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PLOS One logoLink to PLOS One
. 2020 Dec 22;15(12):e0242881. doi: 10.1371/journal.pone.0242881

Development and initial validation of a simple tool to screen for partner support or opposition to HIV prevention product use

Elizabeth E Tolley 1,*,#, Seth Zissette 1,2,#, Andres Martinez 1,#, Thesla Palanee-Phillips 3,, Florence Mathebula 3, Siyanda Tenza 3, Miriam Hartmann 4, Elizabeth T Montgomery 4,
Editor: H Jonathon Rendina5
PMCID: PMC7755213  PMID: 33351805

Abstract

In HIV prevention trials, male partners have influenced women’s ability to adhere to investigational products, including antiretroviral (ARV) containing vaginal rings. Validated scales can be useful tools to systematically measure complex constructs, such as those related to male partner engagement. Although multiple scales exist to assess physical, psychological and sexual violence within intimate relationships, fewer scales focus on supportive behaviors within these relationships. Our intervention involved development of a Healthy Relationship Assessment Tool (HEART) that assessed both positive and negative aspects of male partner involvement in women’s HIV prevention. We identified and refined 127 potential items, representing intimate partner violence, agency and social support. A structured survey, including potential items and other sociodemographic and behavioral variables was administered to former microbicide trial and non-trial participants. We conducted an exploratory factor analysis (EFA) to identify a reduced set of constructs and items to screen women who might experience social harms or benefits from vaginal ring use. We examined associations between constructs and with other survey variables to assess content and construct validity. In a subset of 10 women who participated in the survey and qualitative interviews, we used qualitative data to predict survey scores. We retained five constructs with theoretical relevance and good-to-strong reliability for the tool, including: Traditional Values; Partner Support; Partner Abuse & Control; Partner Resistance to HIV Prevention; and HIV Prevention Readiness. Predicted associations between HEART constructs, and correspondence between participants’ qualitative data and HEART scores were generally correct, while those between constructs and other sociodemographic variables were more mixed. Initial validation of the HEART tool was promising. The tool will be used during the CHARISMA pilot study at the Johannesburg MTN 025/HOPE site and validated as part of a randomized controlled trial of CHARISMA within a PrEP demonstration project. Beyond clinical trial settings, HEART could assist PrEP or antiretroviral treatment (ART) providers with an easy-to-administer tool to identify risk and tailor risk reduction, empowerment and adherence counseling for microbicides, PrEP or ART related services.

Introduction

Although the number of people newly infected with HIV has declined over the past two decades [1], young African women continue to be at risk of HIV and are, in fact, one of the few populations that have not benefited from recent declines in HIV incidence [2]. Of the 1.7 million new HIV infections in 2016, almost half (48%) globally were in women, with 59% of infections occurring among young women between 15–24 years of age [3, 4]. In sub-Saharan Africa, 56% of new infections were in women, and 67% of new infections were comprised of young women aged 15–24 [5]. Research suggests that women’s continued risk of HIV stems from inequitable gender norms and the threat of intimate partner violence (IPV) that both promote high-risk sexual relationships and limit options for HIV prevention behaviors [6, 7].

Despite the promise of new HIV pre-exposure prophylaxis (PrEP) products, women continue to face challenges related to PrEP adherence. While clinical trials of various regimens of oral PrEP have shown moderate to high levels of protection in HIV-discordant couples and men-who-have-sex-with-men (MSM), several phase 3 trials of oral and vaginal PrEP products among African women failed to show evidence of effectiveness [8]. Across these trials, product adherence has been reportedly low [911]. A number of factors have been associated with low or intermittent adherence including low perceived risk perception [12], ambivalence towards research and/or use of investigational products [13], and challenges related to managing social relationships [1416]. Women’s approaches to engaging their male partners in their HIV prevention product use and trial participation have ranged from open communication to gradual disclosure to entirely covert use [17]. Indeed, in some cases, participating in an HIV prevention trial has even enhanced couple communication [18]. Non-disclosure has been attributed either to fearing a partner’s negative and potentially violent reaction or to a belief that the decision for PrEP use and/or trial participation is the woman’s alone to make [17]. Evidence from HIV prevention and treatment trials have reported improvements in adherence among those who have disclosed [19, 20], but challenges with disclosure to partners may impede adherence [20, 21]. And, while reports of social harms, including intimate partner violence (IPV) have been relatively infrequent in PrEP trials, women who reported recent IPV had a higher risk of low adherence than those who reported no IPV or IPV episodes that occurred in the more distant past [22, 23].

Given male partners’ variable role in either enhancing or inhibiting women’s use of HIV prevention products, there is a need for simple screening tools that could help trial implementers or indeed PrEP providers to better tailor PrEP counseling and adherence support to women’s sexual partner contexts. Nevertheless, to our knowledge, no tools exist to date that aim to assess the full spectrum of partner engagement, from supportive to abusive. Our study set out to develop such a tool.

Materials and methods

We developed a Social Benefits-Harms Tool, later referred to as the Healthy Relationship Assessment Tool or HEART, as a preliminary step in the development of a couples’-based HIV prevention intervention called the Community Health Clinic Model for Agency in Relationships and Safer Microbicide Adherence Pilot study, or CHARISMA. Validated scales can be useful tools to systematically measure complex constructs [24, 25], such as male partner engagement. Therefore, the HEART was conceptualized as a set of brief scales to measure aspects of a woman’s own agency, her attitudes towards more traditional gender norms that might dampen this agency, and the degree to which her primary sexual partner was perceived as supportive, controlling or violent. Within the CHARISMA intervention, the HEART was intended to assist lay counselors in determining which of several counseling modules and/or referral mechanisms should be offered based on the potential benefits or harms a participant might encounter from using the vaginal ring. (This tool, as a component of the CHARISMA behavioral counseling intervention, would be piloted within the MTN-025/ HOPE trial of the dapivirine vaginal ring.) In this paper, we describe the development, including finalization of construct and item content, and initial validation of the tool.

Project design and objectives

The goal of this study was to develop and provide initial validation for a set of scales that could be used within a clinical context to identify aspects of a woman’s primary relationship that might facilitate or inhibit her consistent use of an HIV prevention product. We followed a standard scale development process [25]. This entailed identifying a pool of potential items and underlying constructs that would be theoretically associated with our intended measure; conducting rounds of cognitive interviews to ensure that potential items were salient, easy to understand and to respond to; administering a survey with the refined items and other potentially associated variables to enable exploratory factor analysis and psychometric evaluation of the resulting constructs; and using qualitative data to predict survey scores in a subset of women to further assess construct validity.

