Skip to main content
  • Research article
  • Open access
  • Published:

Perceived acceptability and preferences for low-intensity early activity interventions of older hospitalized medical patients exposed to bed rest: a cross sectional study

Abstract

Background

Hospitalized older patients spend most of their time in bed, putting them at risk of experiencing orthostatic intolerance. Returning persons to their usual upright activity level is the most effective way to prevent orthostatic intolerance but some older patients have limited activity tolerance, supporting the need for low-intensity activity interventions. Consistent with current emphasis on patient engagement in intervention design and evaluation, this study explored older hospitalized patients’ perceived acceptability of, and preference for, two low-intensity early activity interventions (bed-to-sitting and sitting-to-walking), and characteristics (gender, illness severity, comorbidity, illnesses and medications with orthostatic effects, and baseline functional capacity) associated with perceived acceptability and preference.

Methods

A convenience sample was recruited from in-patient medical units of two hospitals in Ontario, Canada and included 60 cognitively intact adults aged 65+ who were admitted for a medical condition within the past 72 h, spent ≥ 24 consecutive hours on a stretcher or in bed, presented with ≥ 2 chronic diseases, understood English, and were able to ambulate before admission. A cross-sectional observational design was used. Participants were presented written and oral descriptions and a 2-min video of each intervention. The sequence of the interventions’ presention was randomized. Following the presentation, a research nurse administered measures of perceived acceptability and preference, and collected health and demographic data. Perceived acceptability and preference for the interventions were measured using the Treatment Acceptability and Preferences Scale. Illness severity was measured using the Modified Early Warning Score. Comorbidity was assessed with the Age Adjusted Charlson Comorbidity Scale and the Cumulative Illness Rating Scale – for Geriatrics. Baseline functional capacity was measured using the Duke Activity Status Index.

Results

Participants’ perceived acceptability of both interventions clustered above the scale midpoint. Most preferred the sitting-to-walking intervention (n = 26; 43.3%). While none of the patient characteristics were associated with intervention acceptability, illness severity (odds ratio = 1.9, p = 0.04) and medications with orthostatic effects (odds ratio = 9.9, p = 0.03) were significantly associated with intervention preference.

Conclusions

The interventions examined in this study were found to be acceptable to older adults, supporting future research examining their feasibility and effectiveness.

Peer Review reports

Background

Since the 1950s, getting up out of bed, as a minimum practice, has been part of recommended daily hospital care [1]. Nevertheless, on admission to hospital, older patients (aged 65+) spend most of their time on stretchers in emergency departments or in beds on in-patient units [2, 3]. Studies have found older patients to spend between 71% and 83% of their time in hospital lying down [3,4,5], with up to 40% remaining in bed for at least 24 h [6,7,8]. This exposure has been identified as the starting point in a trajectory to bed rest dependency in those with multiple chronic conditions [9]. Bed rest dependency is characterized by a compulsion to return to bed soon after getting up, self-limited upright activity, and/or refusal to get up [9].

Acutely-ill older patients with multiple chronic conditions are particularly vulnerable to bed rest dependency because they tend to use rest as a strategy for managing symptoms, such as fatigue, associated with chronic illnesses [9]. Many (25% to 34%) older patients believe walking and other exercises are inappropriate during hospitalization [10, 11] and that they need to stay in bed during illness and focus on recuperating, not on walking [10]. Others view the hospital as a dangerous place and prefer to remain inactive [10, 11]. Just a few days of bed rest can lead to rapid functional decline and related complications in this population because their physiologic reserves are diminished [6, 12]. Bed rest has been associated with functional decline, institutionalization, and mortality in hospitalized older patients even after controlling for comorbidity and illness severity [6]. Consequently, preventing bed rest dependency, early in its trajectory, is critical.

Informed by the Medical Research Council’s framework for designing and evaluating interventions [13], we critically analyzed theoretical and empirical evidence to generate a comprehensive understanding of bed rest dependency. This conceptualization guided us in developing two interventions to promote activity during the early phase of hospitalization for older patients with multiple chronic conditions. We developed two distinct interventions because, based on prior research [10, 11], we anticipated that patients’ perspectives would vary on their perceived need for rest and the appropriateness of different types and levels of activity during hospitalization for acute illnesses.

In this paper, we describe our conceptualization of bed rest dependency, the two low-intensity early activity interventions, and, in keeping with the Medical Research Council’s framework’s emphasis on engaging patients in intervention design, we describe older hospitalized patients’ perceived acceptability of, and preference for, those interventions. Perceived acceptability refers to the desirability of interventions to potential users; it reflects the extent to which patients anticipate the interventions to be appropriate and effective in addressing bed rest dependency and related health problems, with minimal side effects or risks, and ease of use in hospital [14]. The Medical Research Council’s framework acknowledges that intervention evaluations are frequently challenged by problems around acceptability that limit feasibility [15]. Assessing perceived acceptability and preferences is increasingly acknowledged as essential in the design of healthcare interventions, prior to determining their effectiveness [15, 16]. Interventions perceived as acceptable and preferred are more likely to be used than those that are not. Consequently, prior to testing the effectiveness of the interventions, it is important to better understand patients’ perspectives on them.

Conceptualization of bed rest dependency

Adequate functioning of the cardiovascular system during physical activities such as walking is highly dependent on exposure to gravitational stress along the longitudinal axis of the body that normally accompanies an upright sitting or standing position [17]. During bed rest, the reclined position of a stretcher or bed furnishes a reduced gravitational environment along the longitudinal axis of the body to which the cardiovascular system quickly adapts (within two to four days) [17]. However, once bed rest has ended, the cardiovascular system has difficulty reversing this adaptation. Its compensatory mechanisms fail to adequately increase cardiac output and due to insufficient delivery of oxygen and nutrients to the tissues, the person experiences orthostatic intolerance [18]. Defined as reduced ability of the cardiovascular system to function effectively against gravitational stress, orthostatic intolerance is the hallmark of bed rest deconditioning and the most prominent determinant of self-limited upright activity after bed rest [19]. Orthostatic intolerance is manifested by symptoms of dizziness, tiredness, and weakness upon return to upright posture [20,21,22]. The severity of orthostatic intolerance is proportional to the duration of bed rest [23] and its recovery takes up to 3 times the duration of bed rest [24]. Symptoms (e.g. weakness, fatigue, dizziness) and fear of falling because of the symptoms are the reasons most frequently identified by patients and clinicians for older patients’ bed rest and reluctance to get up during acute care hospitalization [8, 11]. Avoiding the negative effects of bed rest, however, has been identified by older patients as a crucial factor in their motivation to engage in activity during hospitalization [11].

