Mary E. Slaughter

3.2k total citations · 1 hit paper
62 papers, 2.2k citations indexed

About

Mary E. Slaughter is a scholar working on General Health Professions, Health and Economics and Econometrics. According to data from OpenAlex, Mary E. Slaughter has authored 62 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in General Health Professions, 13 papers in Health and 11 papers in Economics and Econometrics. Recurrent topics in Mary E. Slaughter's work include Health Policy Implementation Science (12 papers), Health disparities and outcomes (12 papers) and Patient Satisfaction in Healthcare (10 papers). Mary E. Slaughter is often cited by papers focused on Health Policy Implementation Science (12 papers), Health disparities and outcomes (12 papers) and Patient Satisfaction in Healthcare (10 papers). Mary E. Slaughter collaborates with scholars based in United States, Uganda and Norway. Mary E. Slaughter's co-authors include Beth Ann Griffin, Daniel F. McCaffrey, Rajeev Ramchand, Daniel Almirall, Lane F. Burgette, Regina A. Shih, Joie Acosta, Sudha K. Iyengar, Chloe E. Bird and Joseph T. Barr and has published in prestigious journals such as American Journal of Public Health, Social Science & Medicine and Journal of the American Society of Nephrology.

In The Last Decade

Mary E. Slaughter

56 papers receiving 2.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A tutorial on propensity score estimation for multiple treatments using generalized boosted models

2013 1.0k citations Daniel F. McCaffrey, Beth Ann Griffin et al. Statistics in Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mary E. Slaughter United States	20	478	321	276	244	235	62	2.2k
Michael Coory Australia	33	578 1.2×	701 2.2×	578 2.1×	335 1.4×	242 1.0×	147	4.8k
Beth Ann Griffin United States	25	578 1.2×	403 1.3×	478 1.7×	392 1.6×	416 1.8×	121	3.3k
Eve Wittenberg United States	21	478 1.0×	331 1.0×	278 1.0×	514 2.1×	214 0.9×	48	2.0k
Lynette Lim Australia	28	681 1.4×	372 1.2×	412 1.5×	294 1.2×	236 1.0×	64	3.1k
Jeanne Jackson United States	26	681 1.4×	232 0.7×	232 0.8×	620 2.5×	240 1.0×	71	3.5k
Lane F. Burgette United States	18	234 0.5×	159 0.5×	231 0.8×	355 1.5×	89 0.4×	69	2.1k
Michael Baiocchi United States	24	294 0.6×	170 0.5×	473 1.7×	207 0.8×	160 0.7×	81	2.4k
Allen Fremont United States	20	1.0k 2.2×	356 1.1×	231 0.8×	443 1.8×	320 1.4×	54	2.4k
Ora L. Strickland United States	22	612 1.3×	581 1.8×	288 1.0×	128 0.5×	170 0.7×	67	3.6k
Paula Lorgelly United Kingdom	29	697 1.5×	254 0.8×	171 0.6×	855 3.5×	232 1.0×	122	2.3k

Countries citing papers authored by Mary E. Slaughter

Since Specialization

Citations

This map shows the geographic impact of Mary E. Slaughter's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mary E. Slaughter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mary E. Slaughter more than expected).

Fields of papers citing papers by Mary E. Slaughter

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mary E. Slaughter. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mary E. Slaughter. The network helps show where Mary E. Slaughter may publish in the future.

Co-authorship network of co-authors of Mary E. Slaughter

This figure shows the co-authorship network connecting the top 25 collaborators of Mary E. Slaughter. A scholar is included among the top collaborators of Mary E. Slaughter based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mary E. Slaughter. Mary E. Slaughter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Predmore, Zachary, et al.. (2025). Language Concordance and Interpreter Use in Primary Care: Perspectives from Spanish-preferring Patients. Journal of Immigrant and Minority Health. 28(1). 187–202.

Slaughter, Mary E., et al.. (2024). A Comparative Analysis of the Demographics and Zip Codes of Patients Seen at the Indiana University Student Outreach Clinic. Journal of Community Health. 49(4). 708–717. 2 indexed citations

Quigley, Denise D., Mary E. Slaughter, Nabeel Qureshi, & Ron D. Hays. (2024). Associations of Primary Care Provider Burnout with Quality Improvement, Patient Experience Measurement, Clinic Culture, and Job Satisfaction. Journal of General Internal Medicine. 39(9). 1567–1574. 5 indexed citations

Herman, Patricia M., Mary E. Slaughter, Nabeel Qureshi, et al.. (2024). Comparing Health Survey Data Cost and Quality Between Amazon’s Mechanical Turk and Ipsos’ KnowledgePanel: Observational Study. Journal of Medical Internet Research. 26. e63032–e63032. 2 indexed citations

