Validity of the French version of the Autonomy Preference Index and its adaptation for patients with advanced cancer.

BACKGROUND: While patient-centered care is recommended as a key dimension for quality improvement, in case of serious illness, patients may have different expectations regarding information and participation in medical decision-making. In oncology, anticipation of disease worsening remains difficult, especially when patient's preferences towards prognosis medical information are unclear. Valid tools to explore patients' preferences could help targeting end-of-life discussions, which have been shown to decrease aggressiveness of end-of-life care. Our aim was to establish the validity and reliability of the French version of the Autonomy Preference Index (API) among patients with incurable cancer and in primary care setting. Three supplementary items were specifically developed to evaluate preparedness to anticipate disease deterioration among patients with incurable cancer.
METHODS: The psychometric properties of the API translated into French were assessed among patients consecutively recruited from January to March 2017 in the waiting rooms of 19 general practitioners (N = 391) and in an oncology (N = 187) clinic in Paris. Relationships between the newly-developed items and the API subscale scores were studied.
RESULTS: A three correlated factors confirmatory model (two factors related to decision-making and a factor related to information-seeking preferences) showed an acceptable fit on the whole sample and no measurement invariance issue was found across settings, age, sex and educational level. Internal consistency and test-retest reliability were acceptable for the information-seeking and decision-making subscales. One of the newly-developed items on patients' ability to anticipate a decision on the use of artificial respiration if a sudden deterioration of their illness occurred was not related to the API subscale scores.
CONCLUSION: The French version of the API was found valid and reliable for use in general practice and oncology settings. The additional items on patient preparedness to anticipate disease deterioration can be of interest to ensure that patient values guide all end-of-life clinical decisions.

1. Introduction

Shared decision-making is a process in which a choice is jointly made by a provider and a patient or a proxy decision-maker [1]. Taking its roots in the “patient-centered care” movement in healthcare, this process was pointed to, at the turn of the millennium, as a key aim to ensure that 21st-century Health Care Systems “cross the Quality chasm” [2,3]. Consideration of patient preferences as to their level of involvement in the decision-making process has now become an ethical imperative, and has been integrated into healthcare programs and legal texts in many countries [3,4].

While patient participation in decision-making processes is essential in all medical contexts, it is particularly complex in situations of incurable illness. Many informed decisions need to be made, for example, treatment limitation or cessation, Do-Not-Resuscitate orders, place of care, etc. [5]. Information-sharing between the patient and the physician is recognized as one of the main characteristics in the definition of shared decision-making in healthcare [6]. Information on disease evolution and prognosis is a prerequisite for patients to assess the risk-benefit ratios of their therapeutic options [7].

In oncology, numerous studies have shown that patients do not receive exhaustive information on their situation maybe because delivery and receipt of this information are tricky for both parties in the sharing process [8-10]. Physicians may worry about increasing patient anxiety, as it has been shown that patients have variable expectations towards prognostic medical information [11]. This may be the reason why anticipation of disease deterioration still remains difficult for both patient and oncologist, although end-of-life discussions were already suggested several years ago to reduce the aggressiveness or invasiveness of end-of-life care by facilitating shared decisions and the traceability of do-not-resuscitate orders [12].

In this context, physicians need to adapt their communication according to patients’ expectations regarding information and their desire to be involved in decisions, and also according to their preparedness to anticipate disease deterioration [13]. For that matter, the need for an assessment of these patient’s preferences has been highlighted in the literature [4,13,14]. To our knowledge, three measurement tools aiming to assess both information preferences and the desire to participate in decision-making have already been used among patients with incurable or terminal cancer: 1) visual analog scales initially developed for patients in emergency wards [15,16], 2) the Krantz Health Opinion Survey, a self-administered 16-item questionnaire, initially developed for students, and concerning medical care in general with a focus on self-medication [17,18], and 3) the Autonomy Preference Index (API), a self-administered 23-item questionnaire, initially developed for patients in primary care settings [19].

The API has various advantages to be used among patients with incurable cancer over the two other measurement tools identified. First, it does not focus on self-medication contrary to the Krantz Health Opinion Survey. Second, its psychometric properties have already been studied in English and German in various populations (primary care settings, patients with asthma, mental illness, chronic pain) [20-25]. Third, its original structure allows for adaptation depending on the context as it has already been done for psychiatric patients for example [21,24,25]. Among the 23 items of its original version, 8 items assess information-seeking (IS score) preferences and the remaining 15 items assess preferences for participation in decision-making (DM) including 6 general items used to compute the DM score and 9 items related to three clinical vignettes representing different levels of severity: the upper respiratory tract illness (URI score) is used to represent a mild condition; hypertension (HBP score) for a moderately severe condition; and myocardial infarction (MI score) for a severe life-threatening condition. In some previous studies, only the 14 items related to the IS and DM scores were used [23,25,26] while in others, vignettes were adapted to the context [20,21,24]. So in our study, we aimed to validate the API in a population of patients with incurable cancer, and to develop an additional vignette with supplementary items, specifically for these patients, to evaluate their preparedness to anticipate disease deterioration, as this was not addressed in the original API.

The working objectives of this study was thus to translate the API, to evaluate its psychometric properties (reliability and construct validity) in a population of primary care patients, as for the original version, and in a population of patients with incurable cancer. We also assessed measurement invariance which is an essential property for questionnaire, as for any measurement tool, to guarantee accurate group comparisons. According to Mokkink et al. and Milsap, “a measuring device should function in the same way across varied conditions, so long as those varied conditions are irrelevant to the attribute being measured” [27,28]. We studied measurement invariance across age, sex and education level as usually performed and recommended, across French and English languages to ensure the comparability of the scores from both language versions, and across both settings (primary care patients and patients with incurable cancer) to check the likeness of the API factor structure in these settings [28-30]. The Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) guidelines were followed to report the results [31].

