Exploration of Digital Health Technologies

Table 1. Demographic and health-related characteristic comparisons between the SMP and NSMP cohorts

Characteristics	Social media presence (n = 665)		No social media presence (n = 334)
Characteristics	n	%	n	%
Sex**
Female	271	40.8	176	52.7
Male	394	59.2	158	47.3
Neighborhood of residence in childhood*
West upper	207	31.6	78	23.5
West lower	168	25.6	85	25.6
East upper	99	15.1	57	17.2
East lower	182	27.7	112	33.7
Family income in childhood
Over $20,000	362	56.1	167	52.7
$10,000–20,000	192	29.8	105	33.1
Under $10,000	91	14.1	45	14.2
Persistent cough in childhood
No	537	96.2	261	95.3
Yes	21	3.8	13	4.7
Chest illness in childhood
No	623	94.1	309	93.1
Yes	39	5.9	23	6.9
Hospitalization before the age of two
Unknown/NA	628	94.4	311	93.1
Hospitalized at least once or more	37	5.6	23	6.9
Asthma ever
No	619	93.1	305	91.3
Yes	46	6.9	29	8.7
Smoked during childhood
No	481	77.7	236	76.1
Yes	138	22.3	74	23.9
Current residence
Hamilton	409	61.5	-	-
Halton region cities	20	3.0	-	-
Toronto	15	2.3	-	-
Other	76	11.4	-	-
Out of province	10	1.5	-	-
Missing	135	20.3	-	-

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Significance tests indicate differences between SMP cohort and NSMP cohort. N may not add up due to missing data. NA: not applicable. *: p < 0.05; **: p < 0.001; -: no data

Declarations

Author contributions

RRA, SJY, and SSM: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing—original draft, Writing—review & editing. SE and CB: Supervision, Conceptualization, Data curation, Resources, Software, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing—original draft, Writing—review & editing.

Conflicts of interest

The authors declare that they have no conflicts of interest.

Ethical approval

Ethics consent to conduct this study and secondary analysis of the HCC study dataset, was received from Ontario Tech University (REB File #17547), and complies with the Declaration of Helsinki.

Consent to participate

Informed consent to participate in the study was obtained from all participants.

Consent to publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Funding

This study received funding from an SSHRC Internal Explore Grant at Ontario Tech University. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright

References

Desai M. Recruitment and retention of participants in clinical studies: Critical issues and challenges. Perspect Clin Res. 2020;11:51–3. [DOI] [PubMed] [PMC]

Fogel DB. Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review. Contemp Clin Trials Commun. 2018;11:156–64. [DOI] [PubMed] [PMC]

Toledano MB, Smith RB, Brook JP, Douglass M, Elliott P. How to Establish and Follow up a Large Prospective Cohort Study in the 21st Century - Lessons from UK COSMOS. PLoS One. 2015;10:e0131521. [DOI] [PubMed] [PMC]

Belanger CF, Hennekens CH, Rosner B, Speizer FE. The nurses’ health study. Am J Nurs. 1978;78:1039–40. [DOI] [PubMed]

Mychasiuk R, Benzies K. Facebook: an effective tool for participant retention in longitudinal research. Child Care Health Dev. 2012;38:753–6. [DOI] [PubMed]

Masson H, Balfe M, Hackett S, Phillips J. Lost without a Trace? Social Networking and Social Research with a Hardto-Reach Population. Br J Soc Work. 2011;43:24–40. [DOI]

Stephenson NL, Hetherington E, Dodd S, Mathews A, Tough S. Mitigation of Participant Loss to Follow-Up Using Facebook: All Our Families Longitudinal Pregnancy Cohort. J Med Internet Res. 2019;21:e10441. [DOI] [PubMed] [PMC]

Price SM, Park CH, Brenner RA, Lo A, Adams S, Baetz RA, et al. Participant retention in a longitudinal study: do motivations and experiences matter? Surv Pract. 2016:9.

Davis E, Demby H, Jenner LW, Gregory A, Broussard M. Adapting an evidence-based model to retain adolescent study participants in longitudinal research. Eval Program Plann. 2016;54:102–11. [DOI] [PubMed]

10.

Gustavson K, Soest Tv, Karevold E, Røysamb E. Attrition and generalizability in longitudinal studies: findings from a 15-year population-based study and a Monte Carlo simulation study. BMC Public Health. 2012;12:918. [DOI] [PubMed] [PMC]

11.

Kleschinsky JH, Bosworth LB, Nelson SE, Walsh EK, Shaffer HJ. Persistence pays off: follow-up methods for difficult-to-track longitudinal samples. J Stud Alcohol Drugs. 2009;70:751–61. [DOI] [PubMed] [PMC]

12.

Young AF, Powers JR, Bell SL. Attrition in longitudinal studies: who do you lose? Aust N Z J Public Health. 2006;30:353–61. [DOI] [PubMed]

13.

Ribisl KM, Walton MA, Mowbray CT, Luke DA, Davidson WS, Bootsmiller BJ. Minimizing participant attrition in panel studies through the use of effective retention and tracking strategies: Review and recommendations. Eval Program Plann. 1996;19:1–25. [DOI]

14.

Teague S, Youssef GJ, Macdonald JA, Sciberras E, Shatte A, Fuller-Tyszkiewicz M, et al. Retention strategies in longitudinal cohort studies: a systematic review and meta-analysis. BMC Med Res Methodol. 2018;18:151. [DOI] [PubMed] [PMC]

15.

