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É Kovács Semmelweis University, Hungary

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I Jónásné Sztruhár Semmelweis University, Hungary
Old Age Home of the Municipality of Budapest, Hungary

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L Mészáros Semmelweis University, Hungary

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ZS Gyombolai Semmelweis University, Hungary

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A Simon Semmelweis University, Hungary

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V Farkas Semmelweis University, Hungary

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Purpose

Reduced functional mobility is a risk factor for falls. The Timed Up and Go test is a complex measurement tool for functional mobility. Our aims were to assess the functional mobility of: (a) community-living elderly who were participating in an exercise programme (n = 40; mean age = 73.7 years), (b) community-living elderly who were physically inactive (n = 40; mean age = 74.1 years), and (c) institutionalized elderly (n = 40; mean age = 73.5 years) and to compare the results with cut-off values for risk of fall.

Materials and methods

After measuring functional mobility, one-way independent ANOVAs and sample t-tests were used for analysis.

Results

The functional mobility of the active participants was better than that of the inactive (p < .001) and institutionalized participants (p < .001). There was no significant difference between the inactive and institutionalized participants (p = .990). The functional mobility of the active participants was better, whereas the functional mobility of the inactive participants was worse than the cut-off value of 13.5 s for risk of fall for community-living elderly. The functional mobility of the institutionalized participants did not differ from the 15-s reference value for predicting risk of fall.

Conclusion

The results indicate that regular physical activity has a positive effect on maintaining functional mobility among both community-living and institutionalized elderly individuals.

Abstract

Purpose

Reduced functional mobility is a risk factor for falls. The Timed Up and Go test is a complex measurement tool for functional mobility. Our aims were to assess the functional mobility of: (a) community-living elderly who were participating in an exercise programme (n = 40; mean age = 73.7 years), (b) community-living elderly who were physically inactive (n = 40; mean age = 74.1 years), and (c) institutionalized elderly (n = 40; mean age = 73.5 years) and to compare the results with cut-off values for risk of fall.

Materials and methods

After measuring functional mobility, one-way independent ANOVAs and sample t-tests were used for analysis.

Results

The functional mobility of the active participants was better than that of the inactive (p < .001) and institutionalized participants (p < .001). There was no significant difference between the inactive and institutionalized participants (p = .990). The functional mobility of the active participants was better, whereas the functional mobility of the inactive participants was worse than the cut-off value of 13.5 s for risk of fall for community-living elderly. The functional mobility of the institutionalized participants did not differ from the 15-s reference value for predicting risk of fall.

Conclusion

The results indicate that regular physical activity has a positive effect on maintaining functional mobility among both community-living and institutionalized elderly individuals.

Introduction

The elderly are the fastest growing age group worldwide, where falling is the most common cause of their fractures, long-lasting immobilization, and loss of independence [1, 2]. By 2030, the proportion of adults aged 65 years or over will account for about 30% of population [3]. About 30% of community-living people aged 65 or over fall each year, and this rate may be as high as 50% among the institutionalized elderly [4, 5]. Although falling is a multifactorial event – that is, a result of the simultaneous effects of several factors – according to the literature, reduced functional mobility is a constant risk factor [1, 69]. Functional mobility describes a person’s ability to move around in the environment to pursue the activities of daily living (ADL). The elements of functional mobility include rising from a chair, sitting down, walking, turning, etc. For this reason, the majority of tests to identify older adults at risk of falling is used to measure one or more of these elements [10].

The Timed Up and Go (TUG) test is a complex measurement tool for functional mobility and a frequent and widespread method of screening those who are prone to fall, including both the community-living and institutionalized elderly [11, 12]. It measures the time (in seconds) needed for an individual to stand up from a chair (with back support) of standard seat height (usually 42–46 cm), walk 3 m, turn around, walk back to the chair, and sit down. A shorter time indicates better functional mobility [11]. The result of this quick, easy-to-perform, and safe test is proven to correlate with the results of several other tests that require more time. Among the frail elderly, results of the TUG test correlate with the Berg Balance Scale (r = −.81), the walking-speed test (r = −.61), and the Barthel Index (r = −.78) [11]. Among community-living elderly, the results of the TUG test correlate with the results of the Tinetti Performance-Oriented Mobility Assessment (balance r = −.55; gait = 0.53), the walking-speed test (r = −.66), and a scale assessing ADL activities (r = −.45) [13].

