Pain is a common problem among older adults, with persistent physical pain being most widespread. It is estimated that 25% to 50% of community-dwelling older adults experience significant pain problems (American Geriatrics Society Panel on Chronic Pain in Older Persons [AGS], 2002), and pain in nursing home residents has been documented in many studies at local and national levels, ranging from a low of 20% to a high of 83% (Boerlage, van Dijk, Stronks, de Wit, & van der Rijt, 2008; A.L. Jones, Dwyer, Bercovitz, & Strahan, 2009, Rolland et al., 2009; Smalbrugge, Jongenelis, Pot, Beekman, & Eefsting, 2007; Torvik, Kaasa, Kirkevold, & Rustøen, 2009; van Herk et al., 2009). Takai, Yamamoto-Mitani, Okamato, Koyama, and Honda (2010) summarized the pain prevalence in nursing home residents in their review of 27 published reports from 1990 to 2009 to range from 3.9% to 79.5%, suggesting that this variation is likely due to the methods and data sources used for pain assessment and the time frame of pain detection. Older adults as a group in general have a high prevalence of comorbid conditions, and one of the consequences of which is an increased risk of pain (Helme & Gibson, 1999). Since nursing home residents in general have high comorbidity, making them vulnerable to experiencing pain, the rates of acute and chronic pain in this population tend to be higher than in community-dwelling older adults (Hicks, 2000). Jakobsson (2004) found that older adults living in institutions reported significantly more pain and were more dependent compared with those living at home.
In addition to the high prevalence rates of pain in nursing home residents, pain in this population tends to be persistent over time or chronic in nature. Persistent pain in nursing home residents has been reported to range from 40% with excruciating daily pain (Teno, Kabumoto, Wetle, Roy, & Mor, 2004) to 49% with recurring pain in the national nursing home data in the United States (Won et al., 2004). On the other hand, Zanocchi et al. (2008) reported that 83% of their sample had chronic pain, defined as pain lasting longer than 3 months. Takai et al. (2010) found that reports of the prevalence of persistent/daily pain ranged from 17% to 70% in nursing home residents. Lapane, Quilliam, Chow, and Kim (2012) reported 25% of their sample of 9,952 nursing home residents to have pain, documented on two consecutive days. High rates of persistent or chronic pain in this population suggest that pain in nursing home residents is not adequately addressed, resulting in unnecessary suffering. This can lead to depression, sleep disturbance, social isolation, helplessness, decreased mobility and functionality, and impaired appetite (AGS, 2002; Weiner & Rudy, 2002).
Pain management is the major nursing responsibility in nursing homes. However, the literature suggests that pain management in nursing homes remains less optimal with the evidence of nursing home residents’ reports of pain. Although there is evidence for a high rate of persistent pain in nursing homes, as suggested by Takai et al. (2010), the rates seem to depend on the way pain is measured. Most of the studies used recall measures or ratings by professionals, rather than actual pain experiences rated by residents and over time. Thus, the aims of this study were to describe the patterns of pain and persistent pain in nursing home residents regarding:
- Prevalence, intensity, and location of pain experiences reported by residents on 5 different days and persistent pain on 5 days over a 14-day period.
- Relationships of pain and persistent pain with personal and clinical factors, such as comorbidity, sleep disturbances, and functioning.
This study used an approach to measure pain experiences as rated by nursing home residents directly to overcome the disadvantages of recalled and/or indirect measurements. Persistent pain usually refers to pain that is present daily or frequently over a period of time. In our study, persistent pain was viewed as pain that exists on 5 different days, measured 1 or 2 days apart, within a period of 2 weeks (14 days). A more rigorous view of persistent pain has been applied in this study by both using the residents’ self-ratings of pain and measuring pain on 5 days within a short duration to overcome the shortcomings in the literature.
