Of 671 individuals who responded to online recruitment, 557 eligible participants completed the baseline questionnaire and were randomized to the intervention (n = 278) or control group (n = 279) (Figure 2). Retention was high, with 88.3% and 84.2% of participants completing end of study and follow-up questionnaires respectively. Participants who failed to complete the end of study questionnaire were eligible and invited to complete the follow-up. There were no differences in loss to follow-up between groups. Participants who did not complete the end of study questionnaire were more likely to have not previously used the Portal (68.3% vs. 51.5%, p = 0.01), have lower baseline self-rated health (3.6 vs. 3.9 on a 5-point Likert scale, p = 0.02), and have lower baseline physical activity (28.7 vs. 35.3 points, p = 0.03). Participants who did not complete the follow-up questionnaire were more likely to have never used the Portal (58.8 vs. 52.4, p = 0.02), and have lower baseline physical activity (26.4 vs. 36.0 points, p <0.001). No other descriptive characteristics were associated with loss to follow-up.
There were no baseline differences in demographic characteristics between the intervention and control groups (Table 1). Participants were predominantly older (65.2 ± 8.0 years), retired (71.6%) female (80.3%), and well-educated (94.1% had post-secondary education, and one-third had a post-graduate degree). Despite 51.4% reporting at least one chronic condition, 71.1% rated their health as ‘excellent’ or ‘very good’. Half of participants had never used the Portal before, and one-quarter were regular users.
Table 1: Participant characteristics
|
Total
|
|
Intervention
|
Control
|
p
|
|
n = 557
|
|
n = 278
|
n = 279
|
|
|
|
|
Mean ± SD
|
|
Age
|
65.2 ± 8.0
|
|
65.4 ± 7.9
|
64.9 ± 8.2
|
0.51
|
|
|
|
|
|
|
|
N (%)
|
|
Female
|
447 (80.3)
|
|
221 (79.5)
|
226 (81.0)
|
0.73
|
Education (%)
|
|
|
|
|
|
Secondary school or less
|
33 (5.9)
|
|
19 (6.9)
|
14 (5.0)
|
0.43
|
Post-secondary diploma
|
102 (18.3)
|
|
49 (17.6)
|
53 (19.1)
|
|
Bachelor’s degree
|
235 (42.3)
|
|
121 (43.5)
|
114 (41.0)
|
|
Post-graduate degree
|
186 (33.5)
|
|
89 (32.0)
|
97 (34.9)
|
|
Employment status (%)
|
|
|
|
|
|
Full-time
|
92 (16.5)
|
|
51 (18.4)
|
41 (14.7)
|
0.75
|
Part-time
|
59 (10.6)
|
|
27 (9.7)
|
32 (11.5)
|
|
Homemaker
|
4 (0.7)
|
|
2 (0.7)
|
2 (0.7)
|
|
Retired
|
398 (71.6)
|
|
196 (70.8)
|
202 (72.4)
|
|
Long-term disability
|
3 (0.5)
|
|
1 (0.4)
|
2 (0.7)
|
|
Geographic location (%)
|
|
|
|
|
|
Urban
|
248 (44.5)
|
|
119 (42.8)
|
129 (46.2)
|
0.63
|
Suburban
|
207 (37.2)
|
|
107 (38.5)
|
100 (35.8)
|
|
Rural/Remote
|
102 (18.3)
|
|
52 (18.7)
|
50 (18.0)
|
|
Chronic disease
|
285 (51.4)
|
|
144 (52.0)
|
141 (50.9)
|
0.87
|
Self-rated health ‘Excellent’ or ‘Very Good’
|
396 (71.1)
|
|
203 (73.0)
|
193 (69.1)
|
0.35
|
Previously used the McMaster Optimal Aging Portal (%)
|
|
|
|
|
|
No
|
297 (53.4)
|
|
148 (53.2)
|
149 (53.6)
|
0.79
|
Yes, regular user
|
140 (25.2)
|
|
73 (26.3)
|
67 (24.1)
|
|
Yes, occasionally
|
119 (21.4)
|
|
57 (20.5)
|
62 (22.3)
|
|
Changes in knowledge, intentions and health behaviours
There were no differences between groups at baseline in knowledge, intentions or health behaviours (Table 2). Only three participants in the study reported being current smokers (data not shown), therefore changes in knowledge, intentions and smoking behaviours were not analyzed. Baseline knowledge of cancer prevention guidelines was high (mean 4.6 out of 5 guidelines correctly identified). Knowledge was highest for fruit and vegetable intake (98%) and lowest for alcohol (80.1%). At end of study and follow-up, total knowledge score was significantly higher in the intervention vs. control group. At end of study, intervention participants were significantly more likely than controls to identify physical activity and alcohol guidelines (OR: 5.57, 95% CI: 1.20, 25.79 and OR: 2.05, 95% CI: 1.02, 41.2 respectively), and at follow-up were more likely to identify red meat and fiber intake guidelines (OR: 3.00, 95% CI: 1.03, 8.71).
