Journal of Rehabilitation Medicine 51-10 | Page 45

Pain catastrophizing and dropout in chronic pain management
765
Table II. Scores of completers and dropouts on categories of the Extended Common-Sense Model of Self-Regulation
Categories E-CSM
Illness representations
Brief IPQ – Consequences 1
Brief IPQ – Timeline 2
Brief IPQ – Personal Control 3
Brief IPQ – Treatment Control 4
Brief IPQ – Identity 5
Brief IPQ – Concerns 6
Brief IPQ – Comprehension 7
Brief IPQ – Emotion 8
Treatment beliefs
TBQ Necessity
TBQ Concerns
TBQ Practical Barriers
Pain Self Efficacy
PSEQ-Pain Self-Efficacy total score
Anxiety and Depression
HADS Anxiety
HADS Depression
Pain catastrophizing
Pain catastrophizing – Helplessness
Pain catastrophizing – Magnification
Pain catastrophizing – Rumination
Pain catastrophizing – Total Score
T0 completers
Mean (SD)
7.86
7.45
4.03
7.38
7.75
6.91
6.12
6.52
T1 completers
Mean (SD)
(1.56)
(2.06)
(2.28)
(1.61)
(1.68)
(2.11)
(2.39)
(2.39)
5.93
6.88
5.36
6.77
5.97
4.78
6.91
5.28
(2.70)
(2.79)
(2.61)
(2.52)
(2.69)
(2.94)
(2.56)
(2.85)
T0 completers
T1 completers
p-value
0.000*
0.001*
0.000*
0.009*
0.000*
0.000*
0.004*
0.000*
T0 dropouts
Mean (SD)
8.17
7.34
3.66
6.69
7.43
7.00
5.89
6.91
T0 completers/dropouts
p-value
(1.52)
(2.22)
(2.72)
(2.29)
(2.05)
(2.40)
(3.14)
(2.57) 0.287
0.794
0.453
0.096
0.399
0.836
0.683
0.415
22.37 (3.00)
4.90 (1.86)
3.59 (1.90) –
–
– –
–
– 22.21 (3.00)
5.03 (1.77)
4.26 (2.17) 0.777
0.707
0.098
33.71 (11.88) 40.42 (13.86) 0.000* 29.51 (11.97) 0.067
8.87 (4.31)
8.22 (4.71) 7.76 (4.57)
6.15 (4.79) 0.000*
0.007* 9.15 (4.69)
8.89 (4.50) 0.067
0.434
9.82 (5.46)
2.54 (2.49)
7.72 (4.01)
20.08 (10.59) 6.76 (5.75)
2.01 (2.44)
5.63 (4.08)
14.40 (11.47) 0.000*
0.007*
0.000*
0.000* 14.03 (5.44)
3.63 (3.30)
9.77 (4.06)
27.43 (10.98)
0.001**
0.073
0.009**
0.001**
*Completers T0 vs. T1 p  < 0.05, **Completers T0 vs. Dropouts T0 p  < 0.05. No statistical analyses on the T1 Dropouts, since only 6 of 35 post-treatment assessments
were available. SD: standard deviation. HADS: Hospital Anxiety and Depression scale; PSEQ: Pain Self Efficacy Questionnaire; IPQ: Illness Perception Questionnaire;
E-CSM: Extended Common-Sense Model of Self-Regulation. TBQ: Treatment Beliefs Questionnaire. Significant values are shown in bold.
Pain self-efficacy (PSEQ – total score). Another po-
tential predictor that scored below a p-value < 0.20
was the total score of the PSEQ (p = 0.063). Lower
scores on the PSEQ – total score were associated with
dropout (Table SII 1 ).
Anxiety and depression (HADS – 2 domains). No as-
sociations with dropout were found for the 2 domains
of the HADS: Anxiety (p = 0.735) and Depression
(p = 0.444) (Table SII 1 ).
Pain catastrophizing (PCS total score and 3 domains).
In univariate logistic regression analyses significant
associations with dropout were found for all 3 domains
of the PCS: Helplessness (p < 0.001), Magnification
(p = 0.034), Rumination (p = 0.009) and the PCS total
score (p = 0.001). Higher scores on the all 3 domains
of the PCS and the PCS total score were associated
with incidence of dropout (Table SII 1 ).
Multiple logistic regression analyses
Based on the univariate logistic regression analyses
7 predictors for dropout of the 18 selected potential
predictors (out of four categories of the E-CSM Self-
Regulation were eligible for inclusion in the multiple
logistic regression analyses. Because the number of
dropouts in this prospective cohort study was limited,
maximal 3 of the 7 potential predictors could be in-
cluded in the multiple logistic regression model (29).
The Brief IPQ item treatment control was chosen for
inclusion above the TBQ domain Practical Barriers,
since the psychometric properties of this measurement
were better than the TBQ (21). In addition, the PCS
total score was preferred to the 3 domains of PCS for
multiple logistic regression analyses, as these domains
were highly correlated with each other (helplessness,
magnification and rumination).
The following 3 potential predictors were included
in the multiple logistic regression analysis: IPQ-B tre-
atment control item, PSEQ- total score and PCS total
score. Only the PCS total score (p = 0.001) was retained
as a predictor for dropout in these analyses. Brief IPQ
item treatment control (p = 0.081) and PSEQ- total
score (p = 0.770) were not significantly associated with
dropout, when adjusted for PCS total score (Table III).
In this IPMP an increase of 1 point on the PCS total
score resulted in an 1.1 higher odds of dropping out
(95% CI 1.028; 1.1071).
Bootstrapping was performed using the Bias-
Corrected and Accelerated (BCa) bootstrap method
with 10,000 draws from the data to internally validate
the prediction model. This led to a somewhat broader
Table III. Result of multiple logistic regression analysis of potential
predictors for dropout (PCS total score, Brief IPQ item treatment
control, PSEQ total score)
Pain Catastrophizing
Total score
B SE p LR OR 95% CI Wald
0.065 0.019 0.001 1.067 1.028; 1.107
ROC curve and area under the curve: 0.688 (95% CI 0.589; 0.786), Hosmer-
Lemeshow test: (p  = 0.508).
PCS: Pain Catastrophizing Scale; IPQ: Illness Perception Questionnaire; PSEQ:
Pain Self Efficacy Questionnaire; OR: odds ratio; CI: confidence interval.
J Rehabil Med 51, 2019