domain: sdv shs

text:
MD Astrid Chevance
email: astrid.chevance@gmail.com

MD, PhD Axel Fortel

BSc Adeline Jouannin

MSc, MD Faustine Denis

MSc, MD; Marie-France Mamzer

MD, PhD Philippe Ravaud

MD, PhD Stephanie Sidorkiewicz

©astrid Chevance

Acceptability of and Willingness to Take Digital Pills by Patients, the Public, and Health Care Professionals: Qualitative Content Analysis of a Large Online Survey

Keywords: acceptability, health technology assessment, clinical effectiveness research, ethics, digital pill, digital health, digital therapeutics, ingestible sensor, adherence

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Introduction

More than one-third of people worldwide live with at least 2 chronic conditions; hence, an increasing number of people are receiving long-term treatment [START_REF]Chronic disease morbidity[END_REF]. Control of many of these conditions depends on adherence to treatment, which can be defined as the degree to which the use of medication by the patient corresponds with the prescribed regimen [START_REF]Adherence to long-term therapies: Evidence for action[END_REF]. However, about half of patients with chronic conditions do not take their medications as prescribed. Poor treatment adherence leads to a range of negative consequences such as poor control of disease, life-threatening events, treatment resistance, and increasing costs [START_REF] Cutler | Economic impact of medication non-adherence by disease groups: a systematic review[END_REF][START_REF] Bramley | Relationship of blood pressure control to adherence with antihypertensive monotherapy in 13 managed care organizations[END_REF][START_REF] Smith | Adherence to antiretroviral HIV drugs: how many doses can you miss before resistance emerges[END_REF][START_REF] Ho | Effect of medication nonadherence on hospitalization and mortality among patients with diabetes mellitus[END_REF][START_REF] Vanhove | Patient Compliance and Drug Failure in Protease Inhibitor Monotherapy[END_REF][START_REF] Yao | Effect of Adherence to Oral Anticoagulants on Risk of Stroke and Major Bleeding Among Patients With Atrial Fibrillation[END_REF]. In 2003, the World Health Organization suggested that improving treatment adherence would have a greater impact than any improvement in specific medical treatments, and this has led to a continuous search for effective interventions to monitor and improve medication adherence (eg, blood drug dosage, self-reported patient diaries, smart pill dispensers) [START_REF]Adherence to long-term therapies: Evidence for action[END_REF][START_REF] Nieuwlaat | Interventions for enhancing medication adherence[END_REF][START_REF] Zijp | Smart Medication Adherence Monitoring in Clinical Drug Trials: A Prerequisite for Personalised Medicine?[END_REF].

The most recent monitoring tool, approved in 2017 by the US Food and Drug Administration, is called a "digital pill." Digital pills are pills combined with a sensor, which sends a signal to a patch connected to the smartphone of the patient when the pill is ingested. Health care professionals and caregivers can access patient data (eg, adherence, activity, heart rate) from digital pills online via their own interface, thus allowing them to check whether a patient took the drug. The sensor is an ingestible event marker made from a copper-magnesium pair of electrodes within a silicon insulating skirt disk 5 mm in diameter and 0.3 mm thick. On contact with gastric fluid, the sensor sends a unique digital code to allow identification and timestamping of the medication and dose form [START_REF] Plowman | Digital medicines: clinical review on the safety of tablets with sensors[END_REF]. The first digital pill was an antipsychotic (aripiprazole) used for schizophrenia or bipolar disorder treatment, which was rapidly followed by a range of other digital pills for multiple medical conditions (eg, antihypertension, diabetes, viral diseases) [START_REF] Bittner | Connected drug delivery devices to complement drug treatments: potential to facilitate disease management in home setting[END_REF].

Digital pills have been developed for the stated goal of improving medication adherence and optimizing treatment management; these are used to identify nonadherence to first-line therapies before more expensive second-line therapies can be considered [START_REF] Zijp | Smart Medication Adherence Monitoring in Clinical Drug Trials: A Prerequisite for Personalised Medicine?[END_REF][START_REF]How does Proteus Discover Work[END_REF]. The European Medicines Agency declared that the evaluation for the digital pill submitted was inadequate and withdrew the application on July 26, 2020; the quality of the available studies (observational studies or small trials) and the lack of clinical relevance of the outcomes (short-term outcomes related to adherence to digital pills, safety outcomes restricted to tolerance of the patch) were points of criticism that led to this withdrawal [START_REF] Bittner | Connected drug delivery devices to complement drug treatments: potential to facilitate disease management in home setting[END_REF][START_REF] Cosgrove | Digital aripiprazole or digital evergreening? A systematic review of the evidence and its dissemination in the scientific literature and in the media[END_REF][START_REF] Frias | Effectiveness of Digital Medicines to Improve Clinical Outcomes in Patients with Uncontrolled Hypertension and Type 2 Diabetes: Prospective, Open-Label, Cluster-Randomized Pilot Clinical Trial[END_REF][START_REF] Osterberg | First Clinical Evaluation of a Digital Health Offering to Optimize Treatment In Patients With Uncontrolled Hypertension and Type 2 Diabetes[END_REF][START_REF] Egilman | Digital medicine systems: an evergreening strategy or an advance in medication management?[END_REF].

Moreover, guidelines for the evaluation of health technologies recommend taking into account patient and public perspectives, which has not been done yet for digital pills [START_REF] Gagnon | Introducing patients' and the public's perspectives to health technology assessment: A systematic review of international experiences[END_REF]. Acceptability is a multifaceted construct that reflects the extent to which people delivering or receiving a health care intervention consider it appropriate based on anticipated, present, or retrospective responses to the intervention [START_REF] Sekhon | Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework[END_REF]. It includes the extent to which the intervention is perceived likely to achieve its purpose (perceived clinical effectiveness), the amount of effort required to participate in the intervention (perceived burden), the extent to which the intervention aligns with individual values (perceived ethicality), the extent to which benefits/values must be compromised to engage in the intervention (perceived opportunity), and how people feel about the intervention (affective attitude) [START_REF] Sekhon | Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework[END_REF].

As part of new health technology assessment, this study aims at evaluating the prospective acceptability of and willingness to take digital pills by 3 subpopulations (patients, public participants, and health care professionals).

Methods

We conducted an online survey by recruiting a representative sample of the French general population, dichotomized into patients and public participants, and an additional convenience sample of health care professionals. The survey included 5 open-ended questions related to the acceptability of digital pills and 1 close-ended question regarding the willingness to take digital pills (Multimedia Appendices 1 and 2).

Participants and Recruitment

Patients were adults (≥18 years old) with at least one self-reported chronic condition for >6 months and who were prescribed long-term treatment for >1 month. Public participants included adults (≥18 years old) who did not meet the eligibility criteria to be classified as patients. Health care professionals were professionals prescribing, delivering, or monitoring pharmaceutical treatments (physicians, nurses, pharmacists, and midwives). All participants were living in France, spoke French, and had access to the internet. We used the 2 distinct methods to recruit participants:

•

The representative sample was recruited using a quota sampling method in the IPSOS Access Panel [START_REF]Ipsos Online Access Panels[END_REF]. Quotas were based on the known profile of the French population in terms of sex, age, socioprofessional category, and population density of the residential area. This sample was secondarily classified into patients and public participants according to the eligibility criteria. We calculated weights with the rim weighting method-raking (Multimedia Appendices 3) [START_REF] Kalton | Weighting methods[END_REF].

•

The additional convenience sample of health care professionals was recruited via an online campaign by sending emails to professional associations and posting advertisements on social networks (Multimedia Appendices 4).

All participants provided informed electronic consent before enrollment. The Institutional Review Board CERAPHP.5, Paris, France, gave ethical approval (IRB0001198).

To recruit patients with various combinations of chronic conditions and socioeconomic status, perform quantitative analysis using logistic regression, and ensure that data saturation was reached based on previous experience with an online survey and considering the fact that 34.5% of the French population lives with a chronic condition, we targeted a representative sample of 2000 participants [START_REF] Tran | Predicting data saturation in qualitative surveys with mathematical models from ecological research[END_REF][START_REF] Chevance | Identifying outcomes for depression that matter to patients, informal caregivers, and health-care professionals: qualitative content analysis of a large international online survey[END_REF]. Regarding the convenience sample of health care professionals, we decided to stop recruitment after reaching 95% data saturation [START_REF] Tran | Predicting data saturation in qualitative surveys with mathematical models from ecological research[END_REF].

Survey Development and Data Collection

We conducted a preliminary qualitative study to draft the questions (wording, formatting, and content) of the survey and provide the investigators with a contextual framework for analyzing and interpreting textual data. A researcher trained in qualitative methods (AC) conducted face-to-face collaborative interviews with 5 patients, 5 public participants, and 3 health care professionals (Multimedia Appendix 5). From the results of this preliminary study, we developed an illustrated explanation of digital pills, 5 open-ended questions on the acceptability (Textbox 1) and 1 close-ended question on the willingness to take digital pills ("Would you agree to use this device for yourself?") (Multimedia Appendices 1 and 2).

Textbox 1. Open-ended questions to all participants on the acceptability of digital pills.

•

What do you think of this device (transmitter + Bluetooth patch + smartphone app + access to data)? We want to know your immediate reaction: try to write down all the ideas that came to you when you first saw this device.

•

The manufacturer says that this device will allow for greater consistency between the prescription and the actual taking of medications. In your opinion, why would a person take their treatment more consistently if they were equipped with this device?

In addition, we collected sociodemographic data (eg, sex, age, level of education) for patients and public participants, professional status data (profession and duration of professional experience) for health care professionals, and health characteristics for all participants (eg, chronic condition, current use of a connected device to collect health data) (Multimedia Appendices 1 and 2).

The survey for patients and public participants was available online in a dedicated IPSOS platform. The survey for health care professionals was available in a LimeSurvey form. Both surveys were tested online for usability, clarity, and wording in a convenience sample of 10 patients, 20 public participants, and 5 health care professionals, whose feedback helped improve the final version.

