The development of individualised work absence prediction models in patients with neck and/or low back pain

Physiotherapy ◽  
2021 ◽  
Vol 113 ◽  
pp. e35
Author(s):  
G. Wynne-Jones ◽  
L. Archer ◽  
K.I.E. Snell ◽  
S. Stynes ◽  
K.M. Dunn ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Prediction Models ◽  
Work Absence ◽  
Low Back

scholarly journals Pain catastrophizing, kinesiophobia and fear-avoidance in non-specific work-related low-back pain as predictors of sickness absence

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0242994
Author(s):  
Israel Macías-Toronjo ◽  
María Jesús Rojas-Ocaña ◽  
José Luis Sánchez-Ramos ◽  
E. Begoña García-Navarro
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Sickness Absence ◽  
Pain Catastrophizing ◽  
Specific Work ◽  
Work Absence ◽  
Low Back ◽  
Fear Avoidance ◽  
Fear Avoidance Beliefs ◽  
Work Related

The influence of pain catastrophizing, kinesiophobia and fear-avoidance attitudes towards non-specific low-back pain has been scarcely studied in an occupational insurance provider context. The objective of this work is to ascertain the relationship between these psychosocial variables with work absence, its duration and the disability of subjects with work-related low back pain. This is a descriptive observational methodological strategy. All patients with work-related non-specific low back pain who attended to an occupational health hospital during the study period were included consecutively. Clinical variables of kinesiophobia, pain catastrophizing, fear-avoidance attitudes, disability and pain were collected; sociodemographic variables of sex, age, type of work, educational level, occupational status and duration in days of work absence were recorded. Kinesiophobia (b = 1.43, P = 0.011, r = 0.333), fear-avoidance beliefs in its global dimension (b = 0.910, P = 0.014, r = 0.321), fear-avoidance beliefs in its work dimension (b = 1.255, P = 0.016, r = 0.321) and pain catastrophizing (b = 0.997, P = 0.013, r = 0.340) show individual association with the duration of sickness absence. Kinesiophobia (b = 0.821, P = 0.011, r = 0.30) and fear-avoidance beliefs (b = 1.760, P = 0.016, r = 0.28) are associated with disability (Kinesiophobia, b = 0.880, P = 0.045, r = 0.26; Fear-avoidance beliefs, b = 0.724, P = 0.010, r = 0.34). Kinesiophobia, fear-avoidance beliefs and pain catastrophizing are related to an increase in the duration of work absence and disability in patients with back pain in an occupational insurance provider context.

Work absence and absence costs in patients with osteoarthritis (OA) and low back pain (LBP) in the United States

2010 ◽  
Vol 11 (4) ◽  
pp. S8
Author(s):  
P. Vo ◽  
R. Brook ◽  
N. Kleinman ◽  
S. Strassels ◽  
J. Smeeding ◽  
...  
Keyword(s):  
United States ◽  
Low Back Pain ◽  
Back Pain ◽  
The United States ◽  
Work Absence ◽  
Low Back

scholarly journals Pain-related fear – Dissociable neural sources of different fear constructs

2018 ◽  
Author(s):  
Michael Lukas Meier ◽  
Andrea Vrana ◽  
Barry Kim Humphreys ◽  
Erich Seifritz ◽  
Philipp Stämpfli ◽  
...  
Keyword(s):  
Machine Learning ◽  
Low Back Pain ◽  
Back Pain ◽  
Musculoskeletal Pain ◽  
Chronic Low Back Pain ◽  
Prognostic Value ◽  
Prediction Models ◽  
Self Report ◽  
Low Back ◽  
Pain Patients

