1Fresenius University, Germany
BACKGROUND: Treatment of patients receiving physiotherapy free of charge should aim at improving their participation in physical activity.
OBJECTIVES: This study aimed to examine physical activity participation among people with disability associated barriers.
METHODS: A cross-sectional survey was conducted of 2799 patients out of 10.596 potential patients with congenital or neurological diseases and sequela from accidents or rheumatism receiving physiotherapy free of charge. Patients were nested within 62 physiotherapists. The sample was selected at random from a pool of 1022 licensed physiotherapist in the Region of Southern Denmark in 2009. The response rate was 26.9% (n = 753). Information was collected on patients’ weekly hours of physical activity, on the external and internal perceived and environmental barriers, social support, self-efficacy, fatigue, pain, and disease duration. Data were analysed with multivariate interval and logistic regression techniques, respectively.
RESULTS: For the available sample (n = 753), the median value for the WHPA was 2–3 hours/week and 27.8% of the respondents were active for three hours or more per week. No statistically significant differences in the WHPA by categories of illness were observed. Internal perceived personal barriers were associated with physical activity, (95% CI -0.21, -0.06) among patients with neurological diseases and accidents or rheumatism,(95% CI -0.25, -0.08), respectively. Self-efficacy was associated with physical activity participation among participants with accidents or rheumatism, (95% CI 0.11, 0.10) For patients with sequela from accidents or rheumatism, a high level of perceived barriers predicted a low participation. The difference in the WHPA between respondents reporting eight perceived barriers (the 25th percentile) and respondents reporting 16 perceived barriers (the 75th percentile) was (95% CI -0.99, -0.34) after holding the other variables constant. This corresponded to 2–3 hours/week and 3–4 hours/week, respectively. Physical activity participation decreased with each year since diagnosis. For respondents with neurological diseases for example, being diagnosed at least 15 years prior to the time of this survey was statistically significantly associated with a lower odds of being active at least 150 min/week, (95% CI 0.2, 0.9) compared to respondents who had received their diagnosis more recently.
CONCLUSION: Promoting physical activity participation is important for patients with chronic illnesses. Patients receiving long-term physiotherapy may be less inclined to participate in physical activity beyond the activities included in their treatment. Physiotherapists should address patients’ concerns about obstacles to physical activity, aim to improve patient self-efficacy and assist in identifying concrete and tailored community-based physical activities. Fatigue, pain, and social support may be less important factors to focus on in promoting physical activity participation.
Keywords: barriers, chronic illness, physical activity participation, physiotherapy free of charge, interval regression
Chronic illness and its associated disability is increasing globally. Currently, some 16% of the population in Europe aged 16 to 64 years old is living with a disability, among whom 3.4% report having a severe disability (WHO, 2011). The benefits of regular physical activity are well known and a recommended level of 150 – 300 minutes of moderate-intensity aerobic physical activity throughout the week, or an equivalent combination of moderate- and vigorous-intensity activity, apply to healthy people as well as to patients with chronic conditions and disabilities (Bull et al., 2020; “WHO Guidelines Approved by the Guidelines Review Committee,” 2010). According to the recommendations, everyone should also do muscle-strengthening activities involving major muscle groups on two or more days a week. Furthermore, regular physical activity can improve the quality of life and reduce the risk of a loss of function (Kim et al., 2019). Thus, promoting physical activity is an integral part of the multidisciplinary management of inactive patients in several countries, including patients with disabilities (Horstink et al., 2006; Kim et al., 2019; Paltamaa et al., 2007). Prescription of physical activity by the patients’ General Practitioner (GP) is a widely used tool for promotion of activity among patients, and are conducted in Canada, New Zeeland, UK and throughout the Nordic countries. Notably, prescription of physical activity to patients in Sweden for example, is not only confined to GPs but include all licensed health professionals including physiotherapist, occupational therapists and nurses (Folkhälsomyndigheten, 2023). Prescriptions are based on patient-centered counseling and knowledge about physical activities evidently appropriate for the patient’s diagnosis. The prescribing health professional collaborate with actors in the local community to help patients’ improve their activity level (Kallings et al., 2008). Physical activity on prescription in Sweden was initiated in 2001 and is now an integral part of the Swedish public health system. Other Nordic countries have developed models similar to the Swedish approach, including Finland, Iceland, Denmark and Norway (Kallings, 2016). Between the countries, differences exist in terms of the intensity of the interventions, the level and scope of collaboration with local actors and interventions can be individually or group oriented. Models in Denmark, Finland, Sweden, and Norway have been evaluated and seems to improve the level of physical activity of the patients. Most important for the present paper is, that evidence indicates that the models are equally effective in promoting physical activity compared to physiotherapy-lead group training sessions 2-3 times weekly for 3-4 month (Leijon et al., 2008). Recognizing the importance and feasibility of the Swedish model, 10 member states of the European Union are now investigating the possibilities to implement the model into their national health care systems (EUPAP European Physical Activity on Prescription, 2023). Along this line of dissemination, the World Health Organization recently published a Toolkit for health professionals to aide in the physical activity assessment and counselling of inactive patients – including patients with chronic illness and disabilities (WHO, 2021). Based on a 5-step approach, health professionals address patient’s barriers to physical activity to promote a higher level of physical activity. Importantly, the toolkit advocates for a shared decision-making and recognizes that the activities to be adopted by the patient should be evaluated in terms of their enjoyability and practicality. Some barriers to physical activity participation are mentioned in the toolkit and centers around the patients’ personal barriers and to some extend barriers stemming from the near social network. Barriers from the patients’ broader social network and from the environmental surroundings are not addressed.
