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Vol. 27. Issue 6.
(1 November 2023)
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Vol. 27. Issue 6.
(1 November 2023)
Systematic Review
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What do people believe to be the cause of low back pain? A scoping review
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1611
Søren Grøna,b,
Corresponding author
sgron@health.sdu.dk

Corresponding author.
, Kasper Bülowa,c, Tobias Daniel Jonssond, Jakob Degnd, Alice Kongsteda,b
a Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
b Chiropractic Knowledge Hub, Campusvej 55, 5230 Odense M, Denmark
c Centre for Health and Rehabilitation, University College Absalon, Slagelse, Denmark
d Independent researcher (chiropractic practice)
Highlights

  • There is a high variation in measuring causal beliefs about low back pain.

  • No measurement exists that clearly isolates causal beliefs from other belief domains.

  • There is a lack of studies exploring longitudinal relationships between causal beliefs and health outcomes.

  • Causal beliefs are just one element of a complex beliefs construct, and there is very little quantitative evidence from which its unique relevance can be judged.

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Table 1. Characteristics of included studies.
Table 2. Categories of causal beliefs.
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Additional material (1)
Abstract
Objective

To explore how causal beliefs regarding non-specific low back pain (LBP) have been quantitatively investigated.

Methods

A scoping review based on the guidelines by the JBI (former Joanna Briggs Institute) was conducted. We searched Medline, Embase, Psychinfo, and CINAHL for relevant studies and included peer-reviewed original articles that measured causal beliefs about non-specific LBP among adults and reported results separate from other belief domains.

Results

A total of 81 studies were included, of which 62 (77%) had cross sectional designs, 11 (14%) were cohort studies, 3 (4%) randomized controlled trials, 4 (5%) non-randomized controlled trials, and 1 (1%) case control. Only 15 studies explicitly mentioned cause, triggers, or etiology in the study aim. We identified the use of 6 questionnaires from which a measure of causal beliefs could be obtained. The most frequently used questionnaire was the Illness Perception Questionnaire which was used in 8 of the included studies. The studies covered 308 unique causal belief items which we categorized into 15 categories, the most frequently investigated being causal beliefs related to “structural injury or impairment”, which was investigated in 45 (56%) of the studies. The second and third most prevalent categories were related to “lifting and bending“ (26 studies [32%]) and “mental or psychological” (24 studies [30%]).

Conclusion

There is a large variation in how causal beliefs are measured and a lack of studies designed to investigate causal beliefs, and of studies determining a longitudinal association between such beliefs and patient outcomes. This scoping review identified an evidence gap and can inspire future research in this field.

Keywords:
Attitudes and beliefs
Causal beliefs
Illness perceptions
Low back pain
Questionnaire
Scoping review
Full Text
Introduction

The way people understand pain can influence their conscious or unconscious response to it, thus pain perceptions impact behavior and pain related disability.1,2 This is outlined in the Common-Sense Model which illustrates that people create cognitive representations to make sense of an experience, e.g., when experiencing pain.2,3 The representation of illness is created from developing a coherent understanding across the following belief domains: a) what is this pain? (Identity beliefs), b) what caused this pain? (Causal beliefs), c) what will this pain mean to me? (Consequence beliefs), d) how can I control this pain? (Control beliefs), and e) how long will it last? (Timeline beliefs).1,2 The theory suggests that people try to make a coherent understanding of an illness which drives actions and behaviors in response to that illness.

In low back pain (LBP), qualitative research indicates that causal beliefs can have an immense impact on people's lives and how they manage their LBP.4-7 For instance, believing that LBP is caused by damage or the spine being weak can lead to overprotective behavior that involves avoiding certain movements or valued activities.5-9 Furthermore, such causal beliefs about LBP may be a barrier to modern guideline-based care for LBP, as it seems some patients feel miscast for self-management interventions because it does not match their illness beliefs.10

