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Sense of Coherence, Disability, and Health-Related Quality of Life: A Cross-Sectional Study of Rehabilitation Patients in Norway

Open AccessPublished:July 03, 2018DOI:https://doi.org/10.1016/j.apmr.2018.06.009

      Abstract

      Objective

      To study relations between sense of coherence (SOC), disability, and mental and physical components of health-related quality of life (HRQOL) among rehabilitation patients.

      Design

      Survey.

      Setting

      Rehabilitation centers in secondary care.

      Participants

      Patients (N=975) from the Western Norway Health Region consented to participate and had valid data of the main outcome measures.

      Interventions

      Not applicable.

      Main Outcome Measures

      SOC was measured with the sense of coherence questionnaire (13-item SOC scale [SOC-13]), disability with the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), and HRQOL with the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36).

      Results

      Mean scores ± SD were 62.9±12.3 for SOC-13, 30.8±16.2 for WHODAS 2.0, 32.8±9.6 for SF-36 physical component score, and 43.6±11.8 for SF-36 mental component score. Linear regression analysis showed that increased SOC score was associated with reduced disability scores in the following domains with estimated regression coefficients (95% confidence interval) cognition –0.20 (–0.32 to –0.08), getting along –0.36 (–0.52 to –0.25), and participation –0.23 (–0.36 to –0.11). The fit of 2 structural models with the association from SOC to HRQOL and disability or with disability as a mediator was better for the mental versus the physical component of HRQOL. High SOC increased the mental component of HRQOL, consistent for all diagnostic groups. For both models, good fit was reported for circulatory and less good fit for musculoskeletal diseases.

      Conclusions

      The results indicate that higher SOC decreases disability in mental domains. The effect of SOC on disability and HRQOL might vary between diagnostic groups. SOC could be a target in rehabilitation, especially among patients with circulatory diseases, but prospective studies are needed.

      Keywords

      List of abbreviations:

      95% CI (95% confidence interval), HADS (Hospital Anxiety and Depression Scale), HRQOL (health-related quality of life), MCS (mental component score), PCS (physical component score), SEM (structural equational modeling), SF-36 (Medical Outcomes Study 36-Item Short-Form Health Survey), SOC (sense of coherence), SOC-13 (13-item SOC), WHODAS 2.0 (World Health Organization Disability Assessment Schedule 2.0)
      Rehabilitation aims to maintain or increase functional status and health-related quality of life (HRQOL).
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      • Di Stasio E.
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      Effects of rehabilitation on quality of life in patients with chronic stroke.
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      Multidisciplinary rehabilitation versus usual care for chronic low back pain in the community: effects on quality of life.
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      Cardiac rehabilitation and quality of life: a systematic review.
      Rehabilitation patients usually have chronic conditions with sensory, cognitive, and mobility impairments, and experience activity limitations as well as participation restrictions. HRQOL is poorer in rehabilitation patients compared with a healthy reference population.
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      Health-related quality of life in a Dutch rehabilitation population: reference values and the effect of physical activity.
      Aron Antonovsky developed a salutogenic model to explain why some people remain healthy, or even improve their health, when experiencing life events (stressors) whereas others become ill.
      • Antonovsky A.
      Health, stress, and coping.
      A key concept in Antonovsky’s model is sense of coherence (SOC), a measure of an individual’s capacity to cope. SOC captures an individual’s perception of life as being comprehensible, manageable, and meaningful.
      • Antonovsky A.
      Health, stress, and coping.
      Strong SOC indicates adaptive strategies when responding to stressors
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      • Lae L.
      Sense of coherence, well-being, coping and personality factors: further evaluation of the sense of coherence scale.
      and results in better health, reduced risk of mortality, and lower distress in depression, anxiety, and pain.
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      • Lehmann S.
      • et al.
      Association of the sense of coherence with physical and psychosocial health in the rehabilitation of osteoarthritis of the hip and knee: a prospective cohort study.
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      • Kroenke K.
      • Outcalt S.
      • et al.
      Association between sense of coherence and health-related quality of life among primary care patients with chronic musculoskeletal pain.
      • Eriksson M.
      • Lindstrom B.
      Antonovsky’s sense of coherence scale and the relation with health: a systematic review.
      • Marks D.F.
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      • et al.
      Health psychology: theory, research and practice.
      • Super S.
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      • et al.
      A weak sense of coherence is associated with a higher mortality risk.
      • Surtees P.
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      • Luben R.
      • et al.
      Sense of coherence and mortality in men and women in the EPIC-Norfolk United Kingdom Prospective Cohort Study.
      Therefore, rehabilitation could include goals that strengthen individuals’ SOC.
      • Griffiths C.A.
      Sense of coherence and mental health rehabilitation.
      Better knowledge of SOC and how it affects disability and HRQOL may help to identify subgroups when planning rehabilitation and tailoring interventions.
      • Virues-Ortega J.
      • Vega S.
      • Seijo-Martinez M.
      • et al.
      A protective personal factor against disability and dependence in the elderly: an ordinal regression analysis with nine geographically-defined samples from Spain.
      Previous studies have shown that strong SOC is related to less disability.
      • Virues-Ortega J.
      • Vega S.
      • Seijo-Martinez M.
      • et al.
      A protective personal factor against disability and dependence in the elderly: an ordinal regression analysis with nine geographically-defined samples from Spain.
      • Boeckxstaens P.
      • Vaes B.
      • De Sutter A.
      • et al.
      A high sense of coherence as protection against adverse health outcomes in patients aged 80 years and older.
      • Schnyder U.
      • Buchi S.
      • Morgeli H.
      • et al.
      Sense of coherence—a mediator between disability and handicap?.
      One study reported that SOC was a protective factor for disability.
      • Virues-Ortega J.
      • Vega S.
      • Seijo-Martinez M.
      • et al.
      A protective personal factor against disability and dependence in the elderly: an ordinal regression analysis with nine geographically-defined samples from Spain.
      However, that study only included older adults and used an overall disability score, which may be less relevant in clinical settings than disability domains. To our knowledge, no previous studies have investigated the effect of SOC on disability (as conceptualized in the International Classification of Functioning, Disability and Health
      World Health Organization
      International Classification of Functioning, Disability and Health (ICF).
      ) among rehabilitation patients. Relations between SOC and disability domains such as participation in society have not been assessed.
      Measurement of HRQOL provides an evaluation of health encompassing many important aspects,
      • Karimi M.
      • Brazier J.
      Health, health-related quality of life, and quality of life: what is the difference?.
      among others disability, and may be considered the ultimate outcome for health care.
      • Tengland P.A.
      The goals of health work: quality of life, health and welfare.
      A comprehensive review has shown that better HRQOL is associated with higher SOC in various patient populations.
      • Eriksson M.
      • Lindstrom B.
      Antonovsky’s sense of coherence scale and its relation with quality of life: a systematic review.
      Moreover, a study among adolescents with congenital heart disease showed a predominant direction of this association from SOC to perceived health,
      • Apers S.
      • Luyckx K.
      • Rassart J.
      • et al.
      Sense of coherence is a predictor of perceived health in adolescents with congenital heart disease: a cross-lagged prospective study.
      suggesting further investigation of this relation and its direction in other populations.
      We have not found any studies investigating the direction of the association from SOC to HRQOL and disability simultaneously, whether SOC has a direct relation to HRQOL and disability, or if the direction of the association from SOC to HRQOL is mediated by disability (fig 1).
      Figure thumbnail gr1
      Fig 1Hypothesized structural models, including the results from SEM among 975 patients accepted for specialized somatic rehabilitation in the Western Norway Health Region during the first half of 2015.*Estimated standard regression coefficients with 95% CIs for model including MCS of HRQOL. Estimated standard regression coefficients with 95% confidence intervals for model including PCS of HRQOL.
      Multimorbidity and pain are associated with increased disability and poorer HRQOL
      • Baruth M.
      • Wilcox S.
      • Schoffman D.E.
      • et al.
      Factors associated with disability in a sample of adults with arthritis.
      • Garin N.
      • Olaya B.
      • Moneta M.V.
      • et al.
      Impact of multimorbidity on disability and quality of life in the Spanish older population.
      • Lacey R.J.
      • Belcher J.
      • Rathod T.
      • et al.
      Pain at multiple body sites and health-related quality of life in older adults: results from the North Staffordshire Osteoarthritis Project.
      • Paananen M.
      • Taimela S.
      • Auvinen J.
      • et al.
      Impact of self-reported musculoskeletal pain on health-related quality of life among young adults.
      ; moreover, multimorbidity impairs SOC.
      • Chumbler N.R.
      • Kroenke K.
      • Outcalt S.
      • et al.
      Association between sense of coherence and health-related quality of life among primary care patients with chronic musculoskeletal pain.
      Studies have also shown associations between sociodemographics, psychological distress, and SOC, disability, and HRQOL.
      • Apers S.
      • Luyckx K.
      • Goossens E.
      • et al.
      Socio-demographic and clinical determinants of sense of coherence in adolescents with congenital heart disease.
      • Brenes G.A.
      • Penninx B.W.
      • Judd P.H.
      • et al.
      Anxiety, depression and disability across the lifespan.
      • Kirchberger I.
      • Heier M.
      • Amann U.
      • Kuch B.
      • Thilo C.
      • Meisinger C.
      Variables associated with disability in male and female long-term survivors from acute myocardial infarction. Results from the MONICA/KORA Myocardial Infarction Registry.
      This study aimed to increase the understanding of SOC, disability, and HRQOL in rehabilitation patients. Specific objectives were to (1) describe the simultaneous distribution of SOC, disability, and HRQOL; (2) investigate possible effects of SOC on disability domains; and (3) investigate hypothesized structural models for SOC, disability, and HRQOL. Analyses were also performed specifically for diagnostic groups to enhance clinical significance.

