Jean-Baptiste Louvet
email: jeanbaptiste.louvet@insa-rouen.fr

Guillaume Dubuisson Duplessis

Nathalie Chaignaud

Laurent Vercouter

Jean-Philippe Kotowicz

Modeling a collaborative task with social commitments

Keywords: human-machine interaction, collaborative document retrieval, social commitments

Our goal is to design software agents able to collaborate with a user on a document retrieval task. To this end, we studied a corpus of human-human collaborative document retrieval task involving a user and an expert. Starting with a scenario built from the analysis of this corpus, we adapt it for a human-machine collaborative task. We propose a model based on social commitments to link the task itself (collaborative document retrieval) and the interaction with the user that our assistant agent has to manage. Then, we specify some steps of the scenario with our model. The notion of triggers in our model implements the deliberative process of the assistant agent. .

Introduction

Document retrieval (DR), which takes place in a closed database indexing pre-selected documents from reliable information resources, is a complex task for non expert users. To find relevant documents, interfaces allowing formulating more specific queries are hardly used because an expertise about the domain terminology is needed. It may require an external assistance to carry out this task according to the users information need. Thus, we propose to design software agents able to collaborate with a user on a document retrieval task.

To this end, we adopt a cognitive approach by studying a corpus of human-human (h-h) collaborative document retrieval task in the quality-controlled health portal CISMeF (www.cismef.org) [START_REF] Darmoni | CISMeF : a structured health resource guide[END_REF] , which involves a user and an expert. In previous work [START_REF] Dubuisson Duplessis | Empirical Specification of Dialogue Games for an Interactive Agent[END_REF][START_REF] Dubuisson Duplessis | A Conventional Dialogue Model Based on Dialogue Patterns[END_REF] , extraction of dialogue patterns from the corpus has been done with their formalization into dialogue games [START_REF] Maudet | Modéliser l'aspect conventionnel des interactions langagières: la contribution des jeux de dialogue[END_REF] , which can be fruitfully exploited during the dialogue management process [START_REF] Dubuisson Duplessis | A Conventional Dialogue Model Based on Dialogue Patterns[END_REF] . This formalization uses the notion of social commitments introduced by Singh [START_REF] Singh | Social and psychological commitments in multiagent systems[END_REF] .

In this article, we are interested in linking the task itself (collaborative DR) and the interaction with the user that our assistant agent has to manage. We show that the formalism 3 used to model the dialogue games through social commitments can be enhanced to describe the task. Our model makes the link between a high level structure (the task) and low level interaction (dialogue games). Starting with a scenario built from the analysis of the corpus of h-h interaction, we adapt it for a human-machine (h-m) interaction. Then, we specify each step of this scenario in terms of social commitments.

This article consists of 5 parts: Section 2 gives a short state of the art on dialogue models. Section 3 describes the model we used to specify a collaborative task. Section 4 presents the scenario modeling the h-h collaborative document retrieval process and a discussion on its transposition in a h-m context. In Section 5, some steps of this scenario are detailed in terms of commitments. Finally, Section 6 gives some conclusions and future work.

Related work on reactive/deliberative dialogue model

To model dialogue, plan-based approaches and conventional approaches are often viewed as opposite, although some researchers argue that they are complementary [START_REF] Hulstijn | Dialogue games are recipes for joint action[END_REF][START_REF] Yuan | Informal logic dialogue games in human-computer dialogue[END_REF][START_REF] Dubuisson Duplessis | A Conventional Dialogue Model Based on Dialogue Patterns[END_REF] : Communication processes are joint actions between participants that require coordination. Nevertheless, coordination must stand on conventions reflected by interaction patterns. Thus, dialogue can be considered as a shared and dynamic activity that requires both high-level deliberative reasoning processes and low-level reactive responses.

Dubuisson Duplessis 3 proposes to use a hybrid reactive/deliberative architecture where a theory of joint actions can be a "semantics" to the interaction patterns described as dialogue games. These dialogue games are modeled through the notions of social commitment and commitment store described below.

Social Commitments

Social commitments are commitments that bind a speaker to a community [START_REF] Singh | Social and psychological commitments in multiagent systems[END_REF] . They are public (unlike mental states such as belief, desire, intention), and are stored in a commitment store. Our formalization classically distinguishes a propositional commitment from an action commitment.

Propositional commitment. A propositional commitment involves that an emitter (x) commits itself at the present on a proposition towards a receiver (y). Such a commitment is written C(x, y, p, s), meaning "x is committed towards y on the proposition p" is in state s. We only consider propositions describing present, which leads us to consider only two states for a propositional commitment: a propositional commitment is initially inactive (Ina). After its creation, it enters the state created (Crt). A created commitment can be canceled by its emitter. In this case it goes back in an inactive state.

Action commitment. An action commitment involves that an emitter (x) commits itself at the present on the happening of an action in the future, towards a receiver (y). Such a commitment is written C(x, y, α, s), meaning "x is committed towards y on the happening of the action α" is in state s. An action commitment is initially inactive (Ina). In this state, it can be created. The creation attempt can fail (Fal) or succeed (Crt). An action commitment in Crt state is active. An active commitment can be violated, leading it to the Vio state. It corresponds to a situation in which the satisfaction conditions of the content of the commitment can not be fulfilled anymore. An active commitment can be fulfilled, leading it to the Ful state. An action commitment is satisfied if its content has been completed.

In order to simplify the writing of the commitments, as in our case the interaction is between two interlocutors, we omit the receiver of the commitments. Consequently, a propositional commitment will be written C(x, p, s) and an action commitment will be written C(x, α, s).

Conversational gameboard

The conversational gameboard describes the state of the dialogue between the interlocutors at a given time. The conversational gameboard describes the public part of the dialogic context supposed strictly shared. T i stands for the conversational gameboard at a time i (the current time). In the framework of this article, we use a simple theory of instants where "<" is the relationship of precedence. The occurrence of an external event increments the time and makes the table evolve. An external event can be dialogic (e.g. an event of enunciation of a dialog act) or extra-dialogic (e.g. an event like light_on showing the occurrence of the action of turning the light on).

The conversational gameboard includes a commitment store, which is a partially ordered set of commitments. It is possible to query the gameboard on the belonging (or non-belonging) of a commitment. This is formalized in equation 1a for belonging and 1b for non-belonging (c being a commitment).

T i c, true if c ∈ T i , false otherwise (1a) T i c, equivalent to ¬(T i c) (1b)

Dialogue games

A dialogue game is a conventional bounded joint activity between an initiator and a partner. Rules of the dialogue game specify the expected moves for each participant, which are supposed to play their roles by making moves according to the current stage of the game. This activity is temporarily activated during the dialogue for a specific goal.

A dialogue game is a couple type, subject , where type belongs to the set of existing dialogue games and subject is the goal of the game in the language of the subject of the game. We usually write a game under the form type(subject). A game is defined with social commitments. It's a quintuplet characterized for the initiator and the partner by [START_REF] Dubuisson Duplessis | Empirical Specification of Dialogue Games for an Interactive Agent[END_REF][START_REF] Dubuisson Duplessis | A Conventional Dialogue Model Based on Dialogue Patterns[END_REF] entry conditions describing the conditions the conversational gameboard must fulfill to enter the game, termination conditions, separated into two categories: Success conditions and failure conditions, rules expressed in terms of dialogic commitments, specifying the expected sequencing of expected or forbidden acts, and effects specifying the contextualized effects of dialogical actions in terms of generation of extra-dialogic commitments (i.e. related to the task).

A sub-dialogue game is a child dialogue game played in an opened parent game. The emitter of the sub-game can be different from the one of the parent game. Conditions for playing a sub-dialogue game can be hard to specify [START_REF] Maudet | Modéliser l'aspect conventionnel des interactions langagières: la contribution des jeux de dialogue[END_REF] .

Dialogical action commitment.

A dialogical action commitment is an action commitment contextualized in a dialogue game. It means that in a dialogue game, a participant is committed to produce dialogical actions conventionally expected relatively to an opened dialogue game. For example, in the context of the offer dialogue game, if x plays offer(x, α), the dialogical action commitment C(y, acceptOffer(y, α)|declineOffer(y, α), Crt) will be created, showing that the receiver of the dialogical action can accept or decline the offer.

