Evidence map›Paper›PMID 32183758›Full record

ArticleBMC public health2020

Evidence, theory and context: using intervention mapping in the development of a community-based self-management program for chronic low back pain in a rural African primary care setting - the good back program.

Chinonso N Igwesi-Chidobe, Sheila Kitchen, Isaac O Sorinola, Emma L Godfrey

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 25 citations in OpenAlex.

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  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Chinonso N Igwesi-ChidobeDepartment of Medical Rehabilitation, Faculty of Health Sciences and Technology, College of Medicine, University of Nigeria (Enugu Campus), Nsukka, Nigeria. chinonso.chidobe@unn.edu.ng.ORCID http://orcid.org/0000-0001-8021-0283
Sheila KitchenDepartment of Physiotherapy, Faculty of Life Sciences and Medicine, School of Population Health Sciences, King's College London, London, SE1 1UL, UK.
Isaac O SorinolaDepartment of Physiotherapy, Faculty of Life Sciences and Medicine, School of Population Health Sciences, King's College London, London, SE1 1UL, UK.
Emma L GodfreyDepartment of Physiotherapy, Faculty of Life Sciences and Medicine, School of Population Health Sciences, King's College London, London, SE1 1UL, UK.
King's College London · GBUniversity of Nigeria · NG

Funding

Schlumberger Foundation 0000University Of Nigeria Nsukka 0000
6 · The paper itself

Abstract

backgroundRural Nigeria has one of the greatest burdens of low back pain but there are no effective evidence-based interventions to manage it in this population. This paper presents the application of the intervention mapping (IM) approach in the development of a complex behavior change intervention - The Good Back program, aimed at reducing non-specific chronic low back pain (CLBP) disability in rural Nigeria.

methodsThe first four steps of IM were applied. A critical review of the literature, 2 qualitative studies and a population-based cross-sectional study in rural Nigeria helped to identify two key program objectives in order to reduce CLBP disability in this population: reduce the impact of illness perceptions, fear avoidance beliefs, catastrophising, anxiety and depression by targeting maladaptive illness perceptions about CLBP; and facilitate the adoption of exercises and good posture to limit disability. A systematic review plus these studies, identified the personal and environmental determinants of the performance objectives including health literacy, self-awareness, self-efficacy, personal preference, health professional skills, health facility structure and family/community support. The theory, techniques and strategies for modifying personal and environmental determinants were also identified from these studies. Intervention components and materials were then produced for practical application. The initial developed intervention was described.

resultsThe feasibility and acceptability of the developed program was then tested using a small pragmatic non-randomised controlled study incorporating qualitative exit feedback interviews in a rural Nigerian primary health care centre. The program appeared feasible and acceptable when delivered by a highly trained physiotherapist. There were promising clinical outcomes in disability, pain intensity, illness perceptions, fear avoidance beliefs and pain medication use. Suggestions for program improvement included shorter but ongoing sessions, video demonstration of exercises/good posture, spacious exercise/demonstration rooms, and community legitimisation of exercise as treatment for back pain. Subsequent modifications to program content and delivery were then described. Theoretical modification included the addition of aspects of the social cognitive theory to the Leventhal's self-regulatory model of illness cognitions.

conclusionsIM appears to be a suitable framework for designing complex behavior change interventions in rural Nigeria. The need for further testing of the intervention was highlighted.

Indexed as

AdultBehavior TherapyCross-Sectional StudiesFemaleHumansLow Back PainMaleMiddle AgedNigeriaPrimary Health CareProgram DevelopmentQualitative ResearchResearch DesignRural PopulationSelf-ManagementBehavior change interventionChronic low back painComplex interventionsRural AfricaSelf-management programThe Good Back Program, Intervention Mapping

Identifiers

PMID32183758
PMCPMC7077009
OpenAlexW3011938940

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.