Analyses

Acceptability of Digital Pills

We conducted a multiple-round qualitative content analysis of each free-text response by following a 3-step approach: inductive open coding of all units of meaning related to the acceptability of digital pills, inductive condensation of the codes, and inductive development of the themes and deductive classification of the themes in the 5 dimensions of acceptability [START_REF] Sekhon | Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework[END_REF][START_REF] Graneheim | Methodological challenges in qualitative content analysis: A discussion paper[END_REF].

In the first step, the team of coders (AC, AF, AJ, FD) read and reread the responses at the individual level (all responses to all questions individual by individual) and at the question level (all responses for all individuals question by question). The process of coding identified in each response units of meaning and assigned a code. A unit of meaning was defined as any expression in the text related to the acceptability of digital pills, as explained by Sekhon et al [START_REF] Sekhon | Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework[END_REF]. The coding was limited to the manifest content of the responses, except for the first open-ended question on the emotional reaction to the digital pill, for which the latent emotional content was interpreted when possible [START_REF] Hsieh | Three approaches to qualitative content analysis[END_REF]. The second and third steps occurred in a meeting in which the 4 coders and SS inductively condensed all the codes using semantic, psychological, and anthropological considerations. Then, they categorized the codes inductively into themes and classified them deductively into the 5 theoretical dimensions of acceptability [START_REF] Sekhon | Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework[END_REF].

We then calculated the number of citations for each code identified with the qualitative content analysis in each group using the weighted data for patients and public participants.

Data saturation was assessed for patients, public participants, and health care professionals with a mathematical model [START_REF] Tran | Predicting data saturation in qualitative surveys with mathematical models from ecological research[END_REF].

Willingness to Take Digital Pills

We calculated the number and proportion of participants who agreed to take digital pills. We estimated odds ratios (ORs) and 95% CIs using the weighted data of the representative sample to calculate the association of the willingness to take digital pills with all socioeconomic and health characteristics. We used the same data for a multivariate logistic regression model, including sex, age, socioprofessional status, residential area, chronic condition, current use of a connected device to collect health data, and ease to talk about treatment with the doctor.

For the regression, we considered the response "I do not wish to answer" to be a refusal to take digital pills. The significance threshold for P values was calculated with Bonferroni correction to correct for multiple testing.

All quantitative analyses involved using the free software R v3.3 (R Foundation for Statistical Computing), and the package "survey."

Data Sharing Statement

The deidentified quantitative data set will be shared on request (astrid.chevance@gmail.com).The textual data set will not be shared because of ethical restrictions.

Results

Between January 29, 2020, and February 5, 2020, IPSOS recruited a representative sample of 2005 participants (767 patients, 38.3%; 1238 public participants, 61.7%) (Figure 1). We recruited a convenience sample of 246 health care professionals between February 4, 2020, and April 18, 2020.

Participants

Among patients, 396/767 (51.6%) were women and the mean age was 54.6 (SD 15.6) years (Table 1). Hypertension was the most reported chronic condition (169/767, 22%), followed by diabetes (135/767, 17.6%) and chronic pain (81/767, 10.6%) (Multimedia Appendix 6). a Chronic condition was defined as at least 1 long-term treatment and 1 self-reported condition. The most common chronic conditions were hypertension, diabetes, chronic pain, thyroid disease, heart disease, asthma, and dyslipidemia. All chronic conditions are presented in Multimedia Appendix 6. b N/A: not applicable.

A total of 99/767 (12.9%) patients and 120/1238 (9.7%) public participants reported checking health data recorded by a connected device daily, and 524/767 (68.3%) patients and 902/1238 (72.9%) public participants reported rarely checking or never checking data (Table 1). Among health care professionals, there were 86/246 (35%) general practitioners, 50/246 (20.3%) psychiatrists, and 40/246 (16.3%) nurses (Table 2; Multimedia Appendix 7). b For clarity, we report the results for only the 3 most prevalent medical specialties. The other medical specialists were anesthetists, intensive care unit physicians, emergency physicians, child psychiatrists, surgeons, obstetricians-gynecologists, hematologists, neurologist, gastroenterologists, dermatologists, endocrinologists, oncologists, pneumologists, infectious diseases specialists, rheumatologists, nephrologists, pediatric care specialists, palliative care specialists. c Chronic condition was defined as at least 1 long-term treatment and 1 self-reported condition.

Acceptability of Digital Pills

The qualitative content analysis of the 11,451 open-text responses identified 98 codes related to acceptability. Data saturation was reached for patients (99.4%), public participants (100%), and health care professionals (97.7%) (Multimedia Appendix 8). We classified the 98 codes into the 5 theoretical dimensions of acceptability: perceived clinical effectiveness (29 codes, 29%), perceived burden (6 codes, 6%), perceived ethicality (25 codes, 25%), perceived opportunity (30 codes, 30%), and affective attitude (8 codes, 8%) [START_REF] Sekhon | Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework[END_REF]. We report the most-cited codes for each dimension with the proportion of citation and participants' quotes in Table 3. Figure 2 and Multimedia Appendix 9 report all 98 codes. In Figure 2, which shows the acceptability of connected drugs, the dots represent codes regarding acceptability of treatments identified by the qualitative content analysis of the responses for 767 patients, 1238 public participants, and 246 health care professionals. The width of the line is proportional to the number of spontaneous citations of the codes by the representative sample of patients and public participants (N=2005). The overarching categories in bold correspond to the 5 dimensions of the theoretical model of acceptability by Sekhon et al [START_REF] Sekhon | Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework[END_REF]. Perceived clinical effectiveness is the extent to which the intervention is likely to achieve its purpose. Perceived burden is the amount of effort required to participate in the intervention. Perceived ethicality is the extent to which the intervention fits well with individual values. Perceived opportunity is the extent to which benefits/values must be given up to engage in the intervention. Affective attitude indicates how people feel about the intervention.

Perceived Clinical Effectiveness

Participants reported perceived benefits (11/98 codes, 11%) and harms (8/98 codes, 8%) and proposed further developments to the device to improve benefits (3/98 codes, 3%). Finally, they determined the underlying mechanisms of digital pills to improve medication adherence (7/98 codes, 7%).

Patients (105/767, 13.7%) and public participants (170/1238, 13.7%) believed that digital pills could improve follow-up. Potential harms cited were adverse events due to sensor ingestion (190/767 patients, 24.8%; 415/1238 public participants, 33.5%) or radiation from wireless technology (102/767 patients, 13.3%; 212/1238 public participants, 17.1%). The underlying mechanisms cited to lead to a potential improvement in adherence included behavioral mechanisms such as a smartphone schedule reminder (96/767 patients, 12.5%; 122/1238 public participants, 9.9%) and the pressure of surveillance (77/767 patients, 10%; 141/1238 public participants, 11.4%).

Out of the 246 health care professionals, 64 (26%) considered digital pills to be useless gadgets, and 60 (24.4%) doubted the safety of the sensor. The mechanisms most cited to lead to improved adherence were the pressure of surveillance (73/246, 29.7%) and fear of arguing with the doctor (44/246, 17.9%).

Participants described the pressure of surveillance as a disciplinary mechanism based on social desirability, fear of being reprimanded, fear of social disqualification as a "bad patient," and fear of shame or guilt. Therefore, participants raised concerns about a policing patient-doctor relationship and the meaning of care in the future.

The fear of being kept under surveillance; it is being treated like a child, I find it, and even degrading. [Patient, woman, 71 years old]

The person would take their treatment because they would know that the doctor has access to the actual taking. It is a social pressure: the doctor has particular expectations that the patient will want to respect. [Patient, woman, 19 years old]

Perceived Burden

Participants distinguished doctors' burden (2/98 codes, 2%) from patients' burden (4/98 codes, 4%).

Patients and public participants mostly cited the complexity of the device (32/767, 4.2% and 46/ 1238, 3.7%, respectively) and the wearing of a cumbersome device (34/767, 4.4% and 41/1238, 3.3%, respectively) to be burdensome. Participants (62/767 patients, 8.1%; 65/1238 public participants, 5.3%) also reported the increased workload due to the processing of a large amount of data to be a problem.

Participants (12/767 patients, 1.6%; 14/1238 public participants, 1.1%; 15/246 health care professionals, 6.1%) identified contradictions in digital pills and found it unconvincing. Participants reported that taking medication seemed easier than applying a patch, activating the Bluetooth function, and ingesting the medication, especially for people who needed assistance with taking medication (eg, older people, individuals with cognitive impairment).

There will be better monitoring if the sick person is a mobile phone enthusiast: true for the young, less obvious for the elderly. [Patient, man, 71 years old] I find it hard to imagine someone who needs monitoring of their medication intake (dependent person, elderly, etc...) having such a patch device / smartphone. [Patient, man, 36 years old]

Perceived Ethicality

Participants described whether taking a digital pill aligned with their values related to technology (7/98 codes, 7%), human rights (4/98 codes, 4%), and medical practice (8/98 codes). Participants also suggested precautions to limit the unethical use of digital pills (6/98 codes).

Regarding ethicality of the technology, patients and public participants mentioned that digital pills align with their values related to progress (59/767, 7.7% and 131/ 1238, 10.6%, respectively) and contradicted their values related to ecology (23/ 767, 3% and 44/1238, 3.5%, respectively). With respect to human rights, patients and public participants considered digital pills to be a policing tool (112/767, 14.6% and 143/1238, 11.6%, respectively) and worried about the associated intrusiveness (66/767, 8.6% and 150/1238, 12.1%, respectively). Regarding medical care, patients and public participants mostly reported concerns with confidentiality (44/767, 5.7% and 95/1238, 7.7%, respectively) and disempowerment of patients (44/767, 5.7% and 44/1238, 3.6%, respectively). To prevent the unethical use of digital pills, they requested further investigation of the associated harms and benefits (50/ 767 patients, 6.5%; 96/ 1238 public participants, 7.8%) and that the use of these pills be restricted to clinical research (9/767 patients, 1.2%; 11/1238 public participants, 0.9%).

