Abstract
Introduction:
Screening for interpersonal violence is used in health care settings to identify patients experiencing violence. However, using unvalidated screening tools may misclassify patients’ experience with violence. The Center for Medicare & Medicaid Innovation adapted a previously validated intimate partner violence screening tool for use in assessing interpersonal violence and retained the tool’s original scoring rubric, despite the new tool’s broader scope. This study evaluated the scoring system for detecting safety concerns.
Methods:
Cross-sectional survey of a convenience sample of adult patients and caregivers of pediatric patients at seven primary care clinics and four emergency departments (2018–2019). Surveys included the adapted four-item Hurt Insult Threat Scream (HITS) tool. Questions are scored by frequency on a Likert scale (1=“Never”; 5=“Frequently”). Scores 11–20 are considered “positive” for safety concerns. Two-sided Fisher’s exact tests were used for descriptive analyses. Data analyses occurred 2019–2020.
Results:
Of 1,014 participants, 66 (6.5%) reported any frequency of physical violence. Of these, 54/66 (81.8%) did not reach the threshold score of 11. 93/1014 (9.2%) reported any frequency of physical violence or being threatened with harm; 76/93 (81.7%) scored <11.
Conclusions:
Using the original scoring criteria for the adapted HITS, >80% of participants reporting physical violence did not screen positive for potential safety concerns. The scoring criteria did not reliably identify participants experiencing or at high risk for violence. To improve patient safety, the adapted HITS scoring rubric should be updated based on stakeholder input and additional validation studies.
Introduction
Adverse health outcomes are strongly linked to intimate partner violence in women.1,2 The U.S. Preventive Services Task Force (USPSTF) and multiple professional organizations therefore recommend screening reproductive age women for intimate partner violence in health care settings.1,3 To facilitate screening, USPSTF recommends several tools that have undergone psychometric testing.1,4,5 However, none have been validated for identifying risk for interpersonal violence (i.e. risk for violence more broadly, including an intimate partner). Implementing unvalidated screening tools may misclassify patients’ experiences of violence and result in missed intervention opportunities.
Unlike intimate partner violence, no USPSTF guidelines recommend screening for interpersonal violence.1 USPSTF found insufficient evidence to support screening for elder abuse or violence in vulnerable populations.1 However, an analysis of the 2017–2018 National Survey of Healthcare Organizations found interpersonal violence was the social risk most commonly assessed in many health care settings.6 This finding is difficult to interpret because, although not synonymous, the terms domestic violence, intimate partner violence, and interpersonal violence are often conflated.7 Furthermore, screening tools to assess various forms of violence have been adapted primarily from intimate partner violence tools without additional psychometric testing.8
The Center for Medicare and Medicaid Innovation (CMMI) developed the Accountable Health Communities (AHC) Health-Related Social Needs Screening Tool to evaluate patients for unmet social needs.8 The tool screens five core domains including housing instability, food insecurity, transportation problems, utility needs, and safety concerns. CMMI adapted the Hurt Insult Threat Scream (HITS) tool, originally designed to detect intimate partner violence in women,9 to screen for interpersonal violence across all gender identities. In this study, we analyzed the adapted HITS to evaluate how the original tool’s scoring criteria impacts the ability to detect safety concerns.
Methods
We conducted a multi-site cross-sectional survey of adult patients or caregivers of pediatric patients (2018–2019). Eligibility, recruitment, and study sample have been described previously.10 The study was approved by the University of California, San Francisco IRB.