Multiple questionnaires exist regarding beliefs about LBP, and some include questions reflecting causal beliefs. For instance, the belief that LBP is caused by damage or injury of an organic structure is measured in the Pain Beliefs Questionnaire (PBQ) asking if “Pain is the result of damage to the tissue of the body” and as part of the Back Pain Attitudes Questionnaire (Back-PAQ): “Back pain means you have injured your back”.11,12 Both are examples of single items in questionnaires that investigate multiple domains of beliefs. The widely used illness perception questionnaire (IPQ) also includes causal belief items.13 However, a systematic review from 2018 that investigated the association between IPQ scores and pain and disability among people with musculoskeletal pain did not include causal beliefs because these are not measured on a numeric scale in the IPQ.14

Thus, as summarized above, it seems from qualitative research that causal beliefs may be highly important in LBP and several questionnaires exist to potentially investigate this quantitatively. However, the quantitative measure of causal beliefs seems to be heterogeneous and there is currently no overview of the literature investigating causal beliefs. It is thus unclear what quantitative evidence exists that isolates the importance of causal beliefs in LBP from other belief domains. To investigate if the relationship seen in qualitative studies between causal beliefs and poor outcomes of LBP has been investigated in quantitative studies, we conducted a scoping review to map out this research. The aim was to provide an overview of how causal beliefs regarding non-specific LBP have been quantitatively investigated. The specific objectives were to examine: a) What questions and questionnaires have been used to measure causal beliefs regarding non-specific LBP? b) What types of causal beliefs about non-specific LBP have been identified and how many studies have investigated these beliefs? c) In which type of studies and contexts have causal beliefs about non-specific LBP been measured? and d) What outcomes have been investigated for an association with causal beliefs about non-specific LBP in cross-sectional and longitudinal designs?

Methods

The protocol for this scoping review was pre-registered at Open Science Framework on December 20, 2021, and is available at https://osf.io/7hezb. The method was based on the instructions provided in the JBI manual of evidence synthesis on scoping reviews, and we reported the review according to the PRISMA-ScR checklist for scoping reviews.15,16

Eligibility criteria

We included published original scientific papers that measured causal beliefs about non-specific LBP and reported results from this domain that could be isolated from other beliefs domains. Population were adults from non-clinical populations with or without non-specific LBP, health-care providers and clinical (i.e., care seeking) populations of patients with non-specific LBP. We excluded studies testing psychometric properties of questionnaires or transcultural adaptations.

Our interpretation of causal beliefs was conceptualized by the common-sense model, which implies that the perception of what caused LBP should be distinguishable from beliefs that according to the common-sense-model relate to other domains. We defined causal beliefs as: a) a perceived cause of LBP, b) a perceived trigger of a new onset of LBP, or c) a perceived risk factor for LBP. Any quantitative measure or data from quantified text responses capturing a causal belief was included. Thus, studies measuring causal beliefs by text responses were only included if the researchers categorized and quantified the text responses in the studies. Studies that in the abstract mentioned causal beliefs specifically or unspecified beliefs were included for full text assessment. Studies measuring beliefs that were specified as other types of beliefs than causal beliefs (e.g., fear avoidance beliefs or kinesiophobia beliefs) were not included.

Furthermore, only peer-reviewed articles written in English were included. We did not use any restriction on time period.

Search strategy

We searched the following electronic databases: Embase, Medline, PsychInfo, and CINAHL. The search strategy was developed in collaboration with a librarian from University Library of Southern Denmark and was initially developed for Embase and then adapted to the other databases. Keywords and search terms were identified from preliminary searches and reading of articles related to the subject. The search combined words of LBP with words for causal beliefs, using both keywords and subject headings (Supplementary material A). The search was conducted on January 10, 2022.

Selection of sources of evidence

Duplicates were removed in Endnote before uploading citations to Covidence review software (Veritas Health Innovation, Melbourne, Australia) for screening and data extraction. Prior to screening of titles and abstracts the inclusion criteria were tested by the entire review team in a pilot screening of a small test sample of 30 titles and abstracts. Two rounds of pilot screening were completed to achieve the desired 75% agreement threshold.

The screening of titles and abstracts as well as full-text assessments were done double-blinded with SG screening the entire sample and TJ, KB, and JD splitting the sample between them. Disagreements between the reviewers were settled through discussion to reach consensus.