      Methods

      Design, sample, and procedure

      The study used a cross-sectional design. All patients in the Western Norway Health Region accepted for inpatient or outpatient rehabilitation at a rehabilitation center in secondary care during the first half of 2015, and who were referred from hospitals or general practitioners, were invited by mail or at admittance. A flow chart showing participant inclusion and exclusion is shown in fig 2. Further details are provided in a previous paper.
      • Moen V.P.
      • Drageset J.
      • Eide G.E.
      • Gjesdal S.
      Dimensions and predictors of disability—a baseline study of patients entering somatic rehabilitation in secondary care.
      Figure thumbnail gr2
      Fig 2Flowchart of patients accepted for rehabilitation at a rehabilitation center in secondary care in the Western Norway Health Region during the first half of 2015.
      Patient-reported data were linked to individual public register data obtained from Statistics Norway, on educational attainment, residence municipality, and marital status.

      Ethics

      This study was approved by the Regional Committee for Medical Research Ethics in Western Norway, REK-No. 2014-1636. Written informed consent, including linkage to public register data, was obtained from study participants.

      Main variables

      The 36-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) assesses disability across 6 domains
      • Üstün T.B.K.
      • Chatterji S.
      • Rehm J.
      Measuring health and disability: manual for WHO Disability Assessment Schedule (WHODAS 2.0).
      : cognition (6 items), mobility (5 items), self-care (4 items), getting along (5 items), life activities (8 items), and participation (8 items). Four life activities items relate to household and 4 to work or study. Responses are on a 5-point Likert scale with 2 anchor responses (“none” and “extreme or cannot do”). Domain scores and a total disability score are calculated using complex scoring according to the manual, ranging from 0 (no disability) to 100 (full disability). An algorithm enabled calculation of a score for the life activities domain and a total score (regardless of whether the 4 items related to work or study were answered). The instrument has satisfactory reliability and moderate validity for use in rehabilitation services.
      • Moen V.P.
      • Drageset J.
      • Eide G.E.
      • et al.
      Validation of World Health Organization Assessment Schedule 2.0 in specialized somatic rehabilitation services in Norway.
      The Medical Outcomes Study Short-Form Health Survey (SF-36) version 1 assesses HRQOL.
      • Ware J.E.
      • Kosinski M.
      • Dewey J.E.
      • et al.
      SF-36 health survey: manual and interpretation guide.
      The scale contains 36 items in 8 domains: mental health, vitality, bodily pain, general health, social functioning, physical functioning, role limitation related to physical problems, and role limitation related to emotional problems. In addition, 1 item assesses changes in general health over the past year. The 8 domain scores can be summarized to give a mental component score (MCS) and a physical component score (PCS), which were used in this study. Scores range from 0 to 100, with higher scores indicating better HRQOL. The instrument is a valid measure of health status for a range of patients
      • Garratt A.M.
      • Ruta D.A.
      • Abdalla M.I.
      • et al.
      The SF36 health survey questionnaire: an outcome measure suitable for routine use within the NHS?.
      with adequate and high reliability.
      • Ruta D.A.
      • Abdalla M.I.
      • Garratt A.M.
      • et al.
      SF 36 health survey questionnaire: I. Reliability in two patient based studies.
      The 13-item SOC (SOC-13)
      • Antonovsky A.
      Unraveling the mystery of health: how people manage stress and stay well.
      scale comprises items in 3 subscales: comprehensibility, manageability, and meaningfulness. Each item is scored on a 7-point Likert scale with 2 anchor responses (“never” and “very often”). After reversing 5 negatively formulated items, all items are summed to give a total score of 13-91; higher scores indicate stronger SOC. The SOC-13 has generally acceptable reliability and validity.
      • Eriksson M.
      • Lindstrom B.
      Validity of Antonovsky’s sense of coherence scale: a systematic review.
      • Feldt T.
      • Lintula H.
      • Suominen S.
      • et al.
      Structural validity and temporal stability of the 13-item sense of coherence scale: prospective evidence from the population-based HeSSup study.
      • Hansen A.O.
      • Kristensen H.K.
      • Cederlund R.
      • et al.
      Test-retest reliability of Antonovsky’s 13-item sense of coherence scale in patients with hand-related disorders.