Measures
The primary outcome measure, reporting any frequency of verbal or physical violence, was assessed using the CMMI-adapted HITS screening tool. USPSTF recommends HITS to screen for intimate partner violence in reproductive age women.1 HITS includes four questions, one on physical violence and three on verbal violence (Table 1). Questions are scored based on frequency of experience (1=“Never”; 5=“Frequently”). Total scores range 4–20. A scoring rubric for the original tool was validated in adult female survivors of intimate partner violence; scores ≥11 signal a strong likelihood of intimate partner violence.9
Table 1.
| Original HITS | Adapted HITS |
|---|---|
| How often does your partner physically hurt you? | How often does anyone, including family and friends, physically hurt you? |
| How often does your partner insult or talk down to you? | How often does anyone, including family and friends, insult or talk down to you? |
| How often does your partner threaten you with physical harm? | How often does anyone, including family and friends, threaten you with harm? |
| How often does you partner scream or curse at you? | How often does anyone, including family and friends, scream or curse at you? |
Answer options and associated scoring for both tools: Never (1), Rarely (2), Sometimes (3), Fairly often (4), Frequently (5)
Neither the original tool nor the CMMI adaptation specified a timeframe.
In 2016, as part of its AHC demonstration project, CMMI broadened HITS to include interpersonal violence.8 The original questions’ stem asks about frequency of violence by a partner: “How often does your partner….” The adapted measure asks, “How often does anyone, including family or friends….” (Table 1). CMMI recommends using the original HITS scoring cutoff, noting “a score of 11 or more … shows that the person might not be safe.”8 This scoring cutoff has not been validated using the modified question stems. HITS has been further validated in other settings, such as the Veterans Health Administration, and optimal cutoff scores were lower than the original scoring cutoff of 11.11 Other studies in specific populations, including men and Spanish-speaking populations, both of whom are eligible for participation in the demonstration project, have shown similar findings.12,13
Additional measures in this study included participant demographics, health care-based discrimination, and clinician trust.10 Trust and prior discrimination were included given their documented effects on violence reporting.14,15
Statistical Analyses
Two-sided Fisher’s exact tests described patterns of 1) reporting any frequency of physical violence, 2) reporting any frequency of verbal violence, and 3) scoring <11 on the adapted HITS. All data analyses were conducted using Stata/SE 15.0 (2019–2020).
Results
Of 1,014 participants (Figure S1), 66 (6.5%) reported any frequency of physical violence; 54/66 (81.8%) scored <11 (Figure 1a). Among those below the threshold, 3/54 (5.6%) reported “fairly often” or “frequently” being physically hurt, while 14/54 (25.9%) reported “sometimes.”
Figure 1a.
Overall screening results for physical violence among 1014 adult participants using the adapted HITS screener
394/1014 (38.9%) reported any frequency of verbal violence; 376/394 (95.4%) scored <11 (Figure 1b). 1/376 (0.3%) reported “fairly often” being threatened with harm, while 24/376 (6.4%) reported “fairly often” or “frequently” being insulted or screamed at. 93/1014 (9.2%) reported any frequency of physical violence or being threatened with harm; 76/93 (81.7%) scored <11.
Figure 1b.
Overall screening results for verbal violence among 1014 adult participants using the adapted HITS screener
Participants reporting any frequency of physical or verbal violence reported significantly lower trust in their clinicians and higher rates of experiencing discrimination in a health care setting. Table 2, Tables S1–S2 include additional participant level factors associated with reporting different forms of violence. In stratified analyses, rates of reporting any physical or verbal violence were more common among younger women and younger men, though differences were not statistically significant (Table S3). Threats of harm and physical violence co-occurred in approximately 50% of participants reporting either form of abuse (Table S4). Rates of reporting fairly often/frequently being screamed/cursed at or insulted were low (Table S1).