The sites for this study were nursing homes in the region of Buskerud, Norway, which is one of the nearby counties of Oslo. A total of six nursing homes were used to draw the sample for this study. The nursing homes were located in the urban areas of the county surrounding the city of Drammen and were typical of municipally-administered nursing homes in Norway with bed capacities ranging from 30 to 100 with both short- and long-stay units. Typically, residents at short-stay units are older adults recovering from acute episodes of illness, such as surgery, stroke, heart attack, pneumonia, whereas residents at long-stay units are those with debilitating chronic illnesses including dementia, requiring dependent, long-term care.
The inclusion criteria for participation in the study were ability to communicate verbally and understand information and to give consent to participate in the study. It is possible that some participants could have had mild to moderate cognitive impairment, as we did not measure the cognitive level specifically. However, we applied the inclusion criteria rigorously in our sample selection to ensure participants would be able to rate their pain appropriately. It has also been shown that even nursing home residents with some cognitive impairment are able to use verbal rating scales correctly if they are able to communicate verbally (Closs, Barr, Briggs, Cash, & Seers, 2004).
The researchers, in consultation with the nursing staff, determined the eligibility of residents for participation in the study. A sample of 200 was considered adequate for this study, based on a power analysis with a power of 0.8, an effect size of 0.15, and an alpha of 0.05 for possible application of analysis of variance (ANOVA) and multiple regression analysis for pain intensity as the dependent variable. All residents of the six nursing homes for 2006 and the first 6 months of 2007 were considered potential study participants. Of the total sample base of 483 nursing home residents during the study period, 223 residents met the inclusion criteria. Of these, 207 consented to participate in the study. A total of 201 residents completed all five pain interviews and provided the data for analyses.
This study obtained four types of information: (a) personal demographic information, (b) medical information, (c) functioning and sleeping, and (d) pain. The personal demographic data on age, sex, educational level, marital status, and employment history were obtained at initial data collection. The medical information included medical diagnoses and current medication use, including analgesic agent orders, obtained from the participants’ medical records at initial data collection. Functioning was measured by the Barthel Index (Mahoney & Barthel, 1965), which has been used routinely in nursing homes and studies of older adults to assess level of dependency in functioning. The Norwegian version translated by Laake et al. (1995) was used. It contains 10 items and ratings of 0 to 1, 0 to 2, or 0 to 3, resulting in a total score ranging from 0 to 20. Lower scores indicate greater degrees of dependency. The total scores, obtained at initial data collection, were used in this study. Measurement of sleeping problems was based on a 5-item questionnaire that included questions regarding (a) difficulty falling asleep, (b) being wakeful at night, (c) having difficulty sleeping during night and staying awake during the daytime, (d) constant need for sleep, and (e) disturbed sleep due to frequent need to void. Response choices were not at all, very little, quite much, and often, as experienced during the past 14 days. These questions were originally developed by Lerdal, Celius, Krupp, and Dahl (2007), derived from the International Classification of Diseases, 10th revision, diagnosis of F51.0 non-organic insomnia and used to construct an Insomnia Index. The Insomnia Index is based on the first three questions and has internal consistency Cronbach’s alpha coefficients of 0.82 (Lerdal et al., 2007) and 0.84 (Lerdal et al., 2010). Scale scores range from 1 to 4. Higher scores indicate greater degrees of sleeping problems. The data on sleeping problems were obtained once at initial data collection.
Pain was measured by applying three sections of the Norwegian version of the McGill Pain Questionnaire, translated by Strand and Wisnes (1990): (a) location of pain on body diagrams of front and back; (b) present pain intensity (PPI) in six levels, 1 (no), 2 (slight), 3 (moderate), 4 (strong), 5 (intense), and 6 (unbearable); and (c) use of as-needed pain medication on the day of measurement. This instrument was used to assess pain on 5 different days within a 14-day period, with the assumption that pain measured every other day would give a general indication of fluctuation in pain levels.
