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Pain prevalence and risk factors based on self-reported data from nursing home residents: a multicentre cross-sectional study

  • Open Access
  • 29.09.2025
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Abstract

Background

Pain has a major impact on nursing home residents’ quality of life, which is why optimizing pain management continues to be a major issue in nursing homes.

Objective

The aim of our study was firstly to investigate the prevalences of pain and severe pain as well as potential indications of undertreatment in Swiss nursing homes by directly interviewing residents. Secondly, we examined which nursing home and resident characteristics are associated with pain, with severe pain and with undertreatment.

Methods

Data on pain in nursing home residents was collected as part of a multicentre cross-sectional survey of 49 nursing homes involving 1198 structured face-to-face interviews with residents. Data were analysed both descriptively and using logistic and linear regression.

Results

The data revealed that 59.7% of residents experienced pain, with a median pain intensity of 5 (moderate). Indications of undertreatment and thus potential for improvement were found, in that 12.6% of residents reported not receiving pain medication despite pain, and 15.9% of residents reported severe pain (7–10) despite receiving pain medication. General health status was identified among others as a relevant predictor of pain frequency, intensity, absence of medication and pain despite pain medication intake.

Conclusion

Pain is still prevalent in Swiss nursing homes, in particular among women and residents with poor or very poor overall health conditions. Therefore, optimising pain management should be a priority in general, but with special attention to these at-risk groups.

Publisher’s Note

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Introduction

The number of older people is steadily rising, both internationally (United Nations Department of Economic and Social Affairs 2019) and nationally in Switzerland (Bundesamt für Statistik 2023). As life expectancy increases, so do the risks of chronic disease and multimorbidity. As a consequence, more people are becoming dependent on help from their relatives or on professional help from outpatient services or residential institutions (Maresova et al. 2019), thus continuously increasing the number of people living in nursing homes (Eurostat 2021). For nursing homes, this translates into residents becoming older and more dependent on care. The existing and worsening shortage of qualified healthcare professionals (Organisation for Economic Co-Operation and Development (OECD) 2019; Schweizerisches Gesundheitsobservatorium (Obsan) 2021) and increasingly restrictive funding for long-term care (Eling and Elvedi 2019) exacerbate the challenge of ensuring a high quality of care and quality of life for nursing home residents.
Physical pain plays an important role in the quality of life of nursing home residents (Bjork et al. 2016; Sjölund et al. 2021; van Kooten et al. 2017). In the context of this article, pain is defined as “an unpleasant sensory and emotional experience associated with actual or potential tissue damage” (Raja et al. 2020). Pain affects all areas of nursing home residents’ lives, such as activities of daily living, mood, participation in activities and social integration. In residents with severe pain, these aforementioned negative effects are particularly present (Brunkert et al. 2020).
Even though more attention has been paid to the issue of pain in nursing home residents in recent years, the situation has not yet improved sufficiently, with pain prevalence rates still ranging between 43 and 84% (Damsgard et al. 2018). These rates indicate considerable potential for quality improvement with regard to the quality of care. Pain is frequently under detected and, accordingly, undertreated (Veal et al. 2018). This is due, for instance, to a lack of training in assessing and treating pain among healthcare professionals (Damsgard et al. 2018) and insufficient cooperation between medical and nursing staff (Veal et al. 2018). Moreover, residents with limited cognitive or communicative abilities cannot adequately express themselves (Miu and Chan 2014) and, last but not least, many residents and staff believe that pain is an expected part of ageing (Bae et al. 2020).
A first important step towards quality improvement is to understand more precisely which residents are affected by pain. Once those in pain are identified, it is particularly significant to understand who is affected by severe pain and undertreatment (Reid et al. 2015). International studies have explored the characteristics of residents who experience pain. Residents with more severe depressive symptoms reported increased severity and consistency of pain (Chen et al. 2020). In residents with impaired cognitive function, the results were mixed: Bae et al. (2020) reported less pain, which was attributed to the fact that these residents are less able to express pain. Sjölund et al. (2021) found no significant difference based on cognitive levels. In addition to resident characteristics, nursing home characteristics were evaluated. Residents in large nursing homes and in homes located in urban areas were more likely to suffer from pain (Sjölund et al. 2021; van Herk et al. 2009).
In the literature, the presence of pain and the characteristics that influence pain have usually been determined by nursing documentation or by interviewing healthcare professionals (Bae et al. 2020; Bjork et al. 2016). However, it has been conclusively shown that the assessment of residents’ pain by staff is not identical to the self-assessment of pain by residents (Sjölund et al. 2021; van Herk et al. 2009), and the gold standard and desirable goal is to ask the residents themselves, whenever possible. This is further underscored by the intended transformation in nursing homes away from task-oriented care and towards person-centred care. In this context, it is essential to focus on the needs, wishes and preferences of residents and to take their perspective into account (Sion et al. 2020).

Aim of the study

The aim of our study was firstly to investigate the prevalences of pain and severe pain as well as potential indications of undertreatment in Swiss nursing homes. Secondly, we examined which nursing home and resident characteristics are associated with pain, with severe pain and with potential undertreatment. Importantly, we interviewed the residents directly. Based on the results, we wanted to determine which residents would benefit most from targeted quality improvement measures.

Research questions

We derived two research questions: what are the prevalences of pain and severe pain among nursing home residents in Switzerland, and are there indications of undertreatment?
Which nursing home and resident characteristics are associated with the presence of pain, severe pain and potential undertreatment among nursing home residents in Switzerland?

Methods

Study design

This study reports the results on pain collected in the multicentre cross-sectional Residents’ Perspectives of Living in Nursing Homes in Switzerland 2019 (RESPONS 2019) study. The RESPONS 2019 study was conducted with the aim of exploring the quality of life, including emotional wellbeing and quality of care, from the perspective of nursing home residents, with in-depth questions on the topics of person-centredness, pain and the organisation of everyday life.

