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Hand hygiene is an effective behavior for preventing the spread of the respiratory disease COVID-19 and was included in public health guidelines worldwide. Behavior change interventions addressing hand hygiene have the potential to support the adherence to public health recommendations and, thereby, prevent the spread of COVID-19. However, randomized trials are largely absent during a pandemic; therefore, there is little knowledge about the most effective strategies to promote hand hygiene during an ongoing pandemic. This study addresses this gap by presenting the results of the optimization phase of a Multiphase Optimization Strategy of
This study aimed to identify the most effective combination and sequence of 3 theory- and evidence-based intervention modules (habit, motivation, and social norms) for promoting hand hygiene. To this end, 9 versions of
This study was a parallel randomized trial with 9 intervention conditions defined by the combination of 2 intervention modules and their sequence. The trial was conducted from March to August 2021 with interested participants from the Swiss general population (N=232; randomized). Randomization was performed using Qualtrics (Qualtrics International Inc), and blinding was ensured. The duration of the intervention was 34 days. The primary outcome was self-reported hand hygiene at follow-up, which was assessed using an electronic diary. The secondary outcomes were user engagement, usability, and satisfaction assessed at follow-up. Nine participants were further invited to participate in semistructured exit interviews. A set of ANOVAs was performed to test the main hypotheses, whereas a thematic analysis was performed to analyze the qualitative data.
The results showed a significant increase in hand hygiene over time across all conditions. There was no interaction effect between time and intervention condition. Similarly, no between-group differences in engagement, usability, and satisfaction emerged. Seven themes (eg, “variety and timeliness of the task load” and “social interaction”) were found in the thematic analysis.
The effectiveness of
ClinicalTrials.gov NCT04830761; https://clinicaltrials.gov/ct2/show/NCT04830761
RR2-10.1136/bmjopen-2021-055971
Hand hygiene is an effective behavior for decreasing the transmission of respiratory illnesses [
The need for research on effective behavior change interventions for promoting hand hygiene during a pandemic was further confirmed by the fluctuation in hand hygiene over the course of the COVID-19 pandemic. At first, results indicated high adherence among the public. During the first wave of the pandemic (ie, between March and May 2020), studies suggested that (1) hand hygiene was one of the most adopted protective behaviors against the spread of COVID-19 [
During an ongoing pandemic in which social contact should be limited, digital interventions have the advantage that no personal contact is required for their use; moreover, they can be personalized and potentially be integrated into the daily lives of an unlimited number of people. Interventions based on smartphone apps can deliver behavior change techniques [
To address these research gaps, we devised a Multiphase Optimization Strategy (MOST) [
This study focused on the optimization phase of Soapp, which aimed to identify the most effective combination and sequence of the developed intervention modules to be included in the subsequent evaluation phase. As described in the study protocol [
Hypothesis (H) 1; H1: The intervention groups show a significant increase in correct hand hygiene at key times after 4 weeks (T3) of intervention compared with baseline (T1).
H2: The intervention groups significantly differ in the effects of the intervention on correct hand hygiene behavior at key times (T1-T3).
In case of significant between-group differences in hand hygiene at key times, post hoc tests were performed to determine the most effective condition. In addition, we investigated the unique contribution of each module by testing the following hypotheses that were not preregistered:
H3: The intervention groups with the
H4: The intervention groups with the
H5: The intervention groups with the
The second optimization criterion leveraged a combination of quantitative and qualitative methods to explore the participants’ engagement and satisfaction with the app as well as its usability. This criterion was tested using the following hypotheses:
The intervention groups significantly differ in the engagement with (H6), usability of (H7), and satisfaction (H8) with the intervention (T3).
In addition, semistructured interviews were conducted to explore which aspects and features of Soapp were perceived as more usable and more important for supporting engagement and satisfactory experiences after 34 days of using the app.
As secondary outcomes, we had preregistered a series of hypotheses regarding the psychological mechanisms and health impact of the intervention that did not inform the optimization decision. We have reported these in
The study design for the optimization phase was a double-blind parallel randomized trial. The participants were randomized to 1 of 9 intervention groups in a 1:1:1:1:1:1:1:1:1 ratio and completed 2 consecutive intervention modules, as shown in
Intervention optimization. Red diaries represent baseline (T1) and follow-up (T3) assessments for the primary outcome (hand hygiene). R: randomization.
