retrospective case control study physiotherapy

QuestionsAnswered.net

What's Your Question?

What Is a Case Study?

When you’re performing research as part of your job or for a school assignment, you’ll probably come across case studies that help you to learn more about the topic at hand. But what is a case study and why are they helpful? Read on to learn all about case studies.

Deep Dive into a Topic

At face value, a case study is a deep dive into a topic. Case studies can be found in many fields, particularly across the social sciences and medicine. When you conduct a case study, you create a body of research based on an inquiry and related data from analysis of a group, individual or controlled research environment.

As a researcher, you can benefit from the analysis of case studies similar to inquiries you’re currently studying. Researchers often rely on case studies to answer questions that basic information and standard diagnostics cannot address.

Study a Pattern

One of the main objectives of a case study is to find a pattern that answers whatever the initial inquiry seeks to find. This might be a question about why college students are prone to certain eating habits or what mental health problems afflict house fire survivors. The researcher then collects data, either through observation or data research, and starts connecting the dots to find underlying behaviors or impacts of the sample group’s behavior.

Gather Evidence

During the study period, the researcher gathers evidence to back the observed patterns and future claims that’ll be derived from the data. Since case studies are usually presented in the professional environment, it’s not enough to simply have a theory and observational notes to back up a claim. Instead, the researcher must provide evidence to support the body of study and the resulting conclusions.

Present Findings

As the study progresses, the researcher develops a solid case to present to peers or a governing body. Case study presentation is important because it legitimizes the body of research and opens the findings to a broader analysis that may end up drawing a conclusion that’s more true to the data than what one or two researchers might establish. The presentation might be formal or casual, depending on the case study itself.

Draw Conclusions

Once the body of research is established, it’s time to draw conclusions from the case study. As with all social sciences studies, conclusions from one researcher shouldn’t necessarily be taken as gospel, but they’re helpful for advancing the body of knowledge in a given field. For that purpose, they’re an invaluable way of gathering new material and presenting ideas that others in the field can learn from and expand upon.

MORE FROM QUESTIONSANSWERED.NET

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• Advanced Search
• Journal List
• Ann Rheum Dis
• v.60(8); 2001 Aug

A case-control study to investigate the relation between low and moderate levels of physical activity and osteoarthritis of the knee using data collected as part of the Allied Dunbar National Fitness Survey

BACKGROUND —Physical activity is being recommended as an intervention for seemingly almost universal improvements to health. A potential concern with this recommendation for increased exercise is that some believe increased levels of activity may lead to increased incidence of osteoarthritis of the knee (knee OA), as a result of accelerated "wear and tear" of the major joints. OBJECTIVE —To investigate the hypothesis that the occurrence of knee OA may be related to the duration of participation in some forms of sport and active recreation. METHODS —The relation between habitual exercise, reported by a cross section of people surveyed in England, and self reported knee OA was investigated. Data were derived from the Allied Dunbar National Fitness Survey (1990-91). A matched retrospective case-control design was used and a new exposure classification system which categorised different grades of activities for different time periods for each subject's lifetime participation in regular physical activities was developed. Additional data on knee injuries sustained and bodily composition were also included in a multivariate analysis. RESULTS —From 4316 people originally interviewed, 216 eligible cases (66 men, 150 women) were identified (mean age 57.1). Each case was matched to four controls. When habitual sport/exercise participation were examined during a subject's life, only exposure to regular long walks and being physically active between the ages of 20   and 24 suggested any association with developing knee OA later in life. The only strong association found was a greatly increased risk of knee OA having previously sustained a knee injury (p<0.01, odds ratio 8.0 (95% confidence interval 2.0 to 32.0)). CONCLUSIONS —There was little evidence to suggest that increased levels of regular physical activity throughout life lead to an increased risk of knee OA later in life. Previous knee injury was associated with an increased risk of knee OA. Additionally, most injuries were caused through participation in physical activities. Hence, when deciding on participation in activities, it is worth taking the likelihood of joint injury into consideration, as the chance of injury is greater in some activities than others.

The Full Text of this article is available as a PDF (177K).

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

• Pate RR, Pratt M, Blair SN, Haskell WL, Macera CA, Bouchard C, Buchner D, Ettinger W, Heath GW, King AC, et al. Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA. 1995 Feb 1; 273 (5):402–407. [ PubMed ] [ Google Scholar ]
• Lane NE. Exercise: a cause of osteoarthritis. J Rheumatol Suppl. 1995 Feb; 43 :3–6. [ PubMed ] [ Google Scholar ]
• Kujala UM, Kaprio J, Sarna S. Osteoarthritis of weight bearing joints of lower limbs in former élite male athletes. BMJ. 1994 Jan 22; 308 (6923):231–234. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• West RR. Valuation of life in long run health care programmes. Br Med J (Clin Res Ed) 1985 Oct 19; 291 (6502):1139–1141. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Spector TD, Harris PA, Hart DJ, Cicuttini FM, Nandra D, Etherington J, Wolman RL, Doyle DV. Risk of osteoarthritis associated with long-term weight-bearing sports: a radiologic survey of the hips and knees in female ex-athletes and population controls. Arthritis Rheum. 1996 Jun; 39 (6):988–995. [ PubMed ] [ Google Scholar ]
• White JA, Wright V, Hudson AM. Relationships between habitual physical activity and osteoarthrosis in ageing women. Public Health. 1993 Nov; 107 (6):459–470. [ PubMed ] [ Google Scholar ]
• Hannan MT, Felson DT, Anderson JJ, Naimark A. Habitual physical activity is not associated with knee osteoarthritis: the Framingham Study. J Rheumatol. 1993 Apr; 20 (4):704–709. [ PubMed ] [ Google Scholar ]
• McAlindon TE, Wilson PW, Aliabadi P, Weissman B, Felson DT. Level of physical activity and the risk of radiographic and symptomatic knee osteoarthritis in the elderly: the Framingham study. Am J Med. 1999 Feb; 106 (2):151–157. [ PubMed ] [ Google Scholar ]
• Cheng Y, Macera CA, Davis DR, Ainsworth BE, Troped PJ, Blair SN. Physical activity and self-reported, physician-diagnosed osteoarthritis: is physical activity a risk factor? J Clin Epidemiol. 2000 Mar 1; 53 (3):315–322. [ PubMed ] [ Google Scholar ]
• Chamberlain MA, Care G, Harfield B. Physiotherapy in osteoarthrosis of the knees. A controlled trial of hospital versus home exercises. Int Rehabil Med. 1982; 4 (2):101–106. [ PubMed ] [ Google Scholar ]
• Fisher NM, Pendergast DR, Gresham GE, Calkins E. Muscle rehabilitation: its effect on muscular and functional performance of patients with knee osteoarthritis. Arch Phys Med Rehabil. 1991 May; 72 (6):367–374. [ PubMed ] [ Google Scholar ]
• Marks R. The effect of isometric quadriceps strength training in mid-range for osteoarthritis of the knee. Arthritis Care Res. 1993 Mar; 6 (1):52–56. [ PubMed ] [ Google Scholar ]
• Fisher NM, Gresham GE, Abrams M, Hicks J, Horrigan D, Pendergast DR. Quantitative effects of physical therapy on muscular and functional performance in subjects with osteoarthritis of the knees. Arch Phys Med Rehabil. 1993 Aug; 74 (8):840–847. [ PubMed ] [ Google Scholar ]
• O'Reilly SC, Jones A, Muir KR, Doherty M. Quadriceps weakness in knee osteoarthritis: the effect on pain and disability. Ann Rheum Dis. 1998 Oct; 57 (10):588–594. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Ettinger WH, Jr, Burns R, Messier SP, Applegate W, Rejeski WJ, Morgan T, Shumaker S, Berry MJ, O'Toole M, Monu J, et al. A randomized trial comparing aerobic exercise and resistance exercise with a health education program in older adults with knee osteoarthritis. The Fitness Arthritis and Seniors Trial (FAST). JAMA. 1997 Jan 1; 277 (1):25–31. [ PubMed ] [ Google Scholar ]
• Hadler NM. Knee pain is the malady--not osteoarthritis. Ann Intern Med. 1992 Apr 1; 116 (7):598–599. [ PubMed ] [ Google Scholar ]
• Altman R, Asch E, Bloch D, Bole G, Borenstein D, Brandt K, Christy W, Cooke TD, Greenwald R, Hochberg M, et al. Development of criteria for the classification and reporting of osteoarthritis. Classification of osteoarthritis of the knee. Diagnostic and Therapeutic Criteria Committee of the American Rheumatism Association. Arthritis Rheum. 1986 Aug; 29 (8):1039–1049. [ PubMed ] [ Google Scholar ]
• O'Reilly SC, Muir KR, Doherty M. Screening for pain in knee osteoarthritis: which question? Ann Rheum Dis. 1996 Dec; 55 (12):931–933. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Ury HK. Efficiency of case-control studies with multiple controls per case: continuous or dichotomous data. Biometrics. 1975 Sep; 31 (3):643–649. [ PubMed ] [ Google Scholar ]
• Wacholder S, Silverman DT, McLaughlin JK, Mandel JS. Selection of controls in case-control studies. III. Design options. Am J Epidemiol. 1992 May 1; 135 (9):1042–1050. [ PubMed ] [ Google Scholar ]
• Cooper C, Coggon D. Physical activity and knee osteoarthritis. Lancet. 1999 Jun 26; 353 (9171):2177–2178. [ PubMed ] [ Google Scholar ]
• Maetzel A, Mäkelä M, Hawker G, Bombardier C. Osteoarthritis of the hip and knee and mechanical occupational exposure--a systematic overview of the evidence. J Rheumatol. 1997 Aug; 24 (8):1599–1607. [ PubMed ] [ Google Scholar ]

Figures and Tables

CRIS Current Research Information System

Background: During COVID-19 pandemic, physiotherapy lecturers faced the challenge of rapidly shifting from face-to-face to online education. This retrospective case-control study aims to compare students’ satisfaction and performances shown in an online course to a control group of students who underwent the same course delivered face-to-face in the previous five years. Methods: Between March and April 2020, a class (n = 46) of entry-level physiotherapy students (University of Verona - Italy), trained by an experienced physiotherapist, had 24-hours online lessons. Students exposed to the same course in the previous five academic years (n = 112), delivered with face-to-face conventional lessons, served as a historical control. The course was organized in 3 sequential phases: (1) PowerPoint presentations were uploaded to the University online platform, (2) asynchronous video recorded lectures were provided on the same platform, and (3) between online lectures, the lecturer and students could communicate through an email chat to promote understanding, dispel any doubts and collect requests for supplementary material (e.g., scientific articles, videos, webinars, podcasts). Outcomes were: (1) satisfaction as routinely measured by University with a national instrument and populated in a database; (2) performance as measured with an oral examination. Results: We compared satisfaction with the course, expressed on a 5-point Likert scale, resulting in no differences between online and face-to-face teaching (Kruskal-Wallis 2 = 0.24, df = 1, p = 0.62). We weighted up students’ results by comparing their mean performances with the mean performances of the same course delivered face-to-face in the previous five years, founding a statistical significance in favour of online teaching (Wilcoxon rank sum test W = 1665, p &lt; 0.001). Conclusions: Online teaching in entry-level Physiotherapy seems to be a feasible option to face COVID-19 pandemic, as satisfies students as well as face-to-face courses and leading to a similar performance. Entry-level Bachelors in Physiotherapy may consider moving to eLearning to facilitate access to higher education. Universities will have to train lecturers to help them develop appropriate pedagogical skills, and supply suitable support in terms of economic, organizational, and technological issues, aimed at guaranteeing a high level of education to their students. Trial registration: Retrospectively registered.