Approvals were obtained for the study from the Norwegian Regional Ethical Committee and the Norwegian Social Science Data Services. Residents who were determined eligible for the study were approached regarding participation, and written informed consents were obtained prior to collecting the first set of data. A total of five interviews were conducted with each participant. The first interview used the assembled questionnaire that contained the study items in a structured format for the four sections (i.e., demographic information, personal data, Barthel Index, Insomnia Index), followed by filling in the medical information (i.e., medical diagnoses, medications, analgesic agent orders) from the participants’ medical records. The first pain measure was also obtained at this time. The pain measures were obtained through interviews. Participants were asked to rate their pain at present on six scales (both shown and read to them) and to mark the location of pain on the body diagram. Four follow-up pain data were collected using the same procedure during a period of 14 days. In general, these follow-up pain measurements were obtained 1 to 2 days apart excluding weekend days. Pain measurements were obtained between 9:00 a.m. and 7:00 p.m. (after morning care and breakfast, and before bedtime). The data were collected in 2006 and the first 6 months of 2007. None of the residents was engaged in any physical activity at the time of pain assessment.
All analyses were performed using the statistical software PASW for Windows® version 17.0. Descriptive statistics including Pearson correlation were used to examine the first research aim, and t test, Pearson’s chi-square test, and one-way ANOVA were applied to examine the second research aim.
There were 201 participants from the six nursing homes. In the sample, 37% were men, and 63% were women, which is similar to the makeup of the general nursing home population. The mean age of the group was 84 (SD = 7.5 years), with approximately 41% in the category of older than 85. Thirty-four percent of the sample was still married, and 59% had an educational level of 7 to 10 years, with an additional 32% completing middle school or high school. The mean functioning score on the Barthel Index was 12.97 (SD = 4.925), indicating a moderate level of dependency, and the mean Insomnia Index score was 1.75 (SD = 0.641), suggesting a mild to moderate level of sleeping problems. The internal consistency of the Insomnia Index in this sample was Cronbach’s alpha coefficient = 0.70, suggesting an adequate level of reliability.
The average number of medical diagnoses of the participants was 3.4 (SD = 1.745), and the participants were taking an average of 4.6 different medications (SD = 2.116). Seventy-six percent of the sample were on the short-stay units, and 24% were on the long-stay units. There was no significant difference between the participants on the long-stay units and those on the short-stay units in all baseline data except the Barthel Index. The mean Barthel Index score for the long-stay unit participants was significantly lower (11.4, SD = 5.257) than those in the short-stay units (13.4, SD = 4.724), indicating a greater degree of dependence in the participants on the long-stay units.
Prevalence, Intensity, and Location of Pain and Persistent Pain
The pain ratings at five measurement points within a 14-day period are shown in Figure 1. In this study, we collapsed the categories of intense and unbearable into one category, intense (rating of 5) because only 7 residents rated their pain as unbearable in the five ratings. Approximately one third (26.9% to 35.8%) of the sample rated having no pain at each point, whereas 15% to 28% rated having strong or intense pain. The Pearson correlations among the pain ratings across five measurements were significantly high, ranging from 0.53 to 0.64 (p < 0.01), and the mean pain levels of those reporting pain were 3.197 (SD = 0.998) at Rating 1, 3.078 (SD = 0.903) at Rating 2, 3.022 (SD = 0.906) at Rating 3, 3.054 (SD = 0.823) at Rating 4, and 3.00 (SD = 0.835) at Rating 5.
Figure 1. Distribution of pain levels at five pain ratings (N = 201).
