1. Felix Naughton Behavioural Science Group University of Cambridge
The acceptability of a context-aware smartphone smoking cessation app (Q Sense)
Felix Naughton
Behavioural Science Group
University of Cambridge
Collaborators
Neal Lathia
Sarah Hopewell
Rik Schalbroeck
Cecilia Mascolo
Andy McEwen
Stephen Sutton
@FelixNaughton
UKSNCC 2016

2. Background
Over half of those attempting to quit smoking relapse within one month (high income countries)
Borland et al (2012), Addiction
Smoking (lapse) during first week of a quit attempt associated with five-fold increase in risk of relapse
Ashare et al (2013), J Addict Med

3. Background
Over half of those attempting to quit smoking relapse within one month (high income countries)
Borland et al (2012), Addiction
Smoking (lapse) during first week of a quit attempt associated with five-fold increase in risk of relapse
Ashare et al (2013), J Addict Med
Cue-induced cravings implicated in almost half of all smoking lapses – major support gap
Shiffman et al (1996), J Consult Clin Psychol; Ferguson & Shiffman (2009), J Subst Abuse Treat
Mobile phone interventions have potential to address gap
Naughton et al (2011), EHP; McClernon & Choudhury (2013), Nicotine Tob Res

4. Sense
SET QUIT DATE

5. Sense
SET QUIT DATE

6. IF REPORTS > THRESHOLD THEN ACTIVE GEOFENCE CREATED
Sense
IF REPORTS > THRESHOLD THEN ACTIVE GEOFENCE CREATED
SET QUIT DATE

7. IF REPORTS > THRESHOLD THEN ACTIVE GEOFENCE CREATED
Sense
IF REPORTS > THRESHOLD THEN ACTIVE GEOFENCE CREATED
SET QUIT DATE

8. Sense
AFTER QUIT DATE

9. Sense
AFTER QUIT DATE

10. Additional Q Sense support

11. Additional Q Sense support

12. Intervention development
Time
MRC framework phase
Intervention development
Theory & literature
Feasibility study
Intervention refinement
Acceptability study
Pilot/exploratory RCT
Effectiveness RCT
Phase Phase 1 Phase Phase Phase 4
Theory and evidence generation
Intervention targets, modelling & barriers
Feasibility, acceptability & trial parameters
Definitive RCT
Examine implementation in practice

13. Intervention development
Time
MRC framework phase
Intervention development
Theory & literature
Feasibility study
Intervention refinement
Acceptability study
Pilot/exploratory RCT
Effectiveness RCT
Phase Phase 1 Phase Phase Phase 4
Theory and evidence generation
Intervention targets, modelling & barriers
Feasibility, acceptability & trial parameters
Definitive RCT
Examine implementation in practice

14. Feasibility study of Q Sense
Mixed methods study (N=15)
Median time to report smoking was 13 seconds
Positive engagement but underreporting of smoking
Reporting barriers - environmental constraints & forgetting
Positive about geofence-triggered support, no privacy concerns
Key refinements
Feedback if mismatch between daily reports and end of day survey
Library of topic based support messages
Option to reset quit date
Inbox for all messages
Naughton et al (in press) JMIR uHealth mHealth

15. Unanswered questions
To assess, among smokers receiving/motivated to engage in support:
Acceptability
Ease of use
Data privacy concerns (partially unanswered!)
Inadvertent reminder/cue to smoke
Engagement
Speed of engagement
Disengagement
Optimisation
Perceived helpfulness
Content and support preferences

16. Aims and design Mixed methods design – data from three sources:
1. app, 2. follow up survey and 3. one-to-one interviews (purposively sampled)
Participants – daily smokers, willing to set a quit date within two weeks, use of Android phone, initiated Q Sense
Recruited via Stop Smoking Services & online (online adverts)
55% female
74% smoked first cigarette within 30 mins of waking
26% accessed Stop Smoking Service support
7% had ever downloaded a smoking cessation app

17. Procedure Baseline survey N=42 Prequit phase ~ 7 days Quit date
Postquit phase
28 days
Follow-up survey
n=30 (71%)
1-to-1 interviews
n=9

18. Procedure Baseline survey N=42 Prequit phase ~ 7 days Quit date
Postquit phase
28 days
16/23 (70%) of those eligible received geofence triggered support messages
Follow-up survey
n=30 (71%)
1-to-1 interviews
n=9