Setting and sample

Nursing home recruitment of the RESPONS 2019 study was based on convenience sampling. The Swiss Nursing Homes Associations Curaviva and Senesuisse informed their members about the study, and interested nursing homes could register for it. Nursing homes had to have at least 20 residents in order to participate, and nursing homes specialised in dementia care with only residents suffering from severe cognitive impairments could not participate, as we interviewed the residents directly. Of the 1485 nursing homes in Switzerland (Bundesamt für Statistik [Swiss Federal Statistical Office] 2022), a total of 49 nursing homes that met the inclusion criteria were recruited to participate in the study.
From these participating nursing homes, residents were recruited to participate in the study according to defined inclusion and exclusion criteria. All residents who understood and spoke the national languages German or French were included. In addition, all residents with severe cognitive impairment, as indicated by a cognitive performance scale score ≥ 4, or poor physical or mental health that would have precluded conducting a standardised interview were excluded. The cognitive performance scale is a standardised assessment carried out in the nursing homes for all residents. Physical and mental health state were assessed by healthcare professionals in the nursing home who knew the residents well. They assessed whether the resident’s physical and mental health would allow them to participate in an interview lasting approximately 30 min. To assist the nursing staff in their assessment, the following examples were provided to make them aware of situations that could make an interview impossible and thus lead to residents being excluded: severe dyspnoea, severe exhaustion, acute anxiety disorder, severe depression, acute psychotic crisis. Residents were informed about the study by those responsible for the study in the nursing homes, and written consent to participate was obtained.
Of the total of 3934 nursing home residents, 1264 could be completely interviewed in the RESPONS 2019 study (Fig. 1). Residents who were not interviewed had either declined to consent to the study or were ill, hospitalised, or absent on the day of data collection.
Fig. 1
Overview of study participant recruitment and the subsample analysed
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Inclusion and exclusion criteria of the pain subsample
In the present study, all residents who did not answer the initial question on pain (‘Do you have physical pain?’) or were under 65 years old were additionally excluded from the data analysis. The subsample analysed was therefore based on the information provided by 1198 nursing home residents.

Instruments

Data for the subsample residents were collected using three existing and validated instruments: an adapted and extended version of the resident quality of life (ResQoL) questionnaire, the care dependency scale and the cognitive performance scale. In addition, sociodemographic data of the residents (age, gender, length of stay) and nursing home-related data (home size, location [rural/urban], language region, legal form) were collected.
The extended ResQoL 2019 questionnaire used in the study was originally based on the resident quality of life questionnaire developed by Kane et al. (2003) at the University of Minnesota, which measures quality of life as a comprehensive multidimensional construct. The resident quality of life questionnaire was translated into German and French using a scientific approach (Wild et al. 2005), adapted by means of psychometric testing and expanded with in-depth questions in conjunction with experts. The ResQoL 2019 instrument includes the subject’s dignity, autonomy, person-centredness and meaningful activities, and the extended ResQoL 2019 questionnaire includes additional questions on activities of daily living, the nursing home entry process and pain. The additional questions were derived from the literature and developed and evaluated by a panel of experts. For the present article, the answers to the three questions on pain listed in Table 1 were analysed. The question of pain intensity was assessed using the numeric rating scale, which is a well-established and validated instrument for pain assessment in older adults (Schofield 2018). Residents were asked to rate their pain with a number between 0 and 10, whereby 0 meant no pain and 10 meant the strongest pain imaginable (Williamson and Hoggart 2005).
The care dependency scale (CDS) assesses the extent to which a person is care dependent (informal or professional care). Each of the 15 dimensions of care dependency (e.g. food and drink, continence, mobility) is measured with a five-point Likert scale ranging from 1 (completely care dependent) to 5 (almost independent). The sum score ranges from 15 to 75 points and can be categorised into five sections: completely care dependent, to a great extent dependent, partially dependent, to a great extent independent and care independent (Dijkstra et al. 2006). The CDS has been psychometrically tested in different settings and languages. Internal consistency is very high, with an average α value of 0.97. Inter-rater reliability is described as good, with Cohen’s kappa of 0.65 (Zürcher et al. 2016).
Table 1
Description of the questions on pain from the extended ResQoL 2019 questionnaire, which served as the basis for the outcomes in the analyses
Question
Response categories
Outcomes in the analyses
Do you have physical pain?
Yes, partly, no
Outcome 1: pain frequency (no [0]/yes/partly [1])
How do you rate the average severity of your pain over the past week?
0–10 (0 = no pain, 10 = strongest pain imaginable)
Outcome 2: pain intensity (0–10)
Do you receive pain medication?
Yes, partly, no
Outcome 3: pain with no medication reported (pain yes/partly and pain medication yes/partly [0]/pain yes/partly and pain medication no [1])
Outcome 4: pain despite receiving pain medication (pain medication yes/partly and pain intensity < 7 [0]/pain medication yes/partly and pain intensity ≥ 7 [1])
The cognitive performance scale (CPS) evaluates a person’s cognitive abilities. It combines information based mainly on a person’s ability to make daily decisions, on the ability to make themselves understood and on their memory. The CPS scores range from 0 (intact) to 6 (very severe impairment). Paquay et al. (2007) confirm that the CPS achieves comparable results to the mini-mental state examination in the assessment of cognitive impairment in nursing home residents. As residents with a CPS ≥ 4 were excluded, the residents analysed had scores of 0–3 only.

Outcomes and covariates

Based on the three questions on pain from the extended ResQoL 2019 questionnaire (Table 1), we formed and examined four outcomes in this study:
  • Outcome 1 was based on the question of whether physical pain was present. The three response categories of this question (yes, partly, no) were dichotomised for the analyses (no = 0, yes/partly = 1).
  • Outcome 2 was based on the question about the intensity of pain.
  • Outcomes 3 and 4 examined whether indications of undertreatment were present.
    • Outcome 3, pain with no medication reported, is based on a combination of the variables physical pain and whether the resident reports receiving pain medication. In order to obtain a binary outcome variable, residents who reported pain (yes/partly) and also reported receiving pain medication (yes/partly) were coded as 0. Residents who reported pain (yes/partly) but reported not receiving pain medication (no) were coded as 1.
    • Outcome 4, pain despite receiving pain medication, is based on a combination of the variables whether the resident reports receiving pain medication and pain intensity. In order to obtain another binary outcome variable, residents who reported receiving pain medication (yes/partly) without reporting high pain intensity (< 7) were coded as 0. Residents who reported receiving pain medication (yes/partly) and high pain intensity (≥ 7) were coded as 1.
The nursing home and resident-related characteristics that were considered as possible covariates in the model developments can be found in Table 2.
Table 2
Description of nursing home- and resident-related characteristics used as covariates in analysis
 
