Hostname: page-component-848d4c4894-4hhp2 Total loading time: 0 Render date: 2024-05-22T12:18:10.826Z Has data issue: false hasContentIssue false

Creation of a tool to evaluate supportive care

Published online by Cambridge University Press:  01 August 2022

Damien Giacchero
Affiliation:
Department of Medical Oncology, University Côte d'Azur, Centre Antoine Lacassagne, Nice, France
Guillaume Buiret
Affiliation:
Department of Otorhinolaryngology Surgery, Hospital of Valence, Valence, France
Cécile Bartolini-Grosjean
Affiliation:
Department of Medical Oncology, University Côte d'Azur, Centre Antoine Lacassagne, Nice, France
Charles Taieb*
Affiliation:
Patient Priority Department, European Market Maintenance Assessment, Fontenay-sous-Bois, France
Mahasti Saghatchian
Affiliation:
Department of Oncology, American Hospital of Paris, Neuilly-sur-Seine, France Department of Medical Oncology, Gustave Roussy Institute, Villejuif, France
Ivan Krakowski
Affiliation:
Association Francophone pour les Soins Oncologiques de Support, Bègles, France
*
Author for correspondence: Charles Taieb, Patient Priority Department, European Market Maintenance Assessment, 18 Rue de la Renardière, 94120 Fontenay-sous-Bois, France. E-mail: charles.taieb@emma.clinic
Rights & Permissions [Opens in a new window]

Abstract

Rational

The absence of a specific tool to evaluate the impact of supportive care in general and socioesthetics (SE) in particular is undoubtedly at the origin of the lack of published research based on scientific standards.

Objective

We developed a supportive-care, patient-reported outcome questionnaire using the multistep methods, following COSMIN recommendations.

Methods

The Patient Centricity Questionnaire (PCQ) was developed using the standardized methodology for designing patient-reported outcome (PRO) questionnaires according to the following steps: elaboration of the questionnaire, measurement properties of the questionnaire, internal and external validation, test–retest validation and translation, cross-cultural adaptation, and cognitive debriefing. A multidisciplinary work group was designed including professionals, such as physicians, public health experts, sociologists, supportive-care experts, and socioestheticians.

Results

Our questionnaire includes 11 items. It is scored by adding each Visual Analogue Scale [VAS], making it range from 0 to 110, with a higher benefit when the score is higher. The Cronbach's α coefficient is 0.88 for the entire questionnaire. As the questionnaire is a reflection of the patient's feelings, it is quite natural that the name “Patient Centricity Questionnaire” (PCQ) was retained and validated by the Scientific Committee. The PCQ correlated negatively and moderately with the Perceived Stress Scale [PSS], positively and moderately with the mental dimension of the Short Form-12, and poorly with the Well Beng 12 [WB12], the physical dimension of the SF-12, and the satisfaction VAS.

Conclusion

Constructed according to the recommendations, the PCQ meets the prerequisite for this type of questionnaire. Its short format and simplicity of use allow it to be used by a large number of people. The PCQ is a simple, reliable, easy-to-use, and validated tool for research teams, making it possible for randomized studies to prove the impact of supportive care in general and SE in particular, on the patient's quality of life.

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Introduction

Supportive care is defined as “all the care and support required by patients throughout their illness in conjunction with oncological or oncohematological treatments” and aims to ensure the best possible quality of life for patients on a physical, psychological, and social level, taking the diversity of their needs and those of their family and friends into account, regardless of their place of care (Krakowski, Reference Krakowski2006).

A recent international study involving more than 11,000 individuals in five countries (France, China, Russia, the USA, and Brazil) assessed the use of supportive cancer care (SCC). 63% of French respondents, 73% of American respondents, 84% of Brazilian respondents, 64% of Russian respondents, and 86% of Chinese respondents who had received chemotherapy or radiotherapy acknowledged that they had used supportive care (Buiret et al., Reference Buiret, Delvigne and Le Dantec2022).

