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SMS text messaging interventions for healthy behaviour change

by Olivia Maynard @OliviaMaynard17

This blog originally appeared on the Mental Elf site on 28th September 2015.

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There’s a lot to like about text messaging (Short Message Service: SMS) interventions for behaviour change: they can deliver cost-effective, brief, real-time and tailored messages at moments when individuals need them most. They reduce time demands on both the individual and health care practitioners, maintain the privacy of the individual and what’s more, given that the majority of the world’s population own a mobile phone, text messaging interventions can be delivered at a global scale.

Given these advantages, there’s been a great deal of research on the effectiveness of SMS interventions for health behaviours, finding mixed results. Last month, I blogged about a meta-analysis which found weak evidence for the efficacy of SMS interventions for smoking cessation. However, smoking cessation is a complex health behaviour and recent reviews have found that SMS interventions are more effective for more simple health behaviours such as medicine adherence and attending medical appointments.

Another recent meta-analysis by Orr and King (2015) published in Health Psychology Review was the first to examine the overall effectiveness of SMS interventions to enhance healthy behaviour, rather than focus on any one health behaviour (i.e. smoking cessation). Similar to the meta-analysis I blogged about last month, the authors also aimed to identify which SMS features have the biggest impact on intervention effectiveness.

Mobile phones are now so ubiquitous that they are a great tool to deliver interventions globally.

Methods

The authors searched for randomised controlled trials (RCTs) which compared SMS interventions targeting health behaviour change to a non-SMS control, which did not attempt to change behaviour (i.e. RCTs which compared two active treatments were not included).

The authors examined the influence of six moderators on the effectiveness of SMS interventions:

  1. SMS dose (i.e. the frequency of the messages: multiple per day, weekly, once only etc);
  2. SMS message tailoring (i.e. standardised, tailored, personalised);
  3. SMS directionality between researcher and participant (i.e. one-way, two-way);
  4. Category of health behaviour targeted (i.e. unhealthy behaviour modification, chronic disease management, medication adherence, appointment attendance, disease or pregnancy preventive behaviours);
  5. Complexity of these behaviours (i.e. complex: chronic disease management, disease-related medication adherence, unhealthy behaviour modification; simple: appointment attendance, non-disease-related medication adherence, preventive behaviour);
  6. Participants’ mean age.

Results

Thirty eight studies met the criteria for inclusion in this meta-analysis.

The meta-analysis found that there was an overall (pooled) positive effect of SMS interventions on healthy behaviour (g = 0.291, 95% CI = 0.219 to 0.363, p < 0.001). The heterogeneity between studies was low (I2 = 38.619, p = 0.009­).

Planned sub-group analyses explored the impact of the six moderators on health behaviour change. There was little evidence that any of the six moderators impacted SMS intervention efficacy. However, when the authors regrouped the studies (i.e. unplanned analyses) for the tailoring, dose and complexity moderators, only SMS dose was found to impact SMS efficacy, with studies using multiple messages per day being more effective than those with reduced frequency.

The effect size for SMS interventions was small, but given that this is a cheap and simple intervention to deliver, it may be worthwhile.

Strengths

The quality of the evidence in the 38 studies was judged to be relatively high, with all but three of the studies assessed as having high to moderate methodological quality. However, the authors judged that the risk of incomplete data was high in 40% of studies, despite efforts to contact the authors of the original studies for further information.

Further analyses of the data found that publication bias was not a threat to the validity of the estimated effect of SMS interventions for healthy behaviour.

Weaknesses

The majority of included studies relied on self-report outcome measures, rather than actual behaviour, which is likely to have increased the observed effects of the studies. Future studies should use objective outcome measures.

The observation that more frequent text messages are more effective than less frequent messages was only found after regrouping the studies and running multiple unplanned comparisons between groups. This finding should therefore be treated with caution.

The authors only included studies which compared SMS intervention to no intervention at all. These findings therefore tell us nothing about how SMS interventions compare to other established interventions, such as verbal or other written reminders and messages.

Very few of the studies included in this meta-analysis were grounded in any health behaviour theory. The authors suggest that future research should examine the impact of established theoretical components on health behaviour change outcomes.

This study does not provide reliable evidence that more frequent text messages are more effective than less frequent messages.

