A systematic review of interventions to improve male knowledge of fertility and fertility-related risk factors

Figures & data

Table 1. PICO framework.

Population	Males aged ≥ 16 years, without a diagnosis of infertility (i.e. presumed fertile)
Intervention	Non-clinical interventions that aimed to improve knowledge of fertility and/or fertility-related risk factors
Control	No receipt of the intervention
Outcome	Knowledge change

Figure 1. PRISMA flow diagram.

Table 2. Study characteristics of the included studies.

Author (year)	Country	Study design	Sample size & population (sex)	Population mean age (age group)	Recruitment & study setting	Intervention & sample size	Control group & sample size	Outcome	Time from baseline to follow-up	Data collection method
Bodin et al. (2018)	Sweden	Randomized controlled trial	N = 201 Male only Dropout rate = 16%	28.4 years (18–50)	Recruited from sexual health clinics	Reproductive life planning (RLP) counselling n = 106 (time1), n = 84 (follow up)	Received standard care n = 95 (time 1), n = 84 (follow up)	Awareness of fertility and lifestyle risk factors	Three months	Phone survey interview after in-person counselling
Maeda et al. (2016, 2018)	Japan	Randomized controlled trial	N = 1455 (2016) Male (n = 726) and female (n = 729) N = 743 (2018) Male (n = 383) and female (n = 360) Dropout rate = 49%	30.5 years (20–39)	Recruited from online database	Educational brochure on infertility facts and infertility risk factors (lifestyle, reproductive)n = 685 (2016) (male n = 242, female n = 243) n = 240 (2018) male (n = 118) and female n = 122)	Brochures on folic acid intake during pregnancy (control 1) or financial support for pregnancy and childbirth (control 2). n = 685 (2016) (male n = 242, female n = 243) Control 1 n = 260 (2018), male (n = 133) and female n = 127) Control 2 n = 243 (2018) male (n = 132) and female (n = 111)	Knowledge about fertility facts, risks and myths	Directly after the intervention and two years later	Online survey using the Japanese version of the Cardiff Fertility Knowledge Scale
Kruglova et al. (2021)	Canada	Experimental study	N = 49 Male only	31.5 years (18–45)	Recruited from online database	Mobile fertility health application (mHealth app; ‘Infertility XY’)	N/A	Knowledge of infertility risk factors	Two weeks	Post-app online survey
Baczek et al. (2020)	Poland	Experimental study	N = 231 Male (n = 108) and female (n = 123)	No mean age provided (16–19)	Secondary and vocational school students	Educational class about fertility delivered in person by a midwife during a school lesson about fertility	N/A	Knowledge of fertility and fertility risk factors	Follow-up was immediately after the class	In-person survey following an educational class
Thomson et al. (2016)	Canada	Experimental study	N = 101 Male (n = 31) and female (n = 70)	25 years (18–34)	First and second-year medical students	Animated educational video covering fertility-related topics	N/A	Knowledge of infertility	One week	Online survey

Note: N/A: not applicable.

Figure 2. Percentage and significance of the change in participants’ fertility knowledge from baseline to follow up.

Table 3. Mean number of fertility-related risk factors identified at baseline and follow-up.

Author of the studies	Mean number/total number of assessed risk factors (baseline)	Mean number/total number of assessed risk factors (follow-up)	p Value
Bodin et al. (2018)	3.6/Not reported	4.4/Not reported	p < 0.001
Kruglova et al. (2021)	11.12/24	17.14/24	p < 0.001
Baczek et al. (2020)	21/33	25/33	p = 0.0012

Bodin, M., Tydén, T., Käll, L., & Larsson, M. (2018). Can reproductive life plan-based counselling increase men’s fertility awareness? Upsala Journal of Medical Sciences, 123(4), 255–263. https://doi.org/10.1080/03009734.2018.1541948

 PubMed Web of Science ®Google Scholar

Maeda, E., Nakamura, F., Kobayashi, Y., Boivin, J., Sugimori, H., Murata, K., & Saito, H. (2016). Effects of fertility education on knowledge, desires and anxiety among the reproductive-aged population: Findings from a randomized controlled trial. Human Reproduction, 31(9), 2051–2060. https://doi.org/10.1093/humrep/dew133

 PubMed Web of Science ®Google Scholar

Maeda, E., Boivin, J., Toyokawa, S., Murata, K., & Saito, H. (2018). Two-year follow-up of a randomized controlled trial: Knowledge and reproductive outcome after online fertility education. Human Reproduction, 33(11), 2035–2042. https://doi.org/10.1093/humrep/dey293

 PubMed Web of Science ®Google Scholar

Kruglova, K., Gelgoot, E. N., Chan, P., Lo, K., Rosberger, Z., Bélanger, E., Kazdan, J., Robins, S., & Zelkowitz, P. (2021). Risky business: Increasing fertility knowledge of men in the general public using the mobile health application infotility XY. American Journal of Men’s Health, 15(5), 15579883211049027. https://doi.org/10.1177/15579883211049027

 Web of Science ®Google Scholar

Baczek, G., Padzik, M., Duda, T., & Giermaziak, W. (2020). The youth’s knowledge of human fertility and reproductive age - evaluation of educational and health care programme. Ginekologia i Poloznictwo, 58(4), 9–20.

 Google Scholar

Thomson, A. A., Brown, M., Zhang, S., Stern, E., Hahn, P. M., & Reid, R. L. (2016). Evaluating acquisition of knowledge about infertility using a whiteboard video. Journal of Obstetrics and Gynaecology Canada: JOGC = Journal D'obstetrique et Gynecologie du Canada: JOGC, 38(7), 646–650. https://doi.org/10.1016/j.jogc.2016.03.010

 PubMedGoogle Scholar

Data availability statement

Data are underlying this review will be shared on reasonable request made to the corresponding author.