Despite the growing number of IPV intervention studies, few clinical settings have policies guiding management of patients who have experienced IPV (Hamberger, Rhodes, & Brown, 2015). This could indicate that knowledge translation and exchange (KTE) strategies are lacking in IPV victim intervention research. It is important to monitor and measure impact of IPV victim intervention research so that we can improve our KTE processes, thereby improving utilization of study findings, improving efficiency of research funding, and in the long term, improving the lives of women who have experienced IPV.

One commonly used measure of knowledge dissemination is the number of citations that a published paper receives. This measure is limited as there can be a long delay between publication of a paper and that paper being cited by another paper because of the time lag between article submission and publication (Evaniew et al., 2017). In addition, conventional citation metrics are typically determined solely through academic mentions (e.g., peer-reviewed journal citations) and does not capture the growing role of non-academic means of knowledge dissemination including social media (e.g., Facebook, Twitter, Reddit), scientific and lay media (e.g., online newspapers and science blogs), and online forums (e.g., Mendeley, PubPeer, Publons; Piwowar, 2013). Alternative metrics, which measure the number of online mentions that an academic paper receives and represent rapidly growing and novel approach to measure how widely an article is disseminated (Piwowar, 2013; Woolston, 2014).

KTE is also known as knowledge translation, knowledge to action, knowledge transfer, implementation science, innovation diffusion, and many more terms (Grimshaw, Eccles, Lavis, Hill, & Squires, 2012). A widely used description of KTE is a cyclical process that starts with knowledge creation, moves to identifying the problem, adapting knowledge to local contexts, assessing barriers to knowledge use, designing and implementing interventions based on the knowledge, monitoring knowledge use, evaluating the intervention, and sustaining the interventions, and then cycles back to creation of more knowledge (Graham et al., 2006). It is well-documented that many researchers stop at knowledge creation and their innovations fail to translate to useful policies or practices (Damschroder et al., 2009). Some granting agencies such as the Canadian Institutes of Health Research (CIHR; 2015) emphasize the need to have a KTE plan that goes beyond traditional dissemination (i.e., publishing in an academic journal and/or presenting at conferences), and they have begun to require a written plan for how the knowledge will be disseminated to maximize the impact of their funding. KTE plans will vary greatly for different studies or bodies of literature. An example KTE plan for IPV victim intervention studies could include publication in a high-impact journal, presentation at a relevant conference, a press release, meeting with stakeholder and policy groups to develop a plan of implementation, educating clinicians on victim interventions, and involving patients and health care advocacy groups. The plan should also involve a process for evaluating knowledge dissemination/uptake/usage and sustaining a change in practice (Graham et al., 2006).

Some previous research has been completed on KTE in the IPV field including the importance of research networks (Kothari, Sibbald, & Wathen, 2014) and education of health care professionals and other stakeholders (MacGregor, Wathen, Kothari, Hundal, & Naimi, 2014; Wathen, Sibbald, Jack, & Macmillan, 2011). However, there have been no studies assessing how IPV victim intervention research is disseminated online and cited in peer-reviewed journals, and no studies focusing on alternative metrics in the IPV field.

Objectives

The primary objective of this study is to describe the dissemination of published IPV intervention studies using alternative metrics compared with conventional citation metrics. As a secondary objective, we aim to explore which study characteristics are associated with a greater number of alternative metric mentions and number of conventional citations.

Method

This review of the literature is a sub-study of a recent scoping review that included all published studies investigating IPV victim interventions in health care settings. The full methodology of the scoping review is reported elsewhere (Sprague et al., 2018).

Literature Search

As part of the scoping review, we developed a comprehensive search strategy, in consultation with a health sciences librarian, to search the following electronic databases: MEDLINE, Embase, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Cochrane Database of Systematic Reviews (CDSR), Proquest, and Web of Science. We performed the literature searches in July 2015 and did not use any language or date restrictions. Reviewers screened articles for eligibility in duplicate using Distiller SR software (systematic-review.ca).

Eligibility Criteria

For the current study, we included studies that met the following inclusion criteria: (a) published in English, (b) focus on IPV, (c) evaluate the effectiveness of an IPV program (i.e., identification, assistance, or health care provider education programs focusing on female victims) in a health care setting, (d) the population is adult participants, and (e) published between 2011 and 2015. We only included studies published in 2011 and after because alternative metric data were not available prior to 2011.