Barriers to physical activity among patients with disability include personal psychological factors, such as motivation and self-efficacy, disease-specific barriers, such as fatigue and pain, barriers from the patients’ near social network and environmental barriers, including transportation and accessibility (Martin Ginis et al., 2016; van der Ploeg et al., 2004). Although some barriers to participation may be common across chronic diseases and associated disabilities, the salience and the interplay between the barriers tend to be contingent on the context in which disabled patients perceive them. Thus, the perceived environmental barriers reported by patients in the USA (Damush et al., 2007; Kolkka & Williams, 1997), UK (Borkoles et al., 2008; Phillips et al., 2009), the Netherlands (Vissers et al., 2008) and Australia (Stroud et al., 2009) may be very different from the perceived barriers reported by patients with disabilities living in other cultural-specific contexts. Furthermore, much of the research on the barriers to physical activity is specific to distinct diseases (e.g. spinal cord injury (Barclay et al., 2016), multiple sclerosis (Borkoles et al., 2008), stroke (Damush et al., 2007) and acquired brain injury (Mulligan et al., 2012)). Research is rarer on the barriers to physical activity in several disease-specific groups of patients receiving continuous treatment. Local and general knowledge of the barriers to physical activity can enable health professionals to address patients’ obstacles to activity. Consequently, the dual purpose of this study was to estimate the level of physical activity and to examine the associations between barriers and level of physical activity among chronically ill patients living in Denmark who receive physiotherapy free of charge (hereafter: “patients”). To this end, a survey of three groups of patients with chronic diseases was conducted, all receiving physiotherapy free of charge within the Region of Southern Denmark. The randomly selected sample consisted of 2799 patients from 62 physiotherapists, across 23 municipalities.
2 Materials and Methods
2.1 Participants and procedures
The sample for the present study consisted of patients with chronic disabilities living in Denmark. In Denmark, general practitioners refer patients eligible to receive physiotherapy free of charge if they fulfil certain diagnostic criteria. The criteria and demographic characteristics of the patients have been described elsewhere (Næss-Schmidt. E T et al., 2020). The diseases that qualify for this service include congenital diseases, acquired neurological diseases and functional sequela caused by accidents or rheumatic diseases (Næss-Schmidt. E T et al., 2020). The objectives of the free-of-charge physiotherapy is to improve or maintain patients’ functions, or to delay the deterioration of functions in adults with a permanent severe physical disability. Patients are entitled to 80 free physiotherapy treatment sessions per year conducted by a licensed physiotherapist in private primary care. The regional administration within the five Regions in Denmark administer the reimbursements and all physiotherapists are assigned a unique license number.
A proportional difference of 15% between individuals with and without barriers was expected from previous reports in this field (Borkoles et al., 2008; Phillips et al., 2009; Vissers et al., 2008). A preliminary sample size estimation yielded a need for 330 individuals to take part in the study analysis to illustrate a difference of this magnitude. To enable the investigation of the differences in the reported barriers to physical activity among the disease groups, it was determined that a sample size of 1980 individuals was needed. Compensating for an expected non-response rate of 30%, the final sample consisted of 2772 individuals. For the present study, the sampling universe consisted of all patients receiving the service in the Region of Southern Denmark. The regional administration provided a list of all eligible patients. The latest counting of patients was from 2009, with 10,560 patients distributed among 1022 physiotherapists in 23 municipalities. Of the 10,560 patients, 2799 were selected at random for the present study. The patients were nested within 62 physiotherapists, across 23 municipalities. Due to the uneven distributions of patients among the physiotherapists, the patients were sampled in an iterative scheme in which one physiotherapist per iteration was sampled until the target number of patients was met. The remaining physiotherapists in a given iteration were assigned a sampling probability corresponding to their number of patients. This scheme ensured a random sampling among all patients, taken any ties into accounts. As the addresses of the selected patients were unknown, the selected participants were invited through the physiotherapist from whom they received treatment in 2009. A cover letter accompanied the study questionnaire (more detail on the questionnaire is given below) explaining the purpose of the study and that all participation in the study was voluntary. In addition, the letter stated that informed consent was considered confirmed by completing the questionnaire. The cover letter explained that withdrawal of the questionnaire once completed and returned was not possible, due to the lack of any data that would permit personal identification to return the questionnaire. Finally, the letter included the contact details of the author of this study and an invitation to make contact if there was a need to clarify any issues (none did so).