In total, 29/246 (11.8%) health care professionals considered digital pills to be part of technological progress that aligned with their values; they mostly worried about policing (90/246, 36.6%) and intrusiveness (62/246, 25.2%).

Participants were afraid that digital pills might cause a breakdown in trust between patients and doctors (36/767 patients, 4.7%; 39/1238 public participants, 3.1%; 147/246 health care professionals, 59.8%), which is seen as the cornerstone of the patient-doctor relationship.

I don't like being kept under surveillance. There is a relationship of trust between my GP, my psychiatrist and me. This would undermine that trust because I would be policed. [Patient, woman, 51 years old] Ethically it's very questionable, it makes it look like we're 'spying on'/'policing' the patient. What about the patient's freedom? Could such a device really improve patient compliance? A good motivational interview seems more relevant. (It is better to act upstream = prevention and health promotion, therapeutic education, rather than downstream = bad compliance to be 'reprimanded') Not to mention that this would put the patient at odds vis-à-vis the doctor in case of poor compliance... And in this case, what about the doctor-patient trust relationship? [General practitioner, woman, 29 years old]

Perceived Opportunity

Participants identified advantages (6/98 codes, 6%), disadvantages (8/98 codes, 8%), and specific target populations for whom they considered digital pills would be beneficial (16/98 codes, 16%).

A total of 135/767 (17.6%) patients and 200/1238 (16.2%) public participants had an overall positive perception of digital pills, and 213/767 (27.8%) patients and 408/1238 (33%) public participants had an overall negative perception of digital pills.

Patients and public participants mostly reported real-time data (70/767, 9.1% and 181/1238, 14.6%, respectively) as an advantage and the addition of another connected device in an already saturated environment (74/767, 9.6% and 86/1238, 6.9%, respectively) as a disadvantage. Regarding potential target populations, some highlighted that digital pills were not suitable for themselves (107/767 patients, 14%; 106/1238 public participants, 8.6%) and reported mostly people with cognitive impairment (87/767 patients, 11.3%; 87/1238 public participants, 7%) or older people (48/767 patients, 6.3%; 81/1238 public participants, 6.5%) to be suitable candidates.

Health care professionals pointed out the precision of digital pills (15/246, 6.1%) and the ease to discuss treatment (eg, tolerance, benefits, adherence) (11/246, 4.5%) as advantages and the cost (41/246, 16.7%) as a disadvantage. They identified people with cognitive impairment (29/246, 11.8%) and chronic conditions (19/246, 7.8%) as the main target population.

Participants identified people living under judicial constraint as a potential target population for digital pills (1/767 patients, 0.9%; 6/1238 public participants, 0.5%; 2/246 health care professionals, 4.6%); these people were depicted as dangerous, unwilling to undergo treatment, and already under surveillance and deprived of liberty, which-according to participants-would make the ethical regimen more flexible for them:

The person will take his treatment because he is compelled to do so by a court order. He is either a delinquent or a criminal. For someone who has not broken the law, there is no reason to proceed in this way. [Public participant, man, 39 years old] I think it can be a good idea for people who are sick (Alzheimer's for example) and forget to take their medication. Or for more complex cases such as people who are dangerous to society and the doctor needs to be sure that the person '

Willingness to Take Digital Pills

In the representative sample, 647/2005 (32.3%) participants declared that they would use a digital pill: 271/767 (35.3%) patients, 376/1238 (30.4%) public participants, and 39/246 (15.8%) health care professionals. After adjustment, willingness to take digital pills by patients and public participants was significantly associated with male sex (OR 1.98, 95% CI 1.62-2.43) and integration of currently used connected devices to monitor health daily (OR 3.42, 95% CI 2.43-4.79) or rarely (OR 1.76, 95% CI 1.30-2.40), with a dose-response relationship (Figure 3). Complete analysis of other characteristics associated with the willingness to take a digital pill is presented with crude and adjusted ORs and 95% CIs in Multimedia Appendix 10. The forest plot (Figure 3) presents the ORs with their 95% CIs and the P value obtained with the logistic regression analysis of the association of the willingness to take connected drugs by sex, age, profession, population density of the residential area ("residential area"), chronic condition, frequency of health data recording with a connected device, and ease to talk about treatments with the doctor. The plot shows the number of participants per category (n) willing to take a connected drug among the total number of participants in the given category (N). The corrected threshold for statistical significance is P=.003. For the continuous variable "age," we present the mean age of the whole sample and the standard deviation. The second column present the number of people willing to take connected drugs (n) over the total number in the patient and public sample (N), except fot the variable "Age", presenting the mean and standard deviation (sd) of people willing to take connected drugs. inh.: inhabitants.

Discussion

Principal Findings

Overall, two-third of patients and public participants in this study refused to take digital pills. Their arguments were grounded in the fear of possible serious clinical and ethical harms. Health care professionals largely refused (177/246, 72%) to take digital pills citing disagreement with their professional deontology and ethics. Participants who accepted digital pills had positive a priori for technology considered as progress: people agreed to take it in the framework of research for a limited investigation time to help medical progress.

Participants who refused to take connected drugs, reported that these would be useful for other people, such as individuals with cognitive impairment, individuals with chronic conditions or mental disorders, and those incarcerated, highlighting the view that potential clinical or ethical harms would be acceptable for these already vulnerable people. Given the condition of the designated populations, the intervention may be stigmatizing and may increase vulnerability.

To our knowledge, this study is the first to explore the acceptability of connected drugs in line with the recommendation that health technology assessment take into account patient and public perspectives [START_REF] Gagnon | Introducing patients' and the public's perspectives to health technology assessment: A systematic review of international experiences[END_REF]. We used a representative sample of the French population, thus allowing for generalizable results in the subsamples of patients and the public. In France, medication for chronic conditions is fully reimbursed, so when participants answered the questionnaire, they were not prematurely restricted by individual economic concerns but could detail their preferences. To limit the risk of capturing only a "hot reaction" and to mimic the process of a rational and balanced deliberation, we used 5 open-ended questions and asked the close-ended question about willingness to use connected drugs at the end of the survey. Only 16.7% of patients and public participants found no cons and 31% found no pros.

Limitations

The first limitation is the restriction to only 1 country as a consequence of the choice to recruit a representative sample. Because culture and health care system may affect the acceptability of digital pills, further studies are required in different settings.

A common limitation of using an online survey is the risk of selection bias because of the need for internet access. However, the target population for the digital pill must have access to smartphones and the internet. While the use of an online survey may have overestimated the acceptability of digital pills in the general population, it may not have done so in the target population. Moreover, to limit potential selection bias due to reading level, we created the questionnaire during a qualitative preliminary study and tested it for clarity.

We could have increased the reliability of the results by verifying the final codes and themes with the participants, but we minimized the risk of misinterpretation by limiting the condensation of codes to synonyms only, halting the inductive interpretation at a very basic level-which led to 98 codes in the final results-and using the participants' wording.

Another limitation is that the sample of health care professionals was not representative of the larger population of health care professionals.

Finally, we only investigated the prospective acceptability because digital pills were not available in France at the time of our study. Studies about concurrent acceptability (while taking connected drugs) and retrospective acceptability (after taking connected drugs) may be complementary and lead to different results.

Comparison With Prior Work

Our results are consistent with the concurrent and retrospective acceptability discussed in 18 observational studies and trials of digital pills, which involved small samples of 5 to 129 patients [START_REF] Martani | Digital pills: a scoping review of the empirical literature and analysis of the ethical aspects[END_REF]. Moreover, some participants who refused digital pills for themselves found them useful for other people considered vulnerable (eg, people with cognitive or mental disorders or those incarcerated), which would lead to a risk of stigmatizing the use of digital pills.

This study added further ethical concerns to the well-known topics raised in the scientific literature (eg, consent, confidentiality, privacy) [START_REF] Bittner | Connected drug delivery devices to complement drug treatments: potential to facilitate disease management in home setting[END_REF][START_REF] Martani | Digital pills: a scoping review of the empirical literature and analysis of the ethical aspects[END_REF][START_REF] Gerke | Ethical and legal issues of ingestible electronic sensors[END_REF][START_REF] Véliz | Three things digital ethics can learn from medical ethics[END_REF][START_REF] Holender | Opinions on the use of technology to improve tablet taking in >65-year-old patients on cardiovascular medications[END_REF][START_REF] De Mendoza | Providers' Perspectives on Adherence to Hormonal Therapy in Breast Cancer Survivors. Is there a Role for the Digital Health Feedback System?[END_REF]. This shows the substantial importance of including patient and public perspectives in health technology assessment, as is already recommended but marginally done, with the risk of neglecting social, ethical, and political aspects of these technologies that are critical determinants of treatment effectiveness in real life settings [START_REF] Gagnon | Introducing patients' and the public's perspectives to health technology assessment: A systematic review of international experiences[END_REF]. A further strength is the use of a representative sample, which allows for generalizable results. This survey contributes to advanced scientific and clinical reflections about medication adherence. As underlined by participants, digital pills seem to be a naïve solution considering the complexity of what determines medication adherence and nonadherence [START_REF] Bittner | Connected drug delivery devices to complement drug treatments: potential to facilitate disease management in home setting[END_REF][START_REF] Sidorkiewicz | Development and validation of an instrument to assess treatment adherence for each individual drug taken by a patient[END_REF][START_REF] Gadkari | Unintentional non-adherence to chronic prescription medications: how unintentional is it really?[END_REF]. Digital pills appear to be burdensome and expensive reminders with an apparent contradiction-whether unintentional or intentional-between their complexity and the ability of those needing support for adherence. Particularly in the case of intentional nonadherence, digital pills would be either useless or efficient at the cost of intrusiveness, policing, and negative effects on the patient-doctor relationship.

