Sex and gender considerations in implementation interventions to promote shared decision making: A secondary analysis of a Cochrane systematic review.

BACKGROUND: Shared decision making (SDM) in healthcare is an approach in which health professionals support patients in making decisions based on best evidence and their values and preferences. Considering sex and gender in SDM research is necessary to produce precisely-targeted interventions, improve evidence quality and redress health inequities. A first step is correct use of terms. We therefore assessed sex and gender terminology in SDM intervention studies.
MATERIALS AND METHODS: We performed a secondary analysis of a Cochrane review of SDM interventions. We extracted study characteristics and their use of sex, gender or related terms (mention; number of categories). We assessed correct use of sex and gender terms using three criteria: "non-binary use", "use of appropriate categories" and "non-interchangeable use of sex and gender". We computed the proportion of studies that met all, any or no criteria, and explored associations between criteria met and study characteristics.
RESULTS: Of 87 included studies, 58 (66.7%) mentioned sex and/or gender. The most mentioned related terms were "female" (60.9%) and "male" (59.8%). Of the 58 studies, authors used sex and gender as binary variables respectively in 36 (62%) and in 34 (58.6%) studies. No study met the criterion "non-binary use". Authors used appropriate categories to describe sex and gender respectively in 28 (48.3%) and in 8 (13.8%) studies. Of the 83 (95.4%) studies in which sex and/or gender, and/or related terms were mentioned, authors used sex and gender non-interchangeably in 16 (19.3%). No study met all three criteria. Criteria met did not vary according to study characteristics (p>.05).
CONCLUSIONS: In SDM implementation studies, sex and gender terms and concepts are in a state of confusion. Our results suggest the urgency of adopting a standardized use of sex and gender terms and concepts before these considerations can be properly integrated into implementation research.

Introduction

Shared decision making (SDM) is an interpersonal, interdependent process in which health professionals and patients relate to and influence each other as they collaborate in making decisions about the patient’s health [1-3]. Often supported by decision aids, SDM is based on best available evidence as well as the patient’s values and preferences [4]. There is an ethical imperative to involve patients in making important health decisions [5] and SDM is appearing in legislation governing healthcare in numerous countries [6, 7]. SDM can improve patient engagement [8-11], satisfaction and adherence to drug therapy [12], and contributes to the optimization of health service utilization and health costs [13]. SDM improves patient experiences and the quality of care provided by health professionals [14]. Despite this potential, SDM is not implemented as much as it could be in clinical practice [15, 16]. A 2018 Cochrane systematic review on interventions to improve the use of SDM by health professionals highlighted that much remains to be done to identify more effective implementation interventions [16].

In recent years, implementation scientists have hypothesized that implementation interventions would be more effective if they incorporated considerations of sex and gender [17-19]. Sex and gender are important determinants of illness. A review exploring the role of sex and gender as modifiers of the most common causes of death and morbidity underlined many sex/gender-based differences [20]. According to authors, heart disease occurs in younger males with more obstructive coronary disease, whereas it occurs in older females with more coronary microvascular dysfunction. Furthermore, women are underdiagnosed for inflammatory airway disease, and have higher myocardial infarction mortality, fewer heart transplants (although they are more frequent donors) and overall receive less evidence-based treatment than men [20]. When findings for males and females are not disaggregated, results can hide important differences [21, 22]. Research has also shown differences in drug reactions and rehabilitation outcomes [23, 24]. Interventions that take sex and gender into consideration are thus likely to produce more reliable evidence. Indeed, if authors fail to consider potential differences in the effectiveness of an intervention for men and women, there is a risk of bias, since it has not accurately assessed for whom the intervention is effective [25]. Furthermore, the structural influence of sex and gender on other variables is often neglected. Yet a wide range of health variables are gendered, for example, occupational status, working conditions, and access to sexual health services [26, 27]. In implementation research, gender may be discussed under four constructs: gender roles, gender identity, gender relations and institutionalized gender. Each is associated with relevant measures, such as the Gender Role Conflict scale [28] and the Bem Sex Role Inventory [29]. Implementation studies that consider these constructs will thus improve outcomes such as acceptability, feasibility, adoption and sustainability [30].

Sex- and gender-considerations are important in both SDM itself and SDM implementation interventions. Sex and gender are important variables for decision making styles, communication styles, and values and preferences—all key issues in SDM [31-35]. Health professionals’ sex and gender awareness will also impact their ability to identify risk factors for various illnesses, variables that may affect treatment options and their implications [36]. Failing to integrate sex and gender in SDM interventions such as training programs or decision aids neglects important determinants of knowledge use, reducing the effectiveness of the intervention, perhaps inadvertently reinforcing sex neutral claims and negative gender stereotypes, and thus perpetuating society’s sex and gender inequities [17].

The first step in considering sex and gender in health research, including implementation research, is to ensure understanding of the terms and their appropriate use [21, 37]. The Canadian Institutes of Health Research (CIHR) and the U.S. National Institutes of Health (NIH) have proposed similar lexicons of appropriate sex and gender terms for health researchers. In their standardized terminologies, “sex” refers to a set of biological attributes in humans and animals. These attributes include physical and physiological features (including chromosomes), gene expression, hormone levels and function, and reproductive/sexual anatomy [38]. Sex is usually categorized as female or male, but there is variation in the biological attributes that comprise sex and how those attributes are expressed [39]. “Gender” refers to the socially constructed roles, behaviours, expressions and identities of girls, women, boys and men. Gender is usually conceptualized as a binary (woman/man or girl/boy), but there is considerable diversity in how individuals and groups understand, experience, and express gender: hence people can also be “gender diverse”, e.g. transgender, agender, genderqueer or Two-Spirited [38]. Gender influences how people perceive themselves and each other, how they act and interact, and how power and resources are distributed in society [40]. The definitions may appear to categorize sex and gender as mutually exclusive, but they are interrelated and intersect [41]. While many interventions have been proposed to improve SDM among health professionals, little is known about how much they incorporate sex and gender. We aimed to take a first step by assessing variations in sex and gender concepts and terms in implementation studies of SDM in clinical practice.

Materials and methods

Study design

We performed a secondary analysis of the studies included in the qualitative synthesis of a Cochrane review on the effectiveness of interventions for increasing the use of SDM by health professionals [16]. There is no reporting guideline for secondary analyses of systematic reviews on the EQUATOR Network [42]. Thus we adapted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for reporting our results [43].

Search strategy and data sources

A detailed description of the search strategy, data sources can be found in the original Cochrane review [16].

Criteria for including studies

We retained all 87 intervention studies included in the qualitative synthesis of the original review (Fig 1) [16]. These studies met the following criteria: a) Study design included randomized trials, non-randomized controlled trials, before-after studies, interrupted time series; b) Participants included health professionals in training or already trained who were responsible for the caring for patients, and patients of those same health professionals; c) Interventions included any that was designed to promote the adoption of SDM by health professionals, such as training (e.g., conferences, workshops), distribution of printed educational materials (e.g., practice guidelines), audits with feedback, reminders, educational field visits, and patient-mediated interventions. The interventions targeted health professionals, patients or both; d) Comparisons included usual care or other interventions targeting either health professionals, patients, or both; e) Outcomes, both patient-reported and observer-reported, concerned SDM that occurred during the meeting between patients (and their families if applicable) and the health professionals. These SDM outcomes could have been a primary or secondary outcome of the study.

