Persuasive health technology

Gemert-Pijnen, Lisette van; Kelders, Saskia M.; Jong, Nienke Beerlage-de; Oinas-Kukkonen, Harri

doi:10.4324/9781315385907-11

Cited by 21 publications

(25 citation statements)

References 27 publications

(30 reference statements)

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“…Furthermore, when creating engaging, gameful, or persuasive designs, designers are steering users toward a desired action. In doing so, one should be careful not to steer users toward making choices that are against their interest or will or create a very limited set of perceived choices for interaction [ 97 , 98 ]. In MyStrengths , the dice only draws exercises for strengths that each person assesses themselves as having and will thus not suggest exercises for strengths that the user considers herself or himself not to have.…”

Section: Discussionmentioning

confidence: 99%

MyStrengths, a Strengths-Focused Mobile Health Tool: Participatory Design and Development

Jessen¹,

Mirković²,

Nes³

2020

JMIR Form Res

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Background People living with chronic illnesses are an increasingly large group. Research indicates that care and self-management should not only focus on the illness and problem-oriented aspects of these individuals’ lives but also support them in recognizing and leveraging their personal strengths in daily life. Objective This paper presents the design and developmental process of MyStrengths, a mobile health (mHealth) app designed to help its users (people with chronic conditions) both find and make use of their personal strengths in their daily lives. Through 4 consecutive phases, this paper presents participant- and researcher-driven activities, discussions regarding design, and development of both the MyStrengths app and its content. Methods During the 4 phases, we used a range of methods and activities, including (1) an idea-generating workshop aimed at creating ideas for strengths-supporting features with different stakeholders, including patients, caregivers, relatives, and designers (N=35); (2) research seminars with an international group of experts (N=6), in which the concept, theoretical background, and design ideas for the app were discussed; (3) a series of co-design workshops with people in the user group (N=22) aiming to create ideas for how to, in an engaging manner, design the app; and (4) in 4 developmental iterations, the app was evaluated by people in the user group (N=13). Content and strengths exercises were worked on and honed by the research team, the expert groups, and our internal editorial team during the entire developmental process. Results The first phase found a wide range of stakeholder requirements to, and ideas for, strengths-focused mHealth apps. From reviewing literature during the second phase, we found a dearth of research on personal strengths with respect to people living with chronic illnesses. Activities during the third phase creatively provided numerous ideas and suggestions for engaging and gameful ways to develop and design the MyStrengths app. The final phase saw the output from all the earlier phases come together. Through multiple increasingly complete iterations of user evaluations testing and developing, the final prototype of the MyStrengths app was created. Conclusions Although research supports the use of strengths-focused mHealth tools to support people living with chronic illnesses, there is little guidance as to how these tools and their content should be designed. Through all activities, we found great support among participating users for strengths-focused apps, and we can consider such apps to be both appropriate and valuable. This paper illustrates how combining a range of user-, researcher-, literature-, and designer-based methods can contribute to creating mHealth tools to support people with chronic illnesses to find and use more of their own personal strengths.

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Section: Discussionmentioning

confidence: 99%

MyStrengths, a Strengths-Focused Mobile Health Tool: Participatory Design and Development

Jessen¹,

Mirković²,

Nes³

2020

JMIR Form Res

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“…All card-sort data were exported into an Excel spreadsheet (Microsoft) that was specifically developed for the analysis of card sorts [36]. This spreadsheet was extended, adapted, and used in this study and previous research from our research group [24,26,37].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Perceived Persuasiveness Questionnaire: User-Centered Card-Sort Study (Preprint)