Finally, digital pills could be useful to assess treatment efficacy in explanatory trials, but there are 2 prerequisites for extending their use in clinical practice. First, digital pills should be evaluated as a complex intervention according to specific standards and not as if they are a mere change in the form of drug administration [START_REF] Egilman | Digital medicine systems: an evergreening strategy or an advance in medication management?[END_REF][START_REF] Craig | Developing and evaluating complex interventions: the new Medical Research Council guidance[END_REF]. Second, there is urgent need to develop an ethical and legal framework to ensure the safe and ethical collection and use of health data through a patient-centered approach [START_REF] Bittner | Connected drug delivery devices to complement drug treatments: potential to facilitate disease management in home setting[END_REF][START_REF] Gerke | Ethical and legal issues of ingestible electronic sensors[END_REF][START_REF] Véliz | Three things digital ethics can learn from medical ethics[END_REF].

Conclusion

Our results suggest that patients, the public, and health care professionals view connected drugs not as a promising new medical device to better monitor medication adherence but as a complex intervention with a possible impact on patient-doctor relationship and patient autonomy. The participants also raised additional concerns about burden of treatment, cost-effectiveness, and privacy, which need to be addressed in further investigations. Future studies should take into account the views of all stakeholders, ie, patients, potential prescribers, as well as health regulatory authorities and researchers, to ensure the safe and ethical collection and use of health data through a patient-centered approach.

Figure 1 .

 1 Figure 1. Flowchart. HCP: health care professional. †Unweighted numbers and proportions of patients and public representatives. *Participants answered 5 open-ended questions (panel 1). We added the number of open-ended questions answered for each type of participant. **Results presented in Figure 3 and Multimedia Appendix 10.

  Depending on the patient and the medical situation 112 (45.5) Systematically for each patient with long-term treatment and at each consultation Agree to take a digital pill 39

Figure 2 .

 2 Figure 2. Acceptability of connected drugs. Dots represent codes regarding acceptability of treatments identified by the qualitative content analysis of the responses for 767 patients, 1238 public participants, and 246 health care professionals. The width of the line is proportional to the number of spontaneous citations of the codes by the representative sample of patients and public participants (N=2005). The overarching categories in bold correspond to the 5 dimensions of the theoretical model of acceptability by Sekhon et al.

Figure 3 .

 3 Figure 3. Determinants of the willingness to take connected drugs among the representative sample of patients and public participants (N=2005). The second column present the number of people willing to take connected drugs (n) over the total number in the patient and public sample (N), except fot the variable "Age", presenting the mean and standard deviation (sd) of people willing to take connected drugs. inh.: inhabitants.

Table 1 .

 1 Sociodemographic and health characteristics of the representative sample and subgroups of patients and public participants.

	Total	Patients a	Public participants
	(N=2005), n (%)	(n=767), n (%)	(n=1238), n (%)

Population density of the residential area (inhabitants)

	Rural city (<2000)	451 (22.5)	(22.3)	280 (22.6)
	2000-19,999	360 (18)	(18)	211 (17)
	20,000-99,999	276 (13.8)	(14.2)	161 (13)
	≥100,000	605 (30.2)	(29.9)	377 (30.5)
	Paris agglomeration	329 (16.4)	(15.6)	209 (16.9)
	Number

of visits to a doctor in the past year

	>10 times	208 (10.4)	(18.3)	68 (5.5)
	5-10 times	590 (29.4)	(43.8)	254 (20.5)
	<5 times	1046 (52.2)	(37.3)	759 (61.3)
	Have not seen a doctor this year	152 (7.6)	5 (0.6)	148 (12)
	Do not wish to answer	9 (0.4)	0 (0)	9 (0.7)

Ease to talk about the treatment with the doctor (eg, adherence, adverse events)

	Sociodemographic and health characteristics	Total	Patients a	Public participants
		(N=2005), n (%)	(n=767), n (%)	(n=1238), n (%)
	Easy	1767 (88.1)	(90.8)	1071 (86.5)
	Difficult	214 (10.7)	70 (9.1)	144 (11.6)
	Do not wish to answer	24 (1.2)	1 (0.1)	23 (1.9)

Skipped the long-term treatment during the past month

	Never	N/A b	496 (64.7)	N/A
	Once a week	N/A	198 (25.8)	N/A
	Several times a week	N/A	54 (7)	N/A
	Almost every day	N/A	15 (1.9)	N/A
	Never started the prescribed treatment	N/A	3 (0.4)	N/A
	Do not wish to answer	N/A	2 (0.2)	N/A
	Checking health settings recorded by connected devices
	Daily	220 (11)	99 (12.9)	120 (9.7)
	Weekly	213 (10.6)	85 (11.1)	128 (10.3)
	Monthly	143 (7.2)	59 (7.7)	84 (6.8)
	Rarely	257 (12.8)	99 (12.9)	159 (12.8)
	Never	1168 (58.2)	425 (55.4)	743 (60)
	Do not wish to answer	4 (0.2)	0 (0)	4 (0.3)
	Agree to take a digital pill
	Yes	647 (32.3)	271 (35.3)	376 (30.4)
	No	1261 (62.9)	461 (60.1)	800 (64.6)
	Do not wish to answer	97 (4.8)	35 (4.6)	62 (5)

Table 2 .

 2 Sociodemographic and health characteristics of the health care professionals (N=246).

	Health care professionals, n (%)

Table 3 .

 3 Quotes of patients, public participants, and health care professionals that illustrate some of the codes regarding acceptability of digital pills.

	Code	Patients (n=767)	(n=1238) Public participants	HCPs a (n=246)	Examples of quotes
	Congruent with val-	59 (7.7)	131 (10.6)	29 (11.8)	•	"I will try it because I have the culture of new tech-
	ue of progress					nologies." (Public participant, man, 34 years old)
					•	"I am for, because I believe in modernity and artificial
						intelligence." (Public participant, man, 43 years old)
					•	"Only by accepting certain methods can one advance
						in medicine." (Nurse, woman, 46 years old)
	Congruent with val-	12 (1.6)	30 (2.4)	9 (3.7)	•	"It's interesting, it's as close to reality as possible and
	ue of credibility					probably the truth." (Public participant, man, 31 years
						old)
					•	"There will no longer be any doubt about taking or
						forgetting to take medication, and the monitoring by
						the doctor that imposes honesty on the patient."
						(Public participant, man, 39 years old)
					•	"This helps to avoid the medical errors that often occur
						when a patient lies about taking their medication."
						(Public participant, man, 29 years old)
	Intrusiveness (con-	66 (8.6)	150 (12.1)	62 (25.2)	•	"This is spying from inside my body. I would be
	flict of value with					worried about the side effects too." (Patient, woman,
	privacy)					64 years old)
					•	"There is far too much indiscretion and invasion of
						privacy." (Public participant, woman, 55 years old)
						33 years
						old)
					•	"It is a categorical refusal, I still prefer to take a drug
						that has less effect but I will never consciously swal-
						low a capsule that allows other people to follow me
						or my lifestyle, even if already in society we are
						monitored in many areas without knowing it, my
						doctor has the right to suggest it after it is up to the
						person to accept it or not" (Patient, woman, 44 years
						old)
	Dehumanization of	32 (4.2)	46 (3.7)	41 (16.7)	•	"We're already guinea pigs and we're becoming
	patients					robots... "(Patient, man, 64 years old)
					•	"When you're sick, you're already dispossessed of
						your 'medical' life, especially in a hospital environ-
						ment, so with that on top of it, no thanks." (Patient,
						woman, 53 years old)
					•	"No thanks, I won't take any connected medication, I
						don't want to be kept under surveillance that much. It
						contributes to the dehumanisation of our society."
						(Neurologist, woman, 29 years old)
	Inconsiderate to pa-	25 (3.3)	21 (1.7)	30 (12.2)	•	"Very bad idea, we're not in a dictatorship. People are
	tient's perspective					free to take care of themselves or not. Even the sick
						are free." (Patient, man, 75 years old)
					•	"Policing, (no) more freedom for the patient to stop
						a treatment that seems to be harming him without be-
						ing observed." (Public participant, woman, 40 years
						old)
					•	"A medication such as you're presenting it to me
						makes me think of forced treatment. If we refuse to
						take the medication or forget about it will our doctor
						contact us to explain ourselves?" (Patient, woman, 25
						years old)

• "It's horrible! It feels as if it's really touching on intimacy. Ethically, it is frightening. That we use applications is one thing because we can limit its use in, in time, but a pill that we ingest is really to futuristic and too invasive." (Public participant, woman, a HCPs: health care professionals.

  s treatment has been taken. [Public participant, woman, 43 years old]

	9%; 41/246 health care professionals, 16.7%), unease (32/767
	patients, 4.2%; 70/1238 public participants, 5.7%; 7/246 health
	care professionals, 2.9%), skepticism (114/767 patients, 14.9%;
	168/1238 public participants, 13.6%; 31/246 health care
	professionals, 5.3%); fear (56/767 patients, 7.3%; 175/1238
	public participants, 14.1%; 13/246 health care professionals,
	5.3%), anger (178/767 patients, 23.2%; 255/1238 public
	participants, 20.6%; 108/246 health care professionals, 43.9%),
	and disgust (7/767 patients, 0.9%; 4/1238 public participants,
	0.3%; 1/246 health care professional, 0.4%). Because of lack
	of clarity and risk of overinterpretation, we could not code the
	affective attitude of 69/767 (9%) patients, 139/1238 (11.2%)
	public participants, and 12/246 health care professionals (4.9%).
	Compared to public participants, patients had more positive
	reactions (316/1238, 25.5% vs 241/767, 31.4%) and less
	negative reactions (672/1238, 54.3% vs 387/ 767, 50.5%).
	Compared to patients and public participants, health care
	professionals expressed more negative attitudes (142/246,
	57.7%) and less positive attitudes (51/246, 20.7%).
	Affective Attitude
	We identified 8 affective attitudes toward digital pills:
	enthusiasm (100/767 patients, 13%; 146/1238 public
	participants, 11.8%; 20/246 health care professionals, 8.1%),
	curiosity (141/767 patients, 18.4%; 170/1238 public participants,
	13.7%; 31/246 health care professionals, 12.6%), balanced
	attitude (70/767 patients, 9.1%; 111/1238 public participants,

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Acknowledgments

We thank Florence Weber for the expert advice in social anthropology and Marion Plaze for expert advice in cognitive psychology. We thank Raphaël Porcher for statistical guidance, Elise Diard for expertise in the design of the figures, Nivantha Naidoo for help in interpreting the data, and Laura Smales for copyediting the manuscript. The study received a grant from the Fondation Université de Paris (19_DON22_001_U4). The funder had no role in the study design, data collection, data analysis, data interpretation, writing of the report, or decision to publish.

