Development and Psychometric Evaluation of the Preconception Health Knowledge Questionnaire

Abstract

Purpose:

To develop and psychometrically test a comprehensive measure of preconception health knowledge.

Design:

Cross-sectional survey, in May and June, 2019.

Setting:

Alberta, Ontario, and Québec, Canada.

Sample:

One thousand seven hundred seventy-seven women and men with ≥1 children born in the last 5 years or planning a pregnancy in the next 5 years.

Measures:

Using prior literature and input from public health nurses and physicians, the Preconception Health Knowledge Questionnaire (PHKQ) was developed and comprised 25 multiple choice questions on reproductive history, sexual health, infectious diseases, chronic medical conditions, mental health, medications, immunizations, lifestyle behaviors, psychosocial stressors, and environmental exposures.

Analysis:

Psychometric testing was undertaken to evaluate item difficulty, discrimination, quality of response alternatives, internal consistency, and construct validity.

Results:

Participants had a mean total score of 15.8/25 (SD = 3.9); women and men had mean total scores of 16.2 (SD = 3.6) and 13.8 (SD = 4.7), respectively. Most items were neither too difficult nor too easy, discriminated well between participants with high and low knowledge, and had appropriate response alternatives. High internal consistency (KR-20 = 0.87) and construct validity, shown via significant correlations with education level and previous preconception care receipt, were demonstrated.

Conclusion:

The PHKQ is a reliable and valid tool for measuring preconception health knowledge and may be useful in identification of high-risk groups in need of preconception health education and evaluation of preconception health interventions.

Keywords

health promotion men’s health preconception care psychometrics women’s health

Purpose

Poor perinatal outcomes persist in North America despite advances in medical care.¹ Because 50% of pregnancies are unplanned,² risk factors for these outcomes can go unaddressed until the first prenatal appointment, which is often too late for preventive action to be taken. Women’s and men’s health before pregnancy (preconception health) is increasingly being recognized as having a significant impact on perinatal outcomes.^3

-6 Preconception health refers to the health of reproductive-aged individuals, regardless of sex, sexual orientation, or pregnancy intentions.⁷ The time between childbirth and the beginning of a subsequent pregnancy (the interconception period) is an integral component of preconception health because most North American families have 2 children.⁸ The time before and between pregnancies is therefore a critical opportunity for health promotion, including identifying modifiable health behaviors, optimizing nutrition, stabilizing chronic disease, and preventing unintended pregnancy.

One commonly used outcome for evaluating such efforts is preconception health knowledge.⁹ While knowledge must be considered within the context of the social determinants of health and the systemic barriers that affect individuals’ abilities to act on their knowledge, Social Cognitive Theory and the Theoretical Domains Framework^10

-13 show that lack of knowledge is an obstacle to health behavior change.¹⁴ Knowledge can be measured with simple, efficient, and cost-effective methods, making it a more accessible indicator of changes related to preconception health than long-term behavior change or incidence of rare outcomes such as congenital anomalies. Previous assessments of preconception health knowledge have been limited in their comprehensiveness, omitting questions about men’s health, the interconception period, and psychosocial stressors.⁹ A comprehensive measure of preconception health knowledge is needed for evaluation of health interventions.

Our objective was to develop and psychometrically test a measure of preconception health knowledge, the Preconception Health Knowledge Questionnaire (PHKQ).

Methods

Design

The PHKQ was developed and tested using data from a cross-sectional survey assessing preconception care attitudes, beliefs, and intervention preferences of women and men in Alberta, Ontario, and Québec, Canada, in May and June, 2019. Participants were recruited via online study promotion, identification in existing research databases, and referrals from ongoing cohort studies. Interested individuals received an introductory email after contacting the research team. Those who agreed to participate received a link to an online consent form and questionnaire using RedCAP. Research assistants were available to assist individuals who had trouble accessing the online questionnaire or required reminder follow-up telephone calls. The study received ethics approval from the University of Toronto and University of Alberta.

Sample

Women and men were eligible if they had ≥1 children in the past 5 years or planned to have children within 5 years, spoke English, and had access to a telephone or the Internet.