This trial is registered at ClinicalTrials.gov (NCT04830761), and the reporting is in line with the CONSORT (Consolidated Standards of Reporting Trials) guidelines [
The target population for the Soapp app was German-speaking adults from the Swiss population who were interested in using an app to improve hand hygiene behavior. The inclusion criteria were as follows: (1) being aged at least 18 years, (2) owning a smartphone with mobile access to the internet, (3) being proficient in the German language, and (4) having signed an electronic informed consent form to participate in the study. As presented in the study protocol [
A subsample (n=9) participated in qualitative interviews. The recruitment was based on the participants’ willingness to participate in semistructured interviews, as assessed at the end of the last survey (T3). The aim of the qualitative interview was to recruit an even number of participants per intervention module according to hand hygiene adherence: low adherence, medium adherence, and high adherence to hand hygiene. The participants in the ≤33rd percentile were assigned to the low adherence group (3/9, 33%), participants in between the 34th and 66th percentiles were assigned to the medium adherence group (3/9, 33%), and participants in the ≥67th percentile were assigned to the high adherence group (3/9, 33%). The sample size (n=9) was smaller than that reported in the study protocol (n=15) because the recruitment was stopped when theoretical saturation was achieved (ie, no new themes emerged) [
The primary outcome of the study (ie, the first optimization criterion), the frequency of correct hand hygiene at key times at T3, was assessed via ecological momentary assessment with the support of an electronic diary embedded in Soapp. On diary days (days 2, 8, 16, 24, and 32), the participants were prompted 5 times per day to indicate whether each of the 13 key times to perform hand hygiene defined by the Swiss Federal Office of Public Health had occurred (eg, upon arriving home and after using the toilet;
Engagement, usability, and satisfaction (ie, the second optimization criterion) were measured at T3. User engagement was assessed using the digital behavior change interventions (DBCI) Engagement Scale [
Other variables assessed during the study but not relevant to the current report are described in the clinical trial registration, and the corresponding results are presented in
The participants were recruited via social media (eg, Facebook [Meta Platforms, Inc] and Instagram [Meta Platforms, Inc]), mailing lists, and leaflets with the help of a market research company and with the aim of recruiting a diverse range of people from the German-speaking adult Swiss general population in terms of gender, age, and socioeconomic status. Interested people who clicked on the campaign link were led to a landing page with the study information. Those who chose to continue were redirected to the study page on REDCap (Research Electronic Data Capture; Vanderbilt University) [
The optimization trial lasted 34 days and included two 2-week intervention modules (
The participants who were given the option and volunteered to participate in the qualitative study were interviewed via telephone by a study team member (CB). This 30-minute interview was recorded and included questions about the usability of the app and the overall experience with the intervention modules in terms of satisfaction and engagement (
In the optimization phase, each arm of the parallel randomized trial was characterized by a unique combination and sequence of 2 of the 3 intervention modules: motivation, habit, and social norms (
Contents of the modules.
Module, TDFa domain, and behavioral predictor | Behavior change technique | ||
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Intention |
1.1 Goal setting (behavior) |
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Skills |
4.1 Instruction on how to perform behavior |
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Knowledge |
5.1 Information about health consequences |
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Resources and material resources (availability and management) |
1.4 Action planning |
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Intention |
1.1 Goal setting (behavior) |
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Risk perception |
5.1 Information about health consequences |
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Attitude |
5.2 Salience of consequences |
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Outcome expectancies |
9.2 Pros and cons |
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Intention |
5.2 Salience of consequences |
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Self-efficacy |
1.2 Problem solving 15.1 Verbal persuasion about capabilities 15.3 Focus on past success |
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Intention |
10.9 Self-reward |
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Knowledge |
4.2 Information about antecedents |
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Action control |
2.3 Self-monitoring of behavior |
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Action planning |
1.4 Action planning 7.1 Prompts and cues |
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Habit strength |
8.1 Behavioral practice and rehearsal 8.3 Habit formation |
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Habit strength |
7.1 Prompts and cues (physical cue) |
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Descriptive norm |
2.1 Monitoring of behavior by others without feedback 2.2 Feedback on behavior 6.2 Social comparison 10.4 Social reward 10.5 Social incentive |
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Injunctive norm |
5.1 Information about health consequences 6.3 Information about others’ approval 9.1 Credible source 10.5 Social incentive 12.1 Restructuring the physical environment |
aTDF: Theoretical Domain Framework.
