Gender inequity and the subsequent health impacts disproportionately affect communities in the Global South. However, most gender equity measures, such as Pulerwitz’ (2000) Sexual Relationship Power Scale (SRPS), are developed and validated in the Global North and then applied in Global South settings without investigation of context applicability or validity. This study examines the SRPS’ validity evidence, comprehensiveness, and contemporary relevance for young South African women and men.Between 2019 and 2021, 38 cognitive interviews (CIs) were conducted among previous participants of a South African youth cohort study ‘AYAZAZI’ (2015–2017) to explore youth’s perceptions of the SRPS. The SRPS measures women’s perceptions of their partner’s controlling behaviours, and men’s perceptions of their own controlling behaviours. Using CIs, participants responded to a 13-item adaptation of the SRPS for use among South African youth (strongly agree-strongly disagree), and then were asked to think-aloud their reasoning for responses, their understanding and perceived relevance of each item, and made overall suggestions for scale adaptations. An item appraisal coding process was applied, whereby Cognitive Coding assessed the types of cognitive problems youth had with understanding the items, and Question Feature Coding assessed which item features caused problems for participant understandings. Finally, youth recommendations for scale adaptations were summarized.Overall, 21 women and 17 men aged 21–30 participated in CIs in Durban and Soweto, South Africa. Cognitive Coding revealed 1. Comprehension issues, and 2. Judgements related to items’ applicability to lived experiences and identities . Question Feature Coding revealed items’ 1. Lack of clarity or vagueness in wording and 2. Logical problems in assumptions leading to multiple interpretations . Multiple, overlapping issues revealed how many items failed to “fit” within the present-day living realities of South African youth. Youth recommended several item adaptations and additions, including strength-based items, to existing measures of gender equity and relationship power.Given identified issues, several adaptations including revising items to be more inclusive, contemporary, context specific, relational, and strength-based are needed to validly measure gender equity and power dynamics within the relationships of South African youth.The online version contains supplementary material available at 10.1186/s12889-022-13686-9. Growing attention has focused on the importance of advancing gender equity to improve global health and development. In 2015, the Sustainable Development Goals (SDGs) were established and focused on 17 key areas for enhancing global peace, prosperity, and global development, including goal 5: gender equality and empowerment of all women and girls. Achieving and accurately monitoring progress towards SDG 5 requires contemporary and contextual measures that accurately reflect the living realities of girls and women in all their diversity –5. Thus,A driving force of gender inequity and subsequent experiences of violence and negative SRH outcomes, is the unequal division of power held by women and other marginalized genders , 7. GiveWhile numerous quantitative studies have used different adaptations of the SRPS to examine sexual behaviour and SRH health outcomes among young women and men in sub-Saharan African settings , limitedThe objectives of this study are to: 1) explore cognitive  and question feature  issues of the SRPS among participants, and 2) make recommendations for any identified improvements, modifications, and additions to the current SRPS. Results from this study can be used to present construct validity evidence of the SRPS and can help to inform the development or adaptation of a scale or scales that reliably and validly measures gender equity and relationship control. Improved scales can then be used to inform future studies, programs and global targets aimed at improving gender relations and power dynamics in the relationships of young people disproportionately affected by the global HIV epidemic.Validity is a principal aspect of research and essential to the development of scales used in quantitative questionnaires , 29. ThiThis study uses cognitive interviews (CIs), a common method in assessing construct validity in measurement science, to examine the ways participants mentally process and respond to survey items, as well as to identify potential measurement error . While oBetween October 2019 and March 2021, CIs were conducted to explore youth’s perceptions of items in the SRPS that have been commonly used within SRH studies among South African youth . ParticiAt the 6- and 12-month follow-up visits, AYAZAZI participants completed a modified 13-item South African youth SRPS that has been used by other studies among youth in South Africa , 35, 36.Using cognitive interviewing techniques conducted by youth and adult-allies, this study centres, prioritizes, and incorporates youth voices to broaden understanding and critiques of gender equity measures in line with AYAZAZI’s youth engagement framework.During the AYAZAZI study (2014–2017), participants agreed and gave informed consent to be recontacted up to 6 years following the completion of data collection. Throughout the AYAZAZI study, a detailed list of contact information was maintained for retention purposes. From this contact information, CI participants were enrolled at both sites telephonically by trained study staff in Durban and Soweto. The study protocol was explained to contacted participants, and participants were asked if were willing to participate in a follow-up qualitative CIs where they would provide their perceptions of some of the questions asked during the AYAZAZI study. Interviewers guided interested participants through the informed consent procedure, detailing the purpose of the study, providing participants with opportunities to ask questions about the procedure, and ensuring that participants were aware that they could withdraw at any time. Participants then provided informed consent either in person (prior to the COVID-19 pandemic in March 2020) or orally/verbally over the phone . Participants were eligible if they had previously participated in the AYAZAZI study, if they were able to provide written or oral consent, and for the interviews conducted after COVID-19 became a global pandemic, if they had access to a phone in which they could conduct an interview lasting 30–60 minutes.The recruitment strategy for the CIs used the 12-month AYAZAZI questionnaire data to purposively select participants to get a diversity of perspectives. Interviewers at both sites were provided a call log of all participants who responded to the SRPS during the 12-month AYAZAZI questionnaire, listing the order at which to call participants. Purposive sampling criteria was based on previous analyses using questionnaire data that explored factors associated with the SRPS including age, age of primary partner, type of relationship  , and incEthical approval for the AYAZAZI study, and the Cognitive Interview sub-study, including the COVID-19 protocol amendments, and the oral consent procedure were approved by the harmonized research ethics boards of Simon Fraser University and the University of British Columbia (H19–00762) as well as the University of the Witwatersrand .Two interviewers in Durban were trained in person. Training involved reviewing the AYAZAZI study files, practicing participant calling, reviewing the study interview guide, and conducting mock interviews. All study documents were reviewed and piloted with the study staff, and Durban staff supported the translation and back translation of all interview consent forms and interview guides into isiZulu. This allowed for an iterative revision to the study documents.Soweto training began near the end of the data collection procedure in Durban and was done virtually (due to COVID-19 travel restrictions) with lessons learned from the Durban team. Details of the training can be found in the Additional file After consenting to the study procedure and the audio recording of the interview, a think-aloud procedure in English or isiZulu (participant preference) was used for the interviews , 40. ThiThe semi-structured interview guide was developed in collaboration with KC’s supervisory committee , the interview team which consisted of four South African-based interviewers, South African colleagues , and informed by existing literature on cognitive interviewing and sexual relationship power , and interactions were created by the interviewers. Each interview was audio-recorded to accurately capture the descriptions provided by the participant. All identifying features were removed from the interview transcripts to ensure confidentiality and interview recordings were stored in a locked cabinet at each of the study sites for the duration of the study and will be kept there for 6 years following the study before they are destroyed. Participants were provided 120ZAR (~$10CAD) for their time and a list of resources were sent to participants who were emotionally activated during the interview. For participants who indicated they would like to speak to a counselor, a social worker at the each of the sites re-contacted participants to check-in and referred them to a local resource.The interview team met with the principal investigator (KC), a white PhD candidate from Canada, on a bi-weekly or weekly basis to discuss emerging codes and themes, and iteratively revise the interview guide where required. For example, it became clear that one of the probes relating to whether participants felt that power dynamics impacted their sexual-decision making was confusing to participants, so the study brainstormed ways that interviewers could further probe about participants’ thoughts on how to accurately measure gender equity in relationships. Also, in some of the early interviews it became apparent that some of the questions seemed repetitive, therefore the interviewers were continuously encouraged to use the interview guide at their discretion, not as a script. Interviews were translated (as needed) and transcribed verbatim either by the interviewers themselves (in Durban) or by an external consultant (in Soweto), then were reviewed by members of the study team. Each transcript was received by the study team and uploaded into NVivo for data analysis.Basic demographics and mean and median SRPS scores of all participants regardless of their current relationship status are presented overall and by gender in Table In order to incorporate perspectives from all team members, and considering a cross-cultural approach to cognitive interviewing, a constant comparative analysis was undertaken, which allowed for the CI data to be analyzed collaboratively as it was collected . Index cFollowing index coding, a cognitive interviewing coding procedure was created. This consisted of Cognitive Coding, which examined the behaviours and responses of the participants, and Question Feature Coding, which focused on the behaviour of the survey items . Both coIndex and cognitive interviewing coding procedures were completed initially by KC with data summaries of findings being presented to the youth research staff (CZ & MK) in weekly meetings. Overall findings were then summarized and co-presented by KC, CZ, and MK for several diverse audiences. During presentations, audience members gave feedback which served as a means to check results and further explore issues with the scale items beyond the perspectives of the study team . Data weOf the total 425 youth included in the baseline AYAZAZI survey, 164/253 young women and 87/172 young men completed the SRPS at 6-month follow-up when the scale was added to the questionnaire, and 163/239 young women and 73/153 young men responded to the scale at 12-month follow-up. We were able to recruit 21 young women and 17 young men who had previously participated in AYAZAZI (aged 21–30) to participate in follow-up qualitative CIs. In Durban, approximately 32% of the 173 participants called (83% of Durban cohort followed-up at 12 months) were reached however, although this rate differed by gender. Only 14% of young men were reached vs. 48% of young women. Of the participants reached 42% of young men and 23% of young women completed the Cls, 12% of young women relocated (prior to telephonic interviews), 15% of young women and 17% of young men were unavailable, and 7% of young women scheduled an appointment to be interviewed but then never answered the interviewers calls at the time of interview. In Soweto, 102 participants were called (55% of Soweto cohort followed up at 12 months) and 31% of called participants were reached. Of the 32 participants reached, 100% of young women and 33.3% of young men participated in the CIs. Of the 14 young men who were contacted who did not participate, 57% agreed to participate, but then did not answer when the interviewer called to conduct the interview, 7% refused to participate, and 36% were unavailable to participate.n = 4) were not in a relationship at the time of interview, 29.0% (n = 9) had been in their relationship < 2 years, and 58.1% for ≥2 years. All participants who were not in a relationship at the time of interview were young women, 21.1% of women were in a relationship for < 2 years vs. 41.7% of men, and a similar proportion of women and men were in a relationship for ≥2 years . Of the participants who discussed the age of their partner (n = 26), 57.7% (n = 15) were in an age-similar relationship (within 5 years of each other) and 26.9% (n = 7) were in a relationship with someone ≥5 years older than them. All young men were in age-similar relationships (n = 10) vs. 31.3% of women. Seven women (43.7%) were in a relationship with someone ≥5 years older than them. Mean (SD) and median  SRPS scores among women were higher than men , with higher scores indicating higher relationship power equity.Table p = 0.04), while men had non-statistically significantly lower scores (p = 0.08), than those measured during the 12-month AYAZAZI questionnaire  it would just be conflicts and we would solve them, you see? […] I will not just let her, I need to ask why she is leaving, what happened to [us].” -Participant 48Some items were not interpreted as originally intended. For example, although most young men agreed to item 6 “Although it might make me sad, my partner is free to leave the relationship anytime she wants” those that disagreed described wanting to figure out why their partner wants to leave instead of just letting the relationship fall apart. For example, one young man in Soweto stated:Similarly, some young women who disagreed to this item also referenced how they wouldn’t (not necessarily that they couldn’t) leave because they loved their partner.These differences in interpretation by young people highlight the lack of research, particularly in contexts where HIV and gender-based violence is high, focused on how young people perceive and enact love and problem solving within their relationships .