1 |
Quality and relevance of information given before the trial |
If low, risk of unrealistic expectations which results in a disengagement |
2 |
Ease of the inclusion process (consent, implementation) |
Quality of recruitment affects attrition. if it is too easy to enroll then the dropout rate may be high |
3 |
Ease of drop out/stop using it |
This parameter can negatively influence the use of the app |
4 |
Ease of use and reliability of the technical interface |
Poor usability (complexity of the interaction between an object and its user) contributes to a high rate of attrition |
5 |
“Incentive” or “push” factors (callbacks, reminders, research assistants chasing participants) |
This parameter can positively influence the use of the app (staying more in the trial) |
6 |
Personal contact (during registration and inclusion) via face-to-face or by phone, rather than virtual contacts |
Human contact promotes the use of the app |
7 |
General quality of the feedback information and of the information summary screen |
Positive feedback and encouragement positively influence the use of the app |
8 |
Perceived benefits of interest in completing the study |
Motivational factor that decreases attrition |
9 |
Free to use |
Paying more commits the user and decreases attrition |
10 |
Time and workload required by the apps |
If the burden is too high, it may result in higher attrition |
11 |
Existence of concurrent interventions (web, therapy) |
Risk that the user no longer perceives the specific interest of the app |
12 |
Major life events, or of society, which could have stopped using the app |
Lead to distraction and nonuse by shifting priorities |
13 |
Experience of the other user (or being able to obtain help) |
Indirectly through to dropout and nonusage |