Table 2:
Characteristics of 1014 participants, stratified by reporting any frequency of violence, and total scores ≥11
| Total | Any verbal violencea N=344 (34%) | No verbal violence N=670 (66%) | Fischer’s exact p value | Any physical violence N=66 (7%) | No physical violence N=948 (93%) | Fischer’s exact p value | HITS Score ≥11b N=18 (2%) | HITS Score <11 N=996 (98%) | Fischer’s exact p value | |
|---|---|---|---|---|---|---|---|---|---|---|
| N | N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | ||||
| Participant characteristics | ||||||||||
| Agec (years) (Nd=1000) | ||||||||||
| 18–44 | 547 | 203 (37.1) | 344 (62.9) | 39 (7.1) | 508 (92.9) | 10 (1.8) | 537 (98.2) | |||
| 45–64 | 294 | 127 (43.2) | 167 (56.8) | 17 (5.8) | 277 (94.2) | 7 (2.4) | 287 (97.6) | |||
| ≥65 | 159 | 60 (37.7) | 99 (62.3) | 0.22 | 9 (5.7) | 150 (94.3) | 0.72 | 1 (0.6) | 158 (99.4) | 0.46 |
| Sexc (N=996) | ||||||||||
| Female | 705 | 249 (35.3) | 456 (64.7) | 42 (6.0) | 663 (94.0) | 11 (1.6) | 694 (98.4) | |||
| Male | 291 | 136 (46.7) | 155 (53.3) | 0.001 | 23 (7.9) | 268 (92.1) | 0.26 | 7 (2.4) | 284 (97.6) | 0.43 |
| Race/Ethnicity (N=957) | ||||||||||
| Non-Hispanic White | 353 | 148 (41.9) | 205 (58.1) | 16 (4.5) | 337 (95.5) | 5 (1.4) | 348 (98.6) | |||
| Non-Hispanic Black | 208 | 84 (40.4) | 124 (59.6) | 12 (5.8) | 196 (94.2) | 3 (1.4) | 205 (98.6) | |||
| Hispanic | 314 | 98 (31.2) | 216 (68.8) | 30 (9.6) | 284 (90.4) | 4 (1.3) | 310 (98.7) | |||
| Non-Hispanic Other/Multiple Races | 82 | 39 (47.6) | 43 (52.4) | 0.007 | 4 (4.9) | 78 (95.1) | 0.07 | 6 (7.3) | 76 (92.7) | 0.02 |
| Preferred Language (N=1014) | ||||||||||
| English | 844 | 354 (41.9) | 490 (58.1) | 41 (4.9) | 803 (95.1) | 16 (1.9) | 828 (98.1) | |||
| Spanish | 170 | 40 (23.5) | 130 (76.5) | <0.001 | 25 (14.7) | 145 (85.3) | <0.001 | 2 (1.2) | 168 (98.8) | 0.75 |
| Education (N=1002) | ||||||||||
| <12 years | 175 | 60 (34.3) | 115 (65.7) | 20 (11.4) | 155 (88.6) | 4 (2.3) | 171 (97.7) | |||
| ≥12 years | 827 | 328 (39.7) | 499 (60.3) | 0.20 | 46 (5.6) | 781 (94.4) | 0.007 | 14 (1.7) | 813 (98.3) | 0.54 |
| Income (N=849) | ||||||||||
| $0-$10,000 | 220 | 104 (47.3) | 116 (52.7) | 20 (9.1) | 200 (90.9) | 10 (4.6) | 210 (95.4) | |||
| $10,001-$25,000 | 184 | 78 (42.4) | 106 (57.6) | 16 (8.7) | 168 (91.3) | 3 (1.6) | 181 (98.4) | |||
| $25,001-$50,000 | 185 | 80 (43.2) | 105 (56.8) | 13 (7.0) | 172 (93.0) | 1 (0.5) | 184 (99.5) | |||
| $50,001-$75,000 | 81 | 42 (51.9) | 39 (48.1) | 3 (3.7) | 78 (96.3) | 1 (1.2) | 80 (98.8) | |||
| ≥$75001 | 179 | 50 (27.9) | 129 (72.1) | <0.001 | 4 (2.2) | 175 (97.8) | 0.02 | 0 (0.0) | 179 (100.0) | 0.006 |
| Participant type (N=1014) | ||||||||||
| Adult patient | 783 | 316 (40.4) | 467 (59.6) | 48 (6.1) | 735 (93.9) | 14 (1.8) | 769 (98.2) | |||
| Adult caregiver of pediatric patient | 231 | 78 (33.8) | 153 (66.2) | 0.08 | 18 (7.8) | 213 (92.2) | 0.37 | 4 (1.7) | 227 (98.3) | 1.00 |
| Trust in clinician (N=978) | ||||||||||
| Complete (10) | 502 | 176 (35.1) | 326 (64.9) | 30 (6.0) | 472 (94.0) | 11 (2.2) | 491 (97.8) | |||
| High (8–9) | 287 | 119 (41.5) | 168 (58.5) | 13 (4.5) | 274 (95.5) | 1 (0.4) | 286 (99.6) | |||
| Medium-Low (1–7) | 189 | 90 (47.6) | 99 (52.4) | 0.007 | 20 (10.6) | 169 (89.4) | 0.03 | 6 (3.2) | 183 (96.8) | 0.03 |
| Any experience prior discrimination within health care (N=998) | ||||||||||
| Yes | 274 | 134 (48.9) | 140 (51.1) | 26 (9.5) | 248 (90.5) | 10 (1.4) | 714 (98.6) | |||
| No | 724 | 256 (35.4) | 468 (64.6) | <0.001 | 40 (5.5) | 684 (94.5) | 0.03 | 8 (2.9) | 266 (97.1) | 0.11 |
Boldface indicates statistical significance (p<0.05)
See Appendix Table S1 for participant characteristics stratified by responses to three individual verbal violence questions.