Theoretical framework for HEART

As described elsewhere [26], we reviewed the scientific and gray literature to identify validated scales or other tools that measured various aspects of intimate relationships [27], including agency [28], social support, as well as partner abuse and violence [29]. We gave precedence to scales or tools used in African contexts. IPV measures generally took one of two approaches: observable or reportable physical behaviors (e.g., hitting, pushing, or kicking), or perceptions of psychological abuse (e.g., embarrassing, withholding financial support, or blaming). Many scales contained a battery of 15–40 items assessing perpetration of violent acts (ever or at stated intervals) by men against women; some were bi-directional (e.g., also women against men). A few tools, such as the four-item “HITS” questionnaire (Hurt, Insulted, Threatened with harm, and Screamed), were much shorter and meant to be administered in clinic settings [30]. Fewer social support measures were identified, and those we found usually measured situation-specific types of social support (e.g., partner supportive behaviors during the prenatal period) [31]. Our review confirmed our initial hypothesis that a new tool would be needed to represent both the supportive as well as abusive or harmful dimensions of an intimate relationship without being overly time consuming to administer.

Based on the literature review, we identified 135 potential items for the HEART representing agency, social support or IPV. Items were translated into isiZulu. We conducted three rounds of cognitive interviews with a total of 25 women with and without prior experience participating in clinical trial research and/or past experiences of violence to assess ease, comprehensibility, and relevance of items. (Women’s eligibility was the same as described below for the HEART survey.) Interviews were conducted in either English or isiZulu, or a mix of both languages. By the end of the third round of cognitive interviews, eight items that were reported to be embarrassing or duplicative had been removed, and some items that had unclear wording or difficult answer choices were edited.

HEART survey procedures

Between April and September 2016, we administered a cross-sectional survey to 309 women in Johannesburg, South Africa. Eligible participants were aged 18–40, residing in communities where previous HIV prevention trials (including the MTN-020/ ASPIRE vaginal ring trial [11], the MTN-003/VOICE vaginal gel and oral PrEP trial [10] and the FACTS vaginal gel trial) [32] had been conducted, not currently participating in other related research studies, and willing and able to provide written informed consent. We recruited both former HIV prevention trial participants (FTPs) who had given permission to be contacted at study exit for future research and women recruited from adjacent non-research public clinics (trial-naïve participants, TNP) through staff led recruitment efforts. The survey included 127 theoretically-relevant items, refined through the cognitive interview process. Responses for most potential HEART items were based on a 6-point scale ranging from “1 = Disagree A Lot” to “6 = Agree A Lot”. In addition, we included sociodemographic and self-reported risk behavior variables. The survey was administered on tablets by trained social scientists in a private location in the Hillbrow Wits RHI clinic. Participants had the option to take the survey in English, isiZulu, or to switch between languages for different items.

Prior to implementation, the study was reviewed and approved by the FHI 360 Protection of Human Subjects Committee and the Wits Human Research Ethics Committee in Johannesburg. Written consent was obtained from each participant in their preferred language of English or Zulu.

Survey analyses

Our initial goal was to recruit a minimum of 400 survey participants with a minimum of 250 former trial participants and 150 similar community members. However, due to a shorted recruitment time and lower than expected access to former—but not current trial participants, we terminated survey recruitment after enrolling 309 participants.

Item and dimension analysis

Following survey completion, we examined the response distribution, means, standard deviations, skewness and kurtosis of all items. We first eliminated four highly skewed items having a mean score below 1.4 or above 5.8, as the floor and ceiling effects demonstrated by these items produced virtually no variability between participants. We then conducted an exploratory factor analysis (EFA) including all non-excluded scale items to determine the number and content of underlying domains for the HEART and to reduce the overall number of items that represented each factor. We followed standard EFA procedures, including use of Promax rotation (allowing for cross-loading of items on multiple factors) and retention of items with a loading of 0.4 or higher on a resulting factor. We examined the eigenvalues and Cattell’s scree plot to determine the number of factors to extract, and the item-to-total and inter-item correlations to determine which items to retain. We assessed the internal consistency of our resulting factors, deleting any items that did not maintain or increase a factor’s Cronbach’s alpha. (Note: Our final solution contained only two items that had similar and relatively low cross-loadings. We retained the two items on the factor based on our analysis of internal consistency.)

Initial construct validation

We assessed construct validity in several ways. First, based on the resulting factors, four geographically distinct groups within our project team developed separate a priori predictions about the direction and strength of correlations (i.e., significant positive association, significant negative association or non-significant) between the potential scales and 10 relevant sociodemographic and behavioral variables, as well as among the resulting scales themselves. Our four groups included two US-based FHI 360 team members, two US-based RTI members, one SA-based RTI member and three SA-based Wits RHI members. Each team submitted their predictions which were tabulated prior to analysis. We then examined the associations between the factors and the theoretically relevant variables included in our survey, using Pearson product-moment correlation statistics. We considered evidence of “as-hypothesized” relationships to provide initial validation that our tool is performing as needed.

Parallel qualitative interviews

Qualitative, in-depth interviews (IDIs) were conducted with 10 survey participants to obtain input on acceptability, feasibility and perceived effectiveness of intervention components proposed for CHARISMA. As many of the topics discussed in interviews thematically related to domains (and often, specific items) on the HEART, we used participants’ IDI data to make predictions about their scale scores on HEART and to determine whether any salient constructs pertaining to the influence of partner dynamics on PrEP use were missing from the tool.

IDI analysis

Transcripts were thematically coded in NVivo by three independent coders, following a basic codebook that included the five HEART constructs and, within each construct, “high”, “medium” and “low” sub-codes to indicate whether the text segment would predict a high, medium or low score on the construct. The coders double-coded one of the ten interviews and met to determine whether they had applied the same text segments to the five broad HEART codes, as well as specific sub-codes. Differences were reconciled through discussion between all coders to standardize the use of codes during the coding process. For each of the 10 IDI participants, coders then examined the frequency and content of text segments to make predictions about whether they would score “high” (≥1 standard deviation (sd) above the mean), “medium” (within 1 sd from the mean), or “low” (≤ 1 sd below the mean) on each scale. For each of the five constructs, coders assessed the number of correct predictions out of a possible 10 participant scores.

As a second level of analysis, a codebook containing codes for each item in the HEART was developed and applied to specific items within the tool. This step was used to identify any noteworthy concepts that arose consistently across participants but were not captured by an existing item. We analyzed the rates at which existing items in the HEART were reflected by natural discussion in the interview transcripts, identified items that were not reflected by any discussion and any potential new items that were discussed but were not currently a part of the HEART.