Authors' Contributions

AC is the guarantor of the study. AC, AJ, SS, PhR, and M-FM conceived and designed the analysis. AC, AJ, SS, and AF collected the data. AC, AJ, SS, AF, and FD performed the analysis. AC wrote the first draft. AC, SS, PhR, M-FM, FD, AF, and AJ edited the manuscript. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. The manuscript's guarantor (AC) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as originally planned (and, if relevant, registered) have been explained. All authors confirm that they had full access to all the data in the study and accept responsibility to submit for publication.

Conflicts of Interest

None declared.

Multimedia Appendix 1

Determinants of the willingness to take digital pills.

Multimedia Appendix 7


Donna Erickson
email: ericksondonna2000@gmail.com1

Albert Rilliard
email: albert.rilliard@limsi.fr2

Yongwei Li
email: yongwei.li@nlpr.ia.ac.cn

Caroline Menezes
email: caroline.menezes@utoledo.edu

Shigeto Kawahara

Toshiyuki Sadanobu
email: sadanobu.toshiyuki.3x@kyoto-u.ac.jp

Ryôko Hayashi
email: rhayashi@kobe-u.ac.jp7

Takaaki Shochi
email: takaaki.shochi@labri.fr8

João Antônio

De Moraes

Kerrie Obert
email: kerriebobert@gmail.com

J Moraes
email: jamoraes3@gmail.com

Cross Cultural perception of Valence and Arousal

Keywords: Cross-cultural, Valence, Arousal, Acoustic analysis, Voice quality

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

The aim of this pilot study is to better understand how the perception of voice quality is affected by a speaker's language and culture. It is well-known that segmental characteristics of speech, i.e., consonants and vowels, are perceived differently depending on the language of the speaker. However, there is a growing body of research reporting that voice quality characteristics of speech may also be perceived differently, depending on the language/culture of the speaker, see e.g., [START_REF] Erickson | Cross cultural differences in arousal and valence perceptions of voice quality[END_REF]. One approach to examining these language/cultural differences is by using a Valence-Arousal-Dominance 3-Dimensional framework of emotions, e.g., [START_REF] Osgood | Cross-cultural universals of affective meaning[END_REF]- [START_REF] Goudbeek | Beyond arousal: Valence and potency/control cues in the vocal expression of emotion[END_REF]. In this paper, we look at Valence and Arousal percepts of vowel sounds produced with different voice qualities. We conducted a linear effect mixed model as well as a multifactorial analysis to ascertain which acoustic cues may be contributing to the Valence and Arousal percepts.

According to some of the previous research, voices that are loud, and high-pitched tend to be perceived as aroused/excited (e.g., [START_REF] Erickson | Cross cultural differences in arousal and valence perceptions of voice quality[END_REF], [START_REF] Goudbeek | Beyond arousal: Valence and potency/control cues in the vocal expression of emotion[END_REF]- [START_REF] Schmidt | Perception of Emotion in Conversational Speech by Younger and Older Listeners[END_REF]). Voices that are breathy [START_REF] Anikin | A Moan of Pleasure Should Be Breathy: The Effect of Voice Quality on the Meaning of Human Nonverbal Vocalizations[END_REF] or have a steep spectral slope [START_REF] Goudbeek | Beyond arousal: Valence and potency/control cues in the vocal expression of emotion[END_REF] are perceived as having positive valence. Mandarin Chinese and Japanese listeners find highpitched, less breathy voices pleasant [START_REF] Erickson | Cross cultural differences in arousal and valence perceptions of voice quality[END_REF] yet German listeners find them unpleasant [START_REF] Schmidt | Perception of Emotion in Conversational Speech by Younger and Older Listeners[END_REF]; Brazilian Portuguese listeners prefer lower pitched, breathy voices [START_REF] Erickson | Cross cultural differences in arousal and valence perceptions of voice quality[END_REF].

The languages we examine for this study are five: American English (AE), Japanese (JP), Mandarin Chinese (MC), Brazilian Portuguese (BP), and Goa Portuguese (GP), as spoken in Goa, India. The study includes results from [START_REF] Erickson | Cross cultural differences in arousal and valence perceptions of voice quality[END_REF] re BP listeners, but reports on new perception data collected using headphones from Japanese and Mandarin Chinese listeners, since the previous study collected the perception data in a classroom with loudspeakers.

METHODS

Corpus

Nine vowels (either /i/ or /ae/) were produced during an MRI study by an American English female speaker, with varying voice quality: the controlled changes were (1) the phonation mode (thick, thin, and stiff vocal folds, as described within the Estill model of voice production [START_REF] Steinhauer | The Estill voice model: theory & translation[END_REF], which roughly correspond to modal, falsetto, and breathy, respectively), [START_REF] Osgood | Cross-cultural universals of affective meaning[END_REF] vocal tract changes produced by (nasal or not) pharyngeal narrowing (resulting in a twang voice quality (see, e.g., [START_REF] Perta | A pilot investigation of twang quality using magnetic resonance imaging[END_REF]) or a lowered/backed bunching of the tongue, and (3) F0 changes (high or low F0) (see table 1 for details). Since the recordings were collected in an MRI session, which has a limited time requirement, it was not possible to do recordings of a complete set of configurations of voice settings.

Acoustic analysis

The model does not use inverse filtering, rather it fits the residual signal to the LF model to simultaneously estimate the glottal source waveform and the vocal tract shape parameters using an analysis-by-synthesis strategy (e.g., [START_REF] Li | Contributions of the glottal source and vocal tract cues to emotional vowel perception in the valence-arousal space[END_REF], [START_REF] Li | $F_0$-Noise-Robust Glottal Source and Vocal Tract Analysis Based on ARX-LF Model[END_REF]). The measurements are shown in Table 1.

Listeners

Five groups of listeners with different cultural backgrounds were recruited: [START_REF] Erickson | Cross cultural differences in arousal and valence perceptions of voice quality[END_REF] The five language groups were selected due to both their representing diverse languages, and also the location of the authors. These nine vowels were presented to the five groups of listeners, individually, through headphones, and they had to judge on a scale of 1 to 5 how "Negative" or "Positive" the sound was (if they liked the sounds, it was positive), and how "Calm" or "Excited" the sound were (5 corresponding to "Excited"). There were four randomizations of each of the nine sounds, presented through a LiveCode computer interface.

Statistics

The perceptual ratings of each of the two scales were fitted using linear mixed-effects models (using R's lme4 library [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF], [START_REF] Core | R: A Language and Environment for Statistical Computing[END_REF]) -one for each language group and each scale. The dependent variable was the answer on each scale (Arousal and Valence), and the fixed effects were the acoustics characteristics of the stimuli, as indicated in Table 1; random intercepts for each listener were included in the model. Then, the four answers given by each listener to each stimulus, for each of the two scales, were summed up and arranged into a table with one row for each subject, and one column for each stimulus and scale, thus having 105 rows x 18 columns (twice 9 stimuli) table. This table was submitted to a Multiple Factor Analysis (using R's FactoMineR library [START_REF] Husson | Exploratory multivariate analysis by example using R[END_REF]) so to analyze the main dimensions linked to the way listeners answer to these two scales, according to the acoustic specificities of each stimulus. The spread of the listeners along the 6 first axes of the MFA was used as an input for hierarchical clustering. An inertia gain indicated a 3-cluster solution.

RESULTS

Regression analysis

Tables 2 and3 present the coefficients of the linear models fitted, for each language group, to the Arousal scale (table 2), and Valence scale (table 3). AE, GP, and MC listeners gave high Arousal ratings to stimuli with high F0 and small OQ, while PB listeners relied on OQ cues only, and JP listeners on high F0, low OQ and higher spectral tilt. AE listeners tend to rate with a positive valence the stimuli with high pitch and low tilt and OQ; conversely, BP listeners rated as positive stimuli with low pitch and low tilt. GP do not show any systematic relation with acoustic characteristics for their valence judgments, while JP relied on high pitch only, and MC on low OQ only for attributing positive valence judgments.

Table 4: Main association with the three clusters obtained from the spread of the listeners along the main dimensions of the MFA: language groups more frequent within each cluster; stimuli whose rating by listeners of the cluster are significantly higher (+) or lower (-) than the mean ratings. The numbers in the cells represent the utterance number.

Cluster

Multiple Factor Analysis

The hierarchical agglomeration of individual listeners is shown on the dendrogram of Figure 2, from which was derived the three clusters. The characteristics of the stimuli (high positive or negative value given to a specific stimulus on a specific scale) significantly associated with each of these clusters are given in Table 4, with the language groups that are the most representative of each cluster (i.e., groups whose frequency within the cluster is significantly higher than the global frequency). Figure 1 presents the spread of listeners along the first two main axes of the MFA: one can show that language groups show large overlaps, but that some tendency of listeners from the same cultural background to fit on the same portion of the plane may hint for some amount of culture-specific behavior. Thus, by agglomerating all listeners on the first 6 axes, we can observe the results on a more general level representing about 80% of the variance.