      Adjustment variables

      Symptoms of depression and anxiety were assessed using the Hospital Anxiety and Depression Scale (HADS)
      • Zigmond A.S.
      • Snaith R.P.
      The Hospital Anxiety and Depression scale.
      which comprises 14 items on 2 subscales: anxiety and depression. Each subscale has 7 items. Scores range from 0 to 21, higher scores representing higher severity. HADS performs well as a screening instrument in assessing symptom severity in somatic patients
      • Bjelland I.
      • Dahl A.A.
      • Haug T.T.
      • et al.
      The validity of the Hospital Anxiety and Depression scale. An updated literature review.
      and has adequate validity and reliability.
      • Mykletun A.
      • Stordal E.
      • Dahl A.A.
      Hospital Anxiety and Depression (HAD) scale: factor structure, item analyses and internal consistency in a large population.
      Diagnostic groups were categorized based on referral diagnoses (registered according to the International Classification of Diseases-10 chapter without any further details) into musculoskeletal, circulatory, and neurologic diseases, neoplasms, and other (including various health conditions with <50 patients).
      Multimorbidity was defined as the coexistence of more than 1 self-reported chronic conditions in the same individual
      • Mercer S.W.
      • Smith S.M.
      • Wyke S.
      • et al.
      Multimorbidity in primary care: developing the research agenda.
      based on the referral diagnosis and a predefined list of self-reported chronic conditions. The list is reported elsewhere.
      • Moen V.P.
      • Drageset J.
      • Eide G.E.
      • Gjesdal S.
      Dimensions and predictors of disability—a baseline study of patients entering somatic rehabilitation in secondary care.
      Pain or discomfort was measured using the EuroQol 5 dimensions 5 levels.
      • Williams A.
      Euroqol—a new facility for the measurement of health-related quality-of-life.
      This instrument comprises 5 questions and a health rating scale. The questions assess physical activity, psychological distress, and pain or discomfort. Pain or discomfort has 5 possible responses, from no pain or discomfort to extreme pain or discomfort. Measurement properties of the instrument have been tested extensively.
      • Janssen M.F.
      • Pickard A.S.
      • Golicki D.
      • et al.
      Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study.
      Age was categorized by decades. Marital status was dichotomized as married or unmarried. The highest completed education level was categorized as primary school, high school, or college or university. Smoking status was dichotomized as current smoking or not. Residence was dichotomized as rural or urban, with the cutoff being 20,000 inhabitants in the municipality. Rehabilitation was dichotomized as initial (referred by a general practitioner) or ongoing management (referred by a hospital).

      Statistical analysis

      For descriptive statistics, mean and SD are reported. To compare the female proportion and age distribution between participants and nonparticipants, exact chi-square and Mann-Whitney U tests were used.
      Multiple linear regression analysis was used to study the effect of SOC on domain-specific disability. Results are reported as estimated regression coefficients with 95% confidence intervals (95% CI) and P values from the F test. The distribution of residuals was checked for adherence to assumptions of linearity, normality, and variance homogeneity. Analysis of variance was performed using the F test to investigate differences in SOC scores for variables with more than 2 categories. Tukey post hoc test was used for subgroup comparisons.
      Path analysis using structural equational modeling (SEM) was performed for 2 hypothesized models (see fig 1). Satisfactory model fit was defined as a comparative fit index close to 0.95 or higher, Tucker-Lewis index close to 0.95 or higher, a root mean square error of approximation close to <0.06 or lower and cutoff close to 0.08 or lower, and standardized root mean square residual close to 0.08 or lower.
      • Hu L.T.
      • Bentler P.M.
      Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives.
      Regression coefficients were examined for statistical significance. Estimated model parameters are given with 95% CI.
      All analyses were performed for the full sample and separately for diagnostic groups. However, the structural models were estimable only in 3 diagnostic groups because the other groups were too small for valid analysis.
      Multiple imputations for missing items were applied according to the WHODAS 2.0 manual,
      • Üstün T.B.K.
      • Chatterji S.
      • Rehm J.
      Measuring health and disability: manual for WHO Disability Assessment Schedule (WHODAS 2.0).
      with the number of imputation sets=5. If the rate of missing WHODAS 2.0 items was >50%, the data were excluded. Missing items in the SF-36 were managed according to the SF-36 manual.
      • Ware J.E.
      • Kosinski M.
      • Dewey J.E.
      • et al.
      SF-36 health survey: manual and interpretation guide.
      For the HADS and SOC-13, scores for patients with fewer than 3 missing questions per subscale were included. For missing data, scores were imputed based on the mean across each person’s available responses for each subscale. For SEM analysis, listwise deletion was used, and no further imputation or adjustments were applied. The criterion for statistical significance was set at 5%. SPSS version 23a was used for all statistical analyses except SEM where RStudio version 1.0.143b with the lavaan package 0.5-23.1097 was used.