2. Methods

2.1. The Autonomy Preference Index and the supplementary items for preparedness to anticipate disease deterioration

A 5-point Likert scale is used to answer to the 23 items of the API (a score of 5 indicating the strongest preference) (S1 Questionnaire, S1 Table). The computation of the five scores from the API was explained in the original publication as follow: The IS and DM scores are computed as the sum of the 8 and 6 answers respectively linearly adjusted to range from 0 to 100 (strongest desire possible). The URI, HBP and MI scores are computed from the sum of the answers to the three items, linearly adjusted to range from 0 to 10 (strongest desire possible) [19].

The additional clinical vignette developed to address the preparedness of patients with advanced cancer to anticipate disease deterioration. This vignette concerns a chronic, terminal respiratory illness requiring oxygen therapy that can potentially evolve towards a sudden deterioration, requiring artificial respiration (S2 Questionnaire, Table 1). This situation was chosen to minimize the chances for a patient with advanced cancer of identifying with this situation. The three items (answers on a 5-point Likert scale) concerned the desire to participate in the advance decision on whether to use artificial respiration, preference regarding the anticipation of this decision, the ability to decide on this point at a time when the situation has not yet arisen.

Table 1

Frequencies (%) of the answers to the items of the additional clinical vignette “preparedness to anticipate disease worsening” in the ONCO group.

Additional clinical vignette: “Suppose you are suffering from a chronic, terminal respiratory disease. At home, you need oxygen therapy all the time and your movements are limited. You know that in case of sudden deterioration (for example because of a lung infection), you may have to be put on artificial respiration (a tube connected to a machine that breathes for you, while you are asleep and unconscious), without you being able to give your opinion. Regarding the decision to use this artificial respiration:”	N (%)
1—In your opinion, who should make this advance decision (at a time when the sudden aggravation has not yet occurred)? (a single answer)
· I would prefer to be left to make my own decision	5 (3)
· I would rather the decision be left to me, after having taken my doctor's advice into consideration	24 (13)
· I would rather decide together with my doctor	71 (38)
· I would prefer to let my doctor decide, once my opinion has been taken into consideration	56 (30)
· I would prefer to let my doctor decide alone	30 (16)
· Missing	1 (0)
2—Is it important for you that your doctor should discuss this decision with you in advance, in anticipation of a sudden deterioration?
· Yes, absolutely	136 (73)
· Mostly yes	41 (22)
· Neutral	3 (2)
· Mostly no	5 (3)
· No, not at all	1 (1)
· Missing	1 (0)
3—Do you think it is possible to express an opinion regarding this decision at a time when the situation has not yet arisen?
· Yes, absolutely	63 (34)
· Mostly yes	67 (36)
· Neutral	23 (12)
· Mostly no	22 (12)
· No, not at all	8 (4)
· Missing	4 (2)

2.2. Translation process

Following the steps described in the current recommendations on the cross-cultural adaptation of questionnaires [32,33], four French experts from various disciplines (palliative care, general medicine, public health, epidemiology, biostatistics, psychometrics) with good English language proficiency and two English-French bilinguals independently translated the English version of the API into French [34]. A consensus meeting was then held to reach a consensual French version of the questionnaire, on the basis of the six independent translations. The author of the first version of the API, J. Ende, was contacted to ask for permission, but he was not available to participate in the translation process. No back-translation was performed as it is not required in this context [35]. Individual semi-structured cognitive debriefing sessions (acceptability, comprehensibility and consistent interpretation across participants) were organized with 13 subjects (7 with incurable cancer and 6 without any declared illness; 8 males; 4 under 30 years, 7 aged 30 to 70 years and 2 over 70 years) who tested this version (completion time: 3 to 10 min). Minor form changes were made on some items following the content analysis of these debriefing meetings, yielding the final French version of the API (S1 Questionnaire).

2.3. Study samples

Two samples of subjects were consecutively recruited from January 2017 to March 2017: 1) in the waiting rooms of 19 general practitioners involved in the general practice network of Paris-Sud University (France) and selected to ensure representation of the various social backgrounds in the Paris area (GP sample), 2) in the oncology outpatient clinic of Cochin Hospital in Paris (ONCO sample). Cochin hospital is a tertiary care hospital treating around 4500 new cancer patients each year, with an oncology ward and three other medical specialty wards (gastroenterology, pneumology, dermatology) that have an oncologic activity of care and use the oncology outpatient clinic for ambulatory anticancer treatment and follow-up. Explanations on the study were provided to all consecutive French-speaking patients aged 18 years or older, without cognitive or psychopathologic disorders, by an independent researcher, unknown to the patients in the two settings. Patients were included in the study if they agreed to participate and, for patients recruited in the oncology clinic, if their Eastern Cooperative Oncology Group (ECOG) performance status was 2 or below and if they had incurable cancer. There was no incentive to participate to this study. This study was approved by the ethics committee “Comité de Protection des Personnes Sud-Est VI” (n°ID-RCB: 2016-A01960-51) and patients provided written informed consent to participate. Measurement invariance across the French and English language versions was studied for the IS and DM items using data from the only known study in which the API was used, involving 120 patients with incurable cancer in Australia [26].

2.4. Data collection

Using a self-administered questionnaire, the patients provided socio-demographic information including sex, age, educational level, profession and whether they were living with a partner or were single. In the ONCO sample, information on their cancer history and treatment was collected from medical files, while in the GP group, their perceived health status was collected using the following question: "Would you say that overall, your health is: excellent / very good / good / medium / poor?". The patients completed the French version of the API (and the additional vignette in the ONCO sample) and answered two questions on their global judgment concerning their information preferences (on a 4-point Likert scale) and their desire to participate in decisions (on a 5-point Likert scale) (Table 2). In the ONCO sample, patients were asked if they would agree to complete the API again at the time of their next scheduled visit (every 15–21 days).

