Prosocial Behavior Can Safeguard Mental Health and Foster Emotional Well-being During the COVID-19 Pandemic

Prosocial Behavior Can Safeguard Mental Health and Foster Emotional Well-being During the COVID-19 Pandemic: A Randomized Clinical Trial

The COVID-19 pandemic and the accompanying lockdown measures have made mental health a pressing public health concern. Acts that focus on benefiting others-known as prosocial behaviors-offer one promising intervention that is both flexible and low cost. However, neither the range of emotional states prosocial acts impact nor the size of those effects is currently clear, both of which directly influence its attractiveness as a treatment option. Using a large online sample from Canada and the United States, the investigators will examine the effect of a three-week prosocial intervention on two indicators of emotional well-being (happiness and the belief that one's life is valuable) and mental health (anxiety and depression). Respondents will be randomly assigned to perform prosocial, self-focused, or neutral behaviors each week. Two weeks after the intervention, a final survey will assess whether the intervention has a lasting effect on mental health and emotional well-being. The results will illuminate whether prosocial interventions are a viable approach to addressing mental health needs during the current COVID-19 pandemic, as well for those who face emotional challenges during normal times.

This study is intended to be published as a registered report. The details of the study design are likely to change somewhat during the review process. However, below is the current plan:

The investigators will examine the effects of prosocial behavior using a 3-week experimental intervention, followed by a follow-up assessment at 5 weeks. At baseline the research team will measure participants' emotional well-being and mental health. Emotional well-being will be assessed using happiness and feeling that one's life is valuable, which is a facet of sense of meaning in life. Mental health will be measured as depression and anxiety. At the end of the baseline survey the researchers will randomly assign participants to one of three experimental conditions (between-subjects design). In each condition, respondents will be asked to perform certain types of behaviors for the first three days of each week, as detailed later in this protocol.

Respondents will be contacted for the first three days each week and asked to report what they did. At the end of weeks 1, 2, and 3 they will complete a longer survey that repeats the same measures of emotional well-being and mental health used at baseline. At this point the intervention will be complete. The investigators will recontact respondent two weeks later (at the end of week 5) to assess whether the intervention has a lasting effect on mental health and emotional well-being. This final survey will also include a measure of whether or not respondents continued their assigned behaviors following the end of the intervention. This measure might be useful for explaining any lasting effects in exploratory analyses.

The expected effect size is d = 0.19. The research team will assess experimental effects using multiple linear regression. The models will include indicator variables for experimental conditions as well as controls for baseline levels of happiness, valued life, depression, and anxiety. These baseline measures should be unrelated to experimental conditions (which will be randomly assigned) so including them will increase the efficiency of estimates. Under the assumption that these variables will account for at least 50% of the variance in the outcomes, the sample size needed to detect an effect of size d = 0.19 with 95% power is N = 357 or approximately 360 per condition. The expected attrition rate is 30% after baseline which means that the investigators will sample 360/0.7 = 514 per condition.

The research team will post the baseline survey in two batches. The first batch will contain half the sample (N = 771), and will be used to gauge the attrition rate (see data exclusion criteria). The sample size of the second batch will be adjusted as needed to try and capture the desired number of respondents per experimental condition. This will lower the size of the second batch if attrition rates are lower than expected or increase the size of the second batch if attrition rates are higher than expected. If a sufficient sample size has not been obtained at this point, the investigators will repeat the process until at least 350 respondents in each experimental condition are recruited. To be clear, the stopping rule for recruiting sample participants does not require estimating any of the effects of interest in the study (i.e., it does not depend on the anticipated effect size). The only factor is whether a sufficient number of respondents have been recruited for each experimental condition.

Obtaining a sufficient per-condition sample size might take several days. The researchers plan to begin sampling on a Sunday and continue sampling (if needed) on Monday. This means respondents will finish their first three days of the study on either Wednesday or Thursday. In either case, the investigators will distribute the end of week 1 survey the following Sunday, which will then put both groups of respondents on the same schedule for the remainder of the study. The researchers will try to recruit the full sample during this initial recruitment phase, as this will simplify administering the study. However, if initial sampling does not yield a sufficient sample size, the researchers will repeat the sampling procedure each week until a sufficient number of respondents is obtained. In this case, the study will be administered to different "cohorts" of respondents spaced a week apart.

Inclusion Criteria:

• Canadian and American respondents from the Amazon Mechanical Turk

Exclusion Criteria:

Respondents will be excluded from the study if any of the following apply:

1. A respondent completes the baseline study unrealistically quickly. We measure response speed using the average number seconds spent on each survey item (seconds per item, or SPI). We judge a response to be unrealistically fast if its SPI value is less than 1. SPI calculations will exclude optional items.
2. A respondent does not complete at least half of the items in the baseline survey.
3. A respondent provides off-topic, non-sensical (e.g., random or gibberish words), or non-English responses to an open-ended question in the baseline survey. The open-ended question follows a dictator game (that is not part of the pre-registered portion of the study) and asks respondents what they hoped to accomplish by acting as they did during the dictator game. The specific nature of this question will make it straightforward to detect off-topic responses. A comment must be judged as off-topic, non-sensical, or non-English by two members of the research team to be excluded.
4. A respondent does not agree to continue with the study when asked if they wish to continue taking part in the study at the end of the baseline study, or in private correspondence with the researchers.
5. A respondent completes the baseline study using an IP address from outside Canada or the United States, or that appears to originate from a VPS or other suspicious source.
6. Technical difficulties prevent a respondent from completing the baseline study.

Because obtain sufficient power to detect effects is a central aim of this study, the investigators will replace respondents who are removed for reasons 1-5 in a rolling fashion. In the case of technical failure (#6), the first approach will be to resolve the issue and administer the baseline survey to the same participant. If this is not possible, a replacement will be recruited.