- Participant 165“We are not married people, married people do that. He has not even paid for lobolo, so no. […] No, he must not expect me to…Yo! I have a lot of things to do and now I must leave them and attend to his needs? […] No, ha, never. He is not my husband. I do all of that if I want to.”One common judgement towards scale items raised by young women and young men was regarding how some items were not applicable to their current relationships as they seemed to be for married couples. For example, when responding to item 10 “My partner expects me to do everything for him”, one young woman from Durban stated:Even among the 38% who disagreed with this item, discussions of future expectations after paying lobola (bride price) were common.Finally, several young women discussed how they felt item 5 “my partner never tells me who I can spend time with” was not applicable to their lives because they chose to not have friends and thus their partner telling them who to spend time with was not an issue. Future research should explore the implications and potential consequences of young women having few to no connections with peers outside of their relationship with their partner.– Participant 13“Ahhh, okay, it is not that clear because it just mentions “greet”, it does not mention uhm, “talking to”, because greeting and talking to someone is two different things. When she greets someone and does not talk to them, it makes me a bit suspicious. So, it is better if you phrase this question like this rather than saying “talking to” someone because if she talked to someone, she would have an explanation for talking to them, expect for just greeting them, she could make just any excuse and just be like “No, it is a friend”, when it is actually a side person or someone else.” Numerous items lacked clarity. For example, item one “I am quite comfortable when my partner greets men she knows” raised discussion among some young men regarding the interpretability of the word “comfortable”, with some young men suggesting the item could be worded as “ok” instead of comfortable. For example, one young man in Durban described some of the issues he found with this item:Issues with this item highlight the subtle differences that are important to understand as they could have different interpretations.– Participant 67“Eeh, this one I, my understanding with it is that, It want to know how I feel when I alerted my partner that I will meet her at her place, and then when I do come and then she is not there, uhhhm then my thought about the question is, yes I agree with the question because I will like my partner to be at her place when I come to check her, because if, because I only come to visit her when I have informed her that on a particular day and time I will come and check you at your place, and then when I eventually do come and then she is not there, then it became problematic for me, because now she is wasting my time, wasted money to travel from my place to her place, only for me not to find her at her place, so that become problematic.” Item 2, which for young men stated “I like my partner to be home when I come to check her, it bothers me if she is not there” lacked clarity, which is well explained by one young man from Durban who stated:Young women also were confused by this question and would at times ask the interviewer for more context. Thus, while 69% of young men and 50% of young women agreed to this item, the majority agreed because they felt their partner would be upset if they had made plans and then they were not at home when they came to follow through with prior plans. The lack of clarity in this item raises important consideration regarding the ways in which young people communicate through social media and using smart phones and location sharing. This should be considered in more contemporary versions of this scale for use among young people.“When you say everything, you mean like house chores eh, laundry, financially?”- Participant 135For women, item 10 stated; “my partner expects me to do everything for him”, which led to a lack of clarity. For example one young woman from Soweto questioned:Another item which lacked clarity for some young women was item 11; “because your partner buys you things, he expects you to please him”. Participants were at times unclear what was meant by “pleasing him”, suggesting that this and many other items in the SRPS could be revised to be more specific to avoid confusion and improve comprehensiveness.Most of the items in the scale were heteronormative and cisnormative, asking young women about their male partners and young men about their female partners. While only one participant described how this raised some issues in responding to the scale, being that she was in a lesbian relationship, future research is needed to understand how power and control functions in non-heterosexual relationships, and how the SRPS could be adapted to better capture diversity in the relationships of young people.– Participant 195“No, […] I live with my parents and I cannot sleep over. […] He knows that my parents are very strict parents and so, he knows that I cannot sleep over whenever he wants me to.” Item 13, which for young woman stated, “my partner expects me to sleep over whenever he chooses”, assumes that young people can have sleep overs, or that they have started having sex. Some of the young women discussed how they hadn’t started having sleep overs or that they aren’t able to have sleep overs because of family dynamics, whereby at least one person in the relationship may still be living with their parents, thus making sleep overs challenging to navigate. For example, one young woman in Durban stated:Future studies may want to consider adapting this item to reflect differing family dynamics, abilities for young people to navigate sleepovers while staying at home with their parents, and for sexually active and inactive youth.“So, in my understanding, if she wears something that make her look beautiful, I am okay with it, but if she wears something that exposes her. I am not quite happy with that. So, I answered this question based on my understanding of beautiful rather than the society’s.” -Participant 13A few of the items seemed to be capturing multiple important elements in young people’s relationships and thus were left to interpretation. For example, item 3 which for young men stated “I get jealous if my partner wears clothes that make her look too beautiful” was at times understood to be that the men’s partners dressed nice and represented them which they appreciated, while some young men interpreted this item to mean that their partner wore revealing clothing and this brought attention from other men, which led to jealousy. One young man from Durban expressed:– Participant 11“Not really, ehm, I guess it’s something it’s an issue that I always had like from growing up, I never liked short things [revealing clothes], so I feel like they are uncomfortable, so that’s why I always avoid wearing them, like if you appear wearing short things it can mean a lot of things, like putting a lot of makeup, your weaves on like, from being simple, from having like a natural hair to relaxing your hair which will make you maybe more beautiful or wearing wigs, so ja, no, but in this question mostly, I would say maybe it’s wearing short, for me, it’s wearing short [clothing] ‘cause I don’t apply as well a lot of make-up.” Discussions raised from this item brought insight into different interpretations of beauty and the role and importance of gendered beauty standards, and how young women must navigate the fine line between being beautiful and attractive to their partners while at the same time ensuring they aren’t dressing too provocatively as to upset them. For example, one young woman from Soweto describes her interpretations of what beautiful means to her in the context of the scale and what the item is trying to measure:For this young woman, even though the issue of her partner being jealous if she looks “too beautiful” was not relevant in her relationship, it clearly shows how there are multiple societal pressures for young Black women in South Africa to look and dress a certain way to be perceived as beautiful. The importance of beauty and attractiveness has not been widely investigated within the relationships of young people, thus future research is needed to explore the role of beauty and beauty standards in the relationships of young South Africans.– Participant 116“Are you saying that’s what he wants, in which sense, like him maybe going out to watch soccer or is it when I say, I don’t want you to touch me when he touches me or do you mean?” Young women also raised concerns around multiple interpretations of item 7 “My partner does what he wants even if I don’t want him to”. For example, one young woman from Soweto stated:This highlights the potential dual interpretation of this item that could be about one’s partner going out and doing things that you don’t want them to do, or that they are making unwanted sexual advances or perpetrating sexual violence. These are two distinct and important relationship issues, that future scales may wish to measure as separate items.“Uhm…Jah, I feel like there is a twist somewhere, somehow […] I feel like it is asking if he is a stalker… […] But I also feel like it is asking if he cares.”- Participant 129Finally, as highlighted in the title of this paper, both young men and women felt that item 9, which for young women stated, “My partner always wants to know where I am”, captured both elements of caring and over-surveying or controlling behaviour. One young woman from Durban captured this issue with double-barreled interpretations when she stated:“If I know where she is and I am not with her, I become so free to say, okay, my partner is at a certain place, she is doing 1, 2, 3, even though I don’t see her […] but I have peace that I mustn’t worry too much about her. If she does not tell me where she went, I will be worried, worse, if I call and she does not take my call, then I will think that eish since these days, there is human trafficking.” -Participant 49Young men from both sites also discussed how in the context of South Africa where there are high rates of violence this item could be interpreted as caring and trying to protect partner from violence. For example, one young man from Soweto stated:In South Africa, a woman is killed every 3 hours, and femicide rates are five times higher than the global average . Under tYoung women and men had lots of suggestions for how to improve the scale, including advice on being more specific, rewording items, adding additional questions about power and control, including questions that were more general about relationship dynamics, as well as adding questions about health, sexual behaviour, and violence and abuse.” – Participant 11“Maybe if we can just…, when you ask the question, maybe add more details so that I know that when I respond I will give you the answer that is appropriate ‘cause now it’s open-ended you know I can say yes, I agree with just everything but then you find that another person perceives it differently, so jaTo address some of the issues raised by participants about items in the SRPS, participants brought up suggestions for making items more specific. For example, one young woman from Soweto stated:“I think that’s how it should be, like more specific whether in public or in private space.”