Data charting process

The extracted data included study characteristics (population, setting, country, and aim), causal beliefs measurement tool, causal belief items, and outcomes investigated for cross-sectional or longitudinal associations with causal beliefs. The outcomes investigated were only extracted in cases where the association could be linked to the isolated causal belief item. SG and AK piloted the extraction tool and made modification before moving on to the final extraction. Extraction was done independently by SG extracting the entire sample of studies and AK, TJ, JD, and KB splitting the sample between them.

Prior to data extraction consensus between the review team was made to determine which items from the identified questionnaires were considered causal beliefs (Supplementary material B). Each member independently voted for each item whether they deemed it to measure a causal belief based on face validity. The votes were compared, and disagreements settled by discussions in the entire review team to reach consensus.

Synthesis of results

Data were exported from Covidence and handled in Stata/MP V.17. (StataCorp Texas, USA). Extracted data were organized in tables and visualized in bar charts made in Microsoft Excel (Microsoft Corporation, Redmond, WA). The causal belief items extracted from the studies were categorized into mutually exclusive categories based upon face validity of the beliefs. The first half of the items were categorized in a consensus forum between SG, JD, KB, and AK. The remaining were categorized by SG whereupon all authors commented and agreed upon the final categorization (for resulting categories see supplementary material C).

Results

Of 8901 titles and abstracts screened, 316 were assessed in full-text, and 81 papers were included (Fig. 1). Most exclusions after full text assessment were because the studies did not measure causal beliefs or did not report a result specifically related to the causal belief. Most of the studies (n = 62 [77%]) had cross sectional designs, 11 (14%) studies were cohorts, 3 (4%) randomized controlled trials, 4 (5%) non-randomized controlled trials, and 1 (1%) was a case-control study (Table 1). Beliefs, attitudes, opinions, myths, or perceptions were mentioned in the aim in 44 (54%) studies, and 15 (19%) had an aim specifically mentioning cause, triggers, or etiology. Thirty-three (41%) of the study samples were from the general population, 26 (32%) from health care providers, 13 (16%) from clinical population, 5 (6%) from health-care students, and 4 (5%) studies included mixed populations (Table 1). Most studies were from Western Europe, Australia, or North America.

Fig. 1.

Flowchart of selection process.

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Table 1.

Characteristics of included studies.