      Results

      In total, 984 of eligible patients provided responses and data of 975 patients were included in the analyses (response rate, 34.6%). The mean age ± SD was 57.6±14.0 years and 63.2% of participants were women. Among nonparticipants the mean age ± SD was 55.6±16.7 years (P<.001) and 67.2% were women (P<.05).
      Main outcome measures could not be calculated for 9 patients. After imputation for missing items, a WHODAS 2.0 overall disability score could be calculated for 967 patients, SF-36 PCS and MCS scores for 885 patients, and SOC scores for 933 patients. For all scales (and variables), missing values for items ranged from 0.4% to 4.2%, except for 1 WHODAS 2.0 item concerning sexual activities (12.8%).
      WHODAS 2.0, SF-36 (PCS and MCS), and SOC-13 scores are shown in table 1. Men had significantly higher SOC scores than women (P<.001), and participants aged ≥50 years had significantly higher SOC scores than those aged <50 years (P≤.01). Participants with circulatory diseases scored significantly higher than those with musculoskeletal diseases (P=.001).
      Table 1Distribution of WHODAS score, SF-36 component scores, and SOC score among 975 patients accepted for specialized somatic rehabilitation in the Western Norway Health Region during the first half of 2015


      Variables

      Categories
      nWomen (%)WHODAS Score
      0=lowest score of disability, 100=highest score of disability.
      (n=967)

      Mean ± SD
      PSF-36
      0=lowest score of HRQOL, physical component, 100=highest score HRQOL, physical component.
      PCS
      0=lowest score of HRQOL, physical component, 100=highest score HRQOL, physical component.
      (n=885)

      Mean ± SD
      PSF-36
      0=lowest score of HRQOL, mental component, 100=highest score HRQOL, mental component.
      MCS
      0=lowest score of HRQOL, mental component, 100=highest score HRQOL, mental component.
      (n=885)

      Mean ± SD
      PSOC
      13=lowest score, 91=highest score (best).
      (n=933)

      Mean ± SD
      P
      All984
      Total included in the study.
      63.430.8±16.2NA32.8±9.6NA43.6±11.8NA62.9±12.3NA
      SexNANANA
      P<.05 (F test).
      NA
      P<.05 (F test).
      NA
      P<.01 (F test).
      NA
      P<.05 (F test).
       Men360027.8±16.6NA35.1±10.3NA45.1±11.5NA65.2±12.0NA
       Women62410032.6±15.6NA31.4±8.9NA42.7±11.9NA61.6±12.3NA
      Age
      Mean ± SD: 57.6±14.0 years.
      (y)
      NANANA
      P<.05 (F test).
      NA
      P<.05 (F test).
      NA
      P<.05 (F test).
      NA
      P<.05 (F test).
       18-292875.033.5±18.6NA37.0±11.6NA39.8±11.9NA53.3±12.5NA
       30-397986.134.0±16.1NA33.0±9.0NA40.7±10.1NA57.7±13.7NA
       40-4918069.436.1±16.5NA32.9±9.1NA39.9±12.3NA58.6±12.1NA
       50-5925260.029.6±14.4NA33.9±9.7NA43.5±12.2NA63.1±12.2NA
       60-6924158.827.6±15.7NA33.6±9.9NA45.3±11.1NA65.4±11.2NA
       70-7915657.929.3±17.0NA30.2±9.3NA47.1±11.3NA66.9±10.4NA
       ≥804858.731.3±16.2NA27.1±7.3NA47.9±9.9NA67.9±11.5NA
      Health condition, ICD-10NANANA
      P<.05 (F test).
      NA
      P<.05 (F test).
      NA
      P<.05 (F test).
      NA
      P<.01 (F test).
       Musculoskeletal diseases45775.934.4±15.0NA29.6±7.3NA42.5±12.1NA61.7±12.6NA
       Circulatory diseases18733.723.2±15.6NA38.9±10.1NA45.8±11.1NA66.1±10.9NA
       Neurologic diseases8755.235.0±16.3NA30.3±8.7NA46.5±10.6NA64.0±11.7NA
       Neoplasms5481.533.3±16.8NA35.1±9.0NA38.9±11.6NA61.6±13.2NA
       Other
      Diseases included the following: endocrine, nutritional, and metabolic diseases (n=36), respiratory diseases (n=37), injuries and external causes (n=27), skin diseases (n=24), factors influencing health status and contact with health services (n=23), mental and behavioral disorders (n=12), symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified (n=9); codes for special purposes (n=7); diseases of the digestive system (n=6); diseases of the blood and blood-forming organs, and certain disorders involving the immune mechanism (n=5); diseases of the ear and the mastoid process (n=3); diseases of the genitourinary system (n=3); congenital malformations, deformations, and chromosomal abnormalities (n=5); and certain infectious and parasitic diseases (n=2).
      19961.327.4±16.0NA34.8±11.0NA44.1±11.7NA62.8±12.3NA
      MultimorbidityNANANA
      P<.05 (F test).
      NA
      P<.05 (F test).
      NA
      P<.01 (F test).
      NA
      P<.05 (F test).
       Yes63565.732.9±16.7NA31.7±9.1NA42.7±12.3NA61.8±12.8NA
       No34959.327.1±14.5NA34.9±10.2NA45.3±10.8NA65.2±11.0NA
      Rehabilitation urgencyNANANA
      P<.001 (F test).
      NA
      P<.01 (F test).
      NANANA
      P<.01 (F test).
       Elective65368.031.9±15.9NA32.3±9.3NA42.8±12.1NA61.6±12.6NA
       Acute27453.627.6±16.3NA34.6±10.2NA45.8±11.1NA66.5±10.7NA
       Unknown5757.934.9±15.6NA29.9±9.8NA43.2±10.9NA61.1±12.2NA
      Marital statusNANANA
      P<.001 (F test).
      NANANA
      P<.05 (F test).
      NA
      P<.05 (F test).
       Unmarried45569.932.3±16.4NA32.6±9.7NA41.4±12.3NA60.9±12.9NA
       Married52557.929.6±15.8NA33.0±9.6NA45.5±11.1NA64.7±11.5NA
       Unknown4NA23.7±16.9NA31.2±10.3NA47.6±6.0NA65.5±11.2NA
      Educational levelNANANA
      P<.001 (F test).
      NA
      P<.01 (F test).
      NANANA
      P<.01 (F test).
       Primary school20568.833.6±17.1NA30.6±9.6NA43.6±11.8NA60.5±12.8NA
       Secondary school49060.230.7±16.1NA32.9±9.9NA43.5±12.5NA63.0±12.2NA
       College/university27866.229.0±15.5NA34.3±10.8NA43.8±10.8NA64.5±11.9NA
       Unknown1166.232.9±14.3NA30.7±9.1NA43.8±7.9NA64.4±12.4NA
      SmokingNANANA
      P<.01 (F test).
      NANANA
      P<.05 (F test).
      NA
      P<.05 (F test).
       Yes18470.734.1±14.6NA31.9±8.6NA39.2±12.3NA58.1±12.6NA
       No78861.430.7±16.4NA33.0±9.9NA44.7±11.5NA64.1±12.0NA
       Unknown1261.429.6±16.0NA36.1±4.9NA41.9±9.5NA62.3±8.7NA
      Living areaNANANANANANANANANANA
       Urban51965.131.3±16.1NA33.0±10.0NA42.9±11.7NA62.9±12.3NA
       Rural46561.530.3±16.2NA32.7±9.3NA44.4±11.9NA63.0±12.3NA
      Abbreviations: ICD-10, International Classification of Diseases-10; NA, not applicable.
      0=lowest score of disability, 100=highest score of disability.
      0=lowest score of HRQOL, physical component, 100=highest score HRQOL, physical component.
      0=lowest score of HRQOL, mental component, 100=highest score HRQOL, mental component.
      § 13=lowest score, 91=highest score (best).
      Total included in the study.
      Mean ± SD: 57.6±14.0 years.
      # Diseases included the following: endocrine, nutritional, and metabolic diseases (n=36), respiratory diseases (n=37), injuries and external causes (n=27), skin diseases (n=24), factors influencing health status and contact with health services (n=23), mental and behavioral disorders (n=12), symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified (n=9); codes for special purposes (n=7); diseases of the digestive system (n=6); diseases of the blood and blood-forming organs, and certain disorders involving the immune mechanism (n=5); diseases of the ear and the mastoid process (n=3); diseases of the genitourinary system (n=3); congenital malformations, deformations, and chromosomal abnormalities (n=5); and certain infectious and parasitic diseases (n=2).
      ∗∗ P<.05 (F test).
      †† P<.01 (F test).
      ‡‡ P<.001 (F test).
      Disability domains with mental components were associated with SOC, with lower disability scores for higher SOC scores (table 2). The estimated regression coefficients (95% CI) of SOC on cognition, getting along, and participation were –0.20 (–0.32 to –0.08), –0.38 (–0.52 to –0.25) and –0.23 (–0.36 to –0.11), respectively. No significant interactions were found, and the reported results were based on analyses with no interaction terms included.
      Table 2Results of a fully adjusted linear regression analysis for predicting WHODAS 2.0 domain scores among 975 patients accepted for specialized somatic rehabilitation in the Western Norway Health Region during the first half of 2015
      Predictor Variable