Based on this evidence, we developed a conceptualization of bed rest dependency which proposes that the amount of time spent lying down: (a) intensifies its negative effects on the cardiovascular system, and (b) perpetuates a cycle of bed rest dependency and functional decline, both of which in turn reinforce further bed rest dependency. Since the orthostatic effects are experienced when upright and relieved when recumbent, the dependency evolves from the person’s belief that resting in bed is the best way to manage the increasing symptoms and accompanying fears (e.g. falling and exacerbating health problems because of weakness and dizziness). This conceptualization supports the need to intervene early in the cycle by minimizing recumbency, promoting low-intensity activity facilitating vascular return, engaging patients in discussions about the negative effects of bed rest, preventing misconceptions about bed rest and motivating activity engagement.

Empirical basis for interventions to prevent bed rest dependency on medical units

Evidence derived from controlled trials in laboratory settings with young to middle-aged adults has established that early activity, in the form of returning persons to their usual upright activity level, is the most efficient and effective non-invasive way to prevent and rehabilitate orthostatic intolerance [24,25,26,27,28,29]. Early activity in the hospital setting delivered during the acute phase of an illness has been minimally evaluated as a single component intervention and its effect on orthostatic intolerance has not been examined in older patients with multiple chronic conditions admitted to medical units. Rather, early activity has often been embedded in a multi-component program implemented in Acute Care for Elders (ACE) units, which has demonstrated effectiveness in reducing older patients’ functional decline and related outcomes [30].

Although studies that evaluated the ACE program did not isolate and test the unique contribution of early activity to outcome achievement, some studies which attempted to do so demonstrated poor feasibility because of patient refusal to participate [31, 32]. Brown reported a drop-out rate of 90% in an early activity program, consisting of progressive ambulation and transfer and resistance training, because it was viewed by older medical patients as too physically demanding [31]. Low-intensity early activity, consisting of walking, demonstrated better feasibility in older medical patients, but the studies included few women (≤ 3%), reported only moderate adherence because of refusals to walk and poor tolerance in some patients, and did not examine patients’ perceptions of the interventions [33, 34]. Older patients’ perceptions of early activity may vary with their gender [35, 36], illness severity [37], comorbidities [38], medications [39] and pre-hospital baseline functional capacity [4], but studies have not explored the influence of these characteristics on hospitalized older patients’ perceptions of early activity.

Taken together, prior research suggests the need to develop early activity interventions that can be used by patients who remain sedentary during hospitalization and are thus at risk of experiencing orthostatic intolerance when they resume ambulation. Yet, little is known about hospitalized older patients’ perceived acceptability of, and preferences for, early activity, which is essential to designing interventions to which patients will adhere [16, 40]. Consequently, consistent with our conceptualization and review of empirical evidence, we developed two low-intensity early activity interventions aimed at preventing orthostatic intolerance as well as consequent bed rest dependency and functional decline in older patients with multiple chronic conditions. The interventions are: 1) bed-to-sitting, and 2) sitting-to-walking (Table 1). The content of the interventions (i.e. the activities) was derived from studies that were predominantly conducted in laboratory settings. The bed-to-sitting-intervention was developed based on evidence suggesting that the orthostatic effects of bed rest can be mitigated through regular exposure to orthostatic stress (e.g. sitting upright with legs dependent) [28] and activation of the muscle venous pump of the legs (e.g. elevating legs, pointing toes) [41, 42]. The sitting-to-walking intervention was designed based on the same evidence, but its activities were more intensive (e.g. walking) with a stronger dose (e.g. being upright for at least 3.5 h in a 24-h period) based on prior evidence indicating that the orthostatic effects of bed rest are mitigated by conditions simulating upright posture for this duration [21, 26]. Both interventions included sitting at the bedside for up to 10 min prior to ambulating, consistent with time frames for the development of the symptoms of orthostatic intolerance [43].

Table 1 Descriptions of low-intensity early activity interventions

Study aims

The purpose of this study was to examine the acceptability of, and preferences for, the bed-to-sitting and sitting-to-walking interventions, as perceived by older patients with multiple chronic conditions admitted to medical units in acute care hospitals. Specifically, we aimed to explore hospitalized older patients’: 1) perceived acceptability of, and preference for, the two interventions, 2) characteristics (gender, illness severity, comorbidity, illnesses and medications with orthostatic effects, baseline functional capacity) associated with acceptability and, 3) characteristics associated with preference.

Methods

Design

A cross-sectional observational design was used to address the study aims. Eligible, consenting patients attended a data collection session, held in their room, and led by a Master’s prepared research nurse with experience working in internal medicine. The nurse explained that people who stay in bed for a few days may feel dizzy, tired and unsteady on their feet and may have trouble walking when they first get up. She explained that the two interventions were developed based on previous research to help reduce these problems, and played a 2-min video of each intervention. Following each video, the nurse provided patients with a written handout describing each intervention and verbally explained (using a standard script) what the interventions entailed, clarifying the activities patients were to perform (e.g. lift your heels up and down), dose (e.g. 10 times), anticipated benefits (e.g. reducing dizziness), and possible side effects (e.g. tiredness if a lot of time had been spent lying down before initiating the interventions). The nurse explained when patients should expect any side effects to abate, based on evidence indicating that the effects of bed rest on orthostatic intolerance can last up to three times the duration of bed rest [24], and then administered the measures of perceived acceptability and preference for the interventions. The sequence of the presentation of the interventions was randomized using a computer-generated randomization scheme to control for possible order effects. A $10 incentive was provided in the form of a coffee shop gift card.

Setting and sample

Participants were recruited from the in-patient general internal medicine units of two hospitals located in the Greater Toronto Area of Ontario, Canada in 2011. The units provide acute care services to patients with complex medical conditions and were comparable on key patient characteristics (e.g. age, chronic illnesses, reason for admission).

The convenience sample included adults aged 65 years and older, who had been admitted for the acute management of a medical condition within the past 72 h. Patients were eligible if they had spent ≥ 24 consecutive hours on a stretcher or in bed, presented with 2 or more chronic diseases identified on the International Classification of Disease-10, understood English, were ambulatory 2 weeks prior to admission, had a Mini Mental Status Exam (MMSE) score ≥ 24 [44] and a non-positive Confusion Assessment Method (CAM) [45]. Patients with a current medical order for bed rest and/or complete lower limb paralysis were excluded because the activity interventions were not applicable to their conditions. Patients admitted for palliation were also excluded on the basis that they may have chosen to remain in bed for comfort reasons.