-Participant 111Another young woman in Soweto provided specific recommendations for item 1 “My partner is comfortable when I greet men I know”, stating:Also, given that the scale was asked about young women’s partner’s behaviour, some young women suggested that items be added to also assess their own behaviours.“I will speak in a manner we usually speak with the guys here in Durban, I will say hey my brother how do you feel about the 50/50 [gender equality] thing?”- Participant 41Both young women and men brought up several suggestions for items that they felt would be important to include to measure power and control in relationships. This included asking participants if they believe in gender equality/equity, if you go out with friends, and if you allow your partner to have a say about decisions in the relationship. For example, one young man from Durban stated:This also highlights how some of the items could be reworded to better reflect the ways in which young people talk about SRP in South Africa.“The emotional wellbeing of a person in that relationship. How are you fitting in emotionally? Because some people can be like. Yes, he understands me but there is that emotional part of them where they are breaking. Where they are not happy emotionally. But in other things they can defend their partner and say yesss he is a good person but emotionally the soul is the important thing,” – Participant 123Specific questions about relationship dynamics were of interest to participants including whether your partner takes you on dates, questions about intimacy, and plans to have children together in the future, as well as emotional wellbeing in your relationship. When asked about SRP in South African youths’ relationships, one young woman from Durban stated:These suggestions call for increased attention to strength-based measures of gender equity that focus on positive assets of relationships and deeper connections that young people have with each other.“Like how, how often do you have sex with your partner or how much sex should one have with her partner per month or per week or, ya, those kinds of questions. […] Well, it also depends on how active, how sexually active you are. If you are very sexually active and your partner is not around, the chances are high that you will find sexual pleasure from someone else, other than your partner.” – Participant 67This desire to explore in greater detail the intricacies of young people’s relationships came up through suggestions to include additional details of young people’s sexual relationships, as a marker for relationship satisfactions. For example, one young man from Durban suggested:Several suggestions came up around sexual health and sexual violence and abuse such as whether you would ever force your partner to have sex with you, if your partner was abusing you, and asking about who in the relationship might have more physical power. Concerns about cheating and the consequences of cheating were also discussed as important for understanding power dynamics in young people’s relationships. This included suggestions to ask questions about whether participants ever got an “infection” (STI or HIV) from a partner and what they did about it. Other questions about health were suggested including asking whether participants ever went to get tested for HIV with their partner.– Participant 58“Maybe what can it be, ooh maybe it can be a job. Maybe if someone have a better job, does that affect the relationship. If I as a male work better and earn better, would it make me not to respect my partner during that period.” Questions about employment and how economic inequities and societal gender roles may impact relationships were also suggested by participants. For example, one young man from Durban stated:This recommendation highlights the intersecting nature of sexual relationship power inequities and ‘gender role strain/stress’ or men’s stress related to inability to achieve hegemonic forms of masculinity including the ability to provide for one’s family through work –56. ThisFinally, both young men and women spoke about adding questions about technology and looking at each other’s phones in relationships.The results from this study highlight multiple issues surrounding items that have been used in youth sexual and reproductive health studies in South Africa. Given that the SRPS was originally developed among women in the US in the year 2000, and the inherently dynamic nature of gender roles, dynamics, and identities , it is nThe use of technology and communication through social media is an important area for future research. For young people in today’s society, relationship formation, sex, and love most often begins and is sustained online and through social media and other dating apps . Thus, tMany participants brought up that the items in the scale seemed to be for married couples and weren’t relevant, as most participants were unmarried. Previous research has highlighted that even young men who are not yet married have perceived entitlement to any woman to whom they will have to pay lobola to marry . This isIn contexts like South Africa, where HIV is endemic, youth relationships are rarely discussed through a strength-based lens, instead researchers and program and policy makers have mostly focused on deficit-based narratives of youth sexual relationships as inherently risky . While tFindings also highlighted how partners as well as parents influenced youths’ relationship dynamics. The items in the SRPS stem from the Northern assumption that decision-making happens at the individual-level, whereas in South Africa, and many other global settings, decision-making is largely relational . Thus, rIssues raised by participants were not equal across items or genders. Overall, data indicated that young men raised more comprehension issues with the scale items, which is not overly surprising given that the scale was originally developed to measure women’s perceptions of their male partners controlling behaviours and dominance in relationships . While tFuture research wishing to use the SRPS in their research with youth globally should consider the recommendations and suggestions for adapting the scale as mentioned by the participants and outlined in Tables Revising the scale language to be more inclusive of gender and sexual diversity as well as different types of relationships .Modifying items so that they have contemporary relevance. This could include ensuring translations of the scale match the age and group context. Also, to reflect youth’s realities, we recommend modifying items about one another’s whereabouts to capture how young people are more connected via technology than they were when the scale was developed. We also recommend revising items that may not make sense for youth in South Africa who generally aren’t married or living with their partners.Adding or modifying items so that they reflect the multidimensional and dynamic aspects of gender and SRP equity, including the importance of relationships at the intimate partner, peer, community, institution, and societal levels.Revising items to be more strength-based, to accurately capture equitable relationship power dynamics and shift the focus away from deficit-based narratives of inequity and risky youth sexuality.Revising some of the items to be more specific to avoid differing and multiple interpretationsExploring whether different response options would make more sense for certain items. Also, if response items should have the option for participants to respond don’t know/unsure. For example, providing the options of: Always, often, sometimes, rarely, and never. This could also include exploring how having more than 4 response options and having a neutral option might affect the responses and overall scale scores.In general, some recommendations for revising the scale include:These recommendations highlight the complexity of creating a one-for-all measure for complex constructs such as SRP equity. Moreover, the ever-changing and involving nature of gendered power dynamics will require researchers to continuously evaluate, modify, and adapt measures to reflect these changes, further complicating efforts to monitor progress towards global goals for gender equality . HoweverParticipants for this qualitative study were recruited from a larger sample of youth who participated in a longitudinal study ‘AYAZAZI’ from 2015 to 2017. Participants, however, had not been in contact with the study for several years. While many participants were unreachable, there were no major differences between participants who were and were not included in this sub-study , may still have meaningful implications for shifts in young men’s tendency to exert greater control and display adult dominant masculinity, as they get older [Improvements in SRP among young women in our study is different than prior research among young women in Kenya, highlighting reductions in SRP with age . This, het older . There iet older .The use of cognitive interviewing in our study provided an opportunity to establish a youth-engaged process for appraising items of a well-established measure of gender equity that provided insight, evidence, and recommendations for scale adaptation strategies for the use of the SRPS in South African youth studies, and specifically how the SRPS may function differently for young women and men. However, due to limitations in recontacting participants several years after last contact with our study team, we were unable to fully follow the intended purposeful sampling approach. Our data collection took place over a period of 15 months due to the ongoing COVID-19 pandemic causing interruptions in data collection and requiring the study team to re-submit ethical approval to continue interviews telephonically. Interviews that were conducted telephonically may have differed from those done in-person pre-COVID, however the interviewers felt that they were able to have meaningful conversations with participants despite not being face-to-face. In fact, the youth interviewer in Soweto (MK), interviewing young women, felt that young women may have been able to be more open about their relationships than would have been possible in person. Telephonic interviews also allowed participants who may have moved out of the area to participate, and thus may have been why all the young women who were contacted in Soweto participated in the cognitive interviews. Moreover, our results present a disproportionate number of quotes from young men in Durban, which was reflective of young men residing in Durban, the majority of whom completed the CI in person, having more to say about the items in the scales than young men in Soweto, all of whom conducted the survey telephonically. These findings raise important gendered considerations for data collection and the importance of exploring youth preference for data collection methods and modalities  in future youth studies focused on topics related to sexuality, relationships, and gender norms and roles.While detailed socio-demographic information , education, food-security ), mentalFinally, our team spent an extensive amount of time reviewing the data, co-coding, and double coding transcripts; however, this cannot prevent our own world views and values from impacting the interpretation of the data. Because members of the team spoke different languages, and interviews were conducted in multiple languages, they had to be translated into English in order to be discussed as a group, which may have posed issues in cross-cultural interpretation of the data . As thisby, with, and for youth. To address gender equity and improve the health and well-being of youth across the life course, the validity evidence of measures used within youth research needs to be evaluated on an ongoing basis to ensure measures remain contemporary and reflect the living realities of young people. As such, the methods used in this study could be applied across a range of disciplines and settings to support the meaningful engagement and participation of affected communities to improve measurement development, adaptation, and appraisal.Given the wide use of the SRPS in research centered on youth’s SRH, this study fills an important gap in unpacking the validity evidence of the scale and provides insights into the gendered comprehensiveness and contemporary relevance of the SRPS in the lives and relationships of young women and men in South Africa. While many of the participants felt that the scale adequately captured SRP and were relevant to their relationships, and the relationships of their peers, this differed by gender, and there were several items which were interpreted differently than the original scale intended. Moreover, even when reminded of the response options, many participants chose to answer the items using their own responses, raising potential issues in validity evidence surrounding scale content as well as response consistencies. Numerous recommendations for additional and more contemporary, relational, and relevant measures of sexual relationship power were suggested by participants, providing opportunity for researchers to adapt youth recommendations into future use of the SRPS in their research and program evaluations Additional file 1: Supplementary material. Details of the Cognitive Interview training.Additional file 2: Supplementary table 1. Comparing participants in Cognitive Interview study to the rest of the AYAZAZI sample.