Primary Outcome: Alternative Metric Mentions

We collected alternative metric data from Altmetric LLP (http://www.altmetric.com/), which is a leading alternative metric company in academic research (Adie & Roe, 2013; Woolston, 2014). The Altmetric index is a weighted score given to individual journal articles based on a proprietary algorithm combining online mentions of an academic article, including social media, online science and mainstream news, blogs, and other academic and lay online sources. The Altmetric index is increasingly being used by academic journals to summarize and highlight non-conventional citations of academic publications (Woolston, 2014). We used Altmetric’s package for R (rAltmetric; freely available) to retrieve all alternative metric mentions including overall number of alternative metric mentions and number of alternative metric mentions per source.

Secondary Outcome: Conventional Metrics

We collected number of conventional citations (i.e., citations in academic journals) using Thomson Reuters Web of Science citation reports for each study. To avoid entry errors, this was completed in duplicate.

Study, Journal, and Author Characteristics

We collected the following for each included article: month and year of publication, study design, study topic (IPV assistance, IPV education, or IPV identification), journal impact factor (IF), and h-index of first and last authors. We defined the study topics as follows: (a) IPV identification studies (also known as screening studies) aim to screen or identify victims of IPV but not provide clinical intervention, (b) IPV assistance programs pair identification of victims with an intervention that aims to improve health or social outcomes (e.g., referral to services, counseling, etc.), and (c) IPV education studies evaluate an education intervention for health care professionals to assist victims of IPV (Sprague et al., 2018). The h-index is a widely used measure of an author’s impact defined as having h publications cited h times or more (Hirsch, 2005). For example, an author with an h-index of 15 would have 15 publications cited at least 15 times. Impact factor, however, is a journal-level metric, which measures the average number of citations that a journal has over a set period of time (e.g., past 5 years for a 5-year IF; Fersht, 2009). We collected h-indices using Thomson Reuters Web of Science. We obtained journal impact factors from Journal Citation Reports in the Thomson Reuters Institute for Scientific Information (ISI) Web of Knowledge. To avoid entry errors, we completed data extraction in duplicate.

Statistical Analysis

We present study characteristics as counts with percentages for frequency data, and as medians with first and third quartiles for continuous data. To explore associations between study characteristics and number of alternative metric mentions and conventional citations, we conducted multivariable negative binomial regression analyses. We used negative binomial regression because the dependent variables are discrete count data. Before the study began, we hypothesized that time since publication (in months), journal impact factor, study design (randomized controlled trial [RCT] vs. systematic review vs. other designs), number of conventional citations, and h-index of the last author would be significantly associated with having more alternative metric mentions. Similarly, we hypothesized that time since publication (in months), journal impact factor, study design (RCT vs. systematic review vs. other designs), number of alternative metric mentions, and h-index of the last author would be significantly associated with having more conventional citations. We based these hypotheses on a previous study of alternative metrics in orthopedic surgery trials (Evaniew et al., 2017). We also conducted a sensitivity analysis removing one predictor from the model if there was evidence of multicollinearity. We present regression analyses with the β coefficient, 95% confidence interval (95% CI), and p value for each characteristic. There was very little missing information so we did not impute for missing data. All analyses were conducted using SPSS Version 23.

Results

Study Characteristics

Of 187 studies from the scoping review considered for this study, we excluded 126 because they were published before 2011 and we excluded two because they focus on perpetrator interventions as opposed to victim interventions. Therefore, 59 studies met our eligibility criteria and were included in this study (Figure 1). We included 22 (37%) IPV assistance program studies, 19 (32%) IPV education studies, and 18 (31%) IPV identification studies. The most common study designs were qualitative/mixed methods (14/59, 24%), RCTs (12/59, 20%), and pre-test/post-test studies (11/50, 19%). The median journal impact factor was 1.84 (quartiles: 0.95-2.89). The median h-index of the last author (nine; quartiles: 3-17) was higher than that of the first author (four; quartiles: 2-10). Full study characteristics can be found in Table 1.

Figure 1.

Study flow diagram.

Table 1.

Characteristics of Included Studies.

