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Abstract

Introduction and Objectives:

Canadians rely on their primary care providers to address their mental health needs, but there are longstanding system gaps that must be addressed to enhance their ability to deliver mental health care. The present study addressed the gap in pediatric mental health care through the development, delivery, and evaluation of a mental health literacy training among non-physician primary care providers.

Methods:

We delivered the training among 97 participants, with all completed the pre-test survey, and 74 completed the post-test survey on knowledge, attitudes toward mental health, and help-seeking intentions. Additionally, participants explained why they attended the training and shared how they would apply the knowledge learned into their practice (behaviors).

Results:

Participants improved their knowledge significantly from pre-test to post-test, P < .001, d = 2.51. We didn’t find any statistical significance between pre-test and post-test on attitudes, P = .067, nor on help-seeking intentions, P = .274. However, participants’ scores were exceedingly high on both outcomes, indicating positive attitudes and intentions at 2 time points and implying a ceiling effect of both outcomes. We did not find outcome differences by demographics, practice year, practice zone, or professional role. While knowledge, years of practice and prior mental health training predicted participants attitudes at pre-test, they didn’t at post-test. Attitudes toward mental health predicted help-seeking intentions. Participants indicated this training will change their practice behaviors.

Conclusion:

This mental health literacy training for primary care providers demonstrated strong evidence of the need to integrate mental health and addiction support into primary care practice.

Keywords

primary care mental health literacy pediatric mental health care non-physician primary care providers children and youth

Introduction

Primary care includes all the services people receive for their basic health needs and care.¹ It is often called “the front door” to health care—and serves as the entry point into the health-care system. Primary care usually includes the initial care, treatment, follow-up of various conditions and referrals to the rest of the health system when needed.^1,2 It also encompasses wellness promotion, prevention and the management of chronic diseases and injuries. A successful primary care team includes family physicians and other health professionals such as mental health specialists, dieticians, pharmacists, and registered nurses working together.¹

The College of Family Physicians of Canada³ supports integrating mental health services as a crucial part of community-based primary care and illustrated case examples on how mental health professionals and primary care providers worked together to improve access to mental health services in the community. Evidence demonstrating the effectiveness and cost-effectiveness of primary care based mental health interventions is emerging in Canada,⁴ drawing attention of various provinces across the country. The Ontario Medical Association and Primary Care Collaborative worked together to have recommended policy actions to support primary care providers in integrating mental health services, including enhancing primary care providers capacity to treat mental disorders such as moderate to severe depression and anxiety.⁵

Most Canadians rely on their primary care providers to address their mental health needs, but there are longstanding system gaps that must be addressed to enhance the ability of primary care providers to deliver mental health care.⁵ Researchers⁶ have further identified the need to develop competencies of pediatric primary care providers in the recognition that adverse psychosocial experiences in childhood have lifelong adverse effects on mental and physical health, and the high prevalence of mental disorders and substance abuse among youth: an estimated of 1 in 5 young people experience a mental disorder requiring professional care and evidence of functional impairment.⁷

Internationally, there have been calls for collaborative mental health care for youth in pediatric primary care⁸ to improve access to quality mental health care. Research is emerging in training primary care providers to care for patient mental health.^9,10 And the Mental Health Gap Action Programme (mhGAP) was launched by the World Health Organization¹¹ for implementation across over 90 countries. While recognizing the importance of addressing youth mental health in primary care,¹² there are few studies focusing on this domain. In 2014, Alberta Health Services (AHS) supported the development of the Canadian Research and Education for the Advancement of Child Health (CanREACH). CanREACH offers evidence-based mental health literacy (MHL) in primary care that has demonstrated measurable changes in referral practices¹³ resulting in improved patient and provider experiences and benefits to the larger health care system.^14,15

Recognizing that the primary care setting includes interdisciplinary professionals, the Primary Care Networks (PCN) in a province in west Canada raised the need to upskill interdisciplinary team members. It enlisted the evidence-based CanREACH program: https://canreach.mhcollab.ca/ and the MHL program: https://mentalhealthliteracy.org/ to partner and develop a new initiative for non-physician professionals in the primary care setting. The initiative adapted the Go-To Educator MHL training, already being applied and proven in the education system among teachers in secondary schools,¹⁶ to align with the CanREACH program which is already being applied and has been proven in the medical system.^13
-15 This adaptation was developed and delivered to non-physician professionals across disciplines (eg administration, nursing, psychology, pharmacy, dieticians) working in the primary care setting. This joint initiative ensured that the information being delivered to the interdisciplinary primary care team was consistent with that being offered to educators and physicians across the province of Alberta through this shared literacy approach.

