Psychometric characteristics of the Revised Illness Perception Questionnaire (IPQ-R) in adults with sickle cell disease

Figures & data

Table 1. Interpretation of IPQ-R dimension scores (from Nicholls et al., 2013).

Dimensions	Interpretation
A high dimension indicates stronger agreement that …
Timeline acute/chronic	Illness will last a long time
Timeline cyclical	Condition is cyclical in nature
Consequences	Condition has a major impact on life
Personal control	Good perceived personal control over symptoms
Treatment control/Cure	Treatment could control symptoms
Illness coherence	Understanding of condition
Emotional representation	Condition affects patients emotionally

Table 2. Comparison of the goodness of fit indices between the nine studies that explored the psychometric properties of the IPQ-R.

Initial model	n	Indices of goodness of fit for the original CFA					AIC	Comment
		CFI	TLI	SRMSR	RMSEA	Χ²/dF
		> 0.90	> 0.90	<0.08	<0.07	<5
Surgenor, L. J., Snell, D. L., Siegert, R. J., Kelly, S., Flint, R., & Coulter, G. (2019).	310	?	?	?	?	?	?	No data provided
Ashley, L., Smith, A. B., Keding, A., Jones, H., Velikova, G., & Wright, P. (2013).	531	0.80		0.086	0.042	1.766
Nicholls, E. E., Hill, S., & Foster, N. E. (2013).	330	0.86			0.064	2.338
	1621	0.86			0.068	8.495
	1319	0.90			0.059	5.635
Brzoska, P., Yilmaz-Aslan, Y., Sultanoglu, E., Sultanoglu, B., & Razum, O. (2012).	302	0.785	0.765	0.109	0.075	3.722	18177.43
Abubakari, A.-R., Jones, M. C., Lauder, W., Kirk, A., Devendra, D., & Anderson, J. (2012).	221	0.83	0.81		0.06	1.707
Dempster, M., & McCorry, N. K. (2012).	587	0.94		0.070	0.068	3.707
Cabassa, L. J., Lagomasino, I. T., Dwight-Johnson, M., Hansen, M. C., & Xie, B. (2008).	339	0.793	0.768		0.069	2.598
Wittkowski, A., Richards, H. L., Williams, J., & Main, C. J. (2008).	284	0.798			0.085	3.061
Hagger, M. S., & Orbell, S. (2005).	660	0.911	0.904		0.042
Modification 1 = items deletion	n	Indices of goodness of fit for the original CFA					AIC	Items deleted
		CFI	TLI	SRMSR	RMSEA	Χ²/dF
		> 0.90	> 0.90	<0.08	<0.07	<5
Surgenor, L. J., Snell, D. L., Siegert, R. J., Kelly, S., Flint, R., & Coulter, G. (2019).	310	?	?	?	?	?		19, 23
Ashley, L., Smith, A. B., Keding, A., Jones, H., Velikova, G., & Wright, P. (2013).	531	0.904		0.058	0.057	2.722		12, 18, 24, 32
Nicholls, E. E., Hill, S., & Foster, N. E. (2013).	330	0.89			0.064	2.344		15, 17, 19, 23, 37, 38
	1621	0.90			0.065	7.801
	1319	0.92			0.058	5.452
Brzoska, P., Yilmaz-Aslan, Y., Sultanoglu, E., Sultanoglu, B., & Razum, O. (2012).	302	0.877	0.864	0.083	0.059	2.924	15404.43	17, 19, 20, 31
Abubakari, A.-R., Jones, M. C., Lauder, W., Kirk, A., Devendra, D., & Anderson, J. (2012).	221	0.86	0.85		0.06	1.669		19, 20, 24,
Dempster, M., & McCorry, N. K. (2012).	587	0.94		0.070	0.068	3.707