Fig 1

Flow chart of the Cochrane systematic review [16].

Process for assessing sex and gender considerations

To assess sex and gender considerations in each of the studies retained, we evaluated the correct use of such terms by measuring frequencies of the use of sex- and gender-related terms and determining categories used to further describe them. Then we assessed studies according to three criteria for correct use of sex and gender terms according to the definitions of sex and gender proposed by the CIHR [38] and the NIH [40]. These criteria were “non-binary use”, “use of appropriate categories” and “non-interchangeable use of sex and gender”.

Non-binary use of sex and gender

Sex can be male, female or intersex. While only two categories are usually used, intersex people are born with ambiguous reproductive or sexual anatomy. Two categories only are usually used for gender also, while gender is on a continuum and many people self-identify neither as men (“he”) nor women (“she”) but as pangender, transgender, gender-diverse etc. (and may prefer to be referred to as “they”). The criterion of “non-binary use” of sex or gender was therefore applied to assess whether studies took these important variations into consideration [44]. We assessed the criterion in studies in which the terms sex and/or gender (i.e. sex, gender or both) were mentioned. We considered the use of the terms as if authors mentioned the terms sex and/or gender and described them by using only two categories (i.e. male or female, man/boy or woman/girl). This included instances where categories were inferred, even if not explicitly mentioned (e.g., if authors only reported the proportion of female participants as 65%, we inferred that the proportion of male participants was 35% and considered that two categories were used). We considered the use as if authors mentioned the terms sex and/or gender and described them using a third category, i.e. ‘intersex’, ‘gender diverse’, or else provided a third sex or gender option by including the category ‘not specified’ or ‘would prefer not to respond’. We considered the “non-binary use” as if authors mentioned only the term sex or gender without specifying further categories (e.g. male, man, female, male, intersex, transgender).

Use of the appropriate categories to describe sex and gender

We assessed the “use of the appropriate categories” to describe sex and gender in studies in which sex and/or gender were mentioned. To assess this criterion, we considered the categories used to assess sex as if authors consistently used the categories male/female/intersex. Similarly, we considered the categories used to assess gender as if authors consistently used the categories “girl/woman”, “boy/man”, (i.e. identities that are culturally rather than biologically determined) and any word applying to gender-diverse people. We considered the categories used as if authors mentioned the terms sex and/or gender but used the categories associated with sex to describe gender, and vice versa. We considered the categories used as if authors mentioned only the term sex and/or gender without subdividing into categories.

Non-interchangeable use of sex and gender

To assess the “non-interchangeable use” of sex and gender, we referred to above-mentioned definitions of sex and gender as proposed by CIHR and NIH [38, 40]. We assessed this criterion in studies in which sex and/or gender and/or related terms were mentioned. We considered sex and gender were used (non-interchangeable use = “No”) if sex terms (sex, female, male, intersex) and gender terms (gender, girl, boy, woman, man, gender-diverse) were mentioned and indiscriminately used to describe either sex or gender of participants in the same study. For example, authors may have used sex terms while describing the sociodemographic characteristics but reported or discussed the results using gender terms to describe the same attributes of the same participants. We considered sex and gender were used (non-interchangeable use = “Yes”) if sex terms were consistently used to describe biological attributes while gender terms were consistently used to describe sociocultural attributes of study participants. We considered the non-interchangeable use to be (non-interchangeable use = “Unclear”) in any other situation where the criteria were applicable.

Defining the “correct use” of sex and gender

The “correct use” of sex and gender was defined by combining all the three criteria: non-binary use, use of appropriate categories and non-interchangeable use of sex and gender. The “correct use” of sex and gender was then assessed in studies in which sex and/or gender were mentioned. We considered the use of sex and gender as if all three criteria were met. We considered the correct use of sex and gender as if there was a combination of unclear and positive answers (e.g. use of categories = “appropriate” and non-interchangeable use = “unclear”). In any other situation, where the assessment was applicable, we considered the use as .

Data collection process

We screened the full text of each of the 87 studies included in the qualitative synthesis of the original Cochrane review [16]. Members of the research team discussed which data to extract. Data were extracted by a single reviewer (ELA) trained in sex and gender considerations in health research at Women's College Research Institute in Toronto, Ontario in March 2017 [45]. We first extracted data related to the characteristics of the included studies (e.g. author’s name, year of publication, regions in which they were conducted, type of interventions, effect of the interventions on the primary outcome). Any ambiguities, unexpected or unanticipated issues faced during the data extraction were discussed with the other members of the research team. We then searched for terms related to the two key concepts: Sex and related terms such as “female”, “male” and “intersex” [46, 47]; and gender and its related terms such as “women”, “men”, “woman”, “man”, “girl”, “boy” and “gender diverse”. We searched the full text either electronically or manually (when an electronic version of the paper was not available). We identified studies in which sex and/or gender and/or related terms were mentioned. We extracted data on the number and the wording of the categories used to describe sex and gender attributes and assessed the three criteria defined above (non-binary use, use of appropriate categories, non-interchangeable use of sex and gender).

Data analysis

We performed a descriptive analysis for the characteristics of the 87 studies using frequency counts (number and percentage). The most recent changes in the definitions of sex and gender proposed by CIHR and NIH occurred around 2015 [38-40]. We therefore categorized “year of publication” as a binary variable: “before 2016” and “after 2016”. We categorized the variable “regions in which the study was conducted” as a binary variable: “North America” and “Europe/Other”. We described (using proportions) studies in which sex and/or gender and/or related terms were mentioned. We calculated the percentage of these studies that met each criteria of interest. We determined the proportion of studies with “correct use” of sex and/or gender, i.e. studies that met all three criteria. We compared the proportion of studies that met each criterion according to the following study characteristics: year of publication, regions in which the studies were conducted, type of intervention, and effect of intervention on primary outcome. To reach this goal, we reduced responses to each criterion from three to two: “criteria was met” and “criteria was not met or unclear”. We evaluated if this categorization would affect our results by performing sensitivity analyses with a third categorization (S1 Table). To explore associations between criteria met and study characteristics, we performed Pearson Chi-squared test [48], Yates’s Khi-2 Correction for continuity [49] or Fischer’s exact test [50]. All analyses were performed using version 9.4 of SAS software.

Results

Characteristics of included studies

Out of 87 included studies, all published between 1995 and 2017, almost a quarter (23.4%) were published in 2016 or 2017 [51-70]. The studies were mainly (54%) conducted in North America [52, 54–58, 61, 66–68, 71–105]. Forty-four (50.6%) studies evaluated interventions targeting patients [32, 51, 52, 54, 57, 59–64, 66, 67, 69, 72, 75–79, 84–86, 88, 90–92, 96, 98, 99, 102, 103, 106–116]. Fifteen (17.2%) studies evaluated interventions targeting health professionals [53, 55, 65, 94, 101, 109, 117–125]. Twenty-eight (32.2%) studies evaluated interventions in both patients and health professionals [56, 58, 68, 71, 73, 74, 83, 86, 89, 93, 95, 97, 99, 104, 105, 126–135]. Effect of the interventions (compared to usual care or the other types interventions by target group, i.e. patients, health professionals or targeting both) on the primary outcome was significant in 24 (28%) of the included studies [60, 64–66, 68–70, 87, 88, 92, 96, 101–103, 109, 113, 115, 117, 122, 124, 125, 129, 130, 136] (Table 1).