Online teaching in physiotherapy education during COVID-19 pandemic in Italy: a retrospective case-control study on students’ satisfaction and performance

Rossettini g.; geri t.; turolla a. ; viceconti a.; scuma c.; mirandola m.; dell'isola a.; gianola s.; maselli f.; palese a., scheda breve scheda completa scheda completa (dc).

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

social impact

Conferma cancellazione.

Sei sicuro che questo prodotto debba essere cancellato?

simulazione ASN

• Home Start here
• Editorial Board Member
• Join Our Editorial Board
• Online Submission
• Current Issue
• Call For conference
• Upcoming Conferences
• Copyright Form
• Manuscript Template
• Author Guideline
• Volume 06 Issue 09 September 2018
• Case Control Study – Retrospective 6 Years Follow Up – Adherence to Physiotherapy in Movement Disorder
• " onclick="window.open(this.href,'win2','status=no,toolbar=no,scrollbars=yes,titlebar=no,menubar=no,resizable=yes,width=640,height=480,directories=no,location=no'); return false;" rel="nofollow"> Print

Title:  Case Control Study – Retrospective 6 Years Follow Up – Adherence to Physiotherapy in Movement Disorder

Authors: Dr S.S.Subramanian, Senthilnathan C.V, Rajalaxmi. V

Corresponding Author

Introduction: study of movement disorders and their impact mainly among elderly population needs more emphasis as longeivity is increasing every year globally WHO projected 60% of the population above 60 years, to be geriatrics was the alarm for neurological, musculoskeletal disorders among geriatric subject.

Materials & Methodology : This original research study with a 6 year follow up was conducted in Chennai from April 2012 till August 2018. An octogenarian with dyskinesia gait disturbances, decreased reaction time was treated with physioball based exercises and home programme. Dyskinesia scale were measured and analyzed

Results: an improved dyskinesia scale by P<.05

Conclusion: with regular adherence to physiotherapy home exercises medication by neurophysciain, support from family members, an improved functional activities with reasonable independence and dignified quality of life were the major findings which can be applied on similar subjects.

Keywords: PD, Dyskinesia, Brady Kinesia, DBS, WHO.

• Schrag A, Jahanshahi M, Quinn N. What contributes to quality of life in patients with Parkinson’s disease?  Journal of Neurology Neurosurgery and Psychiatry 2000;69(3):308–312.
• Shima, T. Sarna, H.M. Swartz, A. Stroppolo, R. Gerbasi, L. ZeccaBinding of iron to neuromelanin of human substantia nigra and synthetic melanin: an electron paramagnetic resonance spectroscopy study. Free Radic. Biol. Med., 23 (1) (1997), pp. 110-119
• McNeely1,2 and Gammon M. Earhart. Medication and subthalamic nucleus deep brain stimulation similarly improve balance and complex gait in Parkinson disease. Parkinsonism Relat Disord. 2013 January ; 19(1): 86–91.
• Mehrholz J, Kugler J, Storch A, Pohl M, Elsner B, Hirsch K. Treadmill training for patients with Parkinson's disease. Cochrane Database Syst Rev.2015 Aug 22;(8)
• Hass CJ, Buckley TA, Pitsikoulis C, Barthelemy EJ. Progressive resistance training improves gait initiation in individuals with Parkinson’s disease. Gait Posture. 2012;35:669–673.
• Berardelli C. Rothwell P. D. Thompson M. Hallett. Pathophysiology of bradykinesia in Parkinson's disease. Volume 124, Issue 11, 1 November 2001, Pages 2131–2146
• Keus SH, Bloem BR, Hendriks EJ, Bredero-Cohen AB, Munneke M; Practice Recommendations Development Group. Evidence-based analysis of physical therapy in Parkinson's disease with recommendations for practice and research. Mov Disord.2007 Mar 15;22(4):451-60; quiz 600.
• Hagell, P. (2000). Timed tests in the clinical assessment of motor function in Parkinson's disease. Journal of neuroscience nursing, 32(6), 331-336.
• Jacob RG, Lilienfeld SO, Furman JMR, Durrant JD, Turner SM. Panic disorder with vestibular dysfunction: further clinical observations and description of space and motion phobic stimuli. J Anxiety Disord 1989; 3: 117–30.
• Crimmins EM. Trends in the health of the elderly. Annu Rev Public Health. 2004;25:79–98
• Mueller M, Strobl R, Jahn K, Linkohr B, Peters A, Grill E. Burden of disability attributable to vertigo and dizziness in the aged: results from the KORA-Age study. Eur J Public Health.2014 Oct;24(5):802-7.
• Devezea,b, L. Bernard-Demanzea , F. Xavier c , J.-P. Lavieillea,b, M. Elziere. Vestibular compensation and vestibular rehabilitation. Current concepts and new trends La compensation vestibulaire et sa rééducation. Concepts actuels et nouvelles tendances. Neurophysiologie Clinique/ Clinical Neurophysiology (2014) 44, 49—57
• Holden MA, Haywood KL, Potia TA, et al.: Recommendations for exercise adherence measures in musculoskeletal settings: a systematic review and consensus meeting (protocol). Syst Rev, 2014, 3: 10.
• Eli Carmeli. Physical Therapy for Neurological Conditions in Geriatric Populations. Frontiers in Public health – 2017, vol – 5, Article – 333, PP: 1-6
• Macaluso A, De Vito G: Muscle strength, power and adaptations to resistance training in older people. Eur J Appl Physiol, 2004, 91: 450–472
• Zoran Milanović, Saša Pantelić, Nebojša Trajković, Goran Sporiš, Radmila Kostić, andNic James. Age-related decrease in physical activity and functional fitness among elderly men and women. Clin Interv Aging. 2013; 8: 549–556. Published online 2013 May 21. 
• Toole T, Park S, Hirsch MA, Lehman DA, Maitland CG. The multicomponent nature of equilibrium in persons with parkinsonism: a regression approach. J Neural Transm. 1996;103:561–580.
• David FJ, Rafferty MR, Robichaud JA, Prodoehl J, Kohrt WM, Vaillancourt DE, Corcos DM. Progressive resistance exercise and Parkinson’s disease: a review of potential mechanisms. Parkinsons Dis. 2012;2012:124527.
• Alessandro Carvalho, Dannyel Barbirato, Narahyana Araujo,  Jose Vicente Martins,  Jose Luiz Sá Cavalcant.  Comparison of strength training, aerobic training, and additional physical therapy as supplementary treatments for Parkinson’s disease: pilot study. Clinical Interventions in Aging 2015:10 183–191
• Frankel JP, Kempster PA, Bovingdon M, et al. The effects of oral protein on the absorption of intraduodenal levodopa and motor performance. J Neurol Neurosurg Psychiatry. 1989;52:1063–7.
• Pechevis M, Clarke CE & Vierrege P (2005) Effects of dyskinesias in Parkinson’s disease on quality of life and health-related costs: a prospective European study. European Journal of Neurology 12, 956–963.
• Rudzińska M, Bukowczan S, Stożek J, Zajdel K, Mirek E, Chwała W, Wójcik-Pędziwiatr M, Banaszkiewicz K, Szczudlik A. Causes and consequences of falls in Parkinson disease patients in a prospective study. Neurol Neurochir Pol.2013 Sep-Oct;47(5):423-30.
• Shumway-Cook A, Horak FB, Yardley L, Bronstein AM. Rehabilitation of balance disorders in the patient with vestibular pathology. In: Bronstein AM, Brandt T, Woollacott M, editors. Clinical Disorders of Balance Posture and Gait.London: Arnold; 1996. pp. 211–235.
• Krisztina Marosi and Mark P. Mattson. BDNF Mediates Adaptive Brain and Body Responses to Energetic Challenges. Trends Endocrinol Metab. NIH Public access 2014 February; 25(2): 89–98.

Dr S.S.Subramanian

M.P.T (Orthopaedics), M.S (Education), M. Phil (Education), Ph.D (Physiotherapy)

The Principal, Sree Balaji College of Physiotherapy, Chennai – 100

Affiliated to BIHER, Chennai – 73

Call For Paper Volume 11 Issue 09 September 2023

The JMSCR is accepting manuscripts for its coming issues to be Publish Volume 11 Issue 09 September 2023  the JMSCR invites authors to submit manuscripts Reporting original medical research, original article, research article, case report, systematic reviews, or educational Innovations for publication for the coming issues that will be released in Volume 11 Issue 09 September 2023 . Types of manuscripts suitable for JMSCR include: Medical research, Clinical research Educational Innovation, Brief Report, Reviews on Teaching In keeping with high quality scholarship,  Read More.....

http://jmscr.igmpublication.org/ems/Submit-Manuscript/

• JMSCR Scope
• Call For paper
• JMSCR Indexing
• Double Blind Peer Review
• Plagiarism Policy
• Open Access Statement
• Authorship Criteria
• Article Withdrawal Policy
• License Terms
• Journal's Instructions
• Digital Archiving Policy
• JMSCR Journal Key Words
• Privacy Policy
• Refund Policy
• Mode of Payment

Cover Page 2020

Crossref - doi.

