Community-Dwelling Older Adults’ Adherence to Environmental Fall Prevention Recommendations

Abstract

This study examined the impact of personalized versus generalized education about environmental fall prevention recommendations on older adults’ adherence with recommendations. Secondary aims focused on the impact of recent falls and perceived susceptibility of future falls on adherence with recommendations. Twenty-four community-dwelling older adults aged 65 to 89 years were randomized into two groups to receive either personalized or generalized education intervention on environmental fall prevention recommendations. A significant difference was found in the mean total percentage of adherence with recommendations of those receiving personalized education (69%) compared with those receiving generalized education (37%). No statistically significant relationship was found between sustaining recent falls, nor perceived susceptibility to future falls, and their extent of adherence with environmental fall prevention recommendations. Providing personalized education for environmental fall prevention recommendations may improve older adults’ adherence with the recommendations given.

Keywords

aged accident prevention accidental falls health behavior occupational therapy

Introduction

According to the Centers for Disease Control and Prevention (CDC; 2017), more than one out of four older adults fall each year. Post fall, individuals may face a variety of functional and emotional declines including decreased ability to complete daily activities, restriction of activities, depression, decreased socialization, increased institutionalization, and an overall decreased quality of life (Boyd & Stevens, 2009; Roe et al., 2008; Shumway-Cook et al., 2009; Tinetti & Williams, 1998). It is estimated that 20% to 30% of falls result in a moderate to severe injury including traumatic brain injury, hip fracture, shoulder dislocation, and injury to internal organs (Tinetti & Williams, 1998; National Center for Injury Prevention and Control [NCIPC], 2011b). In 2000, the direct medical costs in the United States to treat injurious falls reached US$19 billion (Delinger & Stevens, 2016) and costs are expected to rise to nearly US$55 billion by 2020 (Stark et al., 2017), making the prevention of falls vital. In fact, many developed countries consider fall prevention a priority (Todd & Skelton, 2004) and the United States is no exception (NCIPC, 2011a; National Council on Aging, 2011).

Despite known potential implications of falls, and despite national efforts to reduce the number of falls, several research studies showed community-dwelling older adults have low levels of adherence to recommendations for environmental changes (Boyd & Stevens, 2009; Cumming et al., 2001; Leland, Porell, & Murphy, 2011; Shumway-Cook et al., 2009; Yardley, Donovan-Hall, Francis, & Todd, 2006; Yardley et al., 2008). These studies provide presumptions as to what factors may influence the decision to adhere to fall prevention recommendations. Three of these presumed factors include understanding why the recommendations would decrease the risk of falling, having sustained recent falls, and perception of susceptibility to future falls.

The theoretical basis for this study was the Health Belief Model (HBM). Developed in the early 1950s by Hochbaum, Leventhal, Kegeles, and Rosenstock, the HBM provides a means for understanding the likelihood of an individual taking action to change their preventive health-related behaviors including why an individual would be noncompliant with health care recommendations (Mattson, 1999; Rosenstock, 1974). The HBM has been used to research health behaviors toward preventive care (Champion, 1984). Based upon constructs in the HBM, the extent to which an individual takes action to change their behaviors is determined by the interplay of three areas: individual perceptions, modifying factors, and likelihood of action. Specifically, an individual who perceives susceptibility, or who has experienced a modifying factor, has a greater likelihood of engaging in the preventive health behavior. Using these constructs for this study, an individual who has “perceived susceptibility” of future falls, will have an increased “likelihood of action” or increased adherence with fall prevention recommendations. Likewise, the HBM’s modifying factor of “cues to action” proposes an individual who has had experience(s) with falling, or an individual who has had education regarding fall prevention recommendations, will have an increased “likelihood of action” or increased adherence with fall prevention recommendations.

Although education is considered a cue to action for an individual to follow fall prevention recommendations, and previous studies speak to providing fall prevention education, to date no published studies have operationally defined the education provided. However, within the clinical context, health care providers are to provide education in a manner that is individualized to the needs of the patient. This study included a component to begin addressing this gap by providing two levels of education: generalized and personalized.

This study hypothesized that community-dwelling older adults who received personalized education on environmental fall hazards would be more likely to adhere to recommendations compared with those who received generalized education, irrespective of having recent falls or perceiving susceptibility to falling.

Method

Research Design

This randomized, controlled, mixed between-subjects and within-subjects study included a convenience sample of self-selected community-dwelling adults aged 65 years and older residing in the greater Richmond, Virginia, area. Structured as rolling recruitment and enrollment, individuals were randomized into either the treatment or control group. Randomization was completed through a two-step process. The first step consisted of computer-generated random numbers in sets from 1 to 20, then 21 to 40. The second step consisted of computer-generated randomization of the treatment and control groups for each set of numbers. The purpose of dividing the randomization into sets of 20 was to provide for greater likelihood of equal numbers of participants in each group during the recruiting process. As participants were recruited and randomized, the home visits were scheduled and initiated.