Model to specify a collaborative task

This section describes the model we use to specify the task using commitments, conversational gameboard and dialogue games. First of all, we consider that a task can be split into subtasks that we call steps. Each step of the task is described by a table (named step table) divided in three parts: The name of the step, the access conditions to this step and a list of expected behaviors of each participant to the dialogue. Expected behaviors are alternatives and can be played in any order. An expected behavior is a description of:

• A conventionally expected dialogue game, with its emitter and content (action or proposition); • The possible outputs of this dialogue game;

• Trigger (optional) that is conditions that must be fulfilled to play the expected game.

To define the trigger ϕ that emits the predicate E, we use the notation 2a, ϕ being a formula. To express that the conversational gameboard T i fulfills the conditions for a trigger to emit E, we use the notation 2b.

E : T i → ϕ (2a) T i E (2b)
Prior to play an expected game, the emitter must respect the entry conditions of this game. To shorten the writing of a step table, we do not repeat these conditions. 1. Instances of this this model for our specific task can be found in Tables 3 and4. It describes the access conditions and the expected dialogue games of the step and the modifications they bring to the conversational gameboard T i . In our example, access conditions are that T i contains C(z, {α, p}, s) and triggers the predicate E 0 we give an example of expected behavior with DG(z, {β 1 , p 1 }) as dialogue game and T i+1 C(z, {β 1 , p 1 }, s) as a modification to the conversational gameboard brought by DG. For games played by a software agent, the emission of a predicate (e.g. T i E 1 for the first dialogue game of our example) has to be triggered in order to play the expected dialogue game. For games played by a human, there's no trigger row in the table as the decision to play a dialogue game only depends on his own cognitive process. Some expected dialogue games can be played several times, noted with * . This symbol is propagated in the output to show the commitments that can be generated several times. This is shown with the first dialogue game of our example. Sub-dialogue games (like SDG(z', {γ, p 2 }) in the Table 1) that can be played are indicated under their parent game (played by any of the participants), headed by a " ".

The step table is a complete description of what can conventionally happen. A generic example of step table is given in Table

This model gives a clear definition of what is conventionally expected from each participant in one step of the task. It is also possible to see triggers as defining the intentions of the agent. As a matter of fact, most of the agent's decisions are done thanks to the triggers, and the agent's behavior can be adapted by modifying these triggers.

Name of the step

Access ∧ T i C(z, {α, p}, s) T i E 0 Expected game DG(z, {β 1 , p 1 }) * Trigger T i E 1 (only if z is a software agent) Output T i+1 C(z, {β 1 , p 1 }, s) * Expected game DG(-, {β 2 , p 2 }) SDG(z, {γ, p 2 }) Trigger T i E 2 (only if z is a software agent) Output T i+1 C(-, {β 2 , p 2 }, Crt) T i+1 C(z, {γ, p 2 }, s) Expected game DG(z, δ) Trigger T i E 3 (only if z is a software agent) Output ∨ DA1(z', δ) ⇒ T j C(z', δ, s 1 ) DA2(z', δ) ⇒ T j C(z', δ, s 2 )

Expected behaviors

We use a specific syntax for dialogue games implying dialogical action commitments. To reduce the size of the tables, we directly map the expected dialogical action commitments to the expected dialogical action of the dialogue game. For example, the third part of Table 1 shows the writing for the dialogue game DG(z, δ): Playing the dialogue game DG(z, δ) creates the dialogical action commitment C(z', DA1(z', δ)|DA2(z', δ), Crt) (DA1 and DA2 being dialogical actions), playing the dialogical action DA1(z', δ) creates the commitment C(z', δ, s 1 ) and playing the dialogical action DA2(z', δ) creates the commitment C(z', δ, s 2 ).

Analysis of the h-h collaborative document retrieval process

Information Retrieval

This section introduces some models of information retrieval (IR) processed by an isolated person and in a collaborative framework. These models can be applied to DR.

IR is generally considered as a problem solving process 8 implying a searcher having an identified information need. The problem is then to fulfill this lack of information. Once the information need is specified, the searcher chooses a plan he will execute during the search itself. He evaluates the results found to possibly repeat the whole process. IR is considered as an iterative process that can be split into a series of steps [START_REF] Broder | A taxonomy of Web search[END_REF][START_REF] Marchionini | Find What You Need, Understand What You Find[END_REF][START_REF] Sutcliffe | Towards a cognitive theory of information retrieval[END_REF] : (i) information need identification, (ii) query specification (information need formulation and expression in the search engine, etc.), (iii) query launch, (iv) results evaluation, (v) if needed, query reformulation and repetition of the cycle until obtaining satisfying results or abandoning the search.

The standard model is limited by two aspects. On the one hand, the information need of this process is seen as static. On the other hand, the searcher refines repeatedly his query until finding a set of documents fitting his initial information need. Some studies showed that, on the contrary, the information need is not static and that the goal is not to determine a unique query returning a set of documents matching with the information need [START_REF] Bates | The Design of Browsing and Berrypicking Techniques for the Online Search Interface[END_REF][START_REF] O'day | Orienteering in an information landscape: how information seekers get from here to there[END_REF] . Bates proposes the model of "berrypicking" [START_REF] Bates | The Design of Browsing and Berrypicking Techniques for the Online Search Interface[END_REF] which lays the emphasis on two points. The first one is that the information need of the searcher evolves thanks to the resources found during the search. Encountered information can lead the search in a new and unforeseen direction. The second one is that the information need not satisfied by a unique set of documents obtained at the end of the search, but by a selection of resources collected all along the process. To sum up, the IR process is opportunistic and its progression influences the final result.

Study of the h-h collaborative document retrieval process

To understand the collaborative aspect of the DR process of a user assisted by a human expert, we carried out a study on a h-h interaction. This study is based on the analysis of the corpus collected during the Cogni-CISMeF project [START_REF] Loisel | A conversational agent for information retrieval based on a study of human dialogues[END_REF][START_REF] Loisel | An Issue-Based Approach to Information Search Modelling: Analysis of a Human Dialog Corpus[END_REF] .

The Cogni-CISMeF corpus

The corpus consists in assistance dialogues about the DR task between an expert and a user in a co-presence situation. The user expresses his information need. The expert has access to the CISMeF portal and has to lead the search cooperating with the user. The CISMeF portal has a graphical user interface and a query language enabling to decompose a query into MeSH ("Medical Subject Headings") lexicon elements. The CISMeF terminology contains keywords, qualifiers (symptoms, treatments. . . ), meta-terms (medical specialties) and resources types (databases, periodicals, images. . . ). The system also allows for extended queries, although many users are not comfortable with them.

The experiment was carried out with 21 participants (e.g., researchers, students, secretaries of the laboratory) submitting a query to one of the two CISMeF experts (researchers of the project who learned to use the CISMeF terminology). The corpus includes the transcript of the 21 dialogues (12 for the first expert and 9 for the second) and contains around 37 000 words. Yes normally it's a diagnostic / ok / let's try like this A10 We will try like this otherwise we will remove extra things to have some / so I launch the search again with the "cancerology" thematic access, the CISMeF keyword "colon" and the qualifier "diagnostic" without specifying the type of searched resources Table 2. Translated extract of a dialogue from the corpus (VD06). A is the expert and B the searcher.

Figure 1. Scenario presenting the phases (squares) and the steps (ellipses) in a collaborative document retrieval task.

The collaborative document retrieval scenario

The analysis of the corpus enabled us to identify and characterize the different phases of the dialogues of the Cogni-CISMeF corpus playing a role in the task progress. Five phases were distinguished:

• Verbalization: It is the establishment of the search subject between both participants. It always starts by a request formulation from the user and can be followed by spontaneous precision. The expert can then start the query construction if he considers that the verbalization contains enough keywords, ask precision if not or try to reformulate the user's verbalization; • Query construction: It is the alignment of the terms of the user's verbalization with the CISMeF terminology in order to fill in the query form; • Query launch: It is the execution of the current query by the expert. This phase is often implicit;

• Results evaluation: The expert evaluates the results of the query. If they are not satisfying, he decides to directly repair the query. Otherwise he presents them to the user. If the latter finds them satisfying, the goal is reached and the search is over; If he finds them partially satisfying (not adapted to his profile, or not related totally to the information need) or not satisfying, the query must be repaired. If the results are rejected by the user, it is also possible to abandon the search; • Query repair: The expert and the user try to use tactics to modify the query while respecting the information need. Three tactics were observed: Precision (to refine the query), reformulation (using synonyms for example) and generalization (to simplify the query). However, these tactics are not mutually exclusive: It is possible to combine precision or generalization with reformulation.

