Does pre-COVID impulsive behaviour predict adherence to hygiene and social distancing measures in youths following the COVID-19 pandemic onset? Evidence from a South African longitudinal study.

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Study Justification:
This study aimed to investigate the association between pre-COVID impulsivity levels and adherence to hygiene and social distancing measures in youths following the onset of the COVID-19 pandemic in a South African context. Understanding the predictors of engagement in protective behaviors is crucial for future pandemic planning, especially among vulnerable populations.
Highlights:
– The study found that higher impulsivity levels predicted lower engagement in hygiene behaviors post-COVID-19 pandemic onset in a high-risk, sub-Saharan African setting.
– Engagement in social distancing behaviors varied among participants.
– The association between impulsivity and hygiene behaviors remained significant even after controlling for demographic and COVID-related factors.
– The study highlights the importance of considering predictors of engagement in protective behaviors, particularly in the context of adversity.
Recommendations:
– Future pandemic planning should take into account the influence of impulsivity on adherence to hygiene behaviors, especially among vulnerable populations.
– Interventions targeting impulsivity and risk-taking behaviors may be beneficial in promoting adherence to hygiene measures during pandemics.
– Further research is needed to explore additional factors that may influence engagement in protective behaviors, particularly in high-risk settings.
Key Role Players:
– Researchers and scientists specializing in public health and behavioral sciences.
– Policy makers and government officials responsible for pandemic planning and response.
– Community leaders and organizations working with vulnerable populations.
– Healthcare professionals and educators involved in promoting hygiene and social distancing measures.
Cost Items for Planning Recommendations:
– Research funding for conducting further studies on predictors of engagement in protective behaviors.
– Resources for developing and implementing interventions targeting impulsivity and risk-taking behaviors.
– Training and capacity-building programs for healthcare professionals and educators.
– Communication and awareness campaigns to promote hygiene and social distancing measures.
– Monitoring and evaluation systems to assess the effectiveness of interventions and measure adherence to behaviors.
Please note that the provided cost items are general suggestions and may vary depending on the specific context and resources available.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides a clear description of the study design, data collection methods, and statistical analyses. However, the evidence could be strengthened by providing more information on the sample size, statistical significance of the findings, and potential limitations of the study. To improve the evidence, the authors could consider including these additional details in the abstract.

Background: Engagement in protective behaviours relating to the COVID-19 pandemic has been proposed to be key to infection control. This is particularly the case for youths as key drivers of infections. A range of factors influencing adherence have been identified, including impulsivity and risk taking. We assessed the association between pre-COVID impulsivity levels and engagement in preventative measures during the COVID-19 pandemic in a longitudinal South African sample, in order to inform future pandemic planning. Methods: Data were collected from N = 214 youths (mean age at baseline: M = 17.81 (SD =.71), 55.6% female) living in a South African peri-urban settlement characterised by high poverty and deprivation. Baseline assessments were taken in 2018/19 and the COVID follow-up was conducted in June–October 2020 via remote data collection. Impulsivity was assessed using the Balloon Analogue Task (BART), while hygiene and social distancing behaviours were captured through self-report. Stepwise hierarchical regression analyses were performed to estimate effects of impulsivity on measure adherence. Results: Self-rated engagement in hygiene behaviours was high (67.1–86.1% “most of the time”, except for “coughing/sneezing into one’s elbow” at 33.3%), while engagement in social distancing behaviours varied (22.4–57.8% “most of the time”). Higher impulsivity predicted lower levels of hygiene (β =.14, p =.041) but not social distancing behaviours (β = −.02, p =.82). This association was retained when controlling for a range of demographic and COVID-related factors (β =.14, p =.047) and was slightly reduced when including the effects of a life-skills interventions on hygiene behaviour (β = −.13, p =.073). Conclusions: Our data indicate that impulsivity may predict adolescent engagement in hygiene behaviours post COVID-19 pandemic onset in a high risk, sub-Saharan African setting, albeit with a small effect size. For future pandemics, it is important to understand predictors of engagement, particularly in the context of adversity, where adherence may be challenging. Limitations include a small sample size and potential measure shortcomings.