No information on the patients address, phone number or email address was available or obtained in the questionnaire. Only the physiotherapists were contacted and asked to assist in the collection of data. For these reasons, all the data were anonymous and formal ethical approval was not mandatory. However, prior to data collection, the Association of Danish Physiotherapists and the Region of Southern Denmark approved the study.
2.1.4 Data collection
Researchers from the University of Southern Denmark and representatives from the Association of Danish Physiotherapists developed a 72-item (closed ended) questionnaire for the present study. Measures of perceived personal barriers, environmental barriers, self-efficacy and social support were partly adopted from the work of van der Ploeg (van der Ploeg et al., 2004) and the International Classification of Functioning, Disability and Health Model (ICF) (WHO, 2001) and modified for the present study. The appropriateness of selected items for measures of perceived personal barriers, environmental barriers, self-efficacy and social support were discussed until agreement was reached. A pilot test was conducted in February 2012, which included 15 patients receiving treatment from a physiotherapist in a clinic that was not part of this study. Additionally, three detailed interviews were conducted and suggestions for improvement and corrections were incorporated in the final version of the questionnaire. In April 2012, a letter was sent to the 62 selected physiotherapists in 23 municipalities asking for their assistance to distribute and collect questionnaires among their patients, followed by two written reminders in July and August. Physiotherapists who did not return any questionnaires were contacted twice by telephone to prompt them to do so. The data collection was concluded in October 2012. Of the 2799 patients potentially eligible for this study, 753 responded, which correspond to a response rate of 26.9%.
The self-reported weekly hours of physical activity (WHPA) was measured by the question: “How many hours per week do you exercise to the extent where you are warm and out of breath?” The response categories were: “Less than an hour per week”, “1–2 hours per week”, “2–3 hours per week”, “3–4 hours per week”, “4–5 hours per week” and “more than 5 hours per week.” The validity and reliability of seven days recall of physical activity have previously been found to be acceptable but there is a tendency to underestimate the objectively obtained measures of energy expenditure (Dowd et al., 2018). The responses for the WHPA were dichotomised into a new variable named the “recommended level of physical activity (PA),” indicating 2 hours/week or more (coded 1, 0, otherwise). Three hours per week corresponds roughly to the international guideline for the recommended time adults should spend on physical activity – including adults with disabilities (Bull et al., 2020; “WHO Guidelines Approved by the Guidelines Review Committee,” 2010). Both measures, WHPA and PA, were used in the present paper as WHPA indicate the actual weekly hours of physical activity and PA indicate the proportion of respondents with a level of activity roughly above or below the recommended level.
2.2.2 Main exposures
Two measures of perceived personal barriers were constructed based on the nine items presented to the patients. This decision was based on a preliminary factor analysis that revealed a two-factor solution (results not shown). The items: “How often do you lack time to be physically active?”, “How often do duties in your work prevent you from being physically active?”, “How often do family demands refrain you from being physically active?” and “How often do you refrain from being physically active because you feel you must put your family’s needs before your own?”, were selected for the measure External perceived personal barriers. The measure of Internal perceived personal barriers was constructed from a summation of the responses to the questions: “How often does your health prevent you from being physically active?”, “How often do you lack motivation to be physically active?”, “How often do you lack the energy to be physically active?”, and “How often does pain refrain you from being physically active?”. The question: “How often does your weight keep you from being physically active?”, was not related to either of the two identified factors and was consequently omitted. The response options covered five categories ranging from “never” (coded 1) to “very often” (coded 5). The Cronbach alpha was 0.80 for the measure of External perceived personal barriers. All four items were summed into a continuous scale ranging from 0 to 15, after subtraction of the lowest value. The Cronbach alpha was 0.79 for the measure of Internal perceived personal barriers. Four items were summed into a continuous scale ranging from 0 to 16, after subtraction of the lowest value.
The environmental barriers consisted of nine items, such as “How often do you refrain from being physically active because of a lack of transportation?”. The response categories ranged from “never” to “very often”. The Cronbach alpha was 0.85. I constructed a composite score with a range between 0 and 26.