Jong¹,

Kip²,

Kelders³

2020

Preprint

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BACKGROUND eHealth technologies aim to change their users’ health-related behavior. Persuasive design and system features can make an eHealth technology more motivating, engaging or supportive to its users. The Persuasive Systems Design (PSD) model poses software features that have the possibility to increase such persuasiveness of technologies. However, the effects of specific PSD software features on the effectiveness of an intervention are still largely unknown. In order gain insight into the working mechanisms of persuasive technologies, the Perceived Persuasiveness Questionnaire (PPQ) was developed. While the PPQ seems to be a suitable way for measuring subjective persuasiveness, it needs to be further evaluated in order to determine how suitable it is for measuring perceived persuasiveness among the general public. OBJECTIVE Objectives of the current paper are to evaluate the face and construct validity of the PPQ; to identify points of improvement; and to provide suggestions for further development of the PPQ. METHODS In this study, an online closed-ended card sort study was performed, wherein participants grouped existing PPQ items under existing PPQ constructs. Participants were invited via a Massive Open Online Course (MOOC) on eHealth. A total of 398 people (average age 44.15 years, 63% male) completed the card sort. Face validity was evaluated by determining item level agreement of the original PPQ constructs. Construct validity was evaluated by determining (a) in what construct each item was placed most often, regardless of the original placement and (b) how often two items were (regardless of the constructs) paired together and what inter-item correlations were according to a cluster analysis. RESULTS Four PPQ constructs scored a relatively high face validity: Perceived Social Support, Use Continuance, Perceived Credibility and Perceived Effort. Item level agreement on the other constructs was relatively low. Item level agreement for almost all constructs, except for Perceived Effort and Perceived Effectiveness, would increase if items would be grouped differently. Finally, a cluster analysis of the PPQ indicated that the strengths of the newly identified nine clusters varies strongly. Unchanged strong clusters are only found for Perceived Credibility Support, Perceived Social Support and Use Continuance. The placement of the other items was much more spread out over the other constructs, suggesting overlap between them. CONCLUSIONS The findings of the current study provide a solid starting point towards a re-designed PPQ that is a true asset to the field of persuasiveness research. To be able to achieve this, we advocate that the re-designed PPQ should stick more closely to what persuasiveness is according to the PSD model, and to the mental models of potential end-users of technology. The revised PPQ should for example enquire if the user thinks anything is done to provide task support, but not how this is done exactly.

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“…Persuasive technology is defined as 'computerized software or information systems designed to reinforce, change or shape attitudes or behaviors or both without using coercion or deception' (Oinas- Kukkonen and Harjumaa, 2009). According to Van Gemert-Pijnen et al (2018) persuasive technology is characterized by increased interactivity and engagement of users through modern information and communication technologies. A relevant instance of persuasive technology is the Embodied Conversational Agent, abbreviated as ECA.…”

Section: Persuasive Technology Providing User Supportmentioning

confidence: 99%

Can a monologue-style ECA more effectively motivate eHealth users in initial distress than textual guidance?

Scholten

Kelders

Gemert-Pijnen

2021

Heliyon

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Stress is a prevalent issue amongst patients with chronic conditions. As eHealth interventions are gaining importance, it becomes more relevant to invoke the possibilities from the eHealth technology itself to provide motivational acts during experiences of stress as to enhance adherence to the intervention. Embodied Conversational Agents (ECA's) also known as ‘robots on screen’ can potentially provide a remedy. Within our eHealth experiment we applied a between-subjects design and experimentally studied the difference in appraisal of motivation and guidance. We deployed a functionally modest, monologue-style ECA and compared them with textual guidance. This way, we filtered out the considerable positive impact of interactive features that go along with dialogue-style ECA's. The study was carried out amongst eHealth users of which half were deliberately put in a stressful pre-condition. The rationale was two-sided; first, we hypothesized that it would induce a need for motivational support. Second, it would provide a fair representation of eHealth users in real life. Furthermore, we investigated hypothesized positive effects from a gender match between participant and ECA. The results demonstrated preferential ECA effects compared to text but only in the no stress conditions. Although our set-up controlled for user distraction by putting the facilitating ECA in a pane separate from the eHealth environment, we suspect that the enduring visual presence of the ECA during task completion had still inhibited distressed users. Discussing this phenomenon, our stance is that the hypothesis that ECA support is always superior to textual guidance is open for re-evaluation. Text may sometimes serve users equally well because it lacks human-like aspects that in stressful circumstances can become confrontational. We discuss the potential of ECA's to motivate, but also elaborate on the caveats. Further implications for the ECA, intervention adherence, and eHealth study fields are discussed in relation to stress.

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Persuasive health technology

Cited by 21 publications

References 27 publications

MyStrengths, a Strengths-Focused Mobile Health Tool: Participatory Design and Development

MyStrengths, a Strengths-Focused Mobile Health Tool: Participatory Design and Development

Evaluation of the Perceived Persuasiveness Questionnaire: User-Centered Card-Sort Study (Preprint)

Can a monologue-style ECA more effectively motivate eHealth users in initial distress than textual guidance?

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