Response categories
Nursing home characteristics
Size
Small (20–49 beds)
Medium (50–99 beds)
Large (≥ 100 beds)
Location
Urban
Intermediarya
Rural
Language
German
French
Legal status
Public
Publicly funded
Private
Resident-related characteristics
Age
Scaleb
Sex
Male
Female
Cognition
Intact (CPS = 0)
Borderline intact (CPS = 1)
Mild impairment (CPS = 2)
Moderate impairment (CPS = 3)
Care dependency scale (CDS)c
Care dependent (15–24 points)
To a great extent dependent (25–44 points)
Partially dependent (45–59 points)
To a great extent independent (60–69 points)
Care independent (70–75 points)
Participation in choice of nursing home
No
Partly
Yes
Overall healthd
Very poor
Poor
Mediocre
Good
Very good
aNursing homes in densely populated peri-urban areas and rural centres
bAge was used as a categorical variable in the analyses as follows: 65–74 years, 75–84 years, 85–94 years and > 95 years
cDue to a small number of cases, the category care dependent was combined with the category to a great extent dependent in the analyses
dThe response categories very poor and poor as well as the categories good and very good were combined for the analyses

Data collection

Data for the RESPONS 2019 study were collected between March and December 2019. The sociodemographic data of the participating residents were transmitted to us by the nursing homes in advance of the data collection day. The CDS and CPS had also been pre-assessed by nursing home staff and were transmitted to us beforehand. For data collection, staff with a nursing background received specific training to conduct the structured ‘face-to-face’ interviews with the residents in the nursing homes using the extended ResQoL 2019 instrument. On every collection day, a member from the research department was on the respective site to help with data collection as well as having the overall responsibility. A user manual was provided for uniformity of data collection and the completed questionnaires were checked for completeness at the end of the data collection day. The responses were documented in writing on paper and scanned and processed using the Remark Office OMR programme (Gravic, Inc., Malvern, Pennsylvania, USA). In the case of conspicuous data entries, a data plausibility check was carried out with the responsible persons in the nursing homes.

Data analysis

First, the characteristics of the nursing homes and residents included in the present analysis were described by means of frequencies and percentages. Second, to describe the prevalence of pain and severe pain and the indications of undertreatment, the four defined outcome variables (pain frequency, pain intensity, pain with no medication reported, pain despite receiving pain medication) were analysed using frequencies, percentages and 95% confidence intervals (95% CI). The 95% confidence intervals were provided to quantify the precision of the estimated percentages and to indicate the statistical uncertainty associated with the observed percentages. Third, a logistic regression model or a linear regression model (in the case of average pain intensity in the past week) was developed to identify relevant nursing home- and resident-related characteristics per outcome. For this purpose, a so-called full model was first constructed for each outcome, i.e. all available nursing home- and resident-related characteristics according to Table 2 were considered as covariates in these models as well as possible interaction effects. To subsequently obtain a reduced model, a stepwise backward selection process using the Bayesian information criterion was applied to each full model to obtain the final model containing only the most relevant predictors per outcome (Neath and Cavanaugh 2012; Raffalovich et al. 2008). Cases with missing values in the covariates were excluded from the regression analyses (listwise deletion). Due to low variability between the nursing homes as indicated by a low intraclass correlation coefficient for all outcomes, multilevel analysis was omitted despite a hierarchical data structure.
Data preparation and descriptive data analysis were carried out using SPSS© statistical software (version 28; IBM Corp., Armonk, NY, USA). The modelling and visualisation processes were carried out with the statistical programme R, version 4.1.0 (R Core Team 2021), and the packages lme4 (Bates et al. 2015) and effects (Fox 2003). The statistical significance level was set at a p-value below 0.05.

Ethical considerations

The relevant ethics committee, the Ethics Commission of the Canton of Bern, approved the study (project ID 2019-00109). Nursing home residents were informed verbally and in writing about the content and aims of the study by the contact persons in the nursing homes and signed an informed consent form. Before beginning the interview, verbal consent was obtained, and it was pointed out that the interview could be terminated at any time and without giving reasons. Data were pseudonymised.

Results

A total of 49 nursing homes took part in the study. Most of the participating nursing homes were medium sized, with 50–99 beds (42.9%). A clear majority of the nursing homes were located in urban areas (71.4%) and in the German-speaking part of Switzerland (85.7%). A comparable number of nursing homes were private (38.2%) and public (36.7%). Table 3 provides an overview of the participating nursing homes.
Table 3
Overview of the nursing homes studied and their characteristics
Nursing homes
Total (n = 49)
n
%
Size
Small (20–49 beds)
10
20.4
Medium (50–99 beds)
21
42.9
Large (≥ 100 beds)
18
36.7
Location
Urban
35
71.4
Intermediarya
7
14.3
Rural
7
14.3
Language
German
42
85.7
French
7
14.3
Legal status
Public
19
38.8
Publicly funded
12
24.5
Private
18
36.7
aNursing homes in densely populated peri-urban areas and rural centres
The general characteristics of the 1198 residents included in the present study are shown in Table 4. The majority of participants were women (71.5%). Over half of the participants (54.2%) were 85–94 years old, another quarter (26.0%) were 75–84 years old. Cognition of half of the participants was intact (31.5%) or borderline intact (23.5%), 27.3% were mildly impaired and 17.8% were moderately impaired. Most of the participants were care independent (38.2%) or to a great extent independent (32.0%). Only a few residents who were to a great extent dependent or care dependent (6.9%) could be interviewed. The vast majority of participants were able to completely (56.9%) or partially (9.1%) choose the nursing home they wanted to go to. Most participants rated their overall health as good or very good (56.1%) or as mediocre (37.8%).
Table 4
Description of resident characteristics
Characteristics
Total participants (n = 1198)
n
%
Sex
Female
857
71.5
Age
65–74 years
109
9.1
75–84 years
312
26.0
85–94 years
649
54.2
> 94 years
128
10.7
Cognitive performance scale (CPS)
Intact (0)
377
31.5
Borderline intact (1)
281
23.5
Mild impairment (2)
327
27.3
Moderate impairment (3)
213
17.8
Care dependency scale (CDS)a
Care dependent (15–24 points) or to a great extent dependent (25–44 points)
82
6.9
Partially dependent (45–59 points)
272
22.9
To a great extent independent (60–69 points)
379
32.0
Care independent (70–75 points)
453
38.2
Participation in choice of nursing homea
No
402
34.0
Partially
107
9.1
Yes
672
56.9
Overall healtha
Very poor & poor
71
6.0
Mediocre
448
37.9
Good & very good
662
56.1
aNot all residents answered this question. Accordingly, the overall total for this question is lower than the total number of residents included in the analysis