Table 1

Characteristics of the 87 included studies and use of sex/gender terms.

Characteristics	Number of studies	Percentage (%)
Year of publication
Before 2016a	67	77.0
After 2016b	20	23.0
Regions in which the studies were conducted
North America	47	54.0
Europe	35	40.2
Other (Australia and Namibia)	5	5.8
Interventions targeting
Patients	44	50.6
Health professionals	15	17.2
Both	28	32.2
Effect of interventions on primary outcome
Significant	24	27.6
Non-significant/Data not reported	63	72.4
Mention of sex and/or gender and/or related terms
Sex and/or gender mentioned
Sex	37	42.5
Gender	36	41.4
Sex and/or gender	58	66.7
Neither sex nor gender	29	33.3
Related terms mentioned
Female	53	60.9
Male	52	59.8
Woman/Women	38	43.7
Man/Men	11	12.6
Girl	1	1.2
Sex and/or gender and/or related terms mentioned	83	95.4

a Before 2016: 1995–2015;

b After 2016: 2016–2017.

Mention of sex and/or gender and/or related terms in included studies

Out of 87 included studies, the term, sex was mentioned in 37 (42.5%) studies [54–58, 60–64, 66, 68, 70, 71, 79, 83, 85, 87, 89, 95, 96, 98, 103, 105, 107, 110, 112, 114, 119–122, 126, 128, 130–132]. Gender was mentioned in 36 (41.4%) studies [51, 52, 58, 60, 61, 63, 65, 70, 71, 77, 82, 87, 89, 91, 96–99, 101, 104, 106, 112, 114, 117–119, 121, 124, 125, 131, 133–135, 137]. The terms sex and/or gender were mentioned in 58 (66.7%) studies [51, 53–66, 68, 70, 71, 77, 79, 82, 83, 85, 87–89, 91, 95–98, 101, 103–107, 110, 112, 114, 117–120, 122, 124–126, 128–135]. Terms related to sex and gender such as female, male, woman/women, man/men and girl were mentioned respectively in 53 (60.9%), 52 (59.8%), 38 (43.7%), 11 (12.6%) and 1 (1.2%) studies. The term boy was not mentioned in any study. The terms sex, gender and/or related terms were mentioned in almost all of the included studies: 83 (95.4%) [51, 52, 54–59, 64–68, 70–79, 82, 95–106, 109–118, 123–130, 134, 135, 137, 138]. Neither sex nor gender was mentioned in 29 (33.3%) studies [53, 67, 69, 72–76, 78, 81, 84, 86, 90, 92–94, 100, 102, 108, 109, 111, 113, 115, 116, 123, 127, 136–138]. Neither sex, gender nor any related term was mentioned in four (4.6%) studies [53, 69, 81, 136] (Table 1).

Assessing the criteria for correct use of sex and gender

The non-binary use of sex and gender was assessed in the 58 studies in which sex and/or gender were mentioned [51, 53–66, 68, 70, 71, 77, 79, 82, 83, 85, 87–89, 91, 95–98, 101, 103–107, 110, 112, 114, 117–120, 122, 124–126, 128–135]. In these studies, authors clearly described sex as a binary variable in 36 (62.1%) studies [54–58, 60–64, 66, 68, 70, 71, 79, 83, 85, 87, 89, 95, 96, 98, 103, 107, 110, 112, 114, 118–122, 126, 130–132]. Such studies represented 97.3% of the 37 studies in which only sex was mentioned [54–58, 60–64, 66, 68, 70, 71, 79, 83, 85, 87, 89, 95, 96, 98, 103, 105, 107, 110, 112, 114, 119–122, 126, 128, 130–132]. The use of sex as a non-binary variable was unclear in 22 (37.9%) studies [51, 52, 59, 65, 77, 82, 88, 91, 97, 99, 101, 104–106, 117, 124, 125, 128, 129, 133–135] (Table 2). We found no studies whose use of sex was explicitly non-binary, i.e. we found no words or expressions to convey a non-binary conception of sex, such as “intersex”, “not specified” or “would prefer not to respond” when authors were reporting selection of a sex option. Our findings were similar for gender. Out of the 58 studies in which sex and/or gender were mentioned, authors clearly used gender as a binary variable in 34 (58.6%) [39, 51, 52, 58, 59, 61, 63, 65, 70, 71, 77, 82, 88, 89, 91, 96–99, 101, 104, 106, 112, 114, 118, 119, 121, 124, 125, 129, 131–135]. This represented 94.4% of the 36 studies in which only gender was mentioned [51, 52, 58, 60, 61, 63, 65, 70, 71, 77, 82, 87, 89, 91, 96–99, 101, 104, 106, 112, 114, 117–119, 121, 124, 125, 131, 133–135, 137]. Non-binary use of gender was unclear in 24 (41.4%) studies [54–57, 60, 62, 64, 66, 68, 79, 83, 85, 87, 95, 103, 105, 107, 110, 117, 120, 122, 126, 128, 130]. We found no studies whose use of gender was explicitly non-binary, i.e we found no words or expressions to convey a non-binary conception of gender such as “gender-diverse” “transgender”, “not specified” or “would prefer not to respond” when authors were reporting selection of gender options (Table 2).

Table 2

Assessing criteria of assessing a correct use of sex/gender.

Criteria	Number of studies	Percentage (%)
1. Non-binary use of sex and gender (n = 58)
Sex
Binary use	36	62.1
Non-binary use	0	0
Unclear use	22	37.9
Gender
Binary use	34	58.6
Non-binary use	0	0
Unclear use	24	41.4
2. Use of appropriate categories (n = 58)
Sex
Appropriate (Female/male)	28	48.3
Inappropriate (Woman/man)	8	13.8
Unclear	22	37.9
Gender
Appropriate (Woman/man)	8	13.8
Inappropriate (Female/male)	26	44.8
Unclear	24	41.4
3. Non-Interchangeable use (n = 83)
Yes	16	19.3
No	48	57.8
Unclear	19	22.9
Correct use of sex and gender (n = 58)
Correct use	0	0
Incorrect	35	60.3
Unclear	23	39.7

The appropriate categories used to describe sex and/or gender was assessed in the 58 studies in which sex and/or gender were mentioned. Out of these studies, authors used the appropriate categories (female/male) to describe sex in 28 (48.3%) studies [54–58, 61–64, 66, 68, 71, 83, 85, 87, 89, 95, 98, 103, 107, 110, 112, 119, 121, 122, 130–132]. Such studies represented 77.8% of the 36 studies in which sex was used as a binary variable [54–58, 60–64, 66, 68, 70, 71, 79, 83, 85, 87, 89, 95, 96, 98, 103, 107, 110, 112, 114, 118–122, 126, 130–132]. Authors more often used the appropriate categories (female/male) to describe sex than the appropriate categories (woman/man) to describe gender. Out of the 58 studies in which sex and/or gender were mentioned, only 8 (13.8%) used the appropriate categories to describe gender [51, 70, 88, 91, 96, 114, 118, 133]. Such studies represented 23.5% of the 34 studies in which gender was mentioned [39, 51, 52, 58, 59, 61, 63, 65, 70, 71, 77, 82, 88, 89, 91, 96–99, 101, 104, 106, 112, 114, 118, 119, 121, 124, 125, 129, 131–135]. Authors mostly used the words female/male whether they were describing sex or gender (Table 2).