The TUG test as an assessment of the risk of falling was investigated in several elderly populations with the following cut-off values: Among community-living elderly, the cut-off value of 13.5 s could identify elderly who were “at risk of falling” [14]. Among elderly referred to a fall clinic, the cut-off value of 15 s could identify those who required detailed physiotherapy assessment and targeted intervention [15].

Our aim was twofold. Using the TUG test, the first thing is to assess the functional mobility in three groups: (a) community-living elderly who were participating in a regular exercises programme, (b) community-living elderly who were physically inactive, and (c) institutionalized elderly who were living in a nursing home; and then to compare the results of the TUG tests to cut-off values for risk of falling published in the geriatric literature.

Materials and Methods

Participants

This cross-sectional study was conducted in February 2018, in Budapest, Hungary, with the participation of 120 elderly individuals, and in accordance with the 2008 revision of the 1975 Declaration of Helsinki. Inclusion criteria were: (a) age of 60 years or over, (b) ability to walk with or without an assistive device, and (c) no cognitive or sensory impairment that would interfere with the TUG test. The inactive and institutionalized participants were matched by age and gender to the active participants. The maximum age difference was stipulated as 6 years. The mean age in each group was about 74 years. The community-living elderly who were physically active were recruited from attendees of a 60-plus exercise programme. The community-living elderly who were physically inactive were recruited through advertisements in local newspapers, from senior centres, and from religious communities. They were asked to continue their usual daily life, and not to take part in any exercise programmes. The institutionalized elderly were recruited from a nursing home. They participated in a group-based multimodal exercise programme twice a week. This exercise programme consisted of strengthening and balance exercises. The strengthening exercises directed to lower limb muscles playing role in the postural control such as knee extensors, hip extensors, hip abductors, and ankle muscles, using the patients’ body weight. The balance exercises related to everyday activity, including stepping forward, sideway, and backward; walking with and without changing direction; timed stand practice (standing on one leg and tandem stance); and sit-to-stand practice.

Assessments

Data were collected through a questionnaire (for the community-living participants), institutional documentation (for the institutionalized participants), and a physiotherapist-administered TUG test (for all participants). The participants’ age, gender, weight, and height were collected, and their body mass index (BMI) was calculated. Their history of chronic diseases, including cardiopulmonary disease, hypertension, diabetes mellitus, and lower limb arthritis, were also collected. During the TUG test, habitual footwear or walking aids was allowed. Participants were also allowed to use arm support for rising, if necessary. Two consecutive trials were averaged. Between the trials, there was a 30-s rest time, if needed. A longer time indicated worse functional mobility. The TUG tests had high interrater (interclass correlation coefficients = .99) and intrarater (intraclass correlation coefficients = .99) reliability [16].

Procedure

After participants were informed about the purpose and procedure of the study and their right to withdraw at any time, their written informed consent was obtained, and the data were gathered within a 2-week period. The testing was always performed in the morning.

Statistical analysis

Continuous data were given as a mean with a standard deviation (SD) and discrete data were given as frequencies and percentages. Normal distributions were verified by skewness and kurtosis, as well as the Shapiro–Wilk test. One-way analyses of variance (ANOVAs) and χ2 tests were used to analyse the descriptive values of the three groups. If the ANOVAs indicated significant differences, post-hoc tests according to the Games–Howell method were used to perform pairwise comparisons between the groups. One-sample t-tests were used to compare the TUG score of each group to the reference value for the risk of falling. Statistical analyses were carried out with PASW Statistics for Windows, version 18.0 (SPSS Inc., Released 2009, Chicago, IL, USA). The values of p less than .05 were considered significant.

Results

Characteristics of the study sample are shown in Table 1.

Table 1.