Pain reporting

Pain frequency

The first aim of the study was to determine how many residents were affected by pain. Of the 1198 residents interviewed, approximately 6 of 10 residents (59.7%, n = 715, 95% CI = 56.9–62.4%) reported experiencing pain. Table 5 presents the resident characteristics identified in model 1 (pain frequency) that were associated with higher odds of pain. Based on data from 1181 residents included in model 1, women were found to have 1.57 (95% CI = 1.20–2.05%; p = 0.001) higher odds of having pain than men. Additionally, residents with a medium (odds ratio [OR] 3.58, 95% CI = 2.75–4.68%; p < 0.001) as well as a poor or very poor (OR 3.29, 95% CI = 1.92–5.89%; p < 0.001) overall health status had more than three times higher odds of having pain than residents with a good or very good overall health status.
Table 5
Overview of the models regarding pain frequency, pain intensity, lack of pain medication and insufficiently effective medication
 
Model 1
Pain frequency
Model 2
Pain intensity
Model 3
Pain with no medication reported
Model 4
Pain despite reporting receiving pain medication
Predictors
OR
95% CI
p‑value
B
95% CI
p‑value
OR
95% CI
p‑value
OR
95% CI
p‑value
Sex (female)
1.57
1.20–2.05
0.001
0.16
−0.36–0.67
0.548
Overall health status (good or very good)
Reference
Reference
4.42
1.28–27.82
0.046
Reference
Overall health status (moderate)
3.58
2.75–4.68
< 0.001
1.00
0.38–1.63
0.002
3.74
1.09–23.50
0.076
2.41
1.52–3.91
< 0.001
Overall health status (poor or very poor)
3.29
1.92–5.89
< 0.001
0.24
−1.10–1.58
0.725
Reference
3.39
1.61–6.91
0.001
Sex (female): overall health status (moderate)
−0.30
−1.02–0.42
0.415
Sex (female): overall health status (poor or very poor)
1.48
−0.02–2.98
0.052
Age (> 94 years)
Reference
Age (85–94 years)
3.06
1.19–10.42
0.038
Age (75–84 years)
2.22
0.78–7.99
0.167
Age (65–74 years)
3.79
1.23–14.26
0.029
Nursing home size (small [20–49 beds])
Reference
Nursing home size (mediocre [50–99 beds])
2.85
1.17–8.55
0.036
Nursing home size (large [100+ beds])
1.77
0.73–5.28
0.251
Choice of nursing home (yes)
Reference
Choice of nursing home (partly)
0.45
0.15–1.10
0.110
Choice of nursing home (no)
1.19
0.76–1.84
0.443
Observations
1181
637
684
666
OR odds ratio, CI confidence interval

Pain intensity

The next point of enquiry was to determine the average severity of pain in the past week. Participants who reported having pain (n = 715) were asked to rate their average pain intensity on a scale from 0 to 10 (0 = no pain, 10 = worst pain imaginable). A total of 645 residents assessed pain intensity. The minimum pain intensity indicated was 0 and the maximum was 10. On average, moderate pain was reported (median = 5, interquartile range [IQR] = 3). Model 2 (pain intensity), including data from 637 residents, in Table 5 shows the resident characteristics associated with more severe pain. As with model 1 on pain frequency, model 2 on pain intensity showed sex and general health to be relevant predictors of more severe average pain intensity. However, the relationship between overall health and pain intensity differed by sex (interaction effect). Women had less pain the better their overall health. Among men, this was true only for those with moderate and good or very good overall health. Among residents with poor or very poor overall health, women had significantly higher pain intensity than men. Thus, poor overall health was more frequently accompanied by severe pain in women than in men (Fig. 2).
Fig. 2
Visualisation of the interaction effect between general health and sex regarding pain intensity
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Indications of undertreatment of pain

Pain with no medication reported
Subsequently, it was investigated whether residents with pain reported receiving pain medication and which characteristics residents who expressed pain but did not report receiving pain medication shared. Of the 715 residents with pain, 696 provided information on whether they received pain medication. According to the findings, 12.6% (95% CI = 10.3–15.3%) indicated that they did not receive any pain medication. Model 3 (pain with no medication reported) in Table 5 shows the identified nursing home and resident characteristics that were associated with higher odds of residents reporting not receiving pain medication despite experiencing pain. It revealed that residents of medium-sized homes were 2.85 (95% CI 1.17–8.55%; p = 0.036) times more likely to suffer from pain without reporting receiving pain medication than residents from small nursing homes. In comparison to residents with poor or very poor overall health, residents with good or very good overall health had 4.42 (95% CI = 1.28–7.82%; p = 0.046) times higher odds of being in pain without reporting receiving pain medication. A further characteristic of residents in danger of having their pain undertreated was age. Compared to residents over 95 years of age, residents between 65 and 74 years (OR 3.79, 95% CI 1.23–14.26%; p < 0.029) and residents between 85 and 94 years of age (OR 3.06, 95% CI 1.19–10.42%; p < 0.038) had greater odds of having pain without reporting receiving pain medication.
Pain despite reporting receiving pain medication
The last outcome assessed was whether residents who reported receiving pain medication were still experiencing pain. Despite reporting receiving pain medication, 15.9% (95% CI = 13.3–18.8%) of the 666 residents with pain who answered this question reported severe average pain intensity (≥ 7 on a scale of 0–10). Table 5 shows the resident characteristics identified in model 4 (pain despite reporting receiving pain medication) that were associated with being in severe pain despite reporting receiving pain medication. Residents with moderate (OR 2.41, 95% CI 1.52–3.91%; p < 0.001) as well as poor or very poor health (OR 3.39, 95% CI 1.61–6.91%; p < 0.001) had increased odds of having severe pain despite reporting receiving pain medication compared to those in good or very good health.