The measures of self-efficacy consisted of eight items with a 1 to 4 response format, ranging from “not confident at all” to “always confident”. An example of an item included in the self-efficacy measure is: “How confident are you that you can be physically active even though you have many other chores to attend to at home?”. The Cronbach alpha was 0.9. The summation of all the items ranged between 0 and 24. The composite variables “External” and “Internal perceived personal barriers”, “Environmental barriers” and “Self-efficacy”, respectively, were categorised into three groups of approximately equal size. The first category indicated a “low” level of perceived personal barriers (External or Internal, environmental barriers or self-efficacy, respectively), while the second category indicated a “medium” level and the third category indicated a “high” level of barriers. Instrumental social support was measured with eight questions. An example of one of the questions is: “How often does your partner encourage you to be physically active?”. The response categories were “never” to “very often”. The Cronbach alpha was 0.87. A variable covering three categories (low, middle and high support) of approximately equal size was constructed after rescaling and summation. The measures of external and internal perceived personal barriers, environmental barriers, self-efficacy and social support were used as continuous measures with the WHPA as the outcome and as categorical indicators in the logistic regression analyses. The internal consistency, construct validity and reliability of the included measures of external and internal perceived personal barriers, self-efficacy and social support were found to be acceptable, except for the measure for the environmental barriers (van der Ploeg et al., 2009).
Respondents reported their age, gender and the year they received their diagnosis (year of birth for congenital diseases). The responses for the years since diagnosis were categorised into “less than 10 years”, “10 to 14 years” and “15 years or more”. The influence of fatigue within the past four weeks was measured by responses to the items “How much influence has fatigue had on your daily life?” and “How much influence has fatigue had on your relationship to others?”. The responses were recorded on visual analogue scales, with 0 indicating “no influence” and 9 indicating “a lot of influence”. The measure was partly adopted from Kos et al. (Kos et al., 2006) and is moderately reliable and valid. Information about the severity and interference from pain within the past four weeks was obtained through the following two questions selected from the Medical Outcomes Study Pain Measures (Stewart et al., 1992): (1) “How much bodily pain have you generally had during the past 4 weeks?”, with the response format ranging from “none“(coded 0) to “very severe” (coded 5) and (2) “During the past 4 weeks, how much did pain interfere with your normal work (including both work outside the home and housework)?”, with the response categories going from “not at all” (coded 0) to “extremely” (coded 4). A composite score of pain was constructed by calculating the average of the sum of the responses to both items, and then subtracting the minimum value. The selected pain items have been widely used in large-scale population-based surveys in Denmark (Breinholt-Larsen et al., 2011).
2.2.4 Statistical analyses
The mean and proportional distributions by categories of chronic illness were calculated by analysis of variance and cross-tabulations, including Pearson’s χ2. Pearson’s r was calculated to investigate the bivariate correlation between the outcome and the main exposure variables (external and internal perceived personal barriers, environmental barriers, self-efficacy and social support). Following the conceptual model by van Ploeg et al. (van der Ploeg et al., 2004), all the main exposure variables were simultaneously included in the multivariate analysis and adjusted for the relevant covariates. Interval regression analysis was conducted with the WHPA as the main outcome measure, including all the main exposure variables as continuous variables. Also, McFadden’s adjusted R2 was calculated to evaluate the proportion of the explained variance of the WHPA by the model. Since the measures of internal perceived personal barriers and self-efficacy are theoretically and statistically associated, I used Akaike information criterion (AIC) model selection to distinguish among models containing both exposure variables and models without one of the variables. Models with the lowest AIC value were selected and the results are reported here. Logistic regression was used for the analysis, including physical activity (PA) as the outcome measure and the main exposures as the categorical variables. The WHPA and PA were analysed separately for three groups of illnesses (congenital, neurological, and accident and rheumatism, respectively). The alpha level was set to 0.05 for all the analyses. Stata version 14 was used for all the analyses (StataCorp., 2015).
In total, 753 patients responded to the questionnaire, but many did not answer all questions. Hence, the number of respondents available for the various analysis varies considerably. Neurological diseases were the most frequent type of illness (54.1 %), followed by accidents and rheumatism (33.5 %) and congenital diseases (12.4 %). A large majority of the sample consisted of women (68.4 %), and the mean age was 60.5 years old, SD = 13.4 (Table 1).
