Browsing Han Publications by Author "Veenhof, C."

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Development and internal validation of a machine learning prediction model for low back pain non-recovery in patients with an acute episode consulting a physiotherapist in primary care
Knoop, J. ; Lankveld, W.G.J.M. van ; Beijer, L.J. ; Geerdink, F.J.B ; Heymans, M.W. ; Hoogeboom, T.J. ; Hoppenbrouwers, S.J.B.A. ; van Overmeeren, E. ; Soer, R ; Veenhof, C. ; Vissers, K.C.P ; van der Wees, P. J. ; Sappelli, M. ; Staal, J.B. et al. sine al.
2022, Article / Letter to editor (BMC Musculoskeletal Disorders, (2022))Background While low back pain occurs in nearly everybody and is the leading cause of disability worldwide, we lack instruments to accurately predict persistence of acute low back pain. We aimed to develop and internally validate a machine learning model predicting non-recovery in acute low back pain and to compare this with current practice and ‘traditional’ prediction modeling. Methods Prognostic cohort-study in primary care physiotherapy. Patients (nn=n247) with acute low back pain (≤none month) consulting physiotherapists were included. Candidate predictors were assessed by questionnaire at baseline and (to capture early recovery) after one and two weeks. Primary outcome was non-recovery after three months, defined as at least mild pain (Numeric Rating Scalen>n2/10). Machine learning models to predict non-recovery were developed and internally validated, and compared with two current practices in physiotherapy (STarT Back tool and physiotherapists’ expectation) and ‘traditional’ logistic regression analysis. Results Forty-seven percent of the participants did not recover at three months. The best performing machine learning model showed acceptable predictive performance (area under the curve: 0.66). Although this was no better than a’traditional’ logistic regression model, it outperformed current practice. Conclusions We developed two prognostic models containing partially different predictors, with acceptable performance for predicting (non-)recovery in patients with acute LBP, which was better than current practice. Our prognostic models have the potential of integration in a clinical decision support system to facilitate data-driven, personalized treatment of acute low back pain, but needs external validation first.
Stratified care integrated with eHealth versus usual primary care physiotherapy in patients with neck and/or shoulder complaints: protocol for a cluster randomized controlled trial.
TIlburg, M.L. van ; Kloek, C.J.J. ; Pisters, M.F. ; Staal, J.B. ; Dongen, J.M. van ; Weerd, M. de ; Ostelo, R.W.J.G. ; Foster, N.E. ; Veenhof, C.
2021, Article / Letter to editor (BMC Musculoskeletal Disorders, vol. 22, iss. 1, (2021), pp. 143)BACKGROUND: Neck and shoulder complaints are common in primary care physiotherapy. These patients experience pain and disability, resulting in high societal costs due to, for example, healthcare use and work absence. Content and intensity of physiotherapy care can be matched to a patient's risk of persistent disabling pain. Mode of care delivery can be matched to the patient's suitability for blended care (integrating eHealth with physiotherapy sessions). It is hypothesized that combining these two approaches to stratified care (referred to from this point as Stratified Blended Approach) will improve the effectiveness and cost-effectiveness of physiotherapy for patients with neck and/or shoulder complaints compared to usual physiotherapy. METHODS: This paper presents the protocol of a multicenter, pragmatic, two-arm, parallel-group, cluster randomized controlled trial. A total of 92 physiotherapists will be recruited from Dutch primary care physiotherapy practices. Physiotherapy practices will be randomized to the Stratified Blended Approach arm or usual physiotherapy arm by a computer-generated random sequence table using SPSS (1:1 allocation). Number of physiotherapists (1 or > 1) will be used as a stratification variable. A total of 238 adults consulting with neck and/or shoulder complaints will be recruited to the trial by the physiotherapy practices. In the Stratified Blended Approach arm, physiotherapists will match I) the content and intensity of physiotherapy care to the patient's risk of persistent disabling pain, categorized as low, medium or high (using the Keele STarT MSK Tool) and II) the mode of care delivery to the patient's suitability and willingness to receive blended care. The control arm will receive physiotherapy as usual. Neither physiotherapists nor patients in the control arm will be informed about the Stratified Blended Approach arm. The primary outcome is region-specific pain and disability (combined score of Shoulder Pain and Disability Index & Neck Pain and Disability Scale) over 9 months. Effectiveness will be compared using linear mixed models. An economic evaluation will be performed from the societal and healthcare perspective. DISCUSSION: The trial will be the first to provide evidence on the effectiveness and cost-effectiveness of the Stratified Blended Approach compared with usual physiotherapy in patients with neck and/or shoulder complaints. TRIAL REGISTRATION: Netherlands Trial Register: NL8249 . Officially registered since 27 December 2019. Date of first enrollment: 30 September 2020. Study status: ongoing, data collection.