Study Characteristics	Number of Studies (%)
Year
2011	14 (23.7)
2012	10 (16.9)
2013	10 (16.9)
2014	15 (25.4)
2015	10 (16.9)
Study design
Randomized controlled trial	12 (20.3)
Systematic review	7 (11.9)
Pre-test/post-test or quasi-experimental	11 (18.6)
Cohort	6 (10.2)
Cross-sectional	7 (11.9)
Qualitative or mixed methods	14 (23.7)
Other	2 (3.4)
Study topic
IPV assistance program	22 (37.3)
IPV education program	19 (32.2)
IPV identification program	18 (30.5)
Journal and Author Characteristics	Median (First and Third Quartiles)
Journal impact factor	1.84 (0.95-2.89)
H-index first author	4 (2-10)
H-index last author	9 (3-17)
Outcomes	Median (First and Third Quartiles)
Conventional citations	2 (0-9)
Alternative metric mentions	6 (0-23)

Note. IPV = intimate partner violence.

Number of Citations

The 59 included studies had a total of 544 conventional citations and 1,108 alternative metric mentions (Figure 2). The median number of alternative metric mentions was nine (quartiles: 0-23), and the median number of conventional citations was two (quartiles: 0-9). Twenty-four of 59 studies (41%) had no alternative metric mentions, and 16 of 59 studies (27%) had no conventional citations. Alternative metric mentions were primarily driven by Mendeley (63%) and Twitter (33%) with Facebook, news outlets, and blogs making up the majority of the remaining sources (Figure 3).

Figure 2.

Alternative (A) and conventional (B) citations frequency distributions.

Figure 3.

Proportion of alternative metric mentions by source.

Factors Associated With Alternative Metric Mentions

In the multivariable analysis, systematic reviews (β = 1.91, 95% CI = [0.90, 2.92]) and RCTs (β = 1.32, 95% CI = [0.26, 2.38]) had a significantly higher number of alternative metric mentions, as did papers published a longer time ago (β = 0.03, 95% CI = [0.01, 0.05]; Table 2). However, impact factor, conventional citations, and h-index of the last author were not significantly associated (Table 2). Because of high correlation between two of our study characteristics (h-index and impact factor), we conducted a sensitivity analysis removing h-index of the last author, but it did not affect any of the model parameters greatly so we decided to include both h-index and impact factor in the model.

Table 2.

Multivariable Negative Binomial Regression of Study Characteristics on Number of Alternative Metric Mentions.

Characteristic	β Coefficient	95% CI	p Value
Time since publication (months)	0.03	[0.01, 0.05]	.015
Impact factor	0.06	[−0.01, 0.12]	.094
Study design
Systematic review	1.91	[0.90, 2.92]	<.001
RCT	1.32	[.26, 2.38]	.015
Other	REF
Conventional citations	−0.03	[−0.08, 0.03]	.327
H-index last author	0.01	[−0.03, 0.04]	.602

Note. Omnibus test: p < .001. CI = confidence interval; RCT = randomized controlled trial; REF = reference category.

Factors Associated With Conventional Citations

Similar to the alternative metric mentions analysis, systematic reviews (β = 1.91, 95% CI = [0.80, 3.02]) and RCTs (β = 1.17, 95% CI = [0.13, 2.22]) had a significantly higher number of alternative metric mentions, as did papers published a longer time ago (β = 0.05, 95% CI = [0.03, 0.08]; Table 3). However, impact factor, alternative metric mentions, and h-index of the last author were not significantly associated (Table 3).

Table 3.

Multivariable Negative Binomial Regression of Study Characteristics on Number of Conventional Citations.

Characteristic	β Coefficient	95% CI	p Value
Time since publication (months)	0.05	[0.03, 0.08]	<.001
Impact factor	0.04	[−0.01, 0.09]	.104
Study design
Systematic review	1.91	[0.80, 3.02]	.001
RCT	1.17	[0.13, 2.22]	.028
Other	REF
Alternative metric mentions	0.01	[−0.01, 0.02]	.326
H-index last author	−0.03	[−0.7, 0.01]	.069

Note. Omnibus test: p < .001. CI = confidence interval; RCT = randomized controlled trial; REF = reference category.

Discussion

In this study, we found that increasingly rigorous study designs (systematic reviews and RCTs) received more alternative metric mentions and conventional citations than other study designs. In addition, longer time since publication was also associated with studies having more alternative metric mentions and conventional citations, which is plausible because it takes time for citations to build up. IPV intervention studies have more alternative metric mentions than conventional citations, indicating the growing importance of online news and social media in distributing academic findings. Despite this, a large proportion of IPV intervention studies have no alternative and/or conventional citations, stressing the importance of having a good KTE plan and focusing on improving the quality of IPV literature.