Figure 2 shows how the language groups cluster, based on these first six dimensions of the MFA. Cluster #1 is predominantly composed of AE and JP listeners, cluster #2 with BP listeners, and cluster #3 with GP and MC ones.

In terms of Valence, listeners from clusters #1 and #2 tend to give opposite judgments, with the most typical stimuli for this scale being opposed systematically: (Ut5,6,7,9) were judged positive by #1 and negative by #2; (Ut1,2,3,8) were judged the other way. Listeners in cluster #3 have few associations of stimuli with the valence scale: only Ut3 was judged as positive, as was also seen for cluster #2.

For Arousal, clusters #1 and #3 tend to be opposed in their judgments, with (Ut1,3) receiving high arousal by cluster #3 and low by cluster #1, and (Ut7,9) the other way. Listeners from cluster #2 present a mixed judgment, with some oppositions and some similarities with both of the other clusters.

An interpretation of the data in terms of acoustic cues triggering the perceptions is as follows: Re Valence, AE and JP indicate a positive feeling for high F0 vowel sounds (Ut 6, 7, 9 & 5), and negative feelings for low F0 vowel sounds (Ut 1, 8, 3, & 2). BP, however, show the opposite pattern, in that they prefer low F0 vowel sounds (Ut 1, 8, 2, & 3), not high F0 vowel sounds (Ut 6, 9, 7, and 5). GP and MC show a preference for low F0 vowel sounds produced with a modal somewhat breathy voice (Ut 3).

Re Arousal, all listeners rate low F0 breathy or somewhat breathy vowels as not aroused. And, all groups (AE, JP, BP, MC and GP) rate high F0 not breathy vowels produced with twang as aroused. In addition, BP rate vowels with sustained energy in the upper frequencies are rated as aroused. They rate low breathy vowels (Ut 1) as well as high F0 somewhat breathy vowels (Ut 4) as not aroused. It is interesting that BP rate Ut 3 as aroused, but the other language groups rate it as not aroused.

As for the MC and GP groups, according to the MFA, only moderate ratings are given for arousal by these language speakers. A possible interpretation of this is that for these speakers, these specific acoustic cues are not the salient ones for perceiving Arousal for these vowel sounds.

DISCUSSION & CONCLUSIONS

The preliminary results of this study confirm that listeners from different language groups perceive voice quality changes differently. We report an ingroup similarity in the way to answer on these two scales, with listeners from each group being consistently clustered together on the basis of their answers.

A comment on OQ and spectral tilt: generally, when OQ increases, spectral tilt becomes steeper. Falsetto voice, often thought of a voice with high F0, generally has a large OQ and steep spectral tilt. However, adding pharyngeal narrowing to a falsetto voice changes the Speed Quotient (rate of increased contact of the vocal folds to decreased contact of the vocal folds per glottal cycle) [START_REF] Erickson | Interaction between phonation mode and pharyngeal narrowing: A pilot EGG study[END_REF], [START_REF] Erickson | Voice quality: Interactions among F0, vowel quality, phonation mode and phayngeal narrowing[END_REF], as occurs when a singer/speaker produces a twang phonation. The abruptness of the vocal fold closure can affect the spectral tilt [START_REF] Stevens | Prosodic influences on glottal waveform: preliminary data[END_REF].

Future work is needed to further explore these cross-cultural perceptions of Valence and Arousal characteristics of voice quality in speech; specifically, we would like to include more acoustic measurements of voice quality, as well as more groups of language listeners. The five languages studied here represent a diverse group, and we would like to add more diversity.

Voice quality differences due to language/culture has of yet not been well-investigated; however, we feel this research has valuable applications for a number of professional areas, such as teaching in general, teaching second languages, clinical work, interpersonal relationships, professional speaking, advertisement, etc., basically any situation where we use our voices.

Figure 1 :

 1 Figure 1: Spread of the listeners on the first two dimensions of the MFA (about 45% of the variance), coloured by language group

Figure 2 :

 2 Figure 2: Dendrogram obtained from the spread of listeners along the first six dimensions of the MFA; the red lines indicate the place where the tree has been cut, according to an inertia gain criterion.

5 .

 5 Phonation and Voice Quality

Table 1 :

 1 Articulatory and acoustics characteristics of the stimuli:

	V Phonation	PhN N F0	Tilt OQ
					(Hz)
	1 i	stiff (breathy)	-	-Low	-	0.63
					240	16.9
	2 i	thin (falsetto)	-	-Low	-	0.43
					312	13.4
	3 i	Thick (modal)	-	-Low	-	0.49
					230	11.9
	4 i	Stiff (breathy)	-	-High	-	0.43
					480	11.4
	5 i	Thin (falsetto)	-	-High	-	0.4
					500	16.1
	6 i	Thick (modal)	-	-High	-	0.4
					520	10.5
	7 ae Thin (twang)	+	-High	-	0.34
					520	13.4
	8 i	Thin	(tongue	+	-Low	-	0.58
		lowered/backed)		240	16.1
	9 ae Thin (twang)	+	+ High	-4.8 0.35
					520
	2.4. Paradigm

vowel (V), phonation type (Phonation), pharynx narrowed (PhN), presence of nasality (N), fundamental frequency (F0), spectral tilt, and open quotient (OQ).

Table 2 :

 2 Summary of Linear mixed-effects model for

	Arousal (calm-excited) for 5 language groups (AE,
			BP, GP, JP, MC)
	Grp Factor Estimate Std.	t	P
			Error	value
	AE	F0	0.275 0.044	6.2 0.000
		tilt	0.063 0.037	1.7 0.089
		OQ	-0.496 0.055	-9.1 0.000
	PB	F0	0.094 0.060	1.6 0.121
		tilt	0.018 0.050	0.4 0.719
		OQ	-0.616 0.074	-8.3 0.000
	GP	F0	0.317 0.063	5.0 0.000
		tilt	-0.004 0.052	-0.1 0.940
		OQ	-0.236 0.078	-3.0 0.000
	JP	F0	0.461 0.048	9.7 0.000
		tilt	0.080 0.039	2.0 0.042
		OQ	-0.281 0.059	-4.8 0.000
	MC F0	0.141 0.051	2.8 0.006
		tilt	0.053 0.043	1.3 0.211
		OQ	-0.441 0.063	-7.0 0.000

Table 3 :

 3 Summary of Linear mixed-effects model for Valence (negative-positive) for 5 language groups (AE, BP, GP, JP, MC)

	Grp Factor Estimate Std.	t	P
			Error	value
	AE	F0	0.341 0.052	6.5 0.000
		tilt	-0.109 0.044	-2.5 0.012
		OQ	-0.212 0.065	-3.3 0.001

ACKNOWLEDGMENTS

We thank the subjects who participated in the perception tests. This study was partially supported by the Ministry of Education, Culture, Sports, Science and Technology, Grant-in-Aid for Scientific Research (S), 20H05630


Hélène Blanchoud
email: helene.blanchoud@ephe.sorbonne.fr

Gaëlle Tallec

Annie Desportes

Patrick Ansart

Suivi à long terme des pesticides pour la compréhension de leurs processus de transfert à l'échelle du bassin versant

Le suivi en continu de la contamination par les pesticides dans le bassin versant de l'Orgeval a été initié en 2008. Ainsi, 10 ans de données sont maintenant disponibles afin de voir leur comportement sur le long terme et permettre de confronter les résultats de simulation des modèles. Les prélèvements ponctuels ne sont souvent pas pertinents pour la comparaison avec des sorties de modèle car les concentrations sont très fluctuantes dans le temps, surtout dans un petit cours d'eau comme l'Orgeval. Ici, les prélèvements sont asservis au débit et moyennés mensuellement. Un focus est fait ici pour les molécules emblématiques pour lesquelles la tendance d'évolution peut être directement mise en relation avec la dynamique des usages phytosanitaires.

Points clefs

 Le suivi en continu de la contamination est primordial pour la compréhension des transferts et la modélisation  La contamination par les pesticides est saisonnière en lien avec les usages  Pour les molécules actuellement utilisées, une tendance globale est visible en fonction de l'évolution des usages

Introduction

En France métropolitaine, la présence de pesticides dans les eaux est avérée dans 93 % des points de contrôle des cours d'eau et dans 63 % des points de contrôle des eaux souterraines. Alors que la directive cadre sur l'eau (DCE) du 23 octobre 2000 (directive 2000/60) fixe l'objectif général d'atteindre d'ici à 2015 voire 2027, le bon état des différentes masses d'eau sur le territoire européen, cette contamination des ressources en eau impose de maîtriser l'usage des pesticides. Dans cet objectif, le plan ECOPHYTO, piloté par le Ministère en charge de l'Agriculture à la suite du Grenelle de l'Environnement, a été mis en place en 2008. Il vise notamment à réduire progressivement l'utilisation des produits phytosanitaires par les agriculteurs. Dans ce contexte, suivre et évaluer l'évolution de l'usage des pesticides agricoles est un enjeu important pour de nombreux acteurs-gestionnaires (Agences de l'eau, collectivités territoriales, services de l'Etat, etc.) pour évaluer les pressions polluantes, correspondant à l'intensité d'utilisation de ces produits d'une part, et pour estimer le transfert des molécules dans l'environnement d'autre part. Le cas particulier des pesticides vient de la diversité des molécules employées, de la diversité de leur comportement dans les compartiments physiques mais aussi de la difficulté à les détecter. Le suivi de la contamination par les pesticides engendre un cout considérable pour la mise en place de la directive cadre sur l'eau, et les résultats montrent souvent des valeurs inférieures aux limites de quantification. Compte tenu des risques que représentent les pesticides, leur présence dans les cours d'eau et dans les eaux souterraines fait l'objet de suivis réguliers qui n'ont cessé de se renforcer depuis le début des années 2000. Ces suivis mettent en évidence une dispersion importante et une présence généralisée des pesticides dans les milieux aquatiques, le plus souvent en très faible quantité. Les résultats des analyses permettent de vérifier si les normes, lorsqu'elles existent, sont respectées. Ces normes de qualité environnementale sont définies au niveau européen par substance ou groupe de substances et font partie des objectifs de qualité de la directivecadre sur l'eau (ministère de la transition écologique et solidaire, 2018). En 2014, sur 695 molécules pesticides recherchées, 389 ont été quantifiées au moins une fois dans les cours d'eau français (SOeS, 2017) : 180 herbicides dont 79 d'entre eux sont issus de produits interdits à ce jour (molécules et produits de dégradation inclus). La modélisation du transfert des pesticides à l'échelle du bassin versant serait une voie qui permettrait de mieux cibler les molécules à rechercher, mieux comprendre le temps de transfert vers les hydrosystèmes pour en évaluer les impacts sur les écosystèmes et la santé humaine. Cependant, les résultats de simulation ne sont pas encore suffisamment fiables et validés pour que les modèles soient les seuls outils de politique de gestion des eaux.