The authors reviewed uterine fibroid (UF) morcellation and its potential consequences, notably a hypothetical spread and dissemination of occult uterine leiomyosarcoma (LMS) tissue, evaluating the effect of laparoscopic versus open myomectomies with and without morcellation on patients’ outcomes, as well as related medical-legal issues. MEDLINE and PubMed search was performed for the years 1990–2021, using a combination of keywords on this topic. Relevant articles were identified and included in this narrative review. There is an individual risk, for all patients, for LMS diagnosis after myomectomy. However, the risk for occult LMS diagnosis during a laparoscopic myomectomy is generally reduced when the guidelines of scientific societies are followed, with an overall benefit from the laparoscopic approach with morcellation in appropriate cases. Gynecological societies do not ban morcellation and laparoscopic hysterectomy/myomectomy per se, but recommend their use on the basis of the patients’ clinical characteristics. It is suggested for gynecologists to provide detailed information to patients when obtaining an informed consent for open or laparoscopic hysterectomy/myomectomy. A detailed preoperative assessment of patients and the risk benefit ratio of laparoscopic morcellation of uterine mass could overcome the “a priori” banning of the morcellation technique. Power morcellation was approved by the Food and Drug Administration (FDA) in 1995, as a primary method used for removal of uterine fibroids (UF) during laparoscopic myomectomy . The powThe FDA decision to ban the “uncontained” morcellation in gynecologic laparoscopic surgery was after the first reports of cancer spread due to an uncontained morcellation . This FDThis narrative review focuses on uterine masses morcellation and its influence on occult LMS tissue spread and dissemination, discussing laparoscopic versus open myomectomies with and without morcellation and evaluating their influence on patients’ outcomes, as well as medico legal issues.The authors searched the available data on the molecular basis of the pathogenesis, diagnosis, and prognosis of UF and LMS. The authors conducted a MEDLINE, Scopus and PubMed search, for the years 1990–2022, using a combination of keywords, such as “uterine fibroid, “myoma,” “fibromyoma”, “leiomyoma”, “myomectomy,”, “morcellation”, “open myomectomy”, “laparoscopy”, “leiomyosarcoma”, “prognosis”, “treatment”. Literature that was the most relevant to the topic was used based on the authors’ evaluation. Peer-reviewed articles concerning UF, myomas, leiomyomas, LMS and morcellation were included. Additional articles were identified from the references of relevant papers. The terms “uterine fibroids”, “myomas”, “fibromyomas”, and “leiomyomas” can be found in the literature as ways of describing UFs. In the manuscript, we have used the term “fibroid” or “myoma” in equal measure. The results of the research have been divided into sub-sections, in which we illustrate what has been reported in the scientific literature, including the authors’ opinions on such topics.Some studies reported results about the incidence of occult unexpected uterine malignancies, especially LMS, in specimens retrieved by morcellation during laparoscopic hysterectomy or myomectomy.Wright et al.  performeXu et al.  conducteLieng et al.  evaluateKho et al.  analyzedPicerno et al.  evaluateThey reported two women with uterine malignancy, both endometrial carcinoma  and non-uterine sarcomas . It was also observed that six  women showed uterine premalignancy: 2 atypical myomas, 1 STUMP , and 3 endometrial atypical hyperplasia. It was observed that women with uterine malignancies and uterine premalignancy had greater uterine weight and, frequently, UF, as indications compared with women with non-uterine malignancies.Yang et al.  reportedThe results of the studies including a large number of patients showed the low incidence of undiagnosed cancer tissue in UFs tissue specimen retrieval by morcellation. However, the patients with postoperative diagnosed LMS had clinical characteristics which could be evaluated preoperatively and, accordingly, the morcellation could be dismissed in such patients. Unfortunately, there is not available reliable preoperative method to differentiate between a UF and a LMS . The avaEven though the use of morcellation could theoretically lead to the dissemination of malignant cells into the peritoneal cavity, the clear mechanism and degree of dissemination are unknown. Therefore, an open question could be: “Can the UF morcellation potentially cause the undiagnosed LMS cells dissemination during morcellation?”.Asgari et al.  evaluateOn the other hand, the utilization of the morcellation technique during myomectomy is not just a question of surgical practice, but it is a medical-legal issue, especially if an undiagnosed uterine LMS is morcellated and disseminated into the abdominal cavity during surgery. In addition, the loss of use of morcellation technique in gynecologic surgery led to the decrease in minimal invasive procedures and an increase of postoperative complications associated with open surgery.Ottarsdottir et al.  reportedClark et al.  analyzedIt is known that laparoscopic myomectomy has advantages compared to open myomectomy. These advantages are well known, and it is not hard to assume the consequences of the decrease of laparoscopic practice after morcellation banning, especially laparoscopic myomectomy.Tinelli et al.  showed tWhen comparing the laparoscopic and open myomectomy, it is important to emphasis a rate of possible recurrence of UF after surgery. Kotani et al.  comparedMing et al.  performeChen et al.  conducteMultinu et al.  undertooHarris et al.  performeIt has been also observed that changes in laparoscopic practice after the FDA statement on morcellation led to an increase in costs, although eliminating morcellation from laparoscopic surgery is not cost-effective under a wide variety of probability and cost assumptions ,38. RutsThere are also conflicting findings concerning the influence of morcellation based on a survey of patients with preoperative undiagnosed LMS. On the one hand, it has been observed that morcellation did not affect disease-free survival of patients with LMS but, on the other, that patients with morcellation had 3-fold increased risk of death, in comparison with patients who did not have morcellation .Lin et al.  reportedGao et al.  also obsTaking into account the advantages of laparoscopic approaches in myomectomy and, however, the factors which influence the survey of patients with preoperative undiagnosed LMS, the international gynecologic societies as well as the European Society of Gynecological Oncology (ESGO), the International Society for Gynecologic Endoscopy (ISGE), the European Society for Gynecological Endoscopy (ESGE), Die Deutsche Gesellschaft für Gynäkologie und Geburtshilfe (DGGG) and the American College of Obstetricians and Gynecologists (ACOG) have recommended statements about morcellation ,46,47,48The common recommendations are that all patients must be assessed for individual risk of LMS and benefit from the possibility of a laparoscopic approach and morcellation utilization . In patiNowadays, in the light of what has been highlighted in the literature, there are no particular needs or requirements to modify one’s surgical behavior concerning the morcellation of UFs, as long as it is consistent with the assessment of the patients’ characteristics and risk/benefit ratio. We believe that power morcellation can still be widely used, after selecting the patients to submit to laparoscopy. Of course, it is necessary to use the usual prudence before undertaking a myomectomy, not least to avoid annoying and expensive medical-legal ligation in the courts.


