Deep learning-based dimensional emotion recognition for conversational agent-based cognitive behavioral therapy.

Internet-based cognitive behavioral therapy (iCBT) offers a scalable, cost-effective, accessible, and low-threshold form of psychotherapy. Recent advancements explored the use of conversational agents such as chatbots and voice assistants to enhance the delivery of iCBT. These agents can deliver iCBT-based exercises, recognize and track emotional states, assess therapy progress, convey empathy, and potentially predict long-term therapy outcome. However, existing systems predominantly utilize categorical approaches for emotional modeling, which can oversimplify the complexity of human emotional states. To address this, we developed a transformer-based model for dimensional text-based emotion recognition, fine-tuned with a novel, comprehensive dimensional emotion dataset comprising 75,503 samples. This model significantly outperforms existing state-of-the-art models in detecting the dimensions of valence, arousal, and dominance, achieving a Pearson correlation coefficient of r = 0.90, r = 0.77, and r = 0.64, respectively. Furthermore, a feasibility study involving 20 participants confirmed the model's technical effectiveness and its usability, acceptance, and empathic understanding in a conversational agent-based iCBT setting, marking a substantial improvement in personalized and effective therapy experiences.

[To assess Resilience of Russian cities under international sanctions and the consequences of COVID-19: a sociological study].

The paper presents the results of in-depth interviews and a questionnaire survey of the Russian cites administration representatives about cities resilience under the sanctions pressure and COVID-19. The survey was conducted by the Center for Territorial Changes and Urban Development of IPEI RANEPA in March-May 2023, it was attended by representatives of the administration of more than 50 cities of the Russian Federation. We found overall situation as stable: social programs are being implemented in full, unemployment is decreasing, construction of municipal facilities continues, problems with failures in the supply of spare parts, equipment and components are being solved. At the same time, the sanctions have affected the urban economy in completely different ways: while in some cities show significant negative effect, in others the impact of sanctions is insignificant. Cites face number of new challenges: disruption of supply chains, refusal to supply paid equipment, inability to find analogues of imported equipment with the necessary characteristics, rising prices for spare parts. components and construction materials, the rupture of established sales channels to unfriendly countries, a drop in municipal budget revenues, etc. The heads of the city administration work overtime to solve emerging problems, organize interaction between enterprises, establish and deepen business contacts with friendly countries, put forward proposals to improve the situation at the federal level. New tasks successfully solved, although it requires serious efforts. To respond to new challenges, we need a new, more decentralized and local-oriented style of public administration, a process of well-established feedback.

Transcriptome Dynamics and Cell Dialogs Between Oocytes and Granulosa Cells in Mouse Follicle Development.

The development and maturation of follicles is a sophisticated and multistage process. The dynamic gene expression of oocytes and their surrounding somatic cells and the dialogs between these cells are critical to this process. In this study, we accurately classified the oocyte and follicle development into nine stages and profiled the gene expression of mouse oocytes and their surrounding granulosa cells and cumulus cells. The clustering of the transcriptomes showed the trajectories of two distinct development courses of oocytes and their surrounding somatic cells. Gene expression changes precipitously increased at Type 4 stage and drastically dropped afterward within both oocytes and granulosa cells. Moreover, the number of differentially expressed genes between oocytes and granulosa cells dramatically increased at Type 4 stage, most of which persistently passed on to the later stages. Strikingly, cell communications within and between oocytes and granulosa cells became active from Type 4 stage onward. Cell dialogs connected oocytes and granulosa cells in both unidirectional and bidirectional manners. TGFB2/3, TGFBR2/3, INHBA/B, and ACVR1/1B/2B of TGF-ß signaling pathway functioned in the follicle development. NOTCH signaling pathway regulated the development of granulosa cells. Additionally, many maternally DNA methylation- or H3K27me3-imprinted genes remained active in granulosa cells but silent in oocytes during oogenesis. Collectively, Type 4 stage is the key turning point when significant transcription changes diverge the fate of oocytes and granulosa cells, and the cell dialogs become active to assure follicle development. These findings shed new insights on the transcriptome dynamics and cell dialogs facilitating the development and maturation of oocytes and follicles.