Rappel des travaux antérieurs sur le bassin de l'Orgeval

L'intérêt du bassin de l'Orgeval est qu'il est intégré dans l'observatoire ORACLE. Ainsi, un réseau de mesures dit « de base » est maintenu en permanence sur ce bassin versant (pour certaines depuis 1962), afin de ne pas interrompre les chroniques. La longueur et la continuité de certaines chroniques sur le long terme sont nécessaires pour appréhender correctement le fonctionnement des hydro-systèmes [START_REF] Loumagne | L'observation long terme en environnement: Exemple du bassin versant de l'Orgeval[END_REF][START_REF] Tallec | 1962-2012 : Cinquante ans d'observations, un bien précieux pour la recherche et les services opérationnels[END_REF].

Bilan des intrants phytosanitaires

Afin de compléter les données de contamination, un travail d'enquête auprès des agriculteurs a précédemment été réalisé dans le cadre du programme PIREN-Seine [START_REF] Nicola | Dynamique De Changement Des Pratiques Agricoles Dans Le Bassin Versant De l'Orgeval Et Création De La Base De Données APOCA (Agricultural Practices o the Orgeval Catchment Area)[END_REF][START_REF] Schott | La modélisation du devenir des pesticides : Recueil de données et utilisation du modèle agronomique STICS pour simuler les transferts sur le long terme. in "Quelle agriculture pour demain?[END_REF]. Ce travail a permis de renseigner le modèle PeSTICS sur les pratiques phytosanitaires du bassin [START_REF] Queyrel | Modélisation du devenir des pesticides dans les sols à partir d'un modèle agronomique : évaluation sur le long terme[END_REF]. Ainsi, les carnets de plaine, avec leur périodicité annuelle et leurs informations détaillées sur les opérations culturales par parcelle, ont été une source d'information précieuse pour répondre aux besoins de la modélisation, en complément des données issues du recensement général parcellaire (RPG).

Toutefois, le changement d'échelle de la parcelle au territoire du bassin versant n'est, là encore, pas simple à effectuer. Compte tenu de la part de la SAU du bassin renseignée par les carnets de plaine disponibles (jusqu'à 22%) et de la part de la SAU dont l'assolement annuel était connu (jusqu'à 50%), nous avons été conduits à formuler des hypothèses pour extrapoler ces informations à l'ensemble du territoire, qui constituent autant de sources d'incertitude à prendre en compte dans l'interprétation des résultats des modèles [START_REF] Schott | La modélisation du devenir des pesticides : Recueil de données et utilisation du modèle agronomique STICS pour simuler les transferts sur le long terme. in "Quelle agriculture pour demain?[END_REF]. Toutefois, la dynamique de remplacement des molécules au cours du temps est correctement représentée pour les cultures de maïs (Figure 1) et du blé tendre d'hiver (Figure 2). Ainsi, il apparait la diminution des quantités d'atrazine employées par hectare de maïs entre 1990 et 2003 selon la diminution progressive des doses homologuées de 2,5 à 1 kg/Ha avant son interdiction en 2003. Cette diminution s'accompagne de l'apparition de nouvelles substances telles que l'alachlor (interdit en 2008), du nicosulfuron et surtout du S-Métolochlor, très utilisé encore à l'heure actuelle sur de nombreuses cultures. Les traitements s'effectuent en période printanière. De plus, comme les matières actives sont appliquées sur des cultures ciblées, il est également important de tenir compte des surfaces des différentes cultures et de leur évolution au cours du temps pour bien représenter les quantités de matières actives appliquées. En ce qui concerne l'assolement moyen à l'échelle du bassin versant de l'Orgeval, il comporte 8 à 9 cultures « significatives », ce qui représente autant de pratiques phytosanitaires différentes à analyser [START_REF] Schott | La modélisation du devenir des pesticides : Recueil de données et utilisation du modèle agronomique STICS pour simuler les transferts sur le long terme. in "Quelle agriculture pour demain?[END_REF].

Figure 2. Évolution des doses moyennes et homologuées (kg/ha/an) d'isoproturon et du chlortoluron et pourcentages de parcelles traitées pour le blé tendre d'hiver dans le bassin versant de l'Orgeval de 1990 à 2009

Nous avons également pu mettre en évidence la sensibilité du modèle PeSTICS aux paramètres du sol. Une méthode permettant de limiter les incertitudes sur la paramétrisation du sol est de définir l'assolement en fonction des types de sol. Enfin, nous avons pu montrer que le modèle PeStics était capable de reproduire des concentrations moyennes annuelles d'exportation en atrazine et isoproturon pour le bassin versant de l'Orgeval. D'autres molécules pourraient également être testées, pourvu que nous ayons un suivi de contamination existant suffisamment complet pour valider les résultats de simulation. La poursuite du suivi de contamination du bassin de l'Orgeval est donc indispensable pour plusieurs raisons : -D'une part il permet d'assurer la confrontation avec les sorties de simulation sur une échelle de temps la plus longue possible. Le protocole d'échantillonnage asservi au débit permet de lisser les aléas dus aux prélèvements ponctuels, -Le suivi est actualisé avec de nouvelles molécules en fonction des usages sur le bassin, mais les anciennes molécules permettent de mieux comprendre la réactivité du bassin versant, notamment pour la compréhension des échanges napperivière, -Les nouveaux systèmes de prélèvement intégrés (type POCIS) sont un développement d'avenir, mais présentent encore des biais liés aux coefficients d'échange en fonction des propriétés des substances, de la charge en matières en suspension dans l'eau, la vitesse du courant et le temps d'exposition.

A l'heure actuelle, le prélèvement moyen asservi au débit reste la seule méthode fiable pour calculer des flux à l'exutoire d'un bassin versant.

Le suivi de la contamination par les pesticides sur le bassin

Le suivi de la contamination par les pesticides a débuté à la fin des années 1970 [START_REF] Chevreuil | Evolution et transfert des pesticides : exemple du bassin versant de l'Orgeval[END_REF]. La chronologie des différentes études réalisées sur le bassin a déjà été présentée dans la phase précédente [START_REF] Schott | La modélisation du devenir des pesticides : Recueil de données et utilisation du modèle agronomique STICS pour simuler les transferts sur le long terme. in "Quelle agriculture pour demain?[END_REF]. En outre, de la fin des années 70 jusqu'en 2008, les mesures en pesticide ont été ponctuelles et réalisées sur des périodes d'une durée maximale de 3 ans. Le premier jeu de données est associé à la campagne de mesures de 1991-1993 réalisée par Garmouma et al., 1997. Bien que ces informations permettent de renseigner l'évolution de la concentration, elles ne permettent qu'une interprétation qualitative car les mesures ne sont pas asservies au débit. Des campagnes de prélèvements et de mesures en laboratoire ont été mises en oeuvre pour déterminer les propriétés physico-chimiques et les cinétiques de dégradation (la formation de résidus liés et minéralisation). Deux molécules ont été plus particulièrement ciblées lors de cette étude : l'Atrazine et l'Isoproturon. Ce projet a eu pour objectif d'acquérir les informations nécessaires en vue d'une modélisation du transfert des pesticides dans le continuum Sol/ Zone Non Saturée/ Nappe à l'échelle du bassin versant [START_REF] Blanchoud | Les pesticides dans le bassin versant de la Seine : Comprendre les origines et le transfert des pesticides pour en évaluer l'impact sur l'homme et l'environnement[END_REF].

Depuis 2008, un suivi continu de la contamination des eaux de surface du ru des Avenelles a été instauré [START_REF] Blanchoud | Projet d'étude de la contamination par les pesticides d'eaux de rivières et de nappes au niveau du bassin versant de l'Orgeval[END_REF]. Il permet ainsi d'obtenir une information continue dans le temps sur une durée supérieure à 3 ans. Ce suivi donne une vision globale de la contamination en herbicide du sous-bassin des Avenelles. Cette chronique de mesures permet de comparer des sorties de modèle aux observations de terrain. Bien que lacunaires, l'ensemble des différents jeux de données acquis sur l'Orgeval constitue une source d'information sur l'évolution de la contamination en pesticides sur une longue période à l'échelle d'un bassin versant. De tels jeux de données sont difficiles à acquérir. Les mesures réalisées dans le cadre du programme de surveillance des masses d'eau par l'Agence de l'Eau Seine Normandie (AESN), permettent de fournir une information qualitative sur l'évolution de la contamination. Des prélèvements sont effectués plusieurs fois par an par station de mesure. Ce suivi bien que nécessaire ne permet pas de réaliser des bilans de masse à l'échelle des bassins versants. L'eau est prélevée par un préleveur automatique réfrigéré ISCO et asservi au débit. Chaque semaine, l'eau est récupérée pour éviter le débordement du flacon et permettre de conserver l'échantillon. Les échantillons hebdomadaires sont ensuite regroupés par mois. Les analyses de pesticides sont réalisées sur 500 mL d'eau filtrée avec ajout d'étalon interne. Puis les pesticides sont extraits sur cartouche SPE OASIS HLB et élués avec 4 mL de méthanol. Après une seconde filtration à 0,2 µm, les échantillons sont analysés par LC/MS/MS en mode ESI positif (Tableau 1). [START_REF] Schott | La modélisation du devenir des pesticides : Recueil de données et utilisation du modèle agronomique STICS pour simuler les transferts sur le long terme. in "Quelle agriculture pour demain?[END_REF]. Les fluctuations saisonnières seraient alors en lien avec la contribution de la nappe de la Brie. Cependant, l'atrazine avait toujours une concentration plus faible en nappe qu'en rivière. Une autre source pourrait donc etre suspectée pour l'atrazine. Si les concentrations en atrazine restent globalement stables sur la période, celles de la DEA sont en augmentation.