Crossref - DOI Prefix: 10.18535/jmscr

Editorial Policy

Authors should prepare their manuscripts according to the instructions given in the authors' guidelines. Manuscripts which do not ..

Read More.....

Frequency of Publication

JMSCR is published as monthly journal with 12 issues per year. Special editions are also planned subjected to the scope and need....

Read more...

Submission of Articles

Authors are invited to submit their research articles, review papers, Case Report properly formatted as per the author guidelines.........

• Terms & Condition
• Copyright Claims
• Publication Process
• Publishing Ethics

Copyright  2013 JMSCR All rights reserved. 

Study record managers: refer to the Data Element Definitions if submitting registration or results information.

Search for terms

• Advanced Search
• See Studies by Topic
• See Studies on Map
• How to Search
• How to Use Search Results
• How to Find Results of Studies
• How to Read a Study Record

• Learn About Studies
• Other Sites About Studies
• Glossary of Common Site Terms

• Submit Studies to ClinicalTrials.gov PRS
• Why Should I Register and Submit Results?
• FDAAA 801 and the Final Rule
• How to Apply for a PRS Account
• How to Register Your Study
• How to Edit Your Study Record
• How to Submit Your Results
• Frequently Asked Questions
• Support Materials
• Training Materials

• Selected Publications
• Clinical Alerts and Advisories
• Trends, Charts, and Maps
• Downloading Content for Analysis

• ClinicalTrials.gov Background
• About the Results Database
• History, Policies, and Laws
• ClinicalTrials.gov Modernization
• Media/Press Resources
• Linking to This Site
• Terms and Conditions
• Search Results
• Study Record Detail

Retrospective Cohort Study of the Physiotherapy in Critically Ill Covid Patients

• Study Details
• Tabular View
• No Results Posted

Inclusion Criteria:

• Patients diagnosed with COVID-19 in critical condition
• Adults >18 years
• Admission to the ICU from March 11 to May 13, 2020

Exclusion Criteria:

• Patients readmitted on 2 occasions during the study period, the second will be omitted income.
• For Patients and Families
• For Researchers
• For Study Record Managers
• Customer Support
• Accessibility
• Viewers and Players
• Freedom of Information Act
• HHS Vulnerability Disclosure
• U.S. National Library of Medicine
• U.S. National Institutes of Health
• U.S. Department of Health and Human Services

Log in using your username and password

• Search More Search for this keyword Advanced search
• Latest content
• Current issue
• BMJ Journals More You are viewing from: Google Indexer

You are here

• Volume 60, Issue 8
• A case-control study to investigate the relation between low and moderate levels of physical activity and osteoarthritis of the knee using data collected as part of the Allied Dunbar National Fitness Survey
• Article Text
• Article info
• Citation Tools
• Rapid Responses
• Article metrics

• A J Sutton a ,
• K R Muir b ,
• S Mockett c ,
• a Department of Epidemiology and Public Health, University of Leicester, 22–28 Princess Road West, Leicester LE1 6TP, UK, b Division of Public Health Medicine and Epidemiology, University of Nottingham, University Hospital Queen's Medical Centre, Nottingham NG7 2UH, UK, c Division of Physiotherapy Education, School of Community Health Science, Faculty of Medicine and Health Sciences, University of Nottingham, UK, d Division of Stroke Medicine, University of Nottingham, Nottingham City Hospital (NHS) Trust, UK
• Mr Sutton ajs22{at}le.ac.uk

BACKGROUND Physical activity is being recommended as an intervention for seemingly almost universal improvements to health. A potential concern with this recommendation for increased exercise is that some believe increased levels of activity may lead to increased incidence of osteoarthritis of the knee (knee OA), as a result of accelerated “wear and tear” of the major joints.

OBJECTIVE To investigate the hypothesis that the occurrence of knee OA may be related to the duration of participation in some forms of sport and active recreation.

METHODS The relation between habitual exercise, reported by a cross section of people surveyed in England, and self reported knee OA was investigated. Data were derived from the Allied Dunbar National Fitness Survey (1990–91). A matched retrospective case-control design was used and a new exposure classification system which categorised different grades of activities for different time periods for each subject's lifetime participation in regular physical activities was developed. Additional data on knee injuries sustained and bodily composition were also included in a multivariate analysis.

RESULTS From 4316 people originally interviewed, 216 eligible cases (66 men, 150 women) were identified (mean age 57.1). Each case was matched to four controls. When habitual sport/exercise participation were examined during a subject's life, only exposure to regular long walks and being physically active between the ages of 20 and 24 suggested any association with developing knee OA later in life. The only strong association found was a greatly increased risk of knee OA having previously sustained a knee injury (p<0.01, odds ratio 8.0 (95% confidence interval 2.0 to 32.0)).

CONCLUSIONS There was little evidence to suggest that increased levels of regular physical activity throughout life lead to an increased risk of knee OA later in life. Previous knee injury was associated with an increased risk of knee OA. Additionally, most injuries were caused through participation in physical activities. Hence, when deciding on participation in activities, it is worth taking the likelihood of joint injury into consideration, as the chance of injury is greater in some activities than others.

• osteoarthritis

http://dx.doi.org/10.1136/ard.60.8.756

Statistics from Altmetric.com

Request permissions.

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Exercise remains popular throughout the industrialised world. It has become clear that regular exercise can improve general health and possibly increase longevity. 1 , 2 Previous studies have shown strong associations between increased physical activity and decreased risk of cardiovascular disease, assistance in weight reduction, reduction in blood pressure, and improved mood. 3 One potential conflict to this impression is that many believe that there is still truth in the “wear and tear” model of osteoarthritis (OA)—that is, an accelerated wearing out of joints owing to increased exposure to levels of high activity. 4-6 Additionally, it has been suggested that increased knee injury rates, or a combination of these, may cause a higher incidence of knee OA in people who were very active (compared with average population levels) earlier in their lives. 4 If this joint wearing model is true, and whole populations take up the recommendation for increased exercise, then there is a potential for considerable increases in joint wearing diseases as the population ages, in addition to disease caused by injuries related to exercise.

Several studies have investigated the associated risks of contracting OA in elite sportsmen and women, some of which have reported evidence suggesting that high levels of physical activity lead to an increased risk. 5-7 In comparison with this is the study carried out by White et al . 8 This examination of middle aged women specialist teachers of physical education who had undertaken habitual physical activity over many years demonstrated a lower prevalence of knee OA.

The effects of moderate and low levels of physical activity experienced in the general population are possibly more controversial as studies have presented somewhat inconsistent results, suggesting harmful effects only in differing subgroups of the general population. 9-11 Indeed, it cannot be ruled out that a “U” shaped relation exists, where very high and low levels of activity are detrimental to the risk of OA, but moderate levels are beneficial. Hence, to assess the likely impact of realistic levels of physical exercise attainable by normal people on the risk of OA later in life, we chose to investigate the relation between self reported levels of activity throughout life and self reported OA in the community using data from the Allied Dunbar National Fitness Survey (ADNFS) 12 through a retrospective case-control study.

It has been suggested that if a protective effect of exercise on knee OA does exist, a possible explanation would be that it was because of activities strengthening quadriceps muscles, which in turn may offer increased support of the knee joint, and in this way provide some protection against knee OA. 13-18 This is, in part, the basis of the use of physiotherapy regimens for rehabilitating people with existing knee OA. For this reason exposure to activities was graded according to their potential to strengthen quadriceps muscles.

The ADNFS was carried out in 1990–91. 12 The survey focused on the adult population (age 16 and over) of England, and subjects were recruited from all 14 health regions. The electoral register was used to select 200 addresses at random from each of 30 parliamentary constituencies (chosen from a total of 523), giving a total of 6000 addresses. One adult from each of these addresses was selected at random for inclusion in the survey. A total of 4316 subjects responded, with subjects being lost to the survey for a variety of reasons, including unoccupied address. Each respondent was interviewed at their home by specially trained interviewers, who completed a questionnaire about the respondent's health, lifestyle, and physical activity. From these volunteers, 55% were also examined at a mobile laboratory, where, among other things, data on body dimension, composition, and fitness were recorded.

The survey questionnaire was extensive and comprehensively covered details of sport and exercise participation from the age of 14 to the date of interview. The same instrument as that employed in the ADNFS was used to measure levels of habitual physical activity in the Health Survey for England 19 for four consecutive years, when the observed prevalence was consistent. No specific measure of validity was undertaken at the time of the survey in 1990. Reliable objective measures on which to base measures of validity were not available at this time. CSA accelerometers with and without heart rate monitoring and analysis provided a robust external criterion measure. However, analysis of covariance using the ADNFS data for maximum aerobic capacity (V o 2 max ) on the activity summary adjusted for age, body mass index (BMI), smoking, and social class showed significant associations for both men and women, with correlations of 0.68 and 0.63, respectively.

Data on suspected confounding factors were also available; this included a comprehensive section on knee injury. In addition, the data obtained from examination at a mobile laboratory were available for a proportion of the subjects, which provided physiological measurements on subjects at the time of interview, allowing their BMI to be calculated. A more detailed account of this fitness survey is available elsewhere. 12

CASE SELECTION

No specific question was available which allowed direct identification of subjects who had knee OA. Instead, we defined cases using logical criteria acknowledging that knee pain is the malady, 20 and following as closely as we could the self reporting American College of Rheumatology criteria, 21 as has been done previously. 22 To be defined as a case a subject had to:

Criteria 3 and 4 were applied to exclude patients who were likely to have inflammatory arthritis. The reported age of onset of arthritis was taken to be the diagnosis date.

CONTROL SELECTION

Controls were matched by both sex and age. It was possible to pick multiple controls for each case owing to the size of the survey; (exactly) four controls were randomly selected for each case. 23 Anyone who was “disease free” at the diagnosis age of a particular case was eligible for selection as one of their controls. In this way age matching could always be done to exactly the age of the case. This means that a case could be a control for someone who was diagnosed at a younger age than themselves. Additionally, controls were selected with replacement, which implies a subject could be used as a control for multiple cases 24 ; hence subjects could potentially be included several times in the dataset, both as a case and multiple controls. Importantly, only exposure/confounder information (see below) for controls, up until the age of the case diagnosis to which they were matched, was used in the analysis.