The COVID-19 pandemic introduced unprecedented challenges for people and governments. Vaccines are an available solution to this pandemic. Recipients of the vaccines are of different ages, gender, and religion. Muslims follow specific Islamic guidelines that prohibit them from taking a vaccine with certain ingredients. This study aims at analyzing Facebook and Twitter data to understand the discourse related to halal vaccines using aspect-based sentiment analysis and text emotion analysis. We searched for the term “halal vaccine” and limited the timeline to the period between 1 January 2020, and 30 April 2021, and collected 6037 tweets and 3918 Facebook posts. We performed data preprocessing on tweets and Facebook posts and built the Latent Dirichlet Allocation (LDA) model to identify topics. Calculating the sentiment analysis for each topic was the next step. Finally, this study further investigates emotions in the data using the National Research Council of Canada Emotion Lexicon. Our analysis identified four topics in each of the Twitter dataset and Facebook dataset. Two topics of “COVID-19 vaccine” and “halal vaccine” are shared between the two datasets. The other two topics in tweets are “halal certificate” and “must halal”, while “sinovac vaccine” and “ulema council” are two other topics in the Facebook dataset. The sentiment analysis shows that the sentiment toward halal vaccine is mostly neutral in Twitter data, whereas it is positive in Facebook data. The emotion analysis indicates that trust is the most present emotion among the top three emotions in both datasets, followed by anticipation and fear. The COVID-19 pandemic has introduced unprecedented challenges in the world. The health crisis has driven governments to take extraordinary measures to save lives, including lockdowns and social distancing measures. However, the combined effect of these measures and the spread of the virus resulted in an unparalleled dramatic decline in economic activity, as the affected sectors were essentially shut down ,3. ExampVaccine recipients have different nationalities and religions. Among them, Muslims, Hindus, and Jews have questioned the content of COVID-19 vaccines . MuslimsThe coronavirus pandemic of 2020 is the first global health crisis in the age of social media. During this pandemic, numerous social media platforms are used to alleviate and spread harm. During epidemics, people need accurate information to modify their behavior and protect themselves, their families, and their communities against infection . An infoThere are research works on COVID-19 vaccines, focusing on analyzing government performance in the pandemic, vaccine certification, and acceptability of the vaccines ,14. HoweNatural Language Processing (NLP) is a branch of machine learning dealing with text data which uses algorithms to process and analyze text. Among various branches of NLP, sentiment analysis studies text data to determine polarity of text as positive, neutral, and negative. Emotion recognition is another branch of NLP dealing with extraction and recognition of emotion in the text data . It is cAmong many research works published in sentiment analysis and emotion recognition, Deng et al.  proposedThere have been research works on COVID-19 vaccines. Wardhana  has reseThere are other studies conducted specifically on the halal COVID-19 vaccine from various perspectives. For example, Susilo et al.  examinedThere is a gap in the literature to explore the content of social media and evaluate the sentiment and emotion of the users towards the halal vaccine. This helps to facilitate the immunization program by alleviating users’ concerns about the vaccine. Therefore, this paper aims to understand the online discussion of halal COVID-19 vaccines and identify people’s perceptions of them. To the best of our knowledge, this is the first study to conduct aspect-based sentiment and emotion analyses of Facebook and Twitter data to find out what people think and feel about the halal COVID-19 vaccine.This section explains the methodology used in this work. The first step is to collect data from Twitter and Facebook. This subsection discusses the data collection from Twitter and Facebook and the preliminary analysis of the collected data.Twitter provides an official Application Programming Interface (API) to retrieve tweets. However, the API only returns tweets for the last seven days. Furthermore, accessing the premium API is costly. Therefore, we used the Twint package  in the PThe search returned 6037 tweets containing both “halal” and “vaccine”. To complement each tweet, we retrieved metadata such as the time and date of creation, username, name, place, language, mention, number of replies, number of retweets, and number of likes.Since the focus of this work is on English-language tweets, we filtered out non-English-language tweets by checking the language metadata of each tweet. An analysis of the language of the tweets revealed that 80.5% are in English, followed by Indonesian, Hindi, and Tagalog.One of the metadata of tweets is hashtags. A hashtag starts with the hash sign (#), followed by a keyword or topic, without spaces. It has been used to mark and categorize tweets. As we can see in This hashtag was used on 9 December 2020, in the following tweet:“In the name of the pious Shari’a, I appeal to all my Muslim believers to not take the COVID vaccine as it is not Halal certified. Moreover, no Maulana was associated with its development. #MuslimsBoycottCovidVaccine”.Soon afterward, the hashtag started to trend, and on 11 December 2020 alone, it was featured in 46 tweets. The trend then declined. It is worth noting that this tweet is the third most retweeted tweet in our dataset, with 889 retweets and 3582 likes.Location metadata are valuable for our analysis; unfortunately, many fields were left empty, and some tweets had an invalid location. Therefore, we decided not to use this metadata for analysis.The tweets were then put through text processing. Each tweet contains special characters such as @ and #, links to a web page, and punctuation marks. We first converted the tweets to lowercase, and then removed any special characters, punctuation marks, and links. The clean data were also checked for duplicates. In the case of duplicate tweets, only one instance of the tweet was kept.The Facebook data were collected from CrowdTangle . CrowdTaSimilar to the Twitter data, we searched for the term “halal vaccine” and limited the timeline between 1 January 2020 and 30 April 2021. A total of 3918 posts were collected using the specified criteria.The collected data have many metadata. For example, for each post, the following are available: page name, username, page category, number of page likes, number of page followers, post creation date, total interactions, number of likes, number of comments, number of shares, number of “love” reactions, number of “wow” reactions, number of “haha” reactions, number of “sad” reactions, number of “angry” reactions, number of “care” reactions, and message and description of the post.Some of the metadata retrieved from Facebook concern page category, that is, whether a page belongs to a person, an organization, or a group. News companies and agencies dominate the top 10 categories in the number of posts. The person category, which refers to pages that belong to individuals, is ranked fifth. This shows that news and government agencies are very active on Facebook. We can also analyze page categories based on the number of comments, shares, “love”, “likes”, “wow”, “haha”, “sad”, “angry”, and “care” they receive, as shown in As shown in The most shared post was published by the Indonesian Ministry of Health and received 50,343 likes. It addresses collaboration between the government of Indonesia (the most populous Muslim country) and the Imperial College London on COVID-19 vaccine development.Unlike Twitter data, Facebook data do not contain metadata specifying the language of the posts. Therefore, we used a Python library, Whatthelang, to detect the language and filter out the non-English-language posts. Furthermore, text processing was performed on the Facebook data, including removing duplicated posts and empty posts to ensure data consistency.Text processing was the next step. Tweets and Facebook posts contain special characters such as @ or #, punctuation marks, and links to websites. To analyze them effectively, we needed to remove those characters and clean up the text. Therefore, we filtered out non-English-language data and removed special characters and duplicated data. Additionally, we used text normalization on the data, specifically lemmatization, a method of shortening the words to their roots . This method protects the algorithms from confusion.Once the data were clean and ready for analysis, we performed aspect-based sentiment analysis. One of the most well-known research areas in computer science is sentiment analysis, which aims at extracting and identifying users’ opinions . SentimeAspect-based sentiment analysis tries to solve this issue by identifying the topics discussed in the data and performing sentiment analysis on each . Thus, iAs shown in This approach has been used in many contexts in the literature, such as for movie reviews , productThe VADER library is a lexicon and rule-based sentiment analysis tool specifically tuned for sentiments expressed on social media. Since it is a pretrained library, it does not require training. It is constructed from a generalizable, valence-based, human-curated gold-standard sentiment lexicon. It is a fast library that can be used for a large volume of data, such as social media posts. The VADER library produces a score between −1 and +1, with −1 negative, +1 positive, and 0 neutral. A score greater than 0.05 is considered positive and less than −0.05 is considered negative . ResearcText emotion analysis is the process of detecting emotions in data. There are two approaches to detect emotion in text, word-based and learning-based approaches . In the NRCLex is a tool that uses the word-based approach. It is based on the lexicon dictionary of approximately 27,000 words, Canada’s National Research Council (NRC) , and theText2emotion  library IBM Tone Analyzer is another word-based tool. It was developed by IBM and is accessible through API. It can detect document emotion and sentence emotion. However, the results are not easy to understand, and it is slow for large text. It also relies on an active network connection, which slows down the process.This section presents the results of the analyses carried out according to the method described in the previous section, including aspect-based sentiment analysis and text emotion analysis.We introduce the results for Twitter and Facebook data separately. This allows us to compare the two popular social media platforms.The cleaned tweets were used to run the LDA algorithm, which required us to specify the number of topics. We first ran the algorithm with seven topics. However, the results were vague, consisting of “halal status,” “amid halal,” “halal await,” “vaccine halal,” “halal vaccine,” “filled cow,” and “experimental vaccine”. Therefore, we tried the experiment with four topics, which resulted in meaningful topics. For visualization purposes, we plotted the dataset to see the separation of the topics. This separation shows that the dataset can be divided into individual topics and any possible overlap in the data. Based on Similar to the Twitter data analysis, the Facebook posts were fed to the LDA algorithm, and the topics visualization is shown in Like Twitter data, the four topics are separated individually. The topics can then be labeled, and the sentiment of each topic is shown in As shown in Regarding the ulema councils , the difference between negative and neutral sentiments is marginal. Similarly, the