The sample size of 60 was adequate to detect statistically significant associations of moderate magnitude based on the principle of 10 cases per predictor for 6 predictors [46] representing the patient characteristics.

Measures

Screening measures included the MMSE and CAM; both have established psychometric properties [44, 45]. Perceived acceptability and preference for the two low-intensity early activity interventions were measured using the Treatment Acceptability and Preferences (TAP) scale, which demonstrated internal consistency reliability (alpha > .80) and factorial validity in prior research [47]. The TAP consisted of two sections. The first provided a written description of each intervention followed by a set of items to rate its perceived acceptability relative to its anticipated appropriateness, effectiveness, side effects/risks, and ease of use. A five-point scale that ranged from 0 (not at all) to 4 (very much) was used in the rating. The total score was derived by taking the mean of the items’ scores. The second section contained two questions to assess intervention preference: a dichotomous question asking if participants preferred one intervention over the other and, if so, a question asking them to indicate that preference.

Illness severity was measured using the Modified Early Warning Score (MEWS), a scale that was designed specifically for patients admitted under medical service [48]. The scale demonstrated predictive validity; scores ≥ 3 were found to predict admission to the intensive care units in middle aged patients [49] and death in older patients [50]. The MEWS requires extracting routinely collected data on five parameters (e.g. heart rate) from the medical chart, assigning a score to the value of the parameter, and then summing the scores to generate a total scale score. Total scale scores can range from 0 to 14 (higher scores reflect greater illness severity), and a score of 4 is a trigger for urgent medical review [51]. We extracted the first three hospital admission assessments and, where none of the individual MEWS parameters (e.g. pulse) were missing, we calculated total scale scores for the first three measurement occasions and used the mean of these scores.

Because of the lack of consensus on how to measure comorbidity [52], two established scales were used: the Age Adjusted Charlson Comorbidity Index (ACCI) [53, 54] and the Cumulative Illness Rating Scale – for Geriatrics (CIRS-G) [55] by medical chart review. The ACCI demonstrated predictive ability of 90-day and 5-year mortality [56, 57]. The ACCI requires users to indicate the presence of 19 conditions (e.g. congestive heart failure) which have pre-defined weights of 1 (e.g. congestive heart failure), 2 (e.g. hemiplegia), 3 (e.g. moderate or severe liver disease) or 6 (e.g. metastatic solid tumor) [53, 54]. The total scale score was derived by summing the weights for the conditions that are present, which can range from 0 to 37, [53] and then adding one point for each decade of life from age 50 on [54]; higher scores indicate higher comorbidity.

The CIRS-G demonstrated test-retest reliability in older medical patients and construct validity manifested by high correlations with other comorbidity scales [58] and by significantly predicting hospital readmission and one- and 5-year mortality rates [59]. The CIRS-G requires users to rate illnesses in 14 organ systems using a five-point severity scale ranging from 0 (no impairment) to 4 (extremely severe impairment). The total scale score, which can range from 0 to 56, was derived by summing the ratings in the 14 organ systems; higher scores indicate higher comorbidity.

Baseline functional capacity was measured using the Duke Activity Status Index (DASI), an established self-report scale which was designed for use in adults with chronic disease and has shown good psychometric properties [60]. The time referent “at this time” was revised to “two weeks before your current hospital admission” to establish baseline. DASI uses a weighted sum in which a weight based on the known metabolic cost of each activity in MET (metabolic equivalent) units is individually applied to yes responses to questions asking about the ability to perform 12 physical activities (e.g. climbing a flight of stairs); the weighted values are then summed to generate scores ranging from 0 to 58.20, with higher scores indicating higher functional capacity [60].

Information on gender as well as illnesses and medications with orthostatic effects, were extracted from the medical chart using a data collection tool developed by our team and used previously. Demographic and other health related data were collected to examine patient characteristics associated with perceived acceptability and preference as well as to describe the sample. Age, reason for admission, mobility devices used, and amount of time spent in the emergency department were extracted from the medical chart. The latter was calculated by subtracting the time of admission to the unit from the time of admission to the emergency department. Information on highest level of education and living situation were obtained from the patients using standard questions.

Data analysis

Descriptive statistics were used to characterize the sample’s characteristics, as well as their perceived acceptability and preference for the two interventions (aim 1). Prior to conducting the regression analyses exploring the factors associated with perceived acceptability and preferences (aims 2 and 3), the data were examined for departures from normality and violations of the assumptions underlying regression. In addition, collinearity diagnostics were performed to determine if the independent variables were strongly correlated with each other, evidenced by tolerance values less than 0.1 and variance inflation factors (VIF = 1/tolerance) greater than 10 [61]. The forced entry method was used in all regression analyses.

Linear regression using ordinary least squares was employed to explore patient characteristics (gender, illness severity, comorbidity, illnesses and medications with orthostatic effects, and baseline functional capacity) associated with perceived acceptability (aim 2); these were performed separately for the two comorbidity measures (ACCI and CIRS-G) to reduce the potential for multicollinearity. Statistically significant predictors had beta weights with associated P-values ≤0.05. The forced entry method was used in all regression analyses.

Ordinal logistic regression analysis was used to explore the association of the same patient characteristics with preference (aim 3); these were also performed separately for the two comorbidity measures. Preference was defined by three ordinal groups represented by preference for the bed-to-sitting intervention (scored − 1), no preference (scored 0), and preference for the sitting-to-walking intervention (scored + 1). Statistically significant predictors had odds ratio (OR) > 1 and associated P-values ≤0.05.

Results

Participant characteristics and average standing on perceived early activity acceptability and preference

In total, 100 patients agreed to meet with the study nurse but 33 declined to participate in the study. Of the 67 who consented, 6 were ineligible because they did not have the minimum score on the pre-screening measures, and one withdrew after consenting. As shown in Table 2, the average patient was female, aged 79 years old, lived alone and used a cane to walk.