Various SCC treatments, such as corrective makeup, massages, facial care, body care, and clothing advice, which are also called “socioesthetics” (SE), beauty treatments, “beauty care (BC),” or “beauty therapy” in some countries, were reported by numerous patients (Russia: 24%, China or Brazil: 60%, USA: 47%, and France: 37%). It can be defined as “a professional practice of aesthetic care for populations suffering from or weakened by an attack on their physical or psychological integrity, or in social distress.” Several surveys and qualitative studies have shown a positive clinical impact in patients receiving such BC, in terms of improved self-image and self-esteem, reduced anxiety, as well as improved sex life and treatment tolerance.

Thus, SE (also called “onco-aesthetics” in oncology) has largely found its place in supportive care, as, throughout the treatment process, it helps to address the undesirable effects of treatments on the skin and skin appendages, situations of stress and anxiety, and disturbances in body image. Recently, even antalgic effects for male and female cancer patients were proven for the first time (Buiret et al., Reference Buiret, Sandonato and Chidiac2021).

Although patients and medical and nursing teams who refer their patients agree on the benefits of this practice, scientific proof of the improvements has not yet been demonstrated. For instance, its benefits on the quality of life of cancer survivors have not been assessed thus far. Randomized controlled trials dedicated to BC and patients’ body image are needed in order to develop practice guidelines, as well as define necessary resources and standardized procedures, adequate timing, and duration of supportive measures so as to bring meaningful early improvements to patients’ quality of life and thereby sustain long-term impact (Saghatchian et al., Reference Saghatchian, Lacas and Charles2021).

The absence of a specific tool to evaluate the impact of SE as a rendered medical service is undoubtedly at the origin of the lack of studies based on scientific standards.

Methods

We developed this supportive-care, patient-reported outcome (PRO) using multistep methods following COSMIN recommendations (Mokkink et al., Reference Mokkink, de Vet and Prinsen2018). This project obtained a favorable opinion on September 11, 2019 from the Ethics Committee of the CHU La Pitié Salpêtriere, Paris (CCP Ile de France 6-2019-A00204-53) and was conducted according to the Declaration of Helsinki. According to French regulations for this type of research (Reference Methodology 003), no written informed consent had to be obtained from participating patients, and an information and non-objection note was given to them.

A standard methodology for the creation of a PRO was used, and a multidisciplinary work group of experts (professionals, such as physicians, public health experts, sociologists, supportive-care experts, and socioestheticians) was created.

The questionnaire followed the recommendations proposed by Seidenberg et al. and Leidy et al. for the development of a self-report questionnaire (Seidenberg et al., Reference Seidenberg, Haltiner and Taylor1994).

The same group of experts reached a consensus on how to respond. The choice was made to use a numerical visual scale ranging from 0 for “No, not at all” to 10 for “Yes, always.”

To avoid missing data as much as possible, respondents had the option of not expressing themselves if they were not concerned by placing the cursor on zero.

To avoid any confusion regarding timing, all questions began with “currently.”

The diversity of the recruiting centers ensured broad recruitment and a consistent diversity of patients in terms of pathologies, geographical location, age, and sociological status. The participating subjects, aged at least 18 years, had to have received supportive care, SE in this case.

The construction of this questionnaire followed several steps: elaboration of the questionnaire, measurement properties of the questionnaire, internal and external validation, test–retest validation and translation, cross-cultural adaptation, and cognitive debriefing.

Step 1: Elaboration of the questionnaire

We conducted a literature search on PubMed to identify already published questionnaires or scoring systems related to SE. We used the algorithm developed by the COSMIN initiative and combined it with the terms “socioesthetic” and the medical subject subheading “aesthetics” as a major topic.

A qualified sociologist conducted a series of 23 individual interviews to elicit expectations and needs of patients in terms of the management of physical appearance, self-esteem, and relaxation, as well as the role of SA in patient support. Using a triangulation approach, we interviewed 10 patients (who were using or had already used SA) (Terwee et al., Reference Terwee, Jansma and Riphagen2009) as well as 6 SE practitioners, 5 medical professionals advising SE, and 2 members of the SE association. The verbatim data were analyzed using an itinerary method (Desjeux and Zheng, Reference Desjeux and Zheng2002; Carter et al., Reference Carter, Bryant-Lukosius and DiCenso2011, Reference Carter, Bryant-Lukosius and DiCenso2014; Palazzo et al., Reference Palazzo, Klinger and Dorner2016). Such methods aim to contextualize and understand the entire process related to an intervention (when was it proposed, why, what it did, and why was it stopped). The result of this analysis was then translated to a series of patients, trying to stay as close as possible to the patients’ words verbatim.

