The European Journal of Public Health Advance Access originally published online on January 5, 2007
The European Journal of Public Health 2007 17(5):464-470; doi:10.1093/eurpub/ckl272
Prevention |
A multifactorial fall prevention programme in the community-dwelling aged: predictors of adherence
Noora Maria Sjösten1, Maritta Salonoja2, Maarit Piirtola1,3, Tero Juhani Vahlberg4, Raimo Isoaho1,5,6, Hanna Kristiina Hyttinen7, Pertti Toivo Aarnio2 and Sirkka-Liisa Kivelä1,2,8
1 The Institute of Clinical Medicine, Family Medicine, University of Turku, Turku, Finland
2 Satakunta Central Hospital, Pori, Finland
3 Lieto Health Center, Lieto, Finland
4 Biostatistics, University of Turku, Finland
5 Pori Health Center, Pori, Finland
6 Nordic School of Public Health, Gothenburg, Sweden
7 Satakunta University of Applied Sciences, Pori, Finland
8 Turku University Hospital, Unit of Family Medicine, Turku, Finland
Correspondence: Noora Sjösten, Institute of Clinical Medicine, Family Medicine, Lemminkäisenkatu 1, 20014 University of Turku, Finland, tel: +358-2-333-8485, fax: +358-2-333-8439, e-mail: nookau{at}utu.fi
Received August 8, 2006, accepted December 5, 2006
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Background: Overall adherence rates have usually been reported in fall prevention studies, but predictors of adherence have rarely been described. The aim of this study was to determine the adherence rates and the predictors of adherence in four key activities of a multifactorial fall prevention trial.
Methods: This study is part of a multifactorial fall prevention programme implemented among the 65-year-old or older community-dwelling aged who had fallen at least once during the previous 12 months. Subjects (n = 591) were randomly assigned to an intensive prevention programme or to a counselling group. Four key activities of prevention programme included physical exercise in small groups, psychosocial group activities, lectures and home exercises. Associations between adherence rates and potential predictors were analysed using cumulative logistic regression.
Results: The mean adherence rate was 58% in the physical exercise groups, 25% in the psychosocial groups and 33% in lectures. Subjects performed home-exercises on average 11 times per month. In multivariate analyses, infrequent feelings of loneliness, low self-perceived probability of falling at home and good physical functional abilities were significant predictors of active physical exercise group adherence. Good physical and cognitive functional abilities predicted active psychosocial group adherence. Female gender and good physical and cognitive functional abilities predicted more active lecture adherence.
Conclusion: Persons with the poorest physical, cognitive and psychological functional abilities representing the part of the population at highest risk of falling do not seem reachable in multifactorial risk-based intervention.
Keywords: adherence, fall prevention, multifactorial, aged, predictor
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Falls are a major public health concern among the aged and the treatment costs of injuries caused by falls are high.1 A substantial amount of falls is preventable,2 the most effective strategy being a multifactorial approach targeting on various risk factors of falling simultaneously.3–9 However, it is uncertain whether these programmes reach persons most requiring fall prevention, e.g. recurrent fallers and those with multiple risk factors.
When assessing the effects of preventive programmes, adherence (or compliance) is a crucial issue. In some fall prevention studies active participation has been associated with better results at outcome assessments.10,11 To avoid false conclusions of programme efficacy, results should always be interpreted with a simultaneous consideration of adherence. Predictors of adherence could provide important information for practitioners and researchers, given that subject compliance is the most commonly reported barrier to successful intervention in fall prevention.12 Recognizing factors affecting compliance is a prerequisite for successful implementation of a prevention programme.
