Background: In recent years, the effectiveness and cost-effectiveness of digital health services for people with musculoskeletal conditions have increasingly been studied and show potential. Despite the potential of digital health services, their use in primary care is lagging. A thorough implementation is needed, including the development of implementation strategies that potentially improve the use of digital health services in primary care. The first step in designing implementation strategies that fit the local context is to gain insight into determinants that influence implementation for patients and health care professionals. Until now, no systematic overview has existed of barriers and facilitators influencing the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Objective: This systematic literature review aims to identify barriers and facilitators to the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Methods: PubMed, Embase, and CINAHL were searched for eligible qualitative and mixed methods studies up to March 2024. Methodological quality of the qualitative component of the included studies was assessed with the Mixed Methods Appraisal Tool. A framework synthesis of barriers and facilitators to implementation was conducted using the Consolidated Framework for Implementation Research (CFIR). All identified CFIR constructs were given a reliability rating (high, medium, or low) to assess the consistency of reporting across each construct. Results: Overall, 35 studies were included in the qualitative synthesis. Methodological quality was high in 34 studies and medium in 1 study. Barriers (–) of and facilitators (+) to implementation were identified in all 5 CFIR domains: “digital health characteristics” (ie, commercial neutral [+], privacy and safety [–], specificity [+], and good usability [+]), “outer setting” (ie, acceptance by stakeholders [+], lack of health care guidelines [–], and external financial incentives [–]), “inner setting” (ie, change of treatment routines [+ and –], information incongruence (–), and support from colleagues [+]), “characteristics of the healthcare professionals” (ie, health care professionals’ acceptance [+ and –] and job satisfaction [+ and –]), and the “implementation process” (involvement [+] and justification and delegation [–]). All identified constructs and subconstructs of the CFIR had a high reliability rating. Some identified determinants that influence implementation may be facilitators in certain cases, whereas in others, they may be barriers. Conclusions: Barriers and facilitators were identified across all 5 CFIR domains, suggesting that the implementation process can be complex and requires implementation strategies across all CFIR domains. Stakeholders, including digital health intervention developers, health care professionals, health care organizations, health policy makers, health care funders, and researchers, can consider the identified barriers and facilitators to design tailored implementation strategies after prioritization has been carried out in their local context
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Objective To evaluate the validity and reliability of the Dutch STarT MSK tool in patients with musculoskeletal pain in primary care physiotherapy. Methods Physiotherapists included patients with musculoskeletal pain, aged 18 years or older. Patients completed a questionnaire at baseline and follow-up at 5 days and 3 months, respectively. Construct validity was assessed by comparing scores of STarT MSK items with reference questionnaires. Pearson’s correlation coefficients were calculated to test predefined hypotheses. Test-retest reliability was evaluated by calculating quadratic-weighted kappa coefficients for overall STarT MSK tool scores (range 0–12) and prognostic subgroups (low, medium and high risk). Predictive validity was assessed by calculating relative risk ratios for moderate risk and high risk, both compared with low risk, in their ability to predict persisting disability at 3 months. Results In total, 142 patients were included in the analysis. At baseline, 74 patients (52.1%) were categorised as low risk, 64 (45.1%) as medium risk and 4 (2.8%) as high risk. For construct validity, nine of the eleven predefined hypotheses were confirmed. For test-retest reliability, kappa coefficients for the overall tool scores and prognostic subgroups were 0.71 and 0.65, respectively. For predictive validity, relative risk ratios for persisting disability were 2.19 (95% CI: 1.10–4.38) for the medium-risk group and 7.30 (95% CI: 4.11–12.98) for the highrisk group. Conclusion The Dutch STarT MSK tool showed a sufficient to good validity and reliability in patients with musculoskeletal pain in primary care physiotherapy. The sample size for high-risk patients was small (n = 4), which may limit the generalisability of findings for this group. An external validation study with a larger sample of high-risk patients (�50) is recommended.
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Hematological malignancies and treatment with hematopoietic SCT are known to affect patients’ quality of life. The problem profile and care needs of this patient group need clarification, however. This study aimed to assess distress, problems and care needs after allo- or auto-SCT, and to identify risk factors for distress, problems or care needs. In this cross-sectional study, patients treated with allo-SCT or auto-SCT for hematological malignancies completed the Distress Thermometer and Problem List. Three patient groups were created: 0–1, 1–2.5 and 2.5–5.5 years after transplantation. After allo-SCT, distress and the number of problems tended to be lower with longer follow-up. After auto-SCT, distress was highest at 1–2.5 year(s). Patients mainly reported physical problems, followed by cognitive-emotional and practical problems. A minority reported care needs. Risk factors for distress as well as problems after allo-SCT included younger age, shorter time after transplantation and GVHD. A risk factor for distress as well as problems after auto-SCT was the presence of comorbid diseases. Up to 5 years after auto-SCT or allo-SCT, patients continue to experience distress and problems. Judged by prevalence, physical problems are first priority in supportive care, followed by cognitive-emotional and practical problems.