Body areas were specified into 17 different areas for analysis. The Pearson correlations between the number of body areas with pain (scale of 0 to 17) and the pain ratings ranged from 0.37 to 0.47 and were statistically significant at p < 0.01. The findings indicate the greater the pain, the more body areas with pain. The residents with slight pain felt pain in 3.7 to 5.1 areas on average, while residents with intense pain felt pain in 5.2 to 7.3 body areas on average, with significant differences according to the pain levels at all five measurements. For further analyses, the 17 body areas were regrouped into five broad regions: head/neck including shoulder (HN), chest/abdomen (Front), lower extremities (LE), upper extremities (UE), and back including lower spine and buttocks (Back). Table 1 shows the distribution of those having slight to intense pain in the combination of different body areas categorized into five broad regions of the body. Participants with pain in only one region of the body had pain either in the Back or LE, whereas all others had pain in various combinations of body regions. Only 6% to 12.4% of the residents had pain in the regions of HN, Front, and UE. Pain only in LE was reported by 11.9% to 15.9% of the participants, pain only in the Back by 5.5% to 9%, and pain in combination of both the Back and LE by 10.9% to 14.4%. Thus, nearly one third of the participants (30% to 36%) had pain in the Back and/or LE (i.e., had pain in LE only, Back only, or Back and LE), suggesting a possible impact of pain in these body areas on mobility.
Table 1: Participants with Slight to Intense Pain in Various Body Areas at Five Pain Ratings (N = 201)
The five pain ratings were examined for their persistence and fluctuation, and were clustered into four different patterns. The first pattern (No or Low Pain) is for those with no or slight pain (rating of 1 or 2) on at least 3 days and no more than one rating higher than 2; the second pattern (Persistent Moderate Pain) is for those with moderate pain (rating of 3) on at least 3 days, with no more than one rating of 2 or 4; the third pattern (Persistent Intense Pain) is for those with strong or intense pain (rating of 4 or 5) on at least 3 days, with no more than one rating of 3; and the fourth pattern (Fluctuating Pain) is for those with three or more different pain ratings over the five ratings. The distribution into these patterns was: No or Low Pain, 77 (38.3%); Moderate Persistent Pain, 73 (36.3%); Intense Persistent Pain, 22 (10.9%); and Fluctuating Pain, 29 (14.4%). Therefore, nearly half of the participants (47.2%) had moderate to intense persistent pain.
Relationships of Pain and Persistent Pain with Personal and Clinical Factors
We examined the relationships of the pain ratings with age, type of unit, Barthel Index score, Insomnia Index score, number of medical diagnoses, and number of medications. No difference was found in the pain ratings according to type of unit in which the participants resided or Barthel Index score. Pain ratings, in general, were significantly associated with age, Insomnia Index score, number of medical diagnoses, and number of medications. These correlations suggest that the younger the resident, the higher the pain ratings (r = −0.086 to −0.208), and the greater the sleeping problems, the higher the pain ratings (r = 0.177 to 0.257). In addition, those with more medical diagnoses (r = 0.190 to 0.240) and those taking a greater number of medications (r = 0.158 to 0.235) were more likely to have more intense pain. However, these correlations (although most were statistically significant at p < 0.05) were not high, suggesting low degrees of explanation for differences in the pain level by these variables independently.
Five regression models were analyzed for each of the five pain ratings, with age, Insomnia Index score, number of medical diagnoses, and number of medications as predictor variables. Although the overall F for each model was statistically significant, the R2 values were small, suggesting low levels of predictability of pain level by these variables (R2 = 0.123 for Rating 1, 0.113 for Rating 2, 0.064 for Rating 3, 0.093 for Rating 4, and 0.076 for Rating 5).
The mean differences in the pain pattern groups according to age, Insomnia Index score, Barthel Index score, number of medical diagnoses, and number of medications were examined using ANOVA. Insomnia Index score, number of medical diagnoses, and number of medications were significantly different among the four pain pattern groups, as shown in Table 2. The No or Low Pain group had the highest mean age (older), whereas the Persistent Intense Pain group had the lowest mean age (younger). On the other hand, the Fluctuating Pain group had the highest mean insomnia score (higher degree of sleeping problems), and the No or Low Pain group had the lowest insomnia score (lower degree of sleeping problems). The Persistent Intense Pain group had the highest mean number of medical diagnoses and the highest mean number of medications, whereas the No or Low Pain group had the lowest mean scores on these variables.