Table 1 Characteristics of the sample (n=753). Mean, percentage and 95% confidence interval.
|Congenital diagnoses||72||12.4||[9.7, 15.1]|
|Neurological diagnoses||313||54.1||[49.9, 58.1]|
|Accidents and rheumatism||194||33.5||[29.6, 37.3]|
|Weekly Hours of Physical Activity||607|
|<1 hour/week||130||21.4||[18.1, 24.7|
|1–2 hours/week||165||27.2||[23.6, 30.7]|
|2–3 hours/week||143||23.6||[20.2, 26.9]|
|3–4 hours/week||81||13.3||[10.6, 16.1]|
|4–5 hours/week||44||7.2||[5.1, 9.3]|
|>6 hours/week||44||7.2||[5.1, 9.3]|
|Less than 2 hours/week||295||48.6||[44.6, 52.6]|
|More than 2 hours/week||312||51.4||[47.4, 55.3]|
|External perceived personal barriers||588||3.6||[3.4, 3.8]|
|Internal perceived personal barriers||605||7.3||[7.1, 7.6]|
|Environmental Barriers||592||3.1||[2.8, 3.4]|
|Social Support||566||16.4||[15.9, 17.0]|
|Gender – Female||753||68.4||[65.0, 71.7]|
|Years Since Diagnosis||581||14.0||[13.0, 15.0]|
|<10 years||270||46.8||[42.4, 50.5]|
|10–14 years||122||21.0||[17.7, 24.3]|
For the total sample, the median value for the WHPA was 2–3 hours/week and 51.4% of the respondents were active for two hours or more per week. No statistically significant differences in the WHPA by categories of illness were observed, χ2 (10, N = 557) = 14.7, p = .14). The respondents with neurological diseases reported a statistically significantly higher level of social support, M = 17.07, SD = 6.85, 95% CI [16.3, 17.8] compared to congenital diagnoses, M = 15.30, SD = 6.91, 95% CI [13.7, 16.9] and accidents and rheumatism, M = 15.57, SD = 6.00, 95% CI [14.6, 16.6], F(2, 525) = 3.78, p = .02, respectively. No differences by illness were observed in the distribution of the other main predictors (external and internal perceived personal barriers, environmental barriers, and self-efficacy). The mean number of years since diagnosis for respondents with congenital diseases was 26.3 years, 95% CI [23.6, 29.1], while it was 10.7 years for the respondents with neurological diseases, 95% CI [9.4, 11.9] and 14.8 years for the respondents with accidents and rheumatism, 95% CI [13.3, 16.5], F(2, 536) = 52.92, p < .001), respectively. The results of the bivariate analysis showed that the internal perceived personal barriers, r(402) = -.35, p < .001, environmental barriers, r(505) = -.16, p < .001 and self-efficacy, r(546) = .32, p < .001 correlated with the WHPA. However, external perceived personal barriers, social support, pain, fatigue and all potential covariates did not correlate with the WHPA and were omitted from the subsequent multivariate analysis (table 2). Additionally, I observed a correlation between the internal perceived personal barriers and the environmental barriers, r(574) = .25, p < = .001 and self-efficacy, r(556) = .47, p < .001. As collinearity between these variables could affect the calculation of the individual predictors in the subsequent multivariate analysis, the analysis included multivariate models with and without these measures.
In the multivariate models for patients with congenital diagnosis, none of the included measures reached statistical significance, although the environmental barriers were marginally associated, b = -0.09, 95% CI [-0.24, 0.07], p =.05 as was self-efficacy, b = -0.07, 95% CI [ -0.01, 0.14], p = .09 (Table 2). The model explained 2% of the variance of the WHPA. For respondents reporting neurological diagnoses, the internal perceived personal barriers were significantly associated with WHPA, b = -0.13, 95% [CI -0.21, -0.06, p < .001. Again, the association between self-efficacy and WHPA marginally failed to reach statistical significance, p = .06. The years since being diagnosed with a neurological disease was also associated with WHPA, b = -0.03, 95% CI [-0.05, -0.01], p = 0.01. For each year with a neurological disease, the WHPA decreased. The model explained 3% of the variance. The model including both the internal perceived personal barriers and self-efficacy fitted the data best, AIC = 908.35. For the model investigating the influences of the various factors on the WHPA among respondents in the accidents and rheumatism category, it was found that the internal perceived personal barriers were significantly associated with WHPA, b = -0.17, 95% CI [ -0.25, -0.08], p < .001. Thus, the difference in the WHPA between respondents reporting eight perceived barriers (the 25th percentile) and respondents reporting 16 perceived barriers (the 75th percentile) was -0.66, 95% CI [ -0.99, -0.34], p < .001, after holding the other variables constant. This corresponded to 2–3 hours/week and 3–4 hours/week, respectively. Also, self-efficacy was significantly associated with WHPA, b = 0.06, 95% CI [ 0.11, 0.10], p = .01. The percentage of the explained variance of the WHPA was 5%. The models including both the internal perceived personal barriers and self-efficacy fitted the data best, AIC = 542.95.