difference between negative and neutral sentiments is small for the Sinovac vaccine topic.As discussed in The Twitter dataset, once cleaned, was analyzed using the NRCLex library in Python . Figure Interestingly, the results show that trust is the most frequently detected emotion in the tweets. The second emotion is anticipation, followed by fear. Sadness is the fourth emotion in the “COVID-19 vaccine” and “halal certificate” topics, while joy is the fourth emotion in the other two topics.Similar to the Twitter data, the Facebook data were analyzed using NRCLex, the emotion analysis tool. As we can see in We further investigated fear as the most present negative emotion in Twitter and Facebook data. The data labeled “fear” were identified and the 50 most used words were extracted to determine what users talk about in their posts. Twitter data show a similar pattern but from a different perspective. The tweets contain “pork,” “urine,” “animal,” and “gelatin,” indicating Muslim concern about the contents of the vaccine, similar to the Facebook data. In addition, Twitter users ask for halal certification and emphasize the need for a valid certificate for the vaccine, as “certified” and “certification” are among the top 50 words in the data.In this study, we analyzed Twitter and Facebook data related to halal COVID-19 vaccines. The data were collected between January 2020 and May 2021. The period between November 2020 and February 2021 saw the highest number of tweets and posts. The analysis included aspect-based sentiment analysis as well as emotion analysis. The focus of this study was on English-language tweets and posts. We identified topics in the data and calculated the sentiment for each aspect (topic). This approach has the advantage of detecting sentiments related to a specific topic rather than the whole dataset. Emotion detection for each topic was also performed, complementing the sentiment analysis. It further analyzes the emotion in the text compared to positive and negative sentiments.Our findings indicate that online public discourse on Twitter and Facebook regarding halal vaccines reflects a genuine concern in the Muslim community. Users discussed topics such as “halal vaccine,” “halal certificate,” “must halal,” “Sinovac vaccine,” and “ulema council”. The sentiment towards these topics was somewhat similar. While users on Twitter mostly expressed neutral sentiments, the Facebook data show mostly positive sentiments. This study extends the current literature by diving deeper into the two most used social media. Researchers can expand this study by including other social media platforms and exploring the content more comprehensively. Since most Facebook posts were published by government and news agencies, we speculate that they tried to convey positive sentiments to users to encourage them to take the vaccine. In addition, the tweets came from the public and government agencies, contributing to the more neutral sentiment. Considering that fear is among the top emotions expressed by users, policy makers, organizations, and government agencies can use the results of this study to communicate more effectively with the public. This includes alleviating their concerns regarding the halal vaccine and assuring them that they collaborate with the respective companies to develop vaccines complying with halal conditions. The results of this study corroborate those of an earlier study by Zhang et al. , which aOur study focuses on analyzing social media data. The population using social media is relatively young , and theAdditionally, the geolocation of the users may add bias to the data. We can focus our study on a specific region or country and analyze their opinion on the halal vaccine. Selecting a region or a country also helps to consider the culture of that region or country.We collected data from Twitter and Facebook due to their popularity and ubiquity. Other popular social media platforms include Instagram, a platform popular for sharing pictures and videos. Although pictures and videos are different from text, the comment section of the posts is a great source of data. Reddit is also another social media site that is popular among some users.This study filtered and analyzed English content, which leaves out other languages such as Arabic. This is due to limitations in algorithms and the fact that they are well-tuned for the English language. Researchers may analyze contents in other languages in the future when the algorithms are more robust on non-English content.This study analyzed Facebook and Twitter data regarding halal COVID-19 vaccines between January 2020 and May 2021. The results showed that users discussed topics such as “halal vaccine,” “Sinovac vaccine,” “ulema council,” and “must halal”. The sentiment expressed in the data was mostly neutral, followed by positive sentiments. We investigated further by detecting emotions in each topic. We found that trust was the most present emotion, followed by anticipation and fear. Comparison between this study and similar studies corroborates our findings. Our findings may help the relevant Muslim organizations and councils make more decisive announcements regarding the halal status of the vaccines. Additionally, the collaboration between government agencies and vaccine companies, on the one hand, and Muslim organizations, on the other hand, is crucial to encourage more people to choose to take a vaccine.


The stop-signal paradigm has become ubiquitous in investigations of inhibitory control. Tasks inspired by the paradigm, referred to as stop-signal tasks, require participants to make responses on go trials and to inhibit those responses when presented with a stop-signal on stop trials. Currently, the most popular version of the stop-signal task is the ‘choice-reaction’ variant, where participants make choice responses, but must inhibit those responses when presented with a stop-signal. An alternative to the choice-reaction variant of the stop-signal task is the ‘anticipated response inhibition’ task. In anticipated response inhibition tasks, participants are required to make a planned response that coincides with a predictably timed event (such as lifting a finger from a computer key to stop a filling bar at a predefined target). Anticipated response inhibition tasks have some advantages over the more traditional choice-reaction stop-signal tasks and are becoming increasingly popular. However, currently, there are no openly available versions of the anticipated response inhibition task, limiting potential uptake. Here, we present an open-source, free, and ready-to-use version of the anticipated response inhibition task, which we refer to as the OSARI (the Open-Source Anticipated Response Inhibition) task. The ability to inhibit action  is one of the most commonly investigated topics in psychology and cognitive neuroscience. The capacity to enact behavioral inhibition varies across the lifespan and has been identified to be affected in a wide variety of clinical cohorts  can vary, with the recommendation being that the prompt to go should be neither too simple nor too difficult , the stop-signal paradigm is unique in that it also has the capacity to produce estimates of the covert latency of an individual’s stopping process, referred to as their stop signal reaction time (SSRT). SSRTs are estimated through the independent horse race model, which suggests that the success or failure of inhibiting an action can be conceptualized as a race between two processes: the go process (triggered by go stimuli) and the stop process . If the stop process is able to ‘outrun’ and finish before the go process, the prepared action is canceled. Alternatively, if the stop process is unable to outrun and finish before the go process, then the prepared action will be enacted. Using the assumptions of the independent horse race model, an individual’s SSRT can be estimated based on their RTs on go trials and their probability of stopping across a range of SSDs on stop trials .Currently, open-access versions of the stop-signal paradigm exist, with the most popular version being ‘STOP-IT’  task. The ARI task was originally developed by Slater-Hammel in Open-Source ARI task, which we refer to as OSARI. OSARI is a free-to-use, cross-platform task programmed in PsychoPy , which will be loaded automatically in their next run of the task.Once the script is running, users will be presented with a ‘Participant Information’ dialog box Fig. , which iThe default block and trial structure for OSARI are informed by Verbruggen et al. ’s consenOnce participants have completed the ‘practice go and stop block’, they then complete three test ‘test go and stop blocks’. Each ‘test go and stop block’ contains a total of 80 randomly presented trials, with 60 (75%) of those trials being go trials and 20 (25%) being stop trials. If users wish to present trials in a predefined order or alter the proportion of each trial type, they can adjust the excel spreadsheet files in the ‘conditionFiles’ folder of the task and select ‘sequential’ in the ‘Trial Structure Parameters’ dialog box at task start-up. The number of rows labelled as stop and go trials corresponds to the desired trial numbers of each.A schematic overview of the stimuli used in OSARI is presented in Fig. At the beginning of each trial, participants are instructed to ‘Press the space key when you are ready’. The space key is used as the default response key for progressing trials and responding to targets; however, the user can change the default key using the ‘Response Key’ input in ‘Additional Parameters’ dialog box. Once the key is pressed and held, a short, randomly selected interval will occur prior to the filling of the bar. Following the variable start interval, the filling bar takes 1000 ms to fill to the top. If participants lift the key during the variable start interval , they will receive the message: ‘Oops! You lifted too soon! Press space to restart’. If the key is lifted within the first 100 ms of the trial, participants are presented with ‘Try to stop the bar as close to the target as possible’.On go trials, participants are required to release a key to stop the filling bar as close to the target as possible. Feedback is given by way of the target changing color; if the filling bar is stopped, above or below the target, within 20, 40 and 60 ms, the target turns green, yellow and orange respectively. If the filling bar is stopped > 60 ms from the target line, the target turns red. (a color-blind friendly setting is available). Similarly, on stop trials, if participants successfully withhold their response following the stop signal . By default, SSDs are presented using the ‘staircase’ method, where the SSD starts at 500 ms into the trial and is then adjusted by participant performance. Specifically, SSDs are increased if the participant was able to accurately stop in the prior stop trial , and decreased if they were not . The value by which the SSD increases or decreases is determined by the ‘step size’, which by default is 25 ms, but can be adjusted to any value in the Additional Parameters dialog box. This staircase procedure aims to enable the identification of the SSD that results in a participant being able to inhibit their response only 50% of the time  = .50) and is carried across blocks. For the ‘fixed’ option, the SSD on each trial will be selected by using the corresponding value in the ‘fixedStopTime' column of the relevant condition files .Data files are saved regardless of whether the participant completes the task , limiting unwanted data loss. The naming convention for all files is ‘ID_OSARI_yyyy_mo_d_hhmm’, where ID = participant ID, yyyy = year, mo = month in string format, d = day in numeric format, h = hour and m = minute. The unique timestamp provided to each data file enables multiple data