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Items: 1 to 20 of 86

1.

The influence of sex, race, and age on pain assessment and treatment decisions using virtual human technology: a cross-national comparison.

Torres CA, Bartley EJ, Wandner LD, Alqudah AF, Hirsh AT, Robinson ME.

J Pain Res. 2013 Jul 22;6:577-88. doi: 10.2147/JPR.S46295. Print 2013.

2.

The impact of patients' gender, race, and age on health care professionals' pain management decisions: an online survey using virtual human technology.

Wandner LD, Heft MW, Lok BC, Hirsh AT, George SZ, Horgas AL, Atchison JW, Torres CA, Robinson ME.

Int J Nurs Stud. 2014 May;51(5):726-33. doi: 10.1016/j.ijnurstu.2013.09.011. Epub 2013 Sep 29.

3.

Virtual human technology: patient demographics and healthcare training factors in pain observation and treatment recommendations.

Wandner LD, Stutts LA, Alqudah AF, Craggs JG, Scipio CD, Hirsh AT, Robinson ME.

J Pain Res. 2010 Dec 7;3:241-7. doi: 10.2147/JPR.S14708.

4.

Investigating patient characteristics on pain assessment using virtual human technology.

Stutts LA, Hirsh AT, George SZ, Robinson ME.

Eur J Pain. 2010 Nov;14(10):1040-5. doi: 10.1016/j.ejpain.2010.04.003.

5.

Using virtual human technology to capture dentists' decision policies about pain.

Wandner LD, Hirsh AT, Torres CA, Lok BC, Scipio CD, Heft MW, Robinson ME.

J Dent Res. 2013 Apr;92(4):301-5. doi: 10.1177/0022034513480802. Epub 2013 Feb 27.

6.

Assessment of the Influence of Demographic and Professional Characteristics on Health Care Providers' Pain Management Decisions Using Virtual Humans.

Boissoneault J, Mundt JM, Bartley EJ, Wandner LD, Hirsh AT, Robinson ME.

J Dent Educ. 2016 May;80(5):578-87.

7.

The influence of health care professional characteristics on pain management decisions.

Bartley EJ, Boissoneault J, Vargovich AM, Wandner LD, Hirsh AT, Lok BC, Heft MW, Robinson ME.

Pain Med. 2015 Jan;16(1):99-111. doi: 10.1111/pme.12591. Epub 2014 Oct 23.

8.

Pain assessment and treatment decisions for virtual human patients.

Wandner LD, George SZ, Lok BC, Torres CA, Chuah JH, Robinson ME.

Cyberpsychol Behav Soc Netw. 2013 Dec;16(12):904-9. doi: 10.1089/cyber.2012.0707. Epub 2013 Aug 24.

9.

Virtual human technology: capturing sex, race, and age influences in individual pain decision policies.

Hirsh AT, Alqudah AF, Stutts LA, Robinson ME.

Pain. 2008 Nov 15;140(1):231-8. doi: 10.1016/j.pain.2008.09.010. Epub 2008 Oct 18.

10.

Using virtual human technology to provide immediate feedback about participants' use of demographic cues and knowledge of their cue use.

Wandner LD, Letzen JE, Torres CA, Lok B, Robinson ME.

J Pain. 2014 Nov;15(11):1141-7. doi: 10.1016/j.jpain.2014.08.001. Epub 2014 Aug 12.

11.

Evaluation of nurses' self-insight into their pain assessment and treatment decisions.

Hirsh AT, Jensen MP, Robinson ME.

J Pain. 2010 May;11(5):454-61. doi: 10.1016/j.jpain.2009.09.004. Epub 2009 Dec 16.

12.

Effect of a perspective-taking intervention on the consideration of pain assessment and treatment decisions.

Wandner LD, Torres CA, Bartley EJ, George SZ, Robinson ME.

J Pain Res. 2015 Nov 11;8:809-18. doi: 10.2147/JPR.S88033. eCollection 2015.

13.

Patient demographic characteristics and facial expressions influence nurses' assessment of mood in the context of pain: a virtual human and lens model investigation.

Hirsh AT, Callander SB, Robinson ME.

Int J Nurs Stud. 2011 Nov;48(11):1330-8. doi: 10.1016/j.ijnurstu.2011.05.002. Epub 2011 May 19.

14.

Pain assessment and treatment disparities: a virtual human technology investigation.

Hirsh AT, George SZ, Robinson ME.

Pain. 2009 May;143(1-2):106-13. doi: 10.1016/j.pain.2009.02.005. Epub 2009 Mar 9.

15.

Impact of race and sex on pain management by medical trainees: a mixed methods pilot study of decision making and awareness of influence.

Hollingshead NA, Matthias MS, Bair MJ, Hirsh AT.

Pain Med. 2015 Feb;16(2):280-90. doi: 10.1111/pme.12506. Epub 2014 Jul 8.

16.

The influence of patient's sex, race and depression on clinician pain treatment decisions.

Hirsh AT, Hollingshead NA, Bair MJ, Matthias MS, Wu J, Kroenke K.

Eur J Pain. 2013 Nov;17(10):1569-79. doi: 10.1002/j.1532-2149.2013.00355.x. Epub 2013 Jun 30.

PMID:
23813861
17.

Low back pain in the United States: incidence and risk factors for presentation in the emergency setting.

Waterman BR, Belmont PJ Jr, Schoenfeld AJ.

Spine J. 2012 Jan;12(1):63-70. doi: 10.1016/j.spinee.2011.09.002. Epub 2011 Oct 5.

PMID:
21978519
18.

SEX AND RACE DIFFERENCES IN RATING OTHERS' PAIN, PAIN-RELATED NEGATIVE MOOD, PAIN COPING, AND RECOMMENDING MEDICAL HELP.

Alqudah AF, Hirsh AT, Stutts LA, Scipio CD, Robinson ME.

J Cyber Ther Rehabil. 2010;3(1):63-70.

19.

Dispositional optimism among American and Jordanian college students: are Westerners really more upbeat than Easterners?

Khallad Y.

Int J Psychol. 2010 Feb;45(1):56-63. doi: 10.1080/00207590902767020.

PMID:
22043849
20.

Medical student characteristics predictive of intent for rural practice.

Royston PJ, Mathieson K, Leafman J, Ojan-Sheehan O.

Rural Remote Health. 2012;12:2107. Epub 2012 Aug 9.

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