Study  Country  Population  Design  Categories of causal belief measured  Measurement  Associations investigated 
Lindström 199439  Sweden  General population  Cohort study  LB, LMPC, PWS, PP, MP, EE  Other non-validated  No 
Christe 202140  Switzerland  General population  Cross-sectional study  SIP  Back-PAQ-34  No 
Pereira 202017  Portugal  Clinical  Cross-sectional study    IPQ-revised  Cross-sectional: pain intensity, disability, IPQ-domains, suffering, psychology morbidity 
Zusman 198441  Australia  Clinical  Cross-sectional study  SIP  Other non-validated  no 
Talbott 200942  United States  General population  Cross-sectional study  LB  Other non-validated  no 
Dean 201143  New Zealand  General population  Cross-sectional study  LB, PAS, LMPC, PWD, PP, TM, Gen, GHL  IPQ-brief  no 
Matsui 199744  Japan  General population  Cross-sectional study  LB, PAS, PP, TM, Unk  Other non-validated  Cross-sectional: physical work demand 
Byrns 200434  United States  Health-care providers  Cross-sectional study  PWD, OWD, Spi, Oth  Modification of Worker attributions scale, and additional questions  no 
Ree 201645  Norway  General population  Randomised controlled trial  LB  Deyo's back pain myths  Cross-sectional: days of sick leave 
Moffett 200020  UK  General population  Cross-sectional study  SIP, GHL  Other non-validated  Cross-sectional: no back pain, back pain within the past year, consulted General Practitioner for back pain within the last year 
Keeley 200846  UK  Clinical  Cohort study  PWD, TM, Unk  Other non-validated  Longitudinal: health related quality of life, number of health care contacts 
Vargas-Prada 201229  Spain  Mixed  Cohort study  OWD  Questions adapted from FABQ  Longitudinal: new LBP, new disabling LBP, persistence of LBP, persistence of disabling LBP 
Scholey 198947  UK  Mixed  Cross-sectional study  LB, TM  Other non-validated  no 
Adhikari 201448  Nepal  Health-care providers  Cross-sectional study  LB, PWD, OWD, PP  Other non-validated  no 
Battista 202149  Italy  General population  Cross-sectional study  PAS  Other non-validated  no 
French 199750  Hong Kong  Health-care providers  Cross-sectional study  LMPC, PWD, PP  Other non-validated  no 
Sadeghian 201330  Iran  Mixed  Cohort study  OWD  Other non-validated  Longitudinal: reporting LBP 
Alshehri 202051  Saudi Arabia  Health-care providers  Cross-sectional study  SIP, MP, Unk,  PABS-PT (19-items)  no 
Christe 202140  Switzerland  Health-care providers  Cross-sectional study  SIP  Back-PAQ-34  Cross-sectional: Degree of evidence-concordant clinical decisions for young woman with acute LBP and no sign of serious pathology 
Ross 201452  United States  Health-care providers  Cross-sectional study  SIP  Other non-validated  no 
Werner 200753  Norway  General population  Cohort study  SIP  Deyo's back pain myths  no 
Stevens 201654  Australia  Mixed  Cross-sectional study  LB, PAS, LMPC, PP, SIP, TM, MP, GHL, Oth  Other non-validated  no 
Fitzgerald 202055  Australia  Health-care providers  Cross-sectional study  SIP, MP, Unk  PABS-PT-19, ABS-MP, NPQ  no 
Mehok 201956  United States  General population  Cross-sectional study    Other non-validated  Cross sectional: body weight treatment recommendations 
Benny 202057  Canada  Health-care providers  Cross-sectional study  SIP, MP, Unk  PABS-PT (19-items)  no 
Ihlebæk 200422  Norway  Health-care providers  Cross-sectional study  LB, SIP  Deyo's back pain myths  Cross-sectional: sex, age, profession 
Ihlebæk 200558  Norway  General population  Cross-sectional study  LB, SIP  Deyo's back pain myths  no 
Adams 201359  United States  Health-care providers  Cross-sectional study  PWD, SIP  Modification of the standardized Nordic Questionnaire  no 
Boschman 201260  The Netherlands  General population  Cohort study  OWD  Other non-validated  no 
James 201861  Australia  General population  Cross-sectional study  OWD  Other non-validated  no 
Cherkin 198862  United States  Health-care providers  Cross-sectional study  SIP, MP, Unk  Other non-validated  no 
Brennan 200763  Ireland  General population  Cross-sectional study  LB, PAS, TM  Other non-validated  no 
Goubert 200321  Belgium  General population  Cross-sectional study  SIP  Low back pain beliefs questionnaire, specifically developed based on Deyo's myths, TSK, PABS-PT, and the self-care orientation scale  Cross-sectional: pain grade 
Werner 200864  Norway  General population  Cohort study  SIP  Deyo's back pain myths  Cross-sectional and longitudinal: Odds ratios for appropriate responses in intervention vs control counties. 
Walker 200427  Australia  General population  Cross-sectional study  PAS, OWD, PP, TM  Other non-validated  Cross-sectional: Logistic regression assessing the odds-ratio for care seeking using all other categories as a reference group. 
Vujcic 201823  Serbia  Health-care students  Cross-sectional study  PAS, PP, MP, EE, Oth  Other non-validated  Cross-sectional: sex 
Maselli 202165  Italy  General population  Cross-sectional study  PAS  Other non-validated  no 
Patel 201624  Canada  Health-care providers  Cross-sectional study  SIP  Other non-validated  Cross-sectional: sex, years of practice, hours of practice/week, population size of practice 
Tarimo 201766  Malawi  Clinical  Cross-sectional study  LB, PAS, OWD, PP, SIP, TM, MP, GHL, EE, Unk, Oth  Modification of LBP knowledge questionnaire  no 