In addition to these phases, an opening and a closing phases were observed. The opening phase is optional and consists simply in greetings (information demand about the user's name, age. . . ). At last, the closing phase may give ideas for a new search. The analysis of this corpus showed that the DR task fulfilled by the participants is iterative, opportunistic, strategic and interactive [START_REF] Bates | Information search tactics[END_REF][START_REF] Bates | Where should the person stop and the information search interface start?[END_REF] . The iterative aspect of this process is illustrated by the systematic repetition of the pattern launch/evaluation/repair. On top of that, we remarked that it is clearly lead by the expert.

The dialogue in Table 2 is an example of a query repair showing the iterative, opportunistic, strategic and interactive aspects. The expert suggests to widen (generalization) the query (utterance A1). The partners elaborate jointly a plan to modify the query. In this case, it is mainly the user who suggests the moves to carry out (utterances B4 and B6) and the expert agrees (utterances A5 and A7). Then, the expert suggests to add (precision) the qualifier "diagnostic" (utterance A8). The user accepts and suggests the plan execution (utterance B9). The plan execution is accepted and done by the expert (utterance A10), who eventually launches the query.

The scenario presented in Figure 1 synthesizes the phases (squares) split into several steps (ellipses) and the possible runs. The dashed ellipses correspond to actions that can be carried out implicitly by the participants of the interaction.

Discussion

It is possible to take inspiration from the h-h interaction to the h-m interaction. Thus, the presented scenario in the context of the h-h interaction (Figure 1) can be transposed to a h-m context. However, it has to be adapted in order to fit the constrains of the h-m interaction.

The h-m interaction framework changes the collaboration situation as far as it gives to the user the ability to lead the search and to modify the query, without requiring the system's agreement. It is an important change which gives to the user new privileges and more control over the interaction. It implies a restriction of the software assistant's permissions when compared to the human expert. As a matter of fact, the system can take initiatives to modify the query by suggesting modifications that will be applied only if they are accepted by the user. However, this inversion of the query modification rights allows each participant to take part in the interaction: As far as the opportunistic aspect are concerned, the user and the system can participate to the interaction at any moment.

Despite the lack of cognitive abilities that has a human expert, the software agent has some edges that can be beneficial for a collaborative DR task. The system can access online dictionaries of synonyms, hyponyms, hypernyms and "see also" links, allowing it to find terms related to the user's verbalization. For the reformulation, the system can make use of the lexical resources on the query terms [START_REF] Audeh | Semantic query expansion for fuzzy proximity information retrieval model[END_REF] . In the context of CISMeF, Soualmia [START_REF] Soualmia | Strategies for Health Information Retrieval[END_REF] offers tools to correct, precise and enrich queries. On top of that, the assistant agent can store the previous DR sessions and take advantage of them (by linking information needs, queries and documents) to find terms related to the current search [START_REF] Guedria | Customized Document Research by a Stigmergic Approach Using Agents and Artifacts[END_REF] . It also has the ability to launch queries "in background" (i.e. without notifying the user), beforehand suggesting any query modification or launch. It makes possible, before suggesting a modification to the user, to check if it brings interesting results.

Application to the Cogni-CISMeF project

We described a h-h collaboration for DR process from which we want to draw in a h-m framework. The model described in Section 3 can be used for a h-m collaboration. As a matter of fact, this model makes possible to express the different characteristics of a h-m collaborative DR:

• Iterative: It is possible to give a circular sequencing to step tables using their access conditions (to represent the launch/evaluation/repair loop, for example); • Opportunistic: Depending on the current state of the conversational gameboard, the most relevant dialogue games can be played; • Interactive: Each participant can take part to the interaction at any moment; • Strategic: It is possible to describe dialogue games combinations in order to reach given states of the conversational gameboard.

An interesting aspect of our model is that the assistant agent can behave according different cognition levels. This can be done thanks to the triggers that capture the deliberative process of the agent. The agent's reasoning can be very reactive with simple rules or, on the contrary, it can entail a more high level decision process.

In this section, we describe the steps of the DR scenario (see Section 4) in terms of our model (see Section 3). Our goal is to show the expressiveness of our model applied to a h-m collaborative DR task drawn from an h-h one. Only some relevant step tables are presented to illustrate the interest of the model.

Verbalization precision step

This step takes place in the verbalization phase. The user has done a first verbalization of his information need but he has to give more details about it, so he is committed to perform the action of verbalization precision (T i C(x, preciseVerbalization, Crt) present in the "Access" part).

In this situation, it is conventionally expected from the user to add verbalization expressions e to his verbalization with an "inform" dialogue game (inform(x, verbalizationExpression(e))). This action can be repeated as often as the user needs (expressed by the * following the dialogue game). The consequences of this dialogue game on the conversational gameboard are: (i) Every time the dialogue game is played, a new commitment on a verbalization expression is created (Crt) and (ii) The commitment on the action of verbalization precision is fulfilled (Ful). The * in the output is propagated for the creation of the commitment on a verbalization expression but not on the action fulfillment commitment (it is performed only the first time the dialogue game is played).

It is also expected that the user tells the agent when his precision is finished. This can be performed by playing the dialogue game inform(x, verbalizationComplete) that creates the commitment C(x, verbalizationComplete, Crt) in the conversational gameboard. The model of this step is shown in Table 3.

Query precision step

This step takes place in the query repair phase. Query q were launched (T i lastQueryLaunched(q)) and its results evaluated by the user, who turned them down (T i C(x, ¬queryResultsSatisfying(q), Crt)). We place ourselves in the context where query is too general (T i queryTooGeneral(q)) and must be precised. This implies some conventionally expected behavior from each participants: The user is expected to add keywords to the query or request a query launch. The agent is expected to offer the user to add a keyword or to specify one, the goal being to reduce the number of results. It can inform the user that the keyword it is offering to specify the query is actually a specification of a keyword of the query. It can also offer the user to launch the query. All these expected behaviors are explained in the following of this section.

The addition of keywords to the query by the user corresponds to the inform(x, queryKeyWord(kw)) * dialogue game. The user requests to the agent to launch the query with a request(x, launchQuery(q)) dialogue game. In this case, our collaborative agent will always accept the requests formulated by the user (that's why we only put the acceptRequest(y, launchQuery(q)) dialogical action commitment in the output row).

The agent offers to add keywords to the query with an offer(y, addKeyWord(kw)) * and to specify the query with an offer(y, specifyKeyWord(kw, skw)) * . In each case, the user can accept or decline the offer. If he accepts the offer, the conversational gameboard is updated with the commitments generated by execution of the action (keyword addition that generates C(y, queryKeyWord(kw), Crt) * or query specification that generates C(y, queryKeyWord(skw), Crt) * and C(y, queryKeyWord(kw), Ina) * , as skw replaces kw). If the user declines the offer, the action fails (the commitment on the action becomes Fal: C(y, addKeyWord(kw), Fal) * or C(y, specifyKeyWord(kw, skw), Fal) * ).

In the case where the agent proposes to specify a keyword, it can play a sub-dialogue game (inform(y, isSpecification(kw, skw))) to inform the user that the new keyword is a specification of one keyword. The trigger of this sub-dialogue game is empty, because all the conditions needed to play this dialogue game (i.e. checking that skw is actually a specification of kw) are already reached in the parent dialogue game.

When the query has been specified enough, the agent can offer to launch it, if the user did not already decline the offer to launch it.