Table 2 Characteristics of 60 study participants

All patients were admitted to hospital via the emergency department, and most were admitted for lung disease management. The average score on the MEWS was 2, indicating that the average patient’s score on admission was not a trigger for urgent medical review. The median score of 7.2 on the DASI is associated with 3.63 METs, indicating that the average patient, at baseline, had low-moderate functional capacity or could walk a block on ground level (2.75 METs) or vacuum (3.5 METs) but could not climb a flight of stairs (5.5 METs) [62].

Most patients had an illness and were taking medications with orthostatic effects. The average patient had morbidity in 7 (range 2 to 12) CIRS-G organ systems with at least one organ system rated at level 4 or extreme severe impairment (n = 55; 91.7%). Their mean total scores on the ACCI and the CIRS-G reflect moderate comorbidity [55].

As reported in Table 3, mean scores on the TAP were slightly above the mid-range of the scale (i.e. 2) for both the bed-to-sitting and sitting-to-walking interventions, suggesting that participants perceived both interventions as acceptable. Most patients expressed a preference for the sitting-to-walking intervention.

Table 3 Perceived intervention acceptability & preference for 60 study participants

Test of statistical assumptions

No major departures from normality or violations of the assumptions underlying the linear and logistic regression analyses were identified. The variance inflation factors (VIF) were all less than 1.3 and the tolerances were all greater than 0.78, indicating that the independent variables were not redundant or correlated. In the linear regression exploring the associations of the patient characteristics with perceived acceptability of the interventions, the assumptions of normal distribution of residuals and homoscedasticity were met, as indicated by visual inspection of residual plots and results of the Kolmogorov-Smirnov and Shapiro-Wilk Tests of Normality.

In the ordinal logistic regressions exploring the associations of the patient characteristics with preference for the interventions, the Chi-squared Goodness-of-Fit test and the Test of Parallel Lines (i.e. testing if the coefficients/slopes are the same across explanatory variable categories) were not statistically significant (p-values were greater than or equal to .50) as required for proper model fit.

Patient characteristics associated with perceived early activity acceptability

Separate linear regressions were applied to explore the associations of patient characteristics (gender, illness severity, comorbidity, illnesses and medications with orthostatic effects, and baseline functional capacity) with perceived acceptability of each of the two low-intensity, early activity interventions (aim 2); these were performed separately for the two comorbidity measures as additional explanatory variables. None of the characteristics were significantly associated (all P-values > .05) with perceived acceptability of either intervention.

Patient characteristics associated with early activity preference

Ordinal regression was applied to explore the associations of the same set of patient characteristics with early activity preference (aim 3); this was performed separately for the two comorbidity measures. Using the ACCI as a measure of comorbidity, illness severity was associated with early activity preference and had a positive coefficient (0.62) with an odds ratio of 1.9 [95% Confidence Interval (CI), 1.04 to 3.30] Wald χ2(1) = 4.34, p = 0.04). In other words, patients with higher illness severity were almost twice as likely to express a preference for the sitting-to-walking intervention compared to the bed-to-sitting intervention or no preference. Medications with orthostatic effects was associated with early activity preference with a positive coefficient (2.29) and an odds ratio of 9.9 [95% CI, 1.30 to 74.8] Wald χ2(1) = 4.89, p = .03. Patients taking medications with orthostatic effects were almost 10 times more likely to express a preference for the sitting-to-walking intervention (while holding constant the model’s other variables). Similar results were found using the CIRS-G as a measure of comorbidity.

Discussion

Participants’ perceived acceptability of both interventions clustered above the scale midpoint; most preferred the sitting-to-walking intervention (aim 1). While none of the patient characteristics (gender, illness severity, comorbidity, illnesses and medications with orthostatic effects, and baseline functional capacity) were associated with perceived acceptability of the interventions (aim 2), illness severity and medications with orthostatic effects were significantly associated with intervention preference (aim 3). The results are generalizable to cognitively intact older men and women admitted to hospital with an acute medical illness, low-moderate baseline functional capacity and moderate comorbidity.

To our knowledge, this is the first study to identify the early activity intervention preferences of older patients with multiple chronic conditions admitted to hospital with an acute condition. Most (58.3%) expressed a preference for one intervention over the other. The finding concurs with those of meta-analyses indicating that, when offered treatment options, most (≥ 60%) people identify a preference [63, 64]. The few studies that have focused on perceptions of early activity during hospitalization found that some older medical patients have strong beliefs about the need for rest [10, 65], the inappropriateness of activity during illness, and the risks of performing activity in the hospital setting but are motivated to be active by the negative effects of bed rest [11]. The current study adds to this body of knowledge by identifying that, when older medical patients were engaged in a systematic process that involves considering the orthostatic effects of bed rest and critically appraising the acceptability of interventions to address these effects, most (43%) expressed a preference for the sitting-to-walking intervention – only 15% expressed preference for the bed-to-sitting intervention. Clinicians may use this systematic process to help older medical patients make informed decisions around participating in activity during acute illness and hospitalization, and to explore their perceptions of activity. The 8-item TAP scale provides an efficient approach for clinicians to assess older patients’ perceived acceptability of, and preferences for, early activity interventions; the patients’ responses can then be explored in greater depth to clarify any misconceptions about the interventions.

Only 15% of the study participants expressed preference for the bed-to-sitting intervention. Although the ultimate goal is to return patients to their usual level of activity (which in the study sample was walking), the bed-to-sitting intervention provides an alternative to remaining inactive and sedentary for patients who are unable to tolerate walking or refuse to walk during hospitalization. Despite evidence suggesting that the older patient population has varying perceptions of the acceptability of early activity interventions, prior studies have not examined patients’ perceived acceptability of, or preferences for, different early activity interventions. Patients’ inactivity and bed rest in the current acute care environment, where early activity is encouraged, may reflect their personal choices and preferences. Respecting patients’ choices and preferences and offering intervention options aligned with them are key components of patient-centered care [66]. Although the bed-to-sitting intervention requires further testing, its selection by 15% of the study sample suggests that it may be a viable option for sedentary patients. Patients who are provided with interventions that they explicitly expressed a preference for have higher rates of intervention adherence and lower rates of attrition compared to those who are not offered their preferred intervention [67,68,69,70].

About 42% of the study participants expressed no preference for the interventions examined in this study. This finding is difficult to interpret but may relate to features of the sample and/or the interventions. Older adults may not have been socialized to actively engage in treatment selection and may have had difficulty expressing their preference for one intervention over another. Also, with the average perceived acceptability score slightly above the mid-range (i.e., between acceptable and very acceptable), some participants did not view the interventions as highly appealing, suggesting the need for additional research to explore, qualitatively, what participants liked or did not like about each intervention.