Discussion

Using strict inclusion criteria for studies, this meta-analysis found that SMS interventions have a positive, albeit small, effect on healthy behaviour change. There was little evidence that moderators such as tailoring, directionality, health behaviour category or complexity or participant age influence efficacy. There was some evidence that higher SMS dose might increase efficacy.

These findings echo those in a recent meta-analysis of studies exploring the effectiveness of SMS interventions for smoking cessation where no moderator was found to be more effective than any other at increasing quit success and only a small positive effect of SMS intervention was observed.

Although this and previous meta-analyses have found only modest benefits of SMS interventions over control, given the low cost of delivery of SMS interventions and the potential to target large numbers of individuals, the public health benefits are still considerable and future research should continue to examine the efficacy of these interventions.

Despite the small effect sizes, SMS text messages remain a potentially effective intervention that can work on a truly global scale.

Links

Primary paper

Orr JA, King RJ. (2015) Mobile phone SMS messages can enhance healthy behaviour: a meta-analysis of randomised controlled trialsHealth psychology review (just-accepted), 1-36.

Other references

Maynard O. (2015) SMS texting to quit smoking: a meta-analysis of text messaging interventions for smoking cessation. The Mental Elf, 26 Aug 2015.

SMS texting to quit smoking: a meta-analysis of text messaging interventions for smoking cessation

by Olivia Maynard @OliviaMaynard17

This blog originally appeared on the Mental Elf site on 26th August 2015.

The efficacy of different smoking cessation interventions is always a hot topic around our woodland campfire. We’ve blogged previously about the effectiveness of both pharmacological and psychological treatments for smoking cessation, as well as their effectiveness among different populations of smokers.

A recent systematic review and meta-analysis investigated the efficacy of SMS text message interventions for smoking cessation. Unlike the majority of other smoking cessation interventions, using mobile phones to deliver health information allows for direct interaction between clients and practitioners without face-to-face interaction and permits the collection of large amounts of data. It is therefore cost-effective and easily scalable to large populations.

Previous meta-analyses have looked at the effectiveness of text messaging interventions for smoking cessation, but the review recently published by Spohr and colleagues is the first to investigate which elements or moderators of text message interventions are the most effective in supporting smoking cessation.

This review

Methods

The authors searched for randomised controlled trials which investigated the efficacy of text messaging interventions for smoking cessation. Only studies which included a follow-up measure of smoking abstinence were included. 13 articles met all of these inclusion criteria.

The authors also extracted information on the use of each of the moderators described below:

  • Intervention type:
    • SMS only;
    • ‘SMS plus’ (where SMS support is combined with either face-to-face or web-based support).
  • Message frequency:
    • Fixed message schedule (a consistent number of messages throughout the intervention);
    • Decreasing schedule (most messages at quit attempts, followed by a gradual reduction);
    • Dynamic schedule (depends on the stage of cessation the client is at).
  • Message track:
    • Fixed message track (users cannot influence the course of the intervention);
    • Dynamic message track (user quit status and stage of change can influence intervention messages).
  • Message tailoring:
    • Tailored messages (customised message content to a specific individual);
    • Targeted messages (customised messages to a population subgroup).
  • On-demand messaging:
    • On-demand messaging (allow users to text a keyword in emergency situations to receive additional support. Some interventions allow users to connect with other users for support and encouragement).
  • Message direction:
    • Unidirectional messaging (by the researcher);
    • Bidirectional messaging (to obtain data from the client).
  • Message interaction:
    • Researcher-initiated (containing intervention messages and assessment questions);
    • User-initiated (containing requests for additional support).

Intervention success was assessed using seven-day point prevalence as the primary outcome measure, as 11/13 of the studies reported these results. Two other studies only reported 6 month continuous abstinence.

The researchers used an intention to treat analysis.

Perhaps surprisingly (given the ubiquitous nature of smartphones) the reviewers only found 13 trials to include in their analysis.

Results

The 13 articles resulted in a cumulative sample size of n = 13,626. Participants were primarily adult smokers (six studies), but four studies recruited participants aged 15 or over and three targeted adolescents and young adults (ages 16-25).

Smoking quit rates for the text messaging intervention groups were 35% higher as compared to control groups (OR = 1.35, 95% CI = 1.23 to 1.49).