In this study, we described the preliminary results of this Interdisciplinary Professionals in Primary Care (IPPC) MHL training in a province in west Canada, addressing the following research questions:

Does the primary care MHL training improve knowledge, reduce stigma and enhance help-seeking intentions among primary care providers and staff across multi-disciplinary professionals working in the primacy care setting?

Do participants respond to the primary care MHL training differently based on their demographic characteristics?

Do participants’ attitudes toward mental health and help-seeking intentions be predicted by their knowledge, attitudes and their demographics?

What are participants’ perspectives about the benefits of the primary care MHL training?

Methods

Participants were informed of the study during the training and the passive consent was automatically achieved when participants completed the survey. The study ethics was approved by the first author’s institution.

The IPPC training was primarily developed for persons working within the primary care settings associated with the regional Primary Care Networks but was offered to primary care networks in the Central and South Zone of the Northwest Territories. Participants self-selected to participate, and at time of registration were asked general demographic information and questions about their education, years of employment, role in primary care, and experience with child and adolescent mental health. One week prior to the start of their training, participants were e-mailed a link to complete a pre-test to measure their knowledge and attitudes related to mental health. Upon completion of the pre-test, participants were provided the links to their training and course materials. At the end of the training sessions, participants were asked to complete a post-test online. The questions in the post-test mirrored those of the pre-test as described below in the Measures.

The training was co-led by 2 presenters, 1 from each of the 2 programs being represented in this initiative, CanREACH and MHL, and was delivered live, online via the Zoom platform. Three training cohorts were offered with participants self-selecting the cohort that best worked with their schedules. The class sizes for each of the 3 training cohorts ranged from between 30 and 60 participants per cohort. We needed a sample of 71 participants, to ensure that we have 80% power to detect an effect size of d = 0.30 (meaningful changes based on past research and authors’ expertise in the field^17,18 on the related outcomes, assuming the significance level of α = 0.05). Each training cohort was provided with 8 h of total training, which was divided up into two 4-h sessions over a two-week period.

The training offered a foundation and framework for all participants to develop core competencies in child and adolescent MHL. In the first 4-h session, participants learnt a common language and epidemiological information, gained understanding into different mental health states, and developed patient engagement, assessment, and treatment skills. In the second 4-h session, the foundational information served as a framework for the application to some of the most prominent mental disorders seen in primary care. Participants were also toured through resources applicable for use with their patient populations and/or to enhance their own practice with youth and their families. The training sessions consisted of interactive lectures supported by slides and included activities, group discussions, self-reflections, video demonstrations, question-and-answer periods, and interactive games. As participants had a wide variety of roles and backgrounds in their primary care practices (eg, nurses, pharmacists, behavioral health consultants, psychologists, social workers, dieticians, admin), throughout the training participants were encouraged to self-reflect, record and share their key learnings (knowledge) and how they intend to apply this to their specific role (behavior/action).

We evaluated participants outcomes applying 5 sections of questions on demographics (eg, gender, role, years of practice, practice location, and previous training in mental health), knowledge, attitudes toward mental health/stigma, help-seeking intentions, and training satisfaction. Participants created their own unique identifier (middle name or a nickname they go by, Year of Birth, Gender [M/F/O] and favorite color/number) without exposing their real identity. This unique identifier was used to link participants’ pre- and post-test for data analysis.

