Literature DB >> 25925506

Translation and validation of the Persian version of the STarT Back Screening Tool in patients with nonspecific low back pain.

Mohsen Abedi1, Farideh Dehghan Manshadi2, Minoo Khalkhali1, Seyed Javad Mousavi3, Alireza Akbarzadeh Baghban4, Ali Montazeri5, Mohamad Parnianpour6.   

Abstract

OBJECTIVE: To translate the STarT Back Screening Tool (SBT) into Persian and to investigate the psychometric properties of the new version in a group of patients with Non-Specific Low Back Pain (NSLBP).
BACKGROUND: The STarT is a validated questionnaire used for subgrouping LBP patients at three levels of low-, medium-, and high-risk, based on the risk of chronicity. It has previously been translated and validated in different languages.
METHODS: The translation and validation of the original questionnaire were carried out in accordance with the standard guidelines. To approve the construct validity, 295 patients with NSLBP completed a questionnaire package. The package comprised of the STarT, Roland-Morris Disability questionnaire (RMDQ), Tampa Scale for Kinesiophobia (TSK), Coping Strategies Questionnaire (CSQ), and Hospital Anxiety and Depression Scale (HADS). To evaluate test-retest reliability, 35 randomly selected NSLBP patients completed the STarT questionnaire within min. 24-hour interval.
RESULTS: Factor analysis confirmed two subscales of the STarT. The Cronbach α was .83 and .81 for the STarT and the subscale, respectively. This questionnaire showed excellent test-retest reliability (ICC = .85) (p < 0.01). The correlations between the STarT and RMDQ, CSQ, TSK, and the two subscales of HADS were estimated to be .81, .70, .71, .74, and .71, respectively. The Area under the Curve was also calculated for 6 items and the range was between .734 and .860.
CONCLUSIONS: The Persian version of the STarT is reliable and valid, and consistent with the original questionnaire. Therefore, clinicians to subgroup Persian-speaking NSLBP patients can use it.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Nonspecific low back pain; STarT Back Screening Tool; Validation

Mesh:

Year:  2015        PMID: 25925506     DOI: 10.1016/j.math.2015.04.006

Source DB:  PubMed          Journal:  Man Ther        ISSN: 1356-689X


  8 in total

Review 1.  Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews.

Authors:  Scott D Tagliaferri; Maia Angelova; Xiaohui Zhao; Patrick J Owen; Clint T Miller; Tim Wilkin; Daniel L Belavy
Journal:  NPJ Digit Med       Date:  2020-07-09

2.  Validation of the Subgroups for Targeted Treatment for Back (STarT Back) screening tool at a tertiary care centre.

Authors:  Susan Robarts; Helen Razmjou; Albert Yee; Joel Finkelstein
Journal:  Can J Surg       Date:  2022-05-17       Impact factor: 2.840

3.  Translation, cross-cultural adaptation and psychometric validation of the Thai version of the STarT Back Screening Tool in patients with non-specific low back pain.

Authors:  Taweewat Wiangkham; Nattawan Phungwattanakul; Natthathida Thongbai; Nisa Situy; Titipa Polchaika; Isara Kongmee; Duangporn Thongnoi; Rujirat Chaisang; Wanisara Suwanmongkhon
Journal:  BMC Musculoskelet Disord       Date:  2021-05-18       Impact factor: 2.562

Review 4.  Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews.

Authors:  Scott D Tagliaferri; Maia Angelova; Xiaohui Zhao; Patrick J Owen; Clint T Miller; Tim Wilkin; Daniel L Belavy
Journal:  NPJ Digit Med       Date:  2020-07-09

5.  A Practical Sensor-Based Methodology for the Quantitative Assessment and Classification of Chronic Non Specific Low Back Patients (NSLBP) in Clinical Settings.

Authors:  Mehrdad Davoudi; Seyyed Mohammadreza Shokouhyan; Mohsen Abedi; Narges Meftahi; Atefeh Rahimi; Ehsan Rashedi; Maryam Hoviattalab; Roya Narimani; Mohamad Parnianpour; Kinda Khalaf
Journal:  Sensors (Basel)       Date:  2020-05-20       Impact factor: 3.576

6.  Using a Motion Sensor to Categorize Nonspecific Low Back Pain Patients: A Machine Learning Approach.

Authors:  Masoud Abdollahi; Sajad Ashouri; Mohsen Abedi; Nasibeh Azadeh-Fard; Mohamad Parnianpour; Kinda Khalaf; Ehsan Rashedi
Journal:  Sensors (Basel)       Date:  2020-06-26       Impact factor: 3.576

7.  Psychometric Properties of the Japanese Version of the STarT Back Tool in Patients with Low Back Pain.

Authors:  Ko Matsudaira; Hiroyuki Oka; Norimasa Kikuchi; Yuri Haga; Takayuki Sawada; Sakae Tanaka
Journal:  PLoS One       Date:  2016-03-22       Impact factor: 3.240

8.  Cross-cultural adaptation and validation of the STarT back screening tool in isiZulu.

Authors:  Peta-Ann Schmidt; Vaneshveri Naidoo
Journal:  S Afr J Physiother       Date:  2020-06-01
  8 in total

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