Table 2 Summary of the interval regression analysis of the Internal perceived personal barriers, Environmental barriers and Self-efficacy on the Weekly hours of physical activity (n = 432)
|Congenital diagnoses (n = 52)||Neurological diagnoses|
(n = 250)
|Accidents and rheumatism (n = 151)|
|b||95% CI||b||95% CI||b||95% CI|
|Internal percieved personal barriers||-0.08||[-0.23.5, 0.07]||-0.13***||[-0.21, -0.06]||-0.17***||[-0.25, -0.08]|
|Environmental barriers||-0.09||[-0.19, 0.01]||-0.01||[-0.01, 0.04]||-0.05||[-0.14, 0.03]|
|Self-efficacy||0.06||[0.01, 0.146||0.04||[-0.00, 0.07]||0.06**||[-0.2, 0.02]|
|Years since diagnosis||-0.01||[-0.03, 0.01]||-0.03**||[-0.05, -0.01]||-0.00||[-0.02, 0.02]|
|Constant||2.50*||[0.73, 4.4]||3.14***||[2.31, 3.40]||3.20***||[2.02, 4.39]|
|McFadden’s Adjusted R2||.02||.03||.08|
*) p < .05, **) p < .01, ***) p < .001.
In logistic regression models investigating the odds of being physically active for more than 2 hours/week, none of the included factors were observed to be statistically significantly associated with PA among the respondents with congenital diseases, although a high level of self-efficacy was observed marginally significant associated, OR = 5.3, 95% CI [0.9, 29.8], p =.06. However, a duration of 15 years or more since diagnosis was statistically significantly associated with lower odds of achieving the recommended level of PA, OR = 0.2, 95% CI [0.0, 0.8], p = .01 (Table 3). Compared to the model including both internal perceive personal barriers and self-efficacy, the model including self-efficacy only fitted the data best, AIC = 77.36. For the model investigating the respondents with neurological diseases, a high level of internal perceived personal barriers was statistically significantly associated with lower odds of reaching the recommended level of activity, OR = 0.4, 95% CI [0.13, 0.94], p = .03. The probability of reporting the recommended level of physical activity was 19% lower among patients reporting a high-level vs low-level of internal perceived personal barriers, 95% CI [-0.33, -0.39], p =.01. Being diagnosed at least 15 years ago was statistically significantly associated with a lower odds of reaching the recommended level of activity, OR = 0.4, 95% CI [0.2, 0.9], p = .04, compared to respondents who had received their diagnosis more recently.
For respondents in the accident and rheumatism category, a high level of internal perceived personal barriers was associated with lower odds of being physically active for more than 2 hours/week, OR = 0.3, 95% CI [0.1, 0.8], p = .01. The probability of reporting the recommended level of physical activity was 41% lower among patients reporting a high-level vs low-level of internal perceived personal barriers, 95% CI [-0.60, -0.23], p < .001). Respondents reporting a high level of self-efficacy were three times more likely to reach the recommended level of PA, compared to respondents reporting a low level of self-efficacy, OR = 3.3, 95% CI [1.0, 10.4], p =.04, when holding the other variables in the model constant. The difference expressed in probability was 24%, 95% CI [.02, .45], p = .03. The lowest AIC was observed in the models including both the internal perceived personal barriers and self-efficacy simultaneously, irrespective of the category of chronically illness.
Table 3 Odds ratio (OR) and 95% confidence interval (CI) of the Internal perceived personal barriers, Environmental barriers and Self-efficacy for the Recommended level of physical activity (n = 385)
|Congenital diagnoses (n = 53)||Neurological diagnoses|
(n = 205)
|Accidents and rheumatism (n =128)|
|OR||95% CI||OR||95% CI||OR||95% CI|
| Internal perceived personal|
|Medium||–||0.7||[0.4, 1.4]||0.3*||[0.1, 0.8]|
|High||–||0.4*||[0.1, 0.9]||0.1*||[0.0, 0.4]|
|Environmental Barriers Low||Ref||–||Ref||–||Ref||–|
|Medium||1.0||[0.2, 4.9]||1.4||[0.7, 2.8]||0.3*||[0.1, 0.8]|
|High||0.2||[0.0, 1.1]||1.3||[0.6, 2.8]||0.4||[0.1, 1.0]|
|Medium||0.8||[0.2, 4.0]||1.8||[0.9, 3.7]||2.2||[0.8, 6.5]|
|High||5.3||[0.9, 29.8]||2.1*||[1.0, 4.5]||3.3*||[1.1, 10.4]|
|Years Since Diagnosis <10||Ref||–||Ref||–||Ref||–|
|10–14 years||0.5||[0.1, 3.8]||0.7||[0.3, 1.4]||1.0||[0.3, 3.1]|
|>15 years||0.2*||[0.0, 0.8]||0.5*||[0.2, 1.0]||0.9||[0.4, 2.2]|
|Constant||2.8||[0.5, 15.0]||0.4*||[0.2, 0.8]||1.2||[0.3, 4.2]|
|Akaike Information Criterion||77.36||309.87||565.29|
*) p < .05, **) p < .01, ***) p < .001.