Table 2

Characteristics and scores of the samples.

	GPsample	ONCO sample
Characteristics—N (%)	N = 391	N = 187
Age
· 40 years or younger	142 (36)	5 (3)
· 41 to 55 years	113 (29)	33 (18)
· 56 to 70 years	93 (24)	89 (47)
· Older than 70 years	43 (11)	60 (32)
Sex (Male)	132 (34)	86 (46)
Living as a couple	259 (66)	130 (71)
Social benefits	52 (13)	19 (12)
Education
·Middle school or none	78 (20)	28 (15)
· High school	136 (35)	44 (24)
· Higher education	176 (45)	109 (61)
Profession
· Shopkeepers and tradesmen	14 (4)	14 (8)
· Professionals and managers	102 (27)	75 (43)
· Office, sales, and service employees	111 (29)	44 (24)
· Skilled or unskilled manual workers	106 (27)	32 (18)
· White-collar workers	33 (9)	9 (5)
· Never worked ?	21 (5)	6 (3)
Autonomy Preference Index scores—mean (SD)
· Information-seeking score	86.8 (10.3)	85.3 (13.3)
· Decision-making score	47.6 (16.0)	45.6 (17.5)
· Clinical vignette URI	4.6 (1.8)	4.2 (1.7)
· Clinical vignette HBP	3.1 (1.7)	2.5 (1.8)
· Clinical vignette MI	3.5 (1.7)	3.2 (1.8)
Global judgement on information preferences—N (%)
· I would prefer to be informed about everything	232 (59)	138 (76)
· I would prefer to be informed if I ask for i	75 (19)	29 (16)
· I would prefer to let my doctor decide what I need to be informed abou	83 (21	13 (7
· I would prefer not to be informed	1 (0)	2 (1)
Global judgement on decision preferences—N (%)
· I would prefer to be left to make my own decisions	4 (1)	6 (3)
· I would prefer to be left to decide after taking my doctor's advice into consideration	60 (15)	20 (11)
· I would prefer to make a decision together with my doctor	201 (51)	112 (62)
· I would prefer to let my doctor decide after having taken my opinion into consideration	84 (22)	36 (20)
· I would rather let my doctor decide alone	42 (11)	7 (4)

GP: general practice, ONCO: oncologic service, URI: Upper respiratory tract illness, HBP: High blood pressure, MI: Myocardial infarction.

The characteristics of the 578 patients included are described for each sample in Table 2. In the GP sample, subjects were younger (49±17 vs 64±12 years), more frequently women, with a lower level of education and less frequently professionals or managers. In the ONCO sample, cancer had been diagnosed for a median time of 20 (8–41) months and the primary tumour sites were lung, colon and/or rectum, pancreas and ovary for 47(25%), 27(14%), 23(12%) and 22(12%) of the patients respectively. In the GP sample, 297(76%) patients rated their health as “excellent, very good or good” and 93(24%) rated their health as “medium or poor”.

2.5. Statistical analyses

Categorical data was summarized as frequencies (%) and quantitative data as means ± standard deviation or medians (first quartile–third quartile) as appropriate. For each item, we looked for ceiling and floor effects (threshold chosen a priori >95% of respondents choosing the highest and lowest categories respectively).

2.5.1. Psychometric properties of the API

The structural validity was studied using confirmatory factor analysis (CFA) with a robust estimator for categorical data, the Weighted Least Square Means and Variances adjusted [36]. Two models were fitted, as they were both previously found in the literature to possess an acceptable fit: a three-factor model (8 IS items, 6 DM items, 9 clinical vignette items [24]), and a two-factor model (8 IS items, 15 DM and clinical vignette items [19]). In the previous studies, the factor corresponding to the 8 IS items was not or poorly correlated (<0.3) to the factor(s) related to DM items [19,23,24]. Model fit was assessed using the Comparative Fit and Tucker Lewis Indices (CFI & TLI, good fit if >0.95, poor fit if <0.90, acceptable fit otherwise), the Root Mean Square Error Approximation (RMSEA, good fit if <0.06, poor fit if >0.1, acceptable fit otherwise) and models were compared using a nested model test [37].

Measurement invariance was tested consecutively across groups defined by the inclusion setting (GP or ONCO sample), age (categorized according to quartiles), sex, educational level and language version. A multigroup CFA and the classic three-step sequence were used to investigate configural, metric and scalar invariance [38,39]. We consecutively tested these three levels of invariance in fitting three different nested models having increasing constraints. For the sex invariance for example, the same model was hypothesized in both groups and the followed sequence of nested model tests was: 1) configural invariance: unconstrained factor loadings and item thresholds; 2) metric invariance: factor loadings constrained to be equal across sex groups and unconstrained item thresholds; 3) scalar invariance: factor loadings and item thresholds constrained to be equal across sex groups. Each level of measurement invariance was considered to be present if the fit indices difference, ΔCFI and ΔRMSEA, between nested models was –0.01 and 0.015 or below respectively [40-42].

Internal consistency was assessed using Cronbach’s alpha and McDonald’s omega coefficients (acceptable if ≥0.7) [43,44]. Test-retest reliability was assessed among patients in the ONCO sample who agreed to complete the API again at their next scheduled visit, using intra-class correlation coefficients (ICC, acceptable if ≥0.7) for scores on each API subscale [45]. To assess convergent validity, the association between API subscale scores and the patients’ global judgment on their information preferences and desire to participate in decisions was evaluated using a one-way analysis of variance. Finally, for hypothesis testing, mean API subscale scores were compared, using a one-way analysis of variance or Student t-tests as appropriate between patients according to sex (a priori hypothesis: lower scores among men), age (lower scores among older patients), marital status (higher scores for singles) and educational level (higher scores for higher education levels).