Knowledge was assessed using 23 statements created out of the training content by the program developer, asking participants to endorse a response out of 3 options: true, false, and “don’t know.” Each correct response received a score of 1; each incorrect response and “don’t know” response received a score of 0, with a maximum score of 23 and a minimum score of 0. The internal consistency reliability of the knowledge scale at baseline was α = .75. A principal component analysis was conducted with varimax rotation. The Kaiser–Meyer–Olkin (KMO) measure verified the sampling adequacy for the analysis, with KMO = 0.618, which was above the acceptable limit of 0.5.¹⁹ An initial analysis was run to obtain eigenvalues for each factor in the data. Eight factors had eigenvalues over Kaiser’s criterion (>1) and in combination accounted for 60.432% of the variance. However, the scree plot was ambiguous and showed inflexions that would justify retaining just 1 factor that explained 17.245% of the variances.

Participant attitudes toward mental health were assessed using a 12-item 7-point Likert scale. Each response received a minimum score of 1 and maximum score of 7. Each participant gained a total of between 12 and 84, with lower scores indicating negative attitudes (higher stigma) and higher scores indicating positive attitudes (lower stigma). A previous study demonstrated strong reliability and reliability of the scale.²⁰ The internal consistency reliability of the scale with the current sample was α = .74.

Participants were evaluated on their help-seeking intentions using a 5-item 7-point Likert scale. Each response was assigned a value between 1 and 7, with total scores between 5 and 35. Higher scores indicated greater positive intentions for seeking help. A previous study has shown the strong reliability and validity of the scale.²¹ The internal consistency reliability of the scale with the current sample was α=.83.

Participants were asked to rate their satisfaction with the training using a 6-item, 7-point Likert scale with a minimum value of 6 and a maximum of 42. Higher scores on this scale indicated greater satisfaction with the training. In addition, participants were given the chance to provide feedback on the training.

At pre-test, participants were asked to add any comments that they would like to share (eg, reason they took this training, what they hoped to learn). At post-test, participants were invited to describe at least 2 ways they intended to change their practice/behaviors as a result of attending this training program. Further, they were asked to describe at least 2 key messages (learnings, knowledge enhancement) that they took away from this training program. Lastly, participants were given the opportunity to provide any feedback that they would like to share after the training.

Quantitative data analysis contains both descriptive and inferential statistics. Descriptive statistics were reported as counts and percentages for categorical variables, means and standard deviation for normally distributed continuous variables. Differences between the pre- and post-test were examined using t-test. General linear model, 2-way repeated measures ANOVA were used to test the between-group difference at each study time point as appropriate. Regression analysis was used to identify potential predictors of outcomes. All quantitative analyses were conducted using SPSS software, with a significance level of α = .05.

Qualitative content analysis was applied for analyzing qualitative data and interpreting its meaning.²² It was used as a systematic and objective means of describing and quantifying participants’ perspectives about the training. In content analysis, the qualitative data was reduced to concepts by creating categories, concepts, or a model as appropriate.

Results

A total of 97 participants completed the pre-test, and 74 completed the post-test. Of these, 64 were matched between pre- and post-test. Most participants identified themselves as female (94.9% at pre-test and 93.8% at post-test). Approximately half of the participants were in their 0 to 5 years of practice at both time points. More than half of the participants were from the Edmonton zone, followed by Central zone. Most participants had received previous mental health training. Participants were mostly nurses, followed by mental health professionals (eg, social work, psychology), non-clinical support staff (eg, admin, referral coordinator, facilitator, educator) and other clinically responsible professions (eg, pharmacy, nutrition, occupational therapy) (Table 1).

Table 1.

Demographics.

