PMID- 31162130
OWN - NLM
STAT- MEDLINE
DCOM- 20200129
LR  - 20200225
IS  - 2291-5222 (Print)
IS  - 2291-5222 (Electronic)
IS  - 2291-5222 (Linking)
VI  - 7
IP  - 6
DP  - 2019 Jun 3
TI  - Characteristics of Adopters of an Online Social Networking Physical Activity 
      Mobile Phone App: Cluster Analysis.
PG  - e12484
LID - 10.2196/12484 [doi]
LID - e12484
AB  - BACKGROUND: To date, many online health behavior programs developed by 
      researchers have not been translated at scale. To inform translational efforts, 
      health researchers must work with marketing experts to design cost-effective 
      marketing campaigns. It is important to understand the characteristics of end 
      users of a given health promotion program and identify key market segments. 
      OBJECTIVE: This study aimed to describe the characteristics of the adopters of 
      Active Team, a gamified online social networking physical activity app, and 
      identify potential market segments to inform future research translation efforts. 
      METHODS: Participants (N=545) were Australian adults aged 18 to 65 years who 
      responded to general advertisements to join a randomized controlled trial (RCT) 
      evaluating the Active Team app. At baseline they provided demographic (age, sex, 
      education, marital status, body mass index, location of residence, and country of 
      birth), behavioral (sleep, assessed by the Pittsburgh Quality Sleep Index) and 
      physical activity (assessed by the Active Australia Survey), psychographic 
      information (health and well-being, assessed by the PERMA [Positive Emotion, 
      Engagement, Relationships, Meaning, Achievement] Profile; depression, anxiety and 
      stress, assessed by the Depression, Anxiety, and Stress Scale [DASS-21]; and 
      quality of life, assessed by the 12-Item Short Form Health Survey [SF-12]). 
      Descriptive analyses and a k-medoids cluster analysis were performed using the 
      software R 3.3.0 (The R Foundation) to identify key characteristics of the 
      sample. RESULTS: Cluster analyses revealed four clusters: (1) younger inactive 
      women with poor well-being (218/545), characterized by a higher score on the 
      DASS-21, low mental component summary score on the SF-12, and relatively young 
      age; (2) older, active women (153/545), characterized by a lower score on 
      DASS-21, a higher overall score on the SF-12, and relatively older age; (3) 
      young, active but stressed men (58/545) with a higher score on DASS-21 and higher 
      activity levels; and (4) older, low active and obese men (30/545), characterized 
      by a high body mass index and lower activity levels. CONCLUSIONS: Understanding 
      the characteristics of population segments attracted to a health promotion 
      program will guide the development of cost-effective research translation 
      campaigns. TRIAL REGISTRATION: Australian New Zealand Clinical Trial Registry 
      ACTRN12617000113358; https://www.anzctr.org 
      .au/Trial/Registration/TrialReview.aspx?id=371463. INTERNATIONAL REGISTERED 
      REPORT IDENTIFIER (IRRID): RR2-10.1186/s12889-017-4882-7.
CI  - (c)Ilea Sanders, Camille E Short, Svetlana Bogomolova, Tyman Stanford, Ronald 
      Plotnikoff, Corneel Vandelanotte, Tim Olds, Sarah Edney, Jillian Ryan, Rachel G 
      Curtis, Carol Maher. Originally published in JMIR Mhealth and Uhealth 
      (http://mhealth.jmir.org), 03.06.2019.
FAU - Sanders, Ilea
AU  - Sanders I
AUID- ORCID: 0000-0002-7527-2057
AD  - Alliance for Research in Exercise, Nutrition and Activity, School of Health 
      Sciences, University of South Australia, Adelaide, Australia.
FAU - Short, Camille E
AU  - Short CE
AUID- ORCID: 0000-0002-4177-4251
AD  - Freemasons Foundation Centre for Men's Health, Faculty of Health Sciences, The 
      University of Adelaide, Adelaide, Australia.
FAU - Bogomolova, Svetlana
AU  - Bogomolova S
AUID- ORCID: 0000-0003-4449-6514
AD  - Ehrenberg-Bass Institute, School of Marketing, University of South Australia, 
      Adelaide, Australia.
FAU - Stanford, Tyman
AU  - Stanford T
AUID- ORCID: 0000-0002-8570-5493
AD  - School of Mathematical Sciences, The University of Adelaide, Adelaide, Australia.
FAU - Plotnikoff, Ronald
AU  - Plotnikoff R
AUID- ORCID: 0000-0002-3763-8273
AD  - Priority Research Centre for Physical Activity and Nutrition, University of 
      Newcastle, Newcastle, Australia.
FAU - Vandelanotte, Corneel
AU  - Vandelanotte C
AUID- ORCID: 0000-0002-4445-8094
AD  - Physical Activity Research Group, Central Queensland University, Adelaide, 
      Australia.
FAU - Olds, Tim
AU  - Olds T
AUID- ORCID: 0000-0001-6894-5519
AD  - Alliance for Research in Exercise, Nutrition and Activity, School of Health 
      Sciences, University of South Australia, Adelaide, Australia.
FAU - Edney, Sarah
AU  - Edney S
AUID- ORCID: 0000-0002-3925-517X
AD  - Alliance for Research in Exercise, Nutrition and Activity, School of Health 
      Sciences, University of South Australia, Adelaide, Australia.
FAU - Ryan, Jillian
AU  - Ryan J
AUID- ORCID: 0000-0003-0655-3047
AD  - Alliance for Research in Exercise, Nutrition and Activity, School of Health 
      Sciences, University of South Australia, Adelaide, Australia.
FAU - Curtis, Rachel G
AU  - Curtis RG
AUID- ORCID: 0000-0002-1341-7804
AD  - Alliance for Research in Exercise, Nutrition and Activity, School of Health 
      Sciences, University of South Australia, Adelaide, Australia.
FAU - Maher, Carol
AU  - Maher C
AUID- ORCID: 0000-0002-8676-0224
AD  - Alliance for Research in Exercise, Nutrition and Activity, School of Health 
      Sciences, University of South Australia, Adelaide, Australia.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20190603
PL  - Canada
TA  - JMIR Mhealth Uhealth
JT  - JMIR mHealth and uHealth
JID - 101624439
SB  - IM
MH  - Adolescent
MH  - Adult
MH  - Aged
MH  - Australia
MH  - Cluster Analysis
MH  - Exercise/*psychology
MH  - Female
MH  - Humans
MH  - Male
MH  - Middle Aged
MH  - Mobile Applications/*standards/statistics & numerical data
MH  - *Social Networking
MH  - Social Theory
MH  - Surveys and Questionnaires
PMC - PMC6746062
OTO - NOTNLM
OT  - k-medoid cluster analysis
OT  - mobile phone app
OT  - online social networking
OT  - physical activity
OT  - social marketing
COIS- Conflicts of Interest: None declared.
EDAT- 2019/06/05 06:00
MHDA- 2019/06/05 06:01
PMCR- 2019/06/03
CRDT- 2019/06/05 06:00
PHST- 2018/10/17 00:00 [received]
PHST- 2019/04/11 00:00 [accepted]
PHST- 2019/04/07 00:00 [revised]
PHST- 2019/06/05 06:00 [entrez]
PHST- 2019/06/05 06:00 [pubmed]
PHST- 2019/06/05 06:01 [medline]
PHST- 2019/06/03 00:00 [pmc-release]
AID - v7i6e12484 [pii]
AID - 10.2196/12484 [doi]
PST - epublish
SO  - JMIR Mhealth Uhealth. 2019 Jun 3;7(6):e12484. doi: 10.2196/12484.