The non-interchangeable use of sex and gender was assessed in the 83 studies in which sex and/or gender and/or related terms were mentioned. Out of these studies, authors used sex and gender non-interchangeably in 16 (19.3%) studies [55, 62, 64, 66, 82, 85, 87, 89, 103, 107, 110, 119, 122, 126, 127, 130]. They used sex and gender interchangeably in 48 (57.8%) studies [51, 52, 54, 56, 58–61, 63, 65, 70, 71, 75, 77–79, 83, 84, 86, 88, 90, 91, 94–99, 101, 104–106, 109, 112, 114, 117, 118, 120, 121, 124, 125, 129, 131–135, 137], and unclearly in 19 (22.9%) studies [57, 67, 68, 72–74, 76, 92, 93, 100, 102, 108, 111, 113, 115, 116, 123, 128, 138] (Table 2).

Correct use of sex and gender

The correct use of sex and gender was assessed in studies where sex and/or gender were mentioned (n = 58) and in which all the criteria were applicable. None of these studies met all three criteria (Table 2), i.e. none of the included studies made the correct use of sex and gender. The use of sex and/or gender was incorrect in 35 (60.3%) [51, 52, 58, 59, 61, 63, 65, 70, 71, 77, 88, 89, 91, 96–99, 101, 104–106, 112, 114, 117–119, 121, 124, 125, 129, 131–135]. Their use was unclear in 23 (39.7%) studies [54–57, 60, 62, 64, 66, 68, 79, 82, 83, 85, 87, 95, 103, 107, 110, 120, 122, 126, 128, 130] (Table 2).

Associations between criteria met and study characteristics

Year of publication

In studies published before 2016, the proportion that met the “use of appropriate categories” to describe “sex” was 41.5% (i.e. 17/41) [71, 83, 85, 87, 89, 95, 98, 103, 107, 110, 112, 119, 121, 122, 130–132] while it was 64.7% (i.e. 11/17) after 2016 [54–58, 61–64, 66, 68]. For the use appropriate categories to describe “gender” the proportion of studies that met this criterion was 14.6% [88, 91, 96, 114, 118, 133] before 2016 versus 11.8% [51, 70] after 2016. In studies published before 2016, the proportion that met the criterion: “non-interchangeable use of sex and gender” was 18.5% [82, 85, 87, 89, 103, 107, 110, 119, 122, 126, 127, 130] while it was 22.2% after 2016 [55, 62, 64, 66]. Year of publication made no significant difference to whether studies met the criteria of appropriate categories for sex (p = .107), gender (p = .319), or non-interchangeable use (p = .984) (Table 3).

Table 3

Associations between criteria met and study characteristics.

	Use of categories of sex (n = 58)			Use of categories of gender (n = 58)			Non-interchangeable use (n = 83)
Characteristics	Appropriate	Inappropriate or Unclear	P-value	Appropriate	Inappropriate or Unclear	P-value	Yes	No or Unclear	P-value
Year of publication			.107(a)			.319(c)			.984(b)
<2016	17 (41.5)	24		6 (14.6)	35		12 (18.5)	53
≥2016	11 (64.7)	6		2 (11.8)	15		4 (22.2)	14
Regions in which studies were conducted			.425(a)			.627 (b)			.350(a)
North America	16 (53.3)	14		3 (10.0)	27		7 (15.6)	38
Europe/other	12 (42.9)	16		5 (17.9)	23		9 (23.7)	29
Interventions targeting			.619(a)			.737(a)			.771(a)
Patients	13 (54.2)	11		5 (20.8)	19		7 (16.3)	36
Health Professionals	4 (36.4)	7		1 (9.1)	10		3 (23.1)	10
Both	11 (47.8)	12		2 (8.7)	21		6 (22.2)	21
Effect of interventions on primary outcome			.670(a)			.672(c)			.427(b)
Significant	7 (43.8)	9		3 (18.8)	13		6 (27.3)	16
Non-significant/Data not reported	21 (50.0)	21		5 (11.9)	37		10 (16.4)	51

(a) Pearson Chi-squared test;

(b) = Yates’s Khi-2 Correction for continuity;

(c) = Fischer’s exact test.

Regions in which studies were conducted

Studies that met the “use of the appropriate categories” to describe “sex” in the ones conducted in North America was 53.3% (i.e. 16/30) [54–58, 61, 66, 68, 71, 83, 85, 87, 89, 95, 98, 103] versus 42.9% (i.e. 12/28) [62–64, 107, 110, 112, 119, 121, 122, 130–132] in Europe and other regions. For the appropriate categories used to describe “gender”, the proportions of studies that met the criterion “use of the appropriate categories” to describe “gender” were respectively 10.0% [88, 91, 96] in North America versus 17.9% [51, 70, 114, 118, 133] in Europe and other regions. The proportion of studies conducted in North America in which authors used sex and gender non-interchangeably was 15.6% [55, 66, 82, 85, 87, 89, 103] versus 23.7% [62, 64, 107, 110, 119, 122, 126, 127, 130] in Europe and other regions. Regions in which studies were conducted made no significant difference to whether studies met the criteria of “use of the appropriate categories for sex (p = .425), gender (p = .627) or “non-interchangeable use of sex and gender” (p = .350) (Table 3).

Type of interventions

In studies with significant interventions effect, the proportion in which authors used the appropriate categories to describe “sex” were respectively 54.2% (i.e. 13/24) [54, 57, 61–64, 85, 98, 103, 107, 110, 112] for interventions targeting patients, 36.4% (i.e. 4/11) [55, 119, 121, 122], targeting health professionals and 47.8% (i.e. 11/23) [56, 58, 68, 71, 87, 89, 95, 130–132] targeting both. For the appropriate categories to describe “gender”, the proportions were respectively 20.8% [51, 88, 91, 96, 114], 9.1% [118] and 8.7% [70, 133]. Seven (16.3%) [62, 64, 66, 85, 103, 107, 110] of studies that met the criterion “non-interchangeable use of sex and gender” evaluated interventions targeting patients, 3 (23.1%) [55, 119, 122] targeting health professionals and 6 (22.2%) targeting both [82, 87, 89, 126, 127, 130]. The type of interventions made no significant difference to whether studies met the criteria of “use of the appropriate categories” for sex (p = .619), gender (p = .737), or non-interchangeable use (p = .771) (Table 3).