For illustrative purposes, we defined arbitrarily in Equations 3 the trigger predicates used in Table 4. These definitions depend on the expected behavior we want our agent to adopt. Trigger 3a makes sure that the query q is the last launched. Trigger 3b points that the query q is too general (i.e. the results are too numerous). The predicate queryResultsNb(q) gives the number of results returned by the search engine when launching query q. Trigger 3c

Query precision

Access ∧ T i C(x, ¬queryResultsSatisfying(q), Crt) T i lastQueryLaunched(q) T i queryTooGeneral(q) Expected game inform(x, queryKeyWord(kw)) * Output T j C(x, queryKeyWord(kw), Crt) * Expected game request(x, launchQuery(q)) Output acceptRequest(y, launchQuery(q)) ⇒ T j C(y, launchQuery(q), Crt) Expected game offer(y, launchQuery(q)) * Trigger T j C(y, launchQuery(q), Fal) ∧ T i queryPreciseEnough(q) Output ∨ acceptOffer(x, launchQuery(q)) ⇒ T j C(y, launchQuery(q), Crt) declineOffer(x, launchQuery(q)) ⇒ T j C(y, launchQuery(q), Fal) * means that a keyword kw, related to the verbalization of the user (relatedToVerbalization(kw)), brings precision to the current query (currentQuery(q)). Trigger 3d gives a keyword (skw) more specific than a current one (kw). The predicate isMeSHHyponym(kw, skw) gives the information that skw is an hyponym (a more specific word) of kw according to the MeSH lexicon. Trigger 3e expresses that query q is precise enough to be proposed to the user for launch. lastQueryLaunched(q) : T i → ∃n ≤ i, ∧ T n C(y, queryLaunched(q), Crt) T n-1 C(y, queryLaunched(q), Crt)

∧ m > n, ∀q' q, ∧ T m C(y, queryLaunched(q'), Crt) T m-1 C(y, queryLaunched(q'), Crt)

queryTooGeneral(q) : T i → queryResultsNb(q) ≥ 75 (3b) relevantForPrecision(kw) : T i → ∃q, currentQuery(q), queryResultsNb(q) > queryResultsNb(q + kw), relatedToVerbalization(kw) (3c) specification(kw, skw) : T i → isMeSHHyponym(kw, skw) (3d) queryPreciseEnough(q) : T i → ∃q, currentQuery(q), queryResultsNb(q) < 75 (3e)

Conclusion and future work

Our work is based on a cognitive study of a corpus of h-h collaborative DR task for the quality-controlled health portal CISMeF. Starting with a scenario of a collaborative DR task, built from the analysis of this corpus, we adapt it in a h-m context, where an assistant agent (software) helps a user in his task.

In this article, we described a model to specify a collaborative task in terms of social commitments. We shown how these social commitments link the task itself to the interaction with the user. This model has been applied to the CISMeF portal to specify each steps of the scenario in terms of social commitments. The notion of triggers in our model implements the deliberative process of the assistant agent. The agent's reasoning can be very reactive with simple rules or, on the contrary, it can entail a more high level decision process.

We currently work on these triggers to express the decision process of our assistant agent. As a matter of fact, it concerns the reasons of the agent both to enter a step of the scenario and to choose the dialogue game to play.

The validation of our system consists in evaluating the added value brought to CISMeF. The idea is to compare the queries made by the user with and without our assistant agent. This comparison would be made by calculating queries precision and recall.

Finally, to prove the genericity of our approach (the scenario, the model, the dialogue games, ...), we have started to investigate collaborative document retrieval on a transport law database (http://www.idit.asso.fr).

Table 1 .

 1 Generic step table. DG is a dialogue game and SDG is a sub-dialogue game. α, β k , γ are actions, p, p k and p k ' are propositions, DA1 and DA2 are dialogical actions and E k are predicates. z and z' stand for the participants to the interaction.s, s 1 and s 2 are states.

Table 2

 2 presents a translated extract of a dialogue (explained in Section 4.2.2).

	A1	[. . . ] Perhaps we can try to widen the search in our case if we consider the words we used
	B2	We didn't use that much already
	A3	Ummm, forget it then
	B4	Why remove / we can remove "analysis"
	A5	So let's remove "analysis"
	B6	And "diagnostic"
	A7	Yes
	[. . . ]
	A8	[. . . ] I am almost tempted to put diagnostic anyway because / because we will see what it yields
	B9

Table 3 .

 3 Verbalization precision step, i < j.

			Verbalization precision
	Access	T i C(x, preciseVerbalization, Crt)
	Expected game inform(x, verbalizationExpression(e)) *
	Output	∧	T j C(x, verbalizationExpression(e), Crt) * T j C(x, preciseVerbalization, Ful)
	Expected game inform(x, verbalizationComplete)
	Output	T j C(x, verbalizationComplete, Crt)

Table 4 .

 4 Query precision step, i < j. x stands for the expert agent, y for the user and z either for the user or the expert agent

  declineOffer(x, specifyKeyWord(kw, skw)) ⇒ T j C(y, specifyKeyWord(kw, skw), Fal) *

	Expected game offer(y, addKeyWord(kw)) *
	Trigger	T i relevantForPrecision(kw)
	Output	∨	acceptOffer(x, addKeyWord(kw)) ⇒ T j C(y, queryKeyWord(kw), Crt) * declineOffer(x, addKeyWord(kw)) ⇒ T j C(y, addKeyWord(kw), Fal) *
	offer(y, specifyKeyWord(kw, skw)) Expected game offer(y, specifyKeyWord(kw, skw)) Expected game inform(y, isSpecification(kw, skw))
	Trigger	∅
	Output	T

* Trigger T i C(z, queryKeyWord(kw), Crt) ∧ T i specification(kw, skw) Output ∨ acceptOffer(x, specifyKeyWord(kw, skw)) ⇒ ∧ T j C(y, queryKeyWord(skw), Crt) * T j C(y, queryKeyWord(kw), Ina) * j C(y, isSpecification(kw, s), Crt)


domain: shs sdv sdv.mhep

text:
Caroline Huyard
email: caroline.huyard@univ-lille2.fr

Luc Derijks

Louis Lieverse

Intentional Nonadherence as a Means to Exert Control

Keywords: adherence, compliance, nonadherence, noncompliance, chronic, illness and disease, experiences, motivation, power, empowerment, self-care, self, Western Europe, Europe, Europeans, interviews, research strategies, coding, qualitative, failure modes and effects analysis (FMEA)

Medication adherence is a major issue for patients with a chronic illness, who sometimes rationally choose temporary nonadherence. This study aims at better understanding intentional nonadherence and especially why it seems to fluctuate over time. It is based on 48 semi-structured interviews conducted in a hospital in the Netherlands with patients who had been prescribed a medication for a chronic disease for at least 1 year, and who had either type 2 diabetes, hypertension, Parkinson's disease, inflammatory bowel disease, or chronic myeloid leukemia. The analysis uses a simplified version of the failure modes and effects analysis (FMEA) method. Intentional nonadherence appeared to be the result of the respondents' desire (a) to exert control over the treatment and its effects on their body, and (b) to control the hold of the treatment on their daily life. This result provides a rationale for the fluctuation of intentional nonadherence behavior.

Introduction

Nonadherence, or poor adherence, is one of the major contemporary challenges in the field of health. Adherence can be defined as "the extent to which a person's behavior-taking medication, following a diet, and/or executing lifestyle changes, corresponds with agreed recommendations from a healthcare provider" (World Health Organization, 2003, p.4). According to the World Health Organization (2003), nonadherence affects 50% of chronic patients in developed countries and leads to poor health outcomes and increased health costs, so that increasing the effectiveness of adherence interventions may have a greater impact on the health of the population than any improvement in specific medical treatments. Understanding the reasons for nonadherence is therefore essential.

As chronic diseases were expanding in the early 1980s, some authors have suggested that it could be useful to distinguish between intentional and unintentional adherence [START_REF] Cooper | Intentional prescription nonadherence (noncompliance) by the elderly[END_REF] arguing that if nonadherence was intentional, efforts aimed at reducing forgetting to take the medications would have little chance to help the patients. In line with this insight, many studies have tried to evidence what factors could lead patients to intentional nonadherence and what factors could lead them to unintentional nonadherence. Various definitions of intentional nonadherence were crafted for this purpose, ranging from the rather neutral views that intentional nonadherence involves deliberate decisions to adjust medication use [START_REF] Laba | Understanding rational non-adherence to medications. A discrete choice experiment in a community sample in Australia[END_REF] and occurs when patients actively choose not to follow treatment recommendations [START_REF] Daleboudt | Intentional and unintentional treatment nonadherence in patients with systemic lupus erythematosus. A r t h r i t i s C a r e & R e s e a r c h[END_REF] or discontinue, skip or alter the dose of medication they had been prescribed [START_REF] Iihara | Comparing patient dissatisfaction and rational judgment in intentional medication non-adherence versus unintentional nona d h e r e n c e[END_REF] to more hypothesis-ladden views, such as the ones that nonadherence occurs when patients miss or alter doses to suit their needs [START_REF] Wroe | Intentional and unintentional nonadherence: A study of decision making[END_REF] and it is associated with motivation and patients' beliefs about taking medications [START_REF] Clifford | Understanding different beliefs held by adherers, unintentional nonadherers, and intentional nonadherers: Application of the Necessity-Concerns Framework[END_REF].