Dabbous 202067  Lebanon  Health-care providers  Cross-sectional study  SIP  Other non-validated  no 
Ross 201868  United States  Health-care providers  Cross-sectional study  SIP  Other non-validated  no 
Lobo 201369  India  General population  Cross-sectional study  PAS, Gen, GHL  Other non-validated  no 
Buchbinder 200770  Australia  Health-care providers  Cross-sectional study  SIP  Other non-validated  no 
Ulaska 200171  Finland  General population  Case control study  LB, PAS, PP, EE  Other non-validated  no 
Foster 200831  UK  Clinical  Cohort study  MP, GHL, Unk, Oth  IPQ-revised  Longitudinal: disability, global rating 
Glattacker 201232  Germany  Clinical  Non-randomised experimental study  Gen, MP, Unk, Oth  IPQ-revised  no 
Li 202072  China  General population  Cross-sectional study  PAS, SIP, GHL, Spi  Other non-validated  no 
Roussel 201673  Belgium  Clinical  Cross-sectional study  PAS, LMPC, OWD, PP, SIP, TM, Gen, MP, GHL, EE, Unk, Oth  IPQ-revised  no 
Werner 200874  Norway  Health-care providers  Non-randomised experimental study  SIP  Deyo's back pain myths  Longitudinal: work in campaign area or in control area 
Houben 200575  The Netherlands  Health-care providers  Cross-sectional study  SIP, MP, Unk  PABS-PT (31 items)  no 
Ostelo 200376  The Netherlands  Health-care providers  Cross-sectional study  LMPC, SIP, MP, Unk  PABS-PT in its development form  no 
Lefevre-Colau 200977  France  Clinical  Cross-sectional study  OWD, PP, TM,  Other non-validated  no 
Osborne 201378  Ireland  General population  Cross-sectional study  LB, LMPC, PWD, TM, Unk  Other non-validated  no 
Igumbor 200379  Zimbabwe  Health-care providers  Cross-sectional study  LB, LMPC, PWD, OWD  Other non-validated  no 
Shaheed 201580  Australia  Health-care providers  Non-randomised experimental study  SIP  Pharmacists Back Beliefs Questionnaire  no 
Shaheed 201781  Australia  Health-care students  Non-randomised experimental study  SIP  Modified Back beliefs questionnaire  no 
Johnsen 201882  Norway  General population  Randomised controlled trial  LB, SIP  Deyo's back pain myths  no 
Odeen 201383  Norway  General population  Randomised controlled trial  LB  Deyo's back pain myths  no 
Buchbinder 200984  Australia  Health-care providers  Cross-sectional study  SIP  Other non-validated  Cross-sectional: special interest in LBP 
McCabe 201985  Ireland  Health-care students  Cross-sectional study  LB, SIP  Deyo's back pain myths  Cross-sectional: LBP teaching in medical school 
Wilgen 201386  The Netherlands  General population  Cross-sectional study  LB, PAS, OWD, PP, SIP, TM, Gen, MP, GHL, EE  IPQ-revised; Other: converted to IPQ R back pain  no 
Munigangaiah 201625  Ireland  General population  Cross-sectional study  LB, SIP  Deyo's back pain myths  Cross-sectional: sex, education, age 
Coggon 201287  18 different countries: Brazil, Ecuador, Colombia, Costa Rica, Nicaragua, UK, Spain, Italy, Greece, Estonia, Lebanon, Iran, Pakistan, Sri Lanka, Japan, South Africa, Australia, New Zealand  General population  Cohort study  OWD  Other non-validated  no 
Darlow 201488  New Zealand  General population  Cross-sectional study  SIP  Back-PAQ-34  no 
Campbell 201318  UK  Clinical  Cross-sectional study  MP, GHL, Unk, Oth  IPQ-revised  Cross-sectional: pain, disability 
Steffens 201489  Australia  Health-care providers  Cross-sectional study  LB, PAS, LMPC, PP, SIP, TM, Gen, MP, GHL  Other non-validated  no 
Kent 200590  Australia  Health-care providers  Cross-sectional study  PP, SIP    no 
Wolter 201191  Germany  Clinical  Cross-sectional study  LMPC, TM, Gen, MP, GHL, Unk, Oth  Based on the German Pain Questionnaire  no 
Christe 202140  Switzerland  Health-care students  Cohort study  SIP  Back-PAQ-34  no 
Campbell 200492  UK  Clinical  Cross-sectional study  LB, PAS, PP, SIP, TM, Gen, MP, GHL, Oth  Other non-validated  no 
SilvaParreira 201537  Australia  Clinical  Cross-sectional study  LB, PAS, LMPC, PP, TM, GHL, EE, Oth  Other non-validated  Cross-sectional: developing acute LBP 
Igwesi-Chidobe 201726  Nigeria  Clinical  Cross-sectional study  SIP, Gen, GHL, Spi  IPQ-brief  Cross-sectional: disability 
Pierobon 202028  Argentina  General population  Cross-sectional study  SIP  Back-PAQ-34  Cross-sectional: having seen a health care professional 
Pagare 201593  India  General population  Cross-sectional study  LB, SIP  Deyo's back pain myths  no 
Byrns 200233  United States  General population  Cross-sectional study  OWD, Spi, Oth  Other non-validated  Cross-sectional: LBP 
Linton 199338  Sweden  General population  Cross-sectional study  LB, PWD, OWD, PP, MP  Other non-validated  Cross-sectional: job type, upper management, lower management, blue collar 
Pincus 200794  UK  Health-care providers  Cross-sectional study  SIP, MP  ABS-MP  no 
Leysen 202095  Belgium and the Netherlands  Health-care students  Cross-sectional study  SIP, MP, Unk  PABS-PT (19-items)  no 
Bar-Zaccay 201896  UK  Health-care providers  Cross-sectional study  SIP, MP  PABS-PT (19-items)  no 
Ihlebæk 200397  Norway  General population  Cross-sectional study  LB, SIP  Deyo's back pain myths  Cross sectional: living in rural/urban area, age, education 
Grimshaw 201198  UK  Health-care providers  Cohort study  OWD, MP, GHL, EE, Unk, Oth  Other non-validated  Cross-sectional: use of radiographs 

