Table 1

Search results: 13 papers evaluating the fit note

StudyPaperYear of data collectionRecruitment and samplingData collectionFunderStudy design and methodDemographic variationFNsStudy populationOutcomes§
GPs and FFWEmployer1234
1 Chenery 25 January to June 2012Adults selected from the Labour Force Survey (LFS). The Fit Note Survey was attached to the last of five LFS interviews.Survey—computer assisted telephone interviewsDepartment for Work and PensionsCross-sectional
Logistic regression
Age, gender, SES, health condition, size of organisation, sector worked in, self-report health, disability status, health condition1398 employeesYY
et al 26
June 2011 to December 2011Selected from a service evaluationFit note commentsNational Institute for Health ResearchCross-sectional
Content analysis
12121 practice (712 FNs)
(500 FNs)
et al 27
4 years before (April 2006 to March 2010) and 3 years (July 2010 to June 2013)Selected all available data from the THOR-GP surveillance schemeInformation reported by GPs with training in occupational health to diploma level†UK Health and Safety Executive (THOR contract number: HSE JN4243)Longitudinal
Multilevel random effects Poisson regression model fitted to the monthly data count
Type of health condition5517 patients (835 patients since introduction of the fit note)250 GPsYY
4 Coole
et al 29
November 2013 to May 2014A total of 272 GP practices were invited to participate in the study.Data from fit note copies and questionnairesInstitute of Occupational Safety and HealthCross-sectional
Quantitative data were analysed descriptively. Free-text comments using thematic content analysis
Type of health condition9411 GPsYY
et al 28
Study 4+5 combinedStudy 4+5 combinedStudy 4+5 combined94+49813 employer
et al 30
May 2013 to March 2014A combination of opportunistic and random samplingPostal questionnaires498YYY
6 Shiels
et al 31
+ October 2011 to January 2013
Practices were invited to take part from 5 areas of UK.
The second project involved additional data from an evaluation of 19 practices sited in 3 FFWS pilot sites.
Carbonised fit note padsDepartment for Work and PensionsLongitudinal
Logistic regression: multilevel mixed effects model
Patient (age, gender, type of health condition, social deprivation), GP (sex age partner/locum status, full time/part time)
GP practice (size, location, GP deprivation)
58 70025 000
49 practicesYYY
et al 32
Late 2011 to
January 2013
Longitudinal and cross-sectional
Multivariate logistic regression models
79 81533 76868 practices including 3 FFWS pilot sites
et al 33
+ late 2011 to January 2013
25 06110 984YY
et al 34
et al 35
Late 2011 to January 201338 934 episodes31 453Y
et al 36
Late 2011 to January 201381273361YY
7 Digital
NHS 37
December 2014 to March 2017207 CCGs across the UK, 70 had more than 95% coverage, 25 had less than 5%.NHS electronic fit note dataNHS DigitalDescriptive analysisType of health condition, location5 603 986*YYY
  • Bold denotes grey literature.

  • *62.1% of all fit notes prescribed in England during this period to people aged 18–65.

  • †Patients with CMD.

  • ‡Patients with depression only.

  • §Outcome 1: maybe fit for work outcome. Outcome 2: work solutions. Outcome 3: return to work outcomes. Outcome 4: length of sickness absence.

  • CMD, common mental disorder; FFWS, Fit For Work scheme; FN, fit note; GP, general practitioner; NHS, National Health Service; SES, socioeconomic status; THOR, The Health and Occupational Research Network; CCG, clinical commisioning groups.