1.疼痛描述工具被使用描述病徵、區辨不同的診斷(distinguishing between diagnoses),預測治療成效及反應以及偵測治療反應(predicting treatment outcome and other symptoms, and detecting treatment effects)
Ref: in Introduction_The journal of pain,7(11),2006: 823-32
2.疼痛描述工具在疼痛機制的研究上佔有重要地位
Ref:(待)
區別不同的診斷
比較罹患多發性硬化者症及脊髓損傷者,其描述疼痛形容詞不同。此外,脊髓損傷者描述損傷部位以下及以上的形容詞也不相同。
European Journal of Pain 15, 2011:628-33
預測治療成效
治療前的疼痛分數(Pre-treatment NPS-10)與治療成果(fatique量表成績)具有相關性
Fishbain DA, Lewis J, Cole B, Cutler RB, Smets E, Rosomoff HL, Rosomoff RS: Multidisciplinary pain facility treatment outcome for pain-associated fatigue. Pain Med 6:299-304, 2005(引用22)
2011年11月20日 星期日
2011年11月18日 星期五
Pain Quality Assessment Score
The brevity of the NPS makes it useful in clinical and research settings in which assessment burden is a significant issue. However, a number of pain qualities that are common to persons with neuropathic and non-neuropathic pain are not assessed by the NPS. These include “electric,” “tingling” (or “pins and needles”), “radiating,” and “numb” qualities.2,4,5,6,24,36 The work of Bouhassira et al,4,5 in particular, has emphasized the importance of paresthesia as a critical component of neuropathic pain, and that patients can provide reliable and valid ratings of this component of neuropathic pain. Adding items that assess each of these qualities to the NPS should increase its content validity for assessing neuropathic pain. In addition, the utility of the measure could be improved further if it included pain qualities common to other pain conditions,6,36 such as a number of the pain quality domains included in more generic (ie, non–diagnosis-specific) measures (eg, the MPQ-SF).27
These include such qualities as “tender,” “shooting,” “cramping,” “throbbing,” “aching,” and “heavy.” We therefore added 10 descriptors to the NPS to increase its content validity for assessing neuropathic pain
and to make it useful for assessing non-neuropathic pain as well. The specific items added assessed tender, numb, electrical, tingling, radiating, throbbing, aching, shooting, cramping, and heavy pain qualities. Also, to improve the temporal item of the NPS, we provided more clear descriptions of the 3 temporal classifications of pain that this item was designed to assess. Because the resulting questionnaire could be used to assess both neuropathic and non-neuropathic pain, we removed the word neuropathic from the scale name and called the resulting 20-item measure the Pain Quality Assessment Scale (PQAS)
Neuropathic Pain Symptom Inventory
Each of these items was quantified on a (0–10) numerical scale.
Average spontaneous pain severity during the past 24 h.
12 items
a list of descriptors reflecting spontaneous ongoing or paroxysmal pain, evoked pain (i.e. mechanical and thermal allodynia/hyperalgesia) and dysesthesia/paresthesia.
Neuropathic Pain Scale
Includes two items that assess (1) the global dimensions of pain intensity and pain unpleasurement and (2)eight items of specific neuropathic pain qualities (“sharp,” “hot,” “dull,” “cold,” “sensitive,” “itchy,” “deep,” and “surface” pain)
Each of the items includes a description and other similar descriptive words for that item. Each of the items has a 0 to 10 numerical score, in which 1 is “no” or “not” and 10 is “the most”
In additions, the scale also want to patients describe the time quality of pain (the background pain, break-through pain and occasional pain)
Multidimensional Affect and Pain Survey
In the MAPS questionnaire the descriptors are placed in sentences to clarify their meaning. The patient rates these statements on a response scale from not at all (0) to very much so (5).
Supercluster I, somatosensory pain qualities
17 subclusters
57 descriptors of painful sensory qualities
Supercluster II, emotional pain
Eight subclusters
26 descriptors of negative emotional qualities
Supercluster III, well-being
Fve subclusters
18 descriptors of positive affect and health
History:
The 101 items of MAPS were selected from earlier sets of 270 (Clark et al., 1995) and 189 (Yang et al., 2000) descriptors of pain and emotion. The similarities of the 189 descriptors were evaluated by 104 female and male college students of Puerto Rican, European–American and African–American descent. Each volunteer first sorted descriptors that she/he considered to be similar into piles. Following this pile-
sort procedure the volunteers merged their individual piles two at a time on the basis of similarity. This sequentialmerge procedure continued until only two piles remained.
The data were evaluated by an agglomerative, hierarchical clustering technique, the Average-Linkage-Between-Groups algorithm (Sokal and Michener, 1958) to yield hierarchically organized clusters of descriptors that were similar in meaning, a dendrogram. Details of the development and validation of MAPS are presented elsewhere (Yang et al.,2000).The final set of 101 words used in MAPS included those
words that remained after eliminating 88 (of the 189) descriptors that failed to have a common meaning among the six sex-ethnocultural groups. This left a composite dendrogram of 101 words that was relatively free of gender and ethnocultural bias. The structure of the dendrogram
determined which descriptors fell within each cluster for MAPS as well as the location of the 30 subclusters within the three MAPS superclusters.
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