Measures

Development of the PHKQ was informed by a systematic review on preconception health knowledge tools.⁹ The PHKQ adapted 8 items from the Locally Driven Collaborative Project Healthy Pregnancy Knowledge Survey,¹⁵ which assessed pregnancy, lifestyle, and breastfeeding knowledge in women attending prenatal programs, and 2 items from a study by Coonrod et al,¹⁶ which used a 15-item tool to evaluate knowledge on maternal age, family and genetic history, medication use, tobacco use, alcohol and substance use, infectious disease, immunization, psychosocial stressors, nutrition, physical activity, and environmental exposures. Based on consultation with 6 public health nurses, one health promotion specialist, and 2 family physicians, 15 items were added related to interconception health, men’s health, mental health, specific immunizations, and weight changes. The final tool had 25 items covering: reproductive life plans and history, sexual health, infectious diseases, medications, chronic diseases, mental health, tobacco use, alcohol and other substance use, immunizations, nutrition, weight, physical activity, psychosocial stressors, and environmental exposures (Table S1). Questions used a multiple-choice format with one or several correct answers (“select all that apply”). For items with one correct answer, correct responses were given a score of 1, and incorrect or “don’t know” answers a score of 0. For items with >1 correct answer, a score of 1 was given if the participant selected all correct answers, and a score of 0 if the participant did not select all correct answers or selected “don’t know.” Scores were summed to a total of 25.

Data were collected on age, sex, education, employment status, annual household income before taxes, immigration status, marital status, number of children, and plans to become pregnant in the next 5 years. We additionally measured receipt of any previous preconception care from a health care provider, and attitudes toward preconception care rated on a Likert-type scale from “very important” to “not at all important” and assessed by the question “How important do you consider preconception health for the public, in general?”

Analysis

The sample was described using frequencies and percentages, or means and standard deviations (SD). Total knowledge scores were calculated by summing the number of correct responses. The distribution of total scores was evaluated using measures of skewness and kurtosis. Central tendency was captured using the mean and SD, median and interquartile range (IQR), and range. The PHKQ psychometric assessment, described below, was conducted for the cohort overall and women and men separately. Analyses uses SPSS v. 25 and Mplus v. 7.31.

To calculate item difficulty, the number of correct responses for each item separately was divided by the total sample size. Items answered correctly by >90% of the sample were flagged as too easy, and those answered correctly by <10% as too difficult.¹⁷

Item discrimination was calculated using methods described by Kline.¹⁸ First, the sample was divided into 2 groups representing respondents with the highest and lowest scores (23% of respondents in each of the highest and lowest score groups in the overall sample, and 25% and 29% among women and men, respectively). Next, the total number of correct responses in the highest score group was subtracted by the total number of correct responses in the lowest score group. This number was then divided by group size (overall sample: n = 256, women: n = 250, men: n = 65). Item discrimination scores range from 1 (perfect correlation between answering a question correctly and scoring well on the test) and -1 (perfect correlation between answering a question incorrectly and scoring well), with values >0.2 recommended.¹⁷

To evaluate quality of an alternative response, the frequency and proportion of respondents who selected alternative responses other than “don’t know” were tabulated. Response alternatives with 0% or 100% uptake were flagged as not attractive or too attractive.

We assessed internal consistency by calculating the Kuder and Richardson Formula 20 (KR-20) coefficient.¹⁹ As Cronbach’s alpha is criticized, especially for binary data,²⁰ we also calculated composite reliability using standardized factor loadings from a unidimensional model of the PHKQ using Mplus (v. 7.31).

Finally, we tested construct validity using the known-groups method, comparing those with low versus high education, and those who had received preconception care versus those who had not, using independent t-tests. We hypothesized that those with less education and those who had never received preconception care would have lower scores than those with higher education and who had received preconception care. Statistical significance was established using a 2-sided p < 0.05. We also calculated the correlation between PHKQ scores and scores on a measure of preconception attitudes, using Spearman’s rho correlation coefficient. We considered a moderate sized correlation (ρ ≥ 0.3) as indicating a similarity in constructs.

Results

In total, 1,177 participants (n = 977 women, n = 200 men) provided responses to the PHKQ. Their mean age was 34.2 years (SD = 5.0). One-quarter of the sample had a college education or less (23.0%), 34.7% were not working for full- or part-time pay, and 28.5% had a household income <$75,000 CAD. Nearly 1 in 5 were born outside of Canada (17.4%). Most respondents were married (95.2%) and had children (97.0%), and 47.8% were planning to become pregnant in the next 5 years (Table 1).

Table 1.

Characteristics of the Study Sample.