[Reliability of peer review-like dialogue in the German statutory quality assurance program]. / Reliabilität des Strukturierten Dialogs in der gesetzlich verpflichtenden Qualitätssicherung.

BACKGROUND: Quality measurement in the German statutory program for quality in health care follows a two-step process. For selected areas of health care, quality is measured via performance indicators (first step). Providers failing to achieve benchmarks in these indicators subsequently enter into a peer review process (second step) and are asked by the respective regional authority to provide a written statement regarding their indicator results. The statements are then evaluated by peers, with the goal to assess the provider's quality of care. In the past, similar peer review-based approaches to the measurement of health care quality in other countries have shown a tendency to lack reliability. So far, the reliability of this component of the German statutory program for quality in health care has not been investigated. METHOD: Using logistic regression models, the influence of the respective regional authority on the peer review component of health care quality measurement in Germany was investigated using three exemplary indicators and data from 2016. RESULTS: Both the probability that providers are asked to provide a statement as well as the results produced by the peer review process significantly depend on the regional authority in charge. This dependence cannot be fully explained by differences in the indicator results or by differences in case volume. CONCLUSIONS: The present results are in accordance with earlier findings, which show low reliability for peer review-based approaches to quality measurement. Thus, different results produced by the peer review component of the quality measurement process may in part be due to differences in the way the review process is conducted. This heterogeneity among the regional authorities limits the reliability of this process. In order to increase reliability, the peer review process should be standardized to a higher degree, with clear review criteria, and the peers should undergo comprehensive training for the review process. Alternatively, the future peer review component could be adapted to focus rather on identification of improvement strategies than on reliable provider comparisons.

Enriching Thinking Through Discourse.

Great effort is invested in identifying ways to change people's minds on an issue. A first priority should perhaps be enriching their thinking about the issue. With a goal of enriching their thinking, we studied the views of community adults on the DACA issue-young adults who entered the United States illegally as children. A dialogic method was employed, offering dual benefits in providing participants the opportunity to further develop their own ideas and to consider differing ideas. Yet, participants engaged in dialog only vicariously by observing the talk of a pair of actors who held opposing positions on DACA. The effect on participants' thinking was greatest in the condition in which they viewed a dialog between the two actors, rather than a comparison condition in which the actors individually expressed their positions. In control conditions, no presentation was observed. Probing questions included in all conditions encouraged a participant to examine and clarify for themselves their own position, potentially enriching it. This condition proved unsuccessful in enriching thinking; participants' justifications for their own positions in fact became simpler and less qualified. In contrast, observing a video of a like-minded and opposing other did enrich observers' thinking, yet to a greater degree in the dialogic than nondialogic condition. The findings thus suggest observed dialog as a promising practical approach in promoting deeper thinking.

Multi-Level Linguistic Alignment in a Dynamic Collaborative Problem-Solving Task.

Cocreating meaning in collaboration is challenging. Success is often determined by people's abilities to coordinate their language to converge upon shared mental representations. Here we explore one set of low-level linguistic behaviors, linguistic alignment, that both emerges from, and facilitates, outcomes of high-level convergence. Linguistic alignment captures the ways people reuse, that is, "align to," the lexical, syntactic, and semantic forms of others' utterances. Our focus is on the temporal change of multi-level linguistic alignment, as well as how alignment is related to communicative outcomes within a unique collaborative problem-solving paradigm. The primary task, situated within a virtual educational video game, requires creative thinking between three people where the paths for possible solutions are highly variable. We find that over time interactions are marked by decreasing lexical and syntactic alignment, with a trade-off of increasing semantic alignment. However, greater semantic alignment does not translate into better team performance. Overall, these findings provide greater clarity on the role of linguistic coordination within complex and dynamic collaborative problem-solving tasks.