Discussion

Our study investigated the frequency and intensity of pain among residents of Swiss nursing homes by directly interviewing the residents. Further factors associated with pain, such as which residents were affected by pain and in particular by severe pain on average over the past week and which residents showed indications of undertreatment, were explored. Approximately 60% of nursing home residents reported experiencing a median pain intensity of 5 (moderate), with women and those in poorer health having significantly higher odds of both pain and higher pain intensity. Indications of undertreatment were found in that 12.6% of residents with pain reported not receiving pain medication and 15.9% of residents who reported receiving pain medication nevertheless reported severe pain intensity (7–10).
The results of our study confirm that pain remains a major topic in nursing homes in Switzerland among cognitively intact or slightly impaired residents, despite all efforts in recent years to reduce it (Damsgard et al. 2018). Of the 1198 residents interviewed, just under two-thirds reported experiencing pain. In general, pain prevalence is described as varying internationally, but the number found in our study ranks among the higher values (Cole et al. 2023). This is consistent with the finding that higher levels of pain are found when residents themselves or their relatives are interviewed as opposed to when pain data are taken from documentation (Cole et al. 2023).
In order to better address pain in nursing home residents, it is important to know which characteristics residents with pain share. The results from our models 1 and 2 about pain frequency and pain intensity show that women experience more pain than men, which is confirmed in the international literature (Brandauer et al. 2020; Cole et al. 2023; Lukas et al. 2013). Various reasons, such as biological processes related to sex-specific hormones or the different nature of male and female brain structure and function, are discussed (Wranker et al. 2016). It is also conceivable that cultural norms may give an older generation of women a feeling that they do not have the right to express their needs. Our results show that in women, poor overall health is also more often accompanied by severe pain, which is not the case in men. Essentially, pain status needs to be determined more precisely and carefully in female nursing home residents so that a better response can be made when pain is present.
Another indication of residents in pain can come from looking at their overall health. Residents were asked to self-assess their overall health. The results of our models 1 and 2 about pain frequency and pain intensity show that residents who rated their overall health as moderate and poor or very poor were more likely to have pain than residents who self-assessed their overall health as good or very good, which is confirmed in the literature (Axon and Maldonado 2023). It seems reasonable that there is a link between poor overall health and pain, since a poorer health status is associated with illness, and this may be a reason for pain. However, it could not be determined whether residents perceived their overall health to be worse because they were in pain or whether their poor health was leading to pain. Interestingly, model 3 regarding pain with no medication reported shows that residents with good or very good overall health had higher odds of being in pain without reporting receiving medication against it than residents with poor or very poor overall health. In residents with good or very good overall health, pain is probably less expected than in residents with poor or very poor health, so the residents with good overall health might not be asked about pain at all. The same hypothesis may be true for younger versus older residents. In contrast, model 4 about pain despite reporting receiving pain medication showed that residents with moderate as well as poor or very poor overall health had higher odds of reporting pain despite reporting receiving pain medication compared to residents with good or very good overall health. It is conceivable that both residents and healthcare staff in nursing homes simply view pain as an irrevocable given when the chosen pain medications do not seem to work sufficiently, rather than considering a change in therapy.
The descriptive analyses related to the third outcome showed that more than 12% of residents interviewed who were suffering from pain were subjectively not receiving any kind of pain medication. Although this is a lower rate than in previous international studies (Boonstra et al. 2016; Scottish Intercollegiate Guidelines Network (SIGN) 2013, Revised August 2020), it still deserves closer attention. Apart from the aforementioned association with overall health, this specific group presented additional characteristics. Residents of medium-sized nursing homes were more likely to suffer from pain without reporting receiving pain medication than residents from small nursing homes. A reason could be that in medium-sized nursing homes it is less possible to know each resident personally than in small nursing homes (Spangler et al. 2019). On the other hand, medium-sized homes might have fewer resources to have a specific expert group responsible for pain management in comparison to large nursing homes. Experts in pain management can identify pain in residents more effectively and ensure regular training on pain management in the nursing homes (Ersek et al. 2020). Model 4 about pain despite reporting receiving pain medication shows that even if residents receive pain medication, it does not always seem to work sufficiently. This takes on even greater significance considering that 15.9% of residents who stated that they were given pain medication still rated their pain as severe. According to current guidelines, the pain management of these residents must be evaluated regularly (Boonstra et al. 2016; Scottish Intercollegiate Guidelines Network (SIGN) 2013, Revised August 2020). As pain is a highly complex biopsychosocial construct (European Pain Federation 2022), this pain management must not only include pharmacological measures but also other important aspects that can have an impact on pain (e.g. nonpharmacological measures or the overall circumstances of the residents). This knowledge must be firmly established in nursing homes so that pain is regularly recorded and successfully treated.
In contrast to other studies (Bae et al. 2020; Cole et al. 2023), our results showed no association between cognitive impairment and pain or its severity. This might be related to the fact that only residents with intact or mildly to moderately impaired cognition could be included in our study. Care dependence was another characteristic we tested, but it showed no relevant associations with the outcomes in the models and, accordingly, was not selected into the model. This is in contrast to other research, as internationally, higher care dependency was shown to have a negative impact on pain (Hoedl and Bauer 2020). However, in our study, only a minority of those we interviewed were highly care dependent, which might have had an influence on our results. The characteristic of choice of nursing home was selected in one model, but the association did not reach a statistically significant level. There was not much variability between nursing homes. Whether someone is in pain seems to depend more on the person than on which nursing home they live in. Another possible interpretation is that the quality of care in Swiss nursing homes is homogeneous in terms of pain management and that improvements are therefore needed at national level.