Characteristic	Full sample	Women	Men
Characteristic	(n = 1177)	(n = 977)	(n = 200)
Age (years), mean (SD)	34.2 (5.0)	33.8 (4.4)	35.9 (6.8)
Marital status
Married/common-law	1,120 (95.2)	^*	^*
Single/divorced/separated/widowed	57 (4.8)	^*	^*
Education level
Any high school or college	271 (23.0)	218 (22.3)	53 (26.5)
University degree	906 (77.0)	759 (77.7)	147 (73.5)
Employment status
Paid part- or full-time employment	768 (65.3)	586 (60.0)	182 (91.0)
No paid employment	409 (34.7)	391 (40.0)	18 (9.0)
Total combined family income before taxes
Less than $75,000 CAD	336 (28.5)	291 (29.8)	45 (22.5)
$75,000 CAD or above	841 (71.5)	686 (70.2)	155 (77.5)
Born in Canada
Yes	972 (82.6)	803 (82.2)	169 (84.5)
No	205 (17.4)	174 (17.8)	31 (15.5)
Number of children
Zero	35 (3.0)	29 (3.0)	6 (3.0)
One	404 (34.3)	346 (35.4)	58 (29.0)
Two	586 (49.8)	478 (48.9)	108 (54.0)
Three or more	152 (12.9)	124 (12.7)	28 (14.0)
Planning to get pregnant in the next 5 years
No	614 (52.2)	498 (51.0)	116 (58.0)
Yes	563 (47.8)	479 (49.0)	84 (42.0)

Data presented as n (%) unless otherwise indicated.

* Cannot report due to insufficient sample size.

The mean total PHKQ score for the overall sample was 15.8/25 (63.2%, SD = 3.9); the median score was 16 (64.0%, IQR = 14-18). The distribution of total scores was slightly negatively skewed (-1.05, Standard Error [SE] = 0.07), with minimal kurtosis (1.82, SE = 0.14). Scores ranged from 0 to 25. For women, the total mean score was 16.2 (64.8%, SD = 3.6); the median score was 17 (68.0%, IQR = 14-19). For men, the total mean score was 13.8 (55.2%, SD = 4.7); the median score was 14 (56.0%, IRQ = 11-17). For women and men, the distribution of the summary score was slightly negatively skewed and had minimal kurtosis.

For the overall sample, items ranged in difficulty from 18% correct (Q15) to 96% correct (Q9) (Table 2). When stratified by gender, men answered fewer items correctly on average. Exceptions to this were Q4 and Q11, where a slightly higher percentage of men answered correctly compared to women (Table S2).

Table 2.

Response Proportions and Discrimination Indices for Each Item in the Preconception Health Knowledge Questionnaire.

Item	Full sample (n = 1,177)
	Correct		Incorrect		Don’t know		D index*
	N	Proportion	N	Proportion	N	Proportion	D index*
1. What percentage of pregnancies are unplanned?	269	0.23	264	0.22	644	0.55	0.38
2. If you are thinking about getting pregnant, when is the right time for you and your partner (if you have a partner) to visit a family doctor, nurse, or other health care provider?	828	0.70	295	0.25	54	0.05	0.50
3. Success of getting pregnant (either on your own or with medical help like in vitro fertilization) is lower for women who are:	901	0.77	150	0.13	126	0.11	0.33
4. The quality of a man’s sperm decreases:	166	0.14	522	0.44	489	0.42	0.21
5. The best amount of time between pregnancies is:	488	0.41	332	0.28	357	0.30	0.45
6. Women who have had a caesarean section should wait how long to try to get pregnant again?	278	0.24	432	0.37	467	0.40	0.39
7. Sexually transmitted infections (STIs):	957	0.81	23	0.02	197	0.17	0.52
8. If you have a chronic medical condition, it is important to speak with your health care provider before getting pregnant to:	984	0.84	124	0.11	69	0.06	0.44
9. If you are taking medications, it is important to:	1128	0.96	15	0.01	34	0.03	0.17
10. Which of the following could impact the health of your pregnancy?	1064	0.90	57	0.05	56	0.05	0.36
11. A history of depression or anxiety before pregnancy:	463	0.39	573	0.49	141	0.12	0.53
12. Some things you can do to improve mental health include:	1093	0.93	59	0.05	25	0.02	0.25
13. Which of the following can be hazardous to fertility and pregnancy?	1089	0.93	63	0.05	25	0.02	0.23
14. How many alcoholic drinks should women who are pregnant or planning a pregnancy have?	1096	0.93	45	0.04	36	0.03	0.18
15. Which of the following immunizations cannot be given during pregnancy?	215	0.18	257	0.22	705	0.60	0.33
16. Being overweight or underweight can affect:	1060	0.90	72	0.06	45	0.04	0.34
17. A healthy weight gain in pregnancy is:	645	0.55	410	0.35	122	0.10	0.41
18. Folic acid should be taken by:	621	0.53	443	0.38	113	0.10	0.63
19. Healthy nutrition, which can improve your fertility and chances of a healthy pregnancy, should include:	881	0.75	229	0.19	67	0.06	0.49
20. How much moderate/vigorous physical activity should reproductive-age persons get per week?	346	0.29	536	0.46	295	0.25	0.45
21. Feeling very stressed or not having enough money to make ends meet may:	779	0.66	178	0.15	220	0.19	0.61
22. Intimate partner violence tends to:	423	0.36	131	0.11	623	0.53	0.61
23. Which of the following environmental exposures should women limit or avoid when planning a pregnancy or in pregnancy?	891	0.76	211	0.18	75	0.06	0.52
24. Some types of fish should be avoided when planning a pregnancy or in pregnancy because:	1082	0.92	9	0.01	86	0.07	0.25
25. Which of the following describes a partner’s role in preparing for pregnancy?	830	0.71	228	0.19	119	0.10	0.60