The current study also adds to the body of knowledge on the patient demographic and health related characteristics associated with perceived acceptability and preference of early activity interventions during acute illness and hospitalization. Participants with higher illness severity were almost twice as likely to express a preference for the sitting-to-walking intervention. Of the two interventions, the sitting-to-walking intervention, which requires patients to get out of bed, can be considered more intensive. Prior research found beliefs surrounding the causes and consequences of a health condition to influence preferences in other patient populations [71]. People with more serious health conditions tend to consider mediation necessary and, consequently, are more likely to select more intensive and aggressive interventions [72, 73]. Accordingly, participants who were sicker on admission may have preferred the more intensive intervention (i.e., sitting-to-walking) because they perceived themselves as sicker and at greater risk of developing orthostatic intolerance and functional decline. They may have viewed the sitting-to-walking intervention as having better potential to prevent these problems.

Clinicians can use the findings to anticipate that older medical patients with higher levels of illness acuity on admission, as measured by the MEWS, will be more likely to prefer the sitting-to-walking intervention, and to not direct patients to the lower-intensity activity intervention. The MEWS is a simple and easy to use tool that uses routinely collected data from which illness acuity can be quickly calculated at the bedside [51] and may be used to anticipate activity preference in clinical practice and future research.

Participants taking medications with orthostatic effects were more likely to express their preference for the sitting-to-walking intervention; however, while significant, the wide 95% confidence interval suggests low precision. Participants taking these medications could be anywhere from 1.3 to 74.8 (95% CI) times more likely to prefer the sitting-to-walking intervention. This imprecision could be related to the low variance on this dichotomous variable; only seven patients (11.7%) were not taking this type of medication and, consequently, the result should be interpreted with caution. Future studies with larger sample sizes would be needed to generate a more precise interval given an expected high prevalence of these types of illness in the target population [39]. Similarly, the sample varied little on illnesses with orthostatic effects, which may account for the lack of statistical significance in this variable.

Gender was not associated with perceived early activity intervention acceptability or preference. This differs from other studies which identified gender-based differences in physical activity preferences, with men being treated for prostate cancer in ambulatory clinics preferring strength- over aerobic-based activity [35]. Although further research is needed, it is possible that the interventions examined in this study were not perceived to differ in terms of their strength and aerobic basis because they were both designed to promote vascular return.

Comorbidity and baseline functional capacity were not associated with perceived early activity intervention acceptability or preference. Although we found no studies examining the relationship that these variables have with perceived intervention acceptability and preference, prior studies have identified patients with higher comorbidity to have lower functional capacity [37]. Our study sample had a moderate level of comorbidity, with extremely severe impairment in at least one CIRS-G organ system, and their low-moderate baseline functional capacity reflects an inability to perform the levels of moderate-to vigorous-intensity physical activity recommended by national activity guidelines for older adults to maintain good health [74]. The interventions examined in this study were perceived as acceptable by this patient population and support future research examining their effectiveness. To the best of our knowledge, only one controlled trial has examined the effectiveness of early activity in the form of a walking program in this patient population [33], supporting the need for further research.

Strengths and limitations

The results of this study should be interpreted in the context of its aims, which were to explore patients’ perceived acceptability and preference for two early activity interventions prospectively. While a strength of the study was the systematic process used to examine perceived acceptability, the TAP scale does not have validated norms for the target population. Consequently, the subjective responses based on their position along the response options of the TAP scale should be interpreted with caution. Similarly, the sample size was small, and the study should be replicated with a larger sample size.

The study did not measure actual activity performance. Although recent research has found older medical patients’ perceptions and attitudes toward activity during hospitalization to predict their actual activity performance [65], future research is needed to explore patients’ perceived acceptability concurrently as they participate in the interventions and if perceived acceptability predicts actual activity performance during hospitalization.

The interventions have not been tested as stand-alone interventions for their effectiveness in preventing orthostatic intolerance, bed rest dependency or functional decline in the study’s target population. Further research to test their effectiveness should be conducted prior to adopting the interventions in practice. Future research should also examine the relationship between older hospitalized patients’ attitudes toward activity and their acceptability of the early activity interventions to further understanding of factors that influence acceptability and to identify patient characteristics on which to tailor early activity.

Conclusions

Assessing the perceived acceptability and preferences are increasingly acknowledged as essential in the design, evaluation, and, ultimately, implementation of healthcare interventions but prior studies did not examine older hospitalized patients’ perceived acceptability of, and preferences for, early activity interventions and they demonstrated poor feasibility. The two low-intensity early activity interventions that we designed and examined in this study were perceived as acceptable to older patients admitted to hospital with an acute medical illness, low-moderate baseline functional capacity and moderate comorbidity. Patient characteristics were not significantly associated with perceived intervention acceptability, but illness severity was significantly associated with intervention preference. The results support future research examining the effectiveness of the interventions in older hospitalized medical patients admitted to hospital with an acute medical illness, low-moderate baseline functional capacity and moderate comorbidity.

Abbreviations

ACCI:

Age Adjusted Charlson Comorbidity Index

ACE:

Acute Care for Elders

CAM:

Confusion Assessment Method

CI:

Confidence Interval

CIRS-G:

Cumulative Illness Rating Scale – for Geriatrics

DASI:

Duke Activity Status Index

MET:

Metabolic equivalent

MEWS:

Modified Early Warning Score

MMSE:

Mini Mental Status Exam

n:

Number

OR:

Odds ratio

p :

Probability

SD:

Standard deviation

TAP:

Treatment Acceptability and Preferences

VIF:

Variance inflation factors

χ 2 :

Chi-square

References

  1. Fox MT. The effects of scheduled bed rest in complex continuing care [Doctoral dissertation]. Toronto: University of Toronto; 2007.

    Google Scholar 

  2. McCabe JJ, Kennelly SP. Acute care of older patients in the emergency department: strategies to improve patient outcomes. Open Access Emergency Medicine : OAEM. 2015;7:45–54. doi: https://0-doi-org.brum.beds.ac.uk/10.2147/OAEM.S69974.

  3. Brown CJ, Redden DT, Flood KL, Allman RM. The underrecognized epidemic of low mobility during hospitalization of older adults. J Am Geriatr Soc. 2009;57:1660–5.