Participants

This study included adults aged 65 years or older whose primary residence was community-dwelling. Inclusion in the study was contingent upon the ability to engage in dressing, toileting, bathing or hygiene, and self-care transfers at an independent or modified independent level (may need to use adaptive equipment or durable medical equipment to complete task). In addition, interested individuals needed to have the authority to follow through or authorize follow through with the recommendations for environmental changes. Individuals were excluded from the study if they were currently receiving home health therapy services, had received home health services within the past 60 calendar days, or if they had a diagnosis of dementia. Recruiting efforts included distributions and postings of flyers, inclusion of flyers with Meals on Wheels delivery, providing community wellness seminars (on topics other than fall prevention) and distributing flyers, electronic postings, and word-of-mouth. A total of 37 individuals contacted the study coordinator in response to recruitment flyers and advertisements (Figure 1). Thirty-one individuals (84%) were deemed eligible, of which 24 (77%) enrolled in the study and provided written, informed consent. Randomization resulted in 12 participants in each of the treatment and control groups.

Figure 1.

Recruitment and enrollment.

Measures

The number of recent falls experienced within the prior 180 days was gathered via self-report during the first home visit, prior to providing education intervention. Although it is widely accepted that falls and resulting injuries may lead to significant ramifications, currently there is not a universal definition of a fall. Without such a definition, determining what constitutes a fall is left to the interpretation of the study participants, those conducting studies, and those utilizing study results. The World Health Organization’s International Classification of Disease defines a fall as “inadvertently coming to rest on the ground, floor, or other lower level, excluding intentional change in position to rest in furniture, on the wall, or other objects” (Yoshida, 2000, p. 4). Of note, this definition provides only a framework for defining a fall as it lacks excluding events such as overwhelming external forces that result in being knocked over, or major internal disturbances that cause collapse instead of fall. Both Gibson, Andres, Isaacs, Radebaugh, and Worm-Peterson (1987) and Tinetti, Baker, Dutcher, Vincent, and Rozett (1997) coined operational definitions for a fall that have been used in subsequent studies including Feder, Cryer, Donovan, and Carter (2000) and Findorff, Wyman, Nyman, and Croghan (2007). In efforts to capture the fundamental components, this study used a combination of the two aforementioned definitions as this study’s operational definition of a fall:

A sudden, unintentional change in position causing an individual to land at a lower level, on an object, the floor, or the ground, other than as a consequence of sustaining a violent blow, loss of consciousness, sudden onset of paralysis as in stroke or an epileptic seizure or by overwhelming external force.

Four categories were established for data analysis: no reported fall; one reported fall, no injury; two or more reported falls, no injury; and one or more reported falls with an injury.

Participants’ perceived susceptibility (of future falls) was measured via the Activities-Specific Balance Confidence scale (ABC) and was gathered during the first home visit, prior to providing education intervention. This is a brief self-reporting survey developed by Powell and Myers in 1995 which asks respondents to indicate their level of self-confidence in completing a variety of activities without losing their balance or becoming unsteady. ABC has been shown to have greater sensitivity in determining between individuals who were fearful or avoiding activity and those who were not (Myers, Fletcher, Myers, & Sherk, 1998). This scale has been used in previous studies (Lajoie & Gallagher, 2003; Lohnes & Earhart, 2010; Myers et al., 1998) and has been shown to have strong test–retest reliability with r = .92 (Schepens, Goldberg, & Wallace, 2009). Predictive validity of the ABC is supported through excellent correlation with the Balance Evaluation Systems Test (r = .636, p < .01) for individuals with balance disorders (Horak, Wrisley, & Frank, 2009) and excellent correlation with the Falls Efficacy Scale–International for individuals with dizziness and imbalance (r = −.84, p < .01; Morgan, Friscia, Whitney, Furman, & Sparto, 2013). Construct validity of the ABC has been shown as having an excellent correlation with the Berg Balance Scale (r = .752, p < .01) and the Timed Up & Go Test (r = .698, p < .01) for community-dwelling older adults (Hatch, Gill-Body, & Portney, 2003).

Participants’ percentage of adherence (with recommendations) was measured via observation utilizing forms created for this study and was gathered during the third home visit. Percentage of adherence with recommendations was calculated using the total number of environmental recommendations as the denominator and the total number of recommendations followed as the numerator.