For example, in matching controls to a case whose diagnosis date was 50 years, all people disease free at the age of 50, including those who developed knee OA after the age of 50, were eligible to be selected. If a person aged 70 was selected as a control, then they were matched at age 50 and the exposure information between the ages of 50 and 70 ignored for both case and control. It is then possible that this control was also selected as a control for another case whose diagnosis date was different, say 60 years; in this instance the exposure between the ages of 60 and 70 is ignored. It is also possible that this subject developed knee OA, after the age of 60, say at age 67, and is included as a case, with exposure between the ages of 68 and 70 ignored. (See below for how exposure was calculated.)

EXPOSURE MEASURES

Individual data were available for each physical activity in which a volunteer reported participation for the duration of their lives starting from the age of 14, including habitual cycling and long walks. Explicitly, the questionnaire asked: “During these years from when your were 14 up to the present, have you, at any time, done any of these activities on a regular basis. Please don't include any activities you only did in school time, but do include any activities you may already have mentioned. By regular I mean at least once a week for a few months or more.”

Subjects were then asked about 45 different activities (see ), in addition to habitual cycling and long walks (defined as walking for two miles or more, at least once a week). For each activity, the start and stopping age (if stopped) was recorded, together with the number of years of non-regular participation (if any) within that period. From these data, summary exposure variables were calculated across all activities. (Note, habitual cycling was included in these, but long walks were considered separately.)

Each sport's potential for increasing quadriceps strength was graded on a three point scale by consensus of a panel of seven physiotherapists. A score of one indicated it would probably strengthen/maintain quadriceps muscles, a score of two indicated that it would possibly strengthen/maintain quadriceps muscles, and a score of three indicated that it generally would not strengthen maintain quadriceps muscles. A table describing the category assigned to each sport is given in the (table 7 ).

• View inline

List of exercises: the knee strengthening/conditioning potential grades given to each sport

In addition to this, to enable each person's exposure history to be summarised, two 10 year exposure “windows” were defined. These windows were defined to cover the periods 5–14 and 15–24 years before the age of diagnosis/matched age (for controls). A five year gap was left between diagnosis data and the start of exposure history to allow for error in the reported date of diagnosis, and to make sure disease onset did not influence the activities in which the subject participated. The number of activities participated in for each grade was calculated for each window. A person was deemed as exposed for a window and a given activity (and hence corresponding activity grade) if his/her history recorded participation in the activity at any time within the 10 year span of the window.

These calculations were relatively straightforward for most subjects, but when a subject reported a break from an activity for 10 years or more, it was impossible to ascertain whether this break covered the whole of the window of interest. For example, if a subject reported playing football from the age of 14 to 35, but reported not doing it regularly for 12 of those years, it was impossible to ascertain whether they did play regularly for any adjacent 10 year period that was enclosed within the ages 15 to 34. In such situations subjects were classified as exposed, but the potential impact of wrong classification was explored in a sensitivity analysis by making them unexposed.

Six variables were created reporting the number of activities participated in for each grade of activity and time window combination. A further six variables were created by dichotomising each of these six—defining them as one if at least one activity had been participated in for that window/grade and 0 otherwise. Binary variables were also defined for exposure to long walks, for each time window.

Subjects were asked two further questions relating to activity between two age bands: 14–19 and 20–24 years. These were ( i ) when you were aged (14–19 or 20–24) how much sport or exercise did you take part in? ( a ) a lot; ( b ) a moderate amount; ( c ) very little; and ( d ) none at all; and ( ii ) compared with other people of that age at that time, would you describe yourself as ( a ) very physically active; ( b ) fairly physically active; ( c ) not very physically active; or ( d ) not at all physically active. For this analysis, subjects reporting the highest category (that is, a lot or very physically active) for these two questions for each age band were classed as exposed, hence dichotomising the exposure. Box FB1 provides a summary of the exposure measures described above.

Exposure variables Activity grade 1 (probably strengthen/maintain quadriceps) Exposure 5–14 years before diagnosis  1  Binary indicator for some regular participation  2  Number of activities participated in regularly Exposure 15–24 years before diagnosis  3  Binary indicator for some regular participation  4  Number of activities participated in regularly Activity grade 2 (possibly strengthen/maintain quadriceps) Exposure 5–14 years before diagnosis  5  Binary indicator for some regular participation  6  Number of activities participated in regularly Exposure 15–24 years before diagnosis  7  Binary indicator for some regular participation  8  Number of activities participated in regularly Activity grade 3 (generally not strengthen/maintain quadriceps) Exposure 5–14 years before diagnosis  9  Binary indicator for some regular participation 10  Number of activities participated in regularly Exposure 15–24 years before diagnosis 11  Binary indicator for some regular participation 12  Number of activities participated in regularly Long walks Exposure 5–14 years before diagnosis 13  Binary indicator for some regular participation Exposure 15–24 years before diagnosis 14  Binary indicator for some regular participation Activity in young and early adulthood Exposure in ages 14–19 15  Binary indicator for amount of exercise: a lot v moderate or very little or none at all 16  Binary indicator for physically active: very v fairly or not very or not at all Exposure in ages 20–24 17  Binary indicator for amount of exercise: a lot v moderate or very little or none at all 18  Binary indicator for physically active: very v fairly or not very or not at all (Note: see for which exercises were classified in each activity grade)

CONFOUNDING VARIABLES

It was possible to ascertain whether the subject had had a knee injury before the diagnosis/pseudo-diagnosis date. The cause of the injury had also been recorded, but there were too few injuries to make an adjustment and hence obtain risk estimates at this level. For the proportion of study subjects who had been to the mobile laboratory, it was possible to calculate a BMI value at the time of interview that was used as a proxy for BMI at the time of diagnosis.

STATISTICAL ANALYSIS

A multivariate analysis was undertaken using conditional logistic regression on matched sets of size five subjects (one case and four controls). The statistical package EGRET was used for these analyses. 25 Each of the 12 activity exposure variables was examined together with the two variables on habitual walking, and four dichotomised variables indicating general levels of physical activity in youth and early adulthood (box FB1 ). Each variable was fitted individually while adjusting for known risk factors: knee injury, and then knee injury and BMI, where available. Exposure variables were then fitted simultaneously to try to ascertain the best model. A stepwise (forwards-backwards) variable selection procedure was adopted, initially retaining terms in the model if they were significant at the 10% level.

EXPLORATORY ANALYSIS

From the 4316 people originally interviewed, 365 cases were identified using the two question case definition. Of these, 103 were aged less than 40, 38 had pain in both wrists and both hands/fingers, four reported no longer having arthritis, and four had a missing response to the “still got arthritis” question. All these people were excluded leaving 216 eligible cases consisting of 66 men and 150 women. For each case exactly four controls were selected, and thus the final study group comprised 1080 subjects. Owing to the sampling with replacement, the study group consisted of 636 people included once, 143 included twice, 38 three times and 11 four times. Hence the number of distinct individuals was 828. Of these, 57 were included as both cases and controls. The mean (SD) age for cases (and hence controls) was 57.1 (11.0) years (range 40–96).

Six cases reported knee injuries (3%) before the diagnosis date, four from sport and two from other causes (not recorded). For the controls, three (0.3%) knee injuries were reported, none of which were caused through participation in sports.

Data on BMI were limited to the proportion of cases and controls who had the laboratory assessment—108 (50%) cases and 379 (44%) controls had data available. (Note: For the purposes of this analysis we assume values of BMI are missing completely at random.) The mean (SD) BMI for cases was 28.4 (5.0) kg/m 2 and 26.5 (3.9) kg/m 2 for controls. Because this measurement of BMI was at the date of interview and not at the diagnosis/matching date the difference between these two dates was examined. The mean (SD) time between diagnosis/pseudo-diagnosis and BMI measurement for cases was 11.1 (8.6) years and for controls 13.1 (10.1) years.

Table 1 gives a breakdown of the percentages of cases/controls exposed to each grade of activity by the number of activities done in each grade. It can be seen that around 65% of cases and controls were totally unexposed for each grade except grade 1, time period one where approximately 75% of cases and controls were unexposed. The proportions participating in the number of events is again quite similar for each grade with approximately 20% of cases/controls doing one activity, 5% doing two, and <5% doing more than three.

Proportion of cases and controls exposed to the number of graded exercises in each time period

Table 2 displays the distribution of the number of grade 1 (probably strengthen/maintain quadriceps) activities participated in split by case/control status and sex. The exposure for all subject groupings was quite low, with most people participating in no exercise. In no group did more than 12% of people participate in more than three activities. Table 3 shows exposure to long walks. Cases rates are 7.5% and 11.7% higher than those of controls for time periods 1 and 2 respectively. Table 4 shows the self reported levels of activity for the ages 14–19 and 20–24. More people reported doing a lot of exercise/were very physically active for the ages 14–19 than for 20–24. Generally, cases appear to report higher levels of activity in early life than controls, but the numbers of subjects not completing the questionnaire were considerable. The statistical significance of these differences is considered below.

Grade 1 activity (probably strengthen/maintain quadriceps) exposure (%) for both time periods split by case/control status and sex

Percentage of cases and controls who regularly participated in long walks over the time periods given

Responses to general exercise and activity level questions in adolescent and early adult life

STATISTICAL MODELLING RESULTS (USING CONDITIONAL LOGISTIC REGRESSION)

Knee injury, when fitted singularly, was highly significant (p=0.003, OR=8.0 (95% CI 2.0 to 32.0), and remained so when all other variables were added to the model. BMI (fitted as a continuous variable) was also highly significant (p=0.002 OR=1.1 (95% CI 1.0 to 1.2). Because it was not possible to calculate the BMI value for half the subjects, inclusion of this term reduced the number of matched sets from 216 to 101, with many of these remaining sets having fewer than their original four controls. For this reason modelling proceeded both including and excluding BMI.

Table 5 shows the results of including each exercise exposure variable in the model individually. Owing to the small numbers of subjects reporting doing more than one activity for any grade and time window, analysis focused on the six binary variables. None of these were statistically significant at the 10% level, whether or not adjustment was made for knee injury or BMI.