Efficacy of interventions compared to usual care/other interventions on the primary outcome

The proportion of studies with significant interventions effect in which authors used the appropriate categories to describe “sex” was 43.8% (i.e. 7/16) [64, 66, 68, 87, 103, 122, 130] versus 50.0% (i.e. 21/42) [54–58, 61–63, 71, 83, 85, 89, 95, 98, 107, 110, 112, 119, 121, 131, 132] with non-significant interventions effect. For the appropriate categories to describe “gender”, the proportions were respectively 18.8% [70, 88, 96] versus 11.9% [51, 91, 114, 118, 133]. The proportion of studies that evaluated effective interventions in which authors used sex and gender non-interchangeably was 27.3% [64, 66, 87, 103, 122, 130] versus 16.4% [55, 62, 82, 85, 89, 107, 110, 119, 126, 127] of studies that evaluated non-effective interventions in which authors used sex and gender non-interchangeably. The efficacy of interventions made no significant difference to whether studies met the criteria of appropriate categories for sex (p = .670), appropriate categories for gender (p = .672), or non-interchangeable use (p = .427) (Table 3).

Discussion

This study assessed the use of sex and gender terms in 87 implementation intervention studies promoting adoption of SDM in clinical practice. Most authors made some mention of the terms sex and/or gender and/or related terms to describe study participants. The related terms they mostly mentioned were female and male. No authors used sex or gender as non-binary variables. More studies used appropriate categories to describe sex than to describe gender. Sex and gender were used synonymously or interchangeably in most studies. No single study met all criteria for “correct use” of the terms for reporting on sex and gender, i.e. use that is non-interchangeable, appropriately categorized, and non-binary. The proportion of studies meeting the criteria did not vary significantly according to publication year, region, intervention type or efficacy of interventions per target population. These results lead us to make the following observations.

First, authors did not use the terms “sex” and “gender” systematically when describing sociodemographic characteristics of study participants. Many switched back and forth, using them interchangeably, i.e. synonymously. These authors are neglecting an important distinction in the implementation of SDM interventions and create confusion about to whom these interventions are applicable. [41, 139, 140]. Gender was frequently used as a synonym for sex and, even in single-sex studies, investigators consistently considered female (or male) systematically as women (or men) without assessing gender [140]. The studies that do not fall into this trap cannot be associated with a particular time, place, intervention type, or even the efficacity of their interventions: in our study the non-interchangeable use of sex and gender did not vary according to these study characteristics. Second, the variables “sex” and “gender” were not reported according to definitions used by NIH and CIHR [38-40]. The necessity for researchers applying to CIHR (after 2010) and NIH (after 2015) grants to solidly and accurately integrate sex and gender in their research proposals [141] has clearly not yet had an impact on implementation scientists’ efforts to increase the adoption of SDM by health professionals [142]. These requirements in grant applications, training on sex and gender in research, and involving graduate students in sex and gender networks will presumably improve understanding and appropriate use of sex and gender in time [143, 144].

Third, all studies used sex and gender as binary variables. Statistics Canada, a common reference for country-wide data on health and a multitude of other variables, adopted the use of sex and gender as non-binary variables in 2018 [46, 145]. Non-binary people are an important and increasingly vocal segment of the population with their own specific physical and mental health issues. Many already feel excluded by the health system, and being invisible in research results will be a further alienating factor [17].

Regarding measurement, authors in our studies did not report on how the sex of participants was measured. Most of the evaluated interventions occurred in clinical care consultations, and some data on study participants’ sex could be have been accessed using medical charts. If investigators found no known intersex study participants (intersex individuals are fewer than 1 in 2000) [47], they may have probed no further and seen little point reporting a category with zero individuals. Measuring the gender of participants is more challenging, yet equally important. One recent study on cardiovascular risk factors measured gender using information about whether the respondent was the primary household earner, their income, number of housework hours, and stress levels at home, as well as measures of masculinity and femininity from the Bem Sex-Role Inventory [29]. It found that both sex and gender were important in predicting many cardiovascular risk factors, but that the gender score was generally more important [146]. While it has been suggested that gender be operationalized through the four constructs of gender roles, gender identity, gender relations and institutionalized gender [139, 147, 148], it is still not clear how best to capture them. It is not clear if gender is a categorical variable, as Statistics Canada suggested in 2018, describing the variable “gender” with the categories “man”, “woman” and “gender diverse” [145], or if gender should be assessed by scoring through a scale (continuous variable), as suggested by some previous works [29, 149–152]. Measuring gender in secondary data analyses such as ours, where direct measures of gender have not been collected, is even more challenging than in primary studies, as there is no access to the questionnaires used by investigators to understand how the variables were collected and categories defined. Smith et al. used the Labour Force Survey to develop their gender index, because it has questions that are commonly available in other data sources, and a gender-index using such data may be easily applied (and modified or further developed) to other secondary data sources [153]. With Statistics Canada now using non-binary categories, it could also be an interesting source of data for developing a more representative gender-index for further secondary studies in SDM.

Sex and gender are interrelated and dividing them up is misleading. With Tannenbaum et al. [17], we agree that SDM intervention studies should ask a question about “sex assigned at birth” and follow up with a gender question about “how the participant identifies him/herself now” [17]. This will help the participant first to be aware of the fact that it is two different measures, and second to feel that the answer can be diverse. We suggest providing categories to describe both sex (“female”, “male”, “intersex”, “do not want to respond”, “other (please explain)” and gender (“girl/woman”, “boy/man”, “gender diverse”, “do not want to answer”, “other (please explain)”.

To the best of our knowledge, this study may be one of the first studies to evaluate correct use of sex and gender by identifying relevant criteria. These criteria could be transformed into questions that authors can answer to in order to assess whether the first step in sex and gender considerations has been understood.

Conclusions

SDM interventions that do not consider sex and gender miss important biological and cultural differences between people that have a significant impact on health and health communications about health. The first step in correcting this is a good understanding and an appropriate use of sex and gender terms. We established criteria on correct use of terms and found that few studies of interventions to improve SDM in health professionals correctly identified sex and gender and their categories, and none described them as non-binary. Standardizing terminology would be a good start for measuring and reporting on sex and gender in SDM implementation interventions.

PRISMA 2009 checklist.

(DOC)

Click here for additional data file.

Description of the criteria according to the studies characteristics (sensitivity analyses).

(DOCX)

Click here for additional data file.

(XLSX)

Click here for additional data file.

29 Jul 2020

PONE-D-20-16595

Sex and gender considerations in implementation interventions to promote shared decision making: A secondary analysis of a cochrane systematic review

PLOS ONE

Dear Dr. Légaré,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

This is a well conceived piece which has been relatively well executed and reported.

The Reviewer has made some very sensible and constructive points which will enhance the value of your  paper to a more general audience. Given the importance of the subject matter being understood widely, I very much hope you can work with this.

Please submit your revised manuscript by Sep 12 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Robert S. Phillips

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: PLOS ONE Review: Sex and gender considerations in implementation interventions to promote shared decision making: a secondary analysis of a Cochrane systematic review

Overall

• The authors review the extent to which studies on shared decision making reported on sex and gender of participants, and whether that reporting was appropriate. They make the point that sex and gender matter for the effectiveness of SDM interventions, and thus it is important to understand the extent to which research on SDM interventions has accounted for sex and gender.

• Throughout, the authors should make much more clear the evidence for WHY taking into account sex and gender in shared decision-making matters (of course, I believe that it does matter), but the case needs to be made more clearly with specific examples as to why it is essential to accurately measure, report, and discuss these constructs as the distinct characteristics that they are (sex vs gender identity). The whole value of the paper rests on people understanding and accepting WHY sex and gender considerations matter for SDM work.