Results

Sociodemographic information

Most participants in our survey (79%) had not previously participated in HIV prevention clinical research (Table 1). Those with prior trial experience were most likely to have taken part in the MTN-020/ ASPIRE vaginal ring trial (88%), although some participated in trials for vaginal gels or other products. FTPs were, on average, several years older than TNP, more likely to be living with a partner and more likely to earn an income.

Table 1. Socio-demographic information of surveyed participants, overall and by trial experience subgroup.

Total(n = 309) TNP(n = 245) FTP(n = 64)
Years of age (mean) 27 26* 29*
% % %
Ever participated in an HIV prevention clinical trial 21 n/a 100
Type of trial:
 Vaginal ring 88
 Vaginal gel n/a 5
 Other (not oral PrEP) 8
Type of residence:
 Free-standing or town house 33 33 30
 Flat 44 45 42
 Single room 15 14 19
 Informal or other housing 9 9 9
Currently living with:
 Parent(s) (mother and/or father) 25 26 22
 Other family (non-parent) 29 29 28
 Primary sex partner 21 18* 30*
 Own children 26 24 30
 Other 28 31* 17*
Have children 68 66 77
Number of people living in household (mean) 4 4 5
Highest level of education:
 Primary or less 2 1 2
 Secondary, not complete 26 27 22
 Secondary, complete 37 34 48
 Some college or university 24 27 14
 College or university, complete 12 12 14
Earns an income 36 32* 52*

*p < .05.

As presented in Table 2, less than a third of participants (28%) were sure that their partners did not have sexual partners and most participants (72%) reported having discussed condom use with their partner at last sex. Very few participants (8%) reported feeling persuaded or coerced into having sex during their most recent sexual encounter.

Table 2. Sexual behavior characteristics of surveyed participants, overall and by trial-experience subgroup.

Total(n = 309) TNP(n = 245) FTP(n = 64)
% % %
Current relationship status:
 Married or living with regular partner 28 24* 42*
 Regular partner(s), not living together 67 71* 52*
 Sexually active, no regular partner(s) 2 2 3
 Not sexually active currently 4 4 3
Has regular sex partner (married, living with or not) (n = 291) (n = 231) (n = 60)
Years with current/regular partner (mean) 5 4 5
With current/regular partner in last clinical trial n/a 78
Regular partner provides financial or material support 85 84 90
(n = 309) (n = 245) (n = 64)
Age of main sex partner (mean) 31 30* 34*
Partner(s) have other sex partners:
 No 29 30 25
 Don’t know 51 48 63
 Yes 20 22 13
Discussed condom use at most recent sex act 72 71 75
Used a condom at most recent sex act 56 58 50
Willingness to have sex at most recent sex act:
 Willing or wanted to have sex 93 91 97
 Persuaded or talked into sex 7 8 3
 Coerced or threatened 1 1 0
 Physically held down or raped 0 0 0

*p < .05.

Analysis of items and conceptual dimensions

We began with 127 potential items and ultimately retained 42 loading onto five factors (Table 3). The final five-factor solution was originally derived from a four-factor solution in which one factor contained a large number of items (28), resulting in an artificially inflated measure of internal reliability. We then conducted a subsequent EFA with this factor, resulting in three sub-factors. We retained these three factors along with two of the remaining factors from the original four-factor solution. The final remaining factor from the original four-factor solution was dropped due to lack of face validity. Overall, the number of missing responses across all items was small. In fact, all but one of the 42 items had at least 305 valid responses, out of a potential for 309. The only item with a substantial amount of missingness was item 5 in the Partner Abuse & Control scale, with only 277 valid responses. While missingness was uncommon, ceiling and flooring effects—demonstrated by limited variation in responses and/or high levels of skewness in the item responses distributions—were common and in some cases substantial. For example, more than half the responses to all the items in the Partner Resistance to HIV Prevention were in the “Disagree a Lot” response option (lowest). Similarly, more than half the responses to all the items in the HIV Prevention Readiness scale were in the “Agree a Lot” response option (highest). Some of the items in the other scales also exhibited limited variability and high levels of skewness (see S1 Table). The flooring and ceiling effects limit the ability of the scales and of the tool more generally to distinguish ‘average’ respondents from one another.

Table 3. Exploratory factor analysis 5-factor solution for development of HEART.

Factor and items Item loading
Factor 1: Traditional Values (a = .84, Scale range+ 13–78)
1. Changing diapers, giving the kids a bath, and feeding the kids is a mother’s responsibility. 0.65
2. I think that a woman cannot refuse to have sex with her husband. 0.62
3. I think that if a man has paid lobola for his wife, he owns her. 0.61
4. A woman should always listen and abide by the word of her husband without questions. 0.60
5. A man should have the final word about decisions in his home. 0.59
6. A real man produces a male child. 0.58
7. I think that if a man has paid lobola for his wife, she must have sex when he wants it. 0.57
8. I think that a man should have the final say in all family matters. 0.46
9. A woman should accept her partner’s wishes—even when she disagrees—to keep the family together. 0.46
10. I only think I am attractive if other people think I am. 0.45
11. I think that there is nothing a woman can do if her husband wants to have girlfriends. 0.42
12. If someone insults a man, he should defend his status with force if he has to. 0.42
13. It’s only rape if a woman fights back. 0.41
Factor 2: Partner Support (a = .81, Scale range+ 10–60)
1. My partner is as committed as I am to our relationship. 0.65
2. I feel comfortable telling my partner that I see things differently. 0.48
3. In general, my relationship has a lot of tension. (reverse scored) 0.59
4. It takes a long time to work out arguments with my partner. (reverse scored) 0.59
5. I feel trapped or stuck in our relationship. (reverse scored) 0.58
6. Arguments with my partner result in me feeling down or bad about myself. (reverse scored) 0.47
7. My partner does what he wants, even if I do not want him to. (reverse scored) 0.42
8. I feel safe in my current relationship. 0.59
9. My partner takes my earning or refuses to give me money when he has money for other things. (reverse scored) 0.48
10. My partner is/will be very supportive of my use of an HIV prevention product. 0.42
Factor 3: Partner Abuse & Control (a = .81, Scale range+ 9–54)
1. My partner slaps, hits, kicks, or pushes me. 0.79
2. My partner chokes, pulls hair, or burns me. 0.77
3. My partner does things to scare or intimidate me on purpose. 0.69
4. My partner makes fun of me or humiliates me. 0.62
5. My partner makes most of the decisions about how the household finances are used. 0.54
6. I feel frightened by what my partner says or does. 0.48
7. My partner won’t allow me to wear certain things. 0.43
8. I can’t seem to make good decisions about my life. 0.47
9. I do not trust myself to make good decisions about my life. 0.41
Factor 4: Partner Resistance to HIV Prevention (a = .80, Scale range+ 5–30)
1. If I asked my partner to use a condom, he would get angry. 0.76
2. If I asked my partner to use a condom, he would think I'm having sex with other people. 0.70
3. If I asked my partner to use a condom, he would get violent. 0.69
4. I cannot tell my partner about HIV prevention product use because he will become angry. 0.61
5. If I asked my partner to use an HIV prevention product, he would get violent. 0.61
Factor 5: HIV Prevention Readiness (a = .68, Scale range+ 5–30)
1. I understand the risks and benefits of HIV prevention product use and have chosen to use them. 0.52
2. Using an HIV prevention product is the right thing to do. 0.58
3. Using an HIV prevention product shows that my partner and I care about each other. 0.63
4. Using an HIV prevention product with my partner will help us communicate better. 0.54
5 HIV prevention products would help me protect myself. 0.41