The sample was drawn from a longitudinal intervention study conducted in peri-urban Khayelitsha, South Africa, which followed children and their families from before birth until current age (19–21 years; see Fig. 1 for a CONSORT flowchart of assessments). From the antenatal period until 6 months after birth, expectant mothers received either a parenting intervention (‘Thula Sana’; n = 220) aimed at improving parenting skills and attachment, or maternal services as usual (control group, n = 229). All mothers in the community who were eligible for study participation were invited, and group assignment was randomized. Families were followed up several times over the first 18 months of the child’s life [26] and again at 13 years of child age [27]. No effects of the early intervention on adolescent outcomes were identified [27] and we subsequently do not control for receipt of this intervention in the current study. The youths then underwent a second intervention (‘Zifune’; for details, see below), aimed at teaching life skills to improve pro-sociality and reduce violence behaviours, at ages 16–19 years (n = 319; re-randomized based on early intervention group allocation) (Skeen S, Du Toit S, Marlow M, Stewart J, Rabie S, Melendez-Torrez GJ, et al: Zifune: Does a second wave intervention delivered to former recipients of an early mother-infant attachment intervention reduce interpersonal violence during adolescence? A re-randomized controlled trial, in preparation). Data collection took place in 2018/2019, at three time-points: pre-intervention, directly post-interventions (n = 314) and at a 3-month follow-up (n = 307). At the post-intervention assessment, participants completed several behavioural tasks to investigate whether the intervention had led to any changes in risk taking and moral behaviours (n = 280). CONSORT Flow Diagram for Cohort Studies The Zifune life skills intervention was developed for use with youths living in high adversity contexts in low- and middle-income countries (LMIC) (Skeen S, Du Toit S, Marlow M, Stewart J, Rabie S, Melendez-Torrez GJ, et al: Zifune: Does a second wave intervention delivered to former recipients of an early mother-infant attachment intervention reduce interpersonal violence during adolescence? A re-randomized controlled trial, in preparation). An adolescent advisory board provided feedback to ensure applicability and acceptability of its contents. The intervention utilises a collaborative approach, incorporates principles of cognitive behaviour therapy, and employs creative and fun methods to allow youths to reflect on their relationships and behaviours and to devise future plans. Eight group-based sessions for groups of approximately 20 youths each were provided by trained facilitators from the local community. Sessions covered six main themes: vision for the future, time management, financial planning, mindfulness, risk-taking behaviour and interpersonal violence, with sessions about long-term planning and risk-taking behaviours in particular potentially affecting impulsivity levels. An intervention facilitator remained in regular contact with and provided support to the youths throughout the course of the study via phone calls. Following the outbreak of the COVID-19 pandemic, South Africa went into a strict lockdown in March 2020. Brief telephonic interviews were conducted with participants (n = 237) in June to October 2020 through remote-working data collectors. During this time, South Africa’s first large case wave took place (July–August 2020), followed by a strong decline in cases. Participants were assessed on a range of COVID-related variables, including social distancing and hygiene behaviours, household food security, mental health, and schooling outcomes. We utilize data from those who took part in the behavioural tasks at the post-intervention assessment of the Zifune study and completed the COVID-related questionnaire after the pandemic outbreak (n = 214). All participants provided written consent at each wave of the data collection. Assessments were conducted in the participants’ language of choice, predominantly isiXhosa. All data were collected by trained and supervised data collectors, with at least a high school diploma and with prior experience in working with vulnerable populations. For the current phase of the study, ethical approval was obtained from the Health Research Ethics Committee (HREC) from Stellenbosch University (Ref: N17/10/094). Information on the gender, age, level of education (utilised in the form of a “correct grade for age” variable), housing (formal vs informal housing); number of household members the individual was living with during the COVID-19 pandemic, HIV status, and household receipt of any form of government-provided cash grants was collected. The BART [28] is a naturalistic computer task measuring impulsive and risk-taking behaviours. Participants are presented with a balloon, which they can enlarge in a step-wise fashion by pressing a button. Each pump increases the reward pay-off that the participant receives, but also the chance of the balloon popping, which leads to no rewards for the trial. Participants have the choice to step away after each button press, and collect the already accrued rewards for the trial, or to keep pumping. In the current study, all