Univariate analysis for binary exercise exposure variables

The variables for exposure to long walks for each time period were fitted. These were both statistically significant. For time period 1, the odds ratio (95% CI) was 1.7 (1.1 to 2.4) (p=0.01), and for time period 2 it was 2.1 (1.5 to 3.0) (p<0.001).

The general activity according to age was also examined. The difference for those who were physically active compared with others of the same age (14–19 and 20–24 years) were not significant for either group. However, the difference for those reporting doing a lot of exercise compared with controls aged 14–19 was marginally significant (p=0.07) with an increased risk of knee OA (OR=1.5 (95% CI 1.0 to 2.4) and for ages 20–24 doing lots of exercise was significant (p=0.03) with increased risk of knee OA (OR=1.8 (95% CI 1.0 to 3.0)).

Including several activity exposure terms in the model simultaneously was a problem owing to the high correlation between variables, especially between the same exposure measures over the two time periods. When model fitting using all subjects (excluding BMI but adjusting for knee injury), no two exposure terms retained their significance at the 5% level. However, with a 10% level inclusion cut off both walking in time period 2 and a lot of exercise at ages 20–24 were included (table 6 ).

Model including walking and physically active term

These point estimates are consistent with those found when fitting the variables separately. When BMI was included only knee injury retained its significance at the 5% level. The point estimates remained consistent for all exposure variables previously fitted, suggesting that the lack of significance was possibly because of low power as a result of greatly reduced numbers.

This model suggests the possibility of an increased risk of OA later in life for people who are active in their early life, and for those who have participated in regular long walks in the past; though it should be emphasised that neither exercise term is significant at the 5% level.

We chose to look at habitual physical activity and its effect on knee OA within a large random sample of people living in England. The results support the hypothesis that exercise, at the levels undertaken in the general population, does not markedly increase the risk of knee OA later in life. This finding is in agreement with previous studies on professional athletes, where associations with knee OA were observed, 5 , 7 because, generally, the impact loads sustained among this highly select group will be much higher than in the general population. However, a prior knee injury does seem to increase the risk of developing knee OA considerably. This result is in agreement with previous data only on knee injury. 20

As the original ADNFS analysis reported 9 the levels of activity in the British population are quite low. There are many potential health benefits to be gained from increased regular exercise participation. This study found little evidence that exercise increases the risk of OA later in life, suggesting that the potential health benefits from exercise greatly outweigh any risk of OA incurred.

A limited number of previous studies have investigated the effect of habitual levels of exercise throughout life on knee OA in general populations. Studies based on the Framingham cohort have suggested that there is no increased risk, 9 except in the elderly. 10 Another recent study reported the converse of this, stating that high levels of physical activity may be a risk factor for (knee and hip) OA among men under the age of 50. 11 This study did have drawbacks, which brings its validity into question, including lack of information on knee injuries, shown to be important here, and exposure information limited only to walking and jogging.

An advantage of the ADNFS over previous studies in assessing the association between physical activity and knee OA is the extensive information available on recreational habitual physical activity. From this, a person's individual history of participation in physical activity can be derived for every year of their life from the age of 14 until the year of interview. Thus this provides a much more comprehensive exposure history than can be gained from the more typical “snapshot” data often collected relating to a single month/year.

To make the analysis feasible it was necessary to aggregate and classify the exposure information, owing to the large time scale covered, and the wide variety of activities in which people reported participation. The system developed here was new as previous studies in this area have not had such extensive data available.

Although the exposure information available to us is probably unique, we do, however, acknowledge a number of limitations of other aspects of the data. Firstly, the case definition used had limitations. No question was asked specifically about knee OA, but logical criteria were applied based on other information given in the questionnaire. Although it is difficult to validate the definition used, efforts were made to exclude people suspected of having inflammatory arthritis. No data were available on knee replacement surgery, and hence excluding people who said they no longer had knee OA might have excluded additional “genuine” cases, as may exclusion of people who report knee problems caused by other underlying conditions such as inflammatory back pain.

Additionally, the diagnosis date was self reported and so the potential for it to be wrongly recorded exists. Indeed, by looking at a histogram of this self diagnosis age, digit preference seemed to exist, ages divisible by five (that is, 50, 55, 60, 65, etc) being most popular. To take into account this apparent reduction in accuracy, exposure was censored for the five years before the reported diagnosis date by delaying the start of the first exposure window for duration.

The study did not include a formal assessment of the possible effects of lifetime work related physical activity. Evidence from other studies has suggested an increased risk of knee OA with high occupational physical activity. 26 , 27 It has also been found in some studies that high work related physical activity is associated with low participation in leisure physical activities. The closest surrogate measure we had for lifetime work related physical activity was a measure of how demanding their job was at the time of interview. We looked at this variable in a sample of our data and found some evidence to support the notion that high work related physical activity may be associated with low participation in leisure physical activities. However, such findings could certainly be prone to misclassification bias owing to possible selective changing employment status over time, and it was felt that using this proxy variable to adjust the analysis was potentially misleading. Therefore we suggest that further studies should model the affects of both leisure and occupational physical activity in prospectively collected datasets.

The grading of recreational physical activities into three categories was carried out based on the perception of the ability of each activity to exert a strengthening effect on quadriceps muscles. This was done to investigate the possibility that stronger muscles may offer improved support of the knee joint and in this way protect from OA of the knee. Our data offered no support for such a hypothesis. These gradings were made by considering each activity being performed at some arbitrary “typical” level. Without any notion of intensity for an individual subject, a dilution of exposure is inevitable. The second limitation was lack of information on the average time spent on each activity per week/month, again preventing a more detailed classification system. We are currently preparing a manuscript reporting the association between quadriceps strength and the activity grades used here. If one wished to consider grading activities on a more general criteria than strengthening quadriceps muscles, say a three group measure for physical intensity, then, we believe, the grouping of activities would change, but only slightly.

The fact that BMI was only available for approximately 45% of participants, and for those there was often a considerable lag between its measurement and disease diagnosis, limited the multivariate modelling that could be done while controlling for this risk factor. The lack of data on lifetime work related physical activity is also acknowledged. However, because few associations were found between leisure time physical activity and knee OA, the potential for these confounders to raise associations artificially is minimal. Further, it is unlikely that the effect of uncontrolled confounders exactly cancels out any differential risk between the exposed and the unexposed. However, we acknowledge that it is impossible to predict the precise effects of an unmeasured confounder and due caution is needed in interpreting the results.

The decision was made to concentrate on two exposure windows—namely, 5–14 and 15–24 years before the diagnosis/pseudo-diagnosis date. The main reason for this was to simplify the exposure classification. Combining exposures from different activities over time is problematic. Limiting attention to windows avoids the need for calculating cumulative exposures. With no information on intensity or frequency, the only available measure of the amount of exercise was the number of sports or activities participated in within each window. (A calculation based on the number of years of participation within each window was avoided for simplicity.) This is recognised as being crude and for this reason (together with the fact that few subjects did more than one exercise in a given grade) we chose to dichotomise variables, simply indicating exposed/unexposed.

The correlation between the different grades of activity and the different time windows was high, suggesting that those who do exercise of one grade at one time are more likely to do exercise at the other time period and other grades in both time periods. The distribution of people over the two time periods for each grade was so similar that analysis of just one of the time periods would have been sufficient. This suggests that people's activity routines do not change greatly over time. This correlation also makes the investigation of individual activities difficult, as one would need to control for every other activity. There was a concern that because many grade 1 activities are team sports, such as football, rugby, then the exposure of women would be low. Overall, the exposure of women was slightly lower than men, but participation was still broadly comparable.

Studies in elite athletes suggest that at most a modest increase in risk, if any, would be expected. 6 This present study was large with 80% power to detect an odds ratios of 1.5, implying that these small effects could have been detected in our analysis. Our data do not support the suggestion that increased use of the knee joint through moderate sporting and exercise participation wears out the joint and therefore increases the risk of knee OA.

Exercise in levels observed from a random sample of the English population did not increase the risk of knee OA in a predictable way using our exercise classification.

Although two exposure variables remained significant at the 10% level, these associations could be spurious, or owing to confounding, possibly because of factors such as levels of occupational physical activity. There seems to be no reason why going on regular long walks should do more harm than those activities classified as grade 1. Similarly, the possible harmful effect of reporting high levels of activity as a youth and young adult is difficult to explain. Possibly, slight injuries and insults to the knee are more serious in youth, when a person is still physically developing. These were either too slight or too far in the past for people to recall, and the chance of these occurring is increased in people more active during this time.

The strengths of this study are its size and the detailed exercise classification questionnaire used by the ADNFS, which gave an opportunity to explore the hypothesis investigated here. There is scope for further work in this area using both pre-existing datasets and specifically designed further studies. On the basis of our results and those of others, such studies would also need to be large as the magnitude of risk is likely to be small.

The implications for knee injury, the risk of which itself is increased by sports/activity participation is, however, more serious, with an estimated sixfold increase in risk having had a previous injury after the age of 14. Most of these injuries were reported to have been caused through sports. For this reason it is important that care is taken when participating—many injuries can be prevented by warming up sufficiently or using the correct equipment.

Acknowledgments

The authors thank Elizabeth Williams, Kathy Smith, and Ben Palmer for their assistance in completing this paper and the three anonymous referees whose comments improved the manuscript considerably.

• U.S. Department of Health and Human Services
• Bouchard C ,
• Shephard RJ ,
• Haskell WL ,
• Macera CA ,
• Kujala UM ,
• Spector TD ,
• Harris PA ,
• Cicuttini FM ,
• Etherington J ,
• Hannan MT ,
• Felson DT ,
• Anderson JJ ,
• McAlindon TE ,
• Wilson PWF ,
• Aliabadi P ,
• Weissman B ,
• Ainsworth BE ,
• Troped PJ ,
• ↵ ( 1992 ) Activity and health research, Allied Dunbar National Fitness Survey: a report on activity patterns and fitness levels: main findings. ( Sports Council and Health Education Authority , London, England ) .
• Chamberlain MA ,
• Fisher NM ,
• Pendergast DR ,
• Gresham G ,
• Horrigan D ,
• Pendergast DR
• O'Reilly SC ,
• Ettinger WH ,
• Messier SP ,
• Applegate W ,
• Rejeski WJ ,
• Office of Population Censuses and Surveys Social Survey Division
• Borenstein D ,
• Wacholder S ,
• Silverman D ,
• McLaughlin JK ,
• Cytel Software Corporation
• Maetzel A ,
• Bombardier C
• Download figure
• Open in new tab
• Download powerpoint

No financial support was sought for this investigation. None of the authors have industrial affiliations.