Limitations

It is important to acknowledge the limitations of our study. One potential limitation is selection bias, as participation in the study was voluntary and may have attracted nursing homes that were particularly concerned with quality of care and therefore pain management. Therefore, our results may not be representative of all nursing homes, and an underestimation is likely to be assumed. Another limitation is that we could only conduct interviews with residents who were cognitively intact or moderately cognitively impaired. This excluded residents who were severely cognitively impaired and may be at a higher risk for undertreatment of pain. However, thanks to the fact that we conducted interviews and did not have residents fill out questionnaires themselves, at least the mildly to moderately cognitively impaired individuals could be included. Although it is not possible to generalize the results to all nursing home residents, the specific group we interviewed was given a voice.
Furthermore, our study relied on self-report from residents regarding pain medication use, which may be subject to bias. Due to the large number of medications that nursing home residents often take, it is possible that they may not have accurately assessed whether or not they were receiving medication that is administered specifically for their pain. Medication is mostly dispensed by nursing staff in nursing homes, which makes it even more difficult for residents to keep track of their medication. We did not verify whether or not residents had been given pain medication in the residents’ documentation.
The biopsychosocial model of pain describes pain as a personal experience shaped by dynamic interaction of biological, psychological and social factors (European Pain Federation 2022). Since our study was part of a larger study on a wide range of topics, we were only able to analyse the data that were collected as part of the study. Other important aspects in connection with pain, such as nonpharmacological measures or the overall situation of the residents, were not surveyed. In addition, we have too little information to distinguish between whether residents were suffering from chronic or acute pain, which can make a significant difference to treatment (European Pain Federation 2022). For further studies in this area, we strongly recommend that these aspects are considered when planning data collection. Furthermore, in our study, we asked about the presence of physical pain. Due to the biopsychosocial component of pain, it may be difficult for some residents to assess whether their pain is considered to be physical pain. However, it can be assumed that in case of bias, a systematic underestimation of pain is most likely, which further emphasizes that pain management in nursing homes needs to be carefully evaluated and improved.
For variable selection, we chose an exploratory approach by testing factors influencing pain described in the literature (Bae et al. 2020; Bjork et al. 2016). The cross-sectional study design did not reveal causal relationships. For example, it remains unclear whether poor overall health status causes pain or vice versa.
It is important to note that although the supplementary questions of the extended ResQoL 2019 questionnaire used in the study were generated from the literature and with the help of experts, they have not been validated.
The study provides initial insights into possible undertreatment, but with the information available, we cannot answer the question of undertreatment conclusively, merely provide indications. Further investigations are needed to identify the more precise reasons why, for example, residents report that they do not receive pain medication despite being in pain.
Despite these limitations, our study contributes to the existing literature on pain management in nursing homes. By identifying factors that are associated with indications of undertreatment of pain and highlighting the need for regular pain assessments and interprofessional collaboration, our study provides valuable insights that can inform the development of strategies to improve pain management.

Conclusion

The problem of pain is prevalent in nursing homes in Switzerland among cognitively intact or slightly impaired residents, with many residents experiencing high levels of pain intensity and a significant percentage who still report pain even though they report receiving pain medication. Our results indicate that women and residents with poor or very poor overall health conditions are particularly vulnerable to experiencing pain. Therefore, optimising pain management should be a priority in general, but with special attention to these at-risk groups. It is important for nursing homes to regularly evaluate and monitor pain in their residents, preferably by asking them directly. In particular, it is important to check whether residents who are already receiving pain medication find it sufficiently effective. Inadequate pain treatment is a complex issue that requires attention to pain assessment and management concepts.

Funding

Part of the cost was covered by the participating nursing homes. The rest was financed by the Bern University of Applied Sciences.