collection sessions with the same participant ID. Two directories are generated for data output – ‘data_txt’ and ‘data’.The ‘data_txt’ directory contains a single ‘.txt’ file compatible with the supplementary analysis script . The column headers in this file are as follows: ‘id’ = participant identification, ‘block’ = index of current block (per block type), ‘trialType’ = current block label, ‘trial’ = trial number within block, ‘signal’ = signal type , ‘response’ = response type , ‘ssd’ = current SSD , ‘rt’ = response time in seconds . This output file is nearly identical to the output of the STOP-IT task, with the exception of the column header ‘trialType’.https://www.psychopy.org/general/dataOutputs.html).The ‘data’ directory contains three files for additional information: ‘.csv’, ‘.psydat’ and ‘.log’ file. These are the default data files generated through PsychoPy’s experiment handler and are intended for the advanced user and debugging requirements. The ‘.log’ file contains chronological information on what occurred during the experiment . In OSARI the logging level is set to DEBUG which provides the most detailed level of logginghttps://github.com/teamOSTAP/BASTD for installation guide). BASTD was developed using the R programming language , version 4.0.3. BASTD has two main functions for analyzing OSARI data: ‘BASTD_analyze’ and ‘BASTD_visualize’. For those less familiar with R, there is a basic ‘how to’ script available (see ‘howto.R’ file). Additionally, an installation-free version of BASTD is also available as a Shiny App (see: https://bastd.shinyapps.io/shiny_bastd/).The .txt files contained within the ‘data_txt’ directory can be analyzed and visualized using the accompanying open-source Batch Analysis of Stop signal Task Data (BASTD) package in R  and ‘task’ . BASTD_visualize plots the data. Like BASTD_analyze, the BASTD_visualize function only requires the same two statements: data and task. See Fig. The use of stop-signal tasks to assess behavioral inhibition has increased dramatically over the past two decades. While many investigators have favored the use of choice-reaction variants of the stop-signal task, an increasing number of studies have adopted ARI tasks. An openly available ARI variant of the stop-signal task could encourage widespread use and could facilitate cross-study standardization. Here, we outline OSARI, allowing future investigators to easily implement and adapt the task for their desired application. Further to this, we provide an accompanying R package to batch analyze the output data saved from each participant (BASTD). With the publication of OSARI, future investigators will now have the freedom to choose the task that best suits their specific use case. Having provided the motivation for the development of OSARI, and details on how to run and analyze performance from the task, we now discuss the general and advanced considerations of task use.R = 0.48; R2 = 0.23, p = 0.025). The low shared variance between SSRTs estimated from performance on CR stop-signal tasks and ARI tasks could be due to several factors, including mode of response , within-individual variability of SSRT, implementation of inhibition at different points of the motor hierarchy, degree of context independence violations and/or ‘type’ of inhibition being measured.Currently, choice-reaction stop-signal tasks are being used far more prevalently than ARI tasks , completed after the ‘practice go block’. The test go block provides a measurement of how participants perform on the go task before the inclusion of stop trials. A comparison of the mean and standard deviation of the go trial RTs in the ‘test go block’ and in the ‘test mixed blocks’ can be used to provide a measure of proactive inhibition , it is more accurate to index the start rather than end of an action, since it removes the latency between action initiation and action termination. Second, given that the visual stimulus is a vertically filling bar, performing a vertical button release is congruent from a visuospatial perspective . For a more comprehensive comparison and discussion of RTs between button release and button press in ARI tasks, see the work by Leunissen and colleagues  is based on the idea that step sizes should ideally be of a size that allows the stop trials to sample across the necessary range of SSDs to determine the inhibition function  and SSRT for most participants. To illustrate the importance of this, consider a step size that is too large , this may only give us stop trials where a participant’s probability of responding is zero  or one , preventing estimation of the entire inhibition function and thus SSRT. Conversely, if the step size is too small, then the number of stop trials required to reach the SSD where a participant’s probability of responding is 50% (via staircasing) may be too high. A maximum and minimum SSD has also been implemented in OSARI, with the maximum SSD being 775 ms into the trial and the minimum SSD being 50 ms into the trial. The maximum value is to prevent SSDs being presented after where an action should have occurred  and the minimum value is to present some portion of the filling bar, both of which are highly unlikely to be reached.static stimuli , dynamic stimuli are inherent to this task, with the most important stimulus being the vertically filling bar. There are at least two approaches that can be considered for rendering dynamic stimuli and for the purposes of our descriptions below, we term these approaches ‘space’ and ‘time’ approaches. In OSARI, we implement the time method, although we outline both here for the interested reader.Although OSARI implements several space approach for rendering dynamic stimuli, the total distance a stimulus would have to travel, or ‘fill’, within a given duration must be determined prior to the stimulus presentation. Based on the default OSARI parameters, the total distance the filling bar has to travel is 15 cm in 1000 ms . From this we can calculate the distance the stimulus must travel in each frame. If we are using a 60 Hz monitor, the total distance our filling bar must travel per frame is:In the space approach is dependent on consistent monitor refresh rates, which can be problematic if frame rate is not reliable. For example, if a large number of background processes are running, frames can be ‘dropped’. In OSARI, frame dropping may also result in the filling bar never actually achieving its full ‘end of trial’ height, since the filling bar would not be rendered on the dropped frame. The time approach offers one approach to avoiding this issue.From this, the total distance our filling bar would travel per screen refresh is 0.25 cm 15 * [(1/60) / 1]. The time approach, the total time it should take for a stimulus to move the required distance  is first determined. Using OSARIs default parameters, the total time it should take for the filling bar to fill from bottom to top is 1000 ms. In the time approach, the start time of each trial is recorded as well as the time at the start of each subsequent frame with the time elapsed since the start of the trial used to determine where the top of the filling bar should be drawn. More specifically, the position of filling bar would be calculated as:In the Thus, if the elapsed time at the start of a particular frame is 0.337 s, the height of the filling bar will be 5.055 cm [15 * (0.337 / 1)]. The benefit of this approach is that it is more resilient to unreliable frame rates , since time elapsed since the start of the trial is queried at the start of each frame.time approach was conceptualized to be more robust, this method was selected for rendering the filling bar in OSARI. Still, we recommend users make an effort to limit the likelihood of frame drops where possible. An easy way for users to reduce the likelihood of frame dropping is by limiting the number of background programs running. Users can also assess the reliability of frame duration prior to testing (in PsychoPy v2020.1.2 this can be implemented through using the demos > timing > timeByFrames.py). For the most accurate measure of timing, users should measure timing of stimulus presentation with their own experimental set up using a photodiode (for a thorough outline of timing measurement for stimulus presentation and response times see Bridges et al., Given that the OSARI provides a first-place framework to move forward in developing understanding of anticipatory response inhibition using ARI tasks. We welcome community development via GitHub


While it has long been understood that the human mind evolved to learn language, recent studies have begun to ask the inverted question: How has language evolved under the cognitive constraints of its users and become more learnable over time? In this paper, we explored how the semantic change of English words is shaped by the way humans acquire and process language. In Study 1, we quantified the extent of semantic change over the past 200 years and found that meaning change is more likely for words that are acquired later in life and are more difficult to process. We argue that it is human cognition that constrains the semantic evolution of words, rather than the other way around, because historical meanings of words were not easily accessible to people living today, and therefore could not have directly influenced how they learn and process language. In Study 2, we went further to show that semantic change, while bringing the benefit of meeting communicative needs, is cognitively costly for those who were born early enough to experience the change: Semantic change between 1970 and 2000 hindered processing speeds among middle-aged adults (ages 45–55) but not in younger adults (ages <25) in a semantic decision task. This hampering effect may have, in turn, curbed the rate of semantic change so that language does not change too fast for the human mind to catch up. Taken together, our research demonstrates that semantic change is shaped by processing and acquisition patterns across generations of language users.The online version contains supplementary material available at 10.3758/s13421-022-01331-0. While ochange after their emergence, which is the scope of the current study.What factors make some words change their meanings to a greater extent than others? Our approach to this question follows a Darwinian view that considers language as a complex adaptive system that evolves under the selection pressure of human cognitive constraints over generations of language users  that make a word more susceptible to semantic change than others  for words with many distinct meanings (homonyms) than words with few or related meanings in semantic tasks  but not by younger adults (ages 18–25), affected the semantic processing of older and younger participants. Based on previous research showing that slower processing speeds among middle-aged adults could be attributed to interference and information accumulation in long-term memory  is related to semantic change. Since such tasks tend to show strong effects of familiarity to the word form .Study 2:woman  remained the same over the past 200 years, our approach to word meaning would suggest that the meaning of women has changed because its connotation, reflecting the rising socioeconomic status of women, has become increasingly associated with characteristics traditionally perceived to only belong to men  in accordance with their co-occurrence relationships .One potential weakness of SVD is that large semantic change may be an artifact of change in frequency: Because the contexts in which low frequency words appear in may be less representative, estimates of their semantics could be unreliable. However, when analyzing Hamilton et al.’s  word embWe obtained diachronic word embeddings trained on the Google Ngram Corpus from Li et al. , and diavi, vj represents a pair of