+ Factor scores were calculated as the sum of the item responses; these ranges reflect that sum. The average available item response was imputed for any missing values.

From a conceptual perspective, the 5-factor solution met the aims of our tool development. It included a 13-item “Traditional Values” construct that elicited attitudes about gender roles and women’s agency to make decisions; a 10-item “Partner Support” construct that included a mix of statements about a partner’s support or lack of support for the relationship; a 9-item “Partner Abuse & Control” construct that included statements about a partner’s physical and emotionally abusive behaviors and two items indicating a woman’s lack of control over life decision; and two 5-item factors, the first indicating “Partner Resistance to HIV Prevention” and the second indicating “HIV Prevention Readiness”. Internal reliability of the items was good (Cronbach’s Alpha 0.80 or higher) for four of the five factors and borderline acceptable for the HIV Prevention Readiness factor (0.68).

Initial construct validation

We provide an example of our independent predictions between the Partner Abuse & Control scale and the other HEART scales in Table 4. Each group’s predictions are stated and indicated by a color (gray for neutral or non-significant, blue for positive and red for negative correlation). Correlations are bolded if they were predicted in both direction and magnitude by at least three of the four project team groups.

Table 4. Predicted correlations between Partner Abuse & Control and other scales and socio-demographic variables.

Variables Correlation Predicted Direction
Group A Group B Group C Group D
Other HEART scales
Traditional Values 0.41* Neutral Positive Positive Positive
Partner Support -0.64* Negative Negative Negative Negative
Partner Resistance to HIV Prevention 0.53* Positive Positive Positive Positive
 HIV Prevention Readiness -0.09 Neutral Negative Negative Negative
Socio-demographic variables
Age 0.13 Neutral Neutral Negative Neutral
 Education -0.39* Neutral Neutral Negative Neutral
 Past clinical trial participation -0.19* Neutral Positive Negative Negative
 Time with partner 0.16* Neutral Neutral Neutral Neutral
 Current partner, last clinical trial -0.48* Neutral Neutral Negative Negative
Partner provides material support -0.12 Positive Neutral Neutral Neutral
 Discussed condom use at last sex -0.01 Neutral Negative Negative Negative
Coerced at last sex 0.24* Positive Positive Positive Positive
 Used a condom at last sex -0.15 Neutral Negative Negative Negative
 Earns own income -0.09 Neutral Negative Negative Neutral

*Statistically different from 0 at a 0.05 Type I error level.

As illustrated, our predictions were generally correct for correlations between the Partner Abuse & Control scale and three of the other scales. However, we were less successful at predicting the magnitude of associations with the sociodemographic variables. For example, fewer than three of the four groups predicted that Partner Abuse & Control was both significantly and negatively associated with education level, past trial participation or being with the same partner who was with them in a past trial. In a similar way, groups more often predicted strong, negative correlations between Partner Abuse & Control and behaviors such as discussing and/or using a condom at last sex, when the correlation was insignificant.

Overall, at least one group correctly predicted the direction and magnitude of the correlations between the scales and with other variables 83% of the time. The ability to correctly predict correlations differed by factor, from at least one group making correct predictions 93% of the time for Partner Abuse & Control to just 71% of the time for HIV Prevention Readiness.

Fig 1 shows the distribution of individual scale scores (down the main diagonal) and the correlation and significance between each pair of scales (top-right). The bottom-left cells visually indicate the direction (positive = blue; negative = red) of the correlation, with the magnitude (low, medium and high) depicted through the shading of each color. We note that Partner Resistance to HIV Prevention was strongly positively skewed and HIV Prevention Readiness strongly negatively skewed. As predicted, Partner Support was negatively associated with Traditional Values (-0.33), Partner Abuse & Control (-0.64), and Partner Resistance to HIV Prevention (-0.52). Also, HIV Prevention Readiness exhibited a positive association with Partner Support (0.27), but a weak association with the other scales (Fig 1).

Fig 1. Distributions of and correlations among HEART scales.

Fig 1

TrV: Traditional Values; PaS: Partner Support; PAC: Partner Abuse & Control; PaR: Partner Resistance; HPR: HIV Prevention Readiness. Upper-right panels contain the Pearson correlation coefficient with the 95% confidence interval in parenthesis. Lower-left panels contain a visual cue for the direction and magnitude of the correlation coefficient.

Comparisons between qualitative text and HEART scores

In Table 5, we provide illustrative quotes, the resulting prediction made by coders and the rationale for making the prediction related to two of the HEART scales (Partner Abuse & Control and HIV Prevention Readiness). During qualitative interviews, women could describe their partner relationships in detail, providing multiple and sometimes contradictory examples of support, control, abuse and how such interactions affected HIV prevention decision-making. Accurate predictions of HEART scales scores based on these more nuanced descriptions would provide additional evidence for each scale’s construct validity.

Table 5. Illustrative quotes from IDIs used to predict HEART score ranges for Partner Abuse & Control and HIV Prevention Readiness scales.