The modules were delivered to the participants via their personal smartphones through the study app Soapp. They were comparable in terms of user time and extent of content, and each module took 2 weeks to be completed. In addition, each intervention condition included a basic module that provided information on hand hygiene to all the participants. During the configuration process, the Soapp app underwent various iterative testing cycles to refine the content of each module and improve usability. The Soapp app contained all the information required to use it, and there was no direct contact with the study team.
Missing data were handled according to the intention-to-treat (ITT) principle [
To test the hypotheses related to the first optimization criterion, a repeated-measures ANOVA with a within-between interaction was used. The
Summary of hypothesis tests.
Ha | Preregistered | Dependent variable | Within factor (time) | Between factor | |
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H1 | Yes | Hand hygiene | T1-T3 | N/Ab |
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H2 | Yes | Hand hygiene | T1-T3 | Intervention groups |
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H3 | No | Hand hygiene | T1-T3 | Habit exposure |
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H4 | No | Hand hygiene | T1-T3 | Motivation exposure |
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H5 | No | Hand hygiene | T1-T3 | Social exposure |
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H6 | No | Engagement | N/A | Intervention groups |
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H7 | No | Usability | N/A | Intervention groups |
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H8 | No | Satisfaction | N/A | Intervention groups |
aH: hypothesis.
bN/A: not applicable.
The packages
Postintervention user engagement, usability, and satisfaction were explored using semistructured interviews. The interviews were transcribed verbatim, and the transcripts were analyzed using thematic analysis [
The recruitment for the optimization trial began on March 27, 2021, and ended on July 28, 2021. T3 data were collected between April 29 and August 25, 2021. Because of both trial and project timelines, we stopped the trial 6 months after the start of the study, with the recruitment lasting for 5 months. Overall, 232 participants were recruited and randomized into 1 of the 9 intervention conditions. Among these 232 participants, 14 (6%) participants did not fill out any of the 5 hand hygiene diaries, whereas 27 (11.6%) participants did not complete the first diary at T1. Another (1/232, 0.4%) participant completed the first diary but did not encounter any of the key situations to perform hand hygiene during that day. Therefore, these (42/232, 18.1%) participants were excluded from the analysis because the main outcome (ie, hand hygiene) at T1 was missing. Of the 232 participants who were randomized, 190 (81.9%) filled out the hand hygiene diary at T1, and 118 (62.1%; 50.9% of the randomized participants) of them filled out the hand hygiene diary at T3.
Participant recruitment flow. The intervention groups are specified as follows: H-H: habit-habit; H-M: habit-motivation; H-S: habit-social; M-H: motivation-habit; M-M: motivation-motivation; M-S: motivation-social; S-H: social-habit; S-M: social-motivation; and S-S: social-social. T1: baseline: T3: follow-up.
Sociodemographic and hand hygiene behaviors at T1 are reported in
Dropout analysis was performed to investigate T1 differences between the participants who completed the study and those who dropped out at any point during the intervention. We analyzed all the 232 randomized participants, and those who did not complete the last panel assessment at T3 were categorized as dropouts (n=83, 36%). The results suggested no T1 differences between dropouts and retainers with respect to age (
The main effects of time and the interaction between time and the intervention groups are reported in
Main effects and interactions among modules on hand hygiene behavior at key times (N=232).
Ha, outcome, and factor | Participants, n (%) | Parametric ANOVA | ||||||||
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Partial eta–squaredb (95% CI) | ||||||||
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190 (81.9) |
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Groupc |
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0.33 (8) | .95 | 0.01 (0.00-1.00) | ||||
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Time (T1-T3) |
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Time × group |
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1.19 (8) | .31 | 0.05 (0.00-1.00) | ||||
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190 (81.9) |
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Habit |
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1.25 (1) | .27 | 0.01 (0.00-1.00) | ||||
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Time (T1-T3) |
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Time × habit |
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1.07 (1) | .30 | 0.01 (0.00-1.00) | ||||
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190 (81.9) |
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Motivation |
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0.00 (1) | .99 | 0.00 (0.00-1.00) | ||||
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Time (T1-T3) |
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Time × motivation |
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0.94 (1) | .33 | 0.00 (0.00-1.00) | ||||
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190 (81.9) |
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Social |
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0.75 (1) | .39 | 0.00 (0.00-1.00) | ||||
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Time (T1-T3) |
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Time × social |
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0.41 (1) | .52 | 0.00 (0.00-1.00) | ||||
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148 (63.8) |
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Group (T3) |
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148 (63.8) |
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Group (T3) |
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148 (63.8) |
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Group (T3) |
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1.46 (8) | .18 | 0.11 (0.00-1.00) |
aH: hypothesis.