Research into the barriers to physical activity among persons with chronic diseases is essential for health professionals for advising patients about improvement in physical activity. Yet research to date into the barriers to physical activity has produced a fragmented body of literature, with some studies showing an association between almost all functions and disability domains in the ICF model and others showing associations between only a few of the ICF-model domains (Martin Ginis et al., 2021; Newitt et al., 2016; Veldhuijzen van Zanten et al., 2015). The purpose of the present article was to explore the influence of the barriers in various domains of the ICF framework on physical activity among patients with chronic diseases receiving physiotherapy free of charge. The results showed that some but not all of the domains of the ICF model influence physical activity among the patients. For example, neither gender, pain, fatigue nor social support were associated with the respondents’ level of activity for any of the disease categories included.
A low proportion (28%) of respondents reported a level of physical activity corresponding to 3 hours or more per week. This is in accord with the results from several other studies (Damush et al., 2007; de Hollander & Proper, 2018; Mulligan et al., 2012). In contrast, 74% of the general population report adherence to the recommended level of physical activity in a national representative survey conducted around the time of the present study (Breinholt-Larsen et al., 2011). Although speculative, patients receiving long-term physiotherapy may be less inclined to participate in physical activity beyond the activity specifically included in their treatment. Research on patient’s dependency on treatment is rare but points to a poor or deteriorating clarity of treatment goals over time as a possible reason for a patient’s reluctance to finalise their treatment (Geurtzen et al., 2020). The data collected for this study does not include measures of a patient’s dependency on treatment. However, since the average years since being diagnosed exceeds 10 years and free-of-charge physiotherapy is initiated within the first two years since diagnosis (Næss-Schmidt. E et al., 2020), patients may find the original goals of the treatment become unclear. This in turn may cause the service to become a substitute for other physical activities outside the physiotherapy clinics. Future evaluations of this public financed healthcare option should address this issue in detail.
The association between self-efficacy and WHPA across categories of chronical illness was unclear, with small effect sizes and marginal levels of statistical significance. Self-efficacy was found to be associated with WHPA for the accidents and rheumatism-category only. These results are in contrasting with those of other studies that have suggested an association exists between self-efficacy and physical activity (Casey et al., 2017; Jong et al., 2004; Martinez-Calderon et al., 2018; Neuberger et al., 2007), in which goal-setting has been suggested as the most important aspect of self-efficacy (Newitt et al., 2016). In contrast to the observed lack of an association between WHPA and self-efficacy, internal perceived personal barriers was associated with WHPA across the categories of chronical illness from neurological diseases and accidents and rheumatism. The measures of self-efficacy and internal perceived personal barriers are theoretically and statistically two different concepts, although related. Perceived personal barriers are the obstacles or challenges that the patient believes are standing in the way of achieving a particular goal. These barriers could be internal or external. Self-efficacy is the individual’s belief in their own ability to overcome those obstacles. The interchangeable associations with WHPA and internal perceived personal barriers and self-efficacy observed here, may stem from a confusion of the two concepts. The individual-based promotion of sustainable, high-intensity physical activity among persons with chronic diseases has intensified in recent years, and physiotherapists are encouraged to more actively discuss the potential benefits of activity outside the clinic with their patients (Pedersen & Andersen, 2018). However, if a patient’s lack of belief in their own ability to overcome the barriers to be more active is ignored, or the perceived barriers are not addressed, a rigorous focus on the preventive benefits of physical activity as a sole motivator would most likely not be perceived as relevant by the patient and could lead to further disbelief and abstinence from activity. Hence, addressing the patient’s perceived barriers and his/her ability to overcome these obstacles may be an important factor that should be included as part of the treatment when promoting physical activity (Sangelaji et al., 2016). Indeed, some evidence suggest that physiotherapists do acknowledge the importance of for example self-efficacy parallel to the importance of bodily functions when interacting with patients with chronical diseases (Shields et al., 2021). Similarly, providing the patient with concrete information about tailored physical activities in the local community would be useful strategies to enhance physical activity promotion to patients with chronical illness (West et al., 2021).