2.5.2. Relationships between items in the additional vignette and API subscale scores

In the ONCO sample, the relationships between answers to the items in the additional clinical vignette and the API subscale scores were studied using Kruskall-Wallis or Mann-Whitney’s tests as appropriate. Fisher’s exact tests were also used to study associations with global judgments on information preferences and the desire to participate in decisions.

Statistical tests were two-sided and a p-value>0.05 was considered significant. Analyses were performed using Stata v.14 software for data management and basic statistics and Mplus v7.4 software for the confirmatory factor analysis (CFA), which implements full information maximum likelihood to handle missing data (lower than 2% whatever the item in the whole sample) [46,47].

3. Results

The characteristics of the 578 patients included are described for each sample in Table 2. In the GP sample, subjects were younger (49±17 vs 64±12 years), more frequently women, with a lower level of education and less frequently professionals or managers. In the ONCO sample, cancer had been diagnosed for a median time of 20 (8–41) months and the primary tumour sites were lung, colon and/or rectum, pancreas and ovary for 47(25%), 27(14%), 23(12%) and 22(12%) of the patients respectively. In the GP sample, 297(76%) patients rated their health as “excellent, very good or good” and 93(24%) rated their health as “medium or poor”.

Frequencies of answers to each item in the API in the two samples are summarized in S1 Table. No floor or ceiling effect was identified and there were fewer than 2.5% missing answers to each item. Scores on each of the subscales are shown in Table 2. No difference was found concerning the DM and IS scores, but significantly higher scores were observed for the URI and HBP vignettes in the GP sample than in the ONCO sample. Frequencies of answers to each of the three items in the additional vignette in the ONCO sample are shown in Table 1. A third of the sample preferred an equally shared decision with the doctor concerning the use artificial respiration in this fictional situation, and three quarters would wish to address this point with their doctor in advance, and thought that it was possible to give their opinion on this decision at a time when the situation had not yet arisen.

The three-factor CFA model shown in Fig 1, provided an acceptable fit to the data (CFI = 0.94, TLI = 0.93 and RMSEA = 0.060, 95%CI: [0.055 to 0.065]), better (p<0.001) than the fit of the two-factor model (CFI = 0.65, TLI = 0.61 and RMSEA = 0.142, 95%CI: [0.137 to 0.146]). As revealed by the ΔCFI and ΔRMSEA, no measurement invariance issue was found across groups defined by inclusion setting, age, sex, educational level, and language version, as the highest level of measurement invariance studied (scalar invariance) was reached (S2 Table).

Fig 1

Path diagrams (with standardized coefficients) for the three factor model with fit indices using a confirmatory factor analysis (robust weighted least squares [WLSMV] estimator).

Ellipses represent unobserved latent factors, rectangles represent observed variables, single-headed arrows represent the effect of one variable on another (factor loading) and double-headed arrows represent covariance between pairs of variables. Coefficients are all statistically significant with a p-value<0.001, except *p-value = 0.039 and coefficient in grey which is not statistically significant. ε: measurement error df: degree of freedom. CFI: Comparative Fit Index. TLI: Tucker Lewis Index. RMSEA: Root Mean Square Error Approximation.

Cronbach’s alpha coefficients were 0.69 for the 6 DM items, 0.73 for the 9 items related to the clinical vignettes and 0.71 for the 8 IS items. McDonald’s omega coefficients were 0.72 for the 6 DM items, 0.73 for the 9 items related to the clinical vignettes and 0.75 for the 8 IS items. For the assessment of test-retest reliability, 96 patients from the ONCO sample completed the API again at their next scheduled visit (mean time from baseline: 17±4 days). The ICCs were 0.80 (95%CI: 0.70 to 0.87) for the DM score, 0.59 (95%CI: 0.45 to 0.71) for the URI vignette score, 0.68 (95%CI: 0.55 to 0.77) for the HBP vignette score, 0.59 (95%CI: 0.44 to 0.71) for the MI vignette score and 0.72 (95%CI: 0.70 to 0.87) for the IS score.

Results concerning convergent validity and hypothesis testing are shown in Table 3. Good convergent validity was observed for every subscale with statistically higher scores in groups defined by a stronger desire for decision-sharing and information. The a priori hypotheses were supported by the data for all patient characteristics studied on most of the subscales.

Table 3

Convergent validity and hypothesis testing: mean (SD) scores to the API subscales according to patients’ global judgement and characteristics (N = 578).