See Appendix Table S2 for characteristics of participants reporting any physical or verbal violence, stratified by scores ≥ or <11.
Rates of reporting any physical or verbal violence were more common in younger women and younger men, though differences were not statistically significant (Appendix Table S3).
Number of participants with complete responses for each variable.
Discussion
Applying the original HITS scoring criteria, 82% of participants reporting any frequency of physical violence did not screen positive for a safety concern. The original scoring system equally weights verbal and physical violence but has only one question on physical violence, which may contribute to the substantial under-detection of safety concerns.2 Given the potential for health care-based screening and intervention to facilitate safety planning,1,2 it is appropriate to revisit whether and to what extent a specific cutoff point should be used in the adapted HITS.
While we cannot verify participants’ experiences of abuse, these findings are concerning because patient disclosure of violence that does not lead to clinical follow-up is not only an immediate safety risk1,2 but also may amplify patient distrust in the health care system and decrease patient responsiveness to future screening. In our sample, participants who reported verbal or physical violence already had lower baseline trust in their clinicians and higher reported rates of health care-based discrimination than respondents who did not report any violence. For health care settings implementing the adapted HITS tool, we recommend caution in relying on screening scores to guide follow-up and/or intervention. At a minimum, we recommend following-up reports of physical violence or being threatened with harm, regardless of score. Stakeholder input and both reliability and validity testing are needed to increase the utility of screening and to minimize the potential for exacerbating distrust.
Limitations
This study has several limitations. Findings are based on participant self-report and therefore subject to response and social desirability bias. Due to study design and lack of a recognized gold standard tool for interpersonal violence screening, we were unable to assess the true sensitivity or specificity of the adapted HITS. The adapted tool was professionally translated into Spanish.10 We are not aware of any validity or reliability testing of a Spanish version, which may impact study results.
Conclusions
There are potential negative consequences associated with adapting an existing screening tool for new populations and contexts. Our findings highlight how the adapted HITS tool and recommended scoring criteria failed to identify many participants with significant safety risks. To improve patient safety and avoid missing intervention opportunities, stakeholder input and additional psychometric validity testing is needed. In the interim, our findings suggest the scoring rubric for a positive screen should be modified to include all patients reporting major safety concerns, including any physical and/or threats of violence.