    Article  PubMed  Google Scholar 

  4. Pedersen MM, Bodilsen AC, Petersen J, Beyer N, Andersen O, Lawson-Smith L, et al. Twenty-four-hour mobility during acute hospitalization in older medical patients. J Gerontol A Biol Sci Med Sci. 2013;68:331–7.

    Article  PubMed  Google Scholar 

  5. Callen BL, Mahoney JE, Grieves CB, Wells TJ, Enloe M. Frequency of hallway ambulation by hospitalized older adults on medical units of an academic hospital. Geriatr Nurs. 2004;525:212–7.

    Article  Google Scholar 

  6. Brown CJ, Friedkin RJ, Inouye SK. Prevalence and outcomes of low mobility in hospitalized older patients. J Am Geriatr Soc. 2004;52:1263–77.

    Article  PubMed  Google Scholar 

  7. Weill-Engerer S, Meaume S, Lahlou A, Piette F, Saint-Jean O, Sachet A, et al. Risk factors for deep vein thrombosis in inpatients aged 65 and older: a case-control multicenter study. J Am Geriatr Soc. 2004;52:1299–304.

    Article  PubMed  Google Scholar 

  8. Brown CJ, Williams BR, Woodby LL, Davis LL, Allman RM. Barriers to mobility during hospitalization from the perspectives of older patients and their nurses and physicians. J Hosp Med. 2007;2:305–13.

    Article  PubMed  Google Scholar 

  9. Fox MT, Sidani S, Brooks D. Perceptions of bed days for individuals with chronic illness in extended care facilities. Res Nurs Health. 2009;32:335–44.

    Article  PubMed  Google Scholar 

  10. Boltz M, Resnick B, Capezuti E, Shuluk J. Activity restriction vs. self-direction: hospitalised older adults’ response to fear of falling. Int J Older People Nursing. 2014;9:44–53. https://0-doi-org.brum.beds.ac.uk/10.1111/opn.12015.

    Article  Google Scholar 

  11. So C, Pierluissi E. Attitudes and expectations regarding exercise in the hospital of hospitalized older adults: a qualitative study. J Am Geriatr Soc. 2012;60:713–8. https://0-doi-org.brum.beds.ac.uk/10.1111/j.1532-5415.2012.03900.x.

    Article  PubMed  Google Scholar 

  12. Bamford J, Dennis M, Sandercock P, Burn J, Warlow C. The frequency, causes and timing of death within 30 days of a first stroke: the Oxfordshire community stroke project. J Neurol Neurosurg Psychiatry. 1990;53:824–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Campbell NC, Murray E, Darbyshire J, Emery J, Farmer A, Griffiths F, et al. Designing and evaluating complex interventions to improve health care. BMJ. 2007;334:455–9.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Sidani S, Braden CJ. Design, evaluation and translation of nursing interventions. Oxford: Wiley-Blackwell; 2011.

    Book  Google Scholar 

  15. Medical Research Council. A framework for development and evaluation of RCTs for complex interventions to improve health. London: Medical Research Council; 2000. p. 1–18.

    Google Scholar 

  16. Sekhon M, Cartwright M, Francis JJ. Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res. 2017;17:1–13. https://0-doi-org.brum.beds.ac.uk/10.1186/s12913-017-2031-8.

    Article  Google Scholar 

  17. Convertino VA. Cardiovascular consequences of bed rest: effect on maximal oxygen uptake. Med Sci Sports Exerc. 1997;29:191–6.

    Article  CAS  PubMed  Google Scholar 

  18. Smith JJ, Ebert TJ. General responses to orthostatic stress. In: Smith JJ, editor. Circulatory response to the upright posture. Boca Raton: CRC Press, Inc.; 1990. p. 1–46.

    Google Scholar 

  19. Convertino VA, Bloomfield SA, Greenleaf JE. An overview of the issues: physiological effects of bed rest and restricted physical activity. Med Sci Sports Exerc. 1997;29:187–90.

    Article  CAS  PubMed  Google Scholar 

  20. Fox MT, Sidani S, Brooks D. The relationship between bed rest and sitting orthostatic intolerance in adults residing in chronic care facilities. J Nurs Healthc Chronic Illn. 2010;2:187–96.

    Article  Google Scholar 

  21. Convertino VA, Hung PJ, Goldwater D, RF DB. Cardiovascular responses to exercise in middle-aged men after 10 days of bedrest. Circulation. 1982;65:134–40.

    Article  CAS  PubMed  Google Scholar 

  22. Brown CJ, Roth DL, Allman RM. Validation of use of wireless monitors to measure levels of mobility during hospitalization. J Rehabil Res Dev. 2008;45:551–8.

    Article  PubMed  Google Scholar 

  23. Greenleaf JE, Kozlowski S. Physiological consequences of reduced physical activity during bed rest. Exerc Sport Sci Rev. 1982;10:84–119.

    Article  CAS  PubMed  Google Scholar 

  24. DeBusk RF, Convertino VA, Hung J, Goldwater D. Exercise conditioning in middle-aged men after 10 days of bed rest. Circulation. 1983;68:245–50.

  25. Birkhead NC, Blizzard JW, Daly GJ, Haupt B, Issekutz J, Myers RN, et al. Cardiodynamic and metabolic effects of prolonged bed rest with daily recumbent or sitting exercise and with sitting inactivity. AMRL-technical report. Dayton: Wright-Patterson Air Force Base; 1964.

    Google Scholar 

  26. Convertino VA, Sandler H, Webb P. The effect of an elastic reverse gradient garment on the cardiovascular deconditioning following 15-days bed rest. Aerospace Med Assoc Preprints. 1978;148–49.

  27. Convertino VA, Sandler H, Webb P, Annis JR. Induced venous pooling and cardiovascular responses to exercise after bedrest. J Appl Physiol. 1982;52:1343–8.

    Article  CAS  PubMed  Google Scholar 

  28. Convertino VA. Effect of orthostatic stress on exercise performance after bed rest: relation to inhospital rehabilitation. J Cardiac Rehabil. 1983;3:660–3.

    Google Scholar 

  29. Vernikos J, Ludwig DA, Ertl AC, Wade CE, Keil L, O’Hare D. Effect of standing and walking on physiological changes induced by head-down bed rest: implications for spaceflight. Aviat Space Environ Med. 1996;67:1069–79.