		Scores to the API subscales
	N (%)	DM	URI	HBP	MI	IS
Global judgement on decision preferences
· … to be left to make my own decisions /… to decide after taking my doctor's advice into consideration.	90 (16)	58.8(16.4)	5.3(1.8)	3.9(1.7)	4.1(1.8)
· … my doctor and I decide together	313 (55)	48.0(15.0)	4.6(1.6)	3.0(1.7)	3.5(1.6)
· … to let my doctor decide after taking my opinion into consideration / … to let my doctor decide alone	169 (30)	38.4(14.3)	4.0(1.9)	2.2(1.6)	2.9(1.7)
p-value*		<0.001	<0.001	<0.001	<0.001
Global judgement on information preferences
· … to be informed about everything	370(65)					89.2 (9.3)
· … to be informed if I ask for it	104(18)					82.4 (11.6)
· … to let my doctor decide what I need to be informed about / … not to be informed about	99(17)					80.1(13.9)
p-value*						<0.001
Gender
· Male	218(38)	43.7(15.1)	4.4(1.8)	2.6(1.7)	3.3(1.8)	85.3(11.7)
· Female	360(62)	49.0(17.0)	4.6(1.7)	3.1(1.8)	3.5(1.7)	87.0(11.1)
p-value**		<0.001	0.310	0.002	0.201	0.081
Age
· 40 years or younger	147(25)	50.4 (16.2)	4.5(1.6)	3.2(1.7)	3.4(1.6)	88.1(9.0)
· 41 to 55 years	146(25)	48.0(15.3)	4.5(1.7)	3.0(1.6)	3.4(1.7)	86.9(10.7)
· 56 to 70 years	182(31)	46.4(16.7)	4.5(1.9)	2.8(1.5)	3.3(1.9)	84.8(13.0)
· Older than 70 years	103 (18)	41.4(16.9)	4.3(1.8)	2.5(1.8)	3.5(1.8)	85.7(12.0)
p-value*		<0.001	0.655	0.039	0.884	0.066
Living as a couple
· No	186(32)	47.8 (16.3)	4.8(1.9)	3.2(1.8)	3.5(1.7)	85.2(11.2)
· Yes	389(68)	46.5(16.6)	4.3(1.7)	2.8(1.7)	3.3(1.7)	86.9(11.4)
p-value**		0.379	0.001	0.004	0.176	0.095
Education level
· Middle school or none	106 (19)	40.8(16.3)	4.5(2.1)	2.5(1.9)	3.7(1.8)	83.9(12.2)
· High school	180(32)	44.3(15.9)	4.5(1.6)	2.9(1.6)	3.4(1.8)	86.5(10.5)
· Higher education	285(50)	50.9(16.0)	4.5(1.7)	3.1(1.7)	3.3(1.7)	87.0(11.5)
p-value*		<0.001	0.999	0.023	0.101	0.055

*One-way analysis of variance

**Student t-test.

DM: Decision-making preference subscale, URI: Upper respiratory tract illness clinical vignette, HBP: High blood pressure clinical vignette, MI: Myocardial infarction clinical vignette, IS: Information-seeking subscale

The relationships between answers to the items in the additional clinical vignette and the API subscale scores are shown in Table 4. The desire to participate in the advance decisions was strongly and positively related to DM and the vignette subscale scores (p<0.001), but not to the IS score (p = 0.223); preference regarding the anticipation of this decision was related to the IS score (p = 0.010) but not to other API scores (p>0.05), and the ability to decide on this point at a time when the situation had not yet arisen was not related to any of the API subscale scores (p>0.05). The same relationships (or lack of relationships) were observed with the global judgement on information preferences and desire to participate in decisions.

Table 4

Associations between answers to the items of the additional vignette on preparedness to anticipate disease worsening and Autonomy Preference Index (API) subscale scores presented as median (quartile 1 –quartile 3).

Items from the additional clinical vignette	N (%)	API subscale scores
		DM	URI	HBP	MI	IS
1—In your opinion, who should take this decision in anticipation? (when the situation of sudden aggravation has not yet occurred)?
· … my own decision / … after taking into consideration the doctor's advice	29(16)	50(42–63)	5(4–5)	3(2–4)	4(3–6)	81(75–91)
· … my doctor and I decide together	71(38)	50(38–58)	5(4–5)	3(2–4)	3(2–4)	91(78–97)
· … after taking my opinion into consideration / … my doctor decide alone	86(46)	38(29–50)	3(2–5)	2(1–3)	3(2–3)	88(78–97)
p-value*		<0.001	0.003	<0.001	<0.001	0.223
2—Is it important for you that your doctor discusses this decision with you in advance, in anticipation of a sudden worsening?
· Yes, absolutely / Mostly yes	177(95)	46(33–58)	4(3–5)	2(2–4)	3(2–4)	87(78–97)
· Neutral / Mostly no / No, not at all	9(5)	46(38–50)	5(3–6)	2(0–3)	3(0–4)	66(59–84)
p-value**		0.707	0.390	0.780	0.463	0.010
3—Do you think it is possible to give your opinion on this decision when the situation has not yet arisen?
· Yes, absolutely / Mostly yes	130(71)	46(33–58)	4(3–5)	2(2–4)	3(2–4)	91(78–97)
· Neutral / Mostly no / No, not at all	53(29)	42(33–52)	4(3–6)	2(1–3)	3(2–4)	84(75–97)
p-value**		0.079	0.282	0.121	0.845	0.250

* Kruskall-Wallis test

** Mann-Whitney’s test.

DM: Decision Making, URI: Upper respiratory tract illness, HBP: High blood pressure, MI: Myocardial infarction, IS: Information Seeking.

4. Discussion

In this study, the French version of the API showed adequate psychometric properties for use among patients in primary care settings or among patients with incurable cancer. The additional vignette specifically developed for use among patients with advanced cancer brought additional information on the patients’ preparedness to anticipate disease deterioration: while its first item (desire to participate in the advance decision to use artificial respiration) and second item (preference regarding the anticipation of this decision) correlated with the DM and IS subscale scores in the API, its third item (addressing patients’ “ability to decide on this issue at a time when the situation has not yet arisen”) did not correlate with any of the API subscales. Indeed, the API do not address the question of anticipation of end-of life decisions.