AbstractFear of pain demonstrates significant prognostic value regarding the development of persistent musculoskeletal pain and disability. Its assessment often relies on self-report measures of pain-related fear by a variety of questionnaires. However, based either on “fear of movement/(re)injury/kinesiophobia”, “fear avoidance beliefs” or “pain anxiety”, pain-related fear constructs seemingly differ while the potential overlap of the questionnaires is unclear. Furthermore, the relationship to other anxiety measures such as state or trait anxiety remains ambiguous. Because the neural bases of fearful and anxious states are well described, advances in neuroimaging such as machine learning on brain activity patterns recorded by functional magnetic resonance imaging might help to dissect commonalities or differences across pain-related fear constructs. We applied a pattern regression approach in 20 non-specific chronic low back pain patients to reveal predictive relationships between fear-related neural information and different pain-related fear questionnaires. More specifically, the applied Multiple Kernel Learning approach allowed generating models to predict the questionnaire scores based on a hierarchical ranking of fear-related neural patterns induced by viewing videos of potentially harmful activities for the back. We sought to find evidence for or against overlapping pain-related fear constructs by comparing the questionnaire prediction models according to their predictive abilities and associated neural contributors. The results underpin the diversity of pain-related fear constructs by demonstrating evidence of non-overlapping neural predictors within fear processing regions. This neuroscientific approach might ultimately help to further understand and dissect psychological pain-related fear constructs.SignificancePain-related fear, often assessed through self-reports such as questionnaires, has shown prognostic value and clinical utility for a variety of musculoskeletal pain disorders. However, it remains difficult to determine a common underlying construct of pain-related fear due to several proposed constructs among questionnaires. The current study describes a novel neuroscientific approach using machine learning of neural patterns within the fear circuit of chronic low back pain patients that has the potential to identify neural commonalities or differences among the various pain-related fear constructs. Ultimately, this approach might afford a deeper understanding of the suggested constructs and might be also applied to other domains where ambiguity exists between different psychological constructs.

scholarly journals Prognostic Prediction Models for Patients with Low Back Pain: Systematic Review Protocol

2020 ◽  
Author(s):  
Fernanda Gonçalves Silva ◽  
Leonardo Oliveira Pena Costa ◽  
Mark J Hancock ◽  
Gabriele Alves Palomo ◽  
Luciola da Cunha Menezes Costa ◽  
...  
Keyword(s):  
Systematic Review ◽  
Low Back Pain ◽  
Back Pain ◽  
Prediction Model ◽  
Prediction Models ◽  
External Validation ◽  
Risk Of Bias ◽  
Low Back ◽  
Clinical Prediction ◽  
Clinical Prediction Models

Abstract Background: The prognosis of acute low back pain is generally favourable in terms of pain and disability; however, outcomes vary substantially between individual patients. Clinical prediction models help in estimating the likelihood of an outcome at a certain time point. There are existing clinical prediction models focused on prognosis for patients with low back pain. To date, there is only one previous systematic review summarising the discrimination of validated clinical prediction models to identify the prognosis in patients with low back pain of less than 3 months duration. The aim of this systematic review is to identify existing developed and/or validated clinical prediction models on prognosis of patients with low back pain of less than 3 months duration, and to summarise their performance in terms of discrimination and calibration. Methods: MEDLINE, Embase and CINAHL databases will be searched, from the inception of these databases until January 2020. Eligibility criteria will be: (1) prognostic model development studies with or without external validation, or prognostic external validation studies with or without model updating; (2) with adults aged 18 or over, with ‘recent onset’ low back pain (i.e. less than 3 months duration), with or without leg pain; (3) outcomes of pain, disability, sick leave or days absent from work or return to work status, and self-reported recovery; and (4) study with a follow-up of at least 12 weeks duration. The risk of bias of the included studies will be assessed by the Prediction model Risk Of Bias ASsessment Tool, and the overall quality of evidence will be rated using the Hierarchy of Evidence for Clinical Prediction Rules. Discussion: This systematic review will identify, appraise, and summarize evidence on the performance of existing prediction models for prognosis of low back pain, and may help clinicians to choose the best option of prediction model to better inform patients about their likely prognosis. Systematic review registration: PROSPERO reference number CRD42020160988

scholarly journals AYURVEDIC MANAGEMENT OF LOW BACK PAIN WITH MODIFIED ABHYANGA: A CASE STUDY