Read the full text or download the PDF:

• Open Access
• Published: 30 August 2021

Online teaching in physiotherapy education during COVID-19 pandemic in Italy: a retrospective case-control study on students’ satisfaction and performance

• Giacomo Rossettini 1   na1 ,
• Tommaso Geri 2   na1 ,
• Andrea Turolla 3 ,
• Antonello Viceconti 4 ,
• Cristina Scumà 1 ,
• Mattia Mirandola 1 ,
• Andrea Dell’Isola 5 , 6 ,
• Silvia Gianola 7 ,
• Filippo Maselli 4 , 8 &
• Alvisa Palese 9  

BMC Medical Education volume  21 , Article number:  456 ( 2021 ) Cite this article

5989 Accesses

28 Citations

3 Altmetric

Metrics details

During COVID-19 pandemic, physiotherapy lecturers faced the challenge of rapidly shifting from face-to-face to online education. This retrospective case-control study aims to compare students’ satisfaction and performances shown in an online course to a control group of students who underwent the same course delivered face-to-face in the previous five years.

Between March and April 2020, a class (n = 46) of entry-level physiotherapy students (University of Verona - Italy), trained by an experienced physiotherapist, had 24-hours online lessons. Students exposed to the same course in the previous five academic years (n = 112), delivered with face-to-face conventional lessons, served as a historical control. The course was organized in 3 sequential phases: (1) PowerPoint presentations were uploaded to the University online platform, (2) asynchronous video recorded lectures were provided on the same platform, and (3) between online lectures, the lecturer and students could communicate through an email chat to promote understanding, dispel any doubts and collect requests for supplementary material (e.g., scientific articles, videos, webinars, podcasts). Outcomes were: (1) satisfaction as routinely measured by University with a national instrument and populated in a database; (2) performance as measured with an oral examination.

We compared satisfaction with the course, expressed on a 5-point Likert scale, resulting in no differences between online and face-to-face teaching (Kruskal-Wallis 2  = 0.24, df = 1, p  = 0.62). We weighted up students’ results by comparing their mean performances with the mean performances of the same course delivered face-to-face in the previous five years, founding a statistical significance in favour of online teaching (Wilcoxon rank sum test W = 1665, p < 0.001).

Conclusions

Online teaching in entry-level Physiotherapy seems to be a feasible option to face COVID-19 pandemic, as satisfies students as well as face-to-face courses and leading to a similar performance. Entry-level Bachelors in Physiotherapy may consider moving to eLearning to facilitate access to higher education. Universities will have to train lecturers to help them develop appropriate pedagogical skills, and supply suitable support in terms of economic, organizational, and technological issues, aimed at guaranteeing a high level of education to their students.

Trial registration

Retrospectively registered.

Peer Review reports

Introduction

The ongoing Coronavirus disease 2019 (COVID-19) pandemic is still challenging educational systems worldwide. In those countries where governments decided to close educational institutions in an attempt to contain the spreading of the disease, students could not attend face-to-face activities [ 1 ]. Italy was particularly affected, with COVID-19 cases soaring already in February 2020 and lockdowns implemented as early as the 9th of March 2020 forcing all the educational institutions (from primary schools to universities) to switch to online learning [ 2 , 3 ]. Within this context, the online teaching was unprecedented for different institutions, as for the entry-level Bachelor in Physiotherapy [ 4 ].

With no time for extensive training on online teaching and learning and no possibility to change the course contents, physiotherapy lecturers were faced with the challenge of effectively teaching core skills to entry-level physiotherapy students online, assuring the same competence level gained by their predecessors [ 5 ]. In the meanwhile, physiotherapy students, who were already experiencing the impact of the pandemic on their psychosocial wellbeing, had to manage the amplification of the level of negative emotions due to rapid changes in learning habits [ 6 , 7 ].

Even if former systematic reviews reported that distance-online learning arouses the same satisfaction and has the same efficacy as traditional face-to-face teaching in physiotherapy [ 8 , 9 , 10 ], the protected experimental setting in which the included studies were conducted limits the external validity of the findings to the ongoing pandemic. A recent meta-synthesis investigated accessibility and educational methods of online education in the medical curriculum during the COVID-19 pandemic but none of the included studies investigated satisfaction and performance [ 11 ]. Thus, to the best of the authors’ knowledge, this is the first comparative study developed during COVID-19 pandemic that quantitatively evaluates students’ satisfaction and performances after attending online physiotherapy education.

Accordingly, the aims of this retrospective case-control study are: (1) to investigate students’ satisfaction and performance; and (2) to compare their degree of satisfaction and performance with those reported by students attending face-to-face courses.

Study design

This case-control study was developed using guidance and explanations from the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines [ 12 , 13 ].

We conducted this study in compliance with the principles outlined in the Declaration of Helsinki. Written informed consent was assumed when respondents completed and submitted the survey after reading the purpose statement of the study, strategies to ensure confidentiality and privacy of the data collected. Data were fully and irreversibly anonymized by generalization of important variables [ 14 ]. Ethics approval during this pandemic was not required according to the “Ethics and data protection” regulations of the European advisory body and European Commission [ 14 , 15 , 16 ].

“Advanced methodologies in musculoskeletal physiotherapy” lectures at the entry-level Bachelor in Physiotherapy have been shifted from a face-to-face to an online course in only two weeks. Before and during the pandemic, the course covers 3 main topics: clinical reasoning, analysis of pain mechanisms and evidence-based physiotherapy practice. It provides 2 ECTS (European Credit Transfer and Accumulation System), with an estimated learning workload of 50–60 h of study, of which 24 were usually fulfilled by face-to-face lectures [ 17 ].

A physiotherapist lecturer with twelve years of teaching experience in musculoskeletal physiotherapy designed and conducted the course at the University of Verona - Italy for entry-level physiotherapy students. During the weeks between the outbreak of the pandemic and the teaching of the course, the lecturer was trained by the University exclusively on the use of the online platform (how to access the system; how to record lectures; and how to upload learning materials) during a 1-hour online course. No further training on how to prepare the online teaching and how to adapt the learning content was provided.

The course was delivered online between the end of March and the end of April 2020 adopting the Panopto Secure Online Videoplatform [ 18 ]. Students’ attendance was recorded automatically by The Panopto Secure Online Videoplatform as the students accessed the lectures.

The course was organized in 3 sequential phases:

Power-point presentations were uploaded to the University online platform, one to briefly introduce students to the course, and the others to serve as lecture notes.

One week after the upload, asynchronous video recorded lectures were provided on the same platform. Each lesson lasted a maximum of 30 min [ 19 ] and included the explanation of the topic approached, a summary of the key points and a clinical case focused on the subject proposed.

Between online lectures, the lecturer and students could communicate through an email chat to promote understanding, dispel any doubts and collect requests for supplementary materials. Accordingly, the lecturer provided supplementary references (e.g., scientific articles, videos), also suggesting online resources (e.g., webinars and podcasts) to enhance the effectiveness of the course.

The previous five editions of the course, homogeneous in the aims and the contents, were conducted by the same lecturer. The same Syllabus developed for the face-to-face course and provided to former students was uploaded for the online edition. The admission to the oral exam was bound to 100 % attendance to the lectures both in the online and face-to-face editions. The educational strategies adopted during the transition from face-to-face to online teaching are presented in Fig.  1 .

Changes in teaching strategies adopted during the transition from face-to-face to online education.

Participants

Convenience samples for both cases and controls were considered. Students attending the course in the 2019/2020 academic year, exposed to online teaching, were considered as the online group (n = 46). Students exposed to the same course taught face-to-face in the previous five academic years ( n  = 112) were considered as a control group (face-to-face group).

Data collection and Outcome Measures

Demographic (e.g., age and gender) and course (e.g., number of participants attending the course, number of respondents, number of passed students) characteristics were collected. The primary outcomes of interest were students’ satisfaction and performance.

The assessment of students’ satisfaction was obtained from a standardized national-established 12-item questionnaire whose compilation by students is mandatory and takes place before the final exam of each course taught in Italian universities [ 20 ]. The questionnaire covered various aspects of the course (e.g., adequacy of preliminary knowledge, balance between the study load and the number of credits assigned to this course, clarity of information on the exam structure) [ 20 ]. As a summary of students’ satisfaction, we considered the following question “ Overall, are you satisfied with the organisation and the teaching of this course ?”. Answers are allowed upon a 5-point Likert scale (“I don’t know” - value 0, “Strongly disagree” - value 1, “Somewhat disagree” - value 2, “Somewhat agree” - value 3 and “Strongly agree” - value 4) [ 20 ].

The assessment of students’ performance occurred in July of each year and was obtained through an oral exam conducted by the same teacher who delivered the lessons for both face-to-face and online courses. While the online group was assessed remotely using a real-time video-chat (Zoom), the face-to-face group conducted the exam in person at the University. The oral exam lasted a maximum of 30 min for each student and comprised open questions and a patient case study aimed at evaluating both the knowledge acquired and the ability to apply it to a clinical scenario [ 21 ]. The final grade was expressed according to the standard national metrics on a scale from 0 to 31, where 0 is the lowest value and 31 is the highest, and the minimum score to pass the course was 18/31 [ 22 ].

Satisfaction and performances shown by the online group were compared with the face-to-face groups from the previous five academic years. All data were obtained from the personal account of the lecturer, rendered available by the University of Verona (Italy) at the end of each academic year with the purpose of continuous improvement of teaching quality. Reports are divided into academic years and include anonymized students’ demographics, degree of attendance, satisfaction questionnaire responses and performances.