Intervention and Data Collection

Study data were collected during home visits between April 2012 and August 2013. All home visits were conducted by an occupational therapist (OT), licensed to practice in the Commonwealth of Virginia, recognized by the National Board for Certification in Occupational Therapy, with more than 15 years working with older adults, and trained on this study. Due to feasibility constraints of this study, the OT conducting the home visits remained constant for all home visits and was therefore not blinded to randomization. Data were collected across three home visits scheduled 30 to 45 days apart, through a combination of self-reporting, interviewing, and objective observation. The home visit design is shown in Table 1.

Table 1.

Home Visit Design.

	Home Visit 1		Home Visit 2	Home Visit 3
	Hazards identified	Treatment	Review of recommendations	Recommendations followed	Treatment
Treatment Group	Yes	Yes	Yes	Yes	No
Control Group	Yes	No	Yes	Yes	Yes

The first home visit included a semistructured interview, the participant completed the ABC scale, and the OT completed the home environmental evaluation. Created for this study, the environmental evaluation was based upon the CDC publication “Check for Safety: A Home Fall Prevention Checklist for Older Adults” (CDC, 2005), and included the additional areas of chair/sofa height, thresholds, and bed height as these areas were noted in previous studies (Cumming et al., 2001; Greene et al., 2009; Wyman et al., 2007), but not included in the CDC publication. All participants received a written copy of the aforementioned CDC publication along with a written and verbal review of the recommendations generated from the environmental evaluation. Operational definitions for evaluation areas, hazard levels, and recommendations are detailed in Table 2.

Table 2.

Operational Definitions of Environmental Areas, Hazard Levels, and Recommendations.

Area	Operational definition	Hazard level	Recommendations
Chair or sofa height	Participant’s preferred seating surface	Participant is unable to rise on first trial from preferred chair or sofa	Raise/lower seating surface to 90° hip/knee flexion; if rocking motion—stabilize; grab bar(s) nearby
Pathways	Primary pathways for participant to travel between sleeping, living, and bathroom areas	Furniture or items placed in pathway; clutter on floors	Clear pathways; move furniture from pathways
Throw rugs	Rugs that are removable, edges are not fastened to floor	Throw rugs within bathroom, near bed, in hallway, at doors	Remove throw rugs
Thresholds	Change in flooring surface from one area to another or within a doorway	Thresholds with change in floor level > ½ inch	Change thresholds to low profile
Inside stairs	Stairs used to navigate from one level to another level within the home	Rise between steps is unequal; depth of steps is < 20 cm	Alter living space to avoid stairs (primary living on first level)
Stair lighting	Lighting for the stairway	Absent lighting; light switch at only the top or bottom of the stairway	Review other lighting options nearby stairway; self-adhesive, battery-operated touch lights
Handrails	Supportive rails along one or both sides of the stairs	Absent rails; broken or loose rails	Add handrails if missing; fix broken rails
Commode	Primary commode used by participant	Participant is unable to rise on first trial (safety bars or raised toilet seat as needed)	Add raised toilet seat and/or safety grab bars
Bathtub/shower	Participant’s primary method of completing hygiene (shower, tub bath, sponge bathing)	Standing surface is missing nonskid mat or has slippery surface; participant is unable to complete typical hygiene routine in current arrangement (may use safety bars or tub bench)	Add nonskid mat for standing surface; recommend adaptive or durable medical equipment as indicated including safety grab bars
Kitchen tasks	Cabinets and surface areas used for meal preparation	Common items are at heights above shoulders or below knees	Place commonly used items at heights between shoulders and knees
Bedroom lighting	The primary sleeping area for the participant	Lighting is beyond reach while participant is in resting position	Place lamp/light switch within reach while in the resting position
Nightlight	Lighting available for the participant for pathway between sleeping area and commode	No lighting or minimal lighting available to illuminate pathway between sleeping area and commode	Add nightlight(s) to provide illumination from primary sleeping area to commode
Bed height	The primary sleeping surface for the participant	Participant is unable to touch the floor with feet while seated on the edge of the bed	Raise (furniture risers) or lower (remove mattress/lower frame) the bed to allow participant to rest feet on floor while seated at the edge of the bed
Household pets	Pets allowed inside the home: dog(s)/cat(s) or similar pet able to roam freely in the home	Toys and/or food water dishes in pathways; pet alters environment by moving items or leaving toys in the pathways	Place food and water dishes in separate area from pathways; use reacher to keep pathways free from clutter
Small children	Child(ren) below the age of 5 years within the participant’s home	Child(ren) alters the environment by moving items or leaving toys within the pathways	Create designated space in home for child(ren) to play with toys; have assist with keeping pathways free from clutter

During the first home visit, control group participants received generalized education and treatment group participants received personalized education: physical demonstration of the identified environmental fall hazard, explanation as to why the area was considered a fall hazard, and method(s) to correct the hazard. For example,

OT to a control group participant: “The Home Environmental Evaluation shows that you have a cluttered pathway. This is considered a fall hazard and the recommendation is to have your pathways free from clutter.”

