Development of a New Computer Method to Assess Children's Pain

Fanciullo, Gilbert J.; Cravero, Joseph P.; Mudge, B; McHugo, Gregory J.; Baird, John C.

doi:10.1111/j.1526-4637.2007.00376.x

Cited by 21 publications

(14 citation statements)

References 10 publications

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“…25 Western-trained health clinicians are taught to determine first the location, intensity and quality of the pain using standard validated self-reporting tools and to observe body and behavioural cues. [26][27][28] The notion of overt pain behaviour, such as crying and facial grimace, promoted in Western culture may not be appropriate indicators of pain in Aboriginal children and youth. Reliance on self-reporting assumes that the reporter is comfortable or has a language to describe his or her pain similar to Western-held values.…”

Section: Cmaj Openmentioning

confidence: 99%

Expression of pain among Mi'kmaq children in one Atlantic Canadian community: a qualitative study

Latimer

Rudderham³

et al. 2014

CMAJ Open

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Section: Cmaj Openmentioning

confidence: 99%

Expression of pain among Mi'kmaq children in one Atlantic Canadian community: a qualitative study

Latimer

Rudderham³

et al. 2014

CMAJ Open

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“…Others have reached similar conclusions; for example, the children in this age group were able to use five figures to self-assess pain. 16,17 Results from the current study suggest that mothers who estimate their child's level of fullness in concordance with their child's perceived level of fullness pay attention to their child's fullness cue throughout the dinner meal. Mothers whose assessments of their child's level of fullness differed from their child tended to be willing to (1) shift their perceptions of their child's fullness level when given their child's self-report or (2) not shift their perceptions because of past experiences.…”

Section: Discussionmentioning

confidence: 89%

Correspondence between Maternal Determination of Child Fullness and Young Children's Self-Determined Fullness Level: Results from a Standardized Laboratory Protocol

Frankel¹,

Thompson

Power

et al. 2015

Childhood Obesity

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Background: This study examined maternal understanding and acceptance of young children's ability to self-assess fullness using a mixed-methods approach.Methods: Twenty low-income mothers of 5-to 7-year-olds participated in this semistructured laboratory study. After consumption of a buffet dinner meal, mothers were asked to indicate their perception of their child's fullness level, and children were also asked to self-assess their fullness level.Results: Five of the 20 mothers in the study were initially correct in their assessment of their child's level of fullness. Half of the incorrect mothers were willing to change their rating when informed that the child's fullness rating was different than her own.Conclusions: Semistructured interview results provide suggestive evidence that some mothers believe they understand their child's fullness level better than their children. Given that mothers have the potential to override children's ability to self-regulate eating behavior, teaching mothers to understand and appreciate young children's ability to self-regulate eating is an important area for intervention.

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“…Data obtained may include medical and psychiatric diagnoses and comorbidities, clinical presentation (signs and symptoms, brain imaging findings), illness severity, medications and dosages, side effects, abuse-relevant red flags (e.g., early opioid refills), other interventions (e.g., complementary and alternative medicine therapies), genetic variables, and validated pain, psychosocial, and functional outcome measures recorded in electronic databases. Several computerized systems for comprehensive patient self-reported outcomes are already in development or in use 39,94 , including computerized adaptive testing systems such as the NIH PROMIS measures (www.nihpromis.org). Within the PBE approach, electronic medical record data can be combined with computer-based patient-reported outcomes to rapidly identify those CP patient phenotypic and genotypic characteristics that may be associated with favorable treatment outcomes, although with less certainty than with RCTs 1,2,3,37,38 .…”

Section: Is Personalized Medicine a Solution?mentioning

confidence: 99%

Personalized Medicine and Opioid Analgesic Prescribing for Chronic Pain: Opportunities and Challenges

Bruehl

Apkarian

Ballantyne

et al. 2013

The Journal of Pain

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Use of opioid analgesics for pain management has increased dramatically over the past decade, with corresponding increases in negative sequelae including overdose and death. There is currently no well-validated objective means of accurately identifying patients likely to experience good analgesia with low side effects and abuse risk prior to initiating opioid therapy. This paper discusses the concept of data-based personalized prescribing of opioid analgesics as a means to achieve this goal. Strengths, weaknesses, and potential synergism of traditional randomized placebo-controlled trial (RCT) and practice-based evidence (PBE) methodologies as means to acquire the clinical data necessary to develop validated personalized analgesic prescribing algorithms are overviewed. Several predictive factors that might be incorporated into such algorithms are briefly discussed, including genetic factors, differences in brain structure and function, differences in neurotransmitter pathways, and patient phenotypic variables such as negative affect, sex, and pain sensitivity. Currently available research is insufficient to inform development of quantitative analgesic prescribing algorithms. However, responder subtype analyses made practical by the large numbers of chronic pain patients in proposed collaborative PBE pain registries, in conjunction with follow-up validation RCTs, may eventually permit development of clinically useful analgesic prescribing algorithms. Perspective Current research is insufficient to base opioid analgesic prescribing on patient characteristics. Collaborative PBE studies in large, diverse pain patient samples in conjunction with follow-up RCTs may permit development of quantitative analgesic prescribing algorithms which could optimize opioid analgesic effectiveness, and mitigate risks of opioid-related abuse and mortality.

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Development of a New Computer Method to Assess Children's Pain

Cited by 21 publications

References 10 publications

Expression of pain among Mi'kmaq children in one Atlantic Canadian community: a qualitative study

Expression of pain among Mi'kmaq children in one Atlantic Canadian community: a qualitative study

Correspondence between Maternal Determination of Child Fullness and Young Children's Self-Determined Fullness Level: Results from a Standardized Laboratory Protocol

Personalized Medicine and Opioid Analgesic Prescribing for Chronic Pain: Opportunities and Challenges

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