Table 2: Selected Personal and Clinical Variables by Pain Pattern Group
Bonferroni post hoc tests, given the nonsignificant Levene statistics for the test of homogeneity of variance for age (p = 0.869), the Insomnia Index score (p = 0.160), number of medical diagnoses (p = 0.653), and number of medications (p = 0.388) were performed to examine group differences in the pain pattern groups by these variables. The No or Low Pain group and the Persistent Intense Pain group were significantly different in mean number of diagnoses and mean age. The Persistent Intense Pain group had a greater number of medical diagnoses than the No or Low Pain group (mean difference = −1.364, standard error [SE ] = 0.410, p = 0.006), whereas the Persistent Intense Pain group was younger than the No or Low Pain group (mean difference = 5.019, SE = 1.801, p = 0.035). The No or Low Pain group and the Fluctuating Pain group were significantly different in the mean number of medical diagnoses. The Fluctuating Pain group had a greater number of medical diagnoses than the No or Low Pain group (mean difference = −1.000, SE = 0.360, p = 0.044). There was no significant difference between the Persistent Moderate Pain and Persistent Intense Pain groups on these personal characteristics.
We examined the distribution in the pain pattern groups according to the presence of various chronic diseases. There were significant differences in the distribution among the pain pattern groups according to whether or not the participants had the diagnosis of stroke, rheumatoid arthritis, osteoporosis, chronic pain, or cancer, although in different ways, as shown in Figure 2. More than 80% of the participants with cancer, chronic pain, or osteoporosis were in the Persistent Moderate, Persistent Intense, or Fluctuating Pain patterns, while nearly one half of those patients without these diseases were in the No or Low Pain group. On the other hand, those with rheumatoid arthritis were most likely to have moderate or intense persistent pain, compared with the patient groups with other chronic diseases. In contrast, the participants with stroke were most likely not to have persistent pain, with 55% of the patients with stroke in the No or Low Pain group. This is striking, as 38% of the total sample were in the No or Low Pain group.
Figure 2. Distribution in the four pain pattern groups according to selected medical diagnoses.
Our findings regarding the extent and degree of pain felt by nursing home residents, at approximately 50% with moderate to intense pain on 5 days, are similar to those found in several studies. For example, another Norwegian study of nursing home residents reported 51% with “pain now” (Torvik et al., 2009); a study of Dutch nursing home residents on somatic and rehabilitation wards reported 54% to 58% with perceived pain (Achterberg, Pot, Scherder, & Ribbe, 2007); and a study of a national subsample of nursing home residents in the United States found 49% of the sample with pain (Won et al., 2004). Fox, Raina, and Jadad (1999) reported in their review of studies that the rate of pain among nursing home residents ranged from 49% to 83%. The prevailing evidence across countries is that at least one half of nursing home residents have pain and this rate has not changed during the past decade. The results of our study from the residents’ self-ratings of pain give an important affirmation of pain from the resident’s perspective. Our findings regarding the intensity of pain at the moderate level (3 on a scale of 1 to 5, with 1 being no pain) on average are similar to the findings of a Dutch study (Boerlage et al., 2008) and suggest that pain in nursing home residents is significant and may impact their quality of life.
Localization of pain in specific body areas is an important issue to understanding pain in nursing home residents who tend to have multiple chronic diseases. The results of our study are similar to the findings by McClean and Higginbotham (2002), in which the most common sites of pain were found to be the limbs, joints, and back; the findings by Leong and Nuo (2007) of 24% with pain in the lower extremities and 25% with pain in the back in a sample in Singapore nursing home residents; and the findings by Zanocchi et al. (2008) of high prevalence of pain in the knees, hip, and back. Tse, Leung, and Ho (2012) also reported that the most common sites for pain in their sample of nursing home residents were knee, back, shoulder, and musculoskeletal parts, with the most intense pain experienced in the knees. Although pain in the back and lower extremities is likely due to osteoarthritis, which is prevalent in nursing home residents, it is also possible that pain in these regions of body results from having to stay in one position in a bed or chair for extended periods. Since pain in the back and lower extremities has implications for mobility and suggests vulnerability for falls (Proctor & Hirdes, 2001), it is critical to investigate further how pain location influences functioning and mobility and affects falls. In addition, as shown in our study, nursing home residents experience pain in several different body areas at a same time, suggesting a need for pain assessment that is discriminatory not only in terms of intensity but also characteristics related to quality, location, timing, and duration.