Demographics	Pre-test (N = 97)		Post-test (N = 64)
Demographics	N	%	N	%
Gender
Female	92	94.9	60	93.8
Male	4	4.1	4	6.2
Other	1	1.0
Working years
0-2	32	33.0	19	29.7
3-5	17	17.5	14	21.9
6-10	27	27.8	18	28.1
≥11	19	19.6	12	18.8
Unspecified	2	2.1	1	1.6
Professions
Nurse	47	48.5	28	43.8
Mental health professional	24	24.7	16	25.0
Other clinical support	14	14.4	13	20.3
Non-clinical support	12	12.4	7	10.9
Practice location
Calgary zone	1	1.0	1	1.6
Central zone	33	34.0	23	35.9
Edmonton zone	52	53.6	33	51.6
North zone	6	6.2	3	4.7
South zone	5	5.2	4	6.3
Previous MH training
No	44	45.4	27	42.2
Yes	53	54.6	37	57.8

Table 2 describes the percentage of correct and incorrect responses on each knowledge question at two time points. Participants improved their understanding of mental health on 21 questions, however, not on questions 6 and 19.

Table 2.

Knowledge Differences by Question.

		Pre-test		Post-test
Knowledge questions		N	%	N	%
1. Everyday stress is harmful to people and needs to be avoided as much as possible	Incorrect	25	25.8	0	0.0
	Correct	72	74.2	65	100.0
2. Self-harm is a strong indicator of suicidality	Incorrect	47	48.4	14	21.9
	Correct	50	51.6	50	78.1
3. There are many freely available evidence-based treatment resources that patients can access.	Incorrect	39	40.2	0	0.0
	Correct	58	59.8	64	100.0
4. Medication treatments for mental disorders are addictive	Incorrect	12	12.4	1	1.6
4. Medication treatments for mental disorders are addictive	Correct	85	87.6	63	98.4
5. Poverty and other social determinants of health are well-established causes of most mental disorders	Incorrect	64	66.0	1	1.6
	Correct	33	34.0	63	98.4
6. Anxiety Disorders are the result of an individual’s emotional regulation not working effectively^a	Incorrect	60	61.9	40	62.5
	Correct	37	38.1	24	37.5
7. Mental states, from no stress, to distress, to disorder, are part of a continuum	Incorrect	84	86.6	11	17.2
	Correct	13	13.4	53	82.8
8. Mental disorders arise as a result of perturbations of usual brain functions	Incorrect	55	56.7	11	17.2
	Correct	42	43.3	53	82.8
9. The period of time before symptoms and impairment meet is considered the prodrome	Incorrect	54	55.7	3	4.7
	Correct	43	44.3	61	95.3
10. People with depression never have fluctuation in their mood	Incorrect	7	7.2	3	4.7
	Correct	90	92.8	61	95.3
11. There are useful and free tools that aide in BOTH the assessment and treatment of mental illness	Incorrect	19	19.6	1	1.6
	Correct	78	80.4	63	98.4
12. All treatments have the potential for side effects	Incorrect	18	18.6	5	7.7
12. All treatments have the potential for side effects	Correct	79	81.4	60	92.3
13. Nothing can predict which teenagers will die by suicide	Incorrect	72	75.0	6	9.4
13. Nothing can predict which teenagers will die by suicide	Correct	24	25.0	58	90.6
14. Screening for changes to mental health is not recommended unless there is an indication for it	Incorrect	21	21.6	8	12.5
	Correct	76	78.4	56	87.5
15. The three domains of ADHD are inattention, hyperactivity, and oppositionality	Incorrect	65	67.0	3	4.70
	Correct	32	33.0	61	95.3
16. COLDER is a mnemonic to diagnose mental illness	Incorrect	90	92.8	4	6.2
16. COLDER is a mnemonic to diagnose mental illness	Correct	7	7.2	60	93.8
17. Medications used in treating mental illness add neurotransmitters to the brain	Incorrect	57	58.8	14	21.9
	Correct	40	41.2	50	78.1
18. Although ADHD is highly heritable, treatment is highly effective	Incorrect	24	24.7	0	0.0
	Correct	73	75.3	64	100.0
19. Patients under the age of 18 do not have capacity to give consent to non-emergent health care interventions^a	Incorrect	14	14.4	10	15.6
	Correct	83	85.6	54	84.4
20. Major Depressive Disorder can be a consequence of untreated Anxiety Disorder	Incorrect	30	30.9	4	6.2
	Correct	67	69.1	60	93.8
21. Medication should be prescribed based on the size of the patient (eg: children taking lower doses than adults)	Incorrect	85	87.6	15	23.4
	Correct	12	12.4	49	76.6
22. To diagnose Depression there must be a precipitating life event	Incorrect	12	12.4	1	1.5
	Correct	85	87.6	63	98.4
23. A complementary treatment is one that is often applied instead of usual physician recommended interventions	Incorrect	60	61.9	25	39.1
	Correct	37	38.1	39	60.9

Incorrect responses included “Don’t know” responses.