Finally, a multidisciplinary work group involving researchers, methodologists, clinicians (medical, paramedical, sociologist, supportive care expert, and SE practitioner) and patients designed a preliminary questionnaire from the qualitative analysis. Each item of the questionnaire was evaluated with a numerical visual scale ranging from 0 for “No, not at all” to 10 for “Yes, always”. To avoid missing data as much as possible, the respondents had the option of not expressing themselves if they were not concerned by placing the cursor on zero.

Step 2: Measurement properties of the questionnaire

The measurement properties of the questionnaire were assessed in six steps:

  1. (a) reduction of the number of items,

  2. (b) subscale repartition of items and assessment of factorial validity,

  3. (c) assessment of construct validity,

  4. (d) assessment of reliability,

  5. (e) evaluation of the minimal clinically important difference (MCID), and

  6. (f) transcultural validation in US English.

Reduction of the number of items

We reduced the number of items based on redundancy, which was suspected when the inter-item correlation evaluated by the Spearman correlation coefficient was above 0.8 (Palazzo et al., Reference Palazzo, Klinger and Dorner2016). We wanted our questionnaire to be useful in all contexts of SE interventions, as these items can differ greatly, as do benefits for patients. Therefore, we decided to exclude only items presenting a major ceiling or floor effect, and we did not exclude items due to low inter-item correlation.

Subscale repartition of items and assessment of factorial validity

Suitability for factorial analysis was assessed by a Kaiser–Meyer–Olkin (KMO) value above 0.8 for all items (Gries et al., Reference Gries, Berry and Harrington2018). A screen plot with parallel analysis was performed to determine the number of subscales. To allocate each item to a subscale, exploratory factor analysis (EFA) with a cluster rotation was performed. Items presenting a factor loading lower than 0.5 or a cross factor loading higher than 0.2 were excluded from the questionnaire (Palazzo et al., Reference Palazzo, Klinger and Dorner2016). We assessed internal consistency with Cronbach's alpha (Cronbach, Reference Cronbach1951) and McDonald's omega coefficients, aiming to have both >0.7 for the entire questionnaire and each subscale (Cerny and Kaiser, Reference Cerny and Kaiser1977). Readability of the final questionnaire was assessed with a SMOG index corrected for French (Cronbach, Reference Cronbach1951; Humphreys and Montanelli, Reference Humphreys and Montanelli1975).

Factorial validity was assessed using a higher-order factor confirmatory analysis. This analysis confirmed that the subscales could be combined into a single score. The model's suitability was assessed using three criteria: the comparative fit index (CFI) above 0.9, the Tucker–Lewis index (TLI) above 0.9, and root mean square error of approximation (RMSEA) under 0.08.

Validity construct

Patients who receive supportive care are confronted with physical and psychological difficulties, and they may also be confronted with stress and a lack of well-being. These impacts motivated and justified the choice of the PSSS (Cohen et al., Reference Cohen, Kamarck and Mermelstein1983), SF-12 (Lim and Fisher, Reference Lim and Fisher1999), and WBQ12 (Bradley, Reference Bradley and Gamsu1994).

We hypothesized several relationships between the SE score and other constructs. Specifically, there was a moderate negative correlation with the stress evaluated through the Perceived Stress Scale (PSS), a moderate positive correlation with the mental dimension of the SF-12 (r = 0.5–0.7) and a low correlation (r = 0–0.3) with the physical dimension of the SF-12, the satisfaction visual analog scale (VAS) for SE intervention, and well-being evaluated by the well-being questionnaire (WBQ12).

Reliability

Fifty participants who did not previously answer the questionnaire were asked to complete it once and then again three weeks later. Reliability was measured by the intraclass correlation coefficient (ICC) for agreement and presented on a Bland and Altman plot (Contreras et al., Reference Contreras, García-Alonso and Echenique1999; Dunn et al., Reference Dunn, Baguley and Brunsden2014).

Evaluation of the MCID

The MCID represents the smallest modification detectable in a clinical setting (Bland and Altman, Reference Bland and Altman1986). It was determined using the standard deviation method and the standard of mean method. Using two methods rendered our results more robust.

