Cited by 35Smoking Behavior and CessationMobile Health and mHealth ApplicationsDigital Mental Health Interventions

Tailoring of a Smartphone Smoking Cessation App (Kick.it) for Serious Mental Illness Populations: Qualitative Study

Open access
Klein, Pauline, Lawn, Sharon, Tsourtos, George, van Agteren, Joep·2019·JMIR Human Factors

Published version of a preprint

Abstract

Background: Smoking rates of Australians with severe mental illness (SMI) are disproportionately higher than the general population. Despite the rapid growth in mobile health (mHealth) apps, limited evidence exists to inform their design for SMI populations. Objective: This study aimed to explore the feasibility, acceptability, and utility of adapting a novel smoking cessation app (Kick.it) to assist smokers with SMI to prevent smoking relapse and quit. Methods: Using co-design, two in-depth interviews with 12 adult smokers and ex-smokers with SMI were conducted in this qualitative study. Stage 1 interviews explored participants’ smoking-related experiences and perceptions of social support for smoking cessation, informed the development of the stage 2 interview schedule, and provided context for participants’ responses to the second interview. Stage 2 interviews explored participants’ perceptions of the feasibility, utility, and acceptability of the app features for SMI populations. Results: People with SMI perceived mHealth interventions to support their quit smoking attempts as feasible, acceptable, and useful. Key emerging themes included personalization of the app to users’ psychosocial needs, a caring app to mediate self-esteem and self-efficacy, an app that normalizes smoking relapse and multiple quit attempts, a strong focus on user experience to improve usability, and a social network to enhance social support for smoking cessation. Conclusions: This study gained an in-depth understanding of the lived experiences of smoking and quitting among people with SMI and their perception of the Kick.it app features to help inform the tailoring of the app. Specific program tailoring is required to assist them in navigating the complex interactions between mental illness and smoking in relation to their psychosocial well-being and capacity to quit. This study describes the adaptations required for the Kick.it app to meet the specific needs and preferences of people with SMI. Results of this study will guide the tailoring of the Kick.it app for SMI populations. The study findings can also inform a co-design process for the future development and design of smoking cessation apps for SMI populations.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/14023

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [37]Saks M Allsop J Researching Health: Qualitative, Quantitative and Mixed Methods. Second Edition 2013 London, UK Sage Publications

Cited by

Sorted by citations

Authors
Klein, P., Lawn, S., Tsourtos, G., & van Agteren, J.
Affiliations
Flinders University (AU)
Corresponding author
Klein, Pauline
Venue
JMIR Human Factors
Published
2019-09-03
Volume
6
Issue
3
Pages
e14023
ISSN
2292-9495 (ISSN-L)
OpenAlex
W2966821119
Cited by
35
References
40
Citations by year
2026: 1 · 2025: 4 · 2024: 3 · 2023: 9 · 2022: 9 · 2021: 6 · 2020: 2 · 2019: 1
FWCI
3.09
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR Human Factors (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Physiology › Smoking Behavior and Cessation
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Keywords
smoking cessation, severe mental illness, mobile health apps, co-design, smoking relapse, social support, self-efficacy, self-esteem, user experience, app usability, social networks

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review