Participants improved their knowledge significantly from pre-test (M = 12.45, SD = 3.911, n = 64) to post-test (M = 20.19, SD = 1.943, n = 64), t(63) = 15.45, P < .001, d = 2.51. We didn’t find any statistical significance on attitudes between pre-test (M = 78, SD = 6.302, n = 64) and post-test (M = 79.59, SD = 8.355, n = 64), t(63) = 1.522, p = .067, nor on help-seeking intentions between pre-test (M = 32.30, SD = 3.412, n = 64) and post-test (M = 32.59, SD = 3.951), t(63) = 0.604, P = .274.

We compared the outcome differences by participants’ practice year and practice location, demonstrating that they didn’t influence the outcome changes at pre-test and at post-test (P > .05) (Table 3).

Table 3.

Subgroup Differences With ANOVA.

Years of practice
Pret-test	Sum of squares	df	Mean square	F	Sig.
Knowledge
Between groups	21.702	3	7.234	.484	.694
Within groups	1359.603	91	14.941
Total	1381.305	94
Attitudes
Between groups	191.532	3	63.844	1.876	.139
Within groups	3096.468	91	34.027
Total	3288.000	94
Help-seeking
Between groups	4.456	3	1.485	.144	.933
Within groups	936.133	91	10.287
Total	940.589	94
Post-test
Knowledge
Between groups	3.311	3	1.104	.279	.841
Within groups	233.768	59	3.962
Total	237.079	62
Attitudes
Between groups	270.735	3	90.245	1.291	.286
Within groups	4124.693	59	69.910
Total	4395.429	62
Help-seeking
Between groups	23.547	3	7.849	.486	.693
Within groups	953.056	59	16.153
Total	976.603	62
Practice zone
Pre-test
Knowledge
Between groups	34.265	2	17.133	1.193	.308
Within groups	1349.776	94	14.359
Total	1384.041	96
Attitudes
Between groups	53.675	2	26.838	.774	.464
Within groups	3259.315	94	34.674
Total	3312.990	96
Help-seeking
Between groups	12.069	2	6.034	.584	.559
Within groups	970.653	94	10.326
Total	982.722	96
Post-test
Between groups	8.179	2	4.089	1.087	.344
Within groups	229.571	61	3.763
Total	237.750	63
Between groups	86.233	2	43.116	.610	.547
Within groups	4311.205	61	70.675
Total	4397.438	63
Between groups	33.205	2	16.602	1.066	.351
Within groups	950.233	61	15.578
Total	983.438	63
Professional role
Pre-test
Knowledge
Between groups	400.048	3	133.349	12.603	<.001
Within groups	983.993	93	10.581
Total	1384.041	96
Attitudes
Between groups	212.185	3	70.728	2.121	.103
Within groups	3100.805	93	33.342
Total	3312.990	96
Help-seeking
Between groups	39.088	3	13.029	1.284	.284
Within groups	943.633	93	10.147
Total	982.722	96
Post-test
Knowledge
Between groups	17.780	3	5.927	1.617	.195
Within groups	219.970	60	3.666
Total	237.750	63
Attitudes
Between groups	488.316	3	162.772	2.498	.068
Within groups	3909.122	60	65.152
Total	4397.438	63
Help-seeking
Between groups	60.772	3	20.257	1.317	.277
Within groups	922.666	60	15.378
Total	983.438	63

We found greater knowledge level at pre-test among participants with previous mental health training (M = 13.66, SD = 3.469, n = 53) than those who did not (M = 11.20, SD = 3.776, n = 44), t(95) = 3.334, P < .001; however, not at the post-test, P > .05. The ANCOVA controlling pre-test found no differences between the 2 groups on knowledge at post-test, F(2,63) = 1.419, P = .250. We didn’t find significant changes for other outcomes (attitudes and help-seeking intentions) (P > .05).