• These results are of interest and make a contribution, however, in their current form they are too vague and unclear as to make that contribution effectively. Substantial revisions to the writing, to the level of detail provided, and clearer examples and arguments from the authors would go a long way toward making the paper a substantive contribution to the SDM field.

• The language/style of writing throughout the paper is not always clear, and in some cases is grammatically incorrect. The paper would benefit from a thorough review for language flow/accuracy.

• Inconsistent capitalization of sex/gender throughout paper – be consistent.

Abstract

• In background section of the abstract, the authors need to provide their rationale for WHY sex and gender matter for implementation interventions. Also, SDM should be defined and contextualized – are you looking at SDM in all fields? Only certain fields? Certain subpops? All patient populations?

• Materials and methods: While challenging in a short space, more clarity about what was measured and how assessed is needed. Language is vague.

• Results: “sex/gender” in line 43 – is this that sex OR gender was measured? Or both? This is an important distinction that should be clarified.

Introduction

• The introduction should be broken up into several paragraphs to improve readability/flow. For instance, the first paragraph could focus first on defining SDM, the second on WHY SDM is important in clinical care, the third on research/ideas related to how gender and sex are essential to intervention effectiveness, and so on (rather than having all of the above in the first paragraph as currently stands)

• Line 64-65: What is meant by “SDM can also facilitate care…” – what is meant by facilitating care? Give examples. Also – if I interpret correctly, this sentence may be somewhat redundant to the prior sentence – if they are addressing different things, be specific – what does this sentence add?

• Lines 75-76: The authors write that sex and gender can offer insight into how to tailor implementation interventions for greater efficacy – this is ESSENTIAL to the purpose of the paper, so the authors would do well to add several sentences diving in to this. HOW can sex and gender help increase intervention effectiveness? What specific studies have found this? How did they measure sex/gender? What did they find? What is the causal mechanism involved with this hypothesized pathway?

• In lines 80-99, it would help to put quotes around the terms you are defining. This paragraph is hard to follow.

• For “gender diverse”, give examples of gender identities for the unfamiliar research (i.e., agender, nonbinary, transgender, Two-spirit, genderfluid, pangender, etc)

• Authors periodically begin sentences with “It” and seem to be referring to sex or gender, however it is hard to follow – be more specific.

• Line 96-97: “All individuals act in ways that fulfill the gender expectations…” – definitely not true. Many people act in ways that DO NOT fulfill the gender expectations of their society – this is part of why critical gender analysis is such a focus. What is meant by this original sentence? Context is lacking.

Materials and methods

• Criteria for including studies: lines 134-135: section on comparison with another intervention being absent – this does not make sense. Does this mean only studies that did NOT compare the intervention to another intervention were included? Why is that? What is the rationale? Or if it does not mean this, what does it mean?

• Language unclear throughout. More detail/specifics needed.

• Process for assessing sex and gender considerations: more clarity needed throughout. Where possible, give specific examples. For example – the statement in line 143: “First, sex and gender are non-binary variables.” This section is setting up for later sections with more detail, but on first read, it leaves the reader wanting a lot more information right from the start. Either clarify that this information will be provided later, or consider streamlining this section and just diving directly into the more specific sub-sections that follow.

• Lines 147-148: be careful with language here. What is mean by “typical definition” of female or male?

Data collection process

• Lines 227-230: What software (if any) was used to manage and analyze extracted data?

Data analysis

• Line 243: list explicitly the characteristics meant by “characteristics of studies” to summarize/make obvious for reader: i.e., “….according to the characteritics of studies, which included: year of publication, region in which study conducted, study population, etc…”

• Authors list the statistical tests performed, but do not indicate which tests were used for which assessments. More detail is needed to evaluate the appropriateness of testing conducted.

Results

• Line 269: “sex/gender” again used, without clarity as to whether this mean one or the other, versus BOTH

• Table 1 and Table 3:

o for year of publication, give range of years (i.e., 2000-2015, vs 2016-2017) for specificity

o Instead of saying “countries”, say “regions” as you are comparing on region, not country

o Order patients/hc professionals above “both”, as otherwise “both” is confusing before you know what the other options are

o “sex and/or gender” is confusing in this table – shouldn’t it be, “sex AND gender”?

o Why is “boy” not included in Table 1 under “related terms mentioned”

• Language unclear/vague/incorrect in some sentences: i.e., Line 293-294 “Authors used sex as non-binary variable in no study”. Same for lines 307-308, 331-332, 373, etc

• Table 2:

o What is “respect of the criteria (2 and 3)” representing? What does this mean?

• Line 354: “Countries” should be “regions” throughout

Discussion

• Overall, the discussion should be shortened/tightened, remove speculation, and provide MUCH more specific commentary. A thorough grammar review is also warranted, especially on page 24

• More is needed to discuss the implications of sex and gender (measurement and reporting) for shared decision-making. Why does sex/gender matter for SDM? What has this review taught us about state of sex/gender measurement/reporting in SDM intervention studies? What are the implications of these findings for future SDM work? The authors mention these things but very vaguely – instead, the authors should add detail to provide information on specific findings from studies that have established the importance of sex/gender for SDM, and specific suggestions for how future SDM research should measure/report on sex/gender as a result of these findings, and why

• Feels that discussion could be broadly restructured/focused as follows:

o First: succinct narrative summary of main findings: no study met all three criteria for correct reporting on sex/gender. This did not vary by measured study characteristics.

o Second: implications of this finding for existing SDM research, and future SDM research

o Third: strengths/limitations

o Fourth: conclusions � recommendations from authors based on findings

• More specifically: authors could recommend measures of sex and gender that SDM researchers could use going forward – there is a rich literature on measurement of sex and gender identity that they could draw from and cite

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

22 Sep 2020

Reviewer #1: PLOS ONE Review: Sex and gender considerations in implementation interventions to promote shared decision making: a secondary analysis of a Cochrane systematic review

Overall

• The authors review the extent to which studies on shared decision making reported on sex and gender of participants, and whether that reporting was appropriate. They make the point that sex and gender matter for the effectiveness of SDM interventions, and thus it is important to understand the extent to which research on SDM interventions has accounted for sex and gender.

• Throughout, the authors should make much more clear the evidence for WHY taking into account sex and gender in shared decision-making matters (of course, I believe that it does matter), but the case needs to be made more clearly with specific examples as to why it is essential to accurately measure, report, and discuss these constructs as the distinct characteristics that they are (sex vs gender identity). The whole value of the paper rests on people understanding and accepting WHY sex and gender considerations matter for SDM work.

Authors' response:

Thank you for your comments. We addressed your comments, had an English-language editor revise the whole paper. We particularly revised the Introduction and Discussion to put more emphasis on why taking sex and gender in SDM interventions matter and on the implications of our findings (Pages 2-39, lines 29-814).

Comment:

• These results are of interest and make a contribution, however, in their current form they are too vague and unclear as to make that contribution effectively. Substantial revisions to the writing, to the level of detail provided, and clearer examples and arguments from the authors would go a long way toward making the paper a substantive contribution to the SDM field.

Authors' response:

We revised the writing, increased the level of detail and provided clearer examples (Pages 17-29, lines 183 - 597).

Comment:

• The language/style of writing throughout the paper is not always clear, and in some cases is grammatically incorrect. The paper would benefit from a thorough review for language flow/accuracy.