Cabassa, L. J., Lagomasino, I. T., Dwight-Johnson, M., Hansen, M. C., & Xie, B. (2008).	339	0.827	0.802		0.069	2.620		15, 17, 19
Wittkowski, A., Richards, H. L., Williams, J., & Main, C. J. (2008).	284	0.798			0.085	3.061
Hagger, M. S., & Orbell, S. (2005).	660	0.926	0.920		0.040			9, 10
Modification 2 = adding error covariances	n	Indices of goodness of fit for the original CFA					AIC	Item with error covarianced
		CFI	TLI	SRMSR	RMSEA	Χ²/dF
		> 0.90	> 0.90	<0.08	<0.07	<5
Surgenor, L. J., Snell, D. L., Siegert, R. J., Kelly, S., Flint, R., & Coulter, G. (2019).	310	?	?	?	?	?	?	1&4 6&7 6&9 9&11 10&11 12&17 15&17 34&37 37&38
Ashley, L., Smith, A. B., Keding, A., Jones, H., Velikova, G., & Wright, P. (2013).	531	0.859		0.079	0.037	1.526		1&4 15&17 19&23
Nicholls, E. E., Hill, S., & Foster, N. E. (2013).	330	0.89			0.064	2.344
	1621	0.90			0.065	7.801
	1319	0.92			0.058	5.452
Brzoska, P., Yilmaz-Aslan, Y., Sultanoglu, E., Sultanoglu, B., & Razum, O. (2012).	302	0.911	0.901	0.079	0.050	2.502	15189.58	33&34 7&8
Abubakari, A.-R., Jones, M. C., Lauder, W., Kirk, A., Devendra, D., & Anderson, J. (2012).	221	0.89	0.88		0.05	1.522		1&4 7&6 6&8 7&8 9&11 34&35
Dempster, M., & McCorry, N. K. (2012).	587	0.95		0.061	0.064	3.430		1&4
Cabassa, L. J., Lagomasino, I. T., Dwight-Johnson, M., Hansen, M. C., & Xie, B. (2008).	339	0.908	0.900		0.051	1.885		7 errors covariances non-specified
Wittkowski, A., Richards, H. L., Williams, J., & Main, C. J. (2008).	284	0.798			0.085	3.061
Hagger, M. S., & Orbell, S. (2005).	660	0.926	0.920		0.040
Modification 3 = items reallocation (Final model)	n	Indices of goodness of fit for the original CFA					AIC	Items reallocated
		CFI	TLI	SRMSR	RMSEA	Χ²/dF
		> 0.90	> 0.90	<0.08	<0.07	<5
Surgenor, L. J., Snell, D. L., Siegert, R. J., Kelly, S., Flint, R., & Coulter, G. (2019).	310	?	?	?	?	?	?
Ashley, L., Smith, A. B., Keding, A., Jones, H., Velikova, G., & Wright, P. (2013).	531	0.859		0.079	0.037	1.526
Nicholls, E. E., Hill, S., & Foster, N. E. (2013).	330	0.89			0.064	2.344
	1621	0.90			0.065	7.801
	1319	0.92			0.058	5.452
Brzoska, P., Yilmaz-Aslan, Y., Sultanoglu, E., Sultanoglu, B., & Razum, O. (2012).	302	0.929	0.921	0.067	0.045	2.282	15079.40	6 -> chronology
Abubakari, A.-R., Jones, M. C., Lauder, W., Kirk, A., Devendra, D., & Anderson, J. (2012).	221	0.91	0.90		0.05	1.435
Dempster, M., & McCorry, N. K. (2012).	587	0.95		0.060	0.061	3.182		18 – >Treatment control
Cabassa, L. J., Lagomasino, I. T., Dwight-Johnson, M., Hansen, M. C., & Xie, B. (2008).	339	0.908	0.900		0.051	1.885
Wittkowski, A., Richards, H. L., Williams, J., & Main, C. J. (2008).	284	0.798			0.085	3.061
Hagger, M. S., & Orbell, S. (2005).	660	0.926	0.920		0.040

Table 3. The Revised Illness Perception Questionnaire (IPQ-R) seven core-factor items and modified Causal attribution scale.