Detecting Emotional Context for Safer Digital Mental Health Agents.

Digital tools for mental health show great promise, but concerns arise when they fail to recognize the user state. We train a classifier to detect the emotional context of dialogs among 6 categories, achieving 78% accuracy on top choice. Importantly greatest areas of confusion (excited-hopeful, angry-sad) are not of the most unsafe kind. Such a classifier could serve as a resource to the dialog managers of future digital mental health agents.

Facts do not speak for themselves: Community norms, dialog, and evidentiary practices in discussions of COVID-19 on Reddit.

The present study sought to explore the distinct discourse norms and evidentiary practices in discussions of COVID-19 in four subcommunities on Reddit. Qualitative analysis found that communities differed in the degree to which they reinforce and augment Reddit's platform-wide norms for dialog and evidence use. One of the three communities (r/AskTrumpSupporters) differed from the rest by establishing discourse norms for turn-taking between politically opposed users and structuring dialog around authentic questions aimed at understanding alternative points of view. Quantitative analyses revealed that this community significantly differed from the other communities in the proportion of dialogic exchanges and in the use of evidentiary practices (sourcing, source evaluation, and interpretation of evidence). Excerpts of dialog from this community are used to illustrate findings. We conclude with implications for educators interested in preparing youth to critically engage with scientific information they encounter in public discourse.

Beyond the tried and true: How virtual reality, dialog setups, and a focus on multimodality can take bilingual language production research forward.

Bilinguals possess the ability of expressing themselves in more than one language, and typically do so in contextually rich and dynamic settings. Theories and models have indeed long considered context factors to affect bilingual language production in many ways. However, most experimental studies in this domain have failed to fully incorporate linguistic, social, or physical context aspects, let alone combine them in the same study. Indeed, most experimental psycholinguistic research has taken place in isolated and constrained lab settings with carefully selected words or sentences, rather than under rich and naturalistic conditions. We argue that the most influential experimental paradigms in the psycholinguistic study of bilingual language production fall short of capturing the effects of context on language processing and control presupposed by prominent models. This paper therefore aims to enrich the methodological basis for investigating context aspects in current experimental paradigms and thereby move the field of bilingual language production research forward theoretically. After considering extensions of existing paradigms proposed to address context effects, we present three far-ranging innovative proposals, focusing on virtual reality, dialog situations, and multimodality in the context of bilingual language production.

Diagnosis and management of adrenal incidentaloma: use of clinical judgment and evidence in dialog with the patient.

The prevalence of adrenal incidentaloma (AI) in imaging studies, including those of the adrenal glands, is estimated to be 1-5%. Essential factors for the proper management of AI include a correct diagnosis, adequate surgical skills, appropriate perioperative management, and sound dialogue with the patient. Aside from the possibility of overdiagnosis, patients with apparent signs or symptoms attributable to adrenal hormone excess have reasonable indications for surgery. At the same time, milder patients may be candidates for active surveillance without intervention. Even individuals with nonfunctioning AI may benefit from surgery if imaging studies depict the tumor as suggestive of malignancy. However, a differential diagnosis of AI may not be easy for surgeons with little experience in seeing such patients.Furthermore, a patient without a correct diagnosis may miss the window of opportunity for a cure or incur a greater risk of developing complications, such as adrenal insufficiency or cardiovascular events during or after surgery, due to inadequate management. The clinical practice guidelines for AI from around the world may be helpful for shared decision-making; however, Japan lacks established guidelines. In this review article, we propose practical guidelines relevant to management by summarizing the evidence for five key questions that are often asked in dialog with patients with AI.

RISE: an open-source architecture for interdisciplinary and reproducible human-robot interaction research.