OT to a treatment group participant: “The Home Environmental Evaluation shows that you have a cluttered pathway. Please come with me so I can show you. (OT and participant go to the cluttered pathway.) Let me show you how this clutter here could cause you to fall. (OT demonstrates why the cluttered pathway is a fall hazard by showing how a foot or ambulation device may become caught and cause a loss of balance.) The recommendation is to have this clutter cleared so that you have a wide enough pathway and are less likely to catch your foot on something, causing you to lose your balance and fall.”

Treatment group participants were encouraged to verbalize and/or demonstrate their understanding of the recommendations, using a written copy of the recommendations as a guide. Participants in the treatment group were allowed as much additional time as necessary to reach an understanding of the recommendations, thus contributing to personalization of the environmental fall prevention education by meeting their learning needs. The second home visit for all participants included a review of the previously provided recommendations. The third home visit for all participants included determination of which recommendations were followed, as well as a semistructured interview as a means of collecting responses of why the participant chose adherence or nonadherence to recommendations. During the final home visit, after data were collected, control group participants received personalized education, thus all study participants received the treatment intervention of personalized education. Two of the control group participants contacted the study coordinator to schedule an additional (fourth) home visit. They each expressed their desire to demonstrate how they followed recommendations since receiving personalized education during the study’s final visit. These additional visits were completed as a courtesy to the participants; no data were collected.

Data Analysis

Statistical analyses were performed with IBM SPSS Statistics software, version 21 (IBM Corporation, Armonk, New York). Two-sample t test for independent groups was used to assess the relationship between education intervention (personalized vs. generalized education) and percentage of adherence. Two secondary hypotheses in this study proposed that older adults may be more likely to adhere with fall prevention recommendations if they recently had a fall or if they believed they may have a future fall. As these two remaining predictor variables, recent falls and perceived susceptibility (to future falls), relied upon all participants as one group, hierarchical regression was used to control for the known variation between the treatment and control groups due to education intervention. Hierarchical regression requires minimum ratio of 5:1, valid cases to the independent variable. This hypothesis utilized two independent variables and the study contains 22 valid cases, thereby resulting in an appropriate ratio of 11:1 (Tabachnick & Fidell, 2007), although the small sample size threatens the assumption of normality of the data. Again, the purpose of Step 1 was to control for the known variation between the treatment and control group participants’ education intervention. In Step 2 of each hierarchical regression, the additional percentage of adherence was assessed.

Results

A total of 24 participants enrolled in this study of which 22 participants completed all three home visits and were included in data analysis (treatment n = 12, control n = 10). Two participants, both in the control group, were unable to complete all three home visits. Neither of these participants was significantly different from the other participants in demographics nor in the total number of identified hazards. One of these participants completed the first home visit, scheduled the second home visit, but was not home for the scheduled visit and no longer responded to follow-up phone messages. The other participant completed the first two home visits, called to reschedule the third home visit, again canceled, at which point the final visit was no longer able to be scheduled within the 30- to 45-day time frame as per study protocol.

Table 3 displays the characteristics of the study sample. Fisher’s exact testing indicated no significant differences between treatment and control groups for male to female, t(20) = .102, p = 1.0; ethnicity (p = .69); injurious fall (p = 1.0); and the number of recent falls (p = 1.0). An unpaired t test showed perceived susceptibility was not statistically different between the groups, t(20) = 1.19, p = .25. The mean age for the study sample was 74.2 years. The mean age for the treatment and control groups were very similar at 74.3 years and 74.0 years, respectively. As shown in Figure 2, the strongest areas of adherence at the final visit for all participants combined were bedroom light (100%), nightlight (86%), kitchen tasks (67%), and pathways (63%). No recommendations were made for the following areas: thresholds, inside stairs, stair lighting, handrails, commode, and children.

Table 3.

Characteristics of Study Sample.

	Sample (N = 22)	Treatment (n = 12)	Control (n = 10)
Age (M ± SD)	74.2 ± 7.5	74.3 ± 7.5	74.0 ± 7.9
Gender, n (%)
Male	8 (36.4)	4 (33.3)	4 (40)
Female	14 (63.6)	8 (66.7)	6 (60)
Race, n (%)
African American	14 (63.6)	8 (66.7)	6 (60)
Caucasian	8 (36.4)	4 (33.3)	4 (40)
No recent fall, n (%)	9 (40.9)	5 (41.7)	4 (40)
Fall, no injury, n (%)	5 (22.7)	3 (25.0)	2 (20)
Injurious fall, n (%)	8 (36.4)	4 (33.3)	4 (40)

Figure 2.