La valeur du DAR (DEA -Atrazine Ratio) est aussi en augmentation et suit une croissance monotone (test non paramétrique de Mann Kendall, R cran). D'autres études montrent également que le maximum de contamination en DEA n'est pas encore atteind, notamment par la désorption progressive de l'atrazine et de sa lente dégradation et progression dans les sols [START_REF] Chen | Water, nitrate and atrazine transfer through the unsaturated zone of the Chalk aquifer in northern France[END_REF]Mattei, 2017). L'analyse tendancielle de la contamination à l'horizon 2030 a notamment montré que les nappes les plus contaminées étaient celles où les tendances à la baisse sont les plus faibles, voire des tendances à l'augmentation (Mattei, 2017).

Afin de vérifier si les lessivages de l'atrazine diminuent sur la période, les flux annuels ont été calculés pour l'atrazine et la DEA (Tableau 2). Ces résultats ne montrent pas une tendance d'évolution des flux. Ceci est du notamment aux aléas hydrologiques. On remarque qu'en 2016, les flux sont les plus élevés, correspondant à la crue du printemps 2016, en mai sur l'Orgeval, qui représente à elle seule 35% du flux annuel. Ces débits sont associés à des concentrations plus élevées expliquant le doublement du flux entre 2015 et 2016, alors que les années précédentes, on pouvait remarquer un effet de dilution.

Le S-Métolachlor

Le retrait progressif des Autorisations de mise sur le marché (AMM) génère une utilistation restreinte à quelques molécules. Dans le cas du S-Métolachlor, le retrait de l'atrazine, puis de l'alachlor a concentré les usages notamment sur cette molécule et sur le nicosulfuron. Par rapport à l'atrazine, les fluctuations saisonnières sont liées aux usages printaniers (Figure 4). Ils sont beaucoup plus importants (échelle log), mais montrent une tendance progressive à l'augmentation avec notamment une augmentation des minima. Les maxima annuels sont mesurés peu de temps après la période d'application et des valeurs dépassant 1µg/L sont observées. L'isoproturon et le chlortoluron ont une tendance à la diminution depuis 10 ans, suite aux restrictions d'usage et de dose (Figure 5). En septembre 2017, l'isoproturon a été retiré du marché. La comparaison avec les tendances d'évolution de l'atrazine mettront en évidence l'effet des propriétés physico-chimiques et notament les processus de sorption sur la persistance de la contamination.

L'isoproturon et le chlortoluron

Conclusion et perspectives

La difficulté d'étudier la dynamique des pesticides dans un bassin versant réside dans la diversité des molécules, des pratiques et des réglementations d'usage qui changent fréquemment. Le suivi des molécules interdites est intéressant car il permet de quantifier les résidus dans le milieu. L'acquisition de ces données conjuguée à la modélisation de leur transfert donne une idée des stocks encore présents dans le sol et la zone non saturée et/ou la nappe.

Depuis ces dernières années, les quantités de matières actives vendues en France diminuent. Ces diminutions massiques correspondent au remplacement de molécules utilisées à de fortes doses comme l'atrazine par des molécules efficaces à quelques grammes à l'hectare. L'indice de fréquence de traitement (IFT, qui prend en compte la dose homologuée) reste élevé et indique que la pression polluante est inchangée. De nouvelles molécules telles que le nicosulfuron sont maintenant régulièrement détectées dans les échantillons, malgré sa dose homologuée très faible (45 g/Ha contre 1,2 kg/Ha pour l'isoproturon). Depuis 2008, d'autres pesticides sont recherchés : l'imidaclopride et ses produits de dégradation. Par contre, le glyphosate ne peut pas etre quantifié mensuellement, des essais ont montré qu'il se dégrade trop vite.

Le mode de prélèvement qui montre un intérêt pour un suivi intégré est l'analyse par préleveurs passifs. L'implantation in situ d'échantillonneurs passifs de type POCIS pour mettre en évidence la présence de polluants se développe. L'intérêt est de mesurer des quantités extrèmement faibles dans les eaux sur une période intégrée. Cependant, si sur le plan quantitatif, les résultats sont encourageants, il n'en est pas de même sur le plan quantitatif. Par ailleurs, de nouveaux développements de phases permettant d'élargir la gamme de molécules plus polaires comme le glyphosate sont à l'étude. Les temps de latence observés augmentent avec l'hydrophobicité des molécules étudiées et il y a un impact réel des conditions hydrodynamiques sur le POCIS [START_REF] Desgranges | Développement d'échantillonneurs passifs de type POCIS pour l'évaluation de la contamination en pesticides des eaux de bassins versants languedociens[END_REF].

Afin de vérifier l'intérêt de l'utilisation des POCIS pour estimer les flux de pesticides, il serait pertinant de mettre en parallèle pour un an un prélèvement simultané par POCIS et par l'échantillonnage mensuel asservi au débit.

Figure 1 .

 1 Figure 1. Dynamique des principales molécules utilisées sur maïs dans le bassin de l'Orgeval entre 1990 et 2009 (en kg/ha) (Sources : Carnets de plaine), d'après Schott et al.

Figure 4 .

 4 Figure 4. Evolution temporelle de la concentration moyenne mensuelle du S-Métolachlor et sa courbe de tendance exponentielle avec les débits associés.

  Tableau 1. Liste des pesticides recherchés et leurs transitions en LC/MS/MS.

	Name	Scan	Précurseur	production	production	RT:
			Ion	quantifier	qualifier	min
	Alachlor	MRM 270,0	162,0	238,0	10,2

Figure 3. Evolution temporelle de la concentration moyenne mensuelle de l'atrazine (en bleu foncé) et de son produit de dégradation la DEA (en bleu clair) et les débits associés. Le rapport entre la DEA et l'atrazine (le DAR * 10, en rouge) et la régression linéaire. Contrairement aux molécules encore utilisées sur le bassin versant, l'atrazine n'a plus que de faibles fluctuations entre 1 et 50ng/L. Par contre, la DEA est toujours très présente dans le ru des Avenelles avec des concentrations pouvant atteindre 200 ng/L. L'atrazine étant interdite depuis 2003, ces détections correspondent à l'élimination progressive des stocks contenus dans les sols et /ou la nappe. Dans la précédente phase du PIREN-Seine, des prélèvements en nappe mettaient en évidence que la contamination par la DEA du cours d'eau pouvait etre expliquée par celle de la nappe de la Brie

  Tableau 2. Flux annuels d'atrazine et de DEA en g/an.

																Année				Atrazine				DEA
																2010 2011				63,14 65,89					238,07 265,62									ng/l
	Débit en l/s															2012 2013 2014 2015 2016				153,53 286,84 128,84 172,05 337,70			543,82 528,85 559,94 838,84 1737,76								en concentration	Débits DEA Atrazine
																2017				130,19				637,58
																																									DAR*10
	08	9/9/08	18/12/08	28/3/09	6/7/09	14/10/09	22/1/10	2/5/10	10/8/10	18/11/10	26/2/11	6/6/11	14/9/11	23/12/11	1/4/12	10/7/12	18/10/12	26/1/13	6/5/13	14/8/13	22/11/13	2/3/14	10/6/14	18/9/14	27/12/14	6/4/15	15/7/15	23/10/15	31/1/16	10/5/16	18/8/16	26/11/16	6/3/17	14/6/17	22/9/17	31/12/17	10/4/18	19/7/18	27/10/18	4/2/19	Linéaire (DAR*10)
																			Date

PIREN-Seine phase VII -rapport 2018 -Suivi à long terme des pesticides de l'Orgeval

Cette méthode permet d'obtenir des limites de quantification d'environ 1 ng/L pour la majorité des molécules.

Tendances d'évolution de la contamination

Les seules molécules dont le taux de quantification est proche de 100 % sont l'atrazine et son produit de dégradation la DEA, le S-Métolachlor, l'isoproturon et le chlortoluron. Ces molécules reprensentent une grande partie des détections dans les eaux au niveau du bassin de la Seine et font partie du TOP 15. Leurs usages ont considérablement évolué au cours des 20 dernières années.

L'atrazine

Au début de la mise en place du suivi, l'atrazine était déjà interdite depuis 5 ans. Les études antérieures ont montré des pics de contamination allant jusqu'à 30 µg/L sur le bassin de l'Orgeval en 1999, quand l'atrazine était encore autorisée [START_REF] Guivarc | Apports et transfert de pesticides en milieux agricole et urbain sur le bassin versant de la Marne : vers une évaluation globale[END_REF]. Aujourd'hui, elle est toujours détectée dans les eaux de surface et souterraines à des concentrations bien plus faibles. Ce suivi est cependant intéressant car il montre qu'on a toujours une saisonnalité observable dans le cours d'eau (Figure 3). Globalement, les concentrations en atrazine et DEA sont plus élevées en période estivale, c'est-à-dire quand les débits sont les plus faibles.