* Discrimination index, or D Index, indicates the correlation between an individual answering the question correctly and scoring well on the test. Values >0.2 are recommended.

Five items were flagged as too easy because >90% of respondents in the overall sample answered correctly (Q9, Q12-14, Q24), whereas no items were flagged as too difficult. In the sample of women, 7 questions were flagged as too easy (Q9, Q10, Q12-14, Q16, Q24) compared to only 1 question (Q9) for men. While no questions were too difficult in the women-only sample, 1 question (Q15) was too difficult in the sample of men.

For the overall sample, the items ranged in the discrimination index from 0.17 to 0.61. While no items had a negative discrimination value, 2 (Q9, Q14) had less than desirable values (<0.20) (Table 2). Because both questions were also found to be too easy, the discrimination value is less informative. In women alone, 4 items had low discrimination (Q9, Q12, Q14, Q24); these correspond to the items also flagged as too easy. In men, only 1 item had low discrimination (Q15), which was also the item flagged as being too difficult. No items had poor discrimination that were not already flagged as being too easy or too difficult.

None of the response alternatives were answered by 0% or 100% of respondents; however, 3 items (Q9, Q14, Q24) had extremely low use of one or more alternative options (<1%) (Table 3).

Table 3.

Quality of Alternative Response Options for Overall Sample.

Item	A	B	C	D	E
Q1	31 (2.6)	182 (15.5)	269 (22.9)^*	51 (4.3)
Q2	828 (70.3)^*	266 (22.6)	17 (1.4)	12 (1.0)
Q3	54 (4.6)	96 (4.7)	901 (76.6)^*
Q4	166 (14.1)^*	292 (24.8)	230 (19.5)
Q5	488 (41.5)^*	276 (23.4)	56 (4.8)
Q6	277 (23.5)	278 (23.6)^*	155 (13.2)
Q7	47 (4.0)	61 (5.2)	373 (82.7)^*
Q8	1023 (86.9)^*	1008 (85.6)^*	1078 (91.6)^*
Q9	12 (1.0)	1128 (95.8)^*	3 (.3)
Q10	1120 (95.2)^*	1097 (93.2)^*	1077 (91.5)^*
Q11	924 (78.5)^*	942 (80.0)^*	487 (41.4)^*
Q12	1138 (96.7)^*	1130 (96.0)^*	1133 (96.3)^*	1111 (94.4)^*
Q13	1151 (97.9)^*	1100 (93.5)^*	1129 (95.9)^*
Q14	27 (2.3)	9 (.8)	9 (.8)	1096 (93.1)^*
Q15	288 (24.5)^*	360 (30.6)^*	108 (9.2)
Q16	1118 (95.0)^*	1085 (92.2)^*	1098 (93.3)^*
Q17	120 (10.2)	290 (24.6)	645 (54.8)^*
Q18	626 (53.2)^*	844 (71.7)	822 (69.8)	406 (34.5)
Q19	1111 (94.4)^*	971 (82.5)^*	946 (80.4)^*
Q20	83 (7.1)	153 (13.0)	299 (25.4)	345 (29.4)^*
Q21	882 (74.9)^*	820 (69.7)^*	173 (14.7)
Q22	99 (8.4)	423 (35.9)^*	32 (2.7)
Q23	86 (7.3)	1059 (90.0)^*	1040 (88.4)^*	55 (4.7)	983 (83.5)^*
Q24	1082 (91.9)^*	5 (.4)	4 (.3)
Q25	979 (83.2)^*	946 (80.4)^*	903 (76.7)^*

* Correct answer.