Percentage of adherence by area: All participants at final visit.

The final mean total percent of adherence for the treatment group (M = .69, SD = .29) and control group (M = .37, SD = .37) was examined using an independent-samples t test. Analysis for each sample using a normal Q-Q plot revealed no serious threats to assumptions of normality. Levene’s test for homogeneity of variance showed p > .05 (.156) indicating Levene’s test was not significant and equal variances were assumed. As shown in Table 4, the t test indicated that the means differed significantly, t(20) = 2.33, p = .03 (two-tailed), and the effect size was large (d = .96). Therefore, the population of older adults represented by these samples showed a greater percentage of adherence with environmental recommendations when provided personalized education compared with those who received generalized education (Figure 3).

Table 4.

Results of t Test and Descriptive Statistics for Percentage of Adherence by Group.

	Group						95% CI for mean difference	t	df
	Treatment			Control
	M	SD	n	M	SD	n
Percentage adherence	69.33	28.85	12	36.70	36.92	10	[3.40, 61.89]	2.33*	20

Note. CI = confidence interval.

p < .05.

Figure 3.

Percentage of adherence by group.

The R² change in Step 1 was .21, a value that was significant, F(1, 20) = 5.42, MS_residual = .107, p < .05, indicating the predictor variable education intervention explained a significant proportion of the percentage of adherence. The additional contribution of the variable recent falls did not significantly increase the proportion of the explained variance in the percentage of adherence, R² change = .001, F(1, 19) = .02, MS_residual = .113, p = .90. Similarly, in Step 2 of the second hierarchical regression, the additional contribution of perceived susceptibility to predict the percentage of adherence was assessed. The additional contribution of the variable perceived susceptibility did not significantly increase the proportion of the explained variance in the percentage of adherence, R² change = .002, F(1, 19) = .05, MS_residual = .112, p = .83. Tables 5 and 6 show the values of beta for independent variables included at each step of the procedure together with significance tests. As indicated in the tables, in Step 1, the variable education intervention significantly improved prediction of percentage of adherence with recommendations.

Table 5.

Recent Falls and Percentage of Adherence.

	Semipartial r	β	t(20)	Significance
Education intervention	−.46	−.46	−2.33	.03
			t(19)
Recent falls	−.03	−.03	−.13	.90
Education intervention	−.46	−.46	−2.27	.04

Note. The top panel shows semipartial r values and beta values together with significance tests for predictor variables for Step 1 of the hierarchical multiple regression analyses, controlling for education intervention. The bottom panel shows these values for Step 2, recent falls.

Table 6.

Perceived Susceptibility and Percentage of Adherence.

	Semipartial r	β	t(20)	Significance
Education intervention	−.46	−.46	−2.33	.03
			t(19)
Perceived susceptibility	−.05	−.05	−.22	.83
Education intervention	−.46	−.47	−2.25	.04

Note. The top panel shows semipartial r values and beta values together with significance tests for predictor variables for Step 1 of the hierarchical multiple regression analysis. The bottom panel shows these values for Step 2, perceived susceptibility.

Discussion

Following the recommendations of previous studies (Cumming et al., 2001; Greene et al., 2009; Lambert, Sterbenz, Womach, Zarrinkhameh, & Newton, 2001; Leland et al., 2011; Roe et al., 2008; Yardley et al., 2006), this study gathered quantitative data to understand how older adults responded to fall prevention recommendations, using a randomized controlled design to compare personalized and generalized education interventions. It also incorporated a home visit to gather data as a means to reduce weaknesses associated with self-reporting of adherence.

Findings from this study suggest that overall adherence with environmental fall prevention recommendations are greater when personalized education is provided rather than generalized education. This finding is consistent with the findings of a recent study by Schepens, Panzer, and Goldberg (2011) in which participants receiving fall prevention education tailored specifically to the older adult receiving the education demonstrated improved fall prevention behaviors. This finding is also consistent with the focus in health care toward individualized plans of care. Many professional health care organizations and regulating agencies emphasize the need for personalized (individualized) treatment plans including documentation indicating the individual understands the information and recommendations provided (American Nurses Association, 2017; American Occupational Therapy Association, 2017; American Physical Therapy Association, 2017; American Speech-Language-Hearing Association, 2017; The Joint Commission, 2011; Stempak, 2015).

This study did not detect a significant relationship between recent falls and adherence with fall prevention recommendations. One potential reason for this lack of finding may center on the inherent difficulties in achieving accuracy with self-reporting of falls. As previous studies noted, underlying reasons for suspected underreporting of falls may be attributable to denial of falling and reluctance to inform others of recent falls for fears of negative social stigma (Leland et al., 2011; Yardley et al., 2006). Shumway-Cook et al. (2009) also suggested that the fall may have simply been forgotten and thus not reported.