Hays, Ron D., Patricia M. Herman, Anthony Rodriguez, et al.. (2024). The PROMIS-16 reproduces the PROMIS-29 physical and mental health summary scores accurately in a probability-based internet panel. Quality of Life Research. 34(1). 19–26. 2 indexed citations

Martino, Steven C., Kerry Reynolds, Rachel Grob, et al.. (2023). Evaluation of a protocol for eliciting narrative accounts of pediatric inpatient experiences of care. Health Services Research. 58(2). 271–281. 4 indexed citations

Quigley, Denise D., Marc N. Elliott, Mary E. Slaughter, Efrain Talamantes, & Ron D. Hays. (2023). Shadow Coaching Improves Patient Experience for English-Preferring Patients but not for Spanish-Preferring Patients. Journal of General Internal Medicine. 38(11). 2494–2500. 2 indexed citations

Rodriguez, Anthony, Patricia M. Herman, Mary E. Slaughter, Maria Orlando Edelen, & Ron D. Hays. (2023). Classifying patients with non-specific chronic low back pain using the impact stratification score in an online convenience sample. BMC Musculoskeletal Disorders. 24(1). 719–719. 1 indexed citations

Hays, Ron D., Nabeel Qureshi, Maria Orlando Edelen, et al.. (2022). Crosswalking the National Institutes of Health Impact Stratification Score to the PEG. Archives of Physical Medicine and Rehabilitation. 104(3). 425–429. 3 indexed citations

10.

Quigley, Denise D., Marc N. Elliott, Mary E. Slaughter, Efrain Talamantes, & Ron D. Hays. (2022). Follow-Up Shadow Coaching Improves Primary Care Provider-Patient Interactions and Maintains Improvements When Conducted Regularly: A Spline Model Analysis. Journal of General Internal Medicine. 38(1). 221–227. 5 indexed citations

11.

Slaughter, Mary E., et al.. (2022). Childcare Issues and the Pandemic: Working Women’s Experiences in the Face of COVID-19. Societies. 12(4). 103–103. 10 indexed citations

12.

Quigley, Denise D., et al.. (2021). Provider and coach perspectives on implementing shadow coaching to improve provider–patient interactions. Journal of Evaluation in Clinical Practice. 27(6). 1381–1389. 3 indexed citations

13.

Hays, Ron D., Mary E. Slaughter, Karen L. Spritzer, & Patricia M. Herman. (2021). Assessing the Significance of Individual Change in 2 Samples of Patients in Treatment for Low Back Pain Using 5 Different Statistical Indicators. Journal of Manipulative and Physiological Therapeutics. 44(9). 699–706. 4 indexed citations

14.

Hunter, Sarah B., Bing Han, Mary E. Slaughter, Susan H. Godley, & Bryan R. Garner. (2017). Predicting evidence-based treatment sustainment: results from a longitudinal study of the Adolescent-Community Reinforcement Approach. Implementation Science. 12(1). 75–75. 32 indexed citations

15.

Chinman, Matthew, Joie Acosta, Patricia A. Ebener, Patrick S. Malone, & Mary E. Slaughter. (2017). A Cluster-Randomized Trial of Getting To Outcomes’ Impact on Sexual Health Outcomes in Community-Based Settings. Prevention Science. 19(4). 437–448. 19 indexed citations

16.

Chinman, Matthew, Joie Acosta, Patricia A. Ebener, Patrick S. Malone, & Mary E. Slaughter. (2015). Can implementation support help community-based settings better deliver evidence-based sexual health promotion programs? A randomized trial of Getting To Outcomes®. Implementation Science. 11(1). 78–78. 37 indexed citations

17.

McCaffrey, Daniel F., Beth Ann Griffin, Daniel Almirall, et al.. (2013). A tutorial on propensity score estimation for multiple treatments using generalized boosted models. Statistics in Medicine. 32(19). 3388–3414. 1014 indexed citations breakdown →

18.

Slaughter, Mary E., et al.. (2012). The Small Business Course: What Executives Want and What Educators Teach. The Journal of Education for Business.

19.

Pollack, Craig Evan, Mary E. Slaughter, Beth Ann Griffin, Tamara Dubowitz, & Chloe E. Bird. (2012). Neighborhood socioeconomic status and coronary heart disease risk prediction in a nationally representative sample. Public Health. 126(10). 827–835. 24 indexed citations

20.

Pane, John F., et al.. (2009). Math Science Partnership of Southwest Pennsylvania: Measuring Progress toward Goals. Monograph..

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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