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Persuasive technology
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=== Difficulty in studying behavior change === In general, understanding behavioral changes require long-term studies as multiple internal and external factors can influence these changes (such as personality type, age, income, willingness to change and more). For that, it becomes difficult to understand and measure the effect of persuasive technologies. Furthermore, meta-analyses of the effectiveness of persuasive technologies have shown that the behavior change evidence collected so far is at least controversial, since it is rarely obtained by Randomized Controlled Trials (RCTs),{{sfn|Hamari|Koivisto|Pakkanen|2014}} the “gold standard” in causal inference analysis. In particular, due to relevant practical challenges to perform strict RCTs,{{sfn|Bhushan|Steg|Albers|2018}} most of the above-mentioned empirical trials on lifestyles rely on voluntary, self-selected participants. If such participants were systematically adopting the desired behaviors already before entering the trial, then self-selection biases would occur. Presence of such biases would weaken the behavior change effects found in the trials. Analyses aimed at identifying the presence and extent of self-selection biases in persuasive technology trials are not widespread yet. A study by Cellina et al. on an app-based behavior change trial in the mobility field found evidence of no self-selection biases.{{sfn|Cellina|Vittucci Marzetti|Gui|2021}} However, further evidence needs to be collected in different contexts and under different persuasive technologies in order to generalize (or confute) their findings.{{citation needed|date=August 2021}}
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