ID Score Prediction Partner Abuse & Control Example Quotes Rationale
1007 Low INTERVIEWER: Can you describe a time when your partner made you feel scared or humiliated?
PARTICIPANT: Nothing. I didn’t feel humiliated or scared. Unless, [when] it was April Fool’s day. He lied that he got into an accident, stuff like that and I was so shocked. And then after fifteen minutes, no, don’t you know that it’s April Fool’s day.
Participant experiences support and trust in her relationship and denies that partner has ever abused her physically or emotionally.
1026 Medium INTERVIEWER: When he teased you about your weight loss, how did you feel?
PARTICIPANT: Irritated, I hated every minute of it. I hated it.
INTERVIEWER: Did you feel humiliated?
PARTICIPANT: Ja in a way, I mean why would you? it’s not funny and he knew I was complaining that I lost a lot of weight. I don’t even want to bring up the conversation about my weight, because I hate it.
INTERVIEWER: Can you describe a time when you were worried your partner might be or was ever violent?
PARTICIPANT: No, never. I’m almost sure he can’t raise a hand.
Participant has experienced some humiliation from partner when teasing her about her weight but has never experienced physical abuse.
1012 High PARTICIPANT: He did it once. Checked my WhatsApp. I felt nervous, because I was chatting with my ex [boyfriend]. Then he asked me, ‘Why are you still WhatsApping with your ex?’
INTERVIEWER: Hmm.
PARTICIPANT: And so, he took my phone and showed me the messages. So, I said sorry. Ja. Like I’m making him feel, he beat me up. So, I said sorry, but I can’t stop chatting with him, because it’s Whatsapp. It’s not like maybe if you broke up with somebody you don’t chat with them. No, you are wrong on that.
NTERVIEWER: Okay. And what did he do?
PARTICIPANT: He beat me with a belt buckle.
Participant experiences abuse due to her partner’s jealousy.
ID Score Prediction HIV Prevention Readiness Example Quotes Rationale
1009 Low PARTICIPANT: Ja, I was a bit worried continuing using the ring. As I’ve said, like I had a problem with infections, thinking maybe it was the ring. Ja, it was a problem until I stopped using it. Participant was worried about ring use and the risks associated with it.
1007 Medium PARTICIPANT: No. I didn’t feel that I was at risk of getting HIV. But the other thing that made me nervous because of we, in the family we have people who died with AIDS, but we’re having others who have lived a long time with AIDS. So that’s the other thing that made me to become nervous. Participant did not feel at risk herself but decided to participate after reflecting on family members who have died of AIDS.
1026 High INTERVIEWER: How could use of an HIV prevention product make you feel closer to your partner?
PARTICIPANT: It can definitely improve on being closer to their partner because there’s no fear.
INTERVIEWER: Fear of what?
PARTICIPANT: Even if you know that, chances are, he’s cheating, he’s doing stuff, but you are not unprotected, hence there’s no fear. You just let yourself be.
Participant believes that use of an HIV prevention product can improve relationship with partner.

Table 6 presents the number of text segments for each participant that were coded as low, medium or high for two HEART domains, as well as our final score range prediction, and the actual score range for that participant. (Illustrative quotes and predicted versus actual scores for all scales are available in the supplemental materials.) Predictions were highly accurate for most of the scales, at 80% for the Partner Abuse & Control, Traditional Values, and Partner Support scales and 70% for the Partner Resistance to HIV Prevention Scale. The final scale, HIV Prevention Readiness, experienced greater discrepancy, with only 30% of predictions based on thematic analysis matching actual scores. Our ability to predict the strength and direction of scores on the Traditional Values, Partner Support, Partner Abuse & Control, and Partner Resistance to HIV Prevention scales supports the construct validity of these four.

Table 6. Predictive text frequencies and comparison of predictions to survey score range, by IDI.

ID Low Score Medium Score High Score Overall Overall Correct?
References (%) References (%) References (%) Score—Prediction Score—Actual
PARTNER ABUSE & CONTROL PREDICTIONS
1006 8 59 33 Medium Medium Yes
1007 65 35 0 Low Low Yes
1009 33 67 0 Medium Low No
1011 100 0 0 Low Low Yes
1012 8 14 78 High High Yes
1018 0 0 100 High Medium No
1019 24 76 0 Medium Medium Yes
1023 22 78 0 Medium Medium Yes
1026 7 85 9 Medium Medium Yes
1032 6 94 0 Medium Medium Yes
HIV PREVENTION READINESS PREDICTIONS
1006 38 41 21 Medium High No
1007 32 54 14 Medium High No
1009 13 27 60 High Low No
1011 0 28 72 High Medium No
1012 0 20 80 High Medium No
1018 41 59 0 Medium Medium Yes
1019 21 0 79 High High Yes
1023 0 49 51 High High Yes
1026 0 0 100 High Medium No
1032 0 27 73 High Medium No

Finally, for most items in the five HEART scales, we identified multiple matching examples of text segments in our qualitative data. All items in the Partner Support scale were represented by quotes from at least one and as many as all 10 IDI participants, while only three of the five items in the Partner Resistance to HIV Prevention scale were represented by similar qualitative text segments. The item-level qualitative analysis also identified other potential items that fit within the five HEART constructs but didn’t clearly match existing items. For example, some participants identified concerns about trial procedures (e.g., HIV tests and other clinic procedures), or product-specific concerns (e.g., worry that the vaginal ring will affect sex life) as discouraging their readiness to use HIV prevention products. Table 7 provides examples of illustrative quotes for seven of the nine items retained on the Partner Abuse & Control scale. (Examples for existing and proposed items for other scales can be found in the supplemental materials.)

Table 7. Examples of specific Partner Abuse & Control scale items reflected in the qualitative IDIs.

Item # of Transcripts Example Quote
1. My partner slaps, hits, kicks, or pushes me. 6 INTERVIEWER: How often did it happened that he slaps up? PARTICIPANT: It happened once because I drank alcohol without his permission. He slapped me.
2. My partner chokes, pulls hair, or burns me. 1 INTERVIEWEE: Yah, he pulled me with the hair, and the twist fell down, like it was miserable, my uncles were not there and my brothers were not there….no one was at home, it was just my little sisters….they came out…I started shouting and my mother called him asked him “what is wrong with you and why are you abusing my child so much
3. My partner does things to scare or intimidate me on purpose. 3 INTERVIEWER: Okay. How did you respond when your partner said if you cheat on him, he will kill you? PARTICIPANT: I said, “Kill me”, I told him that, “You can kill me. If you want to kill me kill me, I’m not scared of you”.
4. My partner makes fun of me or humiliates me. 3 INTERVIEWER: Another difficult thing is when men are frightening or saying humiliating things to women, can you describe a time when your partner made you feel scared or humiliated? PARTICIPANT: I know he used to just tease me about my weight, because I lost a lot of weight as compared to when we met, like it was irritating, it was annoying me, just that.
5. My partner makes most of the decisions about how the household finances are used. 8 INTERVIEWER: Financial decisions and control can be another difficult thing to negotiate with a partner. How do you and your partner deal with finances? PARTICIPANT: When it comes to the money, I don’t have much to say because I never ask him ‘How much do you get paid?’ because he usually gets paid every week… But I do get money to eat, money to buy clothes. Actually, I do not normally buy clothes. The only thing that I do, I use an account. So, I don’t have much to say when it comes to money.
6. I feel frightened by what my partner says or does. 2 PARTICIPANT: My partner made me feel scared one day because he told me that if I could cheat on him, he would kill. So, I told my mom “Mom, he said if I could cheat on him he would kill me.” I was nervous asking myself “What would he kill me with?”
7. My partner won’t allow me to wear certain things. 2 PARTICIPANT: When I visited my family or relatives. When I’m wearing leggings or something short, he would say “Can’t you see that you are have undressed?" So, I feel he is controlling on such things.
8. I can’t seem to make good decisions about my life. 0 N/A
9. I do not trust myself to make good decisions about my life. 0 N/A