Note: Percentages do not add up to 100% due to multiple correct answers and/or “don’t know” responses.

The KR-20 statistic was 0.87 for the overall sample, 0.84 for women, and 0.91 for men. Composite reliability was calculated using a univariate model that accounted for 33% of the total variance in the overall sample, 30% in women, and 39% in men. Composite reliability was 0.91 for the whole sample, 0.90 for women, and 0.93 for men.

The mean total score was significantly lower among those with less education and among those who had never received preconception care, as hypothesized. This was true of the overall sample (Table 4) and of the samples of women and men alone (Table S3), though the mean difference was greater among men. We detected a correlation between attitudes about preconception care and total knowledge score of 0.22 for the overall sample (ρ = 0.19 for women, ρ = 0.20 for men), but it was lower than our criterion (ρ ≥ 0.30).

Table 4.

Tests of Construct Validity for the Overall Sample.

Type of test	Groups/concept	Overall (n = 1177)
Type of test	Groups/concept	Mean (SD) or ρ^*	t	p-value
Known-group	Education level
	University degree	16.0 (3.7)	−3.54	<.001
	High school or college	15.0 (4.5)
	Prior preconception care
	Yes	17.1 (3.3)	−9.32	<.001
	No	15.0 (4.1)
Related concept	Importance of preconception care	0.22^*		<.001

* Spearman’s rho.

Discussion

We described the development and psychometric properties of a 25-item preconception health knowledge tool tested in a cohort of 1,177 women and men across Canada. The PHKQ examined a comprehensive range of preconception and interconception health topics as determined by previous literature and consultation with public health professionals. Results indicate the PHKQ had good psychometric properties and could be valuable as an outcome measure in intervention and other studies evaluating preconception health.

Men generally scored lower on the PHKQ, indicating that items were more difficult for men than women. This difference between men and women is consistent with studies comparing women’s and men’s knowledge regarding contraception and pregnancy.^21
-23 Notably, only a small fraction of studies that have tested preconception health knowledge have included male participants.⁹ This may be indicative of the lack of education provided to men regarding preconception health, compared to women.^24,25 Our results provide evidence that fathers must be included in preconception interventions, given low preconception knowledge and known paternal effects on reproductive health.²⁶ Results may also indicate the PHKQ is somewhat easy for women, particularly those with children already, and requires adaptation.

Based on item-level analysis, there is 1 item that should be removed or updated (Q9, on medication use), as it was too easy for women and men. While there were 6 other items that could be removed because they were too easy for women (Q10, on medication use; Q12, on sleep, nutrition, and exercise; Q13, on tobacco use; Q14, on alcohol use; Q16, on weight; and Q24, on fish consumption), we suggest retaining these items for future testing because they showed adequate difficulty for men. Similarly, there was 1 item that was too difficult for men, but not women, that should also be retained for testing (Q15, on immunizations). The alternative response options for Q9, Q14, and Q24 could also be revised, as they were selected infrequently.

The PHKQ had high composite reliability and construct validity. Higher scores in groups with higher education levels and prior preconception care receipt are consistent with studies showing individuals with higher education levels tend to have better health literacy^27,28 and those showing the effectiveness of preconception interventions in improving knowledge.^9,29 Correlation between PHKQ scores and preconception care attitudes was not strong. Preconception care attitudes could be more related to perceived or desired knowledge than actual knowledge. This finding could also be indicative of the limitations of health knowledge, wherein knowledge itself does not guarantee behavior or attitude change.^10

-13

Strengths of our study include the large sample comprising women and men across Canada. Males are understudied in preconception health research, making our study unique. However, participants were generally well-educated, married, and with high incomes, which limits the generalizability of the results. We also did not have data on individuals who did not complete the survey and whether they were different from those who responded. Importantly, 97% of participants were already parents and thus were more likely to be knowledgeable regarding preconception health than nulliparous individuals. The survey was not conducted in a practice setting. We do not know whether and how individuals would answer PHKQ questions in such settings. The PHKQ should be tested in a sample with a greater range in socioeconomic background, with nulliparous individuals, and in different practice settings, as these variables may impact preconception health knowledge.^16,30