In this article, we present RISE-a Robotics Integration and Scenario-Management Extensible-Architecture-for designing human-robot dialogs and conducting Human-Robot Interaction (HRI) studies. In current HRI research, interdisciplinarity in the creation and implementation of interaction studies is becoming increasingly important. In addition, there is a lack of reproducibility of the research results. With the presented open-source architecture, we aim to address these two topics. Therefore, we discuss the advantages and disadvantages of various existing tools from different sub-fields within robotics. Requirements for an architecture can be derived from this overview of the literature, which 1) supports interdisciplinary research, 2) allows reproducibility of the research, and 3) is accessible to other researchers in the field of HRI. With our architecture, we tackle these requirements by providing a Graphical User Interface which explains the robot behavior and allows introspection into the current state of the dialog. Additionally, it offers controlling possibilities to easily conduct Wizard of Oz studies. To achieve transparency, the dialog is modeled explicitly, and the robot behavior can be configured. Furthermore, the modular architecture offers an interface for external features and sensors and is expandable to new robots and modalities.

Feasibility and outcomes of using DIALOG+ in primary care to improve quality of life and mental distress of patients with long-term physical conditions: an exploratory non-controlled study in Bosnia and Herzegovina, Colombia and Uganda.

INTRODUCTION: The management of long-term physical conditions is a challenge worldwide, absorbing a majority resources despite the importance of acute care. The management of these conditions is done largely in primary care and so interventions to improve primary care could have an enormous impact. However, very little data exist on how to do this. Mental distress is frequently comorbid with long term physical conditions, and can impact on health behaviour and adherence, leading to poorer outcomes. DIALOG+ is a low-cost, patient-centred and solution-focused intervention, which is used in routine patient-clinician meetings and has been shown to improve outcomes in mental health care. The question arises as to whether it could also be used in primary care to improve the quality of life and mental health of patients with long-term physical conditions. This is particularly important for low- and middle-income countries with limited health care resources. METHODS: An exploratory non-controlled multi-site trial was conducted in Bosnia and Herzegovina, Colombia, and Uganda. Feasibility was determined by recruitment, retention, and session completion. Patient outcomes (quality of life, anxiety and depression symptoms, objective social situation) were assessed at baseline and after three approximately monthly DIALOG+ sessions. RESULTS: A total of 117 patients were enrolled in the study, 25 in Bosnia and Herzegovina, 32 in Colombia, and 60 in Uganda. In each country, more than 75% of anticipated participants were recruited, with retention rates over 90% and completion of the intervention exceeding 92%. Patients had significantly higher quality of life and fewer anxiety and depression symptoms at post-intervention follow-up, with moderate to large effect sizes. There were no significant improvements in objective social situation. CONCLUSION: The findings from this exploratory trial suggest that DIALOG+ is feasible in primary care settings for patients with long-term physical conditions and may substantially improve patient outcomes. Future research may test implementation and effectiveness of DIALOG+ in randomized controlled trials in wider primary care settings in low- and middle-income countries. TRIAL REGISTRATION: All studies were registered prospectively within the ISRCTN Registry. ISRCTN17003451, 02/12/2020 (Bosnia and Herzegovina), ISRCTN14018729, 01/12/2020 (Colombia) and ISRCTN50335796, 02/12/2020 (Uganda).

Surface and Contextual Linguistic Cues in Dialog Act Classification: A Cognitive Science View.

What role do linguistic cues on a surface and contextual level have in identifying the intention behind an utterance? Drawing on the wealth of studies and corpora from the computational task of dialog act classification, we studied this question from a cognitive science perspective. We first reviewed the role of linguistic cues in dialog act classification studies that evaluated model performance on three of the most commonly used English dialog act corpora. Findings show that frequency-based, machine learning, and deep learning methods all yield similar performance. Classification accuracies, moreover, generally do not explain which specific cues yield high performance. Using a cognitive science approach, in two analyses, we systematically investigated the role of cues in the surface structure of the utterance and cues of the surrounding context individually and combined. By comparing the explained variance, rather than the prediction accuracy of these cues in a logistic regression model, we found that (1) while surface and contextual linguistic cues can complement each other, surface linguistic cues form the backbone in human dialog act identification, (2) with word frequency statistics being particularly important for the dialog act, and (3) the similar trends across corpora, despite differences in the type of dialog, corpus setup, and dialog act tagset. The importance of surface linguistic cues in dialog act classification sheds light on how both computers and humans take advantage of these cues in speech act recognition.