Characteristics of the study sample

Physically active community-living elderly (n = 40) Physically inactive community-living elderly (n = 40) Institutionalized elderly (n = 40) p
Age (years) [mean (SD)] 73.7 (8.2) 74.1 (12.1) 73.5 (7.8) .976
BMI (kg/m2) [mean (SD)] 22.4 (5.9) 26.9 (5.3) 27.2 (4.4) <.001
Male [frequency (%)] 3 (8) 10 (25) 4 (10) .750
Female [frequency (%)] 37 (92) 30 (75) 36 (90)
Medical history
Cardiopulmonal disease [number (%)] 7 (17) 28 (70) 13 (32) <.001
Hypertension [number (%)] 27 (67) 29 (72) 34 (85) .072
Diabetes mellitus [number (%)] 7 (17) 16 (40) 13 (32) .145
Lower limb osteoarthritis [number (%)] 12 (30) 34 (85) 30 (75) <.001
Number of chronic diseases [mean (SD)] 1.78 (1.1) 3.15 (1.4) 3.08 (1.6) <.001
TUG (s) [mean (SD)] 10.8 (3.3) 15.1 (1.9) 15.2 (1.9) <.001

Note. Data are presented as mean and standard deviation for continuous data and frequency and percentage for categorical data. SD: standard deviation; BMI: body mass index; TUG: Timed Up and Go.

In terms of BMI, there was a statistically significant difference between groups [F(2, 117) = 9.498, p < .001]. The results of the post-hoc test showed that the BMI of the active participants was significantly lower than the BMI of both the inactive (p = .001) and institutionalized participants (p = .001). Simultaneosuly, the difference between the inactive and the institutionalized participants was not statistically significant (p = .975).

As for the chronic diseases, among the active participants, there were significantly fewer individuals with cardiopulmonary disease and/or lower limb osteoarthritis compared to the inactive and institutionalized participants. There was a statistically significant difference between groups [F(2, 117) = 15.817, p < .001]. The post-hoc test revealed that the active participants suffered from significantly less chronic diseases compared to both the inactive (p < .001) and institutionalized participants (p < .001). However, the difference between the inactive and the institutionalized participants was not statistically significant (p = .964).

In the TUG test, there was a statistically significant difference [F(2, 117) = 27.174, p < .001]. The results of the post-hoc test showed that the active participants performed the TUG test significantly better than the inactive (p < .001) and institutionalized participants (p < .001). At the same time, there was no significant difference between the inactive and the institutionalized participants (p = .990).

The results of the TUG test for the active participants (M = 10.07 s, SD = 3.3) was significantly better by 3.43 s (95% CI [2.36, 4.48]) than the 13.5 s reference value for the risk of falling [t(39) = −6.549, p < .001]. As for the inactive participants, their performance of the TUG test was significantly worse by 1.67 s (95% CI [1.04, 2.26]) than the 13.5-s reference value for the risk of falling [t(39) = 5.467, p < .001]. The performance of the institutionalized participants did not differ significantly from the 15-s reference value for the risk of falling [t(39) = 0.913, p = .367].

Discussion and Conclusions

The aims of this study were to assess the functional mobility of three groups: (a) community-living elderly who were participating in a regular exercises programme, (b) community-living elderly who were physically inactive, and (c) institutionalized elderly who were living in a nursing home. We analysed their functional mobility with the TUG test. Furthermore, we compared the results of the TUG test results for each group to cut-off values for the risk of falling published in the geriatric literature.

The guidelines for assessment and prevention of falls, published by the American Geriatrics Society and British Geriatrics Society nearly two decades ago, recommend applying the TUG test as the first step of a screening algorithm to identify elderly people who are at risk of falling [17, 18]. For this reason, we considered it important to assess the functional mobility of elderly people who were participating in an exercise programme, that is, those who were in the everyday care of a physiotherapist.

We found that the functional mobility of the active participants was significantly better than the 13.5-s cut-off value for the risk of falling for community-living elderly individuals [14]. This result can be attributed to the fact that members of this group participated in an exercise programme consisting of muscle strengthening, flexibility, balance, and walking exercises once or twice a week for at least 6 months. At the same time, the functional mobility of the community-living elderly who were inactive was significantly worse compared to the 13.5-s cut-off value. This result of our study showed that the inactive participants were especially prone to falling and therefore this population requires additional detailed assessment and targeted intervention. Despite the fact that the functional abilities of older people living in a long-term institution usually decline, we found that the functional mobility of elderly individuals living in a nursing home did not differ from the cut-off value of 15 s for the risk of falling [15]. This finding can be explained by the fact that although the elderly who are admitted to a long-term care institution have lost their independence due to physical or mental deterioration, they can still participate in programmes aiming to maintain their functional mobility.