words from the corpus. p corresponds to the empirical probabilities of word co-occurrences within a fixed-size sliding window of original text. As compared to co-occurrence counts, PPMI penalizes high-frequency words  that were used in a wide range of contexts and favors word pairs that frequently appeared together but not with others . Forcing PPMI values to be above zero ensures that they remain finite, and this has been shown to improve results  of a given word can be quantified aswi in year T. The historical embedding is aligned to its modern embedding using orthogonal Procrustes , and car (0.41).where happy is relatively stable in its semantics over the past 2 centuries. In contrast, gay, car, and broadcastgay changed  roughly in the 1950s, whereas the semantic change of broadcast (from “spread of seed” to “spread of information”) took place earlier in the 1920s, and semantics of car (from “wheeled horse-drawn vehicle” to “automobile”) changed gradually over the entire 19th century.Figure r = .76; Brysbaert & Biemiller, In Study 1, we tested hypotheses H1.1, H1.2 and H1.3. The materials we used in both studies are summarized in Table For each corpus, we investigated how semantic change was related to AoA, semantic processing, and lexical recognition in three regression models where semantic stability was regressed on AoA, response time of either lexical decision task or semantic decision task, and other lexical-semantic variables such as log frequency, length, emotionality, arousal, and concreteness that are known to correlate with lexical retrieval , which measures how much the variance of a regression coefficient is inflated due to multicollinearity in the model. We computed VIF for each independent variable. The smallest possible VIF value is 1, suggesting complete absence of multicollinearity. As a rule of thumb, a VIF value that exceeds 5 indicates a problematic amount of collinearity . The results do not completely align with reaction speed. For the Google Ngram Corpus, higher accuracy in both lexical decision and semantic decision task predicted greater semantic stability. However, for the COHA, higher accuracy in semantic decision task only predicted greater semantic stability when reference year was before 1880. As compared with reaction time, accuracy rate is a less informative cue to the efficiency of lexical and semantic processing because these tasks are very easy to native speakers and consequently variance in accuracy rates is very small .In Study 1, we quantified semantic similarity by comparing a word’s meaning in year 1800 to its meaning in year 2000. This allowed us to focus on semantic change that were not directly experienced by people today. However, when semantic change occurs during one’s lifetime, it may make it harder to process the meaning of words because updating words with new meaning could be cognitively costly . Since there is no existing database that includes the performance of both younger and middle-aged adults on the semantic decision task, we conducted an experiment to obtain this data ourselves. The research was conducted with ethics review board approval from the Max Planck Institute for Human Development. We provide our data online (https://osf.io/gw8vj/).To answer the question of whether semantic change comes with a cognitive cost, we studied whether semantically unstable words, when compared to semantically stable words, are harder for middle-aged adults to process, but not younger adults. We were unable to do this using the data in Study 1 because the English Lexicon Project and the Calgary Semantic Decision Project recruited participants from an undergraduate student population. Therefore, in Study 2 we use lexical recognition data from the English Crowdsourcing Project  > 0.8, whereas semantically unstable words were selected from words with stability1970,2000 (w) < 0.65  from Prolific, a crowdsourced data collection platform for psychological research. Each participant responded to each of the 200 words that appeared on the computer screen in random order and decided whether the word was “concrete” or “abstract” by clicking ‘Z’ on the keyboard to indicate abstract or ‘M’ to indicate concrete. The response time was recorded. A randomly selected list of 20 words (10 abstract and 10 concrete) from the stimuli list were used as practice trials for participants to familiarize themselves with the task. We excluded words used in the practice trials from the analysis. The final number of words included in the analysis was 180.Since Study 2 explores the effect of semantic change throughout the lifetime on word processing and recognition, we regressed semantic stability on semantic processing reaction times and lexical recognition reaction times together with other related variables including log frequency, length, emotionality, arousal, valence, and concreteness. To explore whether middle-aged adults were more sensitive to semantic stability, we also included the participant’s age in the regression model. Unlike Study 1, in which reaction time was aggregated by words , in Study 2, we analyzed the unaggregated, trial-level data using linear mixed effects models. We included both participant and word as random intercept effects. The participant random effect controls for an individual’s idiosyncratic factors underlying responses to all words by the same participant. The word random effect controls for the common factors driving response time from all participants to the same word. In the mixed effect model that predicted lexical recognition, we only included the word random effect and not the participant random effect because the average number of people who responded to the same word was too low .b = −20.8), t(171) = −3.19, p = .002. In contrast, there is no significant main effect of semantic stability on lexical decision performance (b = −2.42), t(5296) = −1.23, p = .218).Using two different datasets from the semantic decision task and lexical decision task , our trial-level regression analysis in Study 2 mirrored our finding in Study 1 (see Table SD = 56.8) to process a semantically unstable word. In contrast, younger adults on average took 972 milliseconds to process a semantically stable word, and only 12 additional milliseconds (SD = 60.6) to process a semantically unstable word. The additional processing time people spent on processing semantically unstable words  is an indicator of cognitive cost imposed by semantic change  = −4.48, p < .001.Next, we tested Hypothesis 2.1 regarding whether semantic change slows down processing speed for middle-aged adults but not for younger adults. First, for each participant, we computed the mean of reaction time of semantically stable words and of semantically unstable words. On average, it took middle-aged adults 1,003 milliseconds to process meaning of a semantically stable word, and 46 additional milliseconds , t = −5.17, p < .001. A simple slope analysis .Moreover, using a regression model with three-way interaction effect among semantic stability, age group, and concreteness Table , Model 3sis Fig.  shows thb = −38.8, SE = 9.4, t = −4.14, p < .001) than abstract words , suggesting that semantic change imposes greater cognitive cost on concrete words than on abstract words.Lastly, we explored whether this semantic-change-imposed processing disadvantage among middle-aged adults was driven by concrete words or abstract words. In a simple slope analysis exploring the three-way interaction between age, concreteness, and semantic stability Fig. , we founThe present study examined how the semantics of English words evolved under the constraints of human cognition. We first found that cognitive constraints in language acquisition and processing shaped the evolution of a word’s semantics: words acquired later in life or that are more difficult to process in a semantic decision task are under greater selection pressure to change their meanings. Semantic change is an effective strategy for language to meet the everchanging communicative need to express new meanings. However, it is likely to come with a cognitive cost because semantic change is the process of reestablishing the association between meaning and lexical form in the mind of language speakers. We tested this idea in Study 2 and found supporting evidence for it: Semantic change of words, if and only if the change has occurred during one’s lifetime, makes it harder to process the meaning of words.Using contemporary data on how people process and learn words, our analysis in Study 1 found an association between semantic change and cognitive constraints. It is important to note that since semantic stability in Study 1 was quantified by comparing the contexts of words between year 1800 and year 2000, the historical semantic change of words is largely obscure to most participants who took part in the data collection as they were typically young, college-aged adults recruited from psychology research subject pools. In other words, participants should only be familiar with the modern meanings of words, and it is unlikely for one’s learning history and language performance to be directly influenced by a semantic history that they do not have easy access to. This line of reasoning precludes the conclusion that long-term, historical changes in the meaning of words have strong, direct, measurable effects on the learnability and processing of words. We suggest that it is more plausible to conclude that it is the cognitive constraints associated with learning and using words  that largely shaped the extent of semantic change among words. Specifically, words that are acquired later in life and are more difficult to process in the semantic decision task went through greater semantic change over history.In Study 1, we showed how cognitive constraints in word learning and processing make some words more likely to change their meanings than others. This result introduced a related question: whether semantic change comes with a cognitive cost—that is, an increased difficulty in processing word meanings because one has to update the mapping between lexical form and meaning. To answer this question, we deliberately designed Study 2 to tease apart the influence of historical semantic change and semantic change within one’s lifespan. This was done by yoking lifespan semantic change to year 1970 so that semantic change could only be directly experienced by middle-aged adults but not younger adults in our study. The results of Study 2 indicated that people were indeed sensitive to changes in a word’s semantics that occurred within their lifetimes. Middle-aged adults, but not younger adults, were slower at processing words that changed their semantics during their lifetime. This suggests that higher rates of semantic change can be costly to cognitive processing. This may be because updating words with new meanings can be cognitively costly , we emphasize that language evolution involves trade-offs and suggest that this approach ultimately leads to greater long-term benefits such as maintaining the semantics of the core lexicon while enabling languages to be flexible enough to adapt to the emergence of new meanings.In the present study, we focused our analysis on words that remained in use from 1800 to 2000; otherwise, the computation of semantic stability between 1800 and 2000 would not be possible. That necessarily implies that words that “died” during this period were excluded from the analysis. We speculate that many of these dead words were difficult to learn and process and did not manage to reassociate themselves with new meanings that could have allowed them to survive into the present day. One potential follow-up is to investigate how these dead words differ from the remaining words in terms of learnability, which can be approximated using modern day estimates of the concreteness of words