All data were analyzed using R software version 3.613 for Windows. The significance level was set at p < 0.05.

Results

The literature review did not involve the retrieval of specifically developed and validated tools to evaluate SE intervention benefits.

The elaboration of the questionnaire led to the identification of 62 themes that were transformed into questions by the expert group.

From October 2019 to February 2020, 271 patients were involved in the assessment of the measurement properties of the questionnaire. Their mean age was 56 years (±14.1); 233 were women (86%) (Table 1).

Table 1. Population description

Reduction of the number of items

Firstly, 90% or more of respondents answered that they were either not concerned by or on one of the extremes of the VAS (0 or 10). This led to the elimination of 23 items. Among the 39 questions, 20 were formulated in a positive way, and 19 were formulated in a negative way. For the simplicity of scoring purposes, the scientific committee decided to eliminate negative questions. All questions included in the subsequent analysis are presented in Table 2.

Table 2. Presentation of the questionnaire and EFA

Questions in red were eliminated due to redundancy regarding questions 5 and 6, and factor loading for other questions. Factor loadings for each dimension are colored according to the factor where the item has been attributed. The questionnaire is presented in its final transcultural validated form for questions retained in its final form, and other questions were translated from French by the authors.

The inter-item correlation matrix is presented in Figure 1. High inter-item correlation was presented by Q3 (Currently, I feel like I have a positive outlook.) and Q4 [Currently, I have the feeling that things are going well psychologically (or mentally)], which presented a correlation of 87.7% (95% CI [84.6, 90.11]). Additionally, high inter-item correlation was found for Q5 (Currently, I have the feeling that I have regained my calm.) and Q6 (Currently, I feel at peace.), which presented a correlation of 82.2% (95% CI [77.9, 85.7]). Therefore, Q3 and Q4 were eliminated because they were judged as less direct and more difficult to understand.

Fig. 1. Interitem correlation matrix.

Subscale repartition of items and assessment of factorial validity

All KMO scores were above 0.85, which confirmed the compatibility of the items for factorial analysis. The scree plot determined three pertinent dimensions (Figure 2).

Fig. 2. Screen plot. The number of factors is determined by comparing resampled data and actual data, keeping dimensions where actual data are greater than resampled data.

The EFA determined the distribution of items in the three subscales. These were related to “Serenity” (3 items), “Resilience” (4 items), and “Autonomy” (4 items). Seven items were eliminated due to a low factor loading (Q1, Q7, Q8, Q13, Q14, Q18, and Q20), of which four also had a high cross factor loading (Q1, Q13, Q14, and Q18) (Table 1). Our shortened questionnaire, therefore, included 11 items. It is scored by adding each VAS, making it range from 0 to 110, with a higher benefit when the score is higher. In our population, the score ranged from 12.50 to 110.00, with a mean of 66.7 (22.3 SD).

The Cronbach's α coefficient (Desjeux and Zheng, Reference Desjeux and Zheng2002) was 0.88 (95% CI [0.86, 0.9]) for the entire questionnaire, 0.9 (95% CI [0.88, 0.92]) for the serenity subscale, 0.9 (95% CI [0.88, 0.92]) for the resilience subscale, and 0.9 (95% CI [0.88, 0.92]) for the autonomy subscale. McDonald's Omega coefficient was 0.87 (95% CI [0.82, 0.9]) for the entire questionnaire, 0.9 (95% CI [0.88, 0.92]) for the serenity subscale, 0.89 (95% CI [0.86, 0.92]) for the resilience subscale, and 0.73 (95% CI [0.66, 0.79]) for the autonomy subscale. This confirmed the high coherence of our score.

The readability of the questionnaire was considered excellent (SMOG = 4.73).

The CFA diagram is presented in Figure 3. The TLI was 0.908 and the CFI was 0.931, but the RMSEA was slightly above 0.08 (0.099). The poorer fit indicated by the RMSEA might have been due to the low number of items, as the RMSEA tends to be poorer in this situation (Kenny and McCoach, Reference Kenny and McCoach2003).