bPartial eta–squared corresponds to the proportion of variance explained by a variable that is not explained by other variables.
cGroup: intervention group.
dItalicized values indicate significance.
The effects of the intervention group on engagement, usability, and satisfaction are shown in
Across 9 interviews, 7 themes emerged in relation to the research question (refer to
The first theme that emerged concerned the user experience with the general aesthetics and functionalities of the app. Overall, satisfaction with the intuitive and simple handling of the app was high. The participants considered the usability to be pleasant. Regarding the app aesthetics, some participants were very satisfied with the simplicity of the layout; however, the majority would have preferred more visual structures:
What I liked in particular? Actually, how things were presented. Just the simplicity—all in all it was very simple.
Another point on which most participants agreed was that certain features of the app showed technical flaws, which negatively affected their motivation:
So, when this annoying technical problem occurred—if you were to draw a curve now, it [my motivation] went up quite steadily at the beginning, and then slowly decreased due to this technical problem, and then when it was resolved it [my motivation] got back up again.
Throughout the interviews, the participants regularly highlighted the importance of receiving guidance within the app. Specifically, they mentioned the importance of clarity and meaning regarding the tasks that the app asked them to do:
I also thought it was nice that you kind of knew in the morning “ah today is a day with a big survey,” so that you could already plan “okay, today there are maybe a little bit more push messages coming in and I have to pay a little bit more attention.”
The importance of guidance was also manifested as the need for a better overview of the participants’ journey during the study. For instance, some participants would have liked more background information about the study to better understand the timeline or the reasons behind receiving certain tasks:
And otherwise maybe somehow a little bit more background information about what—why am I being asked these questions, so that I can see even more behind this algorithm and behind this concept and then it would become clearer to me why the same questions keep coming. So, a little bit, so even more background knowledge.
Although guidance was acknowledged as important, too much direction was also perceived as overwhelming, for example, very frequent push notifications:
Was that now at 10 o’clock, at 12 o’clock or at 2 o’clock, I do not remember any more in which intervals the push messages came in. At the end, I no longer knew at what point I had I received the last push notification—there, I lost overview.
Variety in daily engagement with the content of the app emerged as a central topic in the interviews. A few participants were satisfied with the degree of variety in the task load and the timing of the content offered by the intervention. However, most participants wished for substantially more variety in the task load and timing, particularly toward the end of the intervention:
Sometimes, it was just quiet, nothing happened. But later, once again it came “today something is happening,” yes, I liked that.
Towards the end, when there were fewer and fewer exercises, I found it almost a bit boring.
In most interviews, the participants mentioned their initial reasons for participating in the study. One of the most frequently reported motives was curiosity and an interest in learning something new:
I thought, “yeah, sure, I can wash my hands. But do I know everything when they do a study? I could still learn something at the end, I’m not omniscient.” And that's actually what mainly motivated me, this openness, I'm curious to see what else there is to learn.
The participants also elaborated on why they kept using the app. One of the cited motives was the perceived obligation to complete the study:
Well, it [my motivation] certainly did not increase, it was more a matter of persevering—in the sense of whoever says A must also say B. It was said that you could drop out at any time, but still.
A further theme was represented by the increase in participants’ hand hygiene awareness owing to the use of the app. The change in awareness seemed to have been generated by the fact that participants paid more attention to the self-monitoring of the target behavior:
That was simply my observation of my reaction then—you observe yourself during these four weeks incredibly—I do not know if you have also heard this from other people, but you start watching yourself.
The change in awareness generated a positive loop that led to an increase in the frequency of hand hygiene behavior together with a shift in perception of the issue of hand hygiene and its implications:
I certainly washed my hands more than I had before. And therefore, I have the feeling that I have certainly benefitted from it [the intervention].
The theme of social interaction came up several times during most interviews. Two subthemes define this main theme according to the different social aspects that came to light during the interviews: personal communication and connectedness and social comparison.