participants were asked to complete 30 trials. They were told that one trial would be chosen at random in the end, for which they would receive the earned monetary reward. To even out expectations, all participants observed 12 balloons being inflated to their bursting point before commencing the task. The bursting point was set to be identical in each trial between participants. The overall number of pumps was used as a predictor of interest, with a higher number of pumps reflecting higher risk taking. The extent to which participants engaged in each of four hygiene behaviours (hand washing, hand sanitising, coughing/sneezing into one’s elbow, and wearing a face mask) during the past week was measured on a scale from 0 “never” to 3 “most of the time” for each item (see Additional file 1: Appendix 1 for full item list and rating scale). A total score (0–12) was calculated. An exploratory factor analysis revealed that the items did not load well onto a single underlying factor, potentially due to participants picking and choosing certain behaviours or adhering less stringently to measures as the pandemic situation in South Africa relaxed towards September/October 2020. As a result, we decided to investigate the total score, reflecting the overall extent of hygiene behaviours each participant engaged in, but also analysed the four behaviours separately to see whether any effects found were driven by high scores on particular items. The extent to which participants engaged in five social distancing practices during the past week was assessed: keeping a 1–2 m distance, and avoiding public transport, going to the shops/pharmacy, public spaces and going for a walk in the neighbourhood. Items were rated from 0 “never” to 3 “most of the time” and summed up into a total score (0–15). Exploratory factor analysis suggested that the latter three items loaded onto a potential “avoidance of public outings” factor, though individual item loadings were small. Therefore, we chose to investigate the total score, indexing the extent of overall social distancing behaviours, and to additionally explore single-item effects. We added age and sex to the analyses, since risk behaviours in the BART have been shown to be influenced by both factors. We furthermore controlled for education (being in the correct grade for age) and timing of the assessment, since the COVID situation changed substantially in South Africa throughout our data collection, from the first case wave in June/July 2020 to level 1 restrictions in September 2020. In terms of COVID-related factors that could have influenced participants’ abilities to engage in hygiene and social distancing behaviours, we adjusted our analyses for household food security as a measure of deprivation (Household Food Insecurity Access Scale (HFIAS, [29]), and the number of individuals living in the participant’s household, which could have desensitized participants to being around large groups of people, or heightened worries and subsequent measure engagement, especially in multi-generational households. Finally, we controlled for receipt of the life skill intervention at ages 16–19 years, as it was found to influence risk taking in males particularly (Mikus N, Skeen, S, Stewart J, Marlow M, DuToit S, Rabie S, Mendelez Torres GJ, et al: Psychosocial intervention improved self-control in adolescents, in preparation). Analyses were conducted using StataSE 16 and R 4.1.1 In a first step, we investigated descriptive characteristics of the sample and compared it to participants who had completed the BART impulsivity measure and were not included in the COVID follow-up on relevant demographic factors, using t-tests and χ2 tests as appropriate. We then performed Pearson’s correlation analyses between the key variables. Finally, based on findings from the correlation analyses, a hierarchical linear regression analysis was performed, with hygiene behaviours as the key outcome. In the first step, impulsivity was added as a predictor, with higher pumps on the BART indexing higher impulsivity/ risk taking. Secondly, the demographic factors of age, sex and correct class for age were included. In a third step, COVID-related factors (food security, number of people living in the household, time to level 1 restrictions) were added to the model. In a last step, receipt of the life skills intervention was added, to see whether any effects found may be explained by exposure to its contents. Finally, since the intervention was found to affect BART-measured impulsivity in a previous study (Mikus N, Skeen, S, Stewart J, Marlow M, DuToit S, Rabie S, Mendelez Torres GJ, et al: Psychosocial intervention improved self-control in adolescents, in preparation) and showed close to significant predictions of hygiene behaviours (β = .09, p = .190) in the current study, we conducted secondary exploratory causal mediation analyses, using the “mediation” package in R 4.1.1 [30]. The aim was to investigate whether the life skills intervention may be able to buffer potential associations between higher impulsivity and lower protective behaviour engagement. For this, we explored whether any indirect effects of exposure to the life skills intervention on hygiene behaviours through impulsivity would be found. However, we acknowledge limited power due to a small sample size.