Fig. 3. CFA diagram. The diagram presents factor loading on each subscale. F1 presents autonomy, F2 presents serenity, and F3 presents resilience.

Validity construct

The 11-item questionnaire correlated negatively and moderately with the PSS −0.561 (95% CI [−0.637, −0.473]), positively and moderately with the mental dimension of the SF-12 (95% CI 0.551 [0.459, 0.631]), and poorly with the WB12 0.249 (95% CI [0.133, 0.358]), the physical dimension of the SF-12 0.372 (95% CI [0.261, 0.473]), and the satisfaction EVA 0.163 (95% CI [0.044, 0.277]).

The MCID according to the standard deviation method was 11.1.

Reliability

Thirty-nine individuals participated in the test–retest analysis, of whom 23 did not present any event between the two tests. The ICC was 0.985 (95% CI [0.453, 0.997]), indicating good reliability. The Bland and Altman diagram (Figure 4) showed that the difference between the two answers did not depend on the mean.

Fig. 4. Bland and Altman diagram. Each dot represents one test–retest patient.

None of the patients declared any event (personal, medical, and professional) that could have interfered.

The final cross-culturally adapted questionnaire is presented in Table 2.

Transcultural validation in US English

An American English version of the questionnaire was developed by translation and transcultural validation according to the ISPOR task force recommendation (Wild et al., Reference Wild, Grove and Martin2005).

Thus, we obtained one version that is conceptually equivalent to the original: comparable across languages, culturally relevant to the context of the target country, and easily understood by the people to whom the translated instrument is administered

The cognitive debriefing did not result in any major changes of the wording of the questions. Some questions were changed to be clearer or easier to understand by reforming sentences and changing word order. For example, the item “Currently, I feel like I'm taking better care of myself” was preferred over “Currently, I enjoy taking care of myself” in order to take the notion of the patient's feelings into account.

Name of the tool

The questionnaire thus constructed is a reflection of the patient's feelings, and it is quite natural that the name “Patient Centricity Questionnaire” (PCQ) was retained and validated by the Scientific Committee.

Discussion

We have developed an instrument with good internal and external validity to measure the impact of SE on the quality of life.

Interest in instruments for measuring patients’ feelings through the so-called quality of life questionnaires in clinical trials has developed rapidly in the context of the consideration of PROs (Bland and Altman, Reference Bland and Altman1986; Weir, Reference Weir2005; Saghatchian et al., Reference Saghatchian, Lacas and Charles2021).

At the end of the 2000s, both the US) and European drug regulatory agencies published recommendations for the development of PRO measures in clinical trials.

We know that nonspecific questionnaires (SF12: Bradley, Reference Bradley and Gamsu1994 or EQ5D: Balieva et al., Reference Balieva, Kupfer and Lien2017 among the most used) exist, but if they are of major interest to allow comparison between two exposed populations, they are often not sensitive enough to assess specific domains.

Many specific questionnaires have been created to develop tools that are more sensitive to change. This is the case in cancerology, where specific questionnaires for oncology were created to begin with. In a second phase, specific questionnaires for certain cancers were created in order to understand the impact of a treatment on patients more thoroughly.

This is also the case in dermatology, where generic questionnaires, such as the DLQI (Finlay and Khan, Reference Finlay and Khan1994) or the SkinIndex (Chren et al., Reference Chren, Lasek and Quinn1996), are widely used to compare skin diseases between them, but where specific tools have also recently been published for common dermatoses, such as acne or psoriasis (Ezzedine et al., Reference Ezzedine, Fougerousse and Aubert2020; Dréno et al., Reference Dréno, Khammari and Seité2021), or less frequent ones, such as vitiligo, ichthyosis, or hemangioma (Dufresne et al., Reference Dufresne, Hadj-Rabia and Meni2013; Boccara et al., Reference Boccara, Meni and Leaute-Labreze2015; Salzes et al., Reference Salzes, Abadie and Seneschal2016).

Saghatchian pointed out (Saghatchian et al., Reference Saghatchian, Lacas and Charles2021) that no study had formally demonstrated the improvement in the quality of life by SA, recognizing that studies regarding this approach are difficult to implement according to scientific standards, as no specific tools exist to measure the impact of SA.

It was, therefore, important to create a specific tool to objectively and reproducibly evaluate supportive care in general and ADT in particular.