Remote Assessment for ALS using Multimodal Dialog Agents: Data Quality, Feasibility and Task Compliance.

We investigate the feasibility, task compliance and audiovisual data quality of a multimodal dialog-based solution for remote assessment of Amyotrophic Lateral Sclerosis (ALS). 53 people with ALS and 52 healthy controls interacted with Tina, a cloud-based conversational agent, in performing speech tasks designed to probe various aspects of motor speech function while their audio and video was recorded. We rated a total of 250 recordings for audio/video quality and participant task compliance, along with the relative frequency of different issues observed. We observed excellent compliance (98%) and audio (95.2%) and visual quality rates (84.8%), resulting in an overall yield of 80.8% recordings that were both compliant and of high quality. Furthermore, recording quality and compliance were not affected by level of speech severity and did not differ significantly across end devices. These findings support the utility of dialog systems for remote monitoring of speech in ALS.

Development and Implementation of DIALOG+S in the School Setting as a Tool for Promoting Adolescent Mental Well-Being and Resilience in a Post-Armed Conflict Area in Colombia: Exploratory Cluster Randomized Controlled Trial.

BACKGROUND: Educational settings are ideal for promoting mental well-being and resilience in children. The challenges of the COVID-19 pandemic made evident the important role that teachers and school counselors play in the mental health of their students. Therefore, it is imperative to develop and implement cost-effective interventions that allow them to identify and address mental health problems early, especially in post-armed conflict areas, to reduce the burden of mental disorders in this population. OBJECTIVE: This study aimed to adapt an existing patient-focused digital intervention called DIALOG+ from an adult clinical setting to an adolescent educational setting and to assess the feasibility, acceptability, and estimated effect of implementing this intervention as a tool for promoting quality of life, mental well-being, and resilience. METHODS: We conducted an exploratory mixed methods study in 2 public schools in postconflict areas in Tolima, Colombia. This study was conducted in 3 phases. In the adaptation phase, focus groups were conducted with students and teachers to identify changes required in DIALOG+ for it to be used in the school setting. The exploration phase consisted of an exploratory cluster randomized controlled trial. A total of 14 clusters, each with 1 teacher and 5 students, were randomly allocated to either the experimental (DIALOG+S) group or to an active control group (counseling as usual). Teachers in both groups delivered the intervention once a month for 6 months. Through screening scales, information was collected on mental health symptoms, quality of life, self-esteem, resilience, and family functionality before and after the intervention. Finally, the consolidation phase explored the experiences of teachers and students with DIALOG+S using focus group discussions. RESULTS: The changes suggested by participants in the adaptation phase highlighted the central importance of the school setting in the mental health of adolescents. In the exploratory phase, 70 participants with a mean age of 14.69 (SD 2.13) years were included. Changes observed in the screening scale scores of the intervention group suggest that the DIALOG+S intervention has the potential to improve aspects of mental health, especially quality of life, resilience, and emotional symptoms. The consolidation phase showed that stakeholders felt that using this intervention in the school setting was feasible, acceptable, and an enriching experience that generated changes in the perceived mental health and behavior of participants. CONCLUSIONS: Our results are encouraging and show that the DIALOG+S intervention is feasible and acceptable as a promising opportunity to promote well-being and prevent and identify mental health problems in the school context in a postconflict area in Colombia. Larger, fully powered studies are warranted to properly assess the efficacy and potential impact of the intervention and to refine implementation plans. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number (ISRCTN) registry ISRCTN14396374; https://www.isrctn.com/ISRCTN14396374. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/40286.