Statistical methods

Descriptive statistics were used to summarize characteristics and outcomes. To report values of the dependent variables Likert scores, continuous variables were reported as medians with interquartile ranges (IQRs, 25th percentile, 75th percentile) and performances of the oral exams as mean with standard deviation (SD) or 95 %Confidence of Interval (CI). For the inferential statistics, the type of teaching (online vs. face-to-face) was considered as the independent variable. Differences in the Likert scores and the performances were explored, using the Wilcoxon rank sum test and the Kruskal Wallis test, respectively. Alpha was set at 0.05. On a preliminarily basis, given that face-to-face group included students from 2014/2015 to 2018/2019 academic years, homoscedasticity of relevant variables under study was assessed and no differences emerged (Levene’s test: Satisfaction, F 1  = 3.60, p  = 0.06; Performances, F 1  = 0.41, p  = 0.52). R software v3.4.1 was used for statistical analysis, using ggplot2 v3.0.0 for graphs [ 23 , 24 ].

All students of the online group ( n  = 46; 100 %) attended the course entirely. Their mean age was 24.6 (SD 2.9) years distributed as 19 females and 27 males.

Participants of the face-to-face group were 112. They all attended the course entirely (100%). Their mean age was 23.6 (SD 1.7) years, distributed as 47 females and 65 males. The graphic representation of participants is reported in the study flowchart (Fig.  2 ).

Study flowchart

Students attending the online course all completed the final online oral exam, with a mean performance of 29 out of 31 (95 % CI 28.2–29.7), with none failing the course. All the students responded to the University quantitative survey about satisfaction, reporting a median Likert score of 4 (Q 1  = 3, Q 3  = 4 [IQR = 1]).

Students attending the course face-to-face all completed the final oral exam, with a mean performance of 27.6 out of 31 (95 % CI 27.1–28.1), with none failing the course. Each of them (100 %) responded to University quantitative survey about satisfaction, reporting a median Likert score of 4 (Q 1  = 3, Q 3  = 4 [IQR = 1]).

There was a significant difference in the mean performances (Wilcoxon rank sum test W = 1665, p < 0.001). No difference was observed between the two groups of students in the perceived satisfaction of the course (Kruskal-Wallis Χ 2  = 3, df = 1, p  = 0.08) as reported in Table  1 .

Key results

COVID-19 emergency pushed universities to rethink teaching methodologies, forcing teachers to learn online options to continue education and to ensure adequate educational standards [ 1 ]. To the authors’ knowledge, this is the first case-control study aimed at comparing satisfaction and performances of entry-level physiotherapy students experiencing online teaching during COVID-19 pandemic with former face-to-face students of the same Bachelor. According to the main findings, the entry-level students in Physiotherapy showed: (1) no differences in satisfaction whether they attended a face-to-face or an online course; (2) a higher performance in an online course as compared to face-to-face course.

Interpretation

Former systematic reviews, summarizing studies performed before COVID-19 pandemic, found that levels of satisfaction and performances are similar for both distance-online and face-to-face teaching [ 8 , 9 , 10 ]. Our study seems to support these findings, as our online course satisfied students as the face-to-face one. These findings seem to be consistent given that the content of the course, as well as the lecturer and the type of final exam, were homogenous over the years.

The same high satisfaction was expressed by both groups suggesting that students’ needs are evolving. Higher institutions should offer flexibility in the methodologies when these are consistent with the expected learning outcomes allowing students with limited possibility to attend classes (e.g., students working) by continuing their academic career especially in countries where higher education is scarcely widespread [ 25 ]. Even if technological and set up investments for online teaching are required, studies have shown that switching to online teaching can reduce costs for students [ 26 ] which in turn can increase students numbers, especially in those countries where loans for tuitions are a major barrier to university attendance [ 27 , 28 ]. However, building up a digital educational system may increase disparities towards people living in remote and rural regions, poorer social classes, and families experiencing financial difficulties due to COVID-19 induced economic crisis [ 26 , 29 , 30 ].

Moreover, a full eLearning Bachelor’s degree in Physiotherapy have been documented to not fulfil students’ expectations during COVID-19 [ 7 ]. First of all, online resources can act as supplementary material, but not as primary learning activities for acquiring practical skills [ 7 ]. Moreover, online-only learning has been suggested to increase distress and to hinder social interaction with peers and lecturers [ 7 ]. Even if both of these concerns can be easily related to the current uncertainty about the future [ 4 , 6 , 7 ], face-to-face activities have been reported more suitable to favour communication and social support also before the COVID-19 pandemic [ 31 ]. Blended teaching, combining online and face-to-face teaching, have been reported to balance benefits and drawbacks of online and face-to-face teaching [ 7 , 8 ].

Regarding the higher students’ performance, our findings are in line with the growing body of evidence showing that distance-online courses can prepare students as well as face-to-face courses [ 8 , 9 , 10 ].

Although the difference in performance (27.6 in online vs. 29 in face-to-face group) seems to have limited practical meaning, several explanations could justify the higher performance of students in the online group. During the COVID-19 pandemic, other academic activities at universities (e.g., workshops, laboratories, clinical rotations) were suspended to ensure social distancing and physical isolation [ 4 ]. Thus, students could have spent more time studying and delving into the topics of the course. Furthermore, compared to previous years, students benefited from both different teaching strategies (e.g., PowerPoint slides, videos, podcasts, webinars) and the possibility of reviewing the recorded lecturing. This could have better matched the students’ different learning styles [ 32 ], facilitating the acquisition of knowledge for the exam. Finally, it is plausible that the evaluation of students could be less adequate, resulting in an overestimation of the performance. Indeed, an unfamiliar model of assessment (online), as well as the lack of vigilance during the exam performed at home, could lead students to academic misconduct (e.g., cheating, hint) [ 33 ]. Furthermore, the high workload to produce didactic resources, the need to perform concomitant extra academic duties (e.g., clinical service in challenging circumstances), and the difficulty to separate professional and personal activities [ 4 , 5 ], could have impacted the educator and may have in turn influenced the assessment process.

Limitations

Our study has several limitations. First, we analysed one course from a single Italian University, significantly limiting their generalizability. Moreover, the study protocol was not pre-planned but reflected circumstances imposed by the pandemic, that were worldwide unexpected [ 34 ], thus the quality of the study might have been affected. However, we decided to turn our unpreparedness into an opportunity to learn something new about didactic methodologies, and to scrutinise their effect. In this context, we could not have a synchronous control group, as Italian laws did not allow face-to-face teaching for several months [ 3 ]. In fact, one year later the declaration of the state of pandemic, all lessons are still mainly online [ 3 ]. Waiting for face-to-face teaching was not considered a feasible option, as it would have meant an unpredictable delay in students’ graduation. Thus, future studies should investigate the efficacy of online teaching using primary study design (e.g., randomized controlled trial, prospective cohort study) and including also new digital technologies (e.g., augmented and virtual reality) for educational purposes [ 35 , 36 ].

Another limitation was the insufficient lecturer training in online teaching. We quickly adapted the contents of a face-to-face course to online modalities, without specific instructional design based on eLearning. If online courses in physiotherapy education will be implemented in the future, teachers will need specialised support [ 31 ]. On the other hand, teaching provided by the same experienced lecturer improved inter-groups comparability and mitigated discrepancies even if the external validity can be limited.

Online teaching in entry-level Physiotherapy seems to be a feasible option to face COVID-19 pandemic, as satisfies students as well as face-to-face courses and leading to a similar performance. However, further studies should be undertaken to cumulate evidence in the field. Entry-level Bachelors in Physiotherapy may consider moving to eLearning to facilitate access to higher education. Universities will have to train lecturers to help them develop appropriate pedagogical skills, and supply suitable support in terms of economic, organizational, and technological issues, aimed at guaranteeing a high level of education to their students.

Availability of data and materials

The datasets used and analysed during the current study are available from the corresponding author on reasonable requests.

Abbreviations

Coronavirus disease 2019

Strengthening the Reporting of Observational studies in Epidemiology

European Credit Transfer and Accumulation System

Interquartile range

Standard deviation

95 %Confidence of Interval

United Nations Educational, Scientific and Cultural Organization (UNESCO). COVID-19 Response. Education: From disruption to recovery. 2019. Available at: https://en.unesco.org/covid19/educationresponse . Accessed 28 June 2021.

Remuzzi A, Remuzzi G. COVID-19 and Italy: what next? Lancet . 2020; 395:1225–1228. doi: https://doi.org/10.1016/S0140-6736(20)30627-9 .

Article   Google Scholar  

Governo Italiano Presidenza del Consiglio dei Ministri. Coronavirus, la normative vigente. 2020. Available at: http://www.governo.it/it/coronavirus-normativa . Accessed 28 June 2021.

World Physiotherapy. World Physiotherapy response to COVID-19 - briefing paper 1. Immediate impact on the higher education sector and response to delivering physiotherapist entry level education. 2020. https://world.physio/covid-19-information-hub/covid-19-briefing-papers . Accessed 28 June 2021.

Plummer L, Belgen Kaygısız B, Pessoa Kuehner C, Gore S, Mercuro R, Chatiwala N, Naidoo K. Teaching online during the COVID-19 pandemic: a phenomenological study of physical therapist faculty in Brazil, Cyprus, and The United States. Education Sciences. 2021;11:130. doi: https://doi.org/10.3390/educsci11030130 .

World Physiotherapy. World Physiotherapy response to COVID-19 - briefing paper 3. Immediate impact on students and the response to delivering physiotherapist entry level education. 2020. https://world.physio/covid-19-information-hub/covid-19-briefing-papers . Accessed 28 June 2021.

Ng L, Seow KC, Mac Donald L, et al. eLearning in physical therapy: lessons learned from transitioning a professional education program to full eLearning during the COVID-19 pandemic. Phys Ther . 2021;101:pzab082. doi: https://doi.org/10.1093/ptj/pzab082

Pradeep PG, Papachristou N, Belisario JM, et al. Online eLearning for undergraduates in health professions: a systematic review of the impact on knowledge, skills, attitudes and satisfaction. J Glob Health . 2014;4:010406. doi: https://doi.org/10.7189/jogh.04.010406 .

Mącznik AK, Ribeiro DC, Baxter GD. Online technology use in physiotherapy teaching and learning: a systematic review of effectiveness and user’s perceptions. BMC Med Educ . 2015;15:160. doi: https://doi.org/10.1186/s12909-015-0429-8 .