Interestingly, whereas the practice of end-of-life discussions is far from being common in France and very few patients have written their living wills [5], very few patients (0 to 2%) failed to answer these items. Research on end-of-life quality of care has recently shown that Advance Care Planning (ACP) is beneficial for shared decision-making, the traceability of do-not-resuscitate orders, and the reduction of aggressive end-of-life care [12,26,48], but that it can also disrupt coping mechanisms for some patients. Indeed, results from the Coping with Cancer study suggested that patients with such psychosocial factors as emotional numbness may have their fears rather exacerbated by end-of-life discussions, resulting in unreasonable demands of care and life-maintaining treatments [49]. Educational initiatives to improve communication and enhance implication in decision-making among seriously ill patients are therefore needed and are currently being developed in protocols interestingly involving both healthcarers and patients/caregivers perspectives [50-52]. Since this module provides additional information on patient preferences for anticipation, a theme that is not addressed by the API, and since it is well accepted by patients, our clinical vignette can be used in conjunction with the API, as a comprehensive scale to guide doctor-patient communication in the context of advanced cancer.

Concerning the original 23-item API, a three-factor CFA model was found to have a better fit to the data than a two-factor model. While two factors were initially hypothesized [19], in a recently published study, the authors rigorously assessed the structural validity of the API adjusted for the setting of mental health and also found that a three-factor model provided a better fit for the data than a two-factor model [24]. This finding is also more consistent with the API scoring system, which distinguishes the vignette scores from the 6-item DM score, suggesting that these 15 items are likely to be linked to more than one factor. In agreement with previous findings, the desire for information factor was not or poorly correlated with the decision-making factors, [19,21,23] and it was the same items (4, 6 and 20; the reversely coded items) that were found to have low loadings [25]. No further analyses were performed to assess the fit of adapted models (i.e. without these reversely coded items, as in Bonfils et al [25]), as our aim was to adapt the classic version of API into French to facilitate comparisons between studies that have already used this version. However, our results are consistent with those of previous studies and suggest that it would be interesting to carefully reconstruct this instrument to enhance its psychometric properties.

Measurement invariance was assessed precisely to guarantee that group comparisons would be accurately interpreted. In this study, we did not find any measurement invariance issues related to age, sex, educational level or population studied. This means that, for example, the URI and HBP score differences observed between the two samples studied were not due to a different interpretation of one or several items in these two vignettes according to the setting. They could result from a phenomenon of confusion, as there were many imbalanced characteristics between these two samples, or from real preference differences, but not from measurement error deriving from differential functioning of the API measurement tool between these two groups. In addition, thanks to the authors of the Australian study, [26] we were able to assess measurement invariance related to the language version (French and English) and found no issue for the 14 items, setting aside the vignettes (not included in the Australian study), meaning that a comparison of the IS and DM scores obtained using the two language versions can be accurately interpreted.

Finally, the assessment of the other psychometric properties of the original 23-item version of the API showed an acceptable level of internal consistency according to Cronbach’s alpha coefficients, an acceptable level of test-retest reliability according to ICCs, good convergent validity and adequate a priori hypothesis testing for most of the API subscales.

Of course, this study is not without limitations. First of all, the size of the sample of patients with incurable cancer was too small to accurately assess the structural validity of the API. To circumvent the difficulty in recruiting patients with an incurable illness, we decided to recruit patients in a primary care setting and to assess measurement invariance of the API across settings. This study design enabled a sample size that guaranteed the accuracy of the assessment of the structural validity across the two settings. Another limitation concerned the fact that the three vignettes were not used in the Australian study and this precluded the assessment of the measurement invariance across language versions for these vignettes. In most of the studies on the API, these vignettes are not used, and to our knowledge, our study is the first where measurement invariance across language versions has been assessed for the IS and DM scores. Finally, it would have been interesting to assess measurement invariance according to other characteristics, like for example anxiety and depression which may influence the interpretation of some items of the API. However, due to time constraints we did not collect information on depression and anxiety level in the GP sample.

5. Conclusions

Our findings suggest that the French version of the API is valid and reliable in both general practice and oncology settings, and that accurate score comparisons can be made across age, sex, educational level, setting and English and French versions. The additional vignette developed provides interesting information on the patients’ preparedness to anticipate disease deterioration, which can be of interest in the development of research on advance-care planning discussions to promote patient-centered care, ensuring that patient values guide all clinical decisions in the end-of-life period.

French version of the Autonomy Preference Index (API).

(DOCX)

Click here for additional data file.

Additional clinical vignette developed for use among patients with incurable cancer, to assess their preparedness to anticipate disease worsening.

(DOCX)

Click here for additional data file.

Frequency (%) of the answers to each item of the Autonomy Preference Index in both samples.

(DOCX)

Click here for additional data file.

Measurement invariance assessment for the three-factor model of the Autonomy Preference Index.

(DOCX)

Click here for additional data file.

Dataset.

(CSV)

Click here for additional data file.

Labels of variables in the dataset.

(XLS)

Click here for additional data file.

17 Oct 2019

PONE-D-19-15483

Assessment of information preferences and desire to participate in decision-making: validity of the French version of the Autonomy Preference Index and its adaptation for patients with advanced cancer.

PLOS ONE

Dear Doctor Rouquette,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please, see the comments of two Reviewers appended at the bottom of this letter. At this point, Reviewer #1 recommends a minor revision, whereas Reviwer #2 recommends a major revision. After my own reading of the manuscript, I rather coincide with the points raised by Reviewer #2, who has provided extensive, and I think that useful feedback about the current version of your study. Because this might be considered as a major review, please notice that a resubmission will require an additional round of reviews, and that the final outcome of the process cannot be predicted at this point. If you decide to resubmit a revised version of your manuscript, please provide either a proper answer or rebuttal to each of the suggestions that were raised by the Reviewers.

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PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Very interesting piece of research and rigorously presented. Below some comments:

Line 131: may you provide more information on medical data of the ONCO sample: years since diagnosis, type of treatments received (chemo, radio, surgery...); otherwise did you collect any measure of QoL, physical functioning and mood status? If not, I miss some discussion about how differences on these aspects may impact on preferences for DM, IS and preparedness to anticipate disease worsening... May this be a limitation regarding the generability of your findings?

