Background Evidence based practice in health care has become increasingly popular over the last decades. Many guidelines have been developed to improve evidence informed decision making in health care organisations, however it is often overlooked that the actual implementation strategies for these guidelines are as important as the guidelines themselves. The effectiveness of these strategies is rarely ever tested specifically for the allied health therapy group. Methods Cochrane, Medline, Embase and Scopus databases were searched from 2000 to October 2019. Level I and II studies were included if an evidence informed implementation strategy was tested in allied health personnel. The SIGN method was used to evaluate risk of bias. The evidence was synthesised using a narrative synthesis. The National Health and Medical Research Council (NHMRC) model was applied to evaluate the grade for recommendation. Results A total of 490 unique articles were identified, with 6 primary studies meeting the inclusion criteria. Three different implementation strategies and three multi-faceted components strategies were described. We found moderate evidence for educational meetings, local opinion leaders and patient mediated interventions. We found stronger evidence for multi-faceted components strategies. Conclusion Few studies describe the effectiveness of implementation strategies for allied healthcare, but evidence was found for multi-faceted components for implementing research in an allied health therapy group population. When considering implementation of evidence informed interventions in allied health a multi-pronged approach appears to be more successful.
Purpose Motivation may predict return to work (RTW), yet the measurement of motivation needs more scientific evidence. We adopt a dimensional approach, based on the Self-Determination Theory (SDT), distinguishing between amotivation, controlled and autonomous motivation. We seek to explore the presence of these dimensions in sick-disabled patients, and are interested in associations with quality of life, depression, patient's predictions of RTW, and health care provider estimations of patient's motivation. Materials and methodsA cross-sectional study in 336 patients was conducted. Motivation was assessed using the Motivation at Work Scale (MAWS) and examined in relation to patient outcomes, patient's prediction of RTW, and health care provider estimations of patients' motivation. A cluster analysis was performed, and differential associations between motivational profiles were explored. ResultsCluster analysis revealed four profiles. Highly controlled profiles were most prevalent, reported poorer mental quality of life, and expected a longer time before RTW, regardless of the level of autonomous motivation. Interestingly, the health care provider's estimation was not related to controlled motivation. ConclusionOur results show that SDT may help to differentiate people with a work disability regarding their motivation to RTW. Most notably, the devastating consequences of controlled motivation are discussed, and clinical implications are provided.
Background: Long-term sickness absence is a growing concern in Belgium and other European countries. Since 2017, Belgian physicians of the sickness funding organisations are required to assess the re-integration possibilities within the first two months of sickness absence. Given the shortage of physicians in the assessment of work disability and the growing number of people in sickness absence, there is a need for a triage tool, allowing to assign return-to work support to patients having a high-risk profile not to resume work.Methods/design: The current study comprises a comprehensive validation process of a screening tool that supports Belgian physicians in guiding people back to work. The study consists of a theoretical construct validation (face validity and content validity), and an empirical construct validation (concurrence validity, factorial validity, predictive validity, hypothesis testing validity and known- group validity).Expected impact of the study for Public Health: The screening instrument assessing the risk for long-term sickness absence is a tool developed to support physicians who work for sickness funds and for occupational health and safety organisations. Both professionals play an important role in the return to work process and the prevention of long-term sickness absence. The screening tool aims at making a distinction between people who will resume their work independently and people who will need support to do so. Generation of this prediction model will help physicians to focus effort and resources in the high-risk group. Results may also help understand the relationship between the biopsychosocial model and long-term sick-leave.Significance for public healthIn this research, we tested a generic instrument to screen for long-term sickness absence, regardless the cause of the sickness absence or the political context. Both biomedical factors and psychosocial factors (such as the patients’ own prediction) are questioned in the prediction model, which is thus adapted to the modern view on sick leave. A screening method to detect high risk of long-term sickness absence among the large group of sick employees might help to use resources (e.g. money, services) in a more efficient way. Physicians will be able to focus on patients with a high risk on long-term sick leave, and the return to work process of employees at high risk can start much earlier. The instrument will, next to the physicians’ prognosis, offer support in prioritizing patients’ files. Hence, a lot of patients will resume their work spontaneously. Patients who need support will experience shorter follow-up periods, and better quality of care. In addition, the relationship between predicting factors of the biopsychosocial model and long-term sickness absence will be examined.
BackgroundThis study assessed the psychosocial determinants as explanatory variables for the length of the work disability period. The aim was to estimate the predictive value of a selected set of psychosocial determinants from the Quickscan questionnaire for the length of the sick leave period. A comparison was also made with the most common biomedical determinant: diagnosis.MethodsIn a cohort study of 4 981 insured Belgian patients, the length of the sick leave was calculated using Kaplan–Meier. Predictive psychosocial determinants were selected using backward conditional selection in Cox regression and using concordance index values (C-index) we compared the predictive value of the biomedical to the psychosocial model in a sample subset.ResultsFourteen psychosocial determinants were significantly (p<0.10) related to the length of the sick leave: health perception of the patient, physical workload, social support management, social support colleagues, work–health interference, psychological distress, fear of colleagues’ expectations, stressful life-events, autonomy, learning and development opportunities, job satisfaction, workload, work expectations and expectation to return to work. The C-index of this biopsychosocial model including gender, age and labour status was 0.80 (CI: 0.78; 0.81) (n=4 981). In the subset of 2 868 respondents with diagnostic information, the C-index for the same model was .73 (CI: 0.71; 0.76) compared with 0.63 (CI: 0.61; 0.65) for the biomedical model.ConclusionsA set of 14 psychosocial determinants showed good predictive capacity (C-index: 0.80). Also, in a subset of the sample, the selected determinants performed better compared with diagnostic information to predict long-term sick leave (>6 months).
Objective:Increasing long-term sickness absence in many countries asks for specific measures regarding return-to work.Methods:The risk of long-term sickness absence was assessed using a questionnaire containing work-related, function-related, stressful life-events-related, and person-related factors. Additionally, workers’ occupational health physician estimated the worker's chances for work resumption. Reliability, construct, and criterion validity of the questionnaire were measured.Results:Two hundred seventy-six patients and 35 physicians participated in the study. The reliability was satisfying (α > 0.70) for all scales, except for perfectionism (α = 0.62). The results of the CFAs showed that the hypothesized factor models fitted the data well. Criterion validity tests showed that eight predictors significantly related to the estimation of the occupational physicians (ρ < 0.05).Conclusions:The scales of the questionnaire are reliable and valid, and may be implemented to assess sick-listed workers at risk who might benefit from a rehabilitation program.
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