Discussion

These analyses, based on data from the scale survey used to develop the HEART tool, support overall validity of four of the five HEART scales. Retained factors and composition of items on each scale made theoretical sense and were confirmed by the moderate to strong internal reliability of all but the HIV Prevention Readiness scale.

Additionally, evidence for construct validity of four of the five scales was shown by our quantitative correlation analysis. All but the HIV Prevention Readiness scale correlated in predictable ways with other scales. Our project groups had less agreement on the magnitude of correlations between scales and other sociodemographic and psychosocial variables. It is possible that responses to some of these variables (e.g., discussed or used a condom at last sex) were themselves influenced by social desirability bias. Nevertheless, our predictions were more often than not in the correct direction. In addition, our ability to make accurate predictions about how women scored (low, medium or high) on four of the five HEART scales based on their qualitative interviews, as well as the identification of text segments in multiple IDIs that match scale items provide further support for HEART scales and items.

However, our analysis also indicates some ways that the tool could be strengthened. Overall, women tended to favor extreme values (either 1 or 6) on most items. This may be, in part, culturally reinforced [33, 34]. For example, women may find it difficult to keep in mind gradations of agreement and use the full range of response options. If so, it is not clear whether extending the response scale—for example, using a 10-point scale rather than a six-point, would alleviate these floor and ceiling effects. On the other hand, the extreme values of some of our items could have resulted from tapping into socially desirable norms. This would suggest rewording items in ways that make them more difficult to fully (dis)agree with.

Finally, the HIV Prevention Readiness scale did not perform well, compared to the other four scales. The internal reliability of the scale is relatively weak, falling short of the.7 cut-off. In addition, items on the scale show the highest skew and kurtosis of all the constructs. Finally, it is possible that the generic use of “HIV prevention product” rather than a specific product (e.g., vaginal ring) and the absence of items measuring readiness to undergo clinic procedures or navigate product-specific issues explain the scale’s lack of correlations with other predicted measures. The scale could potentially be improved by adding new, cognitively tested items, perhaps identifying them from the qualitative interviews.

The strongest evidence for HEART validity would be its ability to discriminate between women with different levels of relationship harmony, stress or violence and to reliably track changes in relationship context over the duration of their participation in a behavioral intervention. To this end, the HEART was included as an intervention component, in our CHARISMA pilot intervention study within the Hillbrow, Johannesburg site of the MTN-025 HOPE vaginal ring trial [26]. The HEART guided recommendations for provision of counseling content at baseline, and was administered at baseline, Month 3 and Month 6 to measure change in relationships over time. The performance of HEART in the CHARISMA pilot, including how changes in HEART scores are associated with receipt of specific counseling modules by pilot study participants, will be described separately. Further, the HEART is currently incorporated within the CHARISMA intervention that is being tested at the same research site using a randomized, controlled design to assess its effect on improving PrEP adherence and partner support and communication; and reduction of IPV.

Conclusion

We set out to develop and validate a simple tool to assess women’s relationships and risk for harmful gender norms and IPV to best address challenges to HIV prevention use that stem from partner relationships. Initial validation of the HEART is promising. Further evidence on the tool’s ability to characterize women’s relationships, recommend beneficial counseling content and monitor relationship changes over time within several product use contexts is forthcoming. The availability of such a tool to screen for and monitor the impact of women’s sexual relationships on their use of HIV prevention products could support providers and programs to better address partner-related challenges that undermine PrEP uptake and adherence.

Supporting information

S1 Table. HEART Item descriptive statistics: Number of observations (n), mean, standard deviation (SD), median, minimum (min), maximum (max), skewness, kurtosis, and percentage of responses in response categories 1 through 6.

(DOCX)

S2 Table. Illustrative quotes from IDIs used to predict HEART score ranges for Traditional Values, Partner Support, and Partner Resistance to HIV Prevention scales.

(DOCX)

S3 Table. Predictive text frequencies and comparison of predictions to survey score range, by IDI.

(DOCX)

S4 Table. Examples of specific scale items reflected in qualitative interviews for Traditional Values, Partner Support and Partner Resistance to HIV Prevention.

(DOCX)

Acknowledgments

We would like to acknowledge the willing contributions of the women who participated in this study without whom this study would not have been possible. The contributions of the CHARISMA study team and community stakeholders are acknowledged as critical in the implementation of this study. This program is made possible by the generous assistance from the American people through the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) and the U.S. Agency for International Development (USAID). The contents are the responsibility of the authors and do not necessarily reflect the views of PEPFAR, USAID or the United States Government.

Data Availability

The complete data from the quantitative survey have been uploaded the Harvard Dataverse platform and can be viewed at “https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/EULT3T.” The qualitative data for this paper are fully contained in the paper.

Funding Statement

This study was funded by the United States Agency for International Development (USAID) under APS-OAA-14-000076, of which EM was the Principal Investigator. The funders did not play any role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Decision Letter 0

H Jonathon Rendina

27 Aug 2020

PONE-D-20-18744

Development and initial validation of a simple tool to screen for partner support or opposition to HIV prevention product use

PLOS ONE

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Reviewer #1: Tolley et al. submitted an impactful paper developing and testing a screening tool for partner support in the context of HIV prevention among women in Sub-Sahara Africa. The developed scales could be (and are currently) used in survey research and clinical trials. The scales were developed with good methodology, including the use of cognitive interview procedures and item refinement. This is a well-written paper and I only have minor points to be considered in revision.

1. Based on the Methods described, it’s unclear if the authors conducted one large EFA with 127 items or if they conducted EFAs for each hypothesized construct.