      Categories
      CognitionMobilitySelf-CareGetting AlongLife ActivitiesParticipation
      B(SE)B(SE)B(SE)B(SE)B(SE)B(SE)
      Intercept8.32(5.67)−5.53(8.03)−8.63(5.96)32.87(6.45)9.02(8.83)23.53(5.91)
      Women (ref: men)0.66(1.22)1.69(1.72)−0.99(1.27)−3.25(1.38)
      P≤.05 (F test).
      7.07(1.89)
      P≤.001 (F test).
      0.87(1.26)
      Age (y)
      P≤.01 (F test).
      P≤.001 (F test).
      P≤.05 (F test).
      P≤.05 (F test).
       18-298.96(3.40)−3.69(4.82)1.93(3.58)−0.65(3.87)−5.15(5.31)−0.76(3.56)
       30-393.17(2.24)−9.39(3.17)−0.33(2.36)−2.11(2.55)2.10(3.50)2.76(2.34)
       40-495.35(1.69)−4.84(2.39)−0.72(1.78)4.96(1.93)4.97(2.63)3.24(1.76)
       50-591.41(1.52)−4.85(2.15)−2.11(1.59)−0.18(1.72)0.99(2.37)0.53(1.58)
       60–690.00(ref)0.00(ref)0.00(ref)0.00(ref)0.00(ref)0.00(ref)
       70-79−0.86(1.80)6.63(2.53)2.34(1.87)−0.93(2.06)−0.31(2.80)−3.16(1.88)
       ≥800.83(3.00)15.00(4.18)2.55(3.11)0.92(3.40)−3.29(4.60)4.30(3.21)
      Health condition
      P≤.01 (F test).
      P≤.001 (F test).
      P≤.05 (F test).
      P≤.05 (F test).
      P≤.001 (F test).
      P≤.05 (F test).
       Musculoskeletal diseases−0.52(1.75)10.23(2.45)0.87(1.81)0.31(1.96)5.85(2.70)2.67(1.82)
       Circulatory diseases0.00(ref)0.00(ref)0.00(ref)0.00(ref)0.00(ref)0.00(ref)
       Neurologic diseases0.26(2.28)17.32(3.22)4.41(2.38)2.41(2.59)10.80(3.58)6.78(2.38)
       Neoplasms7.85(2.73)3.52(3.86)-1.59(2.87)7.74(3.10)12.46(4.26)4.55(2.80)
       Other
      Diseases included the following: endocrine, nutritional, and metabolic diseases (n=37), respiratory diseases (n=36), injuries and external causes (n=26), factors influencing health status and contact with health services (n=23), mental and behavioral disorders (n=13), symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified (n=9); codes for special purposes (n=7); diseases of the digestive system (n=6); diseases of the blood and blood-forming organs, and certain disorders involving the immune mechanism (n=5); diseases of the ear and the mastoid process (n=3); diseases of the genitourinary system (n=3); congenital malformations, deformations, and chromosomal abnormalities (n=3); and certain infectious and parasitic diseases (n=2).
      −2.13(1.79)4.75(2.52)−2.56(1.86)−0.73(2.02)−0.85(2.77)−0.82(1.86)
      Multimorbidity (ref: no)2.81(1.16)
      P≤.01 (F test).
      2.55(1.64)3.64(1.22)
      P≤.01 (F test).
      1.62(1.32)4.66(1.81)
      P≤.01 (F test).
      2.91(1.21)
      P≤.05 (F test).
      Rehabilitation urgency (ref: elective)1.58(1.27)5.32(1.80)
      P≤.01 (F test).
      5.80(1.33)
      P≤.001 (F test).
      0.16(1.47)4.50(1.98)
      P≤.05 (F test).
      2.52(1.33)
      Unmarried (ref: married)−1.23(1.12)0.58(1.59)0.24(1.18)−1.19(1.29)1.25(1.75)−1.50(1.18)
      Education
      P≤.01 (F test).
      P≤.001 (F test).
       Primary school4.84(1.56)8.70(2.20)3.41(1.63)−2.10(1.76)2.54(2.43)3.07(1.63)
       Secondary school2.05(1.24)3.16(1.75)1.10(1.30)−0.93(1.42)3.28(2.24)1.51(1.29)
       College/university0.00(ref)0.00(ref)0.00(ref)0.00(ref)0.00(ref)0.00(ref)
      Current smoking (ref: yes)2.61(1.45)0.63(2.03)1.01(1.51)0.97(1.63)3.81(2.24)2.08(1.49)
      P≤.05 (F test).
      Rural municipality (ref: urban)0.55(1.09)−2.15(1.54)−0.59(1.14)−0.01(1.24)−1.65(1.70)−0.90(1.14)
      EQ-5D (pain/discomfort)
      From no pain or discomfort to extreme pain or discomfort, 5 categories.
      0.50(0.63)8.47(0.89)
      P≤.001 (F test).
      3.36(0.66)
      P≤.01 (F test).
      1.42(0.71)
      P≤.05 (F test).
      5.72(0.98)
      P≤.001 (F test).
      4.12(0.66)
      P≤.001 (F test).
      HADS-D score
      0=lowest score of depressive symptoms, 21=highest score of depressive symptoms.
      1.69(0.20)
      P≤.001 (F test).
      1.38(0.28)
      P≤.001 (F test).
      0.84(0.21)
      P≤.001 (F test).
      1.77(0.22)
      P≤.001 (F test).
      2.48(0.31)
      P≤.001 (F test).
      1.85(0.21)
      P≤.001 (F test).
      HADS-A score
      0=lowest score of anxiety symptoms, 21=highest score of anxiety symptoms.
      0.52(0.19)
      P≤.01 (F test).
      −0.67(0.27)
      P≤.05 (F test).
      −0.01(0.20)0.24(0.22)−1.01(0.30)
      P≤.001 (F test).
      0.31(0.20)
      SOC score
      13=lowest score, 91=highest score (best).
      −0.20(0.06)
      P≤.01 (F test).
      −0.04(0.09)0.01(0.07)−0.36(0.07)
      P≤.001 (F test).
      −0.11(0.10)−0.23(0.07)
      P≤.001 (F test).
      Abbreviations: B, unstandardized estimated regression coefficient; EQ-5D, EuroQol EQ-5D; HADS-A, Hospital Anxiety and Depression scale, anxiety subscale; HADS-D, Hospital Anxiety and Depression scale, depression subscale; ref, reference.
      Diseases included the following: endocrine, nutritional, and metabolic diseases (n=37), respiratory diseases (n=36), injuries and external causes (n=26), factors influencing health status and contact with health services (n=23), mental and behavioral disorders (n=13), symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified (n=9); codes for special purposes (n=7); diseases of the digestive system (n=6); diseases of the blood and blood-forming organs, and certain disorders involving the immune mechanism (n=5); diseases of the ear and the mastoid process (n=3); diseases of the genitourinary system (n=3); congenital malformations, deformations, and chromosomal abnormalities (n=3); and certain infectious and parasitic diseases (n=2).
      From no pain or discomfort to extreme pain or discomfort, 5 categories.
      0=lowest score of depressive symptoms, 21=highest score of depressive symptoms.
      § 0=lowest score of anxiety symptoms, 21=highest score of anxiety symptoms.
      13=lowest score, 91=highest score (best).
      P≤.05 (F test).
      # P≤.001 (F test).
      ∗∗ P≤.01 (F test).
      The disability domain getting along was associated with SOC for most diagnostic groups, with lower disability score for higher SOC score, and associations with SOC were present in some other domains for some diagnostic groups (table 3).
      Table 3Results of a fully adjusted linear regression analysis for predicting WHODAS 2.0 domain scores in main groups of diseases among 975 patients accepted for specialized somatic rehabilitation in the Western Norway Health Region during the first half of 2015
      Adjusted for sex, age groups, multimorbidity, rehabilitation urgency, marital status, education, smoking, urbanity, pain/discomfort, depressive symptoms, and anxiety symptoms.
      Predictor Variable