Overall adherence rates in different activities of multifactorial fall prevention programmes, such as exercise or educational classes, home-exercises or recommendations for preventive actions, have been reported in previous studies among the aged at high risk of falling8,10,13–15,17,18 as well as in population-based studies.3,16
In high-risk populations, adherence rates in group exercise sessions (from 67% to 73%),4,8 and in home-exercises (from 70% to 90% of persons performing recommended at least twice a week)11,15 have been high. High compliance rates (partial or complete compliance varying from 70% to 90%) have also been reported for different treatment recommendations.8,11,13
The predictors of adherence in fall prevention trials are poorly known and only few predictors have been identified in previous fall prevention studies.3,18 A person's own beliefs about the possibilities to prevent falls by the activities of the programme, predicts adherence with recommendations for home modifications.18 Persons at high risk of falling attend most due to the highest intrinsic motivation to prevent falling accidents.3 These findings support the Health Belief Model, stating that a perceived susceptibility to a health problem and its severity, and person's own beliefs in the efficacy of the advised activities to reduce risk predict changes in health behaviour.19
The aim of this study was to determine the adherence rates and the predictors of adherence in four key activities (group and home-based exercises, psychosocial groups, lectures) of a multifactorial fall prevention trial implemented in the town of Pori, in western Finland among 65-year-old or older community-dwelling persons who had fallen at least once during the 12 months previous to the randomization.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Participants
This study is a part of a large multifactorial fall prevention programme implemented in a town of Pori, in western coast of Finland. Participants to the whole project were recruited by announcements in local newspapers, pharmacies, Pori Health Centre, Satakunta Central Hospital and private clinics and by written invitations delivered by physicians, home aids and nurses (a total of 3300 invitations and announcements, during the 2-year recruitment). In addition, informative meetings were held in four sheltered housing facilities (total population = 402) to recruit persons living in these facilities.
Of 612 persons interviewed by the geriatrician, 591 (97%) fulfilling the inclusion criteria were accepted into the study. There are no official registers of fallers available so the use of announcements and informative meetings was the only way to reach recent fallers. The progression of the whole study, inclusion criteria and the content of the whole intervention are presented in Figure 1.
|
The population of this study consisted of all subjects randomized into the intervention group (n = 293) of this multifactorial fall prevention programme.
Intervention
The 1-year intervention consisted of exercise groups, psychosocial group activities, lectures and home-exercises. These activities were based on an individual risk factor analyses. The frequency of organized activities was the same for all participants, but the intensity of exercise and psychosocial group activities was planned separately for each participant according to his/her health status. In addition, the intensity of home-based exercises was increased progressively.
Key activities
Exercise groups: For the exercise groups the subjects were divided into three levels according to their physical functional abilities at baseline assessments (balance, muscle strength and respiratory function). Each exercise session began with warm up exercises (5–10 min), followed by exercises designed to improve lower leg muscle strength, balance and coordination (30 min) and ended up by cool-down exercises (5–10 min). Exercises could be performed in a sitting or standing position according to the subject’ s health and functional status. Sessions were organized twice a month for each group and were held by a physiotherapist.
Psychosocial group activities: Subjects were divided into two groups according to their psychological health, amount of depressive symptoms, feelings of loneliness and level of social activity. Those having few contacts with other people and feeling themselves lonely and whose sum score was over 10 in the Geriatric Depression Scale (GDS)20 were advised to join a smaller ‘support’ group. All the others were advised to join a bigger psychosocial group. The sessions were organized once a month for both groups and held by nursing students.
Lectures: The subjects in the intervention group were offered lectures once a month on preventive aspects of falling, such as walking aids, nutrition in old age, home hazards, physical exercise and overall fall prevention.
Home exercises: The subjects were advised to perform physical exercises similar to those performed in groups 3 times a week at home. The subjects were given a brochure based on the exercise class content and encouraged to record the amount of their physical activity in the physical exercise diaries daily.
Measures
Adherence rate
Adherence was determined as a participation rate in different organized group-activities (physical exercise groups, psychosocial group activities and lectures) and as a number of home-exercise sessions performed per month.
Adherence was measured in four key activities: group-based physical exercises, psychosocial group activities, lectures and home-exercises. The names of the participants were collected before each exercise session, psychosocial group meeting and lecture and verified by each person's own signature. To record the performance of home-exercises, subjects were given monthly diaries which they were advised to fill in daily and to return at the beginning of each month.
To calculate the adherence rates separately for each organized activity (group exercises, psychosocial groups and lectures), the number of sessions attended was divided by the number of sessions offered during the intervention period and multiplied by 100 to get the percentage. An intervention period was determined for each subject individually as a time scale from signing the consent form to the first follow-up visit or the date the person informed not continuing in the study. For the analyses, participants were classified as persons with (i) 0% adherence rate (non-adherence), (ii) 0.1–33.3% adherence rate (low adherence), (iii) 33.4–66.6% adherence rate (moderate adherence) and (iv) 66.7–100% adherence rate (high or full adherence).