    CAS  PubMed  Google Scholar 

  30. Fox MT, Persaud M, Maimets I, O’Brien K, Brooks D, Tregunno D, et al. Effectiveness of acute geriatric unit care using acute care for elders components: a systematic review and meta-analysis. J Am Geriatr Soc. 2012;60:2237–45.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Brown CJ, Peel C, Bamman MM, Allman RM. Exercise program implementation proves not feasible during acute care hospitalization. J Rehabil Res Dev. 2006;43:939–46.

    Article  PubMed  Google Scholar 

  32. Siebens H, Aronow H, Edwards D, Ghasemi Z. A randomized controlled trial of exercise to improve outcomes of acute hospitalization in older adults. J Am Geriatr Soc. 2000;48:1545–52.

    Article  CAS  PubMed  Google Scholar 

  33. Brown CJ, Foley KT, Lowman JD, MacLennan PA, Razjouyan J, Najafi B, et al. Comparison of posthospitalization function and community mobility in hospital mobility program and usual care patients: a randomized clinical trial. JAMA Intern Med. 2016;176(7):921. https://0-doi-org.brum.beds.ac.uk/10.1001/jamainternmed.2016.1870.

    Article  PubMed  Google Scholar 

  34. Hastings SN, Sloane R, Morey MC, Pavon JM, Hoenig H. Assisted early mobility for hospitalized older veterans: preliminary data from the STRIDE program. J Am Geriatr Soc. 2014;62:2180–4.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Harrington JM, Schwenke DC, Epstein DR. Exercise preferences among men with prostate cancer receiving androgen-deprivation therapy. Oncol Nurs Forum. 2013;40:E358–67. https://0-doi-org.brum.beds.ac.uk/10.1188/13.onf.e358-e367.

    Article  PubMed  Google Scholar 

  36. Lin YC, Yeh MC, Chen YM, Huang LH. Physical activity status and gender differences in community-dwelling older adults with chronic diseases. J Nurs Res. 2010;18:88–97.

    Article  PubMed  Google Scholar 

  37. Waschki B, Kirsten AM, Holz O, Mueller KC, Schaper M, Sack AL, et al. Disease progression and changes in physical activity in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2015;192:295–306.

    Article  PubMed  Google Scholar 

  38. Beveridge C, Knutson K, Spampinato L, Flores A, Meltzer DO, Cauter EV, et al. Daytime physical activity and sleep in hospitalized older adults: association with demographic characteristics and disease severity. J Am Geriatr Soc. 2015;67:1391–400.

    Article  Google Scholar 

  39. Fedorowski A, Melander O. Syndromes of orthostatic intolerance: a hidden danger. J Intern Med. 2013;273:322–35.

    Article  CAS  PubMed  Google Scholar 

  40. Sidani S. Health intervention research: advances in research design and methods. London: Sage; 2015. https://0-doi-org.brum.beds.ac.uk/10.4135/9781473910140.

  41. Bouvette CM, McPhee BR, Opfer-Gehrking TL, Low PA. Role of physical countermaneuvers in the management of orthostatic hypotension: efficacy and biofeedback augmentation. Mayo Clin Proc. 1996;71:847–53. https://0-doi-org.brum.beds.ac.uk/10.1016/S0025-6196(11)63747-6.

    Article  CAS  PubMed  Google Scholar 

  42. Krediet CTP, Go-Schon IK, Kim Y-S, Linzer M, Van Lieshout JJ, Wieling W. Management of initial orthostatic hypotension: lower body muscle tensing attenuates the transient arterial blood pressure decrease upon standing from squatting. Clin Sci. 2007;113:401–7. https://0-doi-org.brum.beds.ac.uk/10.1042/cs20070064.

    Article  PubMed  Google Scholar 

  43. Freeman R, Wieling W, Axelrod FB. Consensus statement on the definition of orthostatic hypotension, neurally mediated syncope and the postural tachycardia syndrome. Clin Auton Res. 2011;21:69–72. https://0-doi-org.brum.beds.ac.uk/10.1007/s10286-011-0119-5.

    Article  PubMed  Google Scholar 

  44. Crum RM, Anthony JC, Bassett SS, Folstein FM. Population-based norms for the mini-mental state examination by age and educational level. J Am Geriatr Soc. 1993;269:2386–91.

    CAS  Google Scholar 

  45. Inouye S, van Dyck C, Alessi C, Balkin S, Siegal A, Horwitz R. Clarifying confusion: the confusion assessment method. Ann Intern Med. 1990;113:941–8.

    Article  CAS  PubMed  Google Scholar 

  46. Cohen J. A power primer. Psychol Bull. 1992;112:155–9.

    Article  CAS  PubMed  Google Scholar 

  47. Sidani S, Epstein D, Bootzin RR, Moritiz P, Miranda J. Assessment of preferences for treatment: validation of a measure. Res Nurs Health. 2009;23:419–31.

    Article  Google Scholar 

  48. Subbe CP, Kruger M, Rutherford P, Gemmell L. Validation of a modified early warning score in medical admissions. QJM Int J Med. 2004;94:521–6.

    Article  Google Scholar 

  49. Tavares RCF, Vieira AS, Uchoa LV, AAP J, FAd M. Validation of an early warning score in pre-intensive care unit. Rev Bras Ter Intensiva. 2007;20:124–7. 

  50. Martin BJ, Oommen E. Use of the modified early warning score (MEWS) in assessment of older patients. Eur Geriatr Med. 2005;7:17–20.

    Google Scholar 

  51. Subbe CP, Davies RG, Williams E, Rutherford P, Gemmell L. Effect of introducing the modified early warning score on clinical outcomes, cardio-pulmonary arrests and intensive care utilisation in acute medical admissions. Anaesthesia. 2003;58:797–802.

    Article  CAS  PubMed  Google Scholar 

  52. Sarfati D. Review of methods to measure comorbidity in cancer populations: No gold standard exists. J Clin Epidemiol. 2012;65:924-33. doi: https://0-doi-org.brum.beds.ac.uk/10.1016/j.jclinepi.2012.02.017. Epub 2012 Jun 26.

  53. Charlson ME, Pompei P, Ales KL, CR MK. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–83.

    Article  CAS  PubMed  Google Scholar 

  54. Charlson M, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol. 1994;47:1245–51.

    Article  CAS  PubMed  Google Scholar 

  55. Miller MD, Paradis CF, Houck PR, Mazumdar S, Stack JA, Rifai AH, et al. Rating chronic medical illness burden in geropsychiatric practice and research: application of the cumulative illness rating scale. Psychiatry Res. 1992;41:237–48.