2. It would be helpful if the authors reported whether each subscale was unidimensional (e.g., if they did not include any cross-loading and each construct only measured one theme). I raise this thought because of the relatively low factor loadings at times (0.40-0.50), which makes me think each construct could have subconstructs. This would be visible with subsequent factor analysis of only the items retained for each scale.

3. Some of the constructs have a lot of items (e.g., 13 for traditional values). This could artificially inflate the internal reliability. The authors could consider reducing the number of items using item-rest correlations (i.e., does reliability increase by removal of one item at a time?). Shorter scales might help with better integration into the clinical setting (and shorter surveys in research).

Reviewer #2: The manuscript "Development and initial validation of a simple tool to screen for partner support or opposition to HIV prevention product use" describes a scale development and validation study to develop a screening tool to assess potential facilitators and barriers for women's use of products to prevent HIV. The strengths of the manuscript include its thorough methodology and use of qualitative data to validate the quantitative measure. My answer to Question 3 regarding making data available is related to the fact that it seems as though some of the supplemental material referred to in the manuscript was not included in the submission (see comment 11 below). My more specific comments for ways that the authors can further strengthen the manuscript are as follows:

1. The transition from the Introduction to the Methods seems a little abrupt. I think it would be improved by ending your introduction with a paragraph highlighting the need for/potential purpose of a screening tool, and how this study will address that need.

2. Please provide more detail about the sample of 25 women with whom cognitive interviews were conducted (line 125). How were these women recruited? Did they meet the same eligibility criteria used for the cross-sectional survey (described lines 131-135)?

3. Please clarify whether all survey items were in English, and how responses may have differed for those for whom English is not their first or preferred language (e.g., those who preferred to complete their consent form in Zulu).

4. Please provide more explanation as to why items with a mean score below 1.4 or above 5.8 were eliminated. It occurs to me that these items could be viewed as valid and assessing the lowest and highest levels of the construct of interest (or reflect floor and ceiling effects seen in general, as described in the Discusssion), so more clarification about the reasoning around this decision would be helpful.

5. Please clarify what is meant by the sentence “All coders similarly applied the full codebook, as well as specific codes to text segments” (line 181-182). I’m not sure what is meant by the “full codebook” versus “specific codes.”

6. Regarding the questions about condom use and willingness to have sex at most recent sex act, I wonder about the potential limitations of these self-report data. Considering the potential power dynamics in these relationships, and that the majority of the women reported that they received financial or material support from their partners, it seems possible that social desirability and/or concerns about confidentiality could have influenced these responses. I had the same thought about this as a possible explanation for the floor/ceiling effects found for the Partner Resistance to HIV Prevention and HIV Prevention Readiness scales, which could possibly be due to participants answering in a socially desirable way related to their involvement in HIV prevention research.

7. It appears as though there is a formatting error in line 260, and Figure 1 is not included in the body of the manuscript.

8. Were any items added or removed based on their match (or lack thereof) with the qualitative text data? The description of this component of the analyses made it seems as though items would be revised based on these data, but there is no mention of this in the results section.

9. Please clarify if the version of HEART included in the CHARISMA pilot intervention included the HIV Prevention Readiness scale. If it was included, please justify the reasoning, given its poor performance in this analysis. Are there any plans to revise the scale?

10. I agree with the author’s suggestion that including items that address product-specific issues or concerns (e.g., taking a daily PrEP pill, concerns about comfort or sex with a vaginal ring) could strengthen the HIV Prevention Readiness scale.

11. It seems like there may be some supplemental materials that were left out of the manuscript submission. For example, I don’t see the equivalent of Tables 5, 6, or 7 for the other HEART scales.

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2020 Dec 22;15(12):e0242881. doi: 10.1371/journal.pone.0242881.r002

Author response to Decision Letter 0


15 Oct 2020

Reviewer #1: Tolley et al. submitted an impactful paper developing and testing a screening tool for partner support in the context of HIV prevention among women in Sub-Sahara Africa. The developed scales could be (and are currently) used in survey research and clinical trials. The scales were developed with good methodology, including the use of cognitive interview procedures and item refinement. This is a well-written paper and I only have minor points to be considered in revision.

1. Based on the Methods described, it’s unclear if the authors conducted one large EFA with 127 items or if they conducted EFAs for each hypothesized construct.

Response: Thank you for this question. We have clarified in the manuscript, abstract and methods section, that it was one large EFA.

2. It would be helpful if the authors reported whether each subscale was unidimensional (e.g., if they did not include any cross-loading and each construct only measured one theme). I raise this thought because of the relatively low factor loadings at times (0.40-0.50), which makes me think each construct could have subconstructs. This would be visible with subsequent factor analysis of only the items retained for each scale.

Response: We have clarified that, by using a Promax rotation, we allowed items to cross-load on multiple factors. However, we did remove any items that did not load mainly on one factor. (If similar loading, we removed the item.) We have also clarified that one of the factors in our final solution was subsequently found to have subconstructs, which we utilized in the final tool.

3. Some of the constructs have a lot of items (e.g., 13 for traditional values). This could artificially inflate the internal reliability. The authors could consider reducing the number of items using item-rest correlations (i.e., does reliability increase by removal of one item at a time?). Shorter scales might help with better integration into the clinical setting (and shorter surveys in research).

Response: We agree with the reviewer about the potential for larger number of items to artificially inflate the internal reliability of some scales. Because our initial scale development efforts were based on a cross-sectional survey (in addition to cognitive interviews), we did not want to be too restrictive in limiting the numbers of items or of scales that could be further evaluated in the pilot phase – and ultimately in the RCT phase of the project. In fact, in subsequent phases of this project, we have examined ways to shorten the HEART, including reducing the numbers of items in several scales and prioritization of HEART subscales for use in clinic settings. However, this will be presented in a subsequent paper.

Reviewer #2: The manuscript “Development and initial validation of a simple tool to screen for partner support or opposition to HIV prevention product use” describes a scale development and validation study to develop a screening tool to assess potential facilitators and barriers for women’s use of products to prevent HIV. The strengths of the manuscript include its thorough methodology and use of qualitative data to validate the quantitative measure. My answer to Question 3 regarding making data available is related to the fact that it seems as though some of the supplemental material referred to in the manuscript was not included in the submission (see comment 11 below).

Response: We apologize for this oversight. We have added/uploaded supplemental tables with illustrate quotes and our predictions for the other HEART subscales. We have also added supplemental tables with predictive text frequencies and comparison of our predictions for the other subscales.