Authors's response:

An English-language editor has revised the paper (Pages 2-39, lines 28-475).

Reviewer's comment:

• Inconsistent capitalization of sex/gender throughout paper.

Authors' response:

We corrected this throughout (Pages 2-39).

Reviewer's comment:

Abstract

• In background section of the abstract, the authors need to provide their rationale for WHY sex and gender matter for implementation interventions. Also, SDM should be defined and contextualized – are you looking at SDM in all fields? Only certain fields? Certain subpops? All patient populations?

Authors' response:

Thank you for your comment. We defined SDM in healthcare and explained why sex and gender matter as follows:

Shared decision making (SDM) in healthcare is an approach in which health professionals support patients in making decisions based on best evidence and their values and preferences. Considering sex and gender in SDM research is necessary to produce precisely-targeted interventions, improve evidence quality and redress health inequities. We provided more details in the background.

There were no restrictions on the patient populations. (Page 2, lines 30-40).

Revierwer's comment:

• Materials and methods: While challenging in a short space, more clarity about what was measured and how assessed is needed. Language is vague.

more clarity about what was measured and how assessed is needed.

Authors' response:

Thank you for comment. We provided more clarification about what was measured and assessed as follows:

We performed a secondary analysis of a Cochrane review of SDM interventions. We extracted study characteristics and their use of sex, gender or related terms (mention; number of categories). We assessed correct use of sex and gender terms using three criteria: “non-binary use”, “use of appropriate categories” and “non-interchangeable use of sex and gender”. We computed the proportion of studies that met all, any or no criteria, and explored associations between criteria met and study characteristics (Page 2-3, lines 41-52).

Reviewer's comment:

• Results: “sex/gender” in line 43 – is this that sex OR gender was measured? Or both? This is an important distinction that should be clarified.

Authors'response:

Thank you for pointing this out. We corrected this as follows: sex and/or gender; and applied throughout the paper and tables (Page 3, lines 53-64).

Revierwer's comment:

Introduction

• The introduction should be broken up into several paragraphs to improve readability/flow.

Separate into many other paragraphs to make it easy to read.

For instance, the first paragraph could focus first on defining SDM, the second on WHY SDM is important in clinical care, the third on research/ideas related to how gender and sex are essential to intervention effectiveness, and so on (rather than having all of the above in the first paragraph as currently stands)

Authors's response:

Thank you for your comment. We have extensively rewritten the Introduction. As suggested, we separated it into four paragraphs and four themes: The first paragraph is now about SDM (definition and importance clinical practice).

The second is about why sex and gender matter in health research, implementation research and specifically in SDM and SDM interventions.

The third is about sex and gender concepts and definitions according to the CIHR and the NIH, and underlines that the first step in sex and gender considerations is defining and using the terms appropriately (Pages 4-9, lines 74-198).

Reviewer's comment:

• Line 64-65: What is meant by “SDM can also facilitate care…” – what is meant by facilitating care? Give examples.

Also – if I interpret correctly, this sentence may be somewhat redundant to the prior sentence – if they are addressing different things, be specific – what does this sentence add?

Authors' response:

Thank you for your comment. We removed this sentence.

Rewiewer' comment:

• Lines 75-76: The authors write that sex and gender can offer insight into how to tailor implementation interventions for greater efficacy – this is ESSENTIAL to the purpose of the paper, so the authors would do well to add several sentences diving into this. HOW can sex and gender help increase intervention effectiveness? What specific studies have found this? How did they measure sex/gender? What did they find? What is the causal mechanism involved with this hypothesized pathway?

Author's response:

Thank you for your comment. We addressed the complex question of sex and gender in implementation research in more depth in the 2nd paragraph, as follows:

“In recent years, implementation scientists have hypothesized that implementation interventions would be more effective if they incorporated considerations of sex and gender (Tannenbaum et al., 2016; Oertelt-Prigione et al., 2011). Sex and gender are important determinants of illness. A review exploring the role of sex and gender as modifiers of the most common causes of death and morbidity underlined many sex/gender-based differences (Mauvais-Jarvis et al., 2020). According to authors, heart disease occurs in younger males with more obstructive coronary disease, whereas it occurs in older females with more coronary microvascular dysfunction. Furthermore, women are underdiagnosed for inflammatory airway disease, and have higher myocardial infarction mortality, fewer heart transplants (although they are more frequent donors) and overall receive less evidence-based treatment than men (Mauvais-Jarvis et al., 2020) Thus when findings for males and females are not disaggregated, results can hide important differences (Day et al., 2016; De Castro et al., 2016) Research has also shown differences in drug reactions and rehabilitation outcomes (Robles et al., 2014; Tamargo et al., 2017) . Interventions that take sex and gender into consideration are thus likely to offer more reliable evidence. Moreover, if authors fail to consider potential differences in the effectiveness of an intervention for men and women, there is a risk of bias, since it has not accurately assessed for whom the intervention is effective (Runnels et al., 2014). Furthermore, the structural influence of sex and gender on other variables is often neglected. Yet a wide range of health variables are gendered, for example, occupational status, working conditions, and access to sexual health services. (Campos-Serna, Ronda-Pérez et al. 2013)

Pelletier R et al. 2015) In implementation research, gender may be discussed under four constructs: gender roles, gender identity, gender relations and institutionalized gender. Each is associated with relevant measures, such as the Gender Role Conflict Index (O'Neil et al., 2013) and the Bem Sex Role Inventory (Bem et al., 1977).Implementation studies that consider these constructs will thus improve outcomes such as acceptability, feasibility, adoption and sustainability (Peters et al., 2013) (Pages 4-6, lines 92-121).

Reviewer's comment:

• In lines 80-99, it would help to put quotes around the terms you are defining. This paragraph is hard to follow.

Authors's response:

Corrected as suggested (Page 7-8, lines 159-179).

Reviewer's comment:

• For “gender diverse”, give examples of gender identities for the unfamiliar research (i.e., agender, nonbinary, transgender, Two-spirit, genderfluid, pangender, etc.)

Authors' responses:

Authots' comment:We gave examples as suggested (Page 8, lines 172-173).

Reviewer' comment:

• Authors periodically begin sentences with “It” and seem to be referring to sex or gender, however it is hard to follow – be more specific.

Authors' response:

We corrected this and added more concrete details (Pages 4-9, lines 74-198).

Reviewer's comment:

• Line 96-97: “All individuals act in ways that fulfill the gender expectations…” – definitely not true. Many people act in ways that DO NOT fulfill the gender expectations of their society – this is part of why critical gender analysis is such a focus. What is meant by this original sentence? Context is lacking .

Authors' response:

Thank you for pointing this out. We were trying to express societal expectations of normative behaviour but worded it wrongly. We have removed the phrase.

Reviewer's comment:

Materials and methods

• Criteria for including studies: lines 134-135: section on comparison with another intervention being absent – this does not make sense. Does this mean only studies that did NOT compare the intervention to another intervention were included? Why is that? What is the rationale? Or if it does not mean this, what does it mean?

• Language unclear throughout. More detail/specifics needed.

Authors' responses:

Thank you for your comment. We corrected this as follows:

Comparisons included usual care or other interventions targeting either health professionals, patients or both.