IPQ-R dimension	Item		English version	French translation
Timeline acute/chronic	1	R	My sickle cell disease will last a short time	Ma drépanocytose ne va pas durer longtemps
	2		My sickle cell disease is likely to be permanent rather than temporary	Ma drépanocytose est susceptible d’être permanente plutôt que temporaire
	3		My sickle cell disease will last for a long time	Ma drépanocytose va durer longtemps
	4	R	My sickle cell disease will pass quickly	Ma drépanocytose va rapidement passer
	5		I expect to have sickle cell disease for the rest of my life	Je pense que j’aurais la drépanocytose pour le restant de ma vie
	18	R	My sickle cell disease will improve in time	Ma drépanocytose va s’améliorer avec le temps
Consequences	6		My sickle cell disease is a serious condition	Ma drépanocytose est grave
	7		My sickle cell disease has major consequences in my life	Ma drépanocytose a des conséquences importantes sur ma vie
	8	R	My sickle cell disease does not have much effect on my life	Ma drépanocytose n’a pas beaucoup d’effet sur ma vie
	9		My sickle cell disease strongly affects the way others see me	Ma drépanocytose affecte beaucoup la façon dont les autres me voient
	10		My sickle cell disease has serious financial consequences	Ma drépanocytose a des conséquences financières graves
	11		My sickle cell disease causes difficulties for those who are close to me	Ma drépanocytose cause des difficultés à mes proches
Personal control	12		There is a lot which I can do to control my symptoms	Il y a beaucoup de choses que je peux faire pour contrôler mes symptômes
	13		What I do can determine whether my sickle cell disease gets better or worse	Ce que je fais peut déterminer l’amélioration ou l’aggravation de ma drépanocytose
	14		The course of my sickle cell disease depends on me	Le déroulement de ma drépanocytose dépend de moi
	15	R	Nothing I do will affect my sickle cell disease	Rien de ce que je fais n’affectera ma drépanocytose
	16		I have the power to influence my sickle cell disease	J’ai le pouvoir d’influencer ma drépanocytose
	17	R	My actions will have no effect on the outcome of my sickle cell disease	Mes actions n’auront aucun effet sur l’évolution de ma drépanocytose
Treatment control	19	R	There is very little that can be done to improve my sickle cell disease	Il y a peu de choses à faire pour améliorer ma drépanocytose
	20		My treatment will be effective in curing my sickle cell disease	Mon traitement sera efficace pour guérir ma drépanocytose
	21		The negative effects of my sickle cell disease can be prevented (avoided) by my treatment	Les effets négatifs de ma drépanocytose peuvent être évités par mon traitement
	22		My treatment can control my sickle cell disease	Mon traitement peut contrôler ma drépanocytose
	23	R	There is nothing which can help my sickle cell disease	Rien ne peut aider mon état
Illness coherence	24	R	The symptoms of my conditions are puzzling to me	Les symptômes de mon état me laissent perplexe
	25	R	My sickle cell disease is a mystery to me	La drépanocytose est un mystère pour moi
	26	R	I don’t understand my sickle cell disease	Je ne comprends pas la drépanocytose
	27	R	My sickle cell disease doesn’t make any sense to me	La drépanocytose n’a aucun sens pour moi
	28		I have a clear picture or understanding of my condition	J’ai une image nette ou une compréhension de mon état
Timeline cyclical	29		The symptoms of my sickle cell disease change a great deal from day to day	Les symptômes de ma drépanocytose changent beaucoup d’un jour à l’autre
	30		My symptoms come and go in cycles	Mes symptômes vont et viennent par cycles
	31		My sickle cell disease is very unpredictable	Ma drépanocytose est très imprévisible
	32		I go through cycles in which my illness gets better and worse	Je passe par des cycles au cours desquels ma drépanocytose diminue ou empire
Emotional representation	33		I get depressed when I think about my sickle cell disease	Je déprime quand je pense à ma drépanocytose
	34		When I think about my sickle cell disease I get upset	Quand j’y pense, ma drépanocytose m’inquiète
	35		My sickle cell disease male me feel angry	Ma drépanocytose me met en colère
	36	R	My sickle cell disease does not worry me	Ma drépanocytose ne me gêne pas
	37		Having this sickle cell disease makes me feel anxious	À cause de la drépanocytose, je suis anxieux
	38		My sickle cell disease makes me feel afraid	Ma drépanocytose me fait peur
Psychological attribution	44		Stress or worry	C’est le stress ou l’ennui
	45		Family problems or worries caused my illness	C’est des problèmes de familles
	55		My mental attitude e.g. thinking about life negatively	C’est mon attitude mentale ex. Avoir une vision négative de la vie.
	61		Overwork	C’est lié à ma surcharge de travail
	68		My emotional state e.g. feeling down, lonely, anxious, empty	C’est dû à mon état émotionnel ex. Ma solitude, mon anxiété …
	70		My personality	C’est ma personnalité
Risk factor – Hereditary	39	N	It runs in my family	C’est courant dans ma famille
	40	N	It is a disease of the origins	C’est une maladie des origines
	51	N	It is hereditary or a genetic disease	C’est héréditaire ou génétique
	57	N	It is passed from parents to children	C’est transmis des parents aux enfants
Risk factor – Blood	41	N	It is a lack of blood	C’est un manque de globule
	47	N	It is a disease of the blood	C’est une maladie du sang
	53	N	It is a poor circulation of blood	C’est une mauvaise circulation du sang
	59	N	It is due to incompatible bloods	C’est dû à des sangs incompatibles
	64		It is a poor quality of blood	C’est la mauvaise qualité du sang
Risk factor – other	43		Diet or eating habits	C’est lié aux habitudes alimentaires
	46	N	It is a disease from Africa	C’est une maladie de l’Afrique
	49		My own behaviour	C’est dû à mon propre comportement
	53		Poor medical care in my past	C’est dû à de mauvais soins médicaux dans mon passé personnel
	62		Ageing	C’est dû au vieillissement
	63	N	It is the poor sperm quality	C’est le mauvais sperme
	65		Alcohol	C’est dû à ma consommation d’alcool
	66		Smoking	C’est dû à ma consommation de tabac
Immunity	50		A germ or virus	C’est dû à un microbe ou un virus
	52		Pollution in the environment	C’est dû à la pollution de l’environnement
	58	N	It is the heat	C’est la chaleur
	67		Altered immunity	C’est la détérioration de l’immunité
Accident or chance	42		Chance or bad luck	C’est le hasard ou la malchance
	48	N	It is a divine punishment	C’est une punition divine
	54	N	It is a malediction	C’est une malédiction
	60	N	It is due to spirits or spells e.g. Djinn, wizard, …	C’est dû à des esprits ou à des sorts ex. Djinn, sorcier …
	69		Accident or injury	C’est dû à un accident ou une blessure

