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Clinical Interventions in Aging 2019:14 145–154
Clinical Interventions in Aging
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Clinical Interventions in Aging
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O r I g I n A l r e s e A r C h
open access to scientific and medical research
Open Access Full Text Article
http://dx.doi.org/10.2147/CIA.s191832
effects of a fall prevention program in elderly:
a pragmatic observational study in two
orthopedic departments
Bodil røyset1
Bente A Talseth-Palmer2–4
stian lydersen5
Per g Farup6,7
1Department for Medicine and
rehabilitation, Møre og romsdal
hospital Trust, Ålesund, norway;
2Department for research,
Innovation, education and
Competence Development, Møre
og romsdal hospital Trust, Molde,
norway; 3Department of Clinical
and Molecular Medicine, Faculty
of Medicine and health sciences,
norwegian University of science
and Technology, Trondheim, norway;
4school of Biomedical sciences and
Pharmacy, Faculty of health and
Medicine, University of newcastle
and hunter Medical research
Institute, newcastle, nsW, Australia;
5regional Centre for Child and Youth
Mental health and Child Welfare,
Department of Mental health, Faculty
of Medicine and health sciences,
norwegian University of science
and Technology, Trondheim, norway;
6Department of research, Innlandet
hospital Trust, Brumunddal, norway;
7Unit for Applied Clinical research,
Department of Clinical and Molecular
Medicine, Faculty of Medicine
and health sciences, norwegian
University of science and Technology,
Trondheim, norway
Purpose: Falls are a common adverse event experienced by elderly in hospitals. This study
assessed the effects of a fall prevention program on the rate of fallers, the patient safety culture,
and patient-perceived safety.
Materials and methods: Two orthopedic departments in different towns in Norway partici-
pated in the study. A comprehensive, multifactorial fall prevention program was implemented
in one of the departments, the other one was used for control. The changes in the outcomes in
the two departments from before to after the intervention were compared. All patients above
64 years of age admitted to the two departments in a 1-year period before and after the interven-
tion were included. All employees at the two departments were invited to participate in surveys
measuring the patient safety culture, and a selection of the patients reported patient-perceived
safety. The primary outcome was the rate of fallers. Secondary outcomes were the employees’
perceived patient safety culture (measured with the Safety Attitudes Questionnaire) and patient-
perceived safety (measured with Norwegian Patient Experience Questionnaire).
Results: Falls were registered in 114 out of 3,143 patients (3.6\%) with 17,006 days in the
hospital. Ten patients had two falls, giving a fall rate of 7.3 falls/1,000 days in the hospital. The
number of fallers before and after the intervention in the intervention department were 37/734
(5.04\%) and 31/735 (4.22\%), P=0.46, and in the control department, 25/811 (3.08\%) and
21/863 (2.43\%), P=0.46. The difference between the changes in the two departments was not
statistically significant; 0.17\% (95\% CI: -2.49 to 2.84; P=0.90). There were also no significant
differences in the changes in patient safety culture and patient-perceived safety.
Conclusion: The fall prevention program revealed no significant effect on the rate of fallers,
the patient safety culture, or patient-perceived safety.
Keywords: accidental falls, accident prevention, adverse effects, patient safety, safety culture
Introduction
The report “To Err is Human,” published in 1999, estimated adverse events in hospitals
to cause 44–98,000 deaths in the USA every year.1 The report draws attention to an
important health care-related concern and has resulted in a significant increase in
patient safety efforts, such as system-based interventions, practical clinical initiatives,
and research. In 2004, the WHO established the network World Alliance for Patient
Safety, which aims to coordinate, disseminate, and accelerate improvements in patient
safety worldwide.2 Systems for reporting adverse events are in use internationally for
quality assurance and patient safety.3–5
Worldwide, falls are one of the most commonly reported adverse events in hospitals
with prevalence rates in the order of 10 per 1,000 patient days or 5\%–15\% of the patients
Correspondence: Per g Farup
Department of research, Innlandet
hospital Trust, PB 104, n-2381
Brumunddal, norway
Tel +47 9 481 8603
Fax +47 6 115 7437
email [email protected]
Journal name: Clinical Interventions in Aging
Article Designation: Original Research
Year: 2019
Volume: 14
Running head verso: Røyset et al
Running head recto: Effects of a fall prevention program in elderly
DOI: 191832
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røyset et al
and are associated with both minor and major injuries.6–8
Preventive measures have been taken with conflicting results.
Overall, fall prevention exercise interventions have shown no
effect, while vitamin D supplement has reduced the rate of
falls but not the risk of falls in elderly in nursing homes.9,10
Multifactorial interventions in hospitals have shown a reduc-
tion in the rate of falls and an inconclusive trend for the risk
of falling according to a Cochrane review.10 In large, fall pre-
vention measures in hospitals have been disappointing.10–13
Norway has since 1994 had a national system for report-
ing adverse events in hospitals.14 The database has been
used to plan and implement prevention activities related to
frequent and serious adverse events. Eleven percent of all
reports from the specialized health services were incidents
related to falls.14
In January 2011, the Norwegian health minister launched
a national patient safety campaign called “In Safe hands.”15
The campaign had three aims: 1) reduce patient-related
adverse events, 2) build sustainable systems and structures
for patient safety, and 3) improve the patient safety culture.
Hospitals and primary care units were invited to participate
in 16 specific and measurable areas for improvement; one
of the areas was fall prevention. One out of four orthopedic
departments at different sites in Møre og Romsdal Hospital
Trust, Norway, participated actively in the national multi-
factorial fall prevention program.
This pragmatic observational study aimed to compare
the differences in the changes from before to after the fall
prevention intervention in the rate of fallers, the employees’
perceived patient safety culture, and the patient experienced
safety between the department with the intervention and the
department without the intervention in the same hospital
trust. The hypothesis was that the fall intervention program
would reduce the rate of fallers in the intervention department
(ID) compared with the department without the intervention.
A secondary aim was to study predictors of fallers.
Materials and methods
study design
The study was performed in two orthopedic departments in
Møre og Romsdal Hospital Trust, located in different cities.
The hospital trust serves a population of 265,000 inhabitants.
The ID served a population of 62,000 inhabitants and had
~1,400 admissions each year. The corresponding numbers
for the control department (CD) were 95,000 inhabitants
and 2,000 admissions. From November 2012 to September
2013, the fall prevention measures were implemented in one
of the orthopedic departments hereafter referred to as the ID.
The intervention was performed as proposed by the national
patient safety campaign “In safe hands.”15 The department
that did not participate in the safety campaign was used for
comparison and will be referred to as the CD. Comparisons
were made between two departments in the same hospital
trust with approximately the same size and organizational
culture, the same expectations and challenges from the
director and the board, and well-matched patients from the
same region.
In both departments, all falls were registered in a 12-month
period before (from November 2011 to October 2012) and
after (from November 2013 to October 2014) the interven-
tion. Before (in April 2012) and after (in April 2014) the
intervention, all employees in both departments were invited
to participate in a survey, measuring patient safety culture.
The survey was a part of the national patient safety campaign
and performed anonymously.
Similarly, two cross-sectional studies conducted by The
Norwegian Institute of Public Health were performed among
a selection of patients admitted to the orthopedic department
in 2012 and 2014 (before and after the intervention). They
were invited to participate in a survey measuring patient-
perceived safety. Figure 1 shows the timeline for data used
in different analyses.
Participants
The fall registration included all patients above 64 years of
age admitted to the ID and CD during the two registration
periods and with a stay of at least 24 hours’ duration.
All employees at the two departments were invited to par-
ticipate in surveys measuring the patient safety culture. The
exact number of employees in the two departments asked to
participate was unknown. Since the surveys were performed
anonymously, no information was available on the subjects’
characteristics, and therefore no matching was possible.
Randomly selected patients from the two orthopedic
departments were invited to participate in surveys measuring
patient-experienced safety. The surveys were part of national
surveys, and the number and characteristics of patients asked
to participate are unknown.
Variables
Participants
The following data were registered for all patients admitted to
the hospital during the two registration periods: age (years),
gender, operation (yes/no), fall (yes/no; if yes, number of
falls, point of time related to the admission, operation, and
time of fall; daytime/evening/night), fall as the cause of
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effects of a fall prevention program in elderly
admission (yes/no), fall causing fracture (yes/no), fall for-
mally reported in the hospital’s systems for adverse events
(yes/no), fall screening performed (yes/no), and the duration
of the stay (days).
Fall
Fall was defined according to WHO as “an event which
results in a person coming to rest inadvertently on the ground
or floor or other lower level.”16
Falls were registered retrospectively. Four individuals
shared the reviewing of all the medical records written by
doctors, nurses, and physiotherapists during the registration
periods. They read parts of the medical records and searched
the records with appropriate keywords to retrieve and find
information about all falls. Also, the hospital’s formal registry
of adverse events was searched and the findings compared
with the medical records.
Fall prevention interventions
Two doctors and three nurses from the ID participated
in the Patient Safety Campaign’s national workgroup for
prevention of falls. The group had meetings and published
national guidelines that proposed tools, training programs,
and improved procedures to prevent falls. The interventions
were implemented in the ID.