Ødegaard NB, Myrhaug HT, Dahl-Michelsen T, Røe Y. Digital learning designs in physiotherapy education: a systematic review and meta-analysis. BMC Med Educ . 2021;21:48. doi: https://doi.org/10.1186/s12909-020-02483-w .

Camargo CP, Tempski PZ, Busnardo FF, Martins MA, Gemperli R. Online learning and COVID-19: a meta-synthesis analysis. Clinics (Sao Paulo) . 2020;75:e2286. doi: https://doi.org/10.6061/clinics/2020/e2286 .

von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. STROBE initiative. The Strengthening the Reporting of OBservational studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med . 2007;147:573–7. doi: https://doi.org/10.7326/0003-4819-147-8-200710160-00010 .

Vandenbroucke JP, von Elm E, Altman DG, et al. STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. PLoS Med . 2007;4:e297. doi: https://doi.org/10.1371/journal.pmed.0040297 .

Article 29 Data Protection Working Party. Opinion 05/2014 on Anonymisation Techniques. 2014, Apr 10. Available at: https://ec.europa.eu/justice/article-29/documentation/opinion-recommendation/files/2014/wp216_en.pdf . Accessed 28 June 2021.

Gazzetta ufficiale dell’Unione europea. L 295/39 Regolamento (UE) 2018/1725 del Parlamento Europeo e del Consiglio. 2018, Nov 18. Available at: https://eur-lex.europa.eu/legal-content/IT/TXT/PDF/?uri=CELEX:32018R1725 &from=en%20 %C2 %B0. Accessed 28 June 2021.

European Commission. Ethics and Data Protection. 2018, Nov 14. Available at: https://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/ethics/h2020_hi_ethics-data-protection_en.pdf . Accessed 28 June 2021.

European Commission. European Credit Transfer and Accumulation System (ECTS). 2015. Available at: https://ec.europa.eu/education/resources-and-tools/european-credit-transfer-and-accumulation-system-ects_en . Accessed 28 June 2021.

Università di Verona. Panopto: piattaforma di video content management. 2020. Available at: https://www.univr.it/it/panopto . Accessed 28 June 2021.

Gewin V. Five tips for moving teaching online as COVID-19 takes hold. Nature . 2020;580: 295–6. doi: https://doi.org/10.1038/d41586-020-00896-7 .

Agenzia Nazionale di Valutazione del Sistema Universitario e della Ricerca (ANVUR). Valutazione della didattica e assicurazione della qualità. 2020. Available at: https://www.anvur.it/atti-e-pubblicazioni/lavori-di-ricerca/valutazione-della-didattica-e-assicurazione-della-qualita/ . Accessed 28 June 2021.

Vendrely A. Assessment Methods in Physical Therapy Education: An Overview and Literature Review. J Phys Ther Educ . 2002;16:64–9. doi: https://doi.org/10.1097/00001416-200207000-00010 .

Regolamento didattico di Ateneo. 2020. Available at: https://www.gazzettaufficiale.it/atto/serie_generale/caricaArticolo?art.progressivo=0&art.idArticolo=1&art.versione=1&art.codiceRedazionale=08A03704&art.dataPubblicazioneGazzetta=2008-06-05&art.idGruppo=0&art.idSottoArticolo1=10&art.idSottoArticolo=1&art.flagTipoArticolo=1 . Accessed 28 June 2021.

R Development Core Team: R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2009.

Google Scholar  

Wickham H: ggplot2: Elegant Graphics for Data Analysis. New York, NY: Springer-Verlag; 2009 Available at: https://www.springer.com/gp/book/9780387981413 . Accessed 28 June 2021.

Istituto Nazionale di Statistica (ISTAT). Livelli di istruzione e ritorni occupazionali. 2020, Jul 22. Available at: https://www.istat.it/it/files/2020/07/Livelli-di-istruzione-e-ritorni-occupazionali.pdf Accessed 28 June 2021.

World Health Organisation (WHO). ELearning for undergraduate health professional education - a systematic review informing a radical transformation of health workforce development. Published 2015, Jan. Available at: https://www.who.int/hrh/documents/elearning_hwf/en/ . Accessed 28 June 2021.

Ambler SB. The debt burden of entry-level physical therapists. Phys Ther . 2020;100:591–9. doi: https://doi.org/10.1093/ptj/pzz179 .

Jette D. Physical therapist student loan debt. Phys Ther . 2016;96:1685–8. doi: https://doi.org/10.2522/ptj.20160307 .

Misra V, Chemane N, Maddocks S, Chetty V. Community-based primary healthcare training for physiotherapy: students’ perceptions of a learning platform. S Afr J Physiother . 2019;75:471. doi: https://doi.org/10.4102/sajp.v75i1.471 .

Cleland J, Tan ECP, Tham KY, Low-Beer N. How Covid-19 opened up questions of sociomateriality in healthcare education. Adv Health Sci Educ Theory Pract . 2020;25:479–482. doi: https://doi.org/10.1007/s10459-020-09968-9 .

Nicklen P, Keating JL, Paynter S, Storr M, Maloney S. Remote-online case-based learning: a comparison of remote-online and face-to-face, case-based learning - a randomized controlled trial. Educ Health. 2016;29:195–202. doi: https://doi.org/10.4103/1357-6283.204213 .

Stander J, Grimmer K, Brink Y. Learning styles of physiotherapists: a systematic scoping review. BMC Med Educ . 2019;19:2. doi: https://doi.org/10.1186/s12909-018-1434-5 .

Sahu P. Closure of universities due to coronavirus disease 2019 (COVID-19): impact on education and mental health of students and academic staff. Cureus . 2020;12:e7541. doi: https://doi.org/10.7759/cureus.7541 .

Hamam H. COVID-19 surprised us and empowered technology to be its own master. Tapuya: Latin American Science, Technology and Society . 2020;3:272–281. doi: https://doi.org/10.1080/25729861.2020.1822072 .

Singh RP, Javaid M, Kataria R, Tyagi M, Haleem A, Suman R. Significant applications of virtual reality for COVID-19 pandemic. Diabetes Metab Syndr. 2020;14:661–4. doi: https://doi.org/10.1016/j.dsx.2020.05.011 .

Javaid M, Haleem A, Singh RP, Suman R. Dentistry 4.0 technologies applications for dentistry during COVID-19 pandemic. Sustainable Operations and Computers . 2021;2:87–96. doi: https://doi.org/10.1016/j.susoc.2021.05.002

Download references

Acknowledgements

The authors want to thank Miss Angie Rondoni for her valuable advices during the advancement of this manuscript.

Authors’ information (optional) : All the authors have a direct experience of distance learning during the COVID-19 pandemic and teaching activity in the healthcare.

The authors declare that they have no funding for this manuscript. Open Access funding provided by Lund University.

Author information

Giacomo Rossettini and Tommaso Geri contributed equally to this work.

Authors and Affiliations

School of Physiotherapy, University of Verona, Verona, Italy

Giacomo Rossettini, Cristina Scumà & Mattia Mirandola

Physiotherapist, Private practitioner, Pistoia, Italy

Tommaso Geri

Laboratory of Rehabilitation Technologies, San Camillo IRCCS srl, Venice, Italy

Andrea Turolla

Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Campus of Savona, Savona, Italy

Antonello Viceconti & Filippo Maselli

Clinical Epidemiology Unit, Orthopedics, Department of Clinical Sciences Lund, Lund University, Entrégatan 8 Lund 22100, Lund, Sweden

Andrea Dell’Isola

Department of Clinical Sciences Orthopaedics, Clinical Epidemiology Unit, Lund University, Lund, Sweden

Unit of Clinical Epidemiology, IRCCS Istituto Ortopedico Galeazzi, Milan, Italy

Silvia Gianola

Sovrintendenza Sanitaria Regionale Puglia, Direzione Regionale Puglia INAIL, Bari, Italy

Filippo Maselli

Department of Medical and Biological Sciences, University of Udine, Udine, Italy

Alvisa Palese

You can also search for this author in PubMed   Google Scholar

Contributions

All authors conceived, designed, drafted and approved the final version of the manuscript.

Corresponding author

Correspondence to Andrea Dell’Isola .

Ethics declarations

Ethics approval and consent to participate.

We conducted this study in compliance with the principles outlined in the Declaration of Helsinki. Written informed consent was assumed when respondents completed and submitted the survey after reading the purpose statement of the study, strategies to ensure confidentiality and privacy of the data collected. Data were fully and irreversibly anonymized by generalization of important variables. Ethics approval during this pandemic was not required according to the “Ethics and data protection” regulations of the European advisory body and European Commission.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

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

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Cite this article.

Rossettini, G., Geri, T., Turolla, A. et al. Online teaching in physiotherapy education during COVID-19 pandemic in Italy: a retrospective case-control study on students’ satisfaction and performance. BMC Med Educ 21 , 456 (2021). https://doi.org/10.1186/s12909-021-02896-1

Download citation

Received : 28 June 2021

Accepted : 17 August 2021

Published : 30 August 2021

DOI : https://doi.org/10.1186/s12909-021-02896-1

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Physiotherapy
• Entry-level
• SARS-CoV-2.

BMC Medical Education

ISSN: 1472-6920

• Submission enquiries: [email protected]
• General enquiries: [email protected]

• Collaborate

Retrospective Case Control Study

A retrospective case control study is one that uses existing data to compare two groups. For example, people who have developed a disease might be compared with a group of people who have not. The researcher will look at whether there is any difference in the two groups in their previous exposure to possible risk factors. This type of study is useful when studying risk factors for rare diseases , and is often used to create new hypotheses which can then be tested.

For example, there are fewer than 300 confirmed cases of new variant Creutzfeldt-Jakob disease (CJD), a degenerative, invariably fatal brain disorder. A cohort study that follows healthy people over time to see what risk factors lead to developing the disease would need to recruit a huge number of people in order for just one to develop symptoms (around 200,000). It would also take a very long time, because the period between infection and showing symptoms is thought to be between 10 and 30 years. A much better approach in this case would be to carry out a case control study , starting with people who already have a diagnosis of new variant CJD, and comparing their past exposure to possible risk factors with a group of people who do not have the disease.

• Glossary: Case Control Studies
• Term: Retrospective Case Control Study
• Term: Rare disease
• Term: Cohort Studies

Find Out More

Creative Commons