To calculate the home-exercise adherence, the total amount of performed home exercise sessions over the intervention period (determined as earlier) was calculated. This amount was then divided by the number of returned monthly exercise diaries to get the monthly home-exercise rates. Monthly rates were then divided by 30 and multiplied by 7 to get weekly home-exercise rates. Participants were then classified as persons performing home-exercises (i) 0–0.99 (ii) 1–2 and (iii) 
3 times a week.
Predictors of adherence
Psychological and cognitive functional abilities
Depressive symptoms were measured by the 30-item Geriatric Depression Scale (GDS) which represents a valid and reliable self-rating scale for depression among the aged.21 Depression was defined according to the validated cut off score; 11 and above indicating a high amount of depressive symptoms.
Fear of falling was measured by one dichotomized (yes/no) question ‘Do you have fear of falling?’
Feelings of loneliness were measured with the question ‘How often do you feel loneliness?’ The answers had five classes, and they were dichotomized as follows: (1) never, seldom or only sometimes and (2) often or always.
Self-perceived risk of falling at home was measured with the question ‘What is your self-perceived probability of a falling event at home?’ The five classes of the answers were dichotomized to (1) quite unlikely or very unlikely and (2) very likely, likely or quite likely.
Self-perceived health was measured by a question with five possible answers classified to (1) very poor or poor, (2) average and (3) good or very good.
Cognitive function was measured by the Mini Mental State Examination (MMSE).22 Those scoring 17–24 sum points were considered to have lowered cognitive abilities and those with 25 or more sum points to be cognitively intact.
Physical functional abilities
Physical functional abilities were graded from very good (1), average (2) to poor (3) on the basis of five different measures; balance measured with Berg's Balance Scale (BBS),23 muscle strength measured by adjustable dynamometer chair (Good Strength®, Metitur, Finland) (classified as very good, average or poor) and peak expiratory flow (PEF). Those having a sum score of BBS 50–56, muscle strength and balance classified as ‘very good’ and PEF over 300 l min–1 were classified as having good physical functional abilities (1). Those having a sum score of BBS 40–49, muscle strength classified as ‘average’ and PEF 200–300 l min–1 were classified as having moderate physical functional abilities (2). Those with a sum score of BBS under 40 and muscle strength classified as ‘poor’ or using walking aids and PEF under 200 l min–1 were classified as having poor physical functional abilities (3).
Medication
All regularly used prescribed medications were recorded during the geriatric assessment by asking the participants and by verifying the information from the medical records at health centre. The amount of these medications was used here by dichotomizing (1) less than four medications (2) four or more medications.
Statistical analyses
For statistical analyses, adherence rates in organized activities were categorized into four categories: 0%, 0.1–33.3%, 33.4–66.6% and 66.7–100% and in home-exercises into three categories: (i) 0–0.99 (ii) 1–2.99 and (iii) 3 times per week. The associations between potential predictors and adherence rates were first analysed by univariate cumulative logistic regression.24 Because the ordinal-type dependent variables (home-exercises and organized activities) consisted of more than two categories, cumulative logistic regression was used instead of the traditional binary logistic regression. In the second phase, independent variables significantly related to the adherence in univariate logistic regression analysis were used as predictors in the multivariate logistic regression analysis. The results of logistic models were quantified by cumulative odds ratios (COR) and their 95% confidence intervals (95% CI). All statistical analyses were performed using SAS System for Windows, version 9.1 (SAS Institute Inc., Cary, NC, USA). P-values less than 0.05 were considered statistically significant.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Background data
The mean age in the intervention group was 73 years, and 86% were women.
Table 1 shows the selected baseline characteristics of the participants in the intervention group.
|
Adherence rate
The mean adherence rate was 58% (SD = 30.2) in physical exercise groups, 25% (SD = 24.6) in psychosocial groups and 33% (SD = 28.2) in lectures. Subjects performed home-exercises on average 3 (SD 2.1) times per week. Of the participants, 47% were highly adherent (67–100% adherence rates) in physical exercise groups, 8% in psychosocial group activities and 14% in lectures (Table 2).
|
Predictors of adherence
In the univariate analysis, lower age, low self-perceived risk of falling at home and better physical functional abilities had the strongest associations with more active physical exercise group adherences. Lower age and higher physical and cognitive functional abilities had the strongest associations with the more active psychosocial group and lecture adherence. Using less than four prescription medicines was the only variable significantly associated with home-exercise adherence and thus omitted from further analyses (Table 3).
|
In the multivariate analyses, lower self-perceived risk of falling at home and better/ physical functional abilities were significant predictors of more active physical exercise group adherence. Good physical and cognitive functional abilities were related to more active psychosocial group adherence. Female gender and good physical and cognitive functional abilities remained significant predictors of more active lecture adherence.