Note: R, reverse item; N, new item.

Table 4. Fit indices presentation (Hooper et al., 2008).

Indices	Presentation	Cut off	Reference
SRMR	Absolute fit indice which determine how well an a priori model fits the sample data. The SRMR are the square root of the difference between the residuals of the sample covariance matrix and the hypothesised covariance model.	<0.08	Hu & Bentler, 1999
RMSEA	The RMSEA tells us how well the model, with unknown but optimally chosen parameter estimates would fit the populations covariance matrix. the RMSEA favours parsimony in that it will choose the model with the lesser number of parameters.	<0.07	Steiger, 2007
relative/normed chi square	The Chi-Square value is the traditional measure for evaluating overall model fit and, assesses the magnitude of discrepancy between the sample and fitted covariances matrices. Because the Chi-Square statistic is in essence a statistical significance test it is sensitive to sample size which means that the Chi-Square statistic nearly always rejects the model when large samples are used. One example of a statistic that minimises the impact of sample size on the Model Chi-Square is Wheaton et al’s relative/normed chi-square (χ2/df).	[2;5]	Wheaton et al., 1977
CFI	The Comparative Fit Index is a revised form of the NFI which takes into account sample size that performs well even when sample size is small.	>0.90	Hu & Bentler, 1999
NNFI/TLI	the Non-Normed Fit Index assesses the model by comparing the χ2 value of the model to the χ2 of the null model.	>0.90	Hooper et al., 2008

Table 5. Goodness-of-fit indices for the original and revised models of the SCD-IPQ-R (n = 406).

Cut-off	SRMR	RMSEA		CFI	TLI	χ²/dF			AIC
	<.08	<.07	90% CI	> .90	> .90	χ^²	dF	<5	Lowest
Model 1	.077	.058	.054-.061	0.83	0.81	1516	644	2.35	42934
Model 2	.075	.058	.054-.062	0.84	0.83	1353	573	2.36	40629
Model 3	.071	.048	.044-.052	.089	.088	1100	565	1.95	40392
Model 4	.058	.042	.038-.047	.092	.091	973.5	562	1.73	40272

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Data availability statement

The data that support the findings of this study are openly available in Open Science Framework (OSF): https://doi.org/10.17605/OSF.IO/YABFV