Line 141: may you enhance description of how and by who patients from the ONCO sample were approached for data collection (what specialist consultation, known or unknown researcher to the patient...)?

Line 245: 8 'DM' items is maybe a typo, I think you mean IS

Line 291: I dont quite understand what you mean by 'disrupt coping mechanisms...', in turn I find this idea interestingly enough to develop it a bit further...

Line 292: 'educational initiatives' mean from the patient perspective, like psychoeducation, or from the healthcarer perspective, as in medical school programs?

Reviewer #2: The article Assessment of information preferences and desire to participate in decision-making: validity of the French version of the Autonomy Preference Index and its adaptation for patients with advanced cancer targets the validation of the Autonomy Preference Index (API). I highly appreciate such validation studies that apply confirmatory factor analysis and invariance testing. Although I see problems several major problems in the structure of the manuscript and the conclusion and handling of the results. In the next sections I further describe problems of the paper in detail.

Title: In my opinion the title is too long and should be shortened.

Abstract: I think the background should also include a quick description why such a validity study and enlargement is necessary. For me it is not clear what is meant by “a consensual French version”. In the results it should be indicated if the three-factors were correlated. As the last sentence in the results sections indicates that one new items was not correlated at all with the API, I believe the conclusion that additional items are of interest for the API is wrong, as this items clearly does not belong to the scale.

Regarding the open data statement: I don´t believe this is correct. Why are you not providing the data anonymized? Anonymized data can be shared and I would also like to so the scripts for analysis shared (e.g., in the OSF).

Introduction:

73ff you describe three questionnaires. You clearly choose API over the others for your validation study. I would appreciate a description why you choose this over the others.

In my opinion the introduction is too short and misses information about results from previous application of the API (e.g., The results of study [26] should be provided and discussed). This would help the reader to understand why you have chosen the API, why you aim a validity study and why you have developed additional items. Besides, I would like to read more about possible invariance in the introduction. After reading the introduction it is not clear, why you would (not) expect measurement invariance for gender, setting and age. A through explanation for that in the introduction (supported by previous results) is needed to understand the necessity and the aim of the study. I think the introduction needs a clear and literature based expansion on all the above named issues in order to be publishable. Also I highly recommend to at least provide research aims that clearly indicates what was assessed and expected (validation, reliability, invariance, etc.).

Methods:

L 102: ) is missing after HBP

As the term vignette can be understand differently it would be helpful if you present an example of the items you invented additionally.

I appreciate the process and description of translation.

2.3 Study samples describe the sample recruitment. What I miss in this section is a clrea description of the sample. How many participants were recruited in total? How is the age, gender, settings and educational level in this sample? Did the participants receive any incentive? How is further data distributed (health status etc.). This is all missing in the methods section and should be in detail included here.

L 159: what is qualitative data? Please elaborate further. I do not understand what of your data can/would be qualitative data (maybe due to confusing/inadequate description of the measurements: the measurement description is distributed all over the methods part and there is no general overview).

L 167: please state how many missing data you have and why you have missing data.

L 172ff: please indicate if the factors were correlated or not.

L 181: a short description of invariance would help reader that are not familiar with invariance to understand what the three invariance types are and how they are tested. I recommend a detail description here.

L 184: please rather indicate Mc Donalds omega (1999) as a reliability coefficient as it is a better estimate than Cronbachs alpha and can be directly estimated in the confirmatory models.

L 190ff: I do not understand how this (age, educational level, etc.) should be indicators for convergent and discriminant validity. Based on its definition a test for convergent validity requires a high correlation with a test that measures arguably the same construct while discriminant validity is indicated by a low correlation with a test that measures a different construct. Please re-consider if these are the correct indicators for testing convergent and discriminant validity – I don´t think so, but I am also no clinical expert – and if so please state why these indicators are correct and how they were testes (normally based on correlations, your test is not clearly understandable for me at this point). I also recommend quickly explaining convergent and discriminant validity.

Results:

Table 1 would rather be a good table for the methods section in order to describe the sample. I also don´t understand what the p-value in table 1 implicates. This clearly needs further explanation. I also do not really understand what the N is for API score, and the global judgments. Does the N displays the amount of people that have answered at all? That have answered in a specific way?

L 206: I would also highly appreciate to read more in the introduction if the different types of cancer might lead to differences in answering the questionnaire.

L 216: see my comment above. Why are there any missings – please describe?

In my opinion table 2 would be easier to understand as a graph (e.g. bar chart etc.) for each of the vignettes.

Figure 1. First, the picture quality is quite bad. Please indicate if all loadings were significantly. Was the correlation between decision making and information seeking (.10) really significant? As the introduction is quite vague and missing a lot of information for me it is not clear if the low/n.s. correlation between information seeking and the other scales is expected and how this was modeled before. Anyways from a psychometrical point of view this indicates that the three scales are not measuring the same thing or at least information seeking is something different than the other two scales. Hence I would highly recommend a careful reconstruction of the questionnaire. I recommend deleting items with very low loadings (e.g., below .30) and reconsider the third scale and its meaning for the API (as statistically it has nothing to do with the other scales). If that is expected or clinical meaningful in some way than it has to be made clear in the introduction.

L 231ff: I appreciate that it was tested for measurement invariance. Although due to the somehow confusing methods section it is not clear for me a) how big the single groups are and b) what cut-off were made (e.g., What cutoff was applied for age? And how was that cutoff selected). That has to be clearly stated.

L 244: as said above I highly recommend the use of McDonalds omega instead of alpha.

L 251: what is concurrent validity? This term is new here and was not introduced before. Why are you reporting a priori hypothesis down here, if you don´t report them in the end of the introduction? Please be consistent here.

