The Efficacy Of Personalized Feedback Interventions Delivered Via Smartphone
Brief motivational interviews,“a widely disseminated clinical approach that uses a directive, client-centered counseling style for eliciting behavior change by helping clients to explore and resolve ambivalence about changing the addictive behavior” (Miller & Rose, 2009)have been used to reduce gambling-related behaviors, especially when they incorporate personalized feedback. Personalized feedback will typically include pieces of information relating specifically to the issues one is facing, such as difficulties that have occurred due to the problem, and comparisons to social norms. This is used as a catalyst for motivating one to change their behavior.
A new study (McAfee et al., 2020), funded by an ICRG Large Grant, set out to look at whether brief motivational interviews with personalized feedback delivered via smartphone to college students would be helpful in reducing gambling related harms.
Hypotheses
Researchers examined the efficacy of personalized feedback based interventions delivered via smartphone and text message with college-aged gamblers. They wished to test three separate hypotheses within the sample. First, they hypothesized that students that received motivational interviews would report lower gambling norms than the control group that received no motivational interview or text messages. Second, they hypothesized that students that received personalized feedback via text during the trial period (PFB-TXT) would report fewer gambling-related cognitive distortions at the one month follow up, and subsequently less gambling and fewer gambling problems at the six-month follow-up than the study group that received general education information about gambling, rather than personalized feedback (PFB-EDU). Lastly, they hypothesized that students in the PFB-TXT group would report use of gambling protective strategies at the one-month follow-up and subsequently less gambling and problems at the six-month follow up than the PFB-EDU group.
Why is this important?
College students, on average, engage in at-risk gambling at a higher rate than the general population. This is concerning because evidence shows that disordered gambling often co-occurs with other health related problems such as alcohol abuse, drug use, and tobacco use. Previous interventions that incorporate personalized feedback have been effective at reducing gambling problems. Most importantly, addressing cognitive distortions about gambling and offering protective behaviors related to gambling may be useful in treatment of gambling problems in college students.
What did they do?
Researchers completed a clinical trial of college students that had gambled in the last 60 days and successfully scheduled an enrollment meeting to participate in the trial. These students, recruited through email announcements and that met the screening threshold, were assigned randomly to one of three study groups. Eighty students were assigned to the Personalized Feedback plus Text group, 68 students assigned to the personalized feedback, no text message group, and 93 were assigned to the control group, which received no personalized feedback or text messages. All participants completed self-report questionnaires at baseline, one month and six months.
- Screening was completed using SOGS (Lesieur & Blume, 1987) and BBGS (Gebauer et al., 2010) to screen for at-risk gambling
- Gambling Frequency was measured by asking participants to indicate days they gambled on a calendar and how much they gambled
- Gambling Problems were measured using the CPGI nine-item measure (Ferris & Wynne, 2001) developed to assess the degree to which participants experienced any consequences related to gambling
- Gambling norms were assessed by asking participants how many times they believe a typical student gambles within a month
- Cognitive distortions were measured using the GRCS gambling related cognitions scale (Raylu & Oei, 2004) to assess cognitions related to gambling.
- Protective strategies were measured via a gambling protective behavior scale
The PBS-TXT group received 12 targeted text messages with a link to personalized feedback including the number of times they gambled per month compared to other college students and a summary of self-reported negative consequences they associated with their gambling.
The PBS-EDU group received personalized feedback identical to the first group, but instead of targeted information, they received generic educational information in texts.
The control group completed the same assessments as the first two groups but received no feedback or texts.
At the completion of the study, researchers conducted three sets of analyses using the PROCESS program, which tests for indirect, direct, and total effects of an intervention condition.
Results
Researchers found that personalized feedback conditions did not have a direct effect compared to the control condition on variables measured at the six-month follow-up. However, they found a significant effect of gambling norms answers at the one-month follow-up. Additionally, they found no differences between the two different PFB conditions in terms of indirect or direct effects at the six-month follow-up, which suggests personalized feedback did not provide greater efficacy in changing gambling -related outcomes throughout the trial. Although the main hypothesis could not be substantiated within this study, researchers had a few significant findings.
- Participants in both of the PFB groups reported less perceived gambling among students at one month, which correlated fewer gambling problems at month 6.
- Participants that received the targeted PFB messages, rather than the generic messages, did not report a significantly greater usage of protective behavioral strategies at one-month follow-up
- Participants in both of the PFB groups reported that the typical student gambled less than the students in the control group reported
Limitations
Although a clinical trial with a control group, this study was not without limitations. Researchers report that they believe the intervention did not work well with the sample chosen, as many of the student gamblers engaged in gambling outside of traditional establishments and the interventions and messages were written for traditional methods of gambling. Researchers also reported generalizability is low, because the sample group is one set of students at one University. Additionally, assessments utilized retrospective self-report, which is prone to bias.
Ferris, J., & Wynne, H. (2001).The Canadian Problem Gambling Index: User’s Manual. Canadian Centre on Substance Abuse (CCSA).
Gebauer, L., LaBrie, R., & Shaffer, H. J. (2010). Optimizing DSM-IV-TR classification accuracy: A brief biosocial screen for detecting current gambling disorders among gamblers in the general household population.Canadian Journal of Psychiatry,55(2), 82–90.
Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of pathological gamblers.American Journal of Psychiatry,144(9), 1184–1188.
McAfee, N., Martens, M. P., Herring, T., Takamatsu, S. K., & Foss, J. (2020). The efficacy of personalized feedback interventions delivered via smartphone among at-risk college student gamblers.Journal of Gambling Issues,45, 39–63.
Miller, W., & Rose, G. (2009). Toward a theory of motivational interviewing.American Psychologist,64(4), 527–537.
Raylu, N., & Oei, T. P. S. (2004). The Gambling Related Cognitions Scale (GRCS): Development, confirmatory factor validation and psychometric properties.Addiction,99(6), 757–769. https://doi.org/10.1111/j.1360-0443.2004.00753.x