Natural-Language-Driven Multimodal Representation Learning for Audio-Visual Scene-Aware Dialog System.

With the development of multimedia systems in wireless environments, the rising need for artificial intelligence is to design a system that can properly communicate with humans with a comprehensive understanding of various types of information in a human-like manner. Therefore, this paper addresses an audio-visual scene-aware dialog system that can communicate with users about audio-visual scenes. It is essential to understand not only visual and textual information but also audio information in a comprehensive way. Despite the substantial progress in multimodal representation learning with language and visual modalities, there are still two caveats: ineffective use of auditory information and the lack of interpretability of the deep learning systems' reasoning. To address these issues, we propose a novel audio-visual scene-aware dialog system that utilizes a set of explicit information from each modality as a form of natural language, which can be fused into a language model in a natural way. It leverages a transformer-based decoder to generate a coherent and correct response based on multimodal knowledge in a multitask learning setting. In addition, we also address the way of interpreting the model with a response-driven temporal moment localization method to verify how the system generates the response. The system itself provides the user with the evidence referred to in the system response process as a form of the timestamp of the scene. We show the superiority of the proposed model in all quantitative and qualitative measurements compared to the baseline. In particular, the proposed model achieved robust performance even in environments using all three modalities, including audio. We also conducted extensive experiments to investigate the proposed model. In addition, we obtained state-of-the-art performance in the system response reasoning task.

A multimodal dialog approach to mental state characterization in clinically depressed, anxious, and suicidal populations.

Background: The rise of depression, anxiety, and suicide rates has led to increased demand for telemedicine-based mental health screening and remote patient monitoring (RPM) solutions to alleviate the burden on, and enhance the efficiency of, mental health practitioners. Multimodal dialog systems (MDS) that conduct on-demand, structured interviews offer a scalable and cost-effective solution to address this need. Objective: This study evaluates the feasibility of a cloud based MDS agent, Tina, for mental state characterization in participants with depression, anxiety, and suicide risk. Method: Sixty-eight participants were recruited through an online health registry and completed 73 sessions, with 15 (20.6%), 21 (28.8%), and 26 (35.6%) sessions screening positive for depression, anxiety, and suicide risk, respectively using conventional screening instruments. Participants then interacted with Tina as they completed a structured interview designed to elicit calibrated, open-ended responses regarding the participants' feelings and emotional state. Simultaneously, the platform streamed their speech and video recordings in real-time to a HIPAA-compliant cloud server, to compute speech, language, and facial movement-based biomarkers. After their sessions, participants completed user experience surveys. Machine learning models were developed using extracted features and evaluated with the area under the receiver operating characteristic curve (AUC). Results: For both depression and suicide risk, affected individuals tended to have a higher percent pause time, while those positive for anxiety showed reduced lip movement relative to healthy controls. In terms of single-modality classification models, speech features performed best for depression (AUC = 0.64; 95% CI = 0.51-0.78), facial features for anxiety (AUC = 0.57; 95% CI = 0.43-0.71), and text features for suicide risk (AUC = 0.65; 95% CI = 0.52-0.78). Best overall performance was achieved by decision fusion of all models in identifying suicide risk (AUC = 0.76; 95% CI = 0.65-0.87). Participants reported the experience comfortable and shared their feelings. Conclusion: MDS is a feasible, useful, effective, and interpretable solution for RPM in real-world clinical depression, anxiety, and suicidal populations. Facial information is more informative for anxiety classification, while speech and language are more discriminative of depression and suicidality markers. In general, combining speech, language, and facial information improved model performance on all classification tasks.

Self-Repair Increases Referential Coordination.