Based on the provided information, it is not clear what specific innovations or recommendations are being sought to improve access to maternal health. The information provided focuses on a study conducted in South Africa that examines the association between pre-COVID impulsivity levels and engagement in preventative measures during the COVID-19 pandemic. It also mentions a longitudinal intervention study conducted in peri-urban Khayelitsha, South Africa, which followed children and their families from before birth until their current age.

To provide recommendations for improving access to maternal health, it would be helpful to have more specific information about the challenges or areas of improvement that need to be addressed.
AI Innovations Description
Based on the provided information, it appears that the study focused on assessing the association between pre-COVID impulsivity levels and engagement in preventative measures during the COVID-19 pandemic, specifically in a South African sample of youths. The study aimed to inform future pandemic planning by understanding the predictors of engagement in protective behaviors, particularly in high-risk, sub-Saharan African settings.

The study collected data from 214 youths living in a peri-urban settlement characterized by high poverty and deprivation. Impulsivity was assessed using the Balloon Analogue Task (BART), while hygiene and social distancing behaviors were captured through self-report. The results showed that higher impulsivity predicted lower levels of hygiene behaviors but did not significantly predict social distancing behaviors. The association between impulsivity and hygiene behaviors remained even after controlling for demographic and COVID-related factors. However, the effect size was small.

The study had some limitations, including a small sample size and potential measure shortcomings. It also mentioned a previous intervention study called “Zifune,” which aimed to teach life skills to improve pro-sociality and reduce violence behaviors in youths living in high adversity contexts in low- and middle-income countries. The Zifune intervention was not directly related to the current study on impulsivity and engagement in protective behaviors during the COVID-19 pandemic.

In conclusion, the study suggests that impulsivity may predict adolescent engagement in hygiene behaviors following the onset of the COVID-19 pandemic in a high-risk, sub-Saharan African setting. Understanding predictors of engagement in protective behaviors, particularly in challenging contexts, is important for future pandemic planning. However, further research with larger sample sizes is needed to confirm and generalize these findings.
AI Innovations Methodology
Based on the provided information, it appears that the study focuses on the association between pre-COVID impulsivity levels and engagement in preventative measures during the COVID-19 pandemic among South African youths. The goal is to inform future pandemic planning and understand predictors of engagement in protective behaviors.

To improve access to maternal health, here are some potential recommendations:

1. Telemedicine and Mobile Health: Implementing telemedicine and mobile health solutions can improve access to maternal health services, especially in remote or underserved areas. This allows pregnant women to receive medical advice, consultations, and monitoring remotely, reducing the need for physical visits to healthcare facilities.

2. Community Health Workers: Training and deploying community health workers can improve access to maternal health services, particularly in areas with limited healthcare infrastructure. These workers can provide education, antenatal care, and postnatal support to pregnant women in their communities.

3. Transportation Support: Providing transportation support, such as subsidized or free transportation services, can help pregnant women reach healthcare facilities for prenatal care, delivery, and postnatal check-ups. This can address transportation barriers that hinder access to maternal health services.

4. Health Information Systems: Implementing robust health information systems can improve coordination and communication between healthcare providers, ensuring seamless access to maternal health services. This includes electronic medical records, appointment scheduling systems, and data sharing platforms.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the Outcome Measures: Determine the specific outcome measures that reflect improved access to maternal health, such as the number of prenatal visits, percentage of deliveries attended by skilled birth attendants, or maternal mortality rates.

2. Collect Baseline Data: Gather data on the current state of access to maternal health services, including the number of prenatal visits, availability of skilled birth attendants, transportation barriers, and other relevant factors.

3. Simulate the Recommendations: Use modeling techniques, such as agent-based modeling or system dynamics modeling, to simulate the implementation of the recommendations. This involves creating a virtual representation of the healthcare system and simulating the effects of the recommendations on access to maternal health services.

4. Analyze the Results: Analyze the simulation results to assess the impact of the recommendations on the defined outcome measures. This can involve comparing the simulated outcomes with the baseline data to quantify the improvements in access to maternal health.

5. Sensitivity Analysis: Conduct sensitivity analysis to explore the robustness of the simulation results. This involves testing the impact of varying assumptions or parameters to understand the potential range of outcomes.

6. Refine and Iterate: Based on the simulation results and sensitivity analysis, refine the recommendations and iterate the simulation to further optimize the impact on improving access to maternal health.

It is important to note that the methodology may vary depending on the specific context and available data. Additionally, involving stakeholders, such as healthcare providers and policymakers, in the simulation process can enhance the relevance and applicability of the findings.

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