Table 3. Due to the lacks in the introduction and methods I have problems of following what is what here. Where do I find the three scales of figure 1 in this table? Why is the clinical vignette now divided in three other scales even though it was one scale in figure 1. I highly recommend a better overview (as already stated) and consistent labeling. Besides, this table should be referenced before the invariance testing (maybe even as descriptive statistics in the methods) as I guess these are the groups you refer to in the invariance testing?

L 263ff: I don´t see any relationships in the table but rather quite un-informative descriptive statistics again. Please report correlations – I also recommend reporting them as heat maps to better visualize. Besides, as said above, please use consistent labeling.

L264ff: where is this relation you are talking about? How big are they? Please state r and p.

Discussion:

L277: For this conclusion I need to see a re-considered scale or a very good theoretical explanation why information seeking is not correlated with the other factors.

L279ff: you do not show that? How did you proved incremental validity of your vignette? Please state that differently or provide prove of any incremental validity over the existing scale.

L 285ff: I do not see the benefit of a vignette that is not correlated with nothing. This is no prove for incremental validity! It is not clear what this vignette is measuring in a psychometric way and I would highly recommend to re-consider its use at all.

L287ff: why did you thought that? Any empirical proof (please cite it here) or just a feeling?

L296ff: why? Please elaborate on how this vignette can do that. From a psychometrical point of view I rather see it questionable (due to its correlational results) and doubt its meaning.

L310ff: I appreciate that you mention loading problems and the low correlations between the subscales. But I think this really implies further analysis. The reason not to dig too deep into modelling issue because of “adapting the classic version” seems quite weak. Arguably the classic version comes along with problems (or at least some items have major problems). So why not improve the scale in order to measure the construct even better, more valide and more reliable?

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Reviewer #1: Yes: Alejandra Cano Carmona

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

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Submitted filename: Review_PlosOne.docx

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21 Nov 2019

A rebuttal letter that responds to each point raised by the academic editor and reviewers has been uploaded as separate file and labeled 'Response to Reviewers'.

Submitted filename: APIvalid_ResponseToReviewers.docx

Click here for additional data file.

20 Dec 2019

PONE-D-19-15483R1

Validity of the French version of the Autonomy Preference Index and its adaptation for patients with advanced cancer.

PLOS ONE

Dear Doctor Rouquette,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Feb 03 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

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Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

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Kind regards,

Angel Blanch, Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Thank you for re-working your paper. I think the paper is much better now, easier to read and shows interesting, valuable and good results. I thank the authors for working on all my prior suggestions.

I have two minor points that has to be addressed prior to publication as I think the authors made a mistake here:

Added information (line 33-34): “A three-factor confirmatory factor model (two correlated factors related to decision-making and an uncorrelated factor related to information-seeking preferences” This is not what you report as final model in figure 1 (these are three correlated factors). Is this the final model you report? I either suggest re-working figure 1 towards your final model (as this is the only model you display it is misleading) if it is not the final model. If figure 1 is the final model you have to re-write the passage accordingly and report three correlated factors. For clarification: the factor information seeking shows only small/no correlation with the other factors. Nevertheless, the model has to be declared as three-correlated factors as you allow the factors to correlate (maybe this was the mistake here?). This indicates: three-correlated factor model that as a result shows that one factor is not/smally correlated with the others.

Added information in Line 243-244: Again the factors were allowed to be correlated but as a result they only showed small/no significant correlation. Please be consistent here.

**********

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Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: PONE-D-19-15483R1.docx

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21 Dec 2019

Reviewer #2: Thank you for re-working your paper. I think the paper is much better now, easier to read and shows interesting, valuable and good results. I thank the authors for working on all my prior suggestions.

I have two minor points that has to be addressed prior to publication as I think the authors made a mistake here:

Added information (line 33-34): “A three-factor confirmatory factor model (two correlated factors related to decision-making and an uncorrelated factor related to information-seeking preferences” This is not what you report as final model in figure 1 (these are three correlated factors). Is this the final model you report? I either suggest re-working figure 1 towards your final model (as this is the only model you display it is misleading) if it is not the final model. If figure 1 is the final model you have to re-write the passage accordingly and report three correlated factors. For clarification: the factor information seeking shows only small/no correlation with the other factors. Nevertheless, the model has to be declared as three-correlated factors as you allow the factors to correlate (maybe this was the mistake here?). This indicates: three-correlated factor model that as a result shows that one factor is not/smally correlated with the others.

� Yes you are right, we fixed this mistake in the abstract as the model depicted in the figure 1 is the final model (line 31-34) : “A three correlated factors confirmatory model (two factors related to decision-making and a factor related to information-seeking preferences) showed an acceptable fit on the whole sample and no measurement invariance issue was found across settings, age, sex and educational level.”

Added information in Line 243-244: Again the factors were allowed to be correlated but as a result they only showed small/no significant correlation. Please be consistent here.

� We also modified this sentence to be more consistent (line 357-359) : “In agreement with previous findings, the desire for information factor was not or poorly correlated with the decision-making factors, [19,21,23] and it was the same items (4, 6 and 20; the reversely coded items) that were found to have low loadings [25].”

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

� We used PACE to ensure that the Figure 1 (APIvalid_Figure1.tif) meet PLOS requirements.

Submitted filename: APIvalid_ResponseToReviewers.docx

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31 Dec 2019

Validity of the French version of the Autonomy Preference Index and its adaptation for patients with advanced cancer.

PONE-D-19-15483R2

Dear Dr. Rouquette,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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Angel Blanch, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

3 Jan 2020

PONE-D-19-15483R2

Validity of the French version of the Autonomy Preference Index and its adaptation for patients with advanced cancer.

Dear Dr. Rouquette:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Angel Blanch

Academic Editor

PLOS ONE