The PCQ is a short questionnaire that has been constructed according to recommendations and meets the prerequisite for this type of questionnaire.

Its short format (11 questions) and simplicity of use allow it to be used by a large number of people.

This questionnaire provides an answer by making a simple, reliable, easy-to-use, and validated tool available to research teams. It makes “randomized studies (…) to prove the impact of SE on quality of life.” possible (Buiret et al., Reference Buiret, Sandonato and Chidiac2021).

Due to the lack of references in literature, SE has recently been classified as wellness care, not supportive care, by the French National Cancer Institute (INCa).

The INCa is the French government agency for health and scientific expertise in cancer, responsible for coordinating actions in the fight against cancer.

The fact that it is placed under the supervision of both the Minister of Health and the Ministry of Research makes it an institution with a central role. It is the equivalent of the National Cancer Institute (NCI) in the USA.

This new tool should help to reconsider this classification. The questionnaire has been validated in the context of SE, but its construction allows us to speculate that it could also be a tool for evaluating various support care services offered to patients as part of their treatment.

The Cronbach's α coefficient found was of good quality since it was close to 0.9 for both the questionnaire as a whole and for its dimensions.

This coefficient is comparable to those found for other questionnaires widely used in many studies, which were used for external validity: the evidence of internal consistency of the revised SF-12 was considered sufficient (Cronbach's α coefficient of 0.72–0.89) (Resnick and Parker, Reference Resnick and Parker2001), for the WBQ 12, the internal consistency, measured by Cronbach's α coefficient, was 0.86 (Watrowski and Rohde, Reference Watrowski and Rohde2014), and for the PSS, several studies carried out in the general population in various countries showed that Cronbach's α coefficient was between 0.75 and 0.91. (Yokokura et al., Reference Yokokura, Silva and Fernandes2017).

The PCQ is currently available for free in French, US English, Brazilian, Portuguese, and Italian (Supplementary material).

Terms of use are available from the Fondation L'Oréal () or from the corresponding author.

The questionnaire form can be accessed by scanning the QR code: .

Data availability statement

All data are available upon request.

Acknowledgments

The authors thank the participating patients, the doctors, the socio-aestheticians, the CEW Association, and the Departmental Committee of the Alpes-Maritimes Cancer League Association who distributed and administered the questionnaire. The authors also thank the following experts for their essential role in the realization of this project: Olivier Le Floch, Irma Bourgeon-Ghittori, Messaline Bouquet, Gilles Calais, Pierre-Marie Bougard, Stéphanie Nouveau, Francesca Vincenez, Ludovic Gicquel, Anne-Béatrice Junière, Michèle Verschoore, Sylviane Balustre, Aude Desanges, and the team of CODES Association.

Author Contributions

C.T. wrote the protocol and its appendices, performed the statistical analysis, and wrote the publication. D.G., G.B., C.G., M.S., and I.K. validated the protocol, recruited the patients, and co-authored the publication. All authors approved the final version to be published.

Funding

This project was funded through financial support from the L'Oreal Foundation, which did not otherwise intervene in the project. The promoter of the project was the EMMA company.

Conflict of interest

There are no conflicts of interest to declare.

Patient consent to participate

An information note respecting French legislation was proposed. This note was validated by the ethics committee.

Ethics approval

This project obtained a favorable opinion on September 11, 2019 from the Ethics Committee of the CHU La Pitié Salpêtriere, Paris (CCP Ile de France 6- 2019-A00204-53) and was conducted according to the Declaration of Helsinki and according to French regulations for this type of research (Reference Methodology 003).