ABS-MP, Attitudes to Back Pain Scale in Musculoskeletal Practitioners; Back-PAQ, Back Pain Attitudes Questionnaire; EE, External environment; FABQ, Fear Avoidance Belief Questionnaire; Gen, Genetic; GHL, General health and lifestyle; IPQ, Illness perception questionnaire; LB, Lifting and bending; LBP, low back pain; LMPC, Loading, movement and physical capacity; MP, Mental/psychological; NPQ, Neurophysiology of pain questionnaire; Oth, Other; OWD, Other work demands; PABS-PT, Pain Attitudes Belief Scale for Physiotherapists; PAS, Physical activity and sports; PP, Posture and position; PWD, Physical word demands; SIP, Structural injury/impairment; Spi, Spiritual; TM, Trauma mechanism; TSK, Tampa Scale of Kinesiophobia; Unk, Unknown.

Questions and questionnaires used to measure causal beliefs regarding non-specific LBP

We identified the following questionnaires from which causal beliefs were obtained: Pain Attitudes and Belief Scale for Physiotherapists (PABS-PT) (7 studies) in which 7 items were deemed to be causal beliefs, Back pain attitudes belief scale (Back-PAQ) (5 studies, 2 items), Illness Perception Questionnaire (IPQ) (8 studies, 1 section), Attitudes to Back Pain Scale in Musculoskeletal Practitioners (ABS-MP) (2 studies, 1 item), Neurophysiology of pain questionnaire (NPQ) (1 study, 5 items), and the Worker Attribution Scale (WAS) (1 study, 1 section). Additionally, questions based on two of “Deyo's myths” regarding low back pain were used in 12 studies. For the remainder of the studies, eight measured causal beliefs using modification or adaptations of other questionnaires and 32 measured causal beliefs by other non-validated questionnaires or items specifically developed for the purpose of the study. Fig. 2 shows the use of the measurements within the investigated populations.

Fig. 2.

The frequency of used questions / questionnaires distributed by population. ABS-MP, Attitudes to Back Pain Scale in Musculoskeletal Practitioners; Back-PAQ, Back pain attitudes belief scale; IPQ, Illness Perception Questionnaire; NPQ, Neurophysiology of pain questionnaire; PABS-PT, Pain Attitudes and Belief Scale for Physiotherapists.

(0.19MB).
Types of causal beliefs and number of studies investigating these

A total of 308 unique causal belief items were identified and categorized into 15 mutually distinct categories. All categories are explained in Table 2, and an in-depth description of items included in each category can be found in Supplemental Material C: Full list of items. The most prevalent investigated category was causal beliefs related to “structural injury or impairment”, which was investigated in 45 (56%) of the studies. The second and third most prevalent categories were related to “lifting and bending“ (26 studies [32%]) and “mental or psychological” (24 studies [30%]) (Fig. 3).