There is now a large body of studies that investigated why patients would rationally choose nonadherence. Some major factors have been identified. Most studies agree that medications' side effects strongly contribute to patients' intentional nonadherence [START_REF] Khan | Barriers to and determinants of medication adherence among hypertensive patients attended National Health Service Hospital, Sunderland[END_REF][START_REF] Laba | Patient preferences for adherence to treatment for osteoarthritis: The Medication Decisions in Osteoarthritis Study (MEDOS)[END_REF][START_REF] Laba | Understanding if, how and why non-adherent decisions are made in an Australian community sample: A key to sustaining medication adherence in chronic disease[END_REF][START_REF] Noens | Measurement of adherence to BCR-ABL inhibitor therapy in chronic myeloid leukemia: Current situation and future c h a l l e n g e s . H a e m a t o l o g i c a[END_REF][START_REF] Thunander Sundbom | Women and men report different behaviours in, and reasons for medication non-adherence: A nationwide Swedish survey[END_REF]. A large number of studies have also highlighted the role of patients' beliefs about the benefits and the necessity of their treatment in their decision not to take it as prescribed [START_REF] Chambers | Adherence to medication in stroke survivors: A qualitative comparison of low and high adherers[END_REF][START_REF] Iihara | Beliefs of chronically ill Japanese patients that lead to intentional non-adherence to m e di c a t i on[END_REF][START_REF] Laba | Understanding rational non-adherence to medications. A discrete choice experiment in a community sample in Australia[END_REF][START_REF] Wileman | Choosing not to take phosphate binders: The role of dialysis patients' medication beliefs[END_REF], and in line with this, studies showed that patients' judgments on the absence of symptoms [START_REF] Ulrik | The patient's perspective: Adherence or non-adherence to asthma controller therapy? The Journal of Asthma[END_REF], their concern beliefs [START_REF] De Vries | Medication beliefs, treatment complexity, and nonadherence to different drug classes in patients with type 2 diabetes[END_REF], perceived risks [START_REF] Laba | Understanding rational non-adherence to medications. A discrete choice experiment in a community sample in Australia[END_REF][START_REF] Ulrik | The patient's perspective: Adherence or non-adherence to asthma controller therapy? The Journal of Asthma[END_REF][START_REF] Wileman | Choosing not to take phosphate binders: The role of dialysis patients' medication beliefs[END_REF], or their perception that the treatment would be ineffective [START_REF] Laba | Understanding if, how and why non-adherent decisions are made in an Australian community sample: A key to sustaining medication adherence in chronic disease[END_REF] foster nonadherence behaviors. This is in line with many qualitative studies pointing to patients' broader concerns about medications as potentially harmful products and their preference to take as little as possible [START_REF] Pound | Resisting medicines: A synthesis of qualitative studies of medicine t a k i n g[END_REF]. Last, many studies agree on the role of health care payment systems: When patients must contribute significantly to the cost of their treatment, they tend to be less adherent [START_REF] Laba | Patient preferences for adherence to treatment for osteoarthritis: The Medication Decisions in Osteoarthritis Study (MEDOS)[END_REF][START_REF] Laba | Understanding if, how and why non-adherent decisions are made in an Australian community sample: A key to sustaining medication adherence in chronic disease[END_REF][START_REF] Wileman | Choosing not to take phosphate binders: The role of dialysis patients' medication beliefs[END_REF]. Other factors have also been identified, such as treatment schedule [START_REF] Laba | Understanding rational non-adherence to medications. A discrete choice experiment in a community sample in Australia[END_REF][START_REF] Laba | Patient preferences for adherence to treatment for osteoarthritis: The Medication Decisions in Osteoarthritis Study (MEDOS)[END_REF][START_REF] Wileman | Choosing not to take phosphate binders: The role of dialysis patients' medication beliefs[END_REF], patient-practitioner relationships [START_REF] Laba | Understanding rational non-adherence to medications. A discrete choice experiment in a community sample in Australia[END_REF], patients' behavioral skills regarding illness and treatment [START_REF] Norton | Informationmotivation-behavioral skills barriers associated with intentional versus unintentional ARV non-adherence behavior among HIV+ patients in clinical care[END_REF], age, and selfefficacy [START_REF] Ostini | Investigating the association between health literacy and non-adherence[END_REF]. Some reviews ruled out two potential explanatory factors, namely, a linear relationship between intentional nonadherence and health literacy [START_REF] Ostini | Investigating the association between health literacy and non-adherence[END_REF] and psychosocial predictors such as coping styles, social influences and social support, personality traits, and psychosocial wellbeing [START_REF] Zwikker | Psychosocial predictors of non-adherence to chronic medication: Systematic review of longitudinal studies[END_REF].

Recently, some studies have focused on the temporal dimension of adherence and intentional nonadherence behavior. Several studies point out that intentional nonadherence is usually a temporary and reversible phenomenon and not a complete discontinuation [START_REF] Murdoch | Challenging social cognition models of adherence: Cycles of discourse, historical bodies, and interactional order[END_REF][START_REF] Laba | Understanding if, how and why non-adherent decisions are made in an Australian community sample: A key to sustaining medication adherence in chronic disease[END_REF][START_REF] Wroe | Intentional and unintentional nonadherence in patients prescribed HAART treatment regimens[END_REF]. Patients report that they sometimes "take a break" [START_REF] Norton | Informationmotivation-behavioral skills barriers associated with intentional versus unintentional ARV non-adherence behavior among HIV+ patients in clinical care[END_REF] This is important, because the factors and reasons for intentional nonadherence listed above do not adequately account for these fluctuations. Existing studies indeed investigated intentional nonadherence as the rational decision to take or not to take the treatment [START_REF] Herrera | Understanding non-adherence from the inside: Hypertensive patients motivations for adhering and not adhering[END_REF][START_REF] Wroe | Intentional and unintentional nonadherence: A study of decision making[END_REF] and considered some parameters that could be involved in weighing the decision, such as information about the disease, about the treatment, and about the benefits and the expected risks; beliefs based on personal experience and personal values; and some constraints, especially economic and practical ones. But for nonadherence to be temporary, this would imply that the information, beliefs, and constraints fluctuate over time and result in similar fluctuations in treatment adherence behavior. This may happen over a time span of several years, but does not seem plausible over the much shorter time span of a few weeks or days evidenced in the studies. So why does intentional nonadherence fluctuate over time?

In this study, we aimed to better understand the reasons for fluctuations in intentional nonadherence behaviors. For this purpose, we draw on a classical idea in the sociology of health, namely, that chronic patients have to perform a certain amount of work [START_REF] Corbin | Unending work and care: Managing chronic illness at home[END_REF][START_REF] Senteio | Trying to make things right: Adherence work in high-poverty, African American neighborhoods[END_REF]. A key dimension of treatment behavior in chronic diseases lays in its repetitive and active nature over long periods of time. Indeed, adherence in chronic diseases means that the patients succeed in performing medication taking, disease monitoring, or carrying on an appropriate lifestyle every single day for decades. In particular, medication adherence behavior is the concrete task of taking the right amount of the right medication at the right time and in the right circumstances. In this perspective, adherence is similar to a prescribed work for which the worker has to use particular tools, at particular stages, to perform a task in a particular way to reach a particular goal. The reasons why workers do not perform their tasks as prescribed can refer to a variety of reasons that are hypothesized not to be only a matter of information, knowledge, or belief. Thus, what must be understood is why the patients sometimes perform treatment adherence as prescribed and sometimes decide to perform this task in their own way.