The fall prevention program, not unlike the 6-PACK
programme,13 was described in detail (in Norwegian).17
It consisted of 1) seven examples of risk factors which might
cause falls (diseases and medications, movement, cognitive
behavior, vision, continence, nutrition, and the room and
surroundings), 2) methods to detect the risk factors, and
3) measures to avoid falls or protect the patient in case of
a fall. The interventions were multifaceted and included
short- and long-term activities to prevent falls. To detect
risk factors, a fall screening was performed with the Norwe-
gian version of the risk assessment tool for falls in elderly
“STRATIFY” (score 0–5).18 Patients were scored on five
risk factors, each of them is one point: falls last 3 months,
reduced vision, uneasy patient, frequent visits to the toilet,
and reduced walking/movement ability. Standard measures
for all patients were a review of the medication and infor-
mation about the room and the surroundings. There were
individually tailored measures such as to lock the wheels of
the bed and the tables, make sure that the patients can reach
the alarm and their personal belongings, lower the bed to the
lowest level, adjust day and night lightening, and remove
furniture and equipment that may cause falls. In patients with
a score of 2 or more, a comprehensive individual plan for
fall prevention was worked out, documented in the medical
records, and communicated to the staff responsible for the
patient. The plan included practical initiatives like adjusting
the beds, proper illumination, instructions not to leave the
bed unaided, and the use of appropriate shoes. There were
also long-term measures like the treatment of underlying
diseases, changes in medication associated with the risk
of fall, physical training, and healthier dietary habits. Dur-
ing the intervention, reports about the process (number of
patients screened, etc) and the results (number of falls, etc)
were regularly sent to the authorities. The governmental
intervention was designed for use in hospitals, care facilities,
and patients living at home. Most of the proposed activities
aimed at preventing falls in a long time perspective. The fall
intervention was added to the routine preventive measures,
which were performed in the CD at the employees’ discre-
tion. The patients were offered suitable, often low, beds
with bed staffs, special surveillance if they were confused
Figure 1 The study design.
Abbreviations: CD, control department; ID, intervention department.
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røyset et al
or dizzy, and were urged to ask for help if they wanted to
get out of the bed.
Patient safety culture
Patient safety culture was measured with the validated
Norwegian version of the Safety Attitudes Questionnaire
(SAQ).19,20 The national campaign used only two factors
(teamwork climate and safety climate) out of the six factors
in the questionnaire. According to the scoring algorithm,
some answers were recoded and the results transformed into
a scale 0–100; high values indicate a good culture.
Patient-perceived safety
The Norwegian Patient Experience Questionnaire (PEQ) has
been used regularly in Norwegian hospitals since 1996.21 This
study used ten out of 52 questions that measure the patient-
experienced patient safety.22 The answers were transformed
according to the scoring algorithm into a scale 0–100; high
values indicate high patient-perceived safety.
statistics
The results have been reported as mean (SD), median
(range), and number (with proportion in brackets). Com-
parisons between groups were analyzed with Fisher’s exact
test, Student’s t-test, and Mann–Whitney U-test depending
on the type of data and distribution, and logistic regression
analyses for the study of predictors of falls. For continuous
variables, the comparisons of changes from before to after the
intervention were performed with linear regression with the
point of time, department, and their interaction as covariates.
For dichotomous variables, the risk difference was calculated
with a semirobust generalized linear model for a binary out-
come. In each analysis, we included all the cases with data on
the relevant variables (“available case analysis”). P-values
,0.05 were judged as statistically significant. The analyses
were performed with IBM SPSS Statistics for Windows,
version 23.0 (IBM Corporation, Armonk, NY, USA), except
for the risk difference for dichotomous variables that were
analyzed with STATA Release 13 (StataCorp LP, College
Station, TX, USA).
ethics approval
The project was approved by the Regional Committees
for Medical and Health Research Ethics (REK) in Norway
(approval number REK 2015/2469). A waiver of consent was
granted in this study as the project was deemed not to be a
medical or health research project according to the Health
Research Act. By virtue of regulations of February 7, 2009,
#989 REK is delegated authority to grant exemption from
the duty of confidentiality pursuant to the Health Personnel
Act, §29 first paragraph and the Act of First Amendment, §13
first paragraph, and a waiver of consent is given to obtain the
data mentioned in the application (see registration variables
under participants) as the project is of genuine interest to
society and the data collection does not significantly interfere
with the welfare and integrity of the patients. The data were
anonymized after registration. The Norwegian Data Inspec-
torate represented by the Privacy Ombudsman for research
at Møre og Romsdal Hospital Trust approved the responses
to the questionnaires SAQ and PEQ for research after ano-
nymization. The study was registered in ClinicalTrials.gov
NCT03354468; date of registration: November 24, 2017;
“Retrospectively registered.”
Results
In all, 3,143 patients with 17,006 days in the hospital were
included in the study. Falls were noted in 114 patients, ten
patients had two falls, which gave an overall fall rate of
3.6\% of the patients or 7.3 falls/1,000 days in the hospital.
Table 1 shows the patients’ characteristics and the results
separately for the ID and CD with comparisons between the
departments.
The overall prevalence rates of fallers in both the regis-
tration periods in the ID and CD were 68/1,469 (4.6\%) and
46/1,674 (2.7\%), respectively (P=0.005), and the prevalence
rates of fallers before and after the intervention were 62/1,545
(4.0\%) and 52/1,598 (3.3\%), respectively (P=0.30). Patients
with falls had a longer stay in hospital compared with those
who did not fall; the median lengths were 7 days (range
1–164) and 4 days (range 0–56), respectively (P,0.001).
The prevalence rate of fallers in patients with and without
an operation were 91/2,274 (4.0\%) and 22/824 (2.7\%),
respectively (P=0.08). In the ID, the fall risk evaluation
was performed in 327/727 (45\%) of the patients after the
intervention. The number of fallers in patients evaluated and
not evaluated for fall risk were 17/327 (5.2\%) and 14/400
(3.5\%) (P=0.27), respectively, and the number of fallers
formally registered in the hospital registry of adverse events
before and after the intervention were 2/37 (5.4\%) and 4/31
(12.9\%) (P=0.40), respectively. Table 2 shows unadjusted
and adjusted predictors of fallers.
In the ID and CD, the changes in the faller rates from
before to after the intervention were 0.82\% and 0.65\%,
respectively, the difference was not statistically significant
(P=0.90). Table 3 shows the details and Figure 2A visualizes
the main results.
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effects of a fall prevention program in elderly
In all, 130 and 128 employees had satisfactorily filled in
the teamwork and safety culture parts of the SAQ, respec-
tively. The patient safety culture did not differ significantly
between the two departments. Table 1 shows the overall
results in the two departments, and Table 3 shows the culture
in the two departments before and after the intervention with
comparisons between the departments and the time of regis-
tration. The changes in the teamwork and safety climate from
the first to the second registration did not differ significantly
between the departments.
Before and after the intervention, 62 and 76 patients in the
ID and 26 and 33 patients in the CD, respectively, answered
the patient-perceived safety questionnaire. The patient-
perceived safety scores did not differ significantly between
the departments and were not significantly influenced by the
intervention. Table 1 shows the overall results, and Table 3
shows the results in the two departments before and after the
intervention with comparisons between the departments and
time of registration.
The main outcomes of the study were the comparisons
of the changes in the faller rates, patient safety culture, and
patient-perceived safety from before to after the intervention
between the departments. There was no significant effect
of the intervention in either of the variables (Table 3 – the
Table 1 Patients’ characteristics and the overall results from both registration periods in the two departments
Patient characteristics and
results
Intervention department (ID)
n=1,469
Control department (CD)
n=1,674
Statistics, P-values
Women/men 943 (64\%)/526 (36\%) 1,072 (64\%)/602 (36\%) 0.94a
Age (years) 77.7 (8.5) 78.0 (8.4) 0.41b
Days in hospital 4.0 (0 to 164) 4.0 (0 to 53) 0.58c
Operation 1,036 (71\%) 1,271 (76\%) 0.001a
Fall as the cause of the admission 538 (37\%) 716 (43\%) ,0.001a
Falls 68 (4.6\%) 46 (2.7\%) 0.005a
Falls causing fracture 4/68 (5.9\%) 3/46 (6.5\%) 1.00a
Falls causing operation 3/68 (4.4\%) 3/46 (6.5\%) 0.68a
Fall: days after admittance 3.0 (0 to 31) 4.0 (0 to 16) 0.07c
Fall: days after an operation 2.0 (-6 to 32) 3.5 (1 to 15) 0.004c
Fall: day/evening/night 23 (34\%)/18 (26\%)/27 (40\%) 21 (46\%)/8 (17\%)/17 (37\%) 0.38a
Falls formally reported 6/66 (9.1\%) 1/46 (2.2\%) 0.24a
Teamwork climated 77 (16) 78 (15) 0.65b
safety climatee 75 (17) 76 (17) 0.98b
Patient-perceived safetyf 89 (18) 85 (17) 0.10b
Notes: The results are given as number and proportion (\%), mean (sD), and median (range). aFisher’s exact test; bt-test; cMann–Whitney U-test. dnumber of subjects in
the ID and CD were 76 and 54, respectively. enumber of subjects in the ID and CD were 75 and 53, respectively. fnumber of patients in the ID and CD were 138 and 59,
respectively.
Table 2 Comparisons of the patients with and without a fall and predictors of fallers
Variables Faller Predictors of fallersa
Yes (n=114) No (n=3,029) P-value OR 95\% CI P-value
gender (female/male) 68 (60\%)/46 (40\%) 1,947 (64\%)/1,082 (36\%) 0.321b 1.30 0.88–1.94 0.19
Age (years) 80 (65–97) 77 (64–101) 0.025c 1.02 0.996–1.05 0.11
Department (ID/CD) 68 (60\%)/46 (40\%) 1,401 (46\%)/1,628 (54\%) 0.005b 0.57 0.39–0.84 0.005
Point of time (before/after the
intervention)
62 (54\%)/52 (46\%) 1,483 (49\%)/1,546 (51\%) 0.294b 0.90 0.61–1.32 0.58
Fall as the cause of the admission 48 (42\%) 1,206 (40\%) 0.627b 1.04 0.68–1.58 0.86
Operation during hospitalization 92 (81\%) 2,215 (73\%) 0.084b 1.38 0.85–2.24 0.20
Days in hospital 7.0 (1–164) 4.0 (0–56) ,0.001c 1.08 1.05–1.10 ,0.001
Notes: The results are given as number (proportion), median (range), and Or with 95\% CI. alogistic regression analysis with faller as the dependent variable and all the
variables in the table as covariates; bFisher’s exact test; cMann–Whitney U-test.