Traditionally, a researcher’s impact has been evaluated based largely on the quality of the journals in which he or she published (i.e., the journal’s impact factor). However, there have been criticisms of using a journal-level metric such as impact factor to determine an individual paper’s impact (Cress, 2014). Number of citations in peer-reviewed journals has also been used to measure an individual paper’s impact, but this ignores the impact that a paper has on the community and potential stakeholders (Dinsmore, Allen, & Dolby, 2014). It has been suggested that alternative metrics be used in addition to conventional metrics to give a more complete picture of a paper’s impact (Cress, 2014; Dinsmore et al., 2014; Evaniew et al., 2017). However, some academics disagree, believing that alternative metrics contribute to the problem of quantity over quality (Cheung, 2013). The results of the current study and Evaniew et al. (2017) study show that alternative metric mentions are associated with higher level of evidence studies and lower risk of bias, respectively, indicating that alternative metrics are valid indicators of higher quality studies. There is even some evidence that alternative metric mentions can predict future conventional citations, which is important because they have the advantage of accumulating faster than conventional citations (Evaniew et al., in press; Thelwall et al., 2013). We therefore recommend using alternative metrics in addition to conventional metrics to evaluate impact of research, which is in line with the San Francisco Declaration on Research Assessment (DORA) initiative to standardize how research impact is assessed (Donato, 2014).

Few previous studies have described patterns of alternative metric mentions among academic studies. Evaniew et al. (2017) explored the impact of orthopedic surgery trials and found a similar pattern. However, in our study, we found a higher median number of alternative metric mentions compared with that of orthopedic trials (six vs. two, respectively). The median number of conventional citations was more similar (two vs. three, respectively). It is arguable that IPV studies are very relevant and interesting to the public compared with many orthopedic papers in which interest may be more specialized to clinicians. This could account for the large difference in alternative metric mentions. Alternatively, this difference could be due to varying patterns of online dissemination between fields. Dinsmore et al. (2014) described the number of Twitter mentions of Wellcome Trust-funded papers published in PLOS and found that there are a large number of studies with no Twitter mentions and very few that have a high number of Twitter mentions. This is similar to what we found in the current study. It is concerning that such a large percentage of the IPV literature receives no online mentions and/or no conventional citations. It is possible that some of the literature is of insufficient quality to be of use in practice or policy. For example, Sprague et al. (2017) found that many IPV studies use inappropriate or sub-optimal outcome measures when evaluating IPV interventions. It is also a possibility that high-quality studies are not being promoted as widely as they could because of insufficient emphasis on KTE plans. The relationship between study quality and alternative citation patterns is an area for future investigation and could indicate that the IPV field needs to focus on generating high-quality literature. We also hypothesize that public interest in the topic or the “virality” (as with viral videos and online memes) of the content matter can drive online activity, which is another area for future exploration.

We hypothesized that impact factor would be significantly associated with number of alternative metric mentions, but the association was not significant in the multivariable analysis. We observed that almost all of the papers published in low impact factor journals that received a large number of alternative metric mentions were RCTs or systematic reviews. This observation warrants further investigation, but we hypothesize that study design is especially important in the IPV field, because IPV intervention RCT findings tend to be controversial and lead to conflicting guideline recommendations (MacMillan & Feder, 2012; Moyer & U.S. Preventive Services Task Force, 2013; U.S. Preventive Services Task Force, 2004). It is also possible that we were unable to find a significant association due to lack of power, given that our multivariable analysis was exploratory in nature.

Strengths of this study include a systematic and thorough search of the literature and that our findings converge with previous research in other fields. Our study is limited to studies published in English only and may not be applicable to studies published in other languages. Our study is also limited in that neither conventional citation metrics nor alternative metric mentions account for type of attention. It is possible that certain studies gain more attention not because of high quality, but because of controversial findings, leading to negative media attention. Our findings are limited to online citations indexed by Altmetric LLP, which is linked to a paper’s DOI or PMID. It could be possible that Altmetric’s algorithm could have missed some online citations, but Altmetric is currently the industry leader in providing online article-level metrics to high-impact journals (Adie & Roe, 2013; Woolston, 2014). In addition, a larger number of included studies would be ideal to better explore factors associated with number of citations and mentions.