Non-clinical support group’s knowledge level was significantly lower than all other groups (P < .05) while other groups didn’t differ significantly on their knowledge at pre-test (Table 3). At post-test, we didn’t identify any differences on all outcomes (P > .05). The mixed two-way repeated measures ANOVA found a significant interaction effect between time and subgroups, F(3,60) = 5.424, r = 0.213; all subgroups improved their knowledge from pre-test to post-test significantly.

At pre-test, the regression model for attitude predictors was a significant fit of the data and 18.5% of variances were explained by the model (R² = 0.185, F(5, 89) = 4.033, P = .002). Knowledge (t(89) = 3.103, P = .003), years of practice (t(89) = −2.105, P = .038), and prior mental health training (t(89) = −2.099, P = .039) were all significant predictors of attitudes toward mental health. As knowledge and practice year increased by 1 standard deviation, the attitudes toward mental health improved by 0.323 and 0.214 standard deviation respectively. Participants without prior mental health training demonstrated more positive attitudes by 0.227 standard deviation than their counterparts. At post-test, the regression model was not a significant fit of the data (P > .05).

For predictors of help-seeking intentions, at pre-test, the model was a significant fit of the data and 35.1% of the variances were explained by the model (R² = 0.351, F(6, 88) = 7.918, P < .001). However, only attitudes toward mental health predicted help-seeking intentions, with 1 standard deviation increase of attitudes resulting in 0.524 standard deviation increase of help-seeking intentions, P < .001. At post-test, the model was a significant fit of the data and 73% of the variances were explained by the model (R² = 0.730, F(6, 56) = 28.902, P < .001). Again, only attitudes toward mental health predicted help-seeking intentions, with 1 standard deviation increase of attitudes resulting in .886 standard deviation increase of help-seeking intentions, P < .001.

Further, at pre-test, 27 participants identified areas of interest including: evidence-based treatment and its processes; facilitators/barriers to prognosis and treatment; knowledge about mental health states and mental/neurodevelopment disorders (eg ADHD, Depression, and Down syndrome); patient consent; local/community resources and support.

At post-test, 48 participants discussed how they would apply their learning to their practice. Among them, 22 indicated that they planned to implement the new screening/assessment tools and rating tools; 18 participants recognized the significance of providing helpful resources to patients. Ten participants reported their intention to change their language to address youth mental health and be more patient and open with patients and families, reduce stigma around mental illness. Many (n = 32) mentioned they developed greater ability to identify signs and symptoms of mental disorders, deeper understanding about treatments, better differentiation between self-harm and suicide, and were more aware of the importance of healthy lifestyles to promote mental health.

Finally, participants expressed high satisfaction about the training, with high endorsement (87.5%-95.4%) of each satisfaction item.

Discussion

The primary care MHL training demonstrated preliminary evidence of effectiveness in improving participants’ knowledge about mental health. The qualitative data further indicated that participants felt more competent in addressing mental health in their everyday practice. Participants scored low at pre-test (M = 12) on knowledge, highlighting the need to enhance the capacity of primary care providers to integrate mental health into services.

Participants demonstrated positive attitudes toward mental health and great intentions for help-seeking at both baseline and post-test, and therefore data analysis didn’t generate statistical significance. This high ceiling effect may be due to the social desirability bias by participants over-reporting “good behavior” or under-reporting “bad,” or undesirable behaviors. One potential solution is the use of social desirability scales in the future evaluation.²³ We found that more knowledge led to more positive attitudes toward mental health, and together encouraged greater help-seeking intentions. This finding explained the positive relationship among these 3 outcomes and were consistent with previous finding among youth.¹⁸

These preliminary outcomes set foundations for further advanced research on clinical outcomes of the primary care MHL training, such as the quality of care and referral and patient satisfaction as the training aims to improve the competencies of primary care providers. Future research may also further investigate what changes actually occur in practice following the training.