Just as with a previous study (Cumming et al., 2001), this study found no significant association between adherence and the participants’ perceived susceptibility to future falls. These findings are at odds with the HBM. Perhaps understanding an individual’s perceived susceptibility is not as important as understanding whether or not the individual places value on being susceptible to a future fall. As one participant explained, he felt off-balance “every time (he tries) to turn around” and admitted to multiple previous falls. He also admitted having a high likelihood of future falls, yet “it doesn’t bother me because I haven’t broken anything.” These statements indicate a high level of perceived susceptibility without eliciting the cue to action as proposed by the HBM. Another participant appeared dismissive of recent falls: almost smiling while stating “I stopped counting since I fall so much.” A different participant explained he was not concerned about falling: “I learned how to get off the floor.” Yet another participant explained there was not a need to worry about falling: “I fall every day and I haven’t gotten hurt yet.” Perhaps the HBM cue to action of perceived susceptibility of future falls elicits a fear of falling, thus serves as a cue to action, whereas having experience with falling no longer evokes a fear, therefore no longer serves as a cue to action.

Recommendations for Clinical Practice

The results of this study suggest that health care professionals working with older adults should adopt an individualized approach (personalized education) when providing fall prevention recommendations as this may increase adherence with the recommendations. Personalized education in this study included several components. First, recommendations were specific to the older adult’s environment. For example, rather than the general recommendation “remove rugs,” the recommendation was personalized by showing exactly which rugs were considered a hazard and recommendations to address the hazard. Second, along with providing written recommendations, discussions were facilitated to ensure the individual understood the recommendations and additional time was allotted as needed, specific to the individual. For example, one individual’s bed height was too high. Her typical daily routine was to “slide” out of the bed and “catch herself” on the door frame of the adjacent bathroom. She wished to attempt a variety of different methods to exit the bed, eventually agreeing that regardless of how she attempted, she felt a loss of balance. The discussion then progressed to options to lower the bed including who might be able to assist her. Finally, this study included physical demonstrations to personalize the education to the individual’s environment. For example, one individual’s favorite rocking recliner was placed near his wife’s favorite hardwood coffee table. Physical demonstration included showing him how attempting to stand while the recliner rocked caused him to be off-balance, and the direction of the potential fall may cause him to hit his head on the coffee table.

Study Limitations

The primary limitation for this study was the sample size (N = 22), which decreases generalizability of findings and threatens assumptions of normality of the data. The small sample size also negatively affected the overall power of the statistical analysis. Therefore, results should be viewed with caution. This study relies upon self-selected participants, and as such, includes inherent limitations. Participants who agreed to home visits may have been more likely to follow recommendations compared with the general population. In addition, participants who were interested in a study associated with home safety and fall prevention recommendations may have been more likely to follow recommendations compared with the general population. Another inherent limitation in this study is that of self-reporting recent falls. This self-reporting depended upon not only the participant’s memory of such an event but also his or her definition of a fall. Besides the obvious scenario that a fall was truly forgotten, it is possible the participant did not remember (or consider) a previous event as a fall, but rather a “slip” or “stumble” and therefore did not report it as a fall. This study attempted to control for this limitation by providing an operational definition of “fall.” Due to study feasibility constraints, the outcomes assessor was not blinded to randomization, resulting in another limitation to the study as rater bias may have been inadvertently introduced.

Future Research

Given the magnitude of implications older adults are subject to as a result of falling, and the need to decrease as many risk factors as possible, future research is needed to further analyze older adults’ response to fall prevention recommendations. This study was unique in the inclusion of a home visit as a follow-up rather than relying upon self-reporting via telephone or survey. It was also unique in utilizing a randomized control group design to review differences between personalized and generalized education.

Future research is needed with larger sample sizes and in a variety of geographical locations to strengthen statistical analysis and improve generalizability of the results. Studies should consider using additional or alternative measures to capture both the individual’s perceived susceptibility of injury from a future fall and the level of importance or value the individual places on avoidance of falling.

Future research methodology should consider including potential impacts of known fall risk factors on an individual’s likelihood of taking action. Perhaps individuals with multiple known risk factors for falling, such as having low vision, taking certain medications, and/or having certain medical conditions, may, as a combined interaction, have a greater likelihood of following fall prevention recommendations. This study did not review such variables and their potential impact. This study recommends continued quantifying adherence with recommendations as a percentage determined by dividing the total number of recommendations followed by the total number of recommendations made. Previous studies have reported either a raw number of recommendations followed or categorized adherence as full, partial, or nonadherence. Reporting adherence as a percentage would allow for more precise comparison across studies. Finally, future research should consider a mixed-methods design to provide analyses for quantitative levels of adherence overlaid with analyzed qualitative responses for adherence and nonadherence as a holistic foundation for understanding older adults’ adherence to fall prevention recommendations.