We clarified our language and provide more details

Reviewer's comment:

• Process for assessing sex and gender considerations: more clarity needed throughout. Where possible, give specific examples. For example – the statement in line 143: “First, sex and gender are non-binary variables.” This section is setting up for later sections with more detail, but on first read, it leaves the reader wanting a lot more information right from the start. Either clarify that this information will be provided later or consider streamlining this section and just diving directly into the more specific sub-sections that follow

Authors'response:

Thank you for your comment. We have substantially rewritten this section. We reduced the introductory “Process” paragraph as follows:

To assess sex and gender considerations in each of the studies retained, we evaluated the use of such terms by measuring frequencies of the use of sex- and gender-related terms and determining categories used to further describe them. Then we assessed studies according to three criteria for the appropriate use of sex and gender terms according to the definitions of sex and gender proposed by the CIHR (27) and the NIH (29). These criteria were “non-binary use”, “use of appropriate categories” and “non-interchangeable use of sex/gender".

We moved the rationale for each criterion into the specific subsections that follow (Page 11, lines 230-238).

Reviewer's comment:

• Lines 147-148: be careful with language here. What is mean by “typical definition” of female or male? Data collection process.

Authors' response:

We removed this phrase.

Reviewer comment:

• Lines 227-230: What software (if any) was used to manage and analyze extracted data?

Authors' response:

We provided this in the section “data analysis”. We used SAS Software to analyze extracted data (Page 17, line 381).

Reviewer's comment:

Data analysis

• Line 243: list explicitly the characteristics meant by “characteristics of studies” to summarize/make obvious for reader: i.e., “….according to the characteristics of studies, which included: year of publication, region in which study conducted, study population, etc…”

Authors' response:

Thank you for your comment. We specified the characteristics (Page17, lines 370-372).

Reviewer' comment:

• Authors list the statistical tests performed, but do not indicate which tests were used for which assessments. More detail is needed to evaluate the appropriateness of testing conducted.

Author's response:

Thank you for your comment. We indicated the tests and the assessment for which we used them in data analysis section and in a footnote of Table 3. We also provided references about each test (Page 17, lines 478-380;

Table 3 : Page 29, line 597).

Reviewer's comment:

• Line 269: “sex/gender” again used, without clarity as to whether this mean one or the other, versus BOTH.

Authors's response:

Thank you for your comment. We have corrected this to sex and/or gender meaning sex, gender or both. We defined it at its first use in the text and used this term throughout (Page 12, Line 272).

Reviewer's comment:

• Table 1 and Table 3:

o for year of publication, give range of years (i.e., 2000-2015, vs 2016-2017) for specificity

Authors's response:

Thank you for the precision. We provided the range of the year of publication in a footnote (Pages 19 and 29).

Reviewer's comment:

o Instead of saying “countries”, say “regions” as you are comparing on region, not country

Authors's response:

We replaced “countries” with “regions” (Pages 19 and 29).

Reviewer's comment:

o Order patients/hc professionals above “both”, as otherwise “both” is confusing before you know what the other options are

Authors's response:

Thank you for your comments. We ordered categories as suggested (Pages 19 and 29).

Reviewer's comment:

o “sex and/or gender” is confusing in this table – shouldn’t it be, “sex AND gender”?

Authors' response:

Thank you for your comment. We replaced this with sex and/or gender (Page 19).

Reviewer's comment:

o Why is “boy” not included in Table 1 under “related terms mentioned”

Authors' response:

Thank you for noticing this. In fact, “Boy” was not used in any study. We added a sentence to this effect. (Page 18, line 407).

Reviewer comment:

• Language unclear/vague/incorrect in some sentences: i.e., Line 293-294 “Authors used sex as non-binary variable in no study”. Same for lines 307-308, 331-332, 373, etc.

Authors's response:

Thank you for your comment. We corrected this: “e.g. Authors did not use gender as a non-binary variable » line 441. The whole section has been revised by an English-language editor (Page 20, line 441).

Reviewer's comment:

• Table 2:

o What is “respect of the criteria (2 and 3)” representing? What does this mean?

Authors's response: We removed this sentence.

Reviewer's comment:

• Line 354: “Countries” should be “regions” throughout.

Author's response:

We replaced “countries” by “regions” throughout the text (Page 16, line 344 to page 29 (table 3)).

Reviewer's comment:

Discussion

• Overall, the discussion should be shortened/tightened, remove speculation, and provide MUCH more specific commentary. A thorough grammar review is also warranted, especially on page 24

Authors's response:

Thank you for your comments, we completely rewrote our discussion as suggested and revised the language (Pages 30-38; lines 600-798).

Reviewer's comment:

• More is needed to discuss the implications of sex and gender (measurement and reporting) for shared decision-making. Why does sex/gender matter for SDM? What has this review taught us about state of sex/gender measurement/reporting in SDM intervention studies? What are the implications of these findings for future SDM work? The authors mention these things but very vaguely – instead, the authors should add detail to provide information on specific findings from studies that have established the importance of sex/gender for SDM, and specific suggestions for how future SDM research should measure/report on sex/gender as a result of these findings, and why

Authors's response:

Thank you for your comments, which have helped us completely revise the discussion (see below) (Pages 30-38; lines 600-798).

Reviewer's comment:

• Feels that discussion could be broadly restructured/focused as follows:

o First: succinct narrative summary of main findings: no study met all three criteria for correct reporting on sex/gender. This did not vary by measured study characteristics.

o Second: implications of this finding for existing SDM research, and future SDM research

o Third: strengths/limitations

o Fourth: conclusions � recommendations from authors based on findings

• More specifically: authors could recommend measures of sex and gender that SDM researchers could use going forward – there is a rich literature on measurement of sex and gender identity that they could draw from and cite.

Authors' response:

Thank you for your comment. We restructured the discussion as follows:

First paragraph – narrative summary of findings.

Second paragraph, implications of findings, especially the interchangeable use of sex and gender, and the fact that time and place of publication etc. seem to make no difference.

Third, implications of the fact that no studies used non-binary variables: Non-binary people are an important and increasingly vocal segment of the population with their own specific physical and mental health issues. Many already feel excluded by the health system, and being invisible in research results will be a further alienating factor »

Third, a paragraph that deals with the measuring of sex (especially non-binary) and gender and discusses whether gender is better captured using categorical or continuous data, with examples. It also mentions the extra difficulty of measuring gender in secondary data analyses and proposes solutions.

Finally, a paragraph proposing how to capture sex and gender data (often interrelated) in questionnaires (Pages 30-38; lines 600-798).

Submitted filename: Response to reviewers.docx

Click here for additional data file.

25 Sep 2020

Sex and gender considerations in implementation interventions to promote shared decision making: A secondary analysis of a cochrane systematic review

PONE-D-20-16595R1

Dear Dr. Légaré,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Thank you for revising this work and making it even clearer and more comprehensible.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. 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.

Kind regards,

Robert S. Phillips

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

29 Sep 2020

PONE-D-20-16595R1

Sex and gender considerations in implementation interventions to promote shared decision making: A secondary analysis of a Cochrane systematic review

Dear Dr. Légaré:

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.

If we can help with anything else, please email us at plosone@plos.org.

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

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr Robert S. Phillips

Academic Editor

PLOS ONE