Abbreviations: CD, control department; ID, intervention department.
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røyset et al
Table 3 Main variables in the two departments before and after the intervention
Variables ID
before
ID
after
Statistics,
P-values
CD
before
CD
after
Statistics,
P-values
ID vs CD
before,
P-values
ID vs CD
after,
P-values
Difference in
change (95\% CI)
Statistics,
P-values
Faller, n
(\%)
37/734
(5.04)
31/735
(4.22)
0.460a 25/811
(3.08)
21/863
(2.43)
0.456a 0.052a 0.048a 0.17\% (-2.49 to 2.84) 0.90b
Teamwork
climate,c
mean (sD)
77 (18) 77 (13) 0.986d 81 (13) 75 (16) 0.130d 0.266d 0.609d 6.3 (-4.6 to 17.3) 0.26e
safety
climate,f
mean (sD)
74 (18) 77 (16) 0.408d 80 (17) 72 (18) 0.094d 0.195d 0.201d 11.3 (-0.8 to 23.5) 0.07e
Patient-
perceived
safety,g
mean (sD)
91 (16) 88 (19) 0.312d 83 (18) 86 (17) 0.563d 0.052d 0.614d -5.8 (-16.8 to 5.2) 0.30e
Notes: The number of fallers, the patient safety culture, and the patient-perceived safety in the two departments before and after the intervention with comparisons between
the time points and comparisons of the changes from before to after between the departments are shown. A positive difference in the changes is in favor of the ID. The
results are given as number (proportion in \%); mean (sD), and differences in the changes of proportions with 95\% CI. aFisher’s exact test; bgeneralized linear model for a
binary outcome; cnumber of subjects in the ID department before and after the intervention were 37 and 39, respectively, and in the CD 27 both before and after. dstudent’s
t-test. elinear regression. fnumber of subjects in the ID department before and after the intervention were 36 and 39, respectively, and in the CD 26 and 27, respectively.
gnumber of patients in the ID department before and after the intervention were 62 and 76, respectively, and in the CD 26 and 33, respectively.
Abbreviations: CD, control department; ID, intervention department.
Figure 2 Changes from before to after the intervention.
Notes: The four parts of the figure show: (A) the proportions of fallers (\%); (B) the teamwork climate (mean); (C) the safety climate (mean); (D) the patient-perceived
safety before and after the intervention in the departments with and without the intervention. The text gives the differences in the changes between the departments from
before to after the intervention; positive values indicate changes in favor of the intervention department.
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151
effects of a fall prevention program in elderly
column “Difference in change”). Figure 2A–D shows the
results with the differences in changes between the depart-
ments from before to after the intervention.
Discussion
We observed no differences in the changes in the faller rates,
patient safety culture, or patient-perceived safety from before
to after the intervention between the two departments and
conclude that the fall intervention had no clinically significant
effect at the time of observation. An initial temporary effect
during the implementation period might have been missed
due to the long period between the two registrations (1 year).
The fall rate in this study (7.3 falls per 1,000 patient days
in hospital) was in accordance with other studies on elderly
patients.6,8 A more conscientious registration of falls in the
medical records in the ID is the most likely explanation of
the higher faller rate in this department compared with the
CD. Patients with falls were older and had more days in
the hospital, but only days in hospital was an independent
predictor of fall. It is unknown if the fall caused prolonga-
tion of the stay in the hospital or if frail patients have more
extended stays and more falls. Independent of the causation,
patients with long stays should receive extra preventive inter-
ventions and surveillance. Both older age and length of stay,
independent of injury caused by the fall, have been associated
with fall in other studies.23,24 Risk factors associated with
falls in other studies, but not in this one, are previous falls
and gender.24,25 Information about falls over a longer period
before the admission was not available. This information and
not only fall as the cause of admittance could have been a
predictor of falls.
The lack of effect on the faller rate …
Observational Study Medicine
®
OPEN
Interventions aimed at lo
neliness and fall
prevention reduce frailty in elderly urban
population
Sanja Ožić, MPHa, Vanja Vasiljev, MSc, PhDb,c, Vanja Ivković, MD, PhDc,d,
∗
,
Lovorka Bilajac, MSc, PhDb,e, Tomislav Rukavina, MD, PhDb,c,e
Abstract
Frailty is a pronounced symptom of aging associated with multiple comorbid states and adverse outcomes. The aim of this study was
to evaluate the impact of 2 interventions, one based on prevention of falls and the other on prevention of loneliness, on total frailty and
dimensions of frailty in urban community-dwelling elderly as well as associations with independent living.
This prospective interventional study followed up 410 persons aged 75 to 95. The participants of the control and intervention
groups were monitored through a public health intervention programme. The level of frailty was measured by the Tilburg Frailty
Indicator (TFI) questionnaire and the factors of independent living were analyzed using validated questionnaires.
After 1 year, physical frailty measured in the control group showed a statistically significant increase (r=�0.11), while in the
intervention groups physical frailty did not increase (both P>.05). Psychological frailty measured after 1 year in the control group was
significantly higher (r=�0.19), as well as in the group where the public health interventions to reduce loneliness were carried out (r=�
0.19). Psychological frailty did not increase in the group in which public health interventions to prevent falls were carried out, and
social frailty did not increase at all in the study period. The total level of frailty in the control group after 1 year was significantly
increased (r=�0.19), while no increase was seen in the overall frailty in the intervention group. Multivariate analysis has shown that
both interventions where independently associated with lower end frailty. Additionally, higher baseline frailty and visit to a physician in
the last year were positively associated with higher end-study frailty level, while higher number of subjects in the household and higher
total psychological quality of life (SF-12) were independently associated with lower end-study frailty. Only in the prevention of falls
group there was no increase in restriction in the activities of daily living throughout study follow-up.
Public health interventions to prevent falls and to prevent loneliness have a positive effect on the frailty and independent living of the
elderly living in their own homes in an urban community.
Abbreviations: ADL = activities of daily living, GARS = Groningen Activity Restriction Scale, IADL = instrumental activities from
daily living.
Keywords: elderly persons, frailty, independent living, public health interventions
1. Introduction
Frailty is perceived as a geriatric syndrome which is a reflection
and consequence of the dysfunction of several organ systems.[1–3]
Editor: Yi Zhu.
The authors have no conflicts of interest to disclose.
a Zagreb Holding, City of Zagreb, b Department of Social Medicine and
Epidemiology, Faculty of Medicine, c Department of Public Health, Faculty of
Health Sciences, University of Rijeka, d Department of Nephrology, Hypertension,
Dialysis and Transplantation, University Hospital Centre Zagreb, e Educational
Institute of Public Health of the Primorje-Gorski Kotar County, Croatia.
∗
Correspondence: Vanja Ivković, Faculty of Health Sciences, University of Rijeka,
Viktora Cara Emina 5, 51000 Rijeka, Croatia (e-mail: [email protected]).
Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc.
This is an open access article distributed under the terms of the Creative
Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is
permissible to download, share, remix, transform, and buildup the work provided
it is properly cited. The work cannot be used commercially without permission
from the journal.
How to cite this article: Ožić S, Vasiljev V, Ivković V, Bilajac L, Rukavina T.
Interventions aimed at loneliness and fall prevention reduce frailty in elderly urban
population. Medicine 2020;99:8(e19145).