Intentions to engage in recommended behaviours were also high at baseline in both groups, particularly for red meat and fiber intake (mean 6.0 on a 7-point Likert scale) and lowest for physical activity (5.5 on a 7-point Likert scale). There were no between-group differences in intentions at end of study or follow-up with respect to behavioural intentions.
At end of study, there was a significant between-group difference for number of bouts of light physical activity per week (+0.6, p = 0.03), eHealth literacy (+0.8 points, p = 0.04), and knowledge (+0.2, p = 0.01) favoring the intervention group. No between-group differences were found in total physical activity score, bouts of strenuous or moderate activity, self-rated health, or any measures of alcohol or dietary intake. At post-intervention follow-up, the only between-group difference was serving per week of liquor, favoring the intervention group (-0.5, p < 0.05).
A secondary aim was to examine the effect of the intervention amongst rural Canadians. We hypothesized that rural Canadians who may have more limited access to health care providers may be more likely to benefit from the intervention. At end of study, there were no between-group differences in total physical activity for those who lived in urban/suburban settings (+3.3, p = 0.07) or rural settings (+1.8, p = 0.26). No between-group differences were found for alcohol or dietary behaviours (data not shown).
In planned subgroup analyses, the magnitude of the intervention effect on total physical activity was larger for those with low baseline self-rated health , however this was not statistically significant (between-group difference +6.0 points, p = 0.06 vs. +0.60, p = 0.07 in those with high self-rated health). A similar pattern was observed when analyses were restricted to those who had never used the Portal before (+4.7 points, p = 0.04). No between-group differences were found in any subgroup analyses for diet or alcohol intake (data not shown).
Table 2: Quantitative outcomes at baseline, end of study and follow-up amongst intervention and control participants
|
Baseline
|
|
|
End of Study
|
|
Follow-up
|
|
Intervention
|
Control
|
p
|
|
Intervention
|
Control
|
p
|
|
Intervention
|
Control
|
p
|
|
|
|
|
|
|
|
|
|
|
|
|
Total Knowledge (Correct answers)
|
4.6 (4.5, 4.7)
|
4.6 (4.5, 4.7)
|
0.56
|
|
+0.3 (0.2, 0.4)
|
+0.1 (0.0, 0.2)
|
0.01
|
|
+0.3 (0.2, 0.4)
|
+0.2 (0.1, 0.3)
|
0.09
|
Physical activity a
|
91.7 (87.9, 94.4)
|
90.7 (86.7, 93.6)
|
0.55
|
|
5.57 (1.20, 25.79)
|
REF
|
0.03
|
|
1.58 (0.37, 6.81)
|
REF
|
0.54
|
Alcohol a
|
80.2 (75.1, 84.5)
|
81.4 (76.4, 85.5)
|
0.68
|
|
2.05 (1.02, 4.12)
|
REF
|
0.04
|
|
1.29 (0.60, 2.76)
|
REF
|
0.52
|
Fruit & Vegetable a
|
98.2 (95.9, 99.2)
|
97.5 (94.9, 98.8)
|
0.46
|
|
1.46 (0.24, 8.95)
|
REF
|
0.68
|
|
1.91 (0.17, 21.5)
|
REF
|
0.60
|
Red meat/fiber a
|
88.9 (84.6, 92.0)
|
91.8 (87.9, 94.5)
|
0.17
|
|
1.89 (0.82, 4.33)
|
REF
|
0.13
|
|
3.00 (1.03, 8.71)
|
REF
|
0.04
|
Intentions (7-point Likert scale)
|
5.8 (5.7, 5.9)
|
5.7 (5.6, 5.9)
|
0.46
|
|
+0.3 (0.1, 0.4)
|
+0.3 (0.1, 0.4)
|
0.51
|
|
+0.3 (0.2, 0.4)
|
+0.3 (0.2, 0.4)
|
0.72
|
Physical activity
|
5.5 (5.3, 5.7)
|
5.4 (5.2, 5.6)
|
0.52
|
|
+0.4 (0.2, 0.6)
|
+0.3 (0.2, 0.5)
|
0.41
|
|
+0.3 (0.1, 0.5)
|