      Diagnostic Groups
      CognitionMobilitySelf-CareGetting AlongLife ActivitiesParticipation
      B(SE)B(SE)B(SE)B(SE)B(SE)B(SE)
      SOC
      13=lowest score, 91=highest score (best). Diseases included the following: endocrine, nutritional, and metabolic diseases (n=37); respiratory diseases (n=36); injuries and external causes (n=26); factors influencing health status and contact with health services (n=23); mental and behavioral disorders (n=13); symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified (n=9); codes for special purposes (n=7); diseases of the digestive system (n=6); diseases of the blood and blood-forming organs, and certain disorders involving the immune mechanism (n=5); diseases of the ear and the mastoid process (n=3); diseases of the genitourinary system (n=3); congenital malformations, deformations, and chromosomal abnormalities (n=3); and certain infectious and parasitic diseases (n=2).
       Musculoskeletal diseases−0.23(0.10)
      P≤.05 (F test).
      0.02(0.12)0.20(0.10)
      P≤.05 (F test).
      −0.30(0.11)
      P≤.01 (F test).
      0.07(0.13)−0.18(0.09)
      P≤.05 (F test).
       Circulatory diseases−0.32(0.14)
      P≤.05 (F test).
      −0.22(0.19)−0.32(0.15)
      P≤.05 (F test).
      −0.03(0.14)−0.18(0.25)−0.28(0.15)
       Neurologic diseases−0.04(0.24)−0.22(0.37)−0.06(0.26)−0.69(0.24)
      P≤.01 (F test).
      −0.40(0.42)−0.48(0.21)
      P≤.05 (F test).
       Neoplasms0.18(0.27)0.38(0.32)0.07(0.25)−0.94(0.37)
      P≤.05 (F test).
      0.34(0.43)0.41(0.32)
       Other
      Adjusted for sex, age groups, multimorbidity, rehabilitation urgency, marital status, education, smoking, urbanity, pain/discomfort, depressive symptoms, and anxiety symptoms.
      −0.21(0.15)−0.23(0.24)−0.20(0.16)−0.54(0.17)
      P≤.01 (F test).
      −0.40(0.23)−0.27(0.17)
      Abbreviation: B, unstandardized estimated regression coefficient.
      Adjusted for sex, age groups, multimorbidity, rehabilitation urgency, marital status, education, smoking, urbanity, pain/discomfort, depressive symptoms, and anxiety symptoms.
      13=lowest score, 91=highest score (best). Diseases included the following: endocrine, nutritional, and metabolic diseases (n=37); respiratory diseases (n=36); injuries and external causes (n=26); factors influencing health status and contact with health services (n=23); mental and behavioral disorders (n=13); symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified (n=9); codes for special purposes (n=7); diseases of the digestive system (n=6); diseases of the blood and blood-forming organs, and certain disorders involving the immune mechanism (n=5); diseases of the ear and the mastoid process (n=3); diseases of the genitourinary system (n=3); congenital malformations, deformations, and chromosomal abnormalities (n=3); and certain infectious and parasitic diseases (n=2).
      P≤.05 (F test).
      § P≤.01 (F test).
      The results from the SEM are shown in fig 1 and table 4. SOC had a positive association with both HRQOL measures, mostly mediated by disability because better SOC led to reduced disability which led to better HRQOL. The model fit was best for the subpopulation with circulatory diseases. All models were significantly better than the independent model.
      Table 4Results from SEM for prior hypothesized structural models of SOC, disability, and HRQOL among 975 patients accepted for specialized somatic rehabilitation in the Western Norway Health Region during the first half of 2015
      Variables