Received: 2 September 2019 / Received in final form: 22 December 2019 /
Accepted: 10 January 2020
http://dx.doi.org/10.1097/MD.0000000000019145
1
While no common and universally accepted definition exists, it is
most commonly defined as a state associated with increased
vulnerability to adverse outcomes due to the decline in reserve
and functions in multiple physiological systems.[4] Studies in
Europe which examined overall (defined as physical or
psychosocial) frailty or frailty defined as complex phenotype
point to the category of “severely frail,” which includes between
1/3 and 1/2 of elderly persons living in the European states.[5,6]
Two recent meta-analyses presented data on epidemiology of
frailty. Meta-analysis by O’Caoimh et al[7] which analyzed data
on frailty, defined using any definition, irrespective of the method
of data collection or instrument used, from 68 unique datasets
with data from 22 European countries showed that overall
prevalence of frailty in the elderly population is 18\%, being 12\%
in community-dwelling elderly and 45\% in non-community
based studies. The other meta-analysis by Siriwardhana et al[8]
which examined the prevalence of frailty and prefrailty measured
by any assessment method among community-dwelling older
adults in low-income and middle-income countries showed that
the prevalence of frailty varied from 3.9\% in China to 51.4\% in
Cuba, while the prevalence of prefrailty ranged from 13.4\% in
Tanzania to 71.6\% in Brazil. Additionally, demographic data on
aging indicate that the number of elderly persons with frailty will
increase, which is why frailty is defined as a priority in public
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Ožić et al. Medicine (2020) 99:8 Medicine
health and health care system for the elderly.[9,10] In cohort
studies, it was found that the prevalence of frailty defined by
various methods ranges from 4\% to 59\% but there is a significant
difference between various methodological approaches and there
are ambiguities in comparing data from different geographic
areas.[5,6]
The clinical picture of frailty in the elderly is characterized by an
increased vulnerability caused by reduced functional abilities in all
physiological systems, which results in the reduced ability to face
the everyday or acute stressors.[11–14] Frail elderly persons are
classified as vulnerable social groups because of the effects on their
quality of life, the institutionalized care, and unwanted health and
death outcomes. Especially vulnerable are elderly persons with
concomitant chronic diseases, exposed to acute infections or acute
confusion and those who were exposed to falls.[15–18]
In this study of frailty among the elderly, an integrative model of
frailty based on a multidimensional approach was used, with an
estimation of physical, psychological, and social dimensions of
frailty.[19] Research shows that most of the elderly in European
countries prefer to remain independent and continue to live in their
own homes.[20,21] Numerous support programmes help elderly
persons to stay in their homes and remain independent as long as
possible,[21,22] because, according to the research, most of the elderly
in Europe are still in good condition and capable of living
independently.[23] However, according to the research data, to be
capable to live independently at home an elderly person needs a
certain state of mental health and satisfactory functional capaci-
ty.[24,25] Therefore, in this research of independent living of the
elderly, focus has been placed on the analysis of the functional
capacity of theelderly.The recognitionoffrailty inthe elderly andan
early intervention within the framework of primary health care are
important for the care of the elderly. Interventions aiming to reduce
frailty contribute tochanges inthe levelsof frailtyandaffectthe costs
for the elderly persons’ health care. The rationale for designing and
studying interventions aiming to prevent the frailty in the elderly has
shown the efficacy of combined interventions.[4,26] However, while
it has been shown that frailty is associated with higher risk of falls
and more pronounced loneliness, there is still insufficient evidence of
theeffectofinterventionsaimedatdecreasingriskoffallsandlevelof
loneliness on frailty. Faber et al[27] examined the effects of a 20-week
moderate intensity group-exercise program on falls in nonfrail, pre-
frail, and frail individuals. The randomized trial showed that frailty
was a strong effect modifier and that, surprisingly, the intervention
had opposite effects in different frailty classifications, non-
significantly reducing fall risk in pre-frail subjects and significantly
increasing fall risk in frail subjects and the study concluded that
physical interventions to reduce falls should be targeted to nonfrail
and pre-frail subjects and could be counterproductive and increase
falls in frail persons. Moreover, there is a clear association between
loneliness and physical and total frailty[28–30] and different activities
have been shown to mediate the relationship between loneliness and
frailty[31] so our hypothesis was that interventions aimed at
loneliness and risk of falls reduce the level of frailty in communi-
ty-dwelling elderly urban population.
2. Methods
2.1. Study design and participants
Enrolment for this prospective interventional study was
conducted between January 2015 and September 2017. Study
was conducted in city of Rijeka which is an urban environment in
2
Primorje-Gorski Kotar County with a population of some
128,000 of which 19.74\% over 65 years of age and an aging
index of 169.8 (data from Croatian Bureau of Statistics). Pilot site
Rijeka was 1 of 5 pilot sites included in the project Urban Health
Centres Europe (UHCE) for testing preventive integrated health
and social care approach for community-dwelling elderly
persons. According to last census data, aging index of Rijeka
(169.8) is higher than that of state capital Zagreb (111.6) and
also Croatia (116.3). According to latest Eurostat data the aging
index of 28 members of European Union is 125.8 (data from:
https://ec.europa.eu/eurostat). This higher aging index makes
Rijeka an especially suitable location for testing interventions
aimed at elderly population. However, the same interventions
carried here are equally implementable in other urban communi-
ties with different ageing indices.
This study was approved by the Ethical Committee - Faculty of
Medicine University of Rijeka (IRB No:07–04–2014; 2170–24–
01–14–02). All subjects provided informed consent. The study
included 410 elderly persons living in their own homes, 283
women and 127 men aged median 80 years (min–max range 75–
95). Inclusion criteria were: age 75 years or older, independent
living, expected to be able to participate in the study for at least 6
months according to the assessment of their community nurse. The
following exclusion criteria were defined: permanent residence
outside the urban community, dementia or psychosis, accommo-
dation in an institution for old and helpless persons, persons who
are not able to comprehend the basic information on the study or
not able to cognitively evaluate the risks and benefits of
participation and are not expected to be able to make an informed
decision regarding participation in the study. At the beginning of
the study frailty, multiple morbidity, polypharmacy, visits to
doctors, and the hospitalization of the elderly were evaluated.
Upon these data the clinical profile, pathological risk, and residual
skills of the elderly were determined. Participants gave their
informed consent to participate in the research for the period of 1
year. Before and after the public health intervention programme
was conducted the visiting nurses interviewed participants in the
control and the intervention group. Physicians, physiatrists, and
physiotherapists were involved in the implementation of the public
health intervention programme to prevent falls. Along with the
visiting nurses, also medical and health professionals of the
Department for Social Medicine of the Faculty of Medicine of the
University and Rijeka and the Department for Public Health of the
Faculty of Health Studies of the University of Rijekaparticipated in
the public health intervention to reduce loneliness.
2.2. Measurement
Frailty was measured with the Tilburg Frailty Indicator (TFI)
questionnaire, which was developed and validated for primary
health care use.[32,33] TFI measures physical frailty (including
components: perception of physical health, inexplicable weight
loss, walking difficulties, difficulty in maintaining balance,
hearing impairments, visual impairments, lack of strength in
the arms, and physical fatigue), psychological frailty (including
components: memory problems, the feeling of being lost, nervous
or anxious, inability to deal with problems), and social frailty
(including components: perception of life, lack of social
relationships, and lack of social support). The independent
living analysis is based on measurements with the Groningen
Activity Restriction Scale which includes activities of daily living
(ADL) items on everyday life activities such as clothing, feeding,
https://ec.europa.eu/eurostat
Ožić et al. Medicine (2020) 99:8 www.md-journal.com
hygiene, and instrumental activities from daily living (IADL). The
instrument on everyday life activities essential to maintaining a
certain quality of life such as driving, communication manage-
ment, financial management, preparing meals, going shopping,
and in addition the total restriction of activities /GARS.[34]
2.3. Interventions
The public health intervention “fall prevention” consisted of 2
activities: determining and eliminating the risk of falls in the
intervention participants home and organized custom exercise
twice a week. The nurses at the participants’ home pointed out
the risky obstacles in the space, educating the participants about
safe movement in old age. Physiotherapists and physiotherapy
students designed and maintain custom exercise for elderly at 4
locations in the City of Rijeka.
The public health intervention “reducing loneliness” consisted
of organized weekly and monthly education and workshops for
the elderly, which were also conducted over a period of 1 year.
Weekly trainings on “healthy aging” were conducted in
cooperation elderly NGOs. Monthly workshops were provided
as part of the program activities Healthy City Rijeka.
Elderly persons resident in the Western part of the City of
Rijeka were included in the intervention groups, and the control
group consisted of the elderly resident in the Eastern part of the
City of Rijeka. Participants were interviewed at the beginning of
the research and participants from the Western part of the city
were free to choose and participate in 1 of the 2 interventions
according to their preference.
2.4. Statistical analysis
Descriptivestatisticsaresummarizedasfrequencies(percentages)for
categorical variables. The normality of the distribution of continu-
ous variables was tested with the Kolmogorov–Smirnov test. In all
cases, median and interquartile ranges were used as central tendency
and scattering measures, while nonparametric statistical tests were
used to test differences within and between the studied groups of
Table 1
Baseline demographic characteristics of subjects.
Total sample No interven
n (\%) n (\%)
Sex
Male 127 (31.0) 60 (28.8
Female 283 (69.0) 148 (71.2
Age (median/IQR) 80 (77–84) 81 (78–8
Education
Less than high school 175 (42.8) 92 (44.2
High school 190 (46.5) 96 (46.2
College or more 44 (10.8) 20 (9.6)
Household income (per month)
Less than 2600 HRK
∗
125 (30.8) 64 (30.9
From 2601 to 3500 HRK 109 (26.8) 56 (27.1
From 3501 to 4500 HRK 64 (15.8) 32 (15.5
From 4501 to 5500 HRK 48 (11.8) 24 (11.6
More than 5500 HRK 60 (14.8) 31 (15.0
Study group
No intervention 208 (50.7)
Prevention of falls 91 (22.2)
Reduction of loneliness 111 (27.1)
Variables education had 1 missing value and Household income had 4.
∗
1 HRK equals approximately 0.15 USD.
3
participants. The McNemar test was used for the differences with
regardtothe categoricalvariablesbetweenthe 2meteringpointsand
the Wilcoxon test of equivalent pairs was used to compare the other
aging parameters between two time points expressed as continuous
variables. In the case of statistically significant differences, these
differences were additionally examined by the post-hoc Mann–
Whitney U test series with Bonferroni correction of the level of
statistical significance. Univariate relationship between frailty and
independent living was investigated using the Spearman correlation
coefficient. Linear multiple regression was used to predict the factors
significant for frailty after the interventions. We have scoped a
number of large intervention studies in frailty and found that the
effect sizes of the interventions (intragroup differences) on total
frailty (measured using Tilburg Frailty Indicator [TFI] which we also
used in this study) range from Cohen d of 0.5 to 0.6, which is
consistent with our hypothesis of small to medium effect size. We
have thus taken a conservative estimate of Cohen d of 0.45
(corresponding to small effect size), 2-tailed hypothesis a=0.05 and
b=0.80 which resulted in a sample size of 79 subjects per group. We
have planned to enrol 158 patients in the control group and 79
patients in each intervention group for a total of 316 subjects in the
study. The level of statistical significance was determined at P<.05
(2-tailed). All data were analyzed with the IBM SPSS v23 (Armonk,
NY: IBM Corp., USA).
3. Results
A total of 410 elderly subjects were included in the study. Among
the active elderly persons, 91 (22.2\%) were involved in the public
health intervention programme to prevent falls, while 111
(27.1\%) of elderly persons were involved in the intervention
programme to prevent loneliness. The control group with
inactive elderly persons numbered 208 (50.7\%) subjects.