Supplementary Material
Acknowledgements:
We thank study participants for their time and involvement. We thank the research staff and site principle investigators at each of our 11 study sites for their assistance with data collection. We thank José Parra, BS and Catherine Arevalo, BA of UCSF for their assistance with study launch and organization of study sites. We thank Remi Frazier, MA and Glenda Sharp, BA of the UCSF Academic Research Systems for their assistance with inputting the study survey into REDCap. E.H.D. had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. This work was supported by The Commonwealth Fund, a national, private foundation based in New York City that supports independent research on health care issues and makes grants to improve health care practice and policy. The views presented here are those of the author and not necessarily those of The Commonwealth Fund (CWF), its directors, officers, or staff. CWF had no role in study design and conduct of the study; collection, management, analysis, and interpretation of data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. E.H.D. was additionally supported by a fellowship training grant, National Research Service Award (NRSA) T32HP19025. NRSA had no role in study design and conduct of the study; collection, management, analysis, and interpretation of data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. A.J.C. was supported by an Advanced Health Services Research and Development (HSR&D) postdoctoral fellowship through the Office of Academic Affiliations, Department of Veterans Affairs (VA). S.T.L. was supported by NIH grants R01AG064949 and R01MD012630. The manuscript’s contents are solely the responsibility of the authors and do not represent the official views of the CWF, NRSA, VA or NIH. The study was approved by the University of California San Francisco IRB (17-23110); per their own institutional requirements, seven of the study sites also obtained site-specific IRB approvals (University of Arkansas 217767; Boston Medical Center H-37489; University of Chicago 18-0139; University of Colorado 17-2434; Dartmouth College STUDY00031049; Hennepin Health 18-4482; New York University i18-00004; Brigham and Women’s Hospital 2018P000990).
Conflicts of interest:
This work was supported by The Commonwealth Fund, a national, private foundation based in New York City that supports independent research on health care issues and makes grants to improve health care practice and policy. The views presented here are those of the author and not necessarily those of The Commonwealth Fund, its directors, officers, or staff. The Commonwealth Fund staff had no role in study design and conduct of the study; collection, management, analysis, and interpretation of data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. E.H.D. was additionally supported by a fellowship training grant, National Research Service Award (NRSA) T32HP19025. NRSA had no role in study design and conduct of the study; collection, management, analysis, and interpretation of data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. A.J.C. was supported by an Advanced Health Services Research and Development (HSR&D) postdoctoral fellowship through the Office of Academic Affiliations, Department of Veterans Affairs. S.T.L. was supported by NIH grants R01AG064949 and R01MD012630. The manuscript’s contents are solely the responsibility of the authors and do not represent the official views of the CWF, NRSA, VA or NIH. All conflict of interest disclosure information is accurate, complete, up-to-date and in the Acknowledgement section of the manuscript.
Financial disclosures:
E.H.D. has no financial disclosures
B.M. has no financial disclosures
E.W.F. was a consultant for Veta Health, a company that develops software for chronic disease management. The research published in this paper is not related to any of the above consulting work and was conducted prior Dr. Fleegler working with Veta Health.
A.J.C. has no financial disclosures
S.T.L. directed a Center for Medicare and Medicaid Innovation Health Care Innovation Award (1C1CMS330997-03) called CommunityRx. This award required development of a sustainable business model to support the model test after award funding ended. To this end, S. T. Lindau is founder and co-owner of NowPow, LLC. Neither the University of Chicago nor the University of Chicago Medicine is endorsing or promoting any NowPow entity or its business, products, or services.
A.G.H. has no financial disclosures
E.L.T. has no financial disclosures
D.H. has no financial disclosures
L.M.G. has no financial disclosures
Contributor Information
Emilia H. De Marchis, Department of Family & Community Medicine, University of California, San Francisco, San Francisco, CA.
Brigid McCaw, California ACES Learning and Quality Improvement Collaborative (CALQIC), University of California, San Francisco, San Francisco, CA.
Eric W. Fleegler, Division of Emergency Medicine, Boston Children’s Hospital; Assistant Professor of Pediatrics and Emergency Medicine, Harvard Medical School, Boston, MA.
Alicia J. Cohen, Providence VA Medical Center; Departments of Family Medicine and Health Services, Policy, and Practice, Brown University, Providence, RI.
Stacy Tessler Lindau, Departments of Ob/Gyn and Medicine-Geriatrics, University of Chicago, Chicago, IL.
Amy G. Huebschmann, Division of General Internal Medicine and Center for Women’s Health Research, University of Colorado School of Medicine, Aurora, CO.
Elizabeth L. Tung, Department of General Internal Medicine, University of Chicago, Chicago, IL.
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