The majority of IPV studies receive very little to no online attention, indicating a need for the field to focus on implementing strong KTE plans to maximize research dissemination. We also recommend using alternative metrics in conjunction with conventional metrics to evaluate the full dissemination of IPV research to academic and non-academic stakeholders. Future research should focus on methods of disseminating IPV studies while maintaining high standards of methodological quality to improve efficiency of IPV research with the aim of improving life for as many women who have experienced IPV as possible.

Footnotes

Acknowledgements

We would like to acknowledge the support of the IPV Scoping Review collaborators—Data Collection: Erika Arseneau, Muzammil Memon, Lucshman Raveendran, Hayley Spurr, and Aparna Swaminathan; Knowledge Users: Jason Busse, Ari Collerman, Vanina Dal Bello-Haas, Samir Faidi, David Florkowski, Clare Freeman, Nisha Gupta, Norma MacIntyre, Brad Petrisor, Angela Reitsma, Emil Schemitsch, Doug Thomson, Diana Tikasz, Milena Vicente, and Andrew Worster; Methodological Support: Gina Agarwal and Gerard Slobogean; Administrative Support: Alisha Garibaldi, Paula McKay, Sofia Bzovsky, and Kerry Tai; and Literature Search Support: Neera Bhatnagar.

Author Contributions

K.M. and N.E. designed the study. S.S., L.T., and M.B. refined the study design. K.M., E.D., T.S., C.S.L., and P.D. collected study data. K.M. drafted the manuscript, and all authors critically revised the manuscript. All authors reviewed and approved the manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is funded by a Canadian Institutes of Health Research (CIHR) Knowledge Synthesis Grant (principal investigator [PI]: Dr. Sprague). Ms. Madden and Dr. Evaniew are funded by CIHR Doctoral Scholarships. The funders had no role in designing, drafting, or approving this protocol.

Author Biographies

Kim Madden is a doctoral student in the Department of Clinical Epidemiology & Biostatistics and a research coordinator at the Centre for Evidence-Based Orthopaedics at McMaster University. She has more than 6 years of experience managing large multicentre trials, promoting evidence-based medicine, and she managed the large multinational PRAISE study on the prevalence of IPV in orthopedics that garnered worldwide media attention and was published in the Lancet.

Nathan Evaniew is an orthopedic surgery resident at the Centre for Evidence-Based Orthopaedics at McMaster University and a doctoral student in the Department of Clinical Epidemiology & Biostatistics at McMaster University. His primary research and subspecialty interests are spine surgery, orthopedic oncology, and evidence-based orthopedics.

Taryn Scott is a research coordinator at the Centre for Evidence-Based Orthopaedics at McMaster University. She is the primary coordinator of a large scoping review of intimate partner violence (IPV) intervention studies. She has a master’s of social work degree and is currently completing a master’s degree in health research methodology.

Elena Domazetoska is an honors life sciences undergraduate student at McMaster University with a growing interest in epidemiology and research methodology.

Pritnek Dosanjh completed his undergraduate degree from the University of Toronto, and his medical degree abroad in Dominica and Chicago, Illinois. He is currently looking forward to a residency position in family medicine.

Chuan Silvia Li is a research coordinator at the Centre for Evidence-Based Orthopaedics at McMaster University. She is currently completing a master’s degree in health research methodology. She has extensive programming experience in modeling and simulation as well as the design of clinical trials.

Lehana Thabane is a professor in the Department of Clinical Epidemiology & Biostatistics at McMaster University. His primary research interest is the development and application of statistical methods in health research.

Mohit Bhandari is a professor and academic head of Orthopaedic Surgery at McMaster University. In addition to being one of the world’s foremost orthopedic researchers, he has dedicated more than a decade of his career to IPV research and assisting victims of IPV. His efforts promoting evidence-based medicine and assisting IPV victims have earned him numerous awards including the Order of Ontario, a Canada Research Chair, induction into the Hamilton Gallery of Distinction, and Canadian Medical Association Journal’s Top Researcher Award.

Sheila Sprague is an assistant professor in the Department of Surgery and research methodologist at the Centre for Evidence-Based Orthopaedics at McMaster University. Her PhD thesis included the large multinational PRAISE study on the prevalence of IPV in orthopedics that garnered worldwide media attention and was published in the Lancet. She is currently principal investigator of a large scoping review of IPV intervention studies.

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