2022 ◽  
Vol 12 (6) ◽  
pp. 1-2
Author(s):  
Resmi Babu K ◽  
Smitha .
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Effective Treatment ◽  
Financial Burden ◽  
Work Hours ◽  
Work Absence ◽  
Low Back ◽  
Procedure Duration

Low back pain is one of the widespread health problems and the leading cause of activity limitation and work absence worldwide. Among the types of low back pain, low back pain due to mechanical causes is more common. Abhyanga is an effective treatment for low back pain, which can be done as an OPD level treatment without causing much financial burden. Though it is a widely practised procedure, we did not explore its possibilities properly. Abhyanga can be modified by incorporating other massage techniques like Swedish massage for better application. Cupping is a variety of tapotement massage techniques of a Swedish massage. Abhyanga performed along with the cupping massage techniques is very effective in managing low back pain. A 45year old lady patient came to OPD complaining of low back pain. On examination, stooping posture during her work hours was concluded as the reason for the pain. She was treated with modified Abhyanga with moorchita tilataila for seven days. The procedure duration was 20 minutes. Treatment was found to be effective after treatment and after follow up as her symptoms wholly vanished.

Are Psychosocial Factors Associated With Low Back Pain and Work Absence for Low Back Pain in an Occupational Cohort?

2013 ◽  
Vol 29 (12) ◽  
pp. 1015-1020 ◽  
Author(s):  
Donna M. Urquhart ◽  
Helen L. Kelsall ◽  
Victor C.W. Hoe ◽  
Flavia M. Cicuttini ◽  
Andrew B. Forbes ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Psychosocial Factors ◽  
Work Absence ◽  
Low Back ◽  
Factors Associated ◽  
Occupational Cohort

Prediction models to identify workers at risk of sick leave due to low-back pain in the Dutch construction industry

2018 ◽  
Author(s):  
Lisa C Bosman ◽  
Lyan Dijkstra ◽  
Catelijne I oling ◽  
Martijn W Heymans ◽  
Jos WR Twisk ◽  
...  
Keyword(s):  
At Risk ◽  
Low Back Pain ◽  
Back Pain ◽  
Sick Leave ◽  
Construction Industry ◽  
Prediction Models ◽  
Low Back

scholarly journals Evaluation of the effects of Microwave Diathermy in Patients with Chronic Low Back Pain

2014 ◽  
Vol 27 (2) ◽  
pp. 64-68
Author(s):  
Farzana Khan Shoma ◽  
Azm Mahfuzur Rahman ◽  
Tariqul Islam ◽  
Md. Ahsan Habib ◽  
Khurshid Mahmood ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Chronic Low Back Pain ◽  
Daily Living ◽  
Work Absence ◽  
Low Back ◽  
Common Cause ◽  
Significant Difference ◽  
Inflammatory Drugs ◽  
Microwave Diathermy

Background: Back pain affects 60-80% of people at some time in their lives. Back pain is the most common cause of sickness-related work absence. Microwave diathermy could be an important treatment modality. Very few studies have been conducted in our country in this regard. Aims: To determine the effects of microwave diathermy in relieving symptoms of chronic low back pain when applied along with other conventional therapies like drug and exercise. Methods: Total 50 patients with chronic low back pain coming to OPD, DMCH were divided randomly into two groups and treated with nonsteroidal anti-inflammatory drugs, exercises, activities of daily living instructions and with or without microwave diathermy. Thereafter, the patients were evaluated weekly. After six weeks of treatment, improvements were observed in both the groups. Results: significant difference (P=0) in improvement was found in microwave diathermy group than in non-diathermy group. Conclusion: This study suggests that microwave diathermy is effective in treatment of patients with chronic low back pain. Bangladesh Journal of Neuroscience 2011; Vol. 27 (2) : 64-68 DOI: http://dx.doi.org/10.3329/bjn.v27i2.17544

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