Ermakova T, Fabian B, Bender B, Klimek K. Web Tracking – A Literature Review on the State of Research. AIS eLibrary. 2018. [DOI]

16.

Patel MX, Doku V, Tennakoon L. Challenges in recruitment of research participants. Adv Psychiatr Treat. 2003;9:229–38. [DOI]

17.

Barakat C, Dash S, Klicnik I, Mohammed S, Yousufzai S. A cross-sectional study to examine constraints to sport participation among ethnically diverse female adolescents from Ontario, Canada. Int J Sport, Exercise Health Res. 2021;5:68–75. [DOI]

18.

Jones L, Saksvig BI, Grieser M, Young DR. Recruiting adolescent girls into a follow-up study: benefits of using a social networking website. Contemp Clin Trials. 2012;33:268–72. [DOI] [PubMed] [PMC]

19.

Dixon SJ. Number of social media users worldwide from 2017 to 2028 [Internet]. [cited 2023 Dec 12]. Available from: https://www.statista.com/statistics/278414/number-of-worldwide-social-network-users/#:~:text=Social%20media%20usage%20is%20one,almost%20six%20billion%20in%202027

20.

Bolanos F, Herbeck D, Christou D, Lovinger K, Pham A, Raihan A, et al. Using facebook to maximize follow-up response rates in a longitudinal study of adults who use methamphetamine. Subst Abuse. 2012;6:1–11. [DOI] [PubMed] [PMC]

21.

Walsh LE, Carter-Bawa L. Using social media to recruit individuals for health-related research: Feasibility and lessons learned. J Health Psychol. 2023;28:599–606. [DOI] [PubMed] [PMC]

22.

Hurwitz LB, Schmitt KL, Olsen MK. Facilitating Development Research: Suggestions for Recruiting and Re-Recruiting Children and Families. Front Psychol. 2017;8:1525. [DOI] [PubMed] [PMC]

23.

Michalek AK, Kan D, Prochaska J. Engaging veterans with substance abuse disorders into a research trial: success with study branding, networking, and presence. Transl Behav Med. 2015;5:167–76. [DOI] [PubMed] [PMC]

24.

Gul RB, Ali PA. Clinical trials: the challenge of recruitment and retention of participants. J Clin Nurs. 2010;19:227–33. [DOI] [PubMed]

25.

Pekarsky C, Skiffington J, Leijser LM, Slater D, Metcalfe A. Social Media Recruitment Strategies to Recruit Pregnant Women Into a Longitudinal Observational Cohort Study: Usability Study. J Med Internet Res. 2022;24:e40298. [DOI] [PubMed] [PMC]

26.

Pengelly LD, Kerigan AT, Goldsmith CH. Sensitivity of children with asthma to chronic low-level sulphur dioxide exposure. In: Brasser LJ, Mulder WC, editors. Man and his Ecosystem. Proceedings to the 8th World Clean Air Congress; 1989 Sep 11-15; The Hague, The Netherlands. Amsterdam: Elsevier; 1989. pp. 7–12.

27.

Barakat-Haddad C, Elliott SJ, Pengelly D. Does Chronic Exposure to Air Pollution in Childhood Impact Long-Term Respiratory Health? Prof Geogr. 2012;64:446–63. [DOI]

28.

Barakat-Haddad CP, Elliott SJ, Eyles J, Pengelly D. Predictors of locating children participants in epidemiological studies 20 years after last contact: Internet resources and longitudinal research. Eur J Epidemiol. 2009;24:397–405. [DOI] [PubMed]

29.

Hampson SE, Edmonds GW, Barckley M, Goldberg LR, Dubanoski JP, Hillier TA. A Big Five approach to self-regulation: personality traits and health trajectories in the Hawaii longitudinal study of personality and health. Psychol Health Med. 2016;21:152–62. [DOI] [PubMed] [PMC]

30.

Marcus PM, Childs J, Gahagan B, Gren LH. Tracking and tracing of participants in two large cancer screening trials. Contemp Clin Trials. 2012;33:601–5. [DOI] [PubMed] [PMC]

31.

Warner ET, Glasgow RE, Emmons KM, Bennett GG, Askew S, Rosner B, et al. Recruitment and retention of participants in a pragmatic randomized intervention trial at three community health clinics: results and lessons learned. BMC Public Health. 2013;13:192. [DOI] [PubMed] [PMC]

32.

Darko EM, Kleib M, Olson J. Social Media Use for Research Participant Recruitment: Integrative Literature Review. J Med Internet Res. 2022;24:e38015. [DOI] [PubMed] [PMC]

33.

Park BK, Calamaro C. A systematic review of social networking sites: innovative platforms for health research targeting adolescents and young adults. J Nurs Scholarsh. 2013;45:256–64. [DOI] [PubMed]

34.

Brooke Auxier MA. Social Media Use in 2021 [Internet]. Pew Research Center; 2024 [cited 2023 Sep 15]. Available from: https://www.pewresearch.org/internet/2021/04/07/social-media-use-in-2021/

35.

Pannucci CJ, Wilkins EG. Identifying and avoiding bias in research. Plast Reconstr Surg. 2010;126:619–25. [DOI] [PubMed] [PMC]

36.

Kristman V, Manno M, Côté P. Loss to follow-up in cohort studies: how much is too much? Eur J Epidemiol. 2004;19:751–60. [DOI] [PubMed]

37.

Fischer EH, Dornelas EA, Goethe JW. Characteristics of people lost to attrition in psychiatric follow-up studies. J Nerv Ment Dis. 2001;189:49–55. [DOI] [PubMed]