This MHL training for primary care providers demonstrated evidence of the need to integrate mental health and addiction support into care provider education and practice through developing primary care providers’ competencies in this domain. This training for non-physicians aligns well with the CanREACH program to jointly address the mental health needs of Albertans in the primary care setting, and therefore has great potential to effectively enhance the mental health of Albertans and beyond. This training is designed to reach non-physicians in other geographical locations with modifications needed to accommodate local health care needs. Part of the training is adapted from the Go-To Educator training¹⁶ that has been widely applied in other countries, which will provide guidance on how to collaborate with local health care systems for successful adoption.

This study lacked randomization in its design, which may lead to biased results. Secondly, most participants were from the Edmonton zone and the results may not be generalized to other non-physician primary care providers in the province. Participant self-selection for study could have contributed to bias. The suboptimal post-test survey rate could also limit result interpretation. These limitations warrant future advanced studies are needed to further validate the findings in the current study.

Footnotes

Acknowledgements

We thank the Edmonton Zone Primary Care Networks, Alberta Health Services, and CASA Mental Health to support this project as part of the “Building Service Capacity for Child and Adolescent Mental Health in Primary Care and Pediatrics” project.

Author Contribution Statement

Wei, McCaffrey, Baxter conceptualized the study together. Wei conducted the literature search and analyzed the data; prepared the manuscript, including designing tables and figures. McCaffrey and Baxter reviewed the data analysis and played the expert role to solve the discrepancies of data analysis. They also made significant revisions to the manuscript. All 3 authors reviewed and approved the final version of the manuscript.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by Edmonton Zone Primary Care Networks.

Ethical Statement

The Health Research Ethics Board at the University of Alberta approved the study (approval: Pro00133446) on September 11, 2024. Respondents provided passive consent by completing the survey.

ORCID iD

Yifeng Wei

References

Thomas-MacLean

Tarlier

Ackroyd-Stolarz

Fortin

Stewart

. No cookie-cutter response: conceptualizing primary health care. University of Western Ontario. 2008. Accessed November 18, 2024. http://www.uwo.ca/fammed/csfm/tutor-phc/documentation/trainingpapers/TUTOR_Definitio_%20of_primar_%20health_care.pdf

Alberta Health Services. Primary care information for Albertans. 2024. Accessed January 17, 2024. https://www.albertahealthservices.ca/info/Page4058.aspx

College of Family Physicians of Canada, Canadian Psychiatric Association, and Canadian Psychological Association. Integrating mental health services in primary care. 2020. Accessed January 17, 2024. https://www.cfpc.ca/CFPC/media/PDF/IPC-Mental-Health-Report-2020-Final.pdf

Moroz

D’Angelo

MS.

Mental health services in Canada: barriers and cost-effective solutions to increase access. Healthc Manag Forum. 2020;33(6):282-287. doi:10.1177/0840470420933911

Ontario Medical Association. Strengthening the delivery of mental health and addiction services in primary care. 2022. Accessed January 17, 2024. https://www.oma.org/uploadedfiles/oma/media/pagetree/advocacy/health-policy-recommendations/primary-care-supports-for-mental-health-and-addiction-challenges.pdf

Committee on Psychosocial Aspects of Child and Family Health and Task Force on Mental Health. The Future of pediatrics: mental Health competencies for pediatric primary care. Pediatrics. 2009;124(1):410-421. Accessed March 12, 2024. doi:10.1542/peds.2009-1061

Kessler

Berglund

Demler

Jin

Walters

EE.

Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Arch Gen Psychiatry. 2005;62(6):593-602. doi:10.1001/archpsyc.62.6.593

American Academy of Child and Adolescent Psychiatry (AACAP) Committee on Collaborative and Integrated Care and AACAP Committee on Quality Issues. Clinical update: collaborative mental health care for children and adolescents in pediatric primary care. J Am Acad Child Adolesc Psychiatry. 2023;62(2):91-119. doi:10.1016/j.jaac.2022.06.007

Crespo-Gonzalez

Dineen-Griffin

Rae

Hill

RA.