      Diagnostic Groups
      Both ModelsModel 1
      Partially mediated.
      Only
      Model 2
      Direct relation only.
      Only
      Fit Indices
      Satisfactory fit of a model was defined by a CFI and TLI close to 0.95 or higher, an RMSEA close to 0.06 or lower, and a standardized root mean square residual close to 0.08 or lower.42
      Regression CoefficientsCovariance
      CFITLIRMSEA(95% CI)SRMRSOC→DisabilitySOC→HRQOLDisability→HRQOLSOC→HRQOLDisability↔HRQOL
      SOC, disability, MCS
       All diseases0.9020.8980.081 (0.080-0.083)
      P≤.001 (F test).
      0.090−0.178
      P≤.001 (F test).
      0.115
      P≤.001 (F test).
      −0.524
      P≤.001 (F test).
      0.209
      P≤.001 (F test).
      −0.115
      P≤.001 (F test).
       Musculoskeletal diseases0.8780.8730.084 (0.082-0.086)
      P≤.001 (F test).
      0.098−0.211
      P≤.001 (F test).
      0.135
      P≤.001 (F test).
      −0.461
      P≤.001 (F test).
      0.233
      P≤.001 (F test).
      −0.116
      P≤.001 (F test).
       Circulatory diseases0.9800.9790.038 (0.032-0.043)
      P≤.001 (F test).
      0.093−0.385
      P≤.01 (F test).
      0.153
      P≤.01 (F test).
      −0.409
      P≤.001 (F test).
      0.311
      P≤.01 (F test).
      −0.032
      P≤.001 (F test).
       Other0.9370.9350.064 (0.06-0.068)
      P≤.001 (F test).
      0.102−0.408
      P≤.05 (F test).
      0.161
      P≤.05 (F test).
      −0.252
      P≤.001 (F test).
      0.264
      P≤.01 (F test).
      −0.058
      P≤.001 (F test).
      SOC, disability, PCS
       All diseases0.8520.8470.093 (0.092-0.094)
      P≤.001 (F test).
      0.103−0.127
      P≤.001 (F test).
      −0.096
      P≤.001 (F test).
      −2.030
      P≤.001 (F test).
      0.162
      P≤.001 (F test).
      −0.318
      P≤.001 (F test).
       Musculoskeletal diseases0.7490.7410.101 (0.099-0.103)
      P≤.001 (F test).
      0.114−0.161
      P≤.001 (F test).
      −0.096
      P≤.001 (F test).
      −0.967
      P≤.001 (F test).
      0.059
      P≤.05 (F test).
      −0.211
      P≤.001 (F test).
       Circulatory diseases0.9550.9540.055 (0.051-0.059)
      P≤.001 (F test).
      0.101−0.294
      P≤.01 (F test).
      −0.026−1.366
      P≤.001 (F test).
      0.375
      P≤.01 (F test).
      −0.096
      P≤.001 (F test).
       Other0.8940.8900.081 (0.078-0.084)
      P≤.001 (F test).
      0.115−0.235
      P≤.05 (F test).
      −0.210
      P≤.05 (F test).
      −1.772
      P≤.001 (F test).
      0.205−0.219
      P≤.001 (F test).
      Abbreviations: CFI, comparative fit index; RMSEA, root mean square error of approximation; SRMR, standardized root mean square residual; TLI, Tucker-Lewis index.
      Partially mediated.
      Direct relation only.
      Satisfactory fit of a model was defined by a CFI and TLI close to 0.95 or higher, an RMSEA close to 0.06 or lower, and a standardized root mean square residual close to 0.08 or lower.
      • Mercer S.W.
      • Smith S.M.
      • Wyke S.
      • et al.
      Multimorbidity in primary care: developing the research agenda.
      § P≤.001 (F test).
      P≤.01 (F test).
      P≤.05 (F test).

      Discussion

      To our knowledge this is the first study to assess the relations between SOC, domain-specific disability, and HRQOL in a large sample of rehabilitation patients with diagnoses that are common in rehabilitation centers in secondary care. SEM was performed, in which 2 structural models were investigated. The largest diagnostic groups were analyzed separately to enhance the clinical relevance.
      In comparisons with previous Norwegian studies, the mean SOC-13 score found in this study was slightly lower than in a population of women after myocardial infarction
      • Lovlien M.
      • Mundal L.
      • Hall-Lord M.L.
      Health-related quality of life, sense of coherence and leisure-time physical activity in women after an acute myocardial infarction.
      and higher than in a sample of patients with musculoskeletal pain,
      • Lillefjell M.
      • Jakobsen K.
      Sense of coherence as a predictor of work reentry following multidisciplinary rehabilitation for individuals with chronic musculoskeletal pain.
      consistent with the lower SOC-13 scores for patients with musculoskeletal diseases compared to patients with circulatory diseases in the present study. The mean SF-36 domain scores in the present study (data not shown) were lower compared with a Dutch study of patients in a rehabilitation center.
      • Lillefjell M.
      • Jakobsen K.
      Sense of coherence as a predictor of work reentry following multidisciplinary rehabilitation for individuals with chronic musculoskeletal pain.
      However, the Dutch study was postrehabilitation, 6-12 months after discharge. In our study population, overall disability scores were higher than in similar populations of other studies.
      • Garin O.
      • Ayuso-Mateos J.L.
      • Almansa J.
      • et al.
      Validation of the “World Health Organization Disability Assessment Schedule, WHODAS-2” in patients with chronic diseases.
      • Posl M.
      • Cieza A.
      • Stucki G.
      Psychometric properties of the WHODASII in rehabilitation patients.