Conflict of interest

S. Siegrist-Dreier and N.S. Bernet declare that they have no competing interests.
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Titel
Pain prevalence and risk factors based on self-reported data from nursing home residents: a multicentre cross-sectional study
Verfasst von
Sandra Siegrist-Dreier
Niklaus S. Bernet
Publikationsdatum
29.09.2025
Verlag
Springer Vienna
Erschienen in
HeilberufeScience / Ausgabe 3-4/2025
Elektronische ISSN: 2190-2100
DOI
https://doi.org/10.1007/s16024-025-00436-1
Zurück zum Zitat Axon, D. R., & Maldonado, T. (2023). Investigating the Association of pain intensity and health status among older US adults with pain who used opioids in 2020 using the medical expenditure panel survey. Healthcare, 11(14), 2010. https://www.mdpi.com/2227-9032/11/14/2010.CrossRefPubMedPubMedCentral
Zurück zum Zitat Bae, S. H., Lee, S., & Kim, H. (2020). Extent of and factors associated with pain among older residents in nursing homes in South Korea: a nationwide survey study. Geriatr Gerontol Int, 20(2), 118–124. https://doi.org/10.1111/ggi.13834.CrossRefPubMed
Zurück zum Zitat Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01.CrossRef
Zurück zum Zitat Bjork, S., Juthberg, C., Lindkvist, M., Wimo, A., Sandman, P. O., Winblad, B., & Edvardsson, D. (2016). Exploring the prevalence and variance of cognitive impairment, pain, neuropsychiatric symptoms and ADL dependency among persons living in nursing homes; a cross-sectional study. BMC Geriatr, 16, 154. https://doi.org/10.1186/s12877-016-0328-9.CrossRefPubMedPubMedCentral
Zurück zum Zitat Boonstra, A. M., Stewart, R. E., Köke, A. J., Oosterwijk, R. F., Swaan, J. L., Schreurs, K. M., & Preuper, S. H. R. (2016). Cut-off points for mild, moderate, and severe pain on the numeric rating scale for pain in patients with chronic musculoskeletal pain: variability and influence of sex and Catastrophizing. Frontiers in Psychology, 7(1466), 1–9. https://doi.org/10.3389/fpsyg.2016.01466.CrossRef
Zurück zum Zitat Brandauer, A., Berger, S., Freywald, N., Gnass, I., Osterbrink, J., Seidenspinner, D., & Kutschar, P. (2020). Quality of life in nursing home residents with pain: pain interference, depression and multiple pain-related diseases as important determinants. Quality of Life Research, 29(1), 91–97. https://doi.org/10.1007/s11136-019-02290-x.CrossRefPubMed
Zurück zum Zitat Brunkert, T., Simon, M., Ruppen, W., & Zuniga, F. (2020). A contextual analysis to explore barriers and facilitators of pain management in Swiss nursing homes. J Nurs Scholarsh, 52(1), 14–22. https://doi.org/10.1111/jnu.12508.CrossRefPubMed
Zurück zum Zitat Bundesamt für Statistik [Swiss Federal Statistical Office] (2022). Alters- und Pflegeheime [Nursing homes]. https://www.bfs.admin.ch/bfs/de/home/statistiken/gesundheit/gesundheitswesen/alters-pflegeheime.html
Zurück zum Zitat Bundesamt für Statistik (2023). Demografisches Porträt der Schweiz – Bestand, Struktur und Entwicklung der Bevölkerung im Jahr 2020 | Publikation. https://www.bfs.admin.ch/asset/de/21764558
Zurück zum Zitat Chen, Y., Wu, M., Zeng, T., Peng, C., Zhao, M., Xiao, Q., Yuan, M., Zhang, K., & Wang, X. (2020). Effect of pain on depression among nursing home residents: Serial mediation of perceived social support and self-rated health. A cross-sectional study. Geriatr Gerontol Int, 20(12), 1234–1240. https://doi.org/10.1111/ggi.14067.CrossRefPubMedPubMedCentral
Zurück zum Zitat Cole, C. S., Blackburn, J., Carpenter, J. S., Chen, C. X., & Hickman, S. E. (2023). Pain and associated factors in nursing home residents. Pain Manag Nurs. https://doi.org/10.1016/j.pmn.2023.03.002.CrossRefPubMedPubMedCentral
Zurück zum Zitat Damsgard, E., Solgard, H., Johannessen, K., Wennevold, K., Kvarstein, G., Pettersen, G., & Garcia, B. (2018). Understanding pain and pain management in elderly nursing home patients applying an interprofessional learning activity in health care students: a Norwegian pilot study. Pain management nursing, 19(5), 516–524. https://doi.org/10.1016/j.pmn.2018.02.064.CrossRefPubMed
Zurück zum Zitat Dijkstra, A., Smith, J., & Margaret, W. (2006). Manual. Measuring care dependency with the Care Dependency Scale (CDS). https://www.umcg.nl/sitecollectiondocuments/research/institutes/share/assessment%20tools/cds%20manual%20english.pdf
Zurück zum Zitat Eling, M., & Elvedi, M. (2019). Die Zukunft der Langzeitpflege in der Schweiz. Kurzfassung. https://www.ivw.unisg.ch/wp-content/uploads/2019/08/Band66-Kurzfassung.pdf
Zurück zum Zitat Ersek, M., Nash, P. V., Hilgeman, M. M., Neradilek, M. B., Herr, K. A., Block, P. R., & Collins, A. N. (2020). Pain patterns and treatment among nursing home residents with moderate-severe cognitive impairment. J Am Geriatr Soc, 68(4), 794–802. https://doi.org/10.1111/jgs.16293.CrossRefPubMed
Zurück zum Zitat European Pain Federation (2022). What is the bio-psycho-social model of pain? Federation of the International Association for the Study of Pain. https://europeanpainfederation.eu/what-is-the-bio-psycho-social-model-of-pain/
Zurück zum Zitat Fox, J. (2003). Effect displays in R for generalised linear models. Journal of Statistical Software, 8(15), 1–27. https://doi.org/10.18637/jss.v008.i15.CrossRef
Zurück zum Zitat van Herk, R., van Dijk, M., Biemold, N., Tibboel, D., Baar, F. P., & de Wit, R. (2009). Assessment of pain: can caregivers or relatives rate pain in nursing home residents? J Clin Nurs, 18(17), 2478–2485. https://doi.org/10.1111/j.1365-2702.2008.02776.x.CrossRefPubMed
Zurück zum Zitat Hoedl, M., & Bauer, S. (2020). The relationship between care dependency and pain in nursing home residents. Arch Gerontol Geriatr, 90, 104166. https://doi.org/10.1016/j.archger.2020.104166.CrossRefPubMed
Zurück zum Zitat Kane, R. A., Kling, K. C., Bershadsky, B., Kane, R. L., Giles, K., Degenholtz, H. B., Liu, J., & Cutler, L. J. (2003). Quality of life measures for nursing home residents. Journals of Gerontology: Medical Sciences, 58(3), 240–248. https://doi.org/10.1093/gerona/58.3.m240.CrossRef
Zurück zum Zitat van Kooten, J., Smalbrugge, M., van der Wouden, J. C., Stek, M. L., & Hertogh, C. (2017). Prevalence of pain in nursing home residents: the role of dementia stage and dementia subtypes. J Am Med Dir Assoc, 18(6), 522–527. https://doi.org/10.1016/j.jamda.2016.12.078.CrossRefPubMed