Most studies examining the persistence of pain determined it by the presence of pain at the second time point in relation to the first time of measurement, with the duration between the two time points often extending to 6 months (e.g., Won et al., 2004). Although persistent pain does not have to be associated with chronic pain caused by certain pathology, it is commonly regarded and measured similarly. Therefore, the concepts of chronic pain and persistent pain are used somewhat interchangeably, and there is no agreement regarding the exact nature of persistent pain. In our study, persistent pain was viewed as pain that exists on 5 different days, measured 1 or 2 days apart, within a period of 14 days. Persistent pain measured in this way provides a greater insight into how pain persists over time. Persistent pain of moderate to intense level measured in this way was present in nearly one half of the participants. Although it is not possible to state that these residents had pain daily, the presence of moderate to intense pain on 5 different days within a 14-day period suggests persistence or frequency. The rates of our study are similar to the findings in nursing home residents from other studies such as by Won et al. (2004), who reported 48.5% with persistent pain, and by Zanocchi et al. (2008), who reported 83% with chronic pain, of which 49% were persistent, although the definition of persistent pain used in these studies was not uniform and was different from the definition used in our study. The extent of persistent pain in nursing home residents suggests their pain management is inadequate in general. The results of our study add to the understanding of persistent pain in nursing home residents especially as experienced within a short time. As there was no previous research examining pain persistence in nursing home residents over several days within a short time period, the findings of this study provide insight regarding how pain is experienced by nursing home residents from one day to the next. This understanding is critical, especially from a pain management perspective.
More intense pain and persistent pain were found to be associated with number of medical diagnoses and number of medications, suggesting, as expected, that nursing home residents with a high number of comorbid conditions were more likely to experience greater pain and persistent pain. Pain as the consequence of various chronic illnesses is an important issue for further understanding, as our findings showed that residents who had chronic diseases with musculoskeletal consequences, such as rheumatoid arthritis and osteoporosis, as well as cancer and chronic pain, tended to have more intense pain. Our findings are similar to those of Proctor and Hirdes (2001). There is a need to understand how various combinations of chronic diseases cause different kinds of pain experiences in nursing home residents.
The residents with more intense pain, as well as those with persistent pain, were more likely to have sleeping problems, as also found in studies by Boerlage et al. (2008), Smalbrugge et al. (2007), and Zanocchi et al. (2008). The major implication of the significant association between pain and sleeping problems is a possibility of a vicious cycle in which pain causes disturbed sleep, which in turn increases discomfort that exacerbates pain, which then influences quality of sleep.
This study had several limitations. One limitation was that the sample was not selected randomly and that the six nursing homes from which the participants were drawn were selected by convenience. However, these nursing homes were typical of nursing homes in Norway and did not differ substantially from other nursing homes regarding resident characteristics. An additional limitation of the sample is that the participants were able to communicate verbally and understand verbal communication, which are not typical characteristics of general nursing home residents. Although we did not test the participants’ cognitive status formally for inclusion in the study, the assumption is that cognitive impairment would have been minimal in this sample. The sample, because of the inclusion criteria, was represented by only one third from nursing home long-stay units, in which residents with chronic cognitive impairment would be found. This means the results should not be generalized to all types of nursing home residents. In one way, the results of this study provide a greater degree of insight regarding nursing home residents’ pain experiences, articulated by those who were able to express themselves clearly.