Some participants particularly appreciated that the app communicated with them in a personal manner. This led to a feeling of authenticity; therefore, these participants no longer had the impression of interacting with a machine when using the app:
You can say that there is someone behind it. I never felt alone, it was not a one-way kind of communication. I always knew that behind these tasks was indeed a computer, but I still felt connected in a way.
By contrast, other participants would have preferred an even more human-centered mode of delivery of the app content, for example, receiving direct motivational support from other humans:
Maybe, despite everything, a video or something like that—or actually, as is often the case nowadays: a small video with other participants who motivate you. Because reading statistics and news is something else than when someone speaks directly to you.
Some participants described having developed a feeling of connectedness with other app users over time. This led to a sense of community, which made them feel supported:
And then I think I had to answer this question three times. And at the end, I think that was at the final question, I thought “yes, I think it is cool that they are taking part, I do not know them, but I think it is cool that they are taking part, and I feel connected to them.”
The participants who were exposed to the social module shared different opinions regarding the opportunity to compare their behavior with that of other participants, which was a feature of the social module only. Indeed, although some participants expressed avoidance of social comparison and fatigue with the competition it created for them, others were pleased about the comparison with other users:
For me, personally, it was too much with the community and otherwise, because others cannot motivate me. Whether someone somehow achieved 100% or 50%, that is actually relatively indifferent to me. And it does not encourage me to become more or less active or whatever.
An issue raised by almost every participant was the lack of personal relevance that the list of key moments for hand hygiene entailed. Being regularly asked about key situations that never occurred for them (eg, not having children or not wearing contact lenses) led to a decrease in motivation to fill out the hand hygiene diaries:
Things are asked again and again, which do not concern you at all. This leads to a decrease in motivation. Now, I have to spend five minutes filling out the form again, even though it does not apply.
The desire to personalize the app also came up in relation to other intervention content, such as the number of push notifications:
But maybe in the beginning you should be able to specify “I would rather have a little more [push notifications] or a little less.” But what I have received, however, has been right for me.
As part of a MOST to develop and test a smartphone-based hand hygiene intervention during the COVID-19 pandemic, this intervention optimization parallel randomized trial aimed to identify the best combination of intervention modules to be included in the subsequent evaluation phase of Soapp. The results from the main analyses confirmed that the participants who participated in the study increased the frequency of correct hand hygiene at key times over time (H1). However, the intervention groups did not differ in their effects on correct hand hygiene at key times (H2). Similarly, the exposure to specific modules was not associated with increased hand hygiene over time (H3, H4, and H5). Taken together, the findings related to the first optimization criterion suggested a promising increase in hand hygiene during the intervention period but did not provide scientific evidence to support the preference of one version of Soapp or a specific module over the others. Similarly, the quantitative results from the second optimization criterion (H6, H7, and H8) did not show any differences in engagement, usability, and satisfaction among the 9 intervention modules at T3.
By contrast, the qualitative results revealed what characteristics and features of Soapp the participants perceived as supportive or, conversely, detrimental in terms of engagement, usability, and satisfaction. The finding that the aesthetics and design of the app are important for participants to better enjoy their interaction with Soapp is in line with a previous study on health-related behavior change [
Owing to the null findings of the first optimization criterion, we were not able to identify the best intervention group based on the quantitative analysis of the primary outcome. Similarly, no between-group differences emerged in relation to the second optimization criterion (ie, engagement, usability, and satisfaction). Therefore, we relied on the results of the thematic analysis to derive implications for the evaluation phase of Soapp. The resulting intervention design decisions based on this optimization study are summarized in
Intervention design recommendations for the evaluation phase of Soapp.