Zurück zum Zitat Lukas, A., Mayer, B., Fialova, D., Topinkova, E., Gindin, J., Onder, G., Bernabei, R., Nikolaus, T., & Denkinger, M. D. (2013). Treatment of pain in European nursing homes: results from the Services and Health for Elderly in Long TERm Care (SHELTER) study. Journal of the American Medical Directors Association, 14(11), 821–831. https://doi.org/10.1016/j.jamda.2013.04.009.CrossRefPubMed
Zurück zum Zitat Maresova, P., Javanmardi, E., Barakovic, S., Barakovic Husic, J., Tomsone, S., Krejcar, O., & Kuca, K. (2019). Consequences of chronic diseases and other limitations associated with old age—a scoping review. BMC Public Health, 19(1), 1431. https://doi.org/10.1186/s12889-019-7762-5.CrossRefPubMedPubMedCentral
Zurück zum Zitat Miu, D., & Chan, K. (2014). Under-detection of pain in elderly nursing home residents with moderate to severe dementia. Journal of Clinical Gerontology and Geriatrics, 5(1), 23–27.CrossRef
Zurück zum Zitat Neath, A. A., & Cavanaugh, J. E. (2012). The Bayesian information criterion: background, derivation, and applications. WIREs Computational Statistics, 4(2), 199–203. https://doi.org/10.1002/wics.199.CrossRef
Zurück zum Zitat Organisation for Economic Co-operation and Development (OECD) (2019). Health at a Glance 2019: OECD Indicators. https://doi.org/10.1787/4dd50c09-en.CrossRef
Zurück zum Zitat Paquay, L., De Lepeleire, J., Schoenmakers, B., Ylieff, M., Fontaine, O., & Buntinx, F. (2007). Comparison of the diagnostic accuracy of the Cognitive Performance Scale (Minimum Data Set) and the Mini-Mental State Exam for the detection of cognitive impairment in nursing home residents. Int J Geriatr Psychiatry, 22(4), 286–293. https://doi.org/10.1002/gps.1671.CrossRefPubMed
Zurück zum Zitat R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
Zurück zum Zitat Raffalovich, L., Deane, G., Armstrong, D., & Tsao, H.-S. (2008). Model selection procedures in social research: Monte-Carlo simulation results. Journal of Applied Statistics, 35(10), 1093–1114. https://doi.org/10.1080/03081070802203959.CrossRef
Zurück zum Zitat Raja, S. N., Carr, D. B., Cohen, M., Finnerup, N. B., Flor, H., Gibson, S., Keefe, F. J., Mogil, J. S., Ringkamp, M., Sluka, K. A., Song, X.-J., Stevens, B., Sullivan, M. D., Tutelman, P. R., Ushida, T., & Vader, K. (2020). The revised International Association for the Study of Pain definition of pain: concepts, challenges, and compromises. Pain, 161(9), 1976–1982. https://doi.org/10.1097/j.pain.0000000000001939.CrossRefPubMedPubMedCentral
Zurück zum Zitat Reid, M. C., O’Neil, K. W., Dancy, J., Berry, C. A., & Stowell, S. A. (2015). Pain management in long-term care communities: a quality improvement initiative. Annals of Long-Term Care, 23(2), 29–35. https://pmc.ncbi.nlm.nih.gov/articles/PMC4418636.PubMed
Zurück zum Zitat Schofield, P. (2018). The assessment of pain in older people: UK national guidelines. Age and Ageing (Oxford), 47(suppl_1), i1–i22. https://doi.org/10.1093/ageing/afx192.CrossRef
Zurück zum Zitat Schweizerisches Gesundheitsobservatorium (Obsan) (2021). Gesundheitspersonal in der Schweiz – Nationaler Versorgungsbericht 2021 | OBSAN. https://www.obsan.admin.ch/de/publikationen/2021-gesundheitspersonal-der-schweiz-nationaler-versorgungsbericht-2021
Zurück zum Zitat Scottish Intercollegiate Guidelines Network (SIGN) (2013). Management of chronic pain, A national clinical guideline. https://www.sign.ac.uk/media/2097/sign136_2019.pdf (Created 08.2020). Accessed 6 Jan 2020.
Zurück zum Zitat Sion, K. Y. J., Verbeek, H., de Boer, B., Zwakhalen, S. M. G., Odekerken-Schröder, G., Schols, J. M. G. A., & Hamers, J. P. H. (2020). How to assess experienced quality of care in nursing homes from the client’s perspective: results of a qualitative study. BMC Geriatrics, 20(1), 67. https://doi.org/10.1186/s12877-020-1466-7.CrossRefPubMedPubMedCentral
Zurück zum Zitat Sjölund, B.-M., Mamhidir, A.-G., & Engström, M. (2021). Pain prevalence among residents living in nursing homes and its association with quality of life and well-being. Scandinavian Journal of Caring Sciences, 35(4), 1332–1341. https://doi.org/10.1111/scs.12955.CrossRefPubMed
Zurück zum Zitat Spangler, D., Blomqvist, P., Lindberg, Y., & Winblad, U. (2019). Small is beautiful? Explaining resident satisfaction in Swedish nursing home care. BMC Health Serv Res, 19(1), 886. https://doi.org/10.1186/s12913-019-4694-9.CrossRefPubMedPubMedCentral
Zurück zum Zitat United Nations Department of Economic and Social Affairs (2019). World population ageing 2019 (highlights) U. Nations. https://www.un.org/en/development/desa/population/publications/pdf/ageing/WorldPopulationAgeing2019-Highlights.pdf
Zurück zum Zitat Veal, F., Williams, M., Bereznicki, L., Cummings, E., Thompson, A., Peterson, G., & Winzenberg, T. (2018). Barriers to optimal pain management in aged care facilities: an Australian qualitative study. Pain Manag Nurs, 19(2), 177–185. https://doi.org/10.1016/j.pmn.2017.10.002.CrossRefPubMed
Zurück zum Zitat Wild, D., Grove, A., Martin, M., Eremenco, S., McElroy, S., Verjee-Lorenz, A., & Erikson, P. (2005). Principles of good practice for the translation and cultural adaptation process for patient-reported outcomes (PRO) measures: report of the ISPOR task force for translation and cultural adaptation. Value in Health, 8(2), 94–104. https://doi.org/10.1111/j.1524-4733.2005.04054.x.CrossRefPubMed
Zurück zum Zitat Williamson, A., & Hoggart, B. (2005). Pain: a review of three commonly used pain rating scales. J Clin Nurs, 14(7), 798–804. https://doi.org/10.1111/j.1365-2702.2005.01121.x.CrossRefPubMed
Zurück zum Zitat Wranker, L. S., Rennemark, M., & Berglund, J. (2016). Pain among older adults from a gender perspective: findings from the Swedish National Study on Aging and Care (SNAC-Blekinge). Scandinavian Journal of Public Health, 44(3), 258–263. https://doi.org/10.1177/1403494815618842.CrossRefPubMed
Zurück zum Zitat Zürcher, S., Vangelooven, C., Borter, N., Schnyder, D., & Hahn, S. (2016). Psychometric testing of the Italian and French care dependency scale in Swiss hospitals. J Adv Nurs, 72(12), 3207–3215. https://doi.org/10.1111/jan.13077.CrossRefPubMed