Another limitation is the lack of standardization regarding the times of pain measurement. Pain measurements on 5 different days were carried out with one specification—that they would be done between the hours of 9:00 a.m. and 7:00 p.m.. This means the pain measurements could have been confounded by the timing of analgesic agent administration or other events such as participation in physical therapy or other activities. The lapse of days from one pain measurement to the next was not standardized rigorously, although all five measurements occurred within a 14-day period and the average lapse being 2 days. This is a weakness in the measurement of pain persistence, since a consecutive, daily measurement may reveal a more accurate picture of pain persistence. The ratings on the McGill Pain Questionnaire as self-ratings were not validated by an objective pain measurement in this study. The reliability of self-ratings could have been jeopardized by the participants’ cognitive status, as we did not formally measure participants’ cognitive status. However, because interviews were used to obtain the pain ratings, it would have been possible for the researchers to identify problematic ratings at the interviews. We did not encounter rating problems due to cognitive status. Additionally we used the Insomnia Index, which is a self-report measure, for which the reliability could be questioned, although the instrument reliability was satisfactory in this sample. Use of an actigraph would have provided objective data.
While it is possible that various nursing strategies were being used to help residents with pain in these settings, the findings of the prevalence and intensity of pain, as well as the persistence of pain in this sample, suggest that pain management by analgesic agents and by other means did not seem to be adequate. From the nursing perspective, there are three issues requiring attention: (a) the prevalence and intensity of pain may mean an undermanagement of pain, which may have resulted from inadequate or insufficient pain assessment, (b) the analgesic agent management for pain may itself be flawed in terms of dosing and medication types, and (c) it is also possible that nursing management of pain is not adequate because nurses are not aware of the extent of pain in nursing home residents, as it has been shown that patients are reluctant to complain about pain (Gran, Festvåg, & Landmark, 2009; K.R. Jones et al., 2006). For a possible problem with pain assessment, it is necessary to re-examine various procedures for pain assessment in nursing homes, such as timing and use of specific instruments, in relation to adequacy and appropriateness in assessing not only the intensity but also duration, location, and quality. Nurses’ responsibility regarding pain management must include both assessment regarding the effectiveness of analgesic agents and being alert to as-needed analgesic agent needs, along with seeking out and applying other pain-preventing and pain-relieving strategies.
The prevalence and intensity of pain in nursing home residents cannot be overlooked and is a serious problem with various consequences. The high rate of persistent pain and the apparent inadequacy of pain therapy via analgesic agents also suggest unnecessary suffering. While the reasons for the high rate of persistent pain are not well understood and may not be attributable solely to poor management, there is a need to examine the current practice of pain management in nursing homes to improve this situation. One area of importance seems to be pain assessment in nursing homes. Since pain in nursing home residents may result from various causes, including not only pathologies and chronic diseases but also inactivity, undernutrition, and other problems such as incontinence, pain assessment may need to incorporate location, duration, quality, and timing, in addition to intensity. There is a need to explore in a greater detail the characteristics of pain persistence and its emergence in nursing home residents to address the problem more adequately.
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Participants with Slight to Intense Pain in Various Body Areas at Five Pain Ratings (N = 201)
|HN, Front, and UE
|LE, HN, Front, and UE
|Back and LE
|Back and other regions excluding LE
|All five regions
|Pearson correlation between number of body areas with pain and pain rating
Selected Personal and Clinical Variables by Pain Pattern Group
||Pain Pattern Types over Five Ratings
||No or Low Pain (n = 77)
||Persistent Moderate Pain (n = 73)
||Persistent Intense Pain (n = 22)
||Fluctuating Pain (n = 29)
||F = 2.592
p = 0.054
||F = 3.287
p = 0.022*
|Number of medical diagnoses
||F = 4.999
p = 0.002**
|Number of medications
||F = 3.274
p = 0.022*