There are some limitations of this study, which must be acknowledged. First, the participants were recruited using a non-probability sampling method. Thus, our results cannot be extrapolated to elderly people who are not willing to participate in exercise programmes. In addition, we used a cross-sectional design, which might reduce the strength of our evidence. Therefore, further retrospective or prospective studies are needed to confirm our results. Finally, differences in the TUG test could be attributed to differences in the number of chronic diseases. Therefore, future studies would be worth conducting on a more homogeneous sample recruited from a larger sample frame.

Despite the limitations, our results indicate that regular physical activity has a positive effect on maintaining the functional mobility of both community-living and institutionalized elderly individuals.

Some recent studies conducted on children, with and without physical disabilities, applied the TUG test to measuring functional mobility, suggesting a more widespread use of this test [1921]. The normal values for the age group from 3 to 18 years have recently been published [22, 23]. In Hungary, several research teams are investigating the effects of neurological interventions among children with neurological disorders [2429]. Therefore, future research is worth conducting in order to use the TUG test to reveal the functional mobility of Hungarian children.

To sum up the results of this study, the attention of health care professionals working in geriatrics should be called to the fact that community-living elderly individuals who are physically inactive are at risk of falling. It is important to design programmes that motivate them to have a physically active lifestyle. Simultaneously, programmes must be safe, considering the multimorbidity and actual condition of older people. According to these considerations, the physiotherapist plays an important role in and is responsible for the design and modification of the content presented in the exercise programmes.

Acknowledgements

The authors would like to thank all participants for their contribution in the study, especially Anikó Virág who delivered the 60-plus programme.

Authors’ contribution

ÉK and AS summarized the scientific background of the paper and carried out the statistical analyses. IJSz and LM collected the data and performed the necessary calculations. AS, ZsG, and VF finalized the manuscript.

Ethical approval

This study was conducted in accordance with the 2008 revision of the 1975 Declaration of Helsinki.

Conflicts of Interest/Funding

The authors declare no conflict of interest. This study was supported by the National Bionics Program ED_17-1-2017-0009.

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  • 1.

    Terroso M , Rosa N , Torres Marques A , Simones R . Physical consequences of falls in the elderly: a literature review from 1995 to 2010. Eur Rev Aging Phys Act. 2014;11(1):519.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2.

    Kumar A , Carpenter H , Morris R , Iliffe S , Kendrick D . Which factors are associated with fear of falling in community-dwelling older people? Age Ageing. 2014;43(1):7684.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Population Division. World Population Prospects 2019, Online Edition [Internet]. United Nations, Department of Economic and Social Affairs; 2019 [cited 2018 Sep 20]. Available from: https://population.un.org/wpp/Download/Probabilistic/Population/

    • Search Google Scholar
    • Export Citation
  • 4.

    Masud T , Morris RO . Epidemiology of falls. Age Ageing. 2001;30(Suppl. 4):37.

  • 5.

    Rubenstein LZ . Falls in older people: epidemiology, risk factors and strategies for prevention. Age Ageing. 2006;35(Suppl. 2):ii3741.

  • 6.

    Rubenstein LZ , Josephson KR . Falls and their prevention in elderly people: what does the evidence show? Med Clin N Am. 2006;90(5):80724.

  • 7.

    WHO. WHO Global Report on Falls Prevention in Older Age [Internet]. Geneva, Switzerland: World Health Organization; 2007 [cited 2018 Sep 20]. Available from: http://www.who.int/ageing/publications/Falls_prevention7March.pdf?ua=1

    • Search Google Scholar
    • Export Citation
  • 8.

    Ganz DA , Bao Y , Shekelle PG , Rubenstein LZ . Will my patient fall? JAMA. 2007;297(1):7786.

  • 9.

    Singh DK , Pillai SG , Tan ST , Tai CC , Shahar S . Association between physiological falls risk and physical performance tests among community-dwelling older adults. Clin Interv Aging. 2015;13(10):131926.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    Oliver D , Daly F , Martin FC , McMurdo ME . Risk factors and risk assessment tools for falls in hospital in-patients: a systematic review. Age Ageing. 2004;33(2):12230.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 11.

    Podsiadlo D , Richardson S . Timed Up and Go: a test of basic functional mobility for frail elderly persons. J Am Geritr Soc. 1990;39(2):1418.

    • Search Google Scholar
    • Export Citation
  • 12.

