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.
Behavioral: Self-focused acts
Completion of daily acts for personal enjoyment.
Behavioral: Prosocial acts
Completion of daily acts for the benefit of others.
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.
Online, Amazon's Mechanical Turk
Toronto, Ontario, Canada
Andrew Miles, PhD, Principal Investigator
University of Toronto