Table 2.

Categories of causal beliefs.

Category  Substance 
Lifting and bending  Beliefs that low back pain (LBP) is caused by lifting, bending, twisting or a combination, and also the item “most back pain is caused by injury or heavy lifting”. 
Physical activity and sports  Beliefs that LBP is caused by exercise, sports, and other types of physical activity. This included either too much or too little exercise. 
Loading, movement, and physical capacity  Beliefs that LBP is caused by repeated, specific, or sudden movements that is not explicitly related to lifting or bending, e.g., “unexpected loads” and “overuse”. 
Physical work demands  Beliefs that LBP is caused by specific job tasks with a focus on the physical aspect, e.g., ”transferring patients” or “physical workloads”. 
Other work demands  Beliefs that LBP is caused by non-physical (or not solely physical) work demands for instance “heavy mental workload” or “a poor working environment”. 
Posture and position  Beliefs that LBP is caused by posture for instance “poor posture”. Also driving, sitting, and standing were included in this category. 
Structural injury or impairment  Beliefs that LBP is always caused by a structural injury or that radiographs can identify the cause of LBP. Items such as “muscle strain” and “disc problem” were included in this category. 
Trauma mechanism  Beliefs that LBP is caused by trauma, sport injury, or fall. 
Genetic  Belief that LBP is caused by genetic factors, heredity, or related to sex. 
Mental or psychological  Beliefs that LBP is caused by mental stress or other psychological factors. 
General health and lifestyle  Beliefs that LBP is caused by a non-musculoskeletal health condition such as diabetes or pregnancy, or by lifestyle factors such as smoking and nutrition. 
External environment  Beliefs that LBP is caused by something external, this could be weather conditions, familial problems, social factors (other than work related), shoes, or mattresses. 
Spiritual  Beliefs that LBP is caused by fate, energy status, or the imbalance of the five elements. 
Unknown  Beliefs that the cause of LBP is unknown or that the respondents did not know the cause of their LBP 
Other  This category contained 15 items that could not be allocated to any other category such as previous LBP episodes, behavioral factors, and fatigue. 
Fig. 3.

The frequency of studies investigating each category of causal beliefs distributed by population.

(0.26MB).

Among the frequently used questionnaires, PABS-PT contained items from the categories “structural injury or impairment”, “mental or psychological”, and “unknown”. Back-PAQ contained only items from “structural injury or impairment”. The questions based on Deyo's myth contained items from “structural injury or impairment”, “lifting and bending”, and “unknown”. IPQ had, due to its free text option, the capability to contain all the categories of causal beliefs created for this review.

Outcomes investigated for an association with causal beliefs

Twenty-eight studies investigated an association between causal beliefs and other factors. Twelve studies (43%) were conducted in the general population, 6 (21%) in clinical populations, 6 (21%) among health-care providers, 2 (7%) in mixed populations, and 2 (7%) among health-care students. Cross-sectional associations were reported in 22 studies (Table 1). The most common cross-sectional associations investigated were with pain,17-21 sex,22-25 disability,17,18,26 and care seeking.20,27,28 Longitudinal associations were investigated in 8 studies. The longitudinal association most commonly investigated was reporting LBP29,30 (Table 1).

Discussion

This scoping review investigated how causal beliefs regarding non-specific LBP have been quantitatively investigated in peer reviewed scientific literature. Eighty-one studies were included accounting for 308 unique causal belief items categorized into 15 categories. Causal beliefs were most often investigated in high-income countries and most often in the general population followed by populations of health-care providers and clinical populations. The most frequent causal beliefs investigated related to structural injury or impairment, lifting and bending, and mental or psychological factors. We identified the use of 6 questionnaires from which a measure of causal beliefs could be obtained. Most of the included studies used cross-sectional designs, and 28 investigated an association between causal beliefs and other factors. Only 8 studies investigated a longitudinal relationship.

