| Literature DB >> 30935151 |
Amen Alrobai1, Abdullah Algashami2, Huseyin Dogan3, Tessa Corner4, Keith Phalp5, Raian Ali6.
Abstract
Digital addiction (hereafter DA) denotes a problematic relationship with technology described by being compulsive, obsessive, impulsive and hasty. New research has identified cases where users' digital behaviour shows symptoms meeting the clinical criteria of behavioural addiction. The online peer groups approach is one of the strategies to combat addictive behaviours. Unlike other behaviours, intervention and addictive usage can be on the same medium; the online space. This shared medium empowers influence techniques found in peer groups, such as self-monitoring, social surveillance, and personalised feedback, with a higher degree of interactivity, continuity and real-time communication. Social media platforms in general and online peer groups, in particular, have received little guidance as to how software design should take it into account. Careful theoretical understanding of the unique attributes and dynamics of such platforms and their intersection with gamification and persuasive techniques is needed as the ad-hoc design may cause unexpected harm. In this paper, we investigate how to facilitate the design process to ensure a systematic development of this technology. We conducted several qualitative studies including user studies and observational investigations. The primary contribution of this research is twofold: (i) a reference model for designing interactive online platforms to host peer groups and combat DA, (ii) a process model, COPE.er, inspired by the participatory design approach to building Customisable Online Persuasive Ecology by Engineering Rehabilitation strategies for different groups.Entities:
Keywords: behaviour change; digital addiction; online peer groups; persuasive social networks; persuasive systems design
Mesh:
Year: 2019 PMID: 30935151 PMCID: PMC6480537 DOI: 10.3390/ijerph16071162
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
The background of the participants.
| Participants | Role | Age | Gender | Field of Study | Years of Experience |
|---|---|---|---|---|---|
| P1 | Designer | 30–40 | Male | Computing | 13 |
| P2 | Designer | 30–40 | Male | Computing | 8 |
| P3 | Designer | 30–40 | Male | Computing | 5 |
| P4 | Designer | 30–40 | Female | Computing | 5 |
| P5 | Counsellor | 40–50 | Male | Psychology | 17 |
| P6 | End-user | 20–30 | Male | Computing | N/A 1 |
| P7 | End-user | 20–30 | Male | Computing | N/A 1 |
| P8 | End-user | 20–30 | Female | Computing | N/A 1 |
1 Not applicable as the years of experience does not apply to participants who roleplay the end-users’ role.
The expert participants’ familiarity with relevant topics 1.
| Participants | Designing for Behavioural Change | Behavioural Addiction | Human-Computer Interaction | Social Informatics | User Involvement | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 1 | 2 | 3 | 4 | 5 | 1 | 2 | 3 | 4 | 5 | 1 | 2 | 3 | 4 | 5 | 1 | 2 | 3 | 4 | 5 | |
| P1 | ● | ● | ● | ● | ● | ||||||||||||||||||||
| P2 | ● | ● | ● | ● | ● | ||||||||||||||||||||
| P3 | ● | ● | ● | ● | ● | ||||||||||||||||||||
| P4 | ● | ● | ● | ● | ● | ||||||||||||||||||||
| P5 | ● | ● | ● | ● | ● | ||||||||||||||||||||
1 The questionnaire was based on 5-points Likert scale which can be interpreted as follows: (1) Very Poor (2) Poor (3) Fair (4) Good (5) Very Good.
Figure 1Case study first phase protocol.
Figure 2Case study second phase protocol.
Figure 3The COPE.er method building blocks.
Figure 4The COPE.er method reference architecture.
Implications on the COPE.er building blocks.
| ■ | A feature with |
|
| A feature with |
|
| A feature with |
Interactive features repository.
Examples for specifying frequency and duration.
| Features | Frequency (F) | Duration (D) |
|---|---|---|
| My mood | Three times a day (7 h gap between each) | N/A |
| Group chatting | Only during formal group meetings | Free-floating mode during the first 30 min |
An example for specifying informational limitations.
| Features | Informational Limitations |
|---|---|
| Addiction scoring | Include: Facebook, Twitter and Instagram |
Examples for specifying time frames.
| Features | Time Frame |
|---|---|
| My mood | Starts: Day 1 of the treatment programme |
| Leaderboard | Starts: End of group therapy transition |
Heuristic principles for inspecting online peer groups design to combat addictive behaviours.
| Principles |
|---|
| Principle 1: Social equality rather than hierarchy |
| Principle 2: Instinct to survive |
| Principle 3: Encourage collaborative decision making |
| Principle 4: Focus on the self |
| Principle 5: Prevent selective and optimised self-presentation |
| Principle 6: Eliminate private relationships and subgroups |
| Principle 7: Learning before doing |
| Principle 8: Encourage user self-labelling and personalisation |
| Principle 9: Emphasis dispositional attribution |
Figure 5The COPE.er method workflow.