Observing the respondents’ marital status, the first point of
measurement showed that most of them were widowers (210/
410, 51.2\%), followed by married persons (176/41,042, 9\%),
persons living in living extramarital relationships (1/410, 0.2\%),
singles (11/410, 2.7\%), and divorced (12/410, 2.9\%) (Table 1).
tion Prevention of falls Reduction of loneliness
n (\%) n (\%)
) 25 (27.5) 42 (37.8)
) 66 (72.5) 69 (62.2)
4) 79 (77–82) 81 (78–85)
) 42 (46.2) 41 (37.3)
) 40 (44.0) 54 (49.1)
9 (9.9) 15 (13.6)
) 33 (36.7) 28 (25.7)
) 20 (22.2) 33 (30.3)
) 13 (14.4) 19 (17.4)
) 12 (13.3) 12 (11.0)
) 12 (13.3) 17 (15.6)
http://www.md-journal.com
Table 2
Marital status, household, and alcohol use.
Baseline End
n (\%) n (\%) P
Partner
Yes 177 (43.2) 154 (37.6) <.001
No 233 (56.8) 256 (62.4)
Number of persons in household
(median and interquartile range)
2 (1–2) 2 (1–2) .19
Smoking
Yes 38 (9.3) 19 (4.6) .001
No 372 (90.7) 391 (95.4)
Frequency of alcohol use
Never 265 (64.6) 296 (72.2) <.001
At least sometimes 145 (35.4) 114 (27.8)
Ožić et al. Medicine (2020) 99:8 Medicine
At the beginning of the study there were 38 (9.3\%) smokers,
while 145 (35.4\%) of respondents consumed alcohol. At the
beginning of the study 177 (43.2\%) of participants had a partner.
There was statistically no significant difference between begin-
ning and end of study concerning the number of persons living in
the household (P=.19). The proportion of smokers between the 2
time points also decreased (P=.001), as well as the proportion of
elderly persons who at least occasionally consume alcohol
(P<.001) (Table 2).
After 1 year, physical frailty measured in the control group
showed a statistically significant increase (z=�2.25; P=.024;
r=�0.11), while in the intervention groups physical frailty did
not increase (both P>.05). Psychological frailty measured after 1
year in the control group was significantly higher (z=�3.87;
P<.001; r=�0.19), as well as in the group where the public
health interventions to reduce loneliness were carried out (z=�
2.07; P=.039; r=�0.19). Psychological frailty did not increase
in the group in which public health interventions to prevent falls
were carried out, and social frailty did not increase at all in the
study period. The total level of frailty in the control group after 1
year was significantly increased (z=�3.84, P<.001, r=�.19),
while no increase was seen in the overall frailty in the intervention
groups (Table 3).
Table 3
Measurement of total, physical, psychological, and social frailty in
study groups at the beginning and end of study.
Group Baseline End P
Physical frailty
No intervention 4 (3–5) 5 (3–6) .024
Prevention of falls 3 (2–5) 3 (2–5) .14
Reduction of loneliness 3 (2–4) 3 (1–4) .49
Psychological frailty
No intervention 2 (1–2) 2 (1–3) <.001
Prevention of falls 1 (0–2) 2 (1–3) .06
Reduction of loneliness 1 (0–2) 2 (0–3) .039
Social frailty
No intervention 1 (1–2) 1 (1–2) .54
Prevention of falls 0 (1–1) 1 (0–2) .98
Reduction of loneliness 1 (1–2) 1 (1–2) .96
Total frailty
No intervention 7 (5–9) 8 (6–10) <.001
Prevention of falls 5 (4–8) 6 (3–8) .80
Reduction of loneliness 6 (3–8) 6 (3–8) .52
Values given as median (interquartile range).
4
When assessing between group differences we compared
differences in change of frailty over time and found that the 3
groups differed in the rate of change, that is, physical frailty
increased more in the control group than in prevention of falls
group (P=.045), while there were no differences among the
control group and prevention of loneliness group or between the
2 intervention groups (P=.24 and P>.99, respectively).
Additionally, there were no statistically significant between
group differences in the rate of change of total, psychological, or
social frailty (all P>.05), but total frailty showed a non-
significantly higher rate in the control group compared with the 2
intervention groups (P=.08).
The analysis of independent living showed that after 1 year in
the control group there was a statistically significant increase in
ADL values, along with restrictions in daily activities (z=�6.35,
P<.001, r=�0.32). The same was observed in the group in
which public health interventions to reduce loneliness were
carried out (z=�2.51; P=.012; r=�0.17). In the group in which
the intervention programme to reduce physical frailty (prevention
of falls) was carried out, there was no increase in ADL restriction
values after 1 year in the respondents’ daily activities. The IADL
measurements relating to the capability of carrying out more
complex tasks related to life quality has shown an increase in the
IADL restriction values in all 3 of the study groups: the control
group (z=�7.52, P<.001, r=�0.37), the group with inter-
ventions to reduce loneliness (z=�5.57; P<.001; r=�0.38), and
the group with interventions to prevent falls (z=�3.20; P=.001;
r=�0.24). In conclusion, the results of the total GARS
restrictions showed the highest increase in the control group
(z=�7.58; P<.001; r=�0.38), a slightly smaller increase in the
group with interventions to reduce loneliness (z=�4.98;
P<.001; r=�0.35), and the lowest increase was found in the
group with interventions to prevent falls (z=�2.45; P=.014;
r=�0.35). In determining the relationship between frailty and
independent living in all groups of participants, a statistically
significant connection of frailty with both forms of restriction was
obtained, ADL and IADL—as well as in the overall result of
GARS restrictions. All of these correlations were positive, which
means that a higher level of frailty is associated with a higher
degree of ADL restrictions in daily activities and IADL complex
tasks related with the quality of life (Tables 4 and 5).
The variables included in the predictive multivariate model of
frailty in the elderly were as follows: demographic characteristics,
Table 4
Restrictions in activities of daily living by intervention and time
point.
Baseline End
Median (IQR) Median (IQR) P
Activities of daily living (ADL)
No intervention 16 (12–22) 19 (14–24) <.001
Prevention of falls 14 (12–20) 15 (12–20) .060
Reduction of loneliness 13 (11–18) 14 (11–19) .012
Instrumental activities from daily living (IADL)
No intervention 12 (8–18) 15 (11–21) <.001
Prevention of falls 10 (7–15) 12 (8–19) .001
Reduction of loneliness 9 (7–14) 13 (8–17) <.001
Groningen Activity Restriction Scale (GARS)
No intervention 28 (20–40) 33 (25–44) <.001
Prevention of falls 25 (19–35) 28 (19–39) .014
Reduction of loneliness 22 (18–31) 28 (21–37) <.001
Table 5
Correlation between frailty and activities of daily living.
Baseline End
rS P rS P
Activities of daily living (ADL)
No intervention 0.62 <.001 0.62 <.001
Prevention of falls 0.48 <.001 0.58 <.001
Reduction of loneliness 0.57 <.001 0.55 <.001
Instrumental activities from daily living (IADL)
No intervention 0.57 <.001 0.57 <.001
Prevention of falls 0.47 <.001 0.48 <.001
Reduction of loneliness 0.57 <.001 0.29 .002
Groningen activity restriction scale (GARS)
No intervention 0.62 <.001 0.61 <.001
Prevention of falls 0.48 <.001 0.53 <.001
Reduction of loneliness 0.59 <.001 0.42 <.001
rS=Spearman correlation coefficient.
Ožić et al. Medicine (2020) 99:8 www.md-journal.com
initial level of frailty, public health interventions, quality of life,
independent living, and the use of health care. The tested
variables explained 56.5\% of the variance in the second time
point of measurement (R2=0.565, F=24.91, df1=19, df2=
365, P<.001). Multivariate analysis also shown that both
interventions where independently associated with lower end
frailty (both P<.05). Additionally, higher baseline frailty and
visit to a physician in the last year were positively associated with
higher end-study frailty level, while higher number of subjects in
the household and higher total psychological quality of life (SF-
12) were independently associated with lower end-study frailty
(all P<.05) (Table 6). Total frailty was included in the final
regression model due to potential multicollinearity problem if
physical, psychological, and social frailty are included separately
in one regression model. However, testing this potential model
with all 3 dimensions of frailty included showed that it did not
Table 6
Multivariate linear regression analysis showing predictors of final/
end study frailty (N=385).
B SE (B) b P
Baseline frailty 0.28 0.05 0.27 <.001
Female sex 0.12 0.31 0.02 .689
Age 0.00 0.03 0.01 .871
Education �0.36 0.24 �0.06 .138
Marital status 0.11 0.28 0.02 .702
Household income �0.44 0.25 �0.07 .076
Number of persons in household �0.36 0.12 �0.11 .003
Smoking 0.34 0.50 0.02 .499
Alcohol intake 0.21 0.27 0.03 .431
Prevention of falls (intervention) �0.72 0.28 �0.10 .010
Prevention of loneliness �0.56 0.27 �0.08 .039
Total physical quality of life, SF-12 �0.04 0.04 �0.07 .340
Total psychical quality of life, SF-12 �0.16 0.03 �0.32 <.001
Activities of Daily Living, ADL 0.05 0.03 0.12 .107
Instrumental Activities from Daily Living, IADL 0.01 0.04 0.01 .851
Visit to physician in the last year 0.87 0.35 0.09 .014
Need for help in house 0.38 0.37 0.04 .303
Need for help in conducting hygiene �0.86 0.47 �0.08 .070
Hospitalization �0.02 0.31 0.00 .944
b=standardized regression coefficient, B=non-standardized regression coefficient, SE B=standard
error of B.