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
The highest adherence rate (58%) was found in the physical exercise groups. Altogether, 92% attended at least one exercise session and 63% took part in at least 50% of the sessions. This finding is consistent with previous fall prevention studies reporting high adherence rates in physical exercise groups among the aged (67–87%).8,13,15,25–27 Especially short-term interventions,25–27 lasting approximately 6 months or less, have been successful in regards to adherence, while in longer interventions adherence tends to decline.16,18,28,29 However, direct comparison between results is difficult due to differences in definitions and measures of adherence and due to inaccurate reporting of the results.
In psychosocial group activities and lectures the adherence rates were lower than in the physical exercise groups. While 73% and 75% attended at least one session, only 16% and 26% attended more than 50% of the psychosocial group activities and lectures, respectively. These rates are, however, partly in accordance with the results of previous studies. Hornbrook et al.3 reported that 78% of the subjects attended at least one health behaviour session in a multifactorial fall prevention intervention. In contrast to our study, the total adherence rate was high; 61% of the subjects attended at least 75% of the sessions, while in our trial only 4–9% attended at least 75% of the psychosocial groups and lectures, respectively. This may be due to the differences in the populations; Hornbrook et al.3 implemented a population-based intervention while we implemented prevention among subjects at increased risk of falling. Five percent of the intervention group participants in our study lived in sheltered housing and had problems to participate in psychosocial and lecture activities due to poor functional abilities or financial reasons. Our budget did not allow us to organize transportation to the sessions, which might have increased adherence. However, the physical exercise group sessions were organized in sheltered housing to facilitate participation.
Home-based exercises appealed to the participants; the average rate of exercising being 3 times per week during the 1-year intervention. In addition, 36% of the participants performed home-exercises at least 3 times a week. Similar results have been reported in previous studies17,28,30 indicating that home exercises may be a suitable form of activity among the aged, even among those with functional limitations.
Good physical functional ability was the strongest predictor of more active adherence in all organized activities. Those with good physical abilities were 2–3 times more likely to adhere compared to those with poor physical functional abilities. A similar association was not found between physical functional abilities and home-exercise adherence. Cognitive abilities were another strong predictor. Higher cognitive abilities remained a significant predictor of psychosocial group and lecture adherence. Those with a MMSE sum score of 25 or over were almost 2.5 times more likely to adhere in psychosocial groups and lectures than those with a MMSE sum score from 17 to 24. Unlike many other fall prevention trials,8,17,28,29,31–33 we also accepted persons with somewhat impaired cognitive abilities (MMSE 17–24) into our study. This may partly explain low adherence, especially in cognitively demanding psychosocial group activities and lectures.
No significant associations were found between psychosocial group or lecture adherence and self-perceived risk of falling or self-perceived health. In addition, a low self-perceived risk of falling was associated with higher physical exercise group adherence and remained a significant predictor of adherence in the multivariate model. These findings are in contrast with the Health Belief Model, which states that a perceived susceptibility of getting a particular condition (here a fall) and its perceived severity predict changes in health behaviour. Even if the fear of falling was quite common among the subjects, falls not leading to medical treatment might not be serious enough to produce a threat needed to fuel the motivation for fall prevention. The aged do not seem to believe that falls may be preventable.
The subjects’ perceived benefits of psychosocial group activities and lectures were probably lower than the perceived benefits of physical exercise activities, where the adherence rates were highest. This is in accordance with the qualitative study of Yardley et al.34 on older person's self- perceived barriers for adherence in multifactorial fall prevention trials, stating that many aged persons, clearly at increased risk of falling, do not perceive being at high risk. In addition, group-based activities do not seem to appeal to everyone, and programmes should be planned according to individual wishes and the needs of the participants.34 The primary aim of the whole project was not to analyse adherence and its predictors and our data did not allow the full application of the theoretical model.
Our data shows that moderate adherence rates are attainable, at least in group and home-exercises, even when the population consists of persons at increased risk of falling. However, motivational and concrete actions to minimize the barriers of participation (e.g. organizing groups near living facilities/housing or offering transportation) should be targeted at those with the poorest physical, cognitive and psychosocial functional abilities who represent the part of the population at highest risk of falling.
