10 research outputs found

    Negotiating over mobile phones: calling or being called can make the difference

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    Mobile phones pervade our everyday life like no other technology, but the effects they have on one-to-one conversations are still relatively unknown. This paper focuses on how mobile phones influence negotiations, i.e., on discussions where two parties try to reach an agreement starting from opposing preferences. The experiments involve 60 pairs of unacquainted individuals (120 subjects). They must make a “yes” or “no” decision on whether several objects increase the chances of survival in a polar environment or not. When the participants disagree about a given object (one says “yes” and the other says “no”), they must try to convince one another and reach a common decision. Since the subjects discuss via phone, one of them (selected randomly) calls while the other is called. The results show that the caller convinces the receiver in 70 % of the cases ( p value = 0.005 according to a two-tailed binomial test). Gender, age, personality and conflict handling style, measured during the experiment, fail in explaining such a persuasiveness difference. Calling or being called appears to be the most important factor behind the observed result

    The SSPNet-Mobile Corpus: from the detection of non-verbal cues to the inference of social behaviour during mobile phone conversations

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    Mobile phones are one of the main channels of communication in contemporary society. However, the effect of the mobile phone on both the process of and, also, the non-verbal behaviours used during conversations mediated by this technology, remain poorly understood. This thesis aims to investigate the role of the phone on the negotiation process as well as, the automatic analysis of non-verbal behavioural cues during conversations using mobile telephones, by following the Social Signal Processing approach. The work in this thesis includes the collection of a corpus of 60 mobile phone conversations involving 120 subjects, development of methods for the detection of non-verbal behavioural events (laughter, fillers, speech and silence) and the inference of characteristics influencing social interactions (personality traits and conflict handling style) from speech and movements while using the mobile telephone, as well as the analysis of several factors that influence the outcome of decision-making processes while using mobile phones (gender, age, personality, conflict handling style and caller versus receiver role). The findings show that it is possible to recognise behavioural events at levels well above chance level, by employing statistical language models, and that personality traits and conflict handling styles can be partially recognised. Among the factors analysed, participant role (caller versus receiver) was the most important in determining the outcome of negotiation processes in the case of disagreement between parties. Finally, the corpus collected for the experiments (the SSPNet-Mobile Corpus) has been used in an international benchmarking campaign and constitutes a valuable resource for future research in Social Signal Processing and more generally in the area of human-human communication

    Investigating Fine Temporal Dynamics of Prosodic and Lexical Accommodation

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    Conversational interaction is a dynamic activity in which participants engage in the construction of meaning and in establishing and maintaining social relationships. Lexical and prosodic accommodation have been observed in many studies as contributing importantly to these dimensions of social interaction. However, while previous works have considered accommodation mechanisms at global levels (for whole conversations, halves and thirds of conversations), this work investigates their evolution through repeated analysis at time intervals of increasing granularity to analyze the dynamics of alignment in a spoken language corpus. Results show that the levels of both prosodic and lexical accommodation fluctuate several times over the course of a conversation

    The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism

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    The INTERSPEECH 2013 Computational Paralinguistics Challenge provides for the first time a unified test-bed for Social Signals such as laughter in speech. It further introduces conflict in group discussions as new tasks and picks up on autism and its manifestations in speech. Finally, emotion is revisited as task, albeit with a broader ranger of overall twelve emotional states. In this paper, we describe these four Sub-Challenges, Challenge conditions, baselines, and a new feature set by the openSMILE toolkit, provided to the participants. \em Bj\"orn Schuller1^1, Stefan Steidl2^2, Anton Batliner1^1, Alessandro Vinciarelli3,4^{3,4}, Klaus Scherer5^5}\\ {\em Fabien Ringeval6^6, Mohamed Chetouani7^7, Felix Weninger1^1, Florian Eyben1^1, Erik Marchi1^1, }\\ {\em Hugues Salamin3^3, Anna Polychroniou3^3, Fabio Valente4^4, Samuel Kim4^4

    Swansea Bay in the 21st century Papers from the Swansea Bay seminar series

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    Edited for the IWA and City and County of SwanseaAvailable from British Library Document Supply Centre-DSC:4589.0718(10) / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

    The INTERSPEECH 2013 Computational Paralinguistics Challenge: Social Signals, Conflict, Emotion, Autism

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    The INTERSPEECH 2013 Computational Paralinguistics Chal- lenge provides for the first time a unified test-bed for Social Signals such as laughter in speech. It further introduces conflict in group discussions as a new task and deals with autism and its manifestations in speech. Finally, emotion is revisited as task, albeit with a broader range of overall twelve enacted emotional states. In this paper, we describe these four Sub-Challenges, their conditions, baselines, and a new feature set by the openSMILE toolkit, provided to the participant

    Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with type 2 diabetes : a systematic review and meta-analysis of randomised controlled trials