5
improve on the final model with total frailty included (R21 vs R
2
2,
0.541 vs 0.542, respectively).
4. Discussion
The study analyzed the physical, psychological, and social nature
of frailty in order to get a comprehensive view on the frailty of the
elderly, and in order to do so an integrated conceptual model of
frailty was implemented.
While few well-designed trials were designed specifically to
target incidence and characteristics of pre-frailty and frailty in the
elderly, some trials have shown success. Frailty Intervention Trial
(FIT) which recruited 216 persons and showed that a
multifactorial, interdisciplinary approach tailored for each
individual subject and targeted specifically to reduce the frailty
component present on baseline exam consisting of dietetic
evaluation and nutritional intervention, measures to reduce social
isolation and physiotherapy and exercise regime significantly
reduced frailty in a 12-months period.[35,36] Recent randomized,
open label, controlled trial by Serra-Prat et al[37] showed that
nutritional assessment and potential intervention and physical
intervention consisting of aerobic, strengthening, balance, and
coordination exercises are …
STUDY PROTOCOL Open Access
A study protocol of a randomised
controlled trial to measure the effects of an
augmented prescribed exercise programme
(APEP) for frail older medical patients in the
acute setting
Ruth McCullagh1*, Eimear O’Connell2, Sarah O’Meara3, Ivan Perry4, Anthony Fitzgerald4, Kieran O’Connor5,
N. Frances Horgan6 and Suzanne Timmons1
Abstract
Background: Older adults experience functional decline in hospital leading to increased healthcare burden and
morbidity. The benefits of augmented exercise in hospital remain uncertain. The aim of this trial is to measure the
short and longer-term effects of augmented exercise for older medical in-patients on their physical performance,
quality of life and health care utilisation.
Design & Methods: Two hundred and twenty older medical patients will be blindly randomly allocated to the
intervention or sham groups. Both groups will receive usual care (including routine physiotherapy care) augmented
by two daily exercise sessions. The sham group will receive stretching and relaxation exercises while the intervention
group will receive tailored strengthening and balance exercises. Differences between groups will be measured at
baseline, discharge, and three months. The primary outcome measure will be length of stay. The secondary outcome
measures will be healthcare utilisation, activity (accelerometry), physical performance (Short Physical Performance
Battery), falls history in hospital and quality of life (EQ-5D-5 L).
Discussion: This simple intervention has the potential to transform the outcomes of the older patient in the acute
setting.
Trial registration: ClinicalTrials.gov Identifier: NCT02463864, registered 26.05.2015.
Keywords: Frail, Medical, Inpatients, Exercise, Physiotherapy, Length of stay
Background
Older medical patients can experience a prolonged acute
hospital stay and functional decline
In Ireland in 2011, 11.6 \% of the population was aged
65 years and over [1], and this is set to rise to 22 \% by
2041 [2]. Extended periods of poor health are predicted
with this longevity [2]. Older patients occupy most acute
hospital beds and most frequently experience a
prolonged length of stay (of greater than 30 days) [3],
functional decline, high re-admission rates, falls, and
institutionalisation [4]. Frailty is described as a geriatric
syndrome with reduced capacity of the individual to re-
sist stress and includes characteristics of slow mobility,
low physical activity (PA) and energy levels [5]. Inactivity
has been identified as a major determinant in the onset
of frailty and exercise has been found to prevent or slow
down this decline [6]. Therefore, maintenance of older
adults’ functional independence while in hospital is of
utmost importance.* Correspondence: [email protected]
1Centre for Gerontology & Rehabilitation, University College Cork, Cork,
Ireland
Full list of author information is available at the end of the article
© 2016 McCullagh et al. 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.
McCullagh et al. BMC Geriatrics (2016) 16:79
DOI 10.1186/s12877-016-0252-z
http://crossmark.crossref.org/dialog/?doi=10.1186/s12877-016-0252-z&domain=pdf
https://clinicaltrials.gov/ct2/show/NCT02463864
mailto:[email protected]
http://creativecommons.org/licenses/by/4.0/
http://creativecommons.org/publicdomain/zero/1.0/
Physical activity levels and exercise intervention for
medical patients in hospital
Recent evidence has shown that older medical patients
walk an average of 1534 (±112) steps per day in hospital
and that prolonged length of stay was inversely associ-
ated with daily step count, even when adjusted for age,
gender and physical performance on admission [7]. Simi-
larly, Fisher et al. [8] found that older adults, who increase
their walking activity by 600 steps on the second day of
observation, were discharged home two days earlier.
These findings suggest that low physical activity in hos-
pital may directly influence length of stay and supports
the theory that patients should exercise and remain active
in the acute setting. Exercise programmes in hospital have
been delivered independently or as a component of a
multidisciplinary intervention and have been shown to
improve physical performance, quality of life, reduce falls
incidence and reduce healthcare utilisation [9–13].
The evidence of effectiveness of augmented exercise in
hospital
To date, small benefits from augmented exercise on func-
tion and healthcare utilisation have been found. A system-
atic review found limited benefits from exercise as part of a
multidisciplinary service on function, length of stay and dis-
charge destination for acutely hospitalised older medical in-
patients [14]. Three trials investigated the benefits of add-
itional exercise alone [15–17]; none of which showed a sig-
nificant improvement on length of stay. The authors
suggested that the findings might have been weakened by
using inappropriate outcome measures, recruitment of pa-
tients who had good baseline physical performance levels,
and poor adherence to the exercise intervention that was
being prescribed.
Rationale for the trial and protocol
To date, additional exercise has not been found to shorten
frail older patients’ hospital stay but the issues reported by
previous authors may have weakened the results. To ad-
dress these issues, the proposed protocol differs from previ-
ous studies in key parameters. A qualified physiotherapist
will deliver and support the exercise sessions. Only patients
who are less able to maintain physical activity will be re-
cruited; those who need a walking aid and/or physical as-
sistance on admission. Those who are unable to walk with
assistance will be excluded from the trial. The Short
Physical Performance Battery (SPPB) and walking speed will
be used to measure physical performance, as these were
previously found to be sensitive and appropriate for the
study group [13]. The control arm will include sham exer-
cises, to control for the considerable increase in patient-
physiotherapist contact time. Finally, independent physical
activity (usually walking) will be promoted outside the exer-
cise sessions, in the intervention group.
Therefore, the aim of this study is to measure the ef-
fects of an augmented prescribed exercise programme
for frail older medical inpatients on their physical per-
formance, quality of life and healthcare utilisation.
Methods
Design and study size
The study is a single blind randomised controlled trial set
in an acute 350-bedded teaching hospital. Power calcula-
tions based on the results of a pilot study indicated that a
sample size of 200 (100 patients in each arm) would be re-
quired. To allow for an expected attrition rate of 5 \% [18],
two hundred and twenty medical patients aged 65 years
and over are randomly allocated to either the intervention
or sham arm in a ratio of 1:1. (see Fig. 1). The study has
been approved by the Clinical Research Ethics Committee
of the Cork Teaching Hospitals. (ECM 3 (vv) 13/10/15).
Selection of participants and allocation
All suitable patients are screened and if eligible, are in-
formed of the study and written consent is sought. The in-
clusion criteria are: medical patients aged 65 and over, who
have been admitted from home and initially planned for
discharge home, whose anticipated length of stay is greater
than 3 days, and who require a mobility aid or assistance
to walk. The exclusion criteria are: patients who have been
an in-patient for more than 48 h prior to screening, who
are unable to follow commands in the English language,
unable to exercise with the assistance of one person only,
bed or chair-bound at baseline, admitted with an acute
psychiatric condition, require active end-of-life or critical
care or when exercise is contraindicated.
To ensure adequate treatment time is given to each pa-
tient, recruitment is paused when there are five patients ac-
tive in the trial. Based on the hospital’s usual length of stay,
this usually results in one patient recruited each weekday. If
more than one patient is eligible for the study on one day,
they are approached in chronological order of admission.
The patients are randomly allocated to either the inter-
vention (APEP) or control group. A computer-generated
random allocation sequence is used. Block randomisation is
applied (in groups of approximately 50 patients). Post hoc
power analysis will be calculated when the first seventy-five
patients have completed the trial.
Roles of the researchers
Randomisation and data entry is completed by the Re-
search Assistant (RA, SO’M). Screening, recruitment, base-
line measurements and all exercise sessions are completed
by the Principal Investigator (PI, RMcC). The discharge
and follow-up assessments are completed by the blinded
Research Physiotherapist (RPT, EO’C), who has no involve-
ment in either the allocation or intervention components
of the trial.
McCullagh et al. BMC Geriatrics (2016) 16:79 Page 2 of 7
Measurements
Patients are assessed within 48 h of admission, at dis-
charge and at three months following discharge. The
assessment tools are described in Table 1. Baseline data
includes demographics, co-morbidity, medication use
and home circumstances.
Fig. 1 Flowchart with details of the study design and flow of participants
McCullagh et al. BMC Geriatrics (2016) 16:79 Page 3 of 7
The primary outcome measure is length of stay, a key
healthcare utilisation metric. The secondary outcome mea-
sures includes patient-related measures: changes in physical
performance (SPPB, walking speed), and quality of life at
3 months following discharge, differences in physical activity
levels between groups in hospital (based on accelerometry
data) and re-admission rates over three months. The base-
line assessment is designed to capture frailty, co-morbidity
and disability. Measurements that are appropriate and quick
to administer have been chosen to limit patient fatigue.