My more specific comments for ways that the authors can further strengthen the manuscript are as follows:

1. The transition from the Introduction to the Methods seems a little abrupt. I think it would be improved by ending your introduction with a paragraph highlighting the need for/potential purpose of a screening tool, and how this study will address that need.

Response: Thank you for this comment. We have added a short paragraph to make this transition more apparent. (Lines 85-89 on page 5).

2. Please provide more detail about the sample of 25 women with whom cognitive interviews were conducted (line 125). How were these women recruited? Did they meet the same eligibility criteria used for the cross-sectional survey (described lines 131-135)?

Response: Yes, women were recruited through the same clinic and community mechanisms as women in the survey. Eligibility was the same as the survey. Because our analyses for this paper focused primarily on the survey, we didn’t want to go into too much detail for the cognitive interviews. However, we have tried to add some additional detail.

3. Please clarify whether all survey items were in English, and how responses may have differed for those for whom English is not their first or preferred language (e.g., those who preferred to complete their consent form in Zulu).

Response: We conducted separate cognitive interviews in English and Zulu, assessing comprehension, relevance and requesting suggested rewording in both languages. We have added this information into the description.

4. Please provide more explanation as to why items with a mean score below 1.4 or above 5.8 were eliminated. It occurs to me that these items could be viewed as valid and assessing the lowest and highest levels of the construct of interest (or reflect floor and ceiling effects seen in general, as described in the Discussion), so more clarification about the reasoning around this decision would be helpful.

Response: We compared the mean scores and standard distributions, modes and response ranges of all items across the entire sample (n=309) and by trial-experience subgroups (former trial participant and trial naïve). Many items showed skewed distributions in one of the subgroups, but only 4 items were highly skewed across the entire sample. We decided to remove these items prior to factor analysis as we concluded that the items provided virtually no variability through which we might differentiate between respondents. In all cases, similar items were retained in the item pool that elicited a wider range of responses.

5. Please clarify what is meant by the sentence “All coders similarly applied the full codebook, as well as specific codes to text segments” (line 181-182). I’m not sure what is meant by the “full codebook” versus “specific codes.”

Response: Thank you for this query. We agree that the text was not very clear and have edited the text to make this description clearer (pages 187-190 on page 9). Essentially, the coders examined whether they had applied both the 5 HEART construct/basic codes (full) and the sub-codes indicating which of 3 levels was predicted by the text in the same way.

6. Regarding the questions about condom use and willingness to have sex at most recent sex act, I wonder about the potential limitations of these self-report data. Considering the potential power dynamics in these relationships, and that the majority of the women reported that they received financial or material support from their partners, it seems possible that social desirability and/or concerns about confidentiality could have influenced these responses. I had the same thought about this as a possible explanation for the floor/ceiling effects found for the Partner Resistance to HIV Prevention and HIV Prevention Readiness scales, which could possibly be due to participants answering in a socially desirable way related to their involvement in HIV prevention research.

Response: Thank you. You make an excellent point. In fact, concerns about social desirability bias in relation to direct questions about potentially unacceptable behaviors – IPV or non-adherence, is part of the justification for using a scale approach, allowing participants to provide more nuanced indications of their own or their partners behaviors. We have incorporated additional language about social desirability bias into the discussion section.

7. It appears as though there is a formatting error in line 260, and Figure 1 is not included in the body of the manuscript.

Response: We had to upload this figure separately, so perhaps somehow it did not get included in the review. We have uploaded again. However, we believe it will be a separate document that will only be inserted at the time of (hopefully) publication.

8. Were any items added or removed based on their match (or lack thereof) with the qualitative text data? The description of this component of the analyses made it seems as though items would be revised based on these data, but there is no mention of this in the results section.

Response: We did not remove any items based on this analysis. However, we did add an additional five “test” items to the HIV Prevention Readiness scale during the Expansion/RCT phase. These new items were based on the qualitative test data.

9. Please clarify if the version of HEART included in the CHARISMA pilot intervention included the HIV Prevention Readiness scale. If it was included, please justify the reasoning, given its poor performance in this analysis. Are there any plans to revise the scale?

Response: We included the HPR scale in the pilot, because we wanted to obtain additional information on this subscale. Given that the majority of participants in our formative research had not previously participated in clinical trials, we assumed that pilot participants might respond to these items differently. Unfortunately, the additional HPR items that emerged from our qualitative analysis were not identified early enough to be a part of the pilot. We did include these new items in the final Expansion/RCT study and they did improve the HPR scale. However, we will present and discuss this in a manuscript that focuses on the final phase of the project.

10. I agree with the author’s suggestion that including items that address product-specific issues or concerns (e.g., taking a daily PrEP pill, concerns about comfort or sex with a vaginal ring) could strengthen the HIV Prevention Readiness scale.

Response: As described in our response above, this scale has now been strengthened, but it continues to be less reliable than the other measures. This is likely because the scale was more generic, and not related to a specific product.

11. It seems like there may be some supplemental materials that were left out of the manuscript submission. For example, I don’t see the equivalent of Tables 5, 6, or 7 for the other HEART scales.

Response: Thank you for pointing out this omission. We have included them now in the supplemental materials as tables S2-S4.

Attachment

Submitted filename: Response to Reviewers.docx

Decision Letter 1

H Jonathon Rendina

11 Nov 2020

Development and initial validation of a simple tool to screen for partner support or opposition to HIV prevention product use

PONE-D-20-18744R1

Dear Dr. Tolley,

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Acceptance letter

H Jonathon Rendina

11 Dec 2020

PONE-D-20-18744R1

Development and initial validation of a simple tool to screen for partner support or opposition to HIV prevention product use

Dear Dr. Tolley:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

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on behalf of

Dr. H. Jonathon Rendina

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. HEART Item descriptive statistics: Number of observations (n), mean, standard deviation (SD), median, minimum (min), maximum (max), skewness, kurtosis, and percentage of responses in response categories 1 through 6.

    (DOCX)

    S2 Table. Illustrative quotes from IDIs used to predict HEART score ranges for Traditional Values, Partner Support, and Partner Resistance to HIV Prevention scales.

    (DOCX)

    S3 Table. Predictive text frequencies and comparison of predictions to survey score range, by IDI.

    (DOCX)

    S4 Table. Examples of specific scale items reflected in qualitative interviews for Traditional Values, Partner Support and Partner Resistance to HIV Prevention.

    (DOCX)

    Attachment

    Submitted filename: Response to Reviewers.docx

    Data Availability Statement

    The complete data from the quantitative survey have been uploaded the Harvard Dataverse platform and can be viewed at “https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/EULT3T.” The qualitative data for this paper are fully contained in the paper.


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