Among the questionnaires identified, only the IPQ, PBQ, and WAS were developed with the purpose of specifically measuring causal beliefs.11,13,33,34 However, in our review we did not find any study that reported results related to the causal belief items of the PBQ in isolation, and thus no studies using the PBQ were included. The PBQ consists of two subscales differentiating between organic and psychological beliefs, however these scales include both causal beliefs and consequence beliefs and therefore did not meet our criteria for separate information on causal beliefs.11 The PABS-PT and Back-PAQ were not developed to specifically measure causal beliefs.12,35 Yet we deemed both to have items measuring causal beliefs, and several studies using either PABS-PT or Back-PAQ were included in our review.

Although 81 studies were included, only 15 had an aim that specifically mentioned cause, triggers, or etiology. This indicates a lack of studies that are designed to investigate causal beliefs. Additionally, only 8 studies investigating longitudinal associations with causal beliefs were included in our review. In contrast, a 2019 Cochrane review of recovery expectations (Timeline beliefs) in people with LBP included 52 longitudinal studies for a narrative synthesis.36 Thus, it seems that expectations beliefs have been more thoroughly investigated than causal beliefs.

Causal beliefs appear to be essential for the construct of illness beliefs.1,4,5,7,9 However, to determine the clinical contribution of causal beliefs it is necessary that they are measured and reported in consistent ways. This would help quantify a proposed behavior reaction based on causal beliefs. The findings of this study illustrates that this can be challenging with the current existing evidence due to the large variation in the measure of causal beliefs. The variation additionally implies that causal beliefs are complex and often interacts with other types of beliefs to make up an illness representation.

Strengths and limitations

The review followed a stringent method and was reported in accordance with current guidelines to ensure high transparency with the choices made in the process. A main concern was that it is not clear cut what constitutes a causal belief, and we consider it a strength that our definition of causal beliefs was based on the common-sense model and the question “what caused my LBP” or “what causes LBP”. However, in the review process we realized that beliefs related to triggers of back pain and contributing factors relate to this domain and thus were eligible for inclusion. For instance, the question “what do you believe may have triggered your LBP?37 and also questions where participants rated how important they believed different items were in causing back pain, were both deemed to be a measure of causal beliefs.38 As these types of beliefs were discovered in the review process, specific search terms for these were not included in our search strategy. We acknowledge that relevant studies may have been missed on this account, but do not consider this a major flaw because we used a broad search strategy and screened a large number of studies.

We were strict on not including aggravating factors as causal beliefs. However, aggravating factors overlap with causal beliefs. For instance, the item from Back-PAQ “Stress in your life (financial, work, relationship) can make back pain worse” was deemed as measuring aggravating factors and not as a causal belief. This distinction may have favored biomedical beliefs and specific structural causes of LBP while items reflecting psychosocial causes may more often be presented as aggravating factors than as an initial cause. It can be argued that a focus on “contributing factors” to LBP would have been more inclusive but would also make the differentiation from other belief domains less clear. The overlap between domains made the isolation of causal beliefs challenging in some studies. Additionally, many studies had a vague description of methodology and how they measured beliefs. Thus, some subjective interpretation was inevitable.

We did not look for gray literature as we decided to limit the scoping review to peer reviewed literature. Thus, additional knowledge regarding measuring of causal beliefs may exist. However, we have no reasons to believe this would change the general findings of this review.

Conclusion

We wanted to explore how causal beliefs regarding LBP have been quantitatively investigated and settle whether there is available evidence to quantify the impact of causal beliefs on outcomes for LBP that has been observed in qualitative studies. Based on the current evidence this is not feasible due to the large variation in measuring causal beliefs and the lack of studies designed to investigate causal beliefs and of studies determining a longitudinal association between such beliefs and patient outcomes. One belief domain does not exist in isolation from others. However, to understand unique contributions of causal beliefs it would be necessary to develop new measurement tools. This scoping review identified an evidence gap and can inspire future research in this field including search strategies and development of relevant questions and questionnaires.

Acknowledgements

This study was funded by the Danish Foundation for Chiropractic Research and Post Graduate Education (grant number: A2528). The funders had no role in designing or conducting the study.

Appendix
Supplementary materials

Supplemental Material

Supplemental material A: Search strategy

Supplemental material B: Consensus chart for causal belief items

Supplemental material C: Full list of items forming the categories of beliefs

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