Feasibility of a stratified blended physiotherapy intervention for patients with non-specific low back pain: a mixed methods study.
TIlburg, M.L. van ; Kloek, C.J.J. ; Staal, J.B. ; Bossen, D. ; Veenhof, C.
2020, Article / Letter to editor (Physiotherapy Theory and Practice, (2020), pp. 1-13)INTRODUCTION: Integrating web-based or mobile components and face-to-face components within a treatment process is called blended care. As part of the participatory development of a blended physiotherapeutic intervention for patients with low back pain (e-Exercise LBP), a proof of concept study was carried out and showed promising results. OBJECTIVE: To investigate the feasibility of the e-Exercise LBP prototype for patients and physiotherapists to improve the intervention. METHODS: A mixed methods study was executed, embedded in the development phase of e-Exercise LBP. 21 physiotherapists treated 41 patients with e-Exercise LBP. Quantitative data consisted of: patients' satisfaction on a five-point Likert Scale; patients' and physiotherapists' experienced usability of the web-based application (System Usability Scale) and; patients' experiences with e-Exercise LBP (closed-ended questions and statements related to the elements and goals of e-Exercise LBP). Semi-structured interviews about experiences with e-Exercise LBP were conducted with seven patients and seven physiotherapists. Qualitative data were analyzed by a phenomenological approach. Quantitative data were analyzed with descriptive statistics. RESULTS: Patients were satisfied with e-Exercise LBP (mean: 4.0; SD:0.8; range: extreme dissatisfaction (1)-extreme satisfaction (5)). Usability of the web-based application was acceptable (patients: mean: 73.2 (SD:16.3); physiotherapists: mean: 63.3 (SD:12.0); range: 0-100). Interviews revealed that physiotherapists' training is essential to successfully integrate the web-based application and face-to-face sessions within physiotherapy treatment. Also, patients addressed the need of reminder messages to support long-term (exercise) adherence. CONCLUSION: e-Exercise LBP appeared to be feasible. However, various prerequisites and points of improvement were mentioned to improve physiotherapists' training and the prototype.
Development and proof of concept of a blended physiotherapeutic intervention for patients with non-specific low back pain.
Kloek, C.J.J. ; TIlburg, M.L. van ; Staal, J.B. ; Veenhof, C. ; Bossen, D.
2019, Article / Letter to editor (Physiotherapy, (2019))
Ontwikkeling van criteria voor indicatiestelling fysiotherapie binnen verpleeghuizen
Hobbelen, H. ; Leemrijse, C. ; Ravensberg, Dorine van ; Koopmans, R.T. ; Swart, B.J.M. de ; Haastert, C. van ; Veenhof, C.
2011, Article / Letter to editor (Fysiotherapie en Ouderenzorg, vol. 25, iss. 3, (2011), pp. 5-16)Er bestaat een grote variatie in het percentage bewoners per verpleeghuis dat wel of geen fysiotherapeutische zorg ontvangt. Hierdoor is het onduidelijk of de juiste groep wel fysiotherapie ontvangt. Er is dan ook behoefte aan meer transparantie en standaardisatie van de indicatiestelling fysiotherapie in verpleeghuizen. Het doel van deze studie is om criteria te ontwikkelen voor de indicatiestelling fysiotherapie in verpleeghuizen en deze te toetsen in de praktijk.

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