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SYNOPSIS: Neck pain, headache, and/ or orofacial symptoms are potentially the first (nonischemic) symptoms of an underlying vascular pathology or blood flow limitation. If an underlying vascular pathology or blood flow limitation is not recognized by the musculoskeletal rehabilitation clinician, it can subsequently be aggravated by treatment, raising the risk of serious adverse events. We argue that clinicians can make an important, and potentially lifesaving, difference by providing specific information and advice. This is especially the case in patients with an intermediate level of concern, for example, in patients who only show a few concerning features regarding a possible underlying serious condition and for whom an initial vasculogenic hypothesis was rejected during the clinical reasoning process. We present background information to help the reader understand the context of the problem and suggestions for how clinicians can provide appropriate information and advice to patients who present with neck pain, headache, and/or orofacial symptoms.
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Due to the ageing population, the prevalence of musculoskeletal disorders will continue to rise, as well as healthcare expenditure. To overcome these increasing expenditures, integration of orthopaedic care should be stimulated. The Primary Care Plus (PC+) intervention aimed to achieve this by facilitating collaboration between primary care and the hospital, in which specialised medical care is shifted to a primary care setting. The present study aims to evaluate the referral decision following orthopaedic care in PC+ and in particular to evaluate the influence of diagnostic tests on this decision. Therefore, retrospective monitoring data of patients visiting PC+ for orthopaedic care was used. Data was divided into two periods; P1 and P2. During P2, specialists in PC+ were able to request additional diagnostic tests (such as ultrasounds and MRIs). A total of 2,438 patients visiting PC+ for orthopaedic care were included in the analysis. The primary outcome was the referral decision following PC+ (back to the general practitioner (GP) or referral to outpatient hospital care). Independent variables were consultation- and patient-related predictors. To describe variations in the referral decision, logistic regression modelling was used. Results show that during P2, significantly more patients were referred back to their GP. Moreover, the multivariable analysis show a significant effect of patient age on the referral decision (OR 0.86, 95% CI = 0.81– 0.91) and a significant interaction was found between the treating specialist and the period (p = 0.015) and between patient’s diagnosis and the period (p < 0.001). Despite the significant impact of the possibility of requesting additional diagnostic tests in PC+, it is important to discuss the extent to which the availability of diagnostic tests fits within the vision of PC+. In addition, selecting appropriate profiles for specialists and patients for PC+ are necessary to further optimise the effectiveness and cost of care.
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Objective: To explore predictors of dropout of patients with chronic musculoskeletal pain from an interdisciplinary chronic pain management programme, and to develop and validate a multivariable prediction model, based on the Extended Common- Sense Model of Self-Regulation (E-CSM). Methods: In this prospective cohort study consecutive patients with chronic pain were recruited and followed up (July 2013 to May 2015). Possible associations between predictors and dropout were explored by univariate logistic regression analyses. Subsequently, multiple logistic regression analyses were executed to determine the model that best predicted dropout. Results: Of 188 patients who initiated treatment, 35 (19%) were classified as dropouts. The mean age of the dropout group was 47.9 years (standard deviation 9.9). Based on the univariate logistic regression analyses 7 predictors of the 18 potential predictors for dropout were eligible for entry into the multiple logistic regression analyses. Finally, only pain catastrophizing was identified as a significant predictor. Conclusion: Patients with chronic pain who catastrophize were more prone to dropout from this chronic pain management programme. However, due to the exploratory nature of this study no firm conclusions can be drawn about the predictive value of the E-CSM of Self-Regulation for dropout.