Surprisingly, pain and fatigue were not associated with physical activity in this study sample. Consensus exists that individually tailored exercise is beneficial for patients suffering from fatigue (Razazian et al., 2020), although too intensive exercising may exaggerate symptoms. One possible explanation for the absent association of fatigue on PA is that the physiotherapists are aware of the beneficial effect of exercise as an effective means of reducing fatigue and are offering their patients exercise regimes specifically tailored to their individual needs, thereby avoiding overtraining. Alternatively, a sampling bias could also explain this result, in that the study sample may represent a healthy sub-group of patients. In fact, Næss-Schmidt et al. (2020) described the demographics of patients receiving free-of-charge physiotherapy using data on all residents in Denmark registered with their primary ICD10 diagnosis and observed that 45% of the patients were prescribed free-of-charge physiotherapy within two years of diagnosis. The respondents with neurological diseases in the present study reported being diagnosed 10 years prior to the data collection. Hence, the results presented here suggest that those who chose to participate in the study may have been less affected by symptoms such as fatigue, compared to the general population of patients receiving free-of-charge physiotherapy.
Social support was not found to be associated with physical activity in the analysis. This finding corresponds to that of a recent review that concluded that the role of social support remains elusive (Casey et al., 2017). A possible explanation for the lack of social support as a predictor of physical activity is that the measure of social support included in the present study was specifically designed to cover instrumental support from the near social environment of the respondents that would support and enable them to be physically active. The importance of social support, however, depends on the situational context (Maisel & Gable, 2009; Sarason et al., 1991) and patients receiving free-of-charge physiotherapy may not regard their lack of physical activity as stressful enough to catalyse a need for social support. Though validated measures of social support do exist, those that are used in research into engagement in physical activity among persons with chronic diseases often focus on emotional support, which in turn may explain the unclear relationship with physical activity among people with disabilities observed across a range of studies (Casey et al., 2017). By limiting the measurement of social support to the instrumental dimension of the construct, references to emotional support were avoided in the present study.
4.1 Strengths and weaknesses of the present study
The present study is one of a few studies investigating the barriers to physical activity among patients with various chronic diseases and levels of disability who are all receiving free-of-charge physiotherapy. A recent study by Næss-Schmidt et al. (2020) on a sample from the same study population as the present study investigated the personal activities, and social and emotional barriers (Næss-Schmidt. E et al., 2020). The present study extends the results from Næss-Schmidt et al. (2020) by providing information about the specific barriers for physical activity among the patients. Specifically, the present study offers further insights into the importance of pain, self-efficacy and social support to physical activity. A further strength is the use of more specific measures of physical activity, enabling quantification of the levels of activity.
The limitations of this study include the modest response rate of 26.9%, which may indicate a risk of selection bias. Comparing the distribution of patients in the sample with information from the national health register on all patients receiving free-of-charge physiotherapy, however, did not reveal any major deviations in terms of gender or age. Conversely, since the level of disability among patients is probably evenly distributed among primary care physiotherapists, any selection bias would most likely be non-differential and would tend to dilute the associations between the barriers and physical activity reported by the participants. A second limitation pertains to the methods used for the data collection. The physiotherapists were required to distribute, collect and return the questionnaires filled out by their patients. In fact, 84% of the selected physiotherapists did return some questionnaires. Although preliminary investigations in the planning of the study suggested that the patients would be interested in participation in the study, only a minor proportion of patients actually responded to the questionnaire, and those that did only answered part of the questions. However, it must also be considered that the treatments of the study patients were similar to those of other patients who were not eligible for free-of-charge physiotherapy and if the physiotherapist was unaware of their status, eligible patients may not have received a questionnaire. Future studies should explore better and more direct ways to reach the patients. Third, the theoretical model used in the present study may be inadequate. Although the theoretical framework was closely aligned to the ICF model (WHO, 2001), and has been used in a number of other studies (de Hollander & Proper, 2018; Loef et al., 2016; Outermans et al., 2016; van Adrichem et al., 2016), some doubts about the applicability of the model when utilised on a diverse sample of persons have been voiced in terms of its ability to capture disease-specific variations of the barriers to physical activity (Karhula et al., 2013; Newitt et al., 2016). Future studies should investigate the validity of the model on various patients with diverse chronic diseases.
I would like to acknowledge with gratitude the effort and engagement of the physiotherapists who assisted with the collection of data, and the willingness of their patients to participate. Also, thanks to Professor Bjarne Ibsen at the University of southern Denmark, and to the late Associate Professor Ejgil Jespersen who both were responsible for the conceptualization of the study.
6. Declaration of Interest
I declare there were no conflicts of interest in conducting and reporting on this study.
7. Funding : The Bevica Foundation. The funding identification number no longer exists.
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