19. Acceptability
* Subsample followed up who received geofence triggered support (n=14)

20. Acceptability “...very easy to use, simple steps.” (ppt 17)
All commented on the app’s simplicity:
“...very easy to use, simple steps.” (ppt 17)
Data privacy not a concern:
“I’ve seen much worse. I mean, geolocation, tagging, I do that for photographs” (ppt 7)
No one felt Q Sense had actually triggered smoking:
“I suppose you see the word, don’t you, and then it kind of draws your mind back to it. But I think that's the idea of having a support system, isn’t it, whether it’s the nurse, whether you join an online group...you do talk about it, and yes, it is a reminder but it’s, I think it’s a positive reminder.” (ppt 1)

21. Engagement Mean smoking reports prequit per ppt = 30 (SD 38)
Acceptability study

22. Engagement Mean smoking reports prequit per ppt = 30 (SD 38)
Acceptability study
Feasibility study

23. Engagement Mean smoking reports prequit per ppt = 30 (SD 38)
85% of smoking reports captured by home, work and socialising categories
Mean smoking reports prequit per ppt = 30 (SD 38)
Acceptability study
87% of smoking reports captured by home, work and socialising categories
Feasibility study

24. Engagement
All notifications (6,606): 65% app opened, 35% deleted by system/user
Mean of over 100 viewed per participant, but high variation due to disengagement
Geofence message notifications (837): 73% app opened, 27% deleted
Mean of ~40 messages viewed per participant (n=16)

25. (Speed of) engagement
Median time to response after geofence message notification (n=15) = 4.5 mins

26. (Speed of) engagement
Median time to response after geofence message notification (n=15) = 4.5 mins
Geofence messages
Support messages
geofence
daily support
p<0.001
79% viewed within 30 minutes
54% viewed within 30 minutes

27. (Dis)engagement
Last completion of an app survey or rating a message

28. (Dis)engagement Last completion of an app survey or rating a message
Approx. end of automated support (38 days)
Median 25 days (IQR 7-41)

29. Optimisation

30. Optimisation Helpfulness of messages:
5-point scale: 1 = not very helpful, 5 = Extremely helpful
About health improvements (3.7/5)
About money spent or saved (3.3/5)
Containing health warnings (3.2/5)
Strategies for managing urges (2.9/5)
Containing stories of visual images (2.5/5)
Messages about NRT (1.7/5)

31. Optimisation Generally very positive about geofence messages:
“When [the messages] actually came through it was as if the programme was written for me. Seriously that is what I did feel...because it was coming through at the times when I felt that I would have smoked and that’s when the support was there.” (ppt 1)
The regularity of support was also highlighted:
“The messages throughout the day were really, really helpful... you were kind of thinking about having a cigarette and it just kind of pops up and says, “You’re doing really well” or something like that” (ppt 18)
Agreement in favour of positive over negative messages:
“I don’t need to see stats about death and throat cancer and decay, because you just switch off, right.” (ppt 7)

32. Optimisation Participants also indicated they wanted:
Support to continue beyond 4 weeks
Increased tailoring of messages
Be able to report smoking retrospectively
More data entry after quit date - an ‘I’m not smoking’ when they’d resisted and a craving button

33. Self-monitoring effects
Value of self monitoring highlighted by some:
“And that was the most important thing to start off with, is realising where in your day the pinch points were going to be and to sort of see a pattern of how much you were smoking and when you were smoking.” (ppt 24)
“One of the worst things about smoking is sometimes before you know it you have a lighter and a cigarette in your hand and you’ve barely thought about it... Whereas inputting it I’d think, “Am I really that stressed? Am I really that anxious?” (ppt 42)

34. Conclusions
Target population positive about Q Sense – ¾ would use again
Most GF notifications engaged with – majority within 5 mins
But steady disengagement over time
Interest in more postquit reporting – urges and resists
Self-monitoring appears a potential mechanism of effect
McFall (1970) J Consult Clin Psychol ; McCarthy et al (2015) Addiction

35. Felix Naughton Behavioural Science Group University of Cambridge
Thank you
Felix Naughton
Behavioural Science Group
University of Cambridge
Collaborators
Neal Lathia
Sarah Hopewell
Rik Schalbroeck
Cecilia Mascolo
Andy McEwen
Stephen Sutton
@FelixNaughton