Overall, the analysis of the intervention moderators did not find strong evidence that any particular moderator was more effective than any other:

  • Intervention type:
    • There were no differences (Q= 0.56, df = 1, p = 0.46) in intervention efficacy between those which provided text-only support (= 6) as compared with text messaging plus additional support (k = 7).
    • However, text-only interventions had a slightly larger effect size than those with text messaging plus additional support.
    • There were no differences (Q= 0.89, df = 1, p = 0.35) in intervention efficacy between those which promoted the use of nicotine replacement therapy (NRT) (= 7) as compared with those which did not (k = 6).
  • Message frequency:
    • There were no differences (Q= 0.96, df = 2, p = 0.62) in intervention efficacy between those which provided decreasing schedule (= 8) as compared with fixed schedule (k = 3) or variable schedule (= 2) support.
    • However, those which had a fixed schedule had larger effect sizes than either of the other types of schedules.
  • Message track:
    • There were no differences (Q= 0.38, df = 1, p = 0.54) in intervention efficacy between those which used a fixed message track (= 5) as compared with a dynamic message track (k = 8).
  • Message tailoring:
    • There were no differences (Q= 1.54, df = 2 p = 0.46) in intervention efficacy between those which used message tailoring (= 8) as compared message targeting (k = 1) or a combination of both (k = 4).
    • All studies included some form of message content tailoring.
  • On-demand messaging:
    • There were no differences (Q= 0.15, df = 1, p = 0.70) in intervention efficacy between those which used on-demand messaging (= 11) as compared with those which did not (k = 2).
    • There were no differences (Q= 0.02, df = 1, p = 0.88) in intervention efficacy between those which provided peer-to-peer support (= 5) as compared with those which did not (k = 8).
  • Message direction:
    • All of the studies used bidirectional messaging so the effectiveness of this moderator to unidirectional messaging could not be assessed.
  • Message interaction:
    • There were no differences (Q= 0.17, df = 1, p = 0.68) in intervention efficacy between those which included assessment messages (= 7) as compared with those which did not (k = 6).

Text messaging does not compare well to many other more effective methods of smoking cessation.

Conclusions

This meta-analysis found that smoking cessation interventions which used text-messaging increased the odds of successfully quitting smoking by 35%.

To put this in perspective, other reviews have found that telephone quit lines increase smoking cessation success by 60%, social support increases success by 30% and practical counselling by 50%. NRT and other medications have been shown to increase cessation success by between 50% and 310% (Fiore et al., 2000).

None of the moderators investigated here were found to be more effective than any other. There was some evidence that interventions which used fixed schedules were more effective than those which used either decreasing or variable schedules. Similarly, there was some evidence that text-only support programs were more effective than those which provided a ‘text-plus’ service. However, there was no robust statistical evidence for these differences.

Overall, these results provide no evidence that text-messaging interventions, which are more complex and time-demanding (i.e. text-plus, on-demand messaging, variable schedules, social support communication), are any more effective than the simplest interventions.

However, given the cost-effectiveness, relative ease of delivery and promise of efficacy of these interventions, future research should continue to determine what moderators make an effective text-based intervention.

Limitations and future directions

These results should be treated with caution however, for a number of reasons:

  • The authors relied on data obtained from the original articles to compile this meta-analysis, rather than contacting the researchers themselves. As data regarding the actual use by users of some of the moderators such as social support and on-demand messaging was not reported in articles, we cannot be certain whether the failure of these moderators to increase quit success is because they are simply not more effective, or because users didn’t actually use these services.
  • The number of studies included in this meta-analysis was small (only 13 studies). This is even more the case for the moderator analyses. Drawing firm conclusions from the statistical evidence is therefore difficult.

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Links

Primary paper

Spohr SA, Nandy R, Gandhiraj D, Vemulapalli A, Anne S, Walters ST. (2015) Efficacy of SMS Text Message Interventions for Smoking Cessation: A Meta-Analysis. Journal of Substance Abuse Treatment, 56, 1-10. doi: http://dx.doi.org/10.1016/j.jsat.2015.01.011

Other references

Fiore MC, Bailey WC, Cohen SJ, Dorfman SF, Goldstein MG, Gritz ER, … Lando HA. (2000) Treating tobacco use and dependence: a clinical practice guideline: Publications Clearinghouse.

– See more at: http://www.nationalelfservice.net/mental-health/substance-misuse/sms-texting-to-quit-smoking-a-meta-analysis-of-text-messaging-interventions-for-smoking-cessation/#sthash.hjMwMixu.dpuf