Growing recognition of the role of preconception health in reproductive and perinatal outcomes has resulted in an increase in the number of preconception interventions over the last 10 years.^3,7,31 Knowledge is often used as a main outcome to evaluate such interventions,^9,29 though few tools have been validated, and rarely include items on men’s health, psychosocial stressors, mental health, or interconception health, despite their relevance to perinatal health.^25,31

-34 Items addressing these subjects were incorporated into the PHKQ, making it one of the most comprehensive preconception health knowledge tools to date. With further validation of the tool in diverse samples, PHKQ scores could eventually be used to identify targets for new preconception interventions for high-risk populations, tailor preconception interventions for women and men separately, inform providers about the specific areas of preconception health in which individuals would benefit from education or follow-up, and evaluate the effectiveness of interventions. To shift reproductive and perinatal outcomes, however, individual knowledge assessments for education-focused interventions must be conducted in concert with population-level efforts including policy changes and communication campaigns.

So What? (Implications for Health Promotion Practitioners and Researchers)

What is already known on this topic?

Preconception health promotion interventions frequently use measures of preconception health knowledge to evaluate their effectiveness, but such tools have not been validated.

What does this article add?

We developed and psychometrically tested the 25-item Preconception Health Knowledge Questionnaire in a sample of 1,777 Canadian women and men, demonstrating its reliability and validity.

What are the implications for health promotion practice or research?

The Preconception Health Knowledge Questionnaire is useful for measuring preconception health knowledge and may be applied in the identification of high-risk groups in need of preconception health education and evaluation of preconception health interventions.

Supplemental Material

Supplemental Material, sj-pdf-1-ahp-10.1177_0890117120946682 - Development and Psychometric Evaluation of the Preconception Health Knowledge Questionnaire

Supplemental Material, sj-pdf-1-ahp-10.1177_0890117120946682 for Development and Psychometric Evaluation of the Preconception Health Knowledge Questionnaire by Zoe Cairncross, Cindy-Lee Dennis, Sarah Brennenstuhl, Saranyah Ravindran, Joanne Enders, Lisa Graves, Catriona Mill, Deanna Telner and Hilary K. Brown in American Journal of Health Promotion

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by a Canadian Institutes of Health Research Healthy Life Trajectories Initiative grant to Dr. Cindy-Lee Dennis. The sponsor had no role in the study design; collection, analysis, or interpretation of data, writing of the manuscript, or decision to submit the proposal for publication.

ORCID iD

Hilary K. Brown

Supplemental Material

Supplemental material for this article is available online.

References

Joseph

Liston

Dodds

Dahlgren

Allen

. Socioeconomic status and perinatal outcomes in a setting with universal access to essential health care services. CMAJ. 2007;177(6):583–590.

Finer

Zolna

. Unintended pregnancy in the United States: incidence and disparities, 2006. Contraception. 2011;84(5):478–485.

Allen

Armson

Wilson

, et al. Teratogenicity associated with pre-existing and gestational diabetes. JOGC. 2007;29(11):927–934.

Herman

Janz

Becker

Prochownik

. Diabetes and pregnancy: preconception care, pregnancy outcomes, resource utilization and costs. Obstet Gynecol Surv. 1999;54(8):489–491.

Kassebaum

Villa

Coggeshall

, et al. Global, regional, and national levels and causes of maternal mortality during 1990–2013: a systematic analysis for the global burden of disease study 2013. Lancet. 2014;384(9947):980–1004.

World Health Organization. Pre-Conception Care: Maximizing the Gains for Maternal and Child Health. World Health Organization; 2013.

Ontario Public Health Organization. Shift–Enhancing the Health of Ontarians: A Call to Action for Preconception Health Promotion and Care. Ontario Public Health Association; 2014.

Statistics Canada. Population Size and Growth in Canada: Key Results From the 2016 Census. Statistics Canada; 2017.

Cairncross

Ravindran

Yoganathan

, et al. Measurement of preconception health knowledge: a systematic review. Am J Health Promot. 2019;33(6):941–954.

10.

Bandura

. Health promotion by social cognitive means. Health Educ Behav. 2004;31(2):143–164.