      Importance of SOC among rehabilitation patients

      From a theoretical perspective, Antonovsky argued for an association between SOC and both mental and physical components of health, with better health according to stronger SOC. However, the lack of association between SOC and the physical domains of disability (mobility, self-care, life activities) found in the present study is consistent with a previous systematic review.
      • Eriksson M.
      • Lindstrom B.
      Antonovsky’s sense of coherence scale and the relation with health: a systematic review.
      An association between mental disability domains and SOC was found in all diagnostic groups and implies that rehabilitation patients with better capacity to cope report less disability in mental domains, also consistent with the same review.
      • Eriksson M.
      • Lindstrom B.
      Antonovsky’s sense of coherence scale and the relation with health: a systematic review.
      Some items in the participation domain assess attitudes, reactions, and actions from significant persons, which may represent aspects of social support that is positively related to SOC.
      • Wolff A.C.
      • Ratner P.A.
      Stress, social support, and sense of coherence.
      The results from the SEM in the full sample showed better fit of both hypothesized models, including the mental components of HRQOL, than the physical components, also in line with previous studies.
      • Eriksson M.
      • Lindstrom B.
      Antonovsky’s sense of coherence scale and the relation with health: a systematic review.
      This suggests that rehabilitation patients who are able to mobilize available resources to manage challenges of everyday life, and who find this meaningful, may have improved mental health. This was also found in a study where higher levels of SOC predicted better mental health in men 3-6 months after a myocardial infarction.
      • Drory Y.
      • Kravetz S.
      • Hirschberger G.
      • et al.
      Long-term mental health of men after a first acute myocardial infarction.
      The fit indices for the hypothesized models found in patients with circulatory diseases support a direction of association from SOC to disability and mental components of HRQOL, consistent with a previous study among adolescents with congenital heart disease.
      • Apers S.
      • Luyckx K.
      • Rassart J.
      • et al.
      Sense of coherence is a predictor of perceived health in adolescents with congenital heart disease: a cross-lagged prospective study.
      However, this comparison requires caution, considering the development of SOC in younger ages, as theorized by Antonovsky.
      • Antonovsky A.
      Unraveling the mystery of health: how people manage stress and stay well.
      The fit indices were also adequate considering the physical component of HRQOL. To our knowledge, this has not been reported previously and further investigation using longitudinal studies is needed to confirm that SOC actually improves the physical component of HRQOL among patients with circulatory diseases.
      Among patients with musculoskeletal diseases, the results from the path analysis did not support the hypothesized models. We have not found any studies explaining this directly, and future studies should investigate if SOC-related constructs such as pain, depression, and anxiety can explain why these relations vary among different diseases. However, a study among patients with long-term musculoskeletal pain showed no association between SOC and work reentry.
      • Lillefjell M.
      • Jakobsen K.
      Sense of coherence as a predictor of work reentry following multidisciplinary rehabilitation for individuals with chronic musculoskeletal pain.
      Thus, the relation between SOC, disability, HRQOL, and other important rehabilitation outcomes should be further investigated especially in this diagnostic group.
      Although the WHODAS 2.0 measures the restriction on daily life activities and social participation and the SF-36 addresses patient’s physical and mental health, these constructs overlap. Nevertheless, the results from the present SEM, which were numerically similar, imply a different causal role of SOC.
      Contrary to our hypothesized structural model, with the direction of association from SOC to disability, the authors of a study investigating the association between SOC and disability among elderly adults suggested an opposite direction.
      • Virues-Ortega J.
      • Vega S.
      • Seijo-Martinez M.
      • et al.
      A protective personal factor against disability and dependence in the elderly: an ordinal regression analysis with nine geographically-defined samples from Spain.
      For people experiencing disability, a strong preexisting SOC may be weakened
      • Virues-Ortega J.
      • Vega S.
      • Seijo-Martinez M.
      • et al.
      A protective personal factor against disability and dependence in the elderly: an ordinal regression analysis with nine geographically-defined samples from Spain.
      ; the authors do not further specify the type of this disability. Although Antonovsky postulated SOC to be relatively stable, he considered that SOC could change under certain conditions.
      • Antonovsky A.
      Unraveling the mystery of health: how people manage stress and stay well.
      Rehabilitation patients with activity limitations and participation restrictions caused by their health condition may have their SOC weakened, consistent with findings from a 5-year prospective population-based study showing that people with certain disease were among those with the largest decrease in SOC score over time.
      • Nilsson B.
      • Holmgren L.
      • Stegmayr B.
      • et al.
      Sense of coherence—stability over time and relation to health, disease, and psychosocial changes in a general population: a longitudinal study.
      Longitudinal studies are needed to assess whether SOC might be decreased before rehabilitation, and if rehabilitation efforts can restore the previous SOC.

      Study limitations

      The main limitation of this study is the cross-sectional design. We used our hypothesized models to investigate whether data were consistent with causal links between the main outcome measures, disability, HRQOL, and SOC as the main predictors. However, the limitations of a cross-sectional design are well known, and the present findings can only contribute to other evidence. Further investigations in this research area are needed to clarify the importance of SOC in rehabilitation.
      One-third of invited patients consented to participate and a large number of survey instruments were completed, indicating an acceptable response rate compared with other large-scale surveys among rehabilitation patients
      • Krops L.A.
      • Jaarsma E.A.
      • Dijkstra P.U.
      • et al.
      Health-related quality of life in a Dutch rehabilitation population: reference values and the effect of physical activity.
      and in the general population.
      • Picavet H.S.
      • Schouten J.S.
      Musculoskeletal pain in the Netherlands: prevalences, consequences and risk groups, the DMC3-study.
      The large number of instruments used may explain some of the attrition. Nevertheless, the lack of data from 65% of eligible participants limits the validity. The age of participants was slightly higher than among nonrespondents, which may lead to an overestimation of SOC scores because these scores were highest among older adults. However, a lack of information on nonparticipants makes it difficult to determine whether participants were actually healthier or had stronger SOC. Further research should include larger samples with younger patients and with other diseases. Most importantly, only a prospective design can give valid proof of causal mechanisms.

      Conclusion

      The present study indicates that SOC is related to mental domains of disability as measured by WHODAS 2.0. However, the role of SOC in relation to disability and HRQOL seemed to vary between the diagnostic groups. We believe that targeting SOC in the rehabilitation setting, especially in patients with circulatory diseases, could improve the mental components of disability and HRQOL. Strengthening SOC involves enhancing patients’ understanding and reflection on stressful situations and the available resources and might help the patient to engage in the rehabilitation process and take control of their own life. Future prospective studies might clarify the role of SOC in achieving important outcomes in rehabilitation.

      Suppliers

      • a.
        SPSS, version 23; IBM Corporation.
      • b.
        RStudio, version 1.0.143; RStudio.

      Acknowledgments

      We thank the World Health Organization for technical support in obtaining the WHODAS 2.0. Furthermore, we thank all rehabilitation institutions (Åstveit Health Center, Red Cross Haugland Rehabilitation Centre, Ravneberghaugen Rehabilitation Centre, LHL Clinics Bergen, LHL Clinics Nærland, Rehabilitering Vest Rehabilitation Centre) and participating staff for recruiting patients for this study. We thank Analisa Avila, ELS, from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.

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