Footnotes

Ethical Approval

The institutional review board of Virginia Commonwealth University granted ethical approval on November 29, 2011 (HM13996).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

References

American Nurses Association. (2017). The nursing process. Retrieved from http://www.nursingworld.org/EspeciallyForYou/What-is-Nursing/Tools-You-Need/Thenursingprocess.html

American Occupational Therapy Association. (2017). About occupational therapy. Retrieved from https://www.aota.org/About-Occupational-Therapy.aspx

American Physical Therapy Association. (2017). The physical therapist scope of practice. Retrieved from http://www.apta.org/ScopeOfPractice/

American Speech-Language-Hearing Association. (2017). Overview of documentation for Medicare outpatient therapy services. Retrieved from http://www.asha.org/practice/reimbursement/medicare/medicare_documentation/

Boyd

Stevens

(2009). Falls and fear of falling: Burden, beliefs and behaviours. Age and Ageing, 38, 423-428.

Centers for Disease Control and Prevention. (2005). Check for safety: A home fall prevention checklist for older adults. Retrieved from https://www.cdc.gov/steadi/pdf/check_for_safety_brochure-a.pdf

Centers for Disease Control and Prevention. (2017). Important facts about falls. Retrieved from: https://www.cdc.gov/homeandrecreationalsafety/falls/adultfalls.html

Champion

(1984). Instrumental development for health belief constructs. Advances in Nursing Science, 6, 73-85.

Cumming

Thomas

Szonyi

Frampton

Salkeld

Clemson

(2001). Adherence to occupational therapist recommendations for home modifications for falls prevention. The American Journal of Occupational Therapy, 55, 641-648.

10.

Delinger

A. M.

Stevens

J. A.

(2006). The injury problem among older adults: Mortality, morbidity, and costs. Journal of Safety Research, 37(5), 519-522.

11.

Feder

Cryer

Donovan

Carter

(2000). Guidelines for the prevention of falls in people over 65. British Medical Journal, 321(7267), 1007-1011.

12.

Findorff

Wyman

Nyman

Croghan

(2007). Measuring the direct healthcare costs of a fall injury event. Nursing Research, 56, 283-287.

13.

Gibson

M. J.

Andres

R. O.

Isaacs

Radebaugh

Worm-Peterson

(1987). The prevention of falls in later life: A report of the Kellogg International Work Group on the prevention of falls by the elderly. Danish Medical Bulletin, 34(Suppl. 4), 1-24.

14.

Greene

Sample

Fruhauf

(2009). Fall-prevention pilot: Hazard survey and responses to recommendations. Occupational Therapy in Health Care, 23, 24-39.

15.

Hatch

Gill-Body

K. M.

Portney

L. G.

(2003). Determinants of balance confidence in community-dwelling elderly people. Physical Therapy, 83, 1072-1079.

16.

Horak

F. B.

Wrisley

D. M.

Frank

(2009). The Balance Evaluation Systems Test (BESTest) to differentiate balance deficits. Physical Therapy, 89, 484-498. doi:10.2522/ptj.20080071

17.

Lajoie

Gallagher

S. P.

(2003). Predicting falls within the elderly community: Comparison of postural sway, reaction time, the Berg balance scale and the Activities-specific Balance Confidence (ABC) scale for comparing fallers and non-fallers. Archives of Gerontology and Geriatrics, 38(2004), 11-26.

18.

Lambert

Sterbenz

Womach

Zarrinkhameh

Newton

(2001). Adherence to a fall prevention program among community dwelling older adults. Physical & Occupational Therapy in Geriatrics, 18(3), 27-43.

19.

Leland

Porell

Murphy

S. L.

(2011). Does fall history influence residential adjustments? The Gerontologist, 51, 190-200.

20.

Lohnes

C. A.

Earhart

G. M.

(2010). External validation of abbreviated versions of the Activities-specific balance confidence scale in Parkinson’s disease. Movement Disorders, 25, 485-489.

21.

Mattson

(1999). Toward a reconceptualization of communication cues to action in the health belief model: HIV test counseling. Communications Monographs, 66, 240-265.

22.

Morgan

M. T.

Friscia

L. A.

Whitney

S. L.

Furman

J. M.

Sparto

P. J.

(2013). Reliability and validity of the Falls Efficacy Scale-International (FES-I) in individuals with dizziness and imbalance. Otology & Neurology, 34, 1104-1108. doi:10.1097/MAO.0b013e318281df5d

23.