    Article  CAS  PubMed  Google Scholar 

  56. Chang C-M, Yin W-Y, Wei C-K, Wu C-C, Su Y-C, Yu C-H, et al. Adjusted age-adjusted Charlson Comorbidity index score as a risk measure of perioperative mortality before cancer surgery. PLoS One. 2016; https://0-doi-org.brum.beds.ac.uk/10.1371/journal.pone.0148076.

  57. Yang C-C, Chen P-C, Hsu C-W, Chang S-L, Lee C-C. Validity of the age-adjusted Charlson comorbidity index on clinical outcomes for patients with nasopharyngeal cancer post radiation treatment: a 5-year nationwide cohort study, Chien M-H, ed. PLoS One. 2015; https://0-doi-org.brum.beds.ac.uk/10.1371/journal.pone.0117323.

  58. de Groot V, Beckerman H, Lankhorst GJ, Nouter LM. How to measure comorbidity: a critical review of available methods. J Clin Epidemiol. 2003;56:221–9.

    Article  PubMed  Google Scholar 

  59. Zekry D, Loures Valle BH, Graf C, Michel J-P, Gold G, Krause K-H, et al. Prospective comparison of 6 comorbidity indices as predictors of 1-year post-hospital discharge institutionalization, readmission, and mortality in elderly individuals. J Am Med Dir Assoc. 2012;13:272–8.

    Article  PubMed  Google Scholar 

  60. Hlatky MA, Boineau RE, Higginbotham MB, Lee KL, Mark DB, Califf RM, et al. A brief self-administered questionairre to determine functional capacity (the Duke activity status index). Am J Cardiol. 1989;64:651–4.

    Article  CAS  PubMed  Google Scholar 

  61. Hahs-Vaughn DL. Applied multivariate statistical concepts. New York: Routledge; 2016.

    Google Scholar 

  62. n.d. MD+ Calculation. The Duke Activity Index (DASI). https://www.mdcalc.com/duke-activity-status-index-dasi. Accesed 8 June 2017.

  63. King M, Nazareth I, Lampe F, Bower P, Chandler M, Morou M, et al. Impact of participant and physician intervention preferences on randomized trials. A systematic review. JAMA Intern Med. 2005;293:1089–109.

    CAS  Google Scholar 

  64. Preference Collaborative Review Group. Patients’ preferences within randomized trials: systematic review and patient level meta-analysis. BMJ. 2009;338:a1864.

    Article  Google Scholar 

  65. Levin C, Gur-Yaish N, Agmon M, Gil E, Rand D, King B, et al. Development and psychometric testing of a measure of older adult patients’ attitudes towards mobility during hospitalization (ATM-H). Geriatr Nurs. 2017;38:119–23.

    Article  PubMed  Google Scholar 

  66. Sidani S, Fox M. Patient-centered care: clarification of its specific elements. J Interprof Care. 2014;28:134–41. https://0-doi-org.brum.beds.ac.uk/10.3109/13561820.2013.862519.

    Article  PubMed  Google Scholar 

  67. Dimidjian S, Goodman S. Preferences and attitudes toward approaches to depression relapse/recurrence prevention among pregnant women. Behav Res Ther. 2014;54:7–11.

    Article  PubMed  Google Scholar 

  68. Kwan BM, Dimidjian S, Risvi SL. Treatment preferences, engagement, and clinical improvement in pharmacotherapy versus psychotherapy for depression. Behav Res Ther. 2010;48:799–204.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Swift JK, Callahan JL, Vollmer BM. Preferences. J Clin Psychol. 2011;67:155–65.

    Article  PubMed  Google Scholar 

  70. Tucker CM, Marsiske M, Rice KG, Nielson JJ, Herman K. Patient-centered culturally sensitive health care: model testing and refinement. Health Psychol. 2011;30:342–50.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Riedel-Heller SG, Matschinger H, Angermeyer MC. Mental disorders--who and what might help? Help-seeking and treatment preferences of the lay public. Soc Psychiatry Psychiatr Epidemiol. 2005;40:167–74.

    Article  PubMed  Google Scholar 

  72. SJY J, Kievit J, Nooij MA, de Haes JCJM, IME O, van Slooten H, et al. Patients’ preferences for adjuvant chemotherapy in early-stage breast cancer: is treatment worthwhile? Br J Cancer. 2001;84:1577–85.

    Article  Google Scholar 

  73. Koedoot CG, RJd H, Stiggelbout AM, PFM S, Ad G, PJM B, et al. Palliative chemotherapy or best supportive care? A prospective study explaining patients’ treatment preference and choice. Br J Cancer. 2003;89:2219–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Canadian Society for Exercise Physiology. Canadian Physical Activity and Sedentary Behaviour Guidelines. 2012. Available from: https://casem-acmse.org/wp-content/uploads/2014/03/CSEP_Guidelines_Handbook.pdf. Accessed 26 Jan 2018.

Download references

Acknowledgements

We are grateful to all of the participants who participated in this study and to Dr. Jeffrey I Butler for his assistance in editing the manuscript.

Funding

The study was funded by the Canadian Institutes for Health Research Grant No. 99005. CIHR had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Availability of data and materials

Researchers interested in using the data may contact Mary T. Fox and submit a data transfer request as required by University Health Network.

Author information

Authors and Affiliations

Authors

Contributions

All authors (MF, SS, DB, and HM) contributed to the conception and design of the study, or analysis and interpretation of the data; drafted the manuscript or revised it; made substantive intellectual contributions to the study, and read and approved the final manuscript; take public responsibility for appropriate portions of the content; and agree to be accountable for all aspects of the work. In particular, MF, SS, and DB conceived and designed the study. MF acquired the data. MF and DB designed the interventions and the video. MF and HM analyzed the data. MF, SS, DB, and HM interpreted the data. MF led the writing and drafted the manuscript. DB, SS, and HM critically revised the manuscript for important intellectual content.

Corresponding author

Correspondence to Mary T. Fox.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the ethics review boards at York University, University Health Network and York Central Hospital. Informed written consent was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fox, M.T., Sidani, S., Brooks, D. et al. Perceived acceptability and preferences for low-intensity early activity interventions of older hospitalized medical patients exposed to bed rest: a cross sectional study. BMC Geriatr 18, 53 (2018). https://0-doi-org.brum.beds.ac.uk/10.1186/s12877-018-0722-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s12877-018-0722-6

Keywords