Difficulties in recruitment, maintenance of study subjects and low adherence are common problems in intervention studies among the aged.16,18,29,35–37 These factors should be kept in mind during the intervention and follow-up periods. Appropriate activities should be carefully planned before the programme implementation to best suit the specific needs of aged individuals. In addition, good reachability (e.g. by providing transportation or providing activities at living-facilities or near homes), and continuous motivation (e.g. by phone calls, home visits, booster sessions) might increase participation.
|
Acknowledgements |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
This study was funded and supported by The Ministry of Social Affairs and Health, The Hospital District of Southwest Finland, The Hospital District of Satakunta, The Päivikki and Sakari Sohlberg Foundation and The Academy of Finland.
Conflict of interest: None declared.
Key points
|
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
1 Carrol NV, Slattum PW, Cox FM. The cost of falls among the community-dwelling elderly. J Manag Care Pharm (2005) 11:307–16.[Medline]
2 Gillespie LD, Gillespie WJ, Robertson MC, Lamb SE, Cumming RG, Rowe BH. Interventions for preventing falls in elderly people. Cochrane Database Syst Rev (2003) 4:CD000340.[Medline]
3 Hornbrook MC, Stevens VJ, Wingfield DJ, Hollis JF, Greenlick MR, Ory MG. Preventing falls among community-dwelling older persons: results from a randomized trial. Gerontologist (1994) 34:16–23.[Abstract]
4 Tinetti ME, Baker DI, McAvay G, et al. A multifactorial intervention to reduce the risk of falling among elderly people living in the community. N Engl J Med (1994) 331:821–7.
5 Wagner EH, LaCroix AZ, Grothaus L, et al. Preventing disability and falls in older adults: a population-based randomized trial. Am J Public Health (1994) 84:1800–6.
6 Close JC. Prevention of falls in older people. Disabil Rehabil (2005) 27:1061–71.[CrossRef][Web of Science][Medline]
7 Close J, Ellis M, Hooper R, Glucksman E, Jackson S, Swift C. Prevention of falls in the elderly trial (PROFET): a randomised controlled trial. Lancet (1999) 353:93–7.[CrossRef][Web of Science][Medline]
8 Clemson L, Cumming RG, Kendig H, Swann M, Heard R, Taylor K. The effectiveness of a community-based program for reducing the incidence of falls in the elderly: a randomized trial. J Am Geriatr Soc (2004) 52:1487–94.[CrossRef][Web of Science][Medline]
9 Rao SS. Prevention of falls in older patients. Am Fam Physician (2005) 72:81–8.[Web of Science][Medline]
10 Nikolaus T, Bach M. Preventing falls in community-dwelling frail older people using a home intervention team (HIT): results from the randomized Falls-HIT trial. J Am Geriatr Soc (2003) 51:300–5.[CrossRef][Web of Science][Medline]
11 Campbell JA, La Crow SJ, Kerse NM, et al. Randomised controlled trial of prevention of falls in people aged with severe visual impairment: the VIP trial. BMJ (2005) 331:817–26.
12 Fortinsky RH, Iannuzzi-Sucich M, Baker DI, et al. Fall-risk assessment and management in clinical practice: views from healthcare providers. J Am Geriatr Soc (2004) 52:1522–6.[CrossRef][Web of Science][Medline]
13 Hogan DB, MacDonald FA, Betts J, et al. A randomized controlled trial of a community-based consultation service to prevent falls. CMAJ (2001) 165:537–43.
14 Shaw FE, Bond J, Richardson DA, et al. Multifactorial intervention after a fall in older people with cognitive impairment and dementia presenting to the accident and emergency department: randomised controlled trial. BMJ (2003) 326:73.
15 Lord SR, Tiedemann A, Chapman K, et al. The effect of an individualized fall prevention program on fall risk and falls in older people: a randomized, controlled trial. J Am Geriatr Soc (2005) 53:1296–304.[CrossRef][Web of Science][Medline]
16 Day L, Fildes B, Gordon I, Fitzharris M, Flamer H, Lord S. Randomised factorial trial of falls prevention among older people living in their own homes. BMJ (2002) 325:128.
17 Davison J, Bond J, Dawson P, Steen IN, Kenny RA. Patients with recurrent falls attending Accident & Emergency benefit from multifactorial intervention—a randomised controlled trial. Age Ageing (2005) 34:162–8.