Measurements of Co-morbidity and frailty
The Cumulative Illness Rating Scale Geriatrics (CIRS-G)
has been chosen as it measures chronic medical illness
burden with good reliability and is a validated tool both
as an indicator of health status and as a predictor of 18-
month mortality and hospitalisation [19]. The CIRS-G
has 14 categories, with a 0 to 4 grading system of im-
pairment in each organ system. The score may theoretic-
ally range from 0 to 56, with a higher score reflecting
greater impairment in several systems.
To measure frailty, the SHARE-FI [20] tool has been
chosen as it is a valid and simple measurement of frailty.
Five SHARE variables approximating Fried’s frailty defin-
ition are used: fatigue, loss of appetite, grip strength, func-
tional difficulties and physical activity. Scores range
between 2.7 to 13.4 and the SHARE-FI calculators (gender-
specific) are freely available on the web to interpret the level
of frailty [20].
The Six-Item Cognitive Impairment Test (6-CIT) will
be used to measure cognition as it is quick to administer,
its diagnostic accuracy is as high as the Mini-Mental
State Examination when used in the acute hospital set-
ting, and it is not sensitive to an educational level and
does require advanced language skills [21].
Measurements of disability
Physical Performance is measured using the Short Phys-
ical Performance Battery (SPPB), which includes walking
speed [22]. The SPPB has been chosen as it is quick,
practical and safe to use with this population. The scores
range from 0 (unable to stand independently,) to 12 (in-
dependent tandem balance for 10 s, able to walk 4 m
within 4.82 s and sit to stand 5 times in 11 s). Walking
speed is known to be a strong indicator of patients’
physical performance and is an independent predictor of
survival and institutionalisation [23]. All patients scoring
less than 1 on the SPPB will be eliminated from the study
to allow us to detect functional decline while in hospital.
Measurements of well-being, self-efficacy and self-
reported functional ability
Quality of Life will be measured using the EuroQol 5-
Domain 5-Level Scale (EQ-5D-5 L) [24] as it is well-
used and easy to administer. The five domains assessed
are mobility, self-care, usual activities, pain/discomfort,
anxiety/depression, and a visual analogue scale, ranging
from 0 to 100, to measure self-rated health status [24].
At baseline only, fear of falling is measured using the
Falls Efficacy Scale-International (FES-I) [25]. This tool
consists of 14 activity-related questions. The questions
aim to determine how concerned older adults are about
falling while performing these activities on a scale of 0
(not concerned at all) to 4 (very concerned).
The Nottingham Extended Activities of Daily Living
Scale (N-EADL) [26] is a self-reported tool to measure
the patients’ ability to complete 16 community-based ac-
tivities. On admission, patients are asked to report their
functional ability both pre-morbidly (before the onset of
the illness) and on admission (the day before they were
admitted) and again, at the three month follow-up as-
sessment. Patients can score 0 (unable to complete the
Table 1 Summary of the Measurements used in the Study
Domain On admission Discharge and 3 months
Medical Morbidity Cumulative Illness Rating Scale (CIRS-G [19]);
Total number of medications
Frailty SHARE- FI [20] Grip Strength (kgs)
Physical Performance Short Physical Performance Battery
(SPPB) (includes walking speed) [22]
SPPB [22] (includes walking speed)
Falls Efficacy and Self-Reported Functional Ability Number of Falls and injuries sustained Number of falls and injuries sustained
Falls Efficacy Scale – International (FES-I) [25] Nottingham Extended Activities of Daily
Living Scale (N-EADL) [26]
Nottingham Extended Activities of Daily
Living Scale (N-EADL) [26]
Cognition 6CIT [21] 6CIT [21]
Quality of Life EQ-5D-5 L [24] EQ-5D-5 L [24]
Physical Activity Accelerometers (Stepwatch Activity Monitor,
SAM) during hospitalisation only
McCullagh et al. BMC Geriatrics (2016) 16:79 Page 4 of 7
activity with/without help) or 1 (able to complete the
score with/without help). This has been used extensively
in older adult populations, including patients with stroke
and fallers [27,28].
Measurements of physical activity
All patients with good skin condition at the ankle are
asked to wear accelerometers (Stepwatch Activity Moni-
tors, SAM) to measure physical activity (step-count) in
the hospital. These devices have been validated in frail
older in-patients and can be worn in the shower, helping
compliance and successful data collection [29]. They are
capable of storing up to seven days of data without inter-
ruption using a 15 s epoch. They are attached on the
first day of recruitment and worn continuously while in
hospital or for the first seven days. All staff are informed
of their application. The accelerometry data will be ana-
lysed to measure
1. Changes in activity between groups.
2. Levels of physical activity compared to a recently
completed observation study (which assisted in
identifying those who were at risk/not at risk of
functional decline).
Procedure
Intervention and routine care schedule
Both groups receive usual multidisciplinary care. The med-
ical team refer patients to physiotherapy if required. It is
delivered, an average of three times weekly, by the clinical
ward physiotherapist and will be routine in nature. It con-
sists of assessment, discharge planning, exercise, provision
of aids and rehabilitation. Both the control and the inter-
vention groups also receive two augmented, twenty minute
to half-hour exercise sessions (tailored to the patient’s en-
durance), five days per week, delivered on a one-to-one
basis by the PI.
Consent, assessment and exercise procedure
Upon screening, the medical team are contacted to con-
firm that there is no medical contra-indication to exercise
for the patient. Eligible patients are informed of the study
verbally and given a copy of the patient information leaflet.
They give written informed consent to the study, including
access to their medical notes, assessment at baseline, out-
come and follow-up, and the twice daily exercise sessions.
If the patient is considered to be cognitively impaired by
the medical or nursing staff, the patients’ written consent
is augmented by verbal assent from their next of kin. Pa-
tients with severe confusion, who are unable to follow
commands, or are agitated, are not recruited to the study.
If recruited, patients are assessed (Time 1), and through
concealed allocation, randomly allocated to the control
group or the intervention group at that time. All recruited
patients, who consent to wearing the accelerometer and
with good skin condition at the ankle, are fitted with the
SAM to measure physical activity in hospital.
For those in the intervention (Augmented Prescribed Ex-
ercise Programme, APEP) group, their exercise programme
is prescribed to address their physical limitations identified
through the assessment. The exercises are chosen to
improve strength and balance, core stability, sit-to-stand
function, balance (in standing and walking), walking and
endurance. The intervention group are also actively encour-
aged to mobilise while in hospital, with assistance when ne-
cessary, and provided with walking aids initially, if required.
The sham exercise sessions for the control group are
not prescribed but consist of standardised stretching
and relaxation exercises.
All exercise sessions begin within 24 h of group alloca-
tion and continue until the day before discharge. Verbal
consent for each session is sought.
To ensure false step-count does not occur, the acceler-
ometer (SAM) is turned upside-down (in this position, it
is unable to record steps) when the patient is exercising at
the bedside, i.e., not walking, and returned to the upright
position before walking or at the end of the session.
Patient compliance, exercise prescription and session
duration is recorded. Within one day of planned dis-
charge, all patients are re-assessed and the accelerometer
(SAM) is removed from the patient by the RPT (Time 2;
see Table 1). Patients who are deemed for long-term care
(as they are unable to manage at home) or for end-of-
life care are re-assessed on the date that the decision is
made and those results are used.
The patients are reassessed at three months post dis-
charge, by the RPT (Time 3, see Table 1). New onset of
illness, physical performance, walking speed, quality of
life and self-reported functional ability is measured. Hos-
pital and Accident and Emergency utilisation since dis-
charge is recorded.
Safety, reporting of adverse events and serious adverse
events
The main adverse events anticipated in this study are skin
rashes from the accelerometer, and falls, cardiac ischaemia
or pulmonary embolism during exercise. All adverse events
are recorded using an adverse event recording work-
sheet, and causality to the study intervention is deter-
mined, in consultation with the treating physician, by a
study physician (KO’C). The Sponsor’s Clinical Research
Supporting Officer is notified electronically, within 24 h,
of any serious adverse event that occurs during the trial.
From a previous local longitudinal study, the Cork De-
mentia Study, the in-hospital mortality of this cohort is
expected to be approximately two per cent [18]. This pre-
dicts approximately 5 deaths of trial subjects. However,
the type of exercise involved is similar to usual care,
McCullagh et al. BMC Geriatrics (2016) 16:79 Page 5 of 7
patients with a contraindication to exercise will be ex-
cluded at source, and patients who are unwell on a par-
ticular day will not exercise.
Statistical analysis
The results will be analysed and presented as recom-
mended by the CONSORT guidelines [30]. The primary
outcome measure will be length of stay. This will be de-
scribed using Kaplan-Meier “survival” curves and the re-
sults between groups will be compared using a log-rank
test. Univariate and multivariate linear regression ana-
lysis will be used to determine differences in physical ac-
tivity in hospital and physical performance, quality of life
at discharge and three months post-discharge, and re-
admission rates at three months.
This analysis will help to define whether a simple
physiotherapy-led exercise intervention will shorten length
of stay, increase physical activity in hospital, limit functional
decline and readmission rates and improve quality of life in
frail older hospitalised patients.
Discussion
This study has been designed to measure the effects of an
augmented prescribed exercise programme for frail older
hospitalised patients. The study design is based upon re-
sults of an earlier pilot study and issues reported from
previously published studies. Therefore, this protocol dif-
fers from previous studies in three key areas: patient selec-
tion, intervention and outcome measurements.
Previous studies included some patients who were fully
independently mobile but de Morton et al. [31] found that
the intervention was most effective for those requiring an
aid or assistance to walk. For this reason, we will exclude
those who are independently mobile. For pragmatic rea-
sons, we will also exclude those unable to walk at baseline,
i.e., bed or chair bound.