Method

This study is based on 48 semi-structured interviews conducted in a public hospital in the Netherlands in 2014 with patients suffering from type 2 diabetes , hypertension, Parkinson's disease, inflammatory bowel disease, or chronic myeloid leukemia who had been prescribed a medication for a chronic disease for at least 1 year. The conditions were selected to have a sample of contrasting situations with respect to treatment and medication practice and to factors that influence them. Some often involve doctor-prescribed lifestyle changes in addition to medication taking (diabetes and hypertension), others often involve patient-chosen lifestyle changes (inflammatory bowel disease), others involve none (Parkinson's disease and chronic myeloid leukemia), and it is known that whether a treatment regimen is limited or pervasive is important [START_REF] Dimatteo | Variations in patients' adherence to medical recommendations: A quantitative review of 50 years of research[END_REF]. Some conditions react to treatment in a way that cannot be monitored by the patients themselves (chronic myeloid leukemia), others can be monitored by the patients themselves on the basis of their own bodily perceptions (Parkinson's disease, inflammatory bowel disease), and others can be monitored by the patients themselves on the basis of their own bodily perceptions or of specific devices (diabetes and hypertension). Some conditions have acute phases (inflammatory bowel disease) or an acute onset (chronic myeloid leukemia, sometimes hypertension), and it is known that both the modes of perception of the illness and its critical phases play a role in medication practices [START_REF] Conrad | The meaning of medications: Another look at compliance[END_REF]. The Institutional Review Board/Independent Ethics Committee of the Máxima Medical Center declared that this study did not have to be reviewed by a medical ethics board according to the Dutch Medical Research Involving Human Subjects Act (WMO). Each interviewee's informed written consent was recorded. Outpatients were contacted by a research nurse or a physician. They were selected according to a simple systematic procedure: The patients were asked some time prior to a scheduled appointment if they would accept an interview in addition to their medical appointment. The first patients who did accept to participate were included. No patient declined to take part. The interview guide addressed the patient's medical history (asking, for instance, "Could you describe how your illness began?") and medical treatment (e.g., "What do you personally expect from this treatment?"), how the medical treatment was integrated into daily life (e.g., "Have you found out particular tricks to help you deal with your illness? What tricks? Did you mention them to your doctor?"), patient's personal experience of the illness (e.g., "Do you sometimes feel weary/discouraged/angry about your treatment? What are the consequences of these feelings?"), patient's knowledge and needs about the disease (e.g., "Where do you find the information you need about your illness and your treatment?"), and illness and treatment disclosure (e.g., "Do your relatives and your friends know about your illness? And about your treatment? How have they been informed about it? How did they react?"). The interviews were recorded and fully transcribed.

The interviewees have a range of backgrounds and family situations that make the interviews diverse enough, while these sociodemographic characteristics are not different from those of the patients' population. Their sociodemographic characteristics are given in Table 1.

The research was informed by the method of failure modes and effects analysis (FMEA; [START_REF] Franklin | Failure mode and effects analysis: Too little for too much?[END_REF]. This method is used in engineering and more specifically quality engineering, including quality engineering with respect to safety hazards [START_REF] Lux | FMEA and consideration of real work situations for safer design of production systems[END_REF] or with respect to human mistakes [START_REF] Hertig | Development and assessment of a medication safety measurement program in a long-term care pharmacy[END_REF]. It is used for identifying all possible failures in a design, a manufacturing or assembly process, or a product or service. It can be used for different purposes, including analyzing failures of an existing process. It addresses a particular function in a process, a product, or a service and aims to identify potential failure modes, potential effects of the failure, potential causes of failure and their occurrence rate, the current process controls and their detection rate, recommended actions to lower occurrence or severity of failures, and the results of these actions. For instance, FMEA can be used to improve safety in a radiation oncology unit [START_REF] Ford | Evaluation of safety in a radiation oncology setting using failure mode and effects analysis[END_REF], where a safe and effective radiotherapy treatment has to treat the correct tissue in the correct patient with the correct dose. Used in a prospective way, FMEA starts with describing the work flow in the unit from the patient's point of view and recording each event that happens to that patient or that patient's medical record. This first part of the analysis helps better visualize what should happen in the unit. It allows for description of subprocesses and identification of possible failures in these processes. On this basis, it is possible to score the severity, frequency, or detectability of failures, and to identify improvements that are feasible and effective. This second part of the analysis highlights what could happen and should be prevented.

A key characteristic of this method is thus its focus on the discrepancy between what is prescribed and how and why things could be different from the prescription and go awry. It is very well suited to the analysis of work flows, and this is precisely how we chose to understand and analyze nonadherence. What has been prescribed is for the patient to take the right amount of the right medication prescribed by the medical professional at the right time. What can happen and have negative consequences is any departure from this pattern of tasks. We focused on intentional departures and intentional nonadherence, that is, when patients actively choose not to follow treatment recommendations [START_REF] Daleboudt | Intentional and unintentional treatment nonadherence in patients with systemic lupus erythematosus. A r t h r i t i s C a r e & R e s e a r c h[END_REF]. FMEA then allows a rigorous and complete understanding of the tasks patients have to perform when taking their medication and of why they sometimes rationally choose to act differently. We would suggest that this makes FMEA patient-centered.

We adapted and used FMEA in a very simplified and retrospective way, as follows: First, all the instances of intentional nonadherence reported in the interviews were identified (i.e., each instance of an actual or potential intentional departure from the prescription, either regarding the medication itself, the amount of the medication, the time when it was taken, or the way to take it); second, these instances were coded and sorted out according to the reason for nonadherence; and third, the labels were blind cross-checked by a second researcher, and differences were discussed until agreement was reached on the final coding. Table 2 illustrates the result of this procedure for two instances.

Results

Among the 48 interviews, eight contained no instance of nonadherent behavior at all, 21 interviews contained at least one instance of intentional nonadherent behavior, and 28 interviews contained at least one instance of unintentional nonadherent behavior (10 interviews contained both instances of intentional and unintentional nonadherent behavior, and are therefore counted in both groups). In the 21 interviews containing instances of intentional nonadherence, there was a total of 30 such instances (this includes instances of a strong temptation of nonadherence, even if there was no actual nonadherence behavior, because the explanations given by the respondents were interesting).

The analysis of the interviews showed that intentional nonadherence behavior had two main causes:  The desire of the respondents to exert personal control over the treatment and its effects on their body, especially to avoid side effects, but also to assess the treatment's effectiveness, or to adapt the doses or the schedule to their case (19 instances in 12 interviews).  The desire of the respondents to control the hold of the treatment on their life, their time, and their activities (11 instances in 10 interviews with only one respondent in both groups).

Patients' Desire to Exert Personal Control Over the Treatment and its Effects on Their Body

In accordance with the results of previous studies, side effects were often reported by the respondents as the trigger for temporarily modifying or interrupting their treatment. However, it was never merely to remove an unpleasant effect of the treatment. The respondents' concerns were wider and deeper, relating to the need to exert personal control over the treatment and its effects on their body. Faced with possible side effects, the respondents explained that they first needed to assess whether their complaints were actually related to their treatment. For this purpose, they performed an experiment. They interrupted the treatment to see whether this resulted in a removal of the complaints, as reported by a 63-year-old woman who has had hypertension for more than 10 years: Eh . . . For a long time, it was fine with those medications, but now, I happen to have some problems with micardis [one of the prescribed medications], I think. Because, on the leaflet, it says that throat complaints can appear. And according to the doctor, it is very infrequent. But, he said, it might be possible. And actually I tried it this week. I have stopped the medication for one week . . . Yes, and I should not do that, because then "psssst" the [tension] values go up. But I'm in a choir, and I can in fact hardly sing, and I find it a real pity. And there's something with temperature; when I change rooms, it completely blocks my throat. And I never had that before. So, I guess that it has to do with the medication. Yes.

Similarly, the respondents reported that they modify their treatment to be able to control when side effects would occur. This describes what this 47-year-old woman who has had chronic myeloid leukemia for 7 years does:

Yes, I have sometimes spent one day without taking it. . . . When we go out for dinner and I have eaten so much, I know that I won't have a good night's rest. I've experienced it a couple of times, and then I thought that it was because of the medication, so I thought, I'm not taking it today. But just once, then (laughs).