Mental health training programs for community pharmacists, pharmacy staff and students: a systematic review. Res Social Adm Pharm. 2022;18(11):3895-3910. doi:10.1016/j.sapharm.2022.06.006

10.

Trimmer

Fuller

Kake

Asbury

Collaborative primary mental health education for correctional nurses. J Correct Health Care. 2019;25(1):55-64. doi:10.1177/1078345818819885

11.

Keynejad

Dua

Barbui

Thornicroft

WHO Mental Health Gap Action Programme (mhGAP) Intervention Guide: a systematic review of evidence from low and middle-income countries. Evid Based Ment Health. 2018;21(1):30-34. doi:10.1136/eb-2017-102750.

12.

O’Regan

Schaffalitzky

Cullen

Educational interventions: equipping general practice for youth mental health and substance abuse. A discussion paper. Ir J Med Sci. 2015;184(3):577-582. doi:10.1007/s11845-015-1285-6.

13.

McCaffrey

Chang

Farrelly

Rahman

Cawthorpe

Mental health literacy in primary care: Canadian Research and Education for the Advancement of Child Health (CanREACH). BMJ EBM. 2017;22(4):123-131. doi:10.1136/ebmed-2017-110714

14.

McCaffrey

Chang

Farrelly

Rahman

Ritchie

Goldade

Cawthorpe

The economic impact of providing evidence-based pediatric mental health literacy training to primary care physicians. Psychiatry Investig. 2021;18(7):695-700. doi:10.30773/pi.2021.0014

15.

McCaffrey

Cawthorpe

Modelling the clinical and economic impacts of foundation-funded versus staff-driven quality improvement mental health strategies. Qeios. 2023. doi:10.32388/0DKU2V

16.

Baxter

Wei

Kutcher

Cawthorpe

School-based mental health literacy training shifts the quantity and quality of referrals to tertiary child and adolescent mental health services: a Western Canada regional study. PLoS One. 2022;17(11):e0277695. doi:10.1371/journal.pone.0277695

17.

McLuckie

Kutcher

Wei

Weaver

Sustained improvements in students’ mental health literacy with use of a mental health curriculum in Canadian schools. BMC Psychiatry. 2014;14(1):379. doi:10.1186/s12888-014-0379-4

18.

Milin

Kutcher

Lewis

, et al. Impact of a mental health curriculum on knowledge and stigma among high school students: a randomized controlled trial. J Am Acad Child Adolesc Psychiatry. 2016;55(5):383-391.e1. doi:10.1016/j.jaac.2016.02.018

19.

Hutcheson

Sofroniou

The Multivariate Social Scientists. Sage Publishing; 1999.

20.

Wei

Baxter

Kutcher

Establishment and validation of a mental health literacy measurement in Canadian educators. Psychiatry Res. 2019;279:231-236. doi:10.1016/j.psychres.2019.03.009

21.

Wei

Carr

Kutcher

Alafee

Mental health literacy development: application of online and in-person professional development for preservice teachers to address knowledge, stigma, and help-seeking intentions. Can J Behav Sci. 2019;52(2):107-114. doi:10.1037/cbs0000164

22.

Cho

Lee

Reducing confusion about grounded theory and qualitative content analysis: similarities and differences. Qual Rep. 2014;19(32):1-20. http://nsuworks.nova.edu/tqr/vol19/iss32/2

23.

Nederhof

AJ.

Methods of coping with social desirability bias: a review. Eur J Soc Psychol. 1985;15(3):263-280. Accessed March 12, 2024. doi:10.1002/ejsp.2420150303

Improving the Capacity of Non-Physician Primary Care Providers to Address Child and Youth Mental Health Through Mental Health Literacy Approaches

Abstract

Introduction and Objectives:

Methods:

Results:

Conclusion:

Keywords

Introduction

Methods

Results

Discussion

Footnotes

Acknowledgements

Author Contribution Statement

Declaration of Conflicting Interests

Funding

Ethical Statement

ORCID iD

References