    Steffen TS , Hacker TA , Mollinger L. Age- and gender-related tests performance in community-dwelling elderly people: Six-Minute Walk Test, Berg Balance Test, Timed Up and Go test and Gait speeds. Phys Ther. 2003;82(2):12837.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    Lin MR , Hwang HF , Hu MH , Wu HD , Wang YW , Huang FC . Psychometric comparisons of the timed up and go, one-leg stand, functional reach, and Tinetti balance measures in community-dwelling older people. J Am Geriatr Soc. 2004;52(8):13438.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Shumway-Cook A , Brauer S , Woollacott M . Predicting the probability for falls in community-dwelling older adults using the Timed Up & Go Test. Phy Ther. 2000;80(9):896903.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Whitney JC , Lord SR , Close JC . Streamlining assessment and intervention in a falls clinic using the Timed Up and Go test and physiological profile assessments. Age Ageing. 2005;34(6):56771.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16.

    VanSwearingen JM , Brach JS . Making geriatric assessment work: selecting useful measures. Phys Ther. 2001;81(1):123352.

  • 17.

    Panel on Prevention of Falls in Older Persons, American Geriatrics Society and British Geriatrics Society. Summary of the Updated American Geriatrics Society/British Geriatrics Society clinical practice guideline for prevention of falls in older persons. J Am Geriatr Soc. 2011;59(1):14857.

    • Search Google Scholar
    • Export Citation
  • 18.

    NICE. Falls: Assessment and Prevention of Falls in Older People [Internet]. Manchester: National Institute for Health and Care Excellence; 2013 [cited 2018 Sep 20]. Available from: https://www.nice.org.uk/guidance/cg161/evidence/falls-full-guidance-190033741

    • Search Google Scholar
    • Export Citation
  • 19.

    Carey H , Martin K , Combs-Miller S , Heathcock JC . Reliability and responsiveness of the timed up and go test in children with cerebral palsy. Pediatr Phys Ther. 2016;28(4):4018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20.

    Hassani S , Krzak JJ , Johnson B , et al. One-Minute Walk and modified Timed Up and Go tests in children with cerebral palsy: performance and minimum clinically important differences. Dev Med Child Neurol. 2014;56(5):4829.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21.

    Nicolini-Panisson RD , Donadio MV . Timed “Up & Go” test in children and adolescents. Rev Paul Pediatr. 2013;31(3):37783.

  • 22.

    Nicolini-Panisson RD , Donadio MV . Normative values for the Timed ‘Up and Go’ test in children and adolescents and validation for individuals with Down syndrome. Dev Med Child Neurol. 2014;56(5):4907.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23.

    Itzkowitz A , Kaplan S , Doyle M , et al. Timed Up and Go: reference data for children who are school age. Pediatr Phys Ther. 2016;28(2):23946.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24.

    Medveczky E , Nyakas CS , Bretz K . Complex biomechanical research methods used for pediatric neurorehabilitation of neuromuscular dystrophy diseases. Dev Health Sci. 2018;1(1):113.

    • Search Google Scholar
    • Export Citation
  • 25.

    Schultheisz J , Kereskényi B , Révész O . Innovations by Gézengúz Foundation. Dev Health Sci. 2018;1(1):147.

  • 26.

    Mézám ZS , Schweitzer N , Jakab A , et al. The Dévény special manual technique – Gymnastics method. Dev Health Sci. 2018;1(1):1820.

    • Search Google Scholar
    • Export Citation
  • 27.

    Bod M , Szűcs S . Aspects of early movement therapy in line with the medical diagnosis. Dev Health Sci. 2018;1(1):223.

  • 28.

    Berényi M . How early is too late? Dev Health Sci. 2018;1(1):246.

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    Szabó Feketéné É , Gruber M . Opportunities of conductive education in early intervention. Dev Health Sci. 2018;1(1):302.