This line of reasoning helps in understanding why intentional nonadherent behaviors may be temporary and fluctuating. When personal circumstances make the burden of side effects heavier, patients may try to contain them and thus be deliberately nonadherent. On the contrary, when they can withstand the side effects, they may be more adherent.

In the absence of side effects, some respondents explained that they remained cautious because they consider medications as potentially harmful. They try to keep the dose they take as low as possible, as reported by this 68-year-old man who has had Crohn's disease for 34 years:

Yes, it was about my question: what does the medication do to my body after nearly 30 years of use? And so he (the doctor) said it himself. He had the idea: now we may perhaps reduce it a bit. See what happens. And I must say, a couple of years ago, I did that too; I did that on my own initiative. At least, I had told him: now, I want to reduce it by half. At that time, I had four pills to take, and I reduced from four to two. And after half a year, it became more difficult to empty my bowel. . . . And then, I simply decided to take four again on my own initiative. So . . . And of course I told him that when we met on the next appointment. That's how I had done that. So.

Treatment control

The desire to assess the effects of the treatment is not limited to identification or to the prevention of side effects. This concern is only the most visible part of the assessment and adjustment practices of the respondents. They also want to assess their treatment's effectiveness and sometimes do so by assessing the results of their medical examinations against their past adherence behavior. This is the case with a 52-year-old man who has had type 2 diabetes for 22 years and who reported that he had unintentionally interrupted his treatment for a few days:

And in fact, it (the blood glucose level) was not sky-high at all. And so I thought something like: hey, when I don't take the medication, the values are not very different from what they are when I take it. And then, I acted in a very rigorous manner, eh . . . differently, sort of: I didn't take the medication, but I also almost hardly ate. In the long run, I knew that this was not good. And then, my values were even better than they had been with the medication. And from that moment, yes, I lost confidence in the treatment.

These assessments and the conclusions that the patients draw from them thus offer a better understanding of the nature of temporary intentional nonadherence. Indeed, if the results of medical examinations are satisfactory, the patients are encouraged to carry on their treatment behavior. Conversely, if the medical examinations deliver disappointing results, the patients will be more prone to modify their behavior. This is what happened with this 67-year-old man who has had type 2 diabetes for 50 years:

When you start changing this and that, it's fine, but then, you notice, oh God, it's not so good. And then at some point, you notice that you have more headaches, or that you don't see so well, and then you check your blood sugar, and you see that it is too high again. Or you experiment a bit with the insulin. No, I don't do that anymore. Some intentionally nonadherent treatment behaviors thus result from the desire to exert a form of personal control over the treatment and its positive as well as negative, and long-term as well as short-term, effects on the disease and the body. Among the 21 respondents who reported instances of intentional nonadherence, 12 reported that they had deliberately modified their treatment to check for side effects, prevent potentially harmful long-term effects, or improve its effectiveness, by assessing the effects on their body, complaints, and medical data of these behavior changes. These respondents were eight men and four women: four with hypertension, four with type 2 diabetes, two with chronic myeloid leukemia, one with inflammatory bowel syndrome, and one with Parkinson's disease. Among these 12 respondents, five were 66 years old and over, five were between 50 and 65 years old, and two were between 30 and 49 years old; nine were married, one was cohabiting, and two were divorced; and 11 had completed secondary education, and two had completed tertiary education. Compared with all 48 respondents, men are overrepresented in this group but it is not possible to draw conclusions from this observation.

Patients' Desire to Control the Hold of the Treatment on Their Life, Their Time, and Their Activities

To our knowledge, the second cause of nonadherence reported by the respondents had not been identified until now. Some respondents stated that their intentional nonadherence resulted from a desire to control and contain the hold of the treatment on their life, their time, and their activities. They felt that this hold was sometimes too strong for them, on a practical and on a motivational plane. On a practical plane, the respondents tried to limit or reduce the time they have to dedicate daily to health care, by removing parts of the related tasks or by adjusting them. On a motivational plane, they sometimes felt that the efforts did not match the results and searched for treatment modifications that would enable them to overcome demotivation.

Some respondents expressed that their treatment is a burden and that they sometimes feel that this burden is too heavy for them. Then, they have to remove the heaviest parts of this burden. These parts were often related to diet, physical activity, or measuring biological values themselves, and to a lesser extent, the medications. In particular, the most time-consuming treatment-related tasks may appear particularly demanding, to the extent that some respondents refused to perform these tasks. This was the case for this 69year-old man, who has had Parkinson's disease for 12 years. He explained that he rigorously complied with the medical recommendations in general, but he sometimes felt that this went beyond his capacity: At some point, I'd had it with the exercises that I had to do at home. Because I had to exercise every day between 15 minutes to half an hour in the morning. And at some point I said: I can no longer do that. That's just too much for me. Yes, I was busy with it for the whole day. There was nothing else anymore.

A similar feeling of having to perform an impossible task was described by this 76-year-old woman, who has had type 2 diabetes for 15 years:

You know what I find annoying? The food lists. For three days, you must write down precisely what you eat. For each lick of butter, and this is really impossible for me, I have to look at the packet of butter and write down the carbohydrates and count them, for one day. Well, this list, I tend sometimes to, hmm . . . throw it away. These nonadherent behaviors are not limited to physical activities, diet, or measuring. Medication taking can also be experienced as a burdensome task. This was what this 29-year-old man who has had inflammatory bowel disease for 4 years said, And during the summer, I went to Vietnam with my brother, and I had to take one and a half pills per day, one pill in the morning and half a pill in the evening, and yes, in the evening, most of the time, we had had dinner, and we were sitting with a beer and then I thought: oh yes, the half pill? It did not make sense. So, for a while, I took just one pill. . . . It's because this half pill is not practical. So he (the doctor) said, let's simply take one pill every day, and twice in the week, two pills. So.

The amount of work the patients have to perform because of a chronic illness can thus lead them to temporarily remove or modify some tasks and result in intentional nonadherence.

But the nature of this work, and not only its quantity, also elicited such behaviors. Indeed, the respondents expressed they were sometimes downhearted about their treatment, saying, for instance, "I'd had enough" and "it does not make sense." The lack of positive perspective seems to lead patients to question being fully adherent to their treatment and sometimes to consider interrupting it.

This is what one respondent described about measuring. This 68-year-old woman who has had type 2 diabetes for 20 years knows what the consequences of nonadherence would be, but she explained that this does not counterweigh her feeling of uselessness regarding some treatment-related tasks:

A couple of years ago, I said something like: I'm not writing my measurements any longer and . . . it does not make sense. Then the doctor got angry and said: yes, you can stop that, but then you should just let us know. That was it (laughs). He did not understand. No. That this sometimes takes you by the throat, all the things you have to do, all these controls. Yes . . . I know well what the consequences would be of course, hey? Yes I mean . . . But sometimes, you don't mind, hey? There are such moments, but, well.

As previously, medication taking was not reported to be the first task affected by intentional nonadherence. However, some respondents explained that they are sometimes disheartened about it, as did this 60-year-old man who has had type 2 diabetes for 4 years: Sometimes, I'm fed up with it. So, yes, every day, eight pills. The blood pressure and all. At some point, I'm really fed up with it. But, but . . . I simply take them, though, so hm . . . [laughs]. I know . . . I'm not angry, but again and again you have to do these things. Sometimes, yes, I am fed up with it. But . . . I have to keep going.

The temptation of nonadherence seems related to the fact that a daily task does not produce satisfactory or tangible results and therefore becomes disheartening. Respondents said they knew that the consequences of nonadherence would be negative and they had no choice in this respect. But these arguments are not always enough to keep them motivated. Thus, they sometimes try to cope by temporarily interrupting their treatment. This describes the situation with this 38-year-old woman who has had hypertension for 5 years and was prescribed a diet:

Of course [laughs]. There are many things that I am not allowed to eat (laughs). Yes, yes and then . . . That's something I was fed up with, for instance, during last summer holidays. That's something I've stopped. At some point, I'd had enough with it. I thought it simply did not make sense to me . . . to drop this and drop that . . . Of course, this has consequences. This has consequences on my blood sugar values, on the cholesterol . . . Of course, this has an effect.