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AIM: To systematically review the available literature on the diagnostic accuracy of questionnaires and measurement instruments for headaches associated with musculoskeletal symptoms.DESIGN: Articles were eligible for inclusion when the diagnostic accuracy (sensitivity/specificity) was established for measurement instruments for headaches associated with musculoskeletal symptoms in an adult population. The databases searched were PubMed (1966-2018), Cochrane (1898-2018) and Cinahl (1988-2018). Methodological quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2) and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist for criterion validity. When possible, a meta-analysis was performed. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) recommendations were applied to establish the level of evidence per measurement instrument.RESULTS: From 3450 articles identified, 31 articles were included in this review. Eleven measurement instruments for migraine were identified, of which the ID-Migraine is recommended with a moderate level of evidence and a pooled sensitivity of 0.87 (95% CI: 0.85-0.89) and specificity of 0.75 (95% CI: 0.72-0.78). Six measurement instruments examined both migraine and tension-type headache and only the Headache Screening Questionnaire - Dutch version has a moderate level of evidence with a sensitivity of 0.69 (95% CI 0.55-0.80) and specificity of 0.90 (95% CI 0.77-0.96) for migraine, and a sensitivity of 0.36 (95% CI 0.21-0.54) and specificity of 0.86 (95% CI 0.74-0.92) for tension-type headache. For cervicogenic headache, only the cervical flexion rotation test was identified and had a very low level of evidence with a pooled sensitivity of 0.83 (95% CI 0.72-0.94) and specificity of 0.82 (95% CI 0.73-0.91).DISCUSSION: The current review is the first to establish an overview of the diagnostic accuracy of measurement instruments for headaches associated with musculoskeletal factors. However, as most measurement instruments were validated in one study, pooling was not always possible. Risk of bias was a serious problem for most studies, decreasing the level of evidence. More research is needed to enhance the level of evidence for existing measurement instruments for multiple headaches.
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Objective To develop and internally validate a prognostic model to predict chronic pain after a new episode of acute or subacute non-specific idiopathic, non-traumatic neck pain in patients presenting to physiotherapy primary care, emphasising modifiable biomedical, psychological and social factors. Design A prospective cohort study with a 6-month follow-up between January 2020 and March 2023. Setting 30 physiotherapy primary care practices. Participants Patients with a new presentation of non-specific idiopathic, non-traumatic neck pain, with a duration lasting no longer than 12 weeks from onset. Baseline measures Candidate prognostic variables collected from participants included age and sex, neck pain symptoms, work-related factors, general factors, psychological and behavioural factors and the remaining factors: therapeutic relation and healthcare provider attitude. Outcome measures Pain intensity at 6 weeks, 3 months and 6 months on a Numeric Pain Rating Scale (NPRS) after inclusion. An NPRS score of ≥3 at each time point was used to define chronic neck pain. Results 62 (10%) of the 603 participants developed chronic neck pain. The prognostic factors in the final model were sex, pain intensity, reported pain in different body regions, headache since and before the neck pain, posture during work, employment status, illness beliefs about pain identity and recovery, treatment beliefs, distress and self-efficacy. The model demonstrated an optimism-corrected area under the curve of 0.83 and a corrected R2 of 0.24. Calibration was deemed acceptable to good, as indicated by the calibration curve. The Hosmer–Lemeshow test yielded a p-value of 0.7167, indicating a good model fit. Conclusion This model has the potential to obtain a valid prognosis for developing chronic pain after a new episode of acute and subacute non-specific idiopathic, non-traumatic neck pain. It includes mostly potentially modifiable factors for physiotherapy practice. External validation of this model is recommended.
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In this thesis, a Dutch version of the Brief IPQ is presented to assess IPs in daily physiotherapy practice in The Netherlands. Further, a literature overview of the existing associations and prognosis of IPs on MSP and functioning is presented, and these associations in primary physiotherapy care in The Netherlands are explored. The impact of a matched care physiotherapy package, matched to dysfunctional IPs, and MSP and physical functioning is studied. In this thesis, three themes (ie. measurement, association / prediction and treatment) are explored for their contribution to physiotherapy management of MSP in general, and especially for low back pain
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a b s t r a c t Prolonged sitting can cause health problems and musculoskeletal discomfort. There is a need for objective and non-obstructive means of measuring sitting behavior. A ‘smart’ office chair can monitor sitting behavior and provide tactile feedback, aiming to improve sitting behavior. This study aimed to investigate the effect of the feedback signal on sitting behavior and musculoskeletal discomfort. In a 12- week prospective cohort study (ABCB design) among office workers (n ¼ 45) was measured sitting duration and posture, feedback signals and musculoskeletal discomfort. Between the study phases, small changes were observed in mean sitting duration, posture and discomfort. After turning off the feedback signal, a slight increase in sitting duration was observed (10 min, p ¼ 0.04), a slight decrease in optimally supported posture (2.8%, p < 0.01), and musculoskeletal discomfort (0.8, p < 0.01) was observed. We conclude that the ‘smart’ chair is able to monitor the sitting behavior, the feedback signal, however, led to small or insignificant changes. © 2017 Elsevier Ltd. All rights reserved.
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