Perceived social risk in medical decision-making for physical child abuse: a mixed-methods study
Tóm tắt
The medical literature reports differential decision-making for children with suspected physical abuse based on race and socioeconomic status. Differential evaluation may be related to differences of risk indicators in these populations or differences in physicians’ perceptions of abuse risk. Our objective was to understand the contribution of the child’s social ecology to child abuse pediatricians’ perception of abuse risk and to test whether risk perception influences diagnostic decision-making. Thirty-two child abuse pediatrician participants prospectively contributed 746 consultations from for children referred for physical abuse evaluation (2009–2013). Participants entered consultations to a web-based interface. Participants noted their perception of child race, family SES, abuse diagnosis. Participants rated their perception of social risk for abuse and diagnostic certainty on a 1–100 scale. Consultations (n = 730) meeting inclusion criteria were qualitatively analyzed for social risk indicators, social and non-social cues. Using a linear mixed-effects model, we examined the associations of social risk indicators with participant social risk perception. We reversed social risk indicators in 102 cases whilst leaving all injury mechanism and medical information unchanged. Participants reviewed these reversed cases and recorded their social risk perception, diagnosis and diagnostic certainty. After adjustment for physician characteristics and social risk indicators, social risk perception was highest in the poorest non-minority families (24.9 points, 95%CI: 19.2, 30.6) and minority families (17.9 points, 95%CI, 12.8, 23.0). Diagnostic certainty and perceived social risk were associated: certainty increased as social risk perception increased (Spearman correlation 0.21, p < 0.001) in probable abuse cases; certainty decreased as risk perception increased (Spearman correlation (−)0.19, p = 0.003) in probable not abuse cases. Diagnostic decisions changed in 40% of cases when social risk indicators were reversed. CAP risk perception that poverty is associated with higher abuse risk may explain documented race and class disparities in the medical evaluation and diagnosis of suspected child physical abuse. Social risk perception may act by influencing CAP certainty in their diagnosis.
Tài liệu tham khảo
Laskey AL, Stump TE, Perkins SM, Zimet GD, Sherman SJ, Downs SM. Influence of race and socioeconomic status on the diagnosis of child abuse: a randomized study. J Pediatr. 2012;160:1003–8.
Lane WG, Rubin DM, Monteith R, Christian CW. Racial differences in the evaluation of pediatric fractures for physical abuse. JAMA. 2002;288:1603–9.
Jenny C, Hymel KP, Ritzen A, Reinert SE, Hay TC. Analysis of missed cases of abusive head trauma. JAMA. 1999;281:621–6.
Henry MK, Wood JN, Metzger KB, Kim KH, Feudtner C, Zonfrillo MR. Relationship between insurance type and discharge disposition from the emergency department of young children diagnosed with physical abuse. J Pediatr. 2016;177:302–6.
Asnes AG, Leventhal JM. Managing child abuse: general principles. Pediatr Rev. 2010;31:47–55.
Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15:1277–88.
Kotch JB, Browne DC, Ringwalt CL, Stewart PW, Ruina E, Holt K, Lowman B, Jung JW. Risk of child abuse or neglect in a cohort of low-income children. Child Abuse Negl. 1995;19:1115–30.
Sidebotham P, Heron J. Child maltreatment in the “children of the nineties”: a cohort study of risk factors. Child Abuse Negl. 2006;30:497–522.
Spencer N, Devereux E, Wallace A, Sundrum R, Shenoy M, Bacchus C, Logan S. Disabling conditions and registration for child abuse and neglect: a population-based study. Pediatrics. 2005;116:609–13.
Schilling J. On the pragmatics of qualitative assessment: designing the process for content analysis. Eur J Psychol Assess. 2006;22:28–37.
Richards L. Handling qualitatiave data: a practical guide. 3rd ed. London: Sage Publications; 2008.
Page KR, Castillo-Page L, Poll-Hunter N, Garrison G, Wright SM. Assessing the evolving definition of underrepresented minority and its application in academic medicine. Acad Med. 2013;88:67–72.
Wong P, Lai C, Nagasawa R, Lin T. Asian Americans as a model minority: self-perceptions and perceptions by other racial groups. Sociol Perspect. 1998;41:95–118.
Moore L, Hanley JA, Lavoie A, Turgeon A. Evaluating the validity of multiple imputation for missing physiological data in the national trauma data bank. J Emerg Trauma Shock. 2009;2:73–9.
Hansen KK, Keeshin BR, Flaherty E, Newton A, Passmore S, Prince J, Campbell KA. Sensitivity of the limited view follow-up skeletal survey. Pediatrics. 2014;134:242–8.
Harper NS, Eddleman S, Lindberg DM, Investigators E. The utility of follow-up skeletal surveys in child abuse. Pediatrics. 2013;131:e672–8.
Croskerry P, Norman G. Overconfidence in clinical decision making. Am J Med. 2008;121(Suppl 5):24–9.
Cavalcanti RB, Sibbald M. Am I right when I am sure? Data consistency influences the relationship between diagnostic accuracy and certainty. Acad Med. 2014;89:107–13.
State Health Facts/Poverty Rate by Race/Ethnicity. The Henry J. Kaiser Family Foundation. 2016. http://kff.org/other/state-indicator/poverty-rate-by-raceethnicity/. Accessed 5 Jan 2015.
Thammasitboon S, Cutrer WB. Diagnostic decision-making and strategies to improve diagnosis. Curr Probl Pediatr Adolesc Health Care. 2013;43:232–41.
Rangel EL, Cook BS, Bennett BL, Shebesta K, Ying J, Falcone RA. Eliminating disparity in evaluation for abuse in infants with head injury: use of a screening guideline. J Pediatr Surg. 2009;44:1229–34.
Sabin J, Nosek BA, Greenwald A, Rivara FP. Physicians’ implicit and explicit attitudes about race by MD race, ethnicity, and gender. J Health Care Poor Underserved. 2009;20:896–913.