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M. Rivano Fischer et al.
quently repeated observations, following each person,
allows for some conclusions to be drawn regarding the
changes observed.
One way to make comparisons between time periods
is to find appropriate control subjects or a reference
group (not subjected to the studied intervention) (9).
However, there are problems inherent in the identifi-
cation of adequate controls, the main one being the
assumption that patients referred to MMR or other
treatments are alike. Referral sources, usually physici-
ans, make judgements before deciding whether to send
patients to pain rehabilitation, judgement weighting
several aspects. Therefore, important variables that
should be controlled for in any matching procedure,
such as functioning, activity levels, and motivation
for change, cannot be controlled for by matching the
usual variables, diagnoses, age and sex. Furthermore,
patients with pain who are not referred to a specific
rehabilitation may seek healthcare in other places,
which may often not have been controlled for. A study
reported by Post Sennehed found ”limited feasibility
in identifying 2 comparable groups for evaluation of
the multimodal rehabilitation programme” (30). Our
study, therefore, approached the problem by using a
large sample and repeated measures over an extended
period of time, in order to obtain answers as to whether
MMR has an impact on sick-leave benefits.
Future research
The possibility of linking SQRP data to the SSIA data-
base opens up several avenues for future research. One
such area is that of identifying subgroups of patients
participating in MMR in relation to changes in their
patterns of sick leave. Other areas refer to possible as-
sociations between patterns of physical, psychological
or activity-related limitations reported by patients and
patterns of sick leave, the prediction value that patients’
self-descriptions might have on patterns of sick leave,
and how work conditions interact with outcomes of
MMR at long-term follow-up after interventions.
Conclusion
Since the extent of sick-leave benefits seems to increase
during the year prior to participating in MMR and de-
crease during 2 years after rehabilitation, the results of
this study highlight the importance of offering MMR to
patients with chronic pain. The results, based on data
from 2 large national databases, indicate that MMR
has an impact on sick-leave benefits regardless of sex
or policy changes in the sick-leave benefit system.
The authors have no conflicts of interest to declare.
www.medicaljournals.se/jrm
REFERENCES
1. Breivik H, Collett B, Ventafridda V, Cohen R, Gallacher D.
Survey of chronic pain in Europe: prevalence, impact on
daily life, and treatment. Eur J Pain 2006; 10: 287–333.
2. Lidwall U. Sick leave diagnoses and return to work: a Swe-
dish register study. Disabil Rehabil 2015; 37: 396–410.
3. Anema JR, Schellart AJ, Cassidy JD, Loisel P, Veerman TJ,
van der Beek AJ. Can cross country differences in return-
to-work after chronic occupational back pain be explai-
ned? An exploratory analysis on disability policies in a six
country cohort study. J Occup Rehabil 2009; 19: 419–426.
4. Karlsson NE, Varstensen JM, Gjesdal S, Alexanderson KA.
Risk factors for disability pension in a population-based
cohort of men and women on long-term sick leave in
Sweden. Eur J Public Health 2008; 18: 224–231.
5. SBU. [The Swedish Council on Health Technology As-
sessment in Health Care, (SBU), Rehabilitation in chronic
pain – a systematic review.] SBU report Vol. no 198,
2010. Stockholm: Swedish National Board of Health and
Welfare (in Swedish).
6. Jensen IB, Bergström G, Ljungqvist T, Bodin L. A 3-year
follow-up of a multidisciplinary rehabilitation programme
for back and neck pain. Pain 2005; 115: 273–283.
7. Norlund A, Ropponen A, Alexanderson K. Multidisciplinary
interventions: review of studies of return to work after
rehabilitation for low back pain. J Rehabil Med 2009; 41:
115–121.
8. Merrick D, Sundelin G, Stålnacke BM. An observational
study of two rehabilitation strategies for patients with
chronic pain, focusing on sick leave at one-year follow-up.
J Rehabil Med 2013; 45: 1049–1057.
9. Norrefalk JR, Ekholm K, Linder J, Borg K, Ekholm J. Evalua-
tion of a multiprofessional rehabilitation programme for
persistent musculoskeletal-related pain: economic benefits
of return to work. J Rehabil Med 2008; 40: 15–22.
10. Meijer EM, Frings-Dresen MH, Sluiter JK. Effects of office
innovation on office workers’ health and performance.
Ergonomics 2009; 52: 1027–1038.
11. Meijer EM, Sluiter JK, Heyma A, Sadiraj K, Frings-Dresen
MH. Cost-effectiveness of multidisciplinary treatment in
sick-listed patients with upper extremity musculoskeletal
disorders: a randomized, controlled trial with one-year fol-
low-up. Int Arch Occup Environ Health 2006; 79: 654–664.
12. Linton SJ, Boersma K, Jansson M, Svärd L, Botvalde M.
The effects of cognitive-behavioral and physical therapy
preventive interventions on pain-related sick leave: a
randomized controlled trial. Clin J Pain 2005; 21: 109–119.
13. Nyberg V, Sanne H, Sjölund BH. Swedish quality registry
for pain rehabilitation: purpose, design, implementation
and characteristics of referred patients. J Rehabil Med
2011; 43: 50–57.
14. Dworkin RH, Turk DC, Farrar JT, Haythornthwaite JA,
Jensen MP, Katz NP, et al. Core outcome measures for
chronic pain clinical trials: IMMPACT recommendations.
Pain 2005; 113: 9–19.
15. SBU. [The Swedish Council on Health Technology Assess-
ment in Health Care, (SBU), Methods of treating chronic
pain]. SBU report Vol. no 177/1-2 2006.] Stockholm: Swe-
dish National Board of Health and Welfare. (in Swedish).
16. WHO, World Health Organization. International Classifi-
cation of Functioning, Disability and Health (ICF). 2001,
Geneva: WHO.
17. Zigmond AS, Snaith RP. The hospital anxiety and depres-
sion scale. Acta Psychiatr Scand 1983; 67: 361–370.
18. Lisspers J, Nygren A, Söderman E. Hospital Anxiety and
Depression Scale (HAD): some psychometric data for a
Swedish sample. Acta Psychiatr Scand 1997; 96: 281–286.
19. Kerns RD, Turk DC, Rudy TE. The West Haven-Yale Mul-
tidimensional Pain Inventory (WHYMPI). Pain 1985; 23:
345–356.