References

Balieva, F, Kupfer, J, Lien, L, et al. (2017) The burden of common skin diseases assessed with the EQ5D™: A European multicentre study in 13 countries. British Journal of Dermatology 176, 11701178.CrossRefGoogle ScholarPubMed
Bland, JM and Altman, DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet 1, 307310.CrossRefGoogle ScholarPubMed
Boccara, O, Meni, C, Leaute-Labreze, C, et al. (2015) Haemangioma family burden: Creation of a specific questionnaire. Acta Dermato-Venereologica 95, 7882.CrossRefGoogle ScholarPubMed
Bradley, C and Gamsu, DS (1994) Guidelines for encouraging psychological well-being: report of a Working Group of the World Health Organization Regional Office for Europe and International Diabetes Federation European Region St Vincent Declaration Action Programme for Diabetes. Diabetic Medicine 11, 510–516. doi: 10.1111/j.1464-5491.1994.tb00316.x.CrossRefGoogle Scholar
Buiret, G, Sandonato, S, Chidiac, F, et al. (2021) Effets antalgiques de la socio-esthétique chez les patients atteints de cancer [antalgic effects of socio-aesthetics in cancer patients]. Bulletin du Cancer 108, 10301035.CrossRefGoogle Scholar
Buiret, G, Delvigne, V, Le Dantec, G, et al. (2022) Prevalence of radiotherapy, chemotherapy and access to supportive care in cancer in France, Brazil, Russia, the USA & China. European Journal of Cancer Care. 16:e13636. doi: 10.1111/ecc.13636. Epub ahead of print. PMID: 35708175.Google Scholar
Carter, N, Bryant-Lukosius, D, DiCenso, A, et al. (2011) The supportive care needs of men with advanced prostate cancer. Oncology Nursing Forum 38, 189198.CrossRefGoogle ScholarPubMed
Carter, N, Bryant-Lukosius, D, DiCenso, A, et al. (2014) The use of triangulation in qualitative research. Oncology Nursing Forum 41, 545547.CrossRefGoogle ScholarPubMed
Cerny, BA and Kaiser, HF (1977) A study of a measure of sampling adequacy for factor-analytic correlation matrices. Multivariate Behavioral Research 12, 4347.CrossRefGoogle ScholarPubMed
Chren, MM, Lasek, RJ, Quinn, LM, et al. (1996) Skindex, a quality-of-life measure for patients with skin disease: Reliability, validity, and responsiveness. Journal of Investigative Dermatology 107, 707713.CrossRefGoogle ScholarPubMed
Cohen, S, Kamarck, T and Mermelstein, R (1983) A global measure of perceived stress. Journal of Health and Social Behavior 24, 385396.CrossRefGoogle ScholarPubMed
Contreras, A, García-Alonso, R, Echenique, M, et al. (1999) The SOL formulas for converting SMOG readability scores between health education materials written in spanish, English, and French. Journal of Health Communication 4, 2129.Google ScholarPubMed
Cronbach, LJ (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16, 297334.CrossRefGoogle Scholar
Desjeux, D and Zheng, L (2002) The itinerary method: comparing intercultural daily life – The case of Guangzhou, China. Consommation & Société. Available at: https://consommations-et-societes.fr/2002-d-desjeux-zheng-lihua-the-itinerary-method-comparing-intercultural-daily-life-the-case-of-guangzhou-china/.Google Scholar
Dréno, B, Khammari, A, Seité, S, et al. (2021) Impact of acne on the daily life of adult patients: Building a self-administered patient questionnaire. Journal of the European Academy of Dermatology and Venereology 35, 12121218.CrossRefGoogle ScholarPubMed
Dufresne, H, Hadj-Rabia, S, Meni, C, et al. (2013) Family burden in inherited ichthyosis: Creation of a specific questionnaire. Orphanet Journal of Rare Diseases 8, 28.CrossRefGoogle ScholarPubMed
Dunn, TJ, Baguley, T and Brunsden, V (2014) From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology 105, 399412.CrossRefGoogle Scholar
Ezzedine, K, Fougerousse, AC, Aubert, R, et al. (2020) Individual burden of psoriasis (I-BOP): Building and validation of a new scoring tool for patients with psoriasis. Clinical, Cosmetic and Investigational Dermatology 13, 325332.CrossRefGoogle ScholarPubMed
Finlay, AY and Khan, GK (1994) Dermatology life quality index (DLQI): A simple practical measure for routine clinical use. Clinical and Experimental Dermatology 19, 210216.CrossRefGoogle ScholarPubMed