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    Background Digital health interventions have shown promising results for the management of type 2 diabetes, but a comparison of the effectiveness and implementation of the different modes is not currently available. Therefore, this study aimed to compare the effectiveness of SMS, smartphone application, and website-based interventions on improving glycaemia in adults with type 2 diabetes and report on their reach, uptake, and feasibility. Methods In this systematic review and meta-analysis, we searched CINAHL, Cochrane Central, Embase, MEDLINE, and PsycInfo on May 25, 2022, for randomised controlled trials (RCTs) that examined the effectiveness of digital health interventions in reducing glycated haemoglobin A1c (HbA1c) in adults with type 2 diabetes, published in English from Jan 1, 2009. Screening was carried out using Covidence, and data were extracted following Cochrane's guidelines. The primary endpoint assessed was the change in the mean (and 95% CI) plasma concentration of HbA1c at 3 months or more. Cochrane risk of bias 2 was used to assess risk of bias. Data on reach, uptake, and feasibility were summarised narratively and data on HbA1c reduction were synthesised in a meta-analysis. Grading of Recommendations, Assessment, Development, and Evaluation criteria was used to evaluate the level of evidence. The study was registered with PROSPERO, CRD42021247845. Findings Of the 3236 records identified, 56 RCTs from 24 regions (n=11 486 participants), were included in the narrative synthesis, and 26 studies (n=4546 participants) in the meta-analysis. 20 studies used SMS as the primary mode of delivery of the digital health intervention, 25 used smartphone applications, and 11 implemented interventions via websites. Smartphone application interventions reported higher reach compared with SMS and website-based interventions, but website-based interventions reported higher uptake compared with SMS and smartphone application interventions. Effective interventions, in general, included people with greater severity of their condition at baseline (ie, higher HbA1c) and administration of a higher dose intensity of the intervention, such as more frequent use of smartphone applications. Overall, digital health intervention group participants had a –0·30 (95% CI –0·42 to –0·19) percentage point greater reduction in HbA1c, compared with control group participants. The difference in HbA1c reduction between groups was statistically significant when interventions were delivered through smartphone applications (–0·42% [–0·63 to –0·20]) and via SMS (–0·37% [–0·57 to –0·17]), but not when delivered via websites (–0·09% [–0·64 to 0·46]). Due to the considerable heterogeneity between included studies, the level of evidence was moderate overall. Interpretation Smartphone application and SMS interventions, but not website-based interventions, were associated with better glycaemic control. However, the studies' heterogeneity should be recognised. Considering that both smartphone application and SMS interventions are effective for diabetes management, clinicians should consider factors such as reach, uptake, patient preference, and context of the intervention when deciding on the mode of delivery of the intervention. Nine in ten people worldwide own a feature phone and can receive SMS and four in five people have access to a smartphone, with numerous smartphone applications being available for diabetes management. Clinicians should familiarise themselves with this modality of programme delivery and encourage people with type 2 diabetes to use evidence-based applications for improving their self-management of diabetes. Future research needs to describe in detail the mediators and moderators of the effectiveness and implementation of SMS and smartphone application interventions, such as the optimal dose, frequency, timing, user interface, and communication mode to both further improve their effectiveness and to increase their reach, uptake, and feasibility

    Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with hypertension : a systematic review and meta-analysis of randomised controlled trials

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    Background Digital health interventions are effective for hypertension self-management, but a comparison of the effectiveness and implementation of the different modes of interventions is not currently available. This study aimed to compare the effectiveness of SMS, smartphone application, and website interventions on improving blood pressure in adults with hypertension, and to report on their reach, uptake, and feasibility. Methods In this systematic review and meta-analysis we searched CINAHL Complete, Cochrane Central Register of Controlled Trials, Ovid Embase, Ovid MEDLINE, and APA PsycInfo on May 25, 2022, for randomised controlled trials (RCTs) published in English from Jan 1, 2009, that examined the effectiveness of digital health interventions on reducing blood pressure in adults with hypertension. Screening was carried out using Covidence, and data were extracted following Cochrane's guidelines. The primary endpoint was change in the mean of systolic blood pressure. Risk of bias was assessed with Cochrane Risk of Bias 2. Data on systolic and diastolic blood pressure reduction were synthesised in a meta-analysis, and data on reach, uptake and feasibility were summarised narratively. Grading of Recommendations, Assessment, Development, and Evaluation criteria were used to evaluate the level of evidence. The study was registered with PROSPERO CRD42021247845. Findings Of the 3235 records identified, 29 RCTs from 13 regions (n=7592 participants) were included in the systematic review, and 28 of these RCTs (n=7092 participants) were included in the meta-analysis. 11 studies used SMS as the primary mode of delivery of the digital health intervention, 13 used smartphone applications, and five used websites. Overall, digital health intervention group participants had a –3·62 mm Hg (95% CI –5·22 to –2·02) greater reduction in systolic blood pressure, and a –2·45 mm Hg (–3·83 to –1·07) greater reduction in diastolic blood pressure, compared with control group participants. No statistically significant differences between the three different modes of delivery were observed for both the systolic (p=0·73) and the diastolic blood pressure (p=0·80) outcomes. Smartphone application interventions had a statistically significant reduction in diastolic blood pressure (–2·45 mm Hg [–4·15 to –0·74]); however, there were no statistically significant reductions for SMS interventions (–1·80 mm Hg [–4·60 to 1·00]) or website interventions (–3·43 mm Hg [–7·24 to 0·38]). Due to the considerable heterogeneity between included studies and the high risk of bias in some, the level of evidence was assigned a low overall score. Interventions were more effective among people with greater severity of hypertension at baseline. SMS interventions reported higher reach and smartphone application studies reported higher uptake, but differences were not statistically significant. Interpretation SMS, smartphone application, and website interventions were associated with statistically and clinically significant systolic and diastolic blood pressure reductions, compared with usual care, regardless of the mode of delivery of the intervention. This conclusion is tempered by the considerable heterogeneity of included studies and the high risk of bias in most. Future studies need to describe in detail the mediators and moderators of the effectiveness and implementation of these interventions, to both further improve their effectiveness as well as increase their reach, uptake, and feasibility
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