There is strong evidence of low physical activity in hos-
pital [32, 33] and Broderick et al. [34] found that many of
the barriers could be addressed easily. For these reasons,
we will not only deliver supervised exercise sessions, but
in addition, will encourage mobility while in hospital and
provide walking aids initially, if required. The exercises are
designed to improve physical performance, transfer func-
tion, walking, balance and strength in order to maintain
functional mobility as much as possible.
Our pilot study [13] showed that there was a consider-
able difference in physiotherapy contact time with the
intervention, possibly introducing a Hawthorne effect. This
has been addressed by using a sham intervention for the
control group. To the authors’ knowledge, this is the first
time that a sham intervention has been included in this
type of study.
The intervention will be delivered by a senior physio-
therapist. The interventions of previous studies have been
delivered by a physiotherapist assistant or a physiotherapy
student, under the guidance of a qualified physiotherapist
[13,16,17]. However, patients’ physical performance fluc-
tuates in the acute setting. If a qualified physiotherapist
delivers the programme, it allows the optimal intervention
to be delivered on a daily basis. It will also allow a greater
opportunity to advise the patient regarding their inde-
pendent physical activity in hospital and to address bar-
riers to the intervention delivery such as pain relief.
Up to 27 \% of the patients were unable to complete
the Timed Up and Go Test in previous studies [16,17].
Therefore, the Short Physical Performance Battery will be
used, which was found to be feasible and sensitive to
change in a previous pilot study [13]. Length of stay will be
used as the primary outcome measure as this is available
electronically and absolutely complete data. A high attrition
rate is predicted for the three-month follow-up attendance
as our study group consist of frailer older adults.
A small number of studies have shown that interven-
tions to increase older medical inpatients’ physical activ-
ity can be modestly beneficial. Previous authors discuss
issues such as patient selection, intervention type and
outcome measures. This protocol has been designed to
include the frailer patient, to include a tailored and com-
prehensive intervention, and to measure the effects with
the most valid outcome measure.
Abbreviations
6-CIT: Six-Item Cognitive Impairment Test; APEP: Augmented prescribed exercise
programme; CIRS-G: Cumulative Illness Rating Scale – Geriatrics; EQ-5D-5 L: EuroQol
5-Domain 5-Level Scale; FES-I: Falls Efficacy Scale International; N-EADL: Nottingham
Extended Activities of Daily Living Scale; PI: Principal Investigator;
RA: Research Assistant; RPT: Research Physiotherapist; SAM: Stepwatch
Activity Monitor; SHARE-FI: Survey of Health, Aging and Retirement in
Europe Frailty Instrument; SPPB: Short Physical Performance Battery.
Competing interests
The authors declare that there are no conflicts of interest. This study has not
received funding or assistance from a commercial organisation.
Authors’ contributions
RMcC: concept and design, acquisition of subjects and baseline data collection,
delivery of the intervention, analysis and interpretation of the data, manuscript
preparation. EO’C: outcome data acquisition, manuscript preparation. SO’M
patient allocation process, data entry, manuscript preparation. IP: concept and
design, manuscript preparation. AF: concept and design, data analysis. KO’C:
concept and design, safety monitoring, manuscript preparation. NFH: concept
and design, study oversight, manuscript preparation. ST: concept and design,
study oversight, analysis and interpretation of the data, manuscript preparation.
All authors read and approved the final manuscript.
Authors’ details
RMcC, Senior Physiotherapist and PhD Student, Centre for Gerontology &
Rehabilitation, University College Cork, Ireland. EO’C, Physiotherapist,
Physiotherapy Department, Mercy University Hospital, Cork, Ireland. SO’M,
Research Assistant, Clinical Research Facility, Mercy University Hospital,
Cork, Ireland. IP, Professor of the Dept. of Epidemiology & Public Health,
University College Cork, Ireland. AF, Senior Statistician, Dept. of Epidemiology &
Public Health, University College Cork, Ireland. KO’C, Consultant Geriatrician, Mercy
University Hospital, Cork, Ireland. NFH, Senior Lecturer, School of Physiotherapy,
Royal College of Surgeons in Ireland, Dublin, Ireland. ST, Consultant Geriatrician,
Mercy University Hospital and Senior Lecturer, Centre for Gerontology &
Rehabilitation, University College Cork, Ireland, Ireland.
McCullagh et al. BMC Geriatrics (2016) 16:79 Page 6 of 7
Acknowledgements
This study is funded by the Health Research Board of Ireland, following a peer-
reviewed competition, as a Research Fellowship Training Grant (HPF 2013 451).
We would like to thank the Clinical Research Facility and the ward staff at the
Mercy University Hospital for facilitating this study.
Author details
1Centre for Gerontology & Rehabilitation, University College Cork, Cork,
Ireland. 2Physiotherapy Department, Mercy University Hospital, Cork, Ireland.
3Clinical Research Facility, Mercy University Hospital, Cork, Ireland.
4Epidemiology & Public Health, University College Cork, Cork, Ireland.
5Department of Geriatric Medicine, Mercy University Hospital, Cork, Ireland.
6School of Physiotherapy, Royal College of Surgeons in Ireland, Dublin,
Ireland.
Received: 24 November 2015 Accepted: 2 April 2016
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5. June 29
After the components sending to the manufacturing house
1. In 1972 the Furman v. Georgia case resulted in a decision that would put action into motion. Furman was originally sentenced to death because of a murder he committed in Georgia but the court debated whether or not this was a violation of his 8th amend
One of the first conflicts that would need to be investigated would be whether the human service professional followed the responsibility to client ethical standard. While developing a relationship with client it is important to clarify that if danger or
Ethical behavior is a critical topic in the workplace because the impact of it can make or break a business
No matter which type of health care organization
With a direct sale
During the pandemic
Computers are being used to monitor the spread of outbreaks in different areas of the world and with this record
3. Furman v. Georgia is a U.S Supreme Court case that resolves around the Eighth Amendments ban on cruel and unsual punishment in death penalty cases. The Furman v. Georgia case was based on Furman being convicted of murder in Georgia. Furman was caught i
One major ethical conflict that may arise in my investigation is the Responsibility to Client in both Standard 3 and Standard 4 of the Ethical Standards for Human Service Professionals (2015). Making sure we do not disclose information without consent ev
4. Identify two examples of real world problems that you have observed in your personal
Summary & Evaluation: Reference & 188. Academic Search Ultimate
Ethics
We can mention at least one example of how the violation of ethical standards can be prevented. Many organizations promote ethical self-regulation by creating moral codes to help direct their business activities
*DDB is used for the first three years
For example
The inbound logistics for William Instrument refer to purchase components from various electronic firms. During the purchase process William need to consider the quality and price of the components. In this case
4. A U.S. Supreme Court case known as Furman v. Georgia (1972) is a landmark case that involved Eighth Amendment’s ban of unusual and cruel punishment in death penalty cases (Furman v. Georgia (1972)
With covid coming into place
In my opinion
with
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The ability to view ourselves from an unbiased perspective allows us to critically assess our personal strengths and weaknesses. This is an important step in the process of finding the right resources for our personal learning style. Ego and pride can be
· By Day 1 of this week
While you must form your answers to the questions below from our assigned reading material
CliftonLarsonAllen LLP (2013)
5 The family dynamic is awkward at first since the most outgoing and straight forward person in the family in Linda
Urien
The most important benefit of my statistical analysis would be the accuracy with which I interpret the data. The greatest obstacle
From a similar but larger point of view
4 In order to get the entire family to come back for another session I would suggest coming in on a day the restaurant is not open
When seeking to identify a patient’s health condition
After viewing the you tube videos on prayer
Your paper must be at least two pages in length (not counting the title and reference pages)
The word assimilate is negative to me. I believe everyone should learn about a country that they are going to live in. It doesnt mean that they have to believe that everything in America is better than where they came from. It means that they care enough
Data collection
Single Subject Chris is a social worker in a geriatric case management program located in a midsize Northeastern town. She has an MSW and is part of a team of case managers that likes to continuously improve on its practice. The team is currently using an
I would start off with Linda on repeating her options for the child and going over what she is feeling with each option. I would want to find out what she is afraid of. I would avoid asking her any “why” questions because I want her to be in the here an
Summarize the advantages and disadvantages of using an Internet site as means of collecting data for psychological research (Comp 2.1) 25.0\% Summarization of the advantages and disadvantages of using an Internet site as means of collecting data for psych
Identify the type of research used in a chosen study
Compose a 1
Optics
effect relationship becomes more difficult—as the researcher cannot enact total control of another person even in an experimental environment. Social workers serve clients in highly complex real-world environments. Clients often implement recommended inte
I think knowing more about you will allow you to be able to choose the right resources
Be 4 pages in length
soft MB-920 dumps review and documentation and high-quality listing pdf MB-920 braindumps also recommended and approved by Microsoft experts. The practical test
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One thing you will need to do in college is learn how to find and use references. References support your ideas. College-level work must be supported by research. You are expected to do that for this paper. You will research
Elaborate on any potential confounds or ethical concerns while participating in the psychological study 20.0\% Elaboration on any potential confounds or ethical concerns while participating in the psychological study is missing. Elaboration on any potenti
3 The first thing I would do in the family’s first session is develop a genogram of the family to get an idea of all the individuals who play a major role in Linda’s life. After establishing where each member is in relation to the family
A Health in All Policies approach
Note: The requirements outlined below correspond to the grading criteria in the scoring guide. At a minimum
Chen
Read Connecting Communities and Complexity: A Case Study in Creating the Conditions for Transformational Change
Read Reflections on Cultural Humility
Read A Basic Guide to ABCD Community Organizing
Use the bolded black section and sub-section titles below to organize your paper. For each section
Losinski forwarded the article on a priority basis to Mary Scott
Losinksi wanted details on use of the ED at CGH. He asked the administrative resident