11.

Cane

O’Connor

Michie

. Validation of the theoretical domains framework for use in behaviour change and implementation research. Implement Sci. 2012;7(1):37.

12.

Novakofski

Karduck

. Improvement in knowledge, social cognitive theory variables, and movement through stages of change after a community-based diabetes education program. J Acad Nutr Diet. 2005;105(10):1613–1616.

13.

O’Leary

Goodhart

Jemmott

Lattimore

. Predictors of safer sex on the college campus: a social cognitive theory analysis. J Am Coll Health. 1992;40(6):254–263.

14.

Dyson

Lawton

Jackson

Cheater

. Does the use of a theoretical approach tell us more about hand hygiene behaviour? The barriers and levers to hand hygiene. J Infect Prev. 2011;12(1):17–24.

15.

Godin

Alton

Gangodawilage

, et al. Knowledge change associated with participation in prenatal education programs in Ontario: a cohort study. CJPH. 2015;106(6): e401–e407.

16.

Coonrod

Bruce

Malcolm

Drachman

Frey

. Knowledge and attitudes regarding preconception care in a predominantly low-income Mexican American population. AJOG. 2009;200(6):686.686.e1-e7.

17.

Beeckman

Vanderwee

Demarré

Paquay

Van Hecke

Defloor

. Pressure ulcer prevention: development and psychometric validation of a knowledge assessment instrument. Int J Nurs Stud. 2010;47(4):399–410.

18.

Kline

. Modern test theory: assumptions, equations, limitations, and item analyses. In: Kline

ed. Psychological Testing: A Practical Approach to Design and Evaluation. Sage Publications, Inc; 2005:107–166.

19.

Kuder

Richardson

. The theory of the estimation of test reliability. Psychometrika. 1937;2(3):151–160.

20.

McNeish

. Thanks coefficient alpha, we’ll take it from here. Psychol Methods. 2018;23(3):412–433.

21.

Frost

Lindberg

Finer

. Young adults’ contraceptive knowledge, norms and attitudes: associations with risk of unintended pregnancy. Perspect Sex Reprod Health. 2012;44(2):107–116.

22.

Delgado

. Undergraduate student awareness of issues related to preconception health and pregnancy. Matern Child Health J. 2008;12(6):774–782.

23.

Mitchell

Levis

Prue

. Preconception health: awareness, planning, and communication among a sample of US men and women. Matern Child Health J. 2012;16(1):31–39.

24.

Frey

Engle

Noble

. Preconception healthcare: what do men know and believe? J Mens Health. 2012;9(1):25–35.

25.

Frey

Navarro

Kotelchuck

. The clinical content of preconception care: preconception care for men. AJOG. 2008;199(6):S389–S395.

26.

O’Brien

Hurley

Linsley

McNeil

Fletcher

Aitken

. Men’s preconception health: a primary health-care viewpoint. Am J Mens Health. 2018;12(5):1575–1581.

27.

van der Heide

Wang

Droomers

Spreeuwenberg

Rademakers

Uiters

. The relationship between health, education, and health literacy: results from the Dutch Adult Literacy and Life Skills Survey. J Health Commun. 2013;18(suppl 1):172–184.

28.

Kickbusch

. Health literacy: addressing the health and education divide. Health Promot Int. 2001;16(3):289–297.

29.

Stephenson

Heslehurst

Hall

, et al. Before the beginning: nutrition and lifestyle in the preconception period and its importance for future health. Lancet. 2018;391(10132):1830–1841.

30.

Frey

Files

. Preconception healthcare: what women know and believe. Matern Child Health J. 2006;10(1):73–77.

31.

Brown

Mueller

Edwards

, et al. Preconception health interventions delivered in public health and community settings: a systematic review. CJPH. 2017;108(4):388–397.

32.

Agudelo

Bermúdez

Kafury Goeta

. Birth spacing and risk of adverse perinatal outcomes: a meta-analysis. JAMA. 2006;295(15):1809–1823.

33.

Sarkar

. The impact of intimate partner violence on women’s reproductive health and pregnancy outcome. J Obstet Gynaecol. 2008;28(3):266–271.

34.

Witt

Wisk

Cheng

Hampton

Hagen

. Preconception mental health predicts pregnancy complications and adverse birth outcomes: a national population-based study. Matern Child Health J. 2012;16(7):1525–1541.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.46 MB