Evidence map›Paper›PMID 32641009›Full record

ArticleBMC psychiatry2020

An enhanced individual placement and support (IPS) intervention based on the Model of Human Occupation (MOHO); a prospective cohort study.

Susan Prior, Donald Maciver, Randi W Aas, Bonnie Kirsh, Annika Lexen, Lana van Niekerk, Linda Irvine Fitzpatrick, Kirsty Forsyth

Registry-linked trialAbstract read
In one paragraph

Article in BMC psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04083404 (Investigating Psychosocial Predictors & Employment Outcomes of Enhanced IPS Intervention A Prospective Cohort Study), which is not on this map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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.

NCT04083404 completednot on this map

Investigating Psychosocial Predictors & Employment Outcomes of Enhanced IPS Intervention A Prospective Cohort Study

Typeobservational_patient_registrySponsorQueen Margaret UniversityRan2015 to 2018Enrolled202ConditionsPsychiatric Disorder
3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Assessing Continued Employability among People with Mental Illnesses: Development of a Scale in Japan.International journal of environmental research and public health · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Article
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

8 authors.

Susan PriorQueen Margaret University, Edinburgh, EH21 6UU, UK. sprior@qmu.ac.uk.ORCID 0000-0003-3069-6961
Donald MaciverQueen Margaret University, Edinburgh, EH21 6UU, UK.ORCID 0000-0002-6173-429X
Randi W AasFaculty of Health Sciences, University of Stavanger & Oslo Metropolitan University, Oslo, Norway.ORCID 0000-0003-4391-6142
Bonnie KirshDepartment of Occupational Science and Occupational Therapy, University of Toronto, Toronto, Canada.ORCID 0000-0002-3266-6742
Annika LexenDepartment of Health Sciences/Mental Health Activity and Participation (MAP), Lund University, Lund, Sweden.ORCID 0000-0002-9776-9304
Lana van NiekerkDivision of Occupational Therapy, University Stellenbosch, Stellenbosch, South Africa.ORCID 0000-0003-0003-6006
Linda Irvine FitzpatrickMental Health and Wellbeing, City of Edinburgh Health and Social Care Partnership, Waverley Court, Edinburgh, EH8 8BG, UK.
Kirsty ForsythQueen Margaret University, Edinburgh, EH21 6UU, UK.ORCID 0000-0002-6732-1699

Funding

Scottish Government n/a
6 · The paper itself

Abstract

backgroundEmployment is good for physical and mental health, however people with severe mental illness (SMI) are often excluded from employment. Standard Individual Placement and Support (IPS) is effective in supporting around 55% of people with SMI into employment or education. Current research considers enhancements to IPS to improve outcomes for those requiring more complex interventions. Clinicians need to better understand who will benefit from these enhanced IPS interventions. This study offers a new enhanced IPS intervention and an approach to predicting who may achieve successful outcomes.

methodsThis prospective cohort study included people with SMI who participated in an enhanced IPS service and had prolonged absence from employment. Secondary data analysis was conducted of data gathered in routine clinical practice. Univariate analysis coupled with previous research and clinical consultation was used to select variables to be included in the initial model, followed by a backward stepwise approach to model building for the final multiple logistic regression model with an outcome of successful or unsuccessful goal attainment (employment or education).

resultsSixty-three percent of participants in the enhanced IPS successfully attained employment or education. Significant relationships from bivariate analyses were identified between outcomes (employment or education) and seven psychosocial variables. Adapting Routines to Minimise Difficulties, Work Related Goals, and Living in an Area of Lesser Deprivation were found to be significant in predicting employment or education in the final multiple logistic regression model R

conclusionAn enhanced IPS service had a 63% rate success in achieving employment or education, higher than comparable studies and provides an alternative to IPS-Lite and IPS-standard for more complex populations. Motivational and habitual psychosocial variables are helpful in predicting who may benefit from an enhanced IPS intervention supporting people after prolonged absence from employment.

trial registrationNCT04083404 Registered 05 September 2019 (retrospectively registered).

Indexed as

Employment, SupportedMental DisordersHumansOccupationsProspective StudiesRehabilitation, VocationalEmploymentEnhanced Individual Placement & SupportModel of human occupationSevere mental illness

Identifiers

PMID32641009
PMCPMC7346406

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Registered trials

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.