+0.4 (0.2, 0.6)
|
0.81
|
Alcohol
|
5.9 (5.7, 6.1)
|
5.9 (5.7, 6.1)
|
0.89
|
|
+0.2 (-0.002, 0.4)
|
+0.2 (0.02, 0.5)
|
0.99
|
|
+0.2 (-0.02, 0.4)
|
+0.2 (-0.01, 0.4)
|
0.95
|
Fruit & Vegetable
|
5.7 (5.5, 5.9)
|
5.7 (5.6, 5.9)
|
0.92
|
|
+0.3 (0.1, 0.4)
|
+0.2 (0.1, 0.4)
|
0.90
|
|
+0.4 (0.2, 0.6)
|
+0.3 (0.2, 0.5)
|
0.72
|
Red meat/fiber
|
6.0 (5.9, 6.2)
|
5.9 (5.8, 6.1)
|
0.42
|
|
+0.2 (0.002, 0.3)
|
+0.2 (-0.002, 0.3)
|
0.42
|
|
+0.1 (-0.05, 0.3)
|
+0.2 (0.04, 0.4)
|
0.91
|
Physical Activity
|
Total PA score
|
35.3 (32.5, 38.1)
|
33.8 (31.0, 36.6)
|
0.46
|
|
+ 4.6 (-0.1, 8.1)
|
+ 2.1 (-0.2, 4.5)
|
0.14
|
|
+ 5.5 (3.0, 7.9)
|
+4.1 (1.7, 6.5)
|
0.43
|
Strenuous PA (bouts/week)
|
1.1 (0.9, 1.3)
|
1.0 (0.8, 1.2)
|
0.49
|
|
+ 0.1 (-0.1, 0.3)
|
-0.0 (-0.2, 0.2)
|
0.58
|
|
0.0 (-0.2, 0.2)
|
+0.1 (-0.1, 0.3)
|
0.61
|
Moderate PA (bouts/week)
|
2.9 (2.6, 3.2)
|
2.7 (2.4, 3.0)
|
0.55
|
|
+0.4 (0.1, 0.7)
|
+0.4 (0.1, 0.7)
|
0.90
|
|
+0.6 (0.3, 0.9)
|
+0.4 (0.1, 0.7)
|
0.38
|
Light PA (bouts/week)
|
3.6 (3.3, 4.0)
|
3.6 (3.3, 4.0)
|
0.99
|
|
+0.7 (0.3, 1.1)
|
+0.1 (-0.3, 0.5)
|
0.03
|
|
+0.8 (0.5, 1.2)
|
+0.6 (0.2, 0.9)
|
0.28
|
Alcohol intake (servings/week)
|
Total
|
5.2 (4.5, 6.0)
|
6.0 (5.2, 6.8)
|
0.18
|
|
-0.4 (-0.8, 0.1)
|
-0.5 (-0.9, 0)
|
0.80
|
|
-0.1 (-0.6, 0.3)
|
-0.1 (-0.6, 0.3)
|
0.99
|
Beer
|
1.1 (0.7, 1.5)
|
1.4 (1.0, 1.9)
|
0.26
|
|
0.0 (-0.2, 0.3)
|
0.0 (-0.2, 0.3)
|
0.98
|
|
+0.5 (0.2, 0.7)
|
+0.5 (0.2, 0.7)
|
0.98
|
Wine
|
4.4 (3.8, 5.0)
|
4.6 (4.0, 5.2)
|
0.75
|
|
-0.3 (-0.6, 0.0)
|
-0.6 (-1.0, -0.3)
|
0.22
|
|
-0.3 (-0.6, 0.1)
|
-0.7 (-1.1, -0.4)
|
0.08
|
Liquor
|
1.2 (0.7, 1.6)
|
1.3 (0.8, 1.7)
|
0.66
|
|
-0.2 (-0.5, 0.2)
|
+0.3 (-0.0, 0.7)
|
0.07
|
|
-0.2 (-0.9, 0.4)
|
0.3 (-0.0, 0.7)
|
<0.05
|
Diet
|
Fruit/veg (servings per day)
|
3.0 (2.9, 3.1)
|
2.9 (2.8, 3.0)
|
0.17
|
|
+0.1 (0.01, 0.2)
|
+0.2 (0.1, 0.2)
|
0.16
|
|
+0.2 (0.1, 0.3)
|
+0.2 (0.1, 0.3)
|
0.80
|
Whole grains (servings per day)
|
0.9 (0.9, 1.0)
|
0.9 (0.9, 1.0)
|
0.80
|
|
0.0 (-0.0, 0.0)
|
0.0 (-0.0, 0.0)
|
0.69
|
|
-0.0 (-0.1, 0.0)
|
-0.0 (-0.1, 0.0)
|
0.53
|
Fiber (g/day)
|
18.2 (17.8, 18.5)
|
18.0 (17.7, 18.3)
|
0.48
|
|
+0.2 (-0.1, 0.4)
|
+0.3 (0.0, 0.6)
|
0.49
|
|
+0.2 (-0.1, 0.5)
|
+0.3 (0.0, 0.5)
|
0.70
|
Self-rated Health
|
3.8 (3.7, 3.9)
|
3.8 (3.8, 3.9)
|
0.87
|
|
+0.02 (-0.1, 0.1)
|
-0.04 (-0.1, 0.03)
|
0.20
|
|
0.03 (-0.04, 0.1)
|
0.01 (-0.1, 0.1)
|
0.70
|
E-health literacy score
|
30.4 (29.8, 31.1)
|
29.1 (28.5, 29.8)
|
0.01
|
|
+1.4 (0.8, 1.9)
|
+0.6 (0.1, 1.1)
|
0.04
|
|
+1.6 (1.0, 2.1)
|
+1.4 (0.8, 1.9)
|
0.65
|
|
|
|
|
|
|
|
|
|
|
|
|
p-value from generalized mixed model, group*time interaction at respective time points; a end of study and follow-up data presented as odds ratio, comparing odds of correctly identifying guideline in intervention vs. control group
|
Engagement with KT strategies
At baseline, 97.5% of participants indicated they would use email content during the intervention period compared to 70.0% for the Portal Browse page, 44.0% for Facebook, and 14.7% for Twitter (no between-group differences) (Table 3). During the intervention, 95.1% of the intervention group reported using email alerts, compared to 46.3% who browsed the Portal, 15.2% who used Facebook, and 5.3% who used Twitter. While some control group participants did report accessing content, engagement was higher in the intervention group across each strategy (Table 3). Of those who reported using each KT strategy, satisfaction (measured as perceived usefulness, and likelihood of continued use) was rated highly across all platforms (mean 5.6 to 6.5 on a 7-point Likert scale).