18 Cumming RG, Thomas M, Szonyi G, Frampton G, Salkeld G, Clemson L. Adherence to occupational therapist recommendations for home modifications for falls prevention. Am J Occup Ther (2001) 55:641–8.[Web of Science][Medline]
19 Janz K, Champion VL, Stretcher VJ. The Health belief model. In: Health Behavior and Health Education: Theory, Research, and Practice—Glanz K, Rimer BK, Lewis FM, eds. (2002) San Francisco: Jossey-Bass. 45–66.
20 Yesavage JA, Brink TL, Rose TL, et al. Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res (1982) 17:37–49.[CrossRef][Web of Science][Medline]
21 Brink TL, Yesavage JA, Lum O, Heersema P, Adey MB, Rose TL. Screening tests for geriatric depression. Clin Gerontol (1982) 1:37–44.[CrossRef]
22 Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res (1975) 12:189–98.[CrossRef][Web of Science][Medline]
23 Berg KO, Wood-Dauphinee SL, Williams JI, Maki B. Measuring balance in the elderly: validation of an instrument. Can J Public Health (1992) 83(2 Suppl):S7–11.[Web of Science][Medline]
24 Hosmer DW, Lemeshow S. Applied Logistic Regression (2000) 2nd edn. New York: John Wiley & Sons Inc.
25 Liu-Ambrose T, Khan KM, Eng JJ, Janssen PA, Lord SR, McKay HA. Resistance and agility training reduce fall risk in women aged 75 to 85 with low bone mass: a 6-month randomized, controlled trial. J Am Geriatr Soc (2004) 52:657–65.[CrossRef][Web of Science][Medline]
26 Rubenstein LZ, Josephson KR, Trueblood PR, et al. Effects of a group exercise program on strength, mobility, and falls among fall-prone elderly men. J Gerontol A Biol Sci Med Sci (2000) 55:M317–21.
27 Morgan RO, Virnig BA, Duque M, Abdel-Moty E, Devito CA. Low-intensity exercise and reduction of the risk for falls among at-risk elders. J Gerontol A Biol Sci Med Sci (2004) 59:1062–7.[Web of Science][Medline]
28 Barnett A, Smith B, Lord SR, Williams M, Baumand A. Community-based group exercise improves balance and reduces falls in at-risk older people: a randomised controlled trial. Age Ageing (2003) 32:407–14.
29 Nowalk MP, Prendergast JM, Bayles CM, D'Amico FJ, Colvin GC. A randomized trial of exercise programs among older individuals living in two long-term care facilities: the FallsFREE program. J Am Geriatr Soc (2001) 49:859–65.[CrossRef][Web of Science][Medline]
30 Helbostad JL, Sletvold O, Moe-Nilssen R. Effects of home exercises and group training on functional abilities in home-dwelling older persons with mobility and balance problems. A randomized study. Aging Clin Exp Res (2004) 16:113–21.[Web of Science][Medline]
31 Devereux K, Robertson D, Briffa NK. Effects of a water-based program on women 65 years and over: a randomised controlled trial. Aust J Physiother (2005) 51:102–8.[Web of Science][Medline]
32 Wolf SL, Sattin RW, Kutner M, O'Grady M, Greenspan AI, Gregor RJ. Intense tai chi exercise training and fall occurrences in older, transitionally frail adults: a randomized, controlled trial. J Am Geriatr Soc (2003) 51:1693–701.[CrossRef][Web of Science][Medline]
33 Huang TT, Acton GJ. Effectiveness of home visit falls prevention strategy for Taiwanese community-dwelling elders: randomized trial. Public Health Nurse (2004) 21:247–56.[CrossRef]
34 Yardley L, Donovan-Hall M, Francis K, Todd C. Older people's views of advice about falls prevention: a qualitative study. Health Edu Res (2006) Feb 8.
35 Campbell AJ RM, Gardner MM, Norton RN, Tilyard MW, Buchner DM. Randomized controlled trial of a general practice programme of a home based exercise to prevent falls in elderly women. BMJ (1997) 315:1065–9.
36 Carter WB, Elward K, Malmgren J, Martin ML, Larson E. Participation of older adults in health programs and research: a critical review of the literature. Gerontologist (1991) 31:584–92.[Abstract]
37 Nitz JC, Choy NL. The efficacy of a specific balance-strategy training programme for preventing falls among older people: a pilot randomised controlled trial. Age Ageing (2004) 33:52–8.
CiteULike 
Connotea 
Del.icio.us What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||