Recommendation | Rationale |
The social module is excluded from the next evaluation phase. | Habit and motivation modules seem best suited to leverage some of the themes that emerged during the thematic analysis. For instance, themes such as change in awareness and guidance can be better supported by the app features that characterize these modules (ie, action planning tasks, self-monitoring, opportunity to schedule custom reminder, and video on health implication). In addition, the social module might be detrimental for engagement, as it embeds social comparison features, which were perceived as counterproductive by some users. |
A parallel delivery of modules is preferrable over a sequential one. | The specific sequence of intervention modules (ie, habit-motivation vs motivation-habit) was not associated with differences in hand hygiene. Therefore, according to the participants’ needs identified as part of the theme “variety and timeliness of the task load,” a parallel delivery of the selected intervention modules is preferable. |
Define a more even distribution of the intervention content and notifications over the course of the study. | A parallel delivery of the modules would allow to distribute each module’s content and tasks over 32 days instead of 16 days, as done during the optimization phase. Therefore, there is more flexibility to define the timeline of the intervention with the aim of balancing the daily task load and, ultimately, guaranteeing a more suited dose of content over the course of the intervention. |
This study is not without limitations. A main weakness is the sample size achieved for testing the main hypotheses. Indeed, an a posteriori achieved power of 0.44 (n=190, 81.9%; α=.05; partial η2=0.01) suggests that the probability of detecting a true effect of the intervention groups was lower than the recommended standard (ie, 0.80). Different factors contributed to the collection of data from a limited sample of 190 participants. First, we stopped recruitment 5 months after the start of the study, although the target sample size was not achieved. As specified in the study protocol, the criterion of discontinuing the enrollment of participants after 5 months was based on the constraints of the project timeline [
A further limitation that affected the analysis of the primary outcome was attrition. Of the 190 participants who filled out the T1 diary, 118 (62.1%) completed the diary at T3, leading to 38% and 49% attrition compared with the T1 and randomization figures, respectively. The attrition rate was higher than the estimated rate (ie, 20%). To account for potential differences between dropouts and retainers, we conducted a dropout analysis to investigate whether they differed in regard to key variables such as age, sex, hand hygiene, and intention to increase hand hygiene behavior. Because no significant differences emerged, we considered the participants who completed the study to be representative of our target population (ie, adults interested in using an app to improve hand hygiene behavior). A possible explanation for attrition could be the possibility that the longitudinal study design with 5 diary days and further quasidaily tasks might have generated an interaction fatigue. In addition, the pandemic trajectory during the enrollment period flattened in Switzerland, which may have made hand hygiene less of a priority for potential participants. To overcome this issue and in line with the ITT approach, we used the last observation carried forward method to replace the missing observations in the T3 diary with the latest available diary assessment. However, it should be noted that this method is based on the assumption that behavior is stable and, therefore, might have introduced bias.
Furthermore, the recruited sample was characterized by a high prevalence of women (ie, 139/190, 73.2%). This imbalance was in line with previous research on hand hygiene during the COVID-19 pandemic [
Finally, the self-reported measurement of hand hygiene may be biased. The use of an electronic diary to measure hand hygiene behavior at key times should have had limited retrospective bias. However, social desirability cannot be disregarded. In addition, thematic analysis indicated that the diary may have worked as an unintentional behavior change technique (ie, self-monitoring).
This study described the optimization phase of Soapp, a smartphone app for promoting hand hygiene in the context of the COVID-19 pandemic. By leveraging digital technologies and MOST, we addressed the call raised by public health experts for developing evidence-based behavior change interventions that are designed and optimized to be effective in a pandemic context [
Hand hygiene items and secondary hypothesis testing.
CONSORT (Consolidated Standards of Reporting Trials) checklist.
Qualitative interview guide.
Supplement to quantitative results.
Summary and quotes from the thematic analysis.
Consolidated Standards of Reporting Trials
digital behavior change interventions
hypothesis
intention-to-treat
Multiphase Optimization Strategy
Research Electronic Data Capture
baseline
follow-up
Fragebogen zur Messung der Patientenzufriedenheit
The authors thank Melanie Bamert, Dominik Zeilstra, Lisa Maria Summermatter, and gfs.bern for study support and their help with app development. Moreover, they thank the Technology Platform of the Faculty of Human Sciences at the University of Bern, especially Stefan Kodzhabashev, for facilitating app development. This study was funded by Ursula-Wirz Stiftung.
DB was involved in formal analysis and the writing of the original draft. MAA contributed to conceptualization and methodology. MDRC and CF contributed to qualitative methodology. GGR contributed to resource accumulation and data curation. CB contributed to resource accumulation, data curation, and qualitative methodology. CR was involved in formal qualitative analysis and the writing of the qualitative report. JI contributed to funding acquisition, conceptualization, methodology, formal qualitative analysis, and supervision. All the authors were involved in discussion and in writing, reviewing, and editing the manuscript.
None declared.