A similar behavior was reported by this 67-year-old man, who has had type 2 diabetes for 20 years, and who insisted that he needed to be temporarily in control over his life, in spite of the negative consequences he would experience afterwards:

At some point, you rebel; you think, now, it's enough. Now, I do for once something that I have decided myself. But after some days, there is the weighing scale and you are really punished.

This complex feeling of uselessness, weariness, and need for control over one's life thus leads to temporary nonadherence behaviors that aim to put a temporary end to an absurd-seeming task, to store up energy during this treatment break, to do enjoyable things, and to be in control again.

This type of nonadherence behavior was described by 10 respondents. Among them were six men and four women; six had type 2 diabetes, two inflammatory bowel disease, one had hypertension, and one had Parkinson's disease. Among them, five were 66 years old and above, three were between 50 and 65 years old, one was between 30 and 49, and one was below 30 years old; seven were married and three were single; and two had completed primary education only, six had completed secondary education only, and two had completed tertiary education. Contrary to what one might have expected, type 2 diabetes and hypertension are not overrepresented, and young patients are also present in this group. However, it is not possible to draw a conclusion from these observations.

Discussion and Conclusion

This study evidenced two causes of intentional nonadherence that had not been, to our knowledge, identified previously: A desire to control the effects of the treatment, and thus to adjust the treatment through self-designed micro experiments, and a desire to control and contain the hold of the treatment on personal life, which can cause the patients to reject or modify certain treatment-related tasks or to take breaks when they are disheartened. Identifying these two types of control allows a better understanding of the temporary and fluctuating dimension of intentional nonadherence.

The FMEA method was useful to connect both objective and subjective dimensions of intentional nonadherence, that is, the concrete behavior of the interviewees and their interpretation thereof. Indeed, focusing on the instances of intentional discrepancies between prescribed and actual behavior, and not only on patients' subjective experience in general, allowed us to engage in a deeper understanding of the fluctuations of adherence behavior and the reasons for it. The results of our study are thus in line with studies that pointed to the burden of managing a chronic illness, to its different dimensions such as financial burden, time and travel burden, medication burden, health care access burden [START_REF] Sav | Treatment burden among people with chronic illness and their carers in Australia[END_REF] or side effects, cost, time, impact on family and lifestyle [START_REF] Sav | Burden of treatment for chronic illness: A concept analysis and review of the literature[END_REF], and to its dynamic nature [START_REF] Sav | Burden of treatment for chronic illness: A concept analysis and review of the literature[END_REF]. However, the FMEA method made it possible to understand a key underlying dimension of this burden, namely, patients' feeling that there are losing control over their own life. The results of our study are also useful to better understand patients' strategies for adaptation and coping. Those aim not only at reducing the illness burden but also at holding on to control, even if the burden could appear relatively small for external observers.

The FMEA method would be of interest for medical teams wishing to help patients improve their adherence behavior. In line with the FMEA approach, adherence can indeed be viewed as a continual quality control cycle of assessing, adapting, and maintaining behaviors. Medical teams could, for instance, precisely describe the medication adherence process and the corresponding work flow, identify all the causes for possible divergences, and then think of how health practitioners could help patients both maintaining the work flow and exercising control.

These results emerged from an analysis of adherence as an active process, a set of tasks performed by patients with a chronic disease. This perspective is rooted in now classical sociological studies on the work of the patients and their relatives, and more particularly on health care tasks performed at home for chronic illness [START_REF] Corbin | Unending work and care: Managing chronic illness at home[END_REF][START_REF] Senteio | Trying to make things right: Adherence work in high-poverty, African American neighborhoods[END_REF]. Such a perspective can be fruitfully deepened and enriched by more recent psychological research on motivation and commitment in the workplace. Indeed, some results presented here are in line with this literature. The issue of routine jobs and the fact that unenriched routine work can lead to depression has long been known in the sociology and psychology of work [START_REF] Parker | Longitudinal effects of lean production on employee outcomes and the mediating role of work characteristics[END_REF]. The time that patients spend on their daily care is of course not equivalent to a full day of work, but the problem of routine clearly arises, as suggested by the disheartened perspective some respondents expressed about their treatment.

Another major issue in the sociology and psychology of work was also apparent in the interviews: autonomy. Job autonomy is very important for employees, and it has been evidenced that it could improve work performance [START_REF] Cordery | Reinventing work design theory and p r a c t i c e[END_REF][START_REF] Howard | The changing nature of work[END_REF]. Autonomy operates along three dimensions: method, timing, and goals [START_REF] Spector | Perceived control by employees: A metaanalysis of studies concerning autonomy and participation a t w o r k . H u m a n R e l a t i o n s[END_REF]. These dimensions are also present in the experiments reported by respondents: They chose a method for assessing the effects of their treatment on their body and biological parameters, they adjusted their time schedule, and they paid attention to the fit between their life goals and their activities, including health care activities. It is interesting to note that employees' autonomy is affected by the attitude of their superiors, and by how the supervisor (a) provides clear, attainable goals, (b) exerts control over work activities, (c) ensures that the requisite resources are available, and (d) gives timely, accurate feedback on progress toward goal attainment [START_REF] Cordery | Reinventing work design theory and p r a c t i c e[END_REF]. Studying how these results could be transposed to the therapeutic relationship, and how they affect treatment adherence, has the potential to improve our understanding of adherence.

Motivation in the workplace is related to autonomy but also to goal setting [START_REF] Locke | Building a practically useful theory of goal setting and task motivation: A 35year odyssey[END_REF]. This is probably one of the major challenges for the patients. All respondents expressed that they pursued negative goals, to the extent that all they could expect was to avoid getting worse and, at best, remain in their current state. This has a negative impact on their adherence behavior because such goals are not suited to maintain motivation in the long run. They produce no tangible results and may elicit the feeling that the goals are not attainable, precisely because they are not tangible. How these types of negative goals may influence patients' motivation at work would need to be examined closely, as well as how other, more tangible, goals could be devised and pursued.

Our study was limited to a particular cultural and institutional setting, in the Netherlands. Further studies in non-European countries and targeting more specifically other types of patients and/or other types of health services would be needed to fully confirm our results.

Patients need to act in an intentionally nonadherent way to exert control over the treatment and its effects on their body and to control the hold of the treatment on their life, their time, and their activities, and they subsequently modify their adherence behavior in accordance with the impact of these actions either on their condition or their personal life. This result provides a rationale for fluctuating nonadherence behavior and opens new research and intervention perspectives on this issue.

Table 1 .

 1 Sociodemographic Characteristics of the Interviewees.

			Number of
	Parameter	Value	Interviewees
	Sex
	Men Women		26 22
	Disease Type 2 diabetes	16
	Types 2 diabetes + hypertension Hypertension	6 8
	Inflammatory bowel disease Chronic myeloid leukemia	11 5
	Parkinson's disease Age, years	2
	Above 66 50-65		21 17
	30-49 Less than 30	7 3
	Personal life Married		33
	Cohabiting Single		5 4
	Divorced Widowed		3 3
	Education Primary education	9
	Secondary education Higher education	22 17

Table 2 .

 2 Outcome of the FMEA Procedure for Two Instances of Nonadherence.

	Prescribed Behavior	Actual Behavior	Reason for the Actual Behavior: Final Coding
	To inject insulin following a particular schedule	The only problem is the [insulin] injections. That's really hard for me. Yes, phhhh . . . And at one point I	Burden control
		had enough to inject 4 times a day. But yes, there is no alternative.
		Q: And what do you do? Well nothing really, I simply do it and I complain a
		bit and I talk a bit with the diabetes nurse. And then they'll come back with a different solution. A
		pump or something. Or I search one more time on the Internet. And then we gently start doing the
	To inject insulin following a	injections again. And we try to keep going. My blood sugar was always low, not too low, but it
	particular schedule	was always low. So last week, I thought that I would reduce them myself. The injections. Because I had
		seen [the doctor] the week before and he had said, well it's perfect. I said yes, but I think it is not
		enough, the blood sugar is too low. So I've decided to cut down myself, and he was very satisfied.

Q: But you had decided it on your own? I have done that on my own for one week. Adapting the quantity [of insulin].

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a Marie Curie grant of the European Commission (Marie Curie CIG 321855), by a grant from the Région Nord Pas-de-Calais and by a grant from Lille Métropole.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.