Myers

A. M.

Fletcher

P. C.

Myers

A. H.

Sherk

(1998). Discriminative and evaluative properties of the Activities-specific Balance Confidence (ABC) scale. Journal of Gerontology: Medical Sciences. A, 53, M287-M294.

24.

National Center for Injury Prevention and Control. (2011a). CDC Injury Center:Research Priorities. Retrieved from https://www.cdc.gov/injury/pdfs/researchpriorities/cdc-injury-research-priorities.pdf

25.

National Center for Injury Prevention and Control. (2011b). Falls among older adults: An overview. Retrieved from http://www.cdc.gov/HomeandRecreationalSafety/Falls/adultfalls.html

26.

National Council on Aging. (2011). Falls prevention. Retrieved from http://www.ncoa.org/improving-health/falls-prevention/

27.

Powell

L. E.

Myers

A. M.

(1995). The activities-specific balance confidence (ABC) scale. The Journal of Gerontology: Series A: Biological Sciences & Medical Sciences. A, 50, 1M28-1M34.

28.

Roe

Howell

Riniotis

Beech

Crome

Ong

(2008). Older people’s experience of falls: Understanding, interpretation and autonomy. Journal of Advanced Nursing, 63, 586-596.

29.

Rosenstock

(1974). The health belief model and personal health behavior. Thorofare, NJ: Charles B Slack.

30.

Schepens

S. L.

Goldberg

Wallace

(2009). The short version of the Activities-specific Balance Confidence (ABC) scale: It’s validity, reliability, and relationship to balance impairment and falls in older adults. Archives of Gerontology and Geriatrics, 51, 9-12.

31.

Schepens

S. L.

Panzer

Goldberg

(2011). Randomized controlled trial comparing tailoring methods of multimedia-based fall prevention education for community-dwelling older adults. American Journal of Occupational Therapy, 656, 702-709.

32.

Shumway-Cook

Ciol

Hoffman

Dudgeon

Yorkston

Chan

(2009). Falls in the Medicare population: Incidence, associated factors, and impact on health care. Physical Therapy, 89, 324-332.

33.

Stark

Somerville

Keglovits

Conte

Y.-L.

Yan

(2017). Protocol for the home hazards removal program (HARP) study: A pragmatic, randomized clinical trial and implementation study. BMC Geriatrics, 17, doi: 10.1186/s12877-017-0478-4

34.

Stempak

(2015). CMS proposes individualized care plan for long-term care patients. I Advance Senior Care. Retrieved from https://www.iadvanceseniorcare.com/article/cms-proposes-individualized-care-plan-long-term-care-patients

35.

Tabachnick

B. G.

Fidell

L. S.

(2007). Using multivariate statistics (5th ed.). Boston, MA: Education.

36.

The Joint Commission. (2011). Accreditation guide for hospitals. Retrieved from http://www.jointcommission.org/assets/1/6/accreditation_guide_hospitals_2011.pdf

37.

Tinetti

Baker

Dutcher

Vincent

Rozett

(1997). Reducing the risk of falls among older adults in the community. Berkeley, CA: Peaceable Kingdom Press.

38.

Tinetti

Williams

(1998). The effect of falls and fall injuries on functioning in community-dwelling older persons. The Journals of Gerontology: Series A: Biological Sciences & Medical Sciences, 53(2), M112-M119.

39.

Todd

Skelton

(2004). What are the main risk factors for falls among older people and what are the most effective interventions to prevent these falls? (Health Evidence Network, World Health Organization Regional Office for Europe). Copenhagen, Denmark: Retrieved from http://www.euro.who.int/document/E82552.pdf

40.

Wyman

J. F.

Croghan

C. F.

Nachreiner

N. M.

Gross

C. R.

Stock

H. H.

Talley

Monigold

(2007). Effectiveness of education and individualized counseling in reducing environmental hazards in the homes of community-dwelling older women. Journal of the American Geriatrics Society, 55, 1548-1556.

41.

Yardley

Donovan-Hall

Francis

Todd

(2006). Older people’s views of advice about falls prevention: Qualitative. Health Education Research, 21, 508-517.

42.

Yardley

Kirby

Ben-Shlomo

Gilbert

Whitehead

Todd

(2008). How likely are older people to take up different fall prevention activities? Preventive Medicine, 47, 554-558.

43.

Yoshida

(2000). A global report on falls prevention: Epidemiology of falls. (9): World Health Organization: Ageing Projects. Retrieved from http://www.who.int/ageing/projects/1.Epidemiology%20of%20falls%20in%20older%20age.pdf