Gries, K, Berry, P, Harrington, M, et al. (2018) Literature review to assemble the evidence for response scales used in patient-reported outcome measures. Journal of Patient-Reported Outcomes 2, 41.CrossRefGoogle ScholarPubMed
Humphreys, LG and Montanelli, RG Jr. (1975) An investigation of the parallel analysis criterion for determining the number of common factors. Multivariate Behavioral Research 10, 193205.CrossRefGoogle Scholar
Kenny, DA and McCoach, DB (2003) Effect of the number of variables on measures of fit in structural equation modeling. Structural Equation Modeling 10, 333.CrossRefGoogle Scholar
Krakowski, I (2006) Soins de support en oncologie: Concept et état des lieux [supportive care for people affected by cancer: Concept and management]. Revue du Praticien 56, 19891996.Google Scholar
Lim, LL and Fisher, JD (1999) Use of the 12-item short-form (SF-12) health survey in an Australian heart and stroke population. Quality of Life Research 8, 18.CrossRefGoogle Scholar
Mokkink, LB, de Vet, HCW, Prinsen, CAC, et al. (2018) COSMIN risk of bias checklist for systematic reviews of patient-reported outcome measures. Quality of Life Research 27, 11711179.CrossRefGoogle ScholarPubMed
Palazzo, C, Klinger, E, Dorner, V, et al. (2016) Barriers to home-based exercise program adherence with chronic low back pain: Patient expectations regarding new technologies. Annals of Physical and Rehabilitation Medicine 59, 107113.CrossRefGoogle ScholarPubMed
Resnick, B and Parker, R (2001) Simplified scoring and psychometrics of the revised 12-item short-form health survey. Outcomes Management for Nursing Practice 5(4), 161166Google ScholarPubMed
Saghatchian, M, Lacas, B, Charles, C, et al. (2021) BEAUTY and the breast: Is adjuvant chemotherapy the right time for a beauty boost? Lessons learned from a large randomized controlled trial. Quality of Life Research 31, 723732. doi: 10.1007/s11136-021-02947-6.CrossRefGoogle ScholarPubMed
Salzes, C, Abadie, S, Seneschal, J, et al. (2016) The vitiligo impact patient scale (VIPs): Development and validation of a vitiligo burden assessment tool. Journal of Investigative Dermatology 136, 5258.CrossRefGoogle ScholarPubMed
Seidenberg, M, Haltiner, A, Taylor, MA, et al. (1994) Development and validation of a multiple ability self-report questionnaire. Journal of Clinical and Experimental Neuropsychology 16, 93104.CrossRefGoogle ScholarPubMed
Terwee, CB, Jansma, EP, Riphagen, II, et al. (2009) Development of a methodological PubMed search filter for finding studies on measurement properties of measurement instruments. Quality of Life Research 18, 11151123.CrossRefGoogle ScholarPubMed
Watrowski, R and Rohde, A (2014) Psychological well-being of gynecologic and obstetric patients: A validation of the 12-item well-being questionnaire (W-BQ12). Wiener Klinische Wochenschrift 126(17–18), 524531. doi: 10.1007/s00508-014-0569-6.CrossRefGoogle Scholar
Weir, JP (2005) Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. The Journal of Strength and Conditioning Research 19, 231240.Google ScholarPubMed
Wild, D, Grove, A, Martin, M, et al. (2005) Principles of good practice for the translation and cultural adaptation process for patient-reported outcomes (PRO) measures: Report of the ISPOR task force for translation and cultural adaptation. Value in Health 8, 94104.CrossRefGoogle ScholarPubMed
Yokokura, AVCP, Silva, AAMD, Fernandes, JKB, et al. (2017) Perceived stress scale: Confirmatory factor analysis of the PSS14 and PSS10 versions in two samples of pregnant women from the BRISA cohort. Cadernos de Saúde Pública 33(12), e00184615. doi: 10.1590/0102-311X00184615.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Population description

Figure 1

Table 2. Presentation of the questionnaire and EFA

Figure 2

Fig. 1. Interitem correlation matrix.

Figure 3

Fig. 2. Screen plot. The number of factors is determined by comparing resampled data and actual data, keeping dimensions where actual data are greater than resampled data.

Figure 4

Fig. 3. CFA diagram. The diagram presents factor loading on each subscale. F1 presents autonomy, F2 presents serenity, and F3 presents resilience.

Figure 5

Fig. 4. Bland and Altman diagram. Each dot represents one test–retest patient.