When interlocutors repeatedly describe referents to each other, they rapidly converge on referring expressions which become increasingly systematized and abstract as the interaction progresses. Previous experimental research suggests that interactive repair mechanisms in dialogue underpin convergence. However, this research has so far only focused on the role of other-initiated repair and has not examined whether self-initiated repair might also play a role. To investigate this question, we report the results from a computer-mediated maze task experiment. In this task, participants communicate with each other via an experimental chat tool, which selectively transforms participants' private turn-revisions into public self-repairs that are made visible to the other participant. For example, if a participant, A, types "On the top square," and then before sending, A revises the turn to "On the top row," the server automatically detects the revision and transforms the private turn-revisions into a public self-repair, for example, "On the top square umm I meant row." Participants who received these transformed turns used more abstract and systematized referring expressions, but performed worse at the task. We argue that this is due to the artificial self-repairs causing participants to put more effort into diagnosing and resolving the referential coordination problems they face in the task, yielding better grounded spatial semantics and consequently increased use of abstract referring expressions.

Safety assessment of the process Dialog Diyou PCR, based on the Starlinger iV+ technology, used to recycle post-consumer PET into food contact materials.

The EFSA Panel on Food Contact Materials, Enzymes and Processing Aids (CEP) assessed the safety of the recycling process Dialog Diyou PCR (EU register number RECYC296), which uses the Starlinger iV+ technology. The input is hot caustic washed and dried poly(ethylene terephthalate) (PET) flakes mainly originating from collected post-consumer PET containers, with no more than 5% PET from non-food consumer applications. The flakes are dried and crystallised in a first reactor, then extruded into pellets. These pellets are crystallised, preheated and treated in a solid-state polycondensation (SSP) reactor. Having examined the challenge test provided, the Panel concluded that the drying and crystallisation (step 2), extrusion and crystallisation (step 3) and SSP (step 4) are critical in determining the decontamination efficiency of the process. The operating parameters to control the performance of these critical steps are temperature, air/PET ratio and residence time for the drying and crystallisation step, and temperature, pressure and residence time for the extrusion and crystallisation step as well as the SSP step. It was demonstrated that this recycling process is able to ensure that the level of migration of potential unknown contaminants into food is below the conservatively modelled migration of 0.1 µg/kg food. Therefore, the Panel concluded that the recycled PET obtained from this process is not of safety concern when used at up to 100% for the manufacture of materials and articles for contact with all types of foodstuffs, including drinking water, for long-term storage at room temperature, with or without hotfill. The final articles made of this recycled PET are not intended to be used in microwave and conventional ovens and such uses are not covered by this evaluation.

Migrant women's engagement in health-promotive activities through a women's health collaboration.

Introduction: Social determinants of health impact health, and migrants are exposed to an inequitable distribution of resources that may impact their health negatively, leading to health inequality and social injustice. Migrant women are difficult to engage in health-promotional activities because of language barriers, socioeconomic circumstances, and other social determinants. Based on the framework of Paulo Freire, a community health promotion program was established in a community-academic partnership with a community-based participatory research approach. Aim: The aim of this study was to describe how a collaborative women's health initiative contributed to migrant women's engagement in health promotion activities. Materials and methods: This study was part of a larger program, carried out in a disadvantaged city area in Sweden. It had a qualitative design with a participatory approach, following up on actions taken to promote health. Health-promotional activities were developed in collaboration with a women's health group, facilitated by a lay health promoter. The study population was formed by 17 mainly Middle Eastern migrant women. Data was collected using the story-dialog method and the material was analyzed using thematic analysis. Result: Three important contributors to engagement in health promotion were identified at an early stage of the analysis process, namely, the group forming a social network, the local facilitator from the community, and the use of social places close to home. Later in the analysis process, a connection was made between these contributors and the rationale behind their importance, that is, how they motivated and supported the women and how the dialog was conducted. This therefore became the designated themes and were connected to all contributors, forming three main themes and nine sub-themes. Conclusion: The key implication was that the women made use of their health knowledge and put it into practice. Thus, a progression from functional health literacy to a level of critical health literacy may be said to have occurred.