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Senior Editors

Editor-in-Chief: Zoltán Zsolt NAGY
Vice Editors-in-Chief: Gabriella Bednárikné DÖRNYEI, Ákos KOLLER
Managing Editor: Johanna TAKÁCS

Editorial Board

  • Zoltán BALOGH (Department of Nursing, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Klára GADÓ (Department of Clinical Studies, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • István VINGENDER (Department of Social Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Attila DOROS (Department of Imaging and Medical Instrumentation, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Judit Helga FEITH (Department of Social Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Mónika HORVÁTH (Department of Physiotherapy, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Illés KOVÁCS (Department of Clinical Ophthalmology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Ildikó NAGYNÉ BAJI (Department of Applied Psychology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Tamás PÁNDICS (Department for Epidemiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • József RÁCZ (Department of Addictology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Lajos A. RÉTHY (Department of Family Care Methodology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • János RIGÓ (Department of Clinical Studies in Obstetrics and Gynaecology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Andrea SZÉKELY (Department of Oxyology and Emergency Care, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Márta VERESNÉ BÁLINT (Department of Dietetics and Nutritional Sicences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Gyula DOMJÁN (Department of Clinical Studies, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Péter KRAJCSI (Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • György LÉVAY (Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Csaba NYAKAS (Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Vera POLGÁR (Department of Morphology and Physiology, InFaculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • László SZABÓ (Department of Family Care Methodology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Katalin TÁTRAI-NÉMETH (Department of Dietetics and Nutrition Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Katalin KOVÁCS ZÖLDI (Department of Social Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Gizella ÁNCSÁN (Library, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • András FALUS (Department of Genetics, Cell- and Immunbiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary)
  • Zoltán UNGVÁRI (Department of Public Health, Faculty of medicine, Semmelweis University, Budapest, Hungary)
  • Romána ZELKÓ (Faculty of Pharmacy, Semmelweis University, Budapest, Hungary)
  • Mária BARNAI (Faculty of Health Sciences and Social Studies, University of Szeged, Szeged, Hungary)
  • László Péter KANIZSAI (Department of Emergency Medicine, Medical School, University of Pécs, Pécs, Hungary)
  • Bettina FŰZNÉ PIKÓ (Department of Behavioral Sciences, Faculty of Medicine, University of Szeged, Szeged, Hungary)
  • Imre SEMSEI (Faculty of Health, University of Debrecen, Debrecen, Hungary)
  • Teija-Kaisa AHOLAAKKO (Laurea Universities of Applied Sciences, Vantaa, Finland)
  • Ornella CORAZZA (University of Hertfordshire, Hatfield, Hertfordshire, United Kingdom)
  • Oliver FINDL (Department of Ophthalmology, Hanusch Hospital, Vienna, Austria)
  • Tamás HACKI (University Hospital Regensburg, Phoniatrics and Pediatric Audiology, Regensburg, Germany)
  • Xu JIANGUANG (Shanghai University of Traditional Chinese Medicine, Shanghai, China)
  • Paul GM LUITEN (Department of Molecular Neurobiology, University of Groningen, Groningen, Netherlands)
  • Marie O'TOOLE (Rutgers School of Nursing, Camden, United States)
  • Evridiki PAPASTAVROU (School of Health Sciences, Cyprus University of Technology, Lemesos, Cyprus)
  • Pedro PARREIRA (The Nursing School of Coimbra, Coimbra, Portugal)
  • Jennifer LEWIS SMITH (Collage of Health and Social Care, University of Derby, Cohehre President, United Kingdom)
  • Yao SUYUAN (Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China)
  • Valérie TÓTHOVÁ (Faculty of Health and Social Sciences, University of South Bohemia, České Budějovice, Czech Republic)
  • Tibor VALYI-NAGY (Department of Pathology, University of Illonois of Chicago, Chicago, IL, United States)
  • Chen ZHEN (Central European TCM Association, European Chamber of Commerce for Traditional Chinese Medicine)
  • Katalin LENTI FÖLDVÁRI-NAGY LÁSZLÓNÉ (Department of Morphology and Physiology, Semmelweis University, Budapest, Hungary)
  • László FÖLDVÁRI-NAGY (Department of Morphology and Physiology, Semmelweis University, Budapest, Hungary)

2020  

CrossRef
Documents

9
CrossRef Cites 8
CrossRef H-index 2
Days from submission to acceptance 219
Days from acceptance to publication 176
Acceptance
Rate
47%

 

 

2019  
CrossRef
Documents
13
Acceptance
Rate
83%

 

Developments in Health Sciences
Publication Model Online only Gold Open Access
Submission Fee none
Article Processing Charge none
Subscription Information Gold Open Access

Developments in Health Sciences
Language English
Size A4
Year of
Foundation
2018
Volumes
per Year
1
Issues
per Year
2
Founder Semmelweis Egyetem
Founder's
Address
H-1085 Budapest, Hungary Üllői út 26.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2630-9378 (Print)
ISSN 2630-936X (Online)

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