Table 3: Participant engagement and satisfaction by KT strategy
|
CONT
|
INT
|
p
|
n
|
N = 279
|
N = 278
|
|
(At baseline) Which of the following do you plan to use to access study material:
|
Email
|
274 (98.2)
|
269 (96.8)
|
0.41
|
Browse on Portal
|
187 (67.0)
|
203 (73.0)
|
0.15
|
Facebook
|
121 (43.4)
|
124 (44.6)
|
0.84
|
Twitter
|
35 (12.5)
|
47 (16.9)
|
0.18
|
|
|
|
|
Over the 12-week study period, did you access the McMaster Optimal Aging Portal via … (% Yes)
|
|
N = 251
|
N = 244
|
|
Email
|
162 (64.5)
|
232 (95.1)
|
<0.001
|
Perceived usefulness
|
|
5.91 ± 1.33
|
|
I will continue to use
|
|
6.09 ± 1.58
|
|
Browse on Portal n = 250
|
56 (22.3)
|
113 (46.3)
|
<0.001
|
Perceived usefulness
|
|
6.10 ± 1.06
|
|
I will continue to use
|
|
6.02 ± 1.28
|
|
Facebook n = 250
|
18 (7.2)
|
37 (15.2)
|
<0.01
|
Perceived usefulness
|
|
5.81 ± 1.27
|
|
I will continue to use
|
|
6.16 ± 1.24
|
|
Twitter n - 250
|
3 (1.2)
|
13 (5.3)
|
0.02
|
Perceived usefulness
|
|
5.62 ± 1.98
|
|
I will continue to use
|
|
6.46 ± 1.39
|
|
|
|
|
|
[At 3-month follow-up] Since the study ended, have you accessed the Portal via…? (% Yes)
|
|
N = 240
|
N = 232
|
|
Email
|
163 (67.9)
|
182 (78.4)
|
0.01
|
Browse on Portal
|
92 (38.3)
|
103 (44.4)
|
0.21
|
Facebook
|
32 (13.3)
|
51 (22.0)
|
0.02
|
Twitter
|
12 (5.0)
|
28 (12.1)
|
0.01
|
|
|
|
|
Qualitative data reinforced our quantitative findings, conveying that participants preferred email content over other KT strategies. They highlighted the ease of use of emails, the ability to save emails for reading later, and the ability to share information with family and friends as being the main benefits.
…the emails, they seemed to be topic, like there was a topic and I was like okay if I'm interested in that topic I can read more. And so I liked that aspect and I liked when I clicked on something and … when it came up and it was like okay here's the main message, there's a very quick summary of something and then I can follow links if I was more interested.”
“It’s simple. You get it. It’s very easy to read, like it’s in point form somewhat and you see it and you go, “Oh, let’s have a look at that”.
“Well, so it was very convenient for me for all the obvious reasons. You can read it when you have time and you can review it and you make a file and keep your file and go back and look and reference them again, so all of those things with all the convenience of digital communication. And it was especially nice for me because I don’t choose to participate in Facebook or Twitter so it was great to be able to get the emails and also to know about the McMaster Optimal Aging Portal.”
Qualitative data reinforced that social media was not preferred. Many participants reported not having social media accounts (particularly Twitter) and not being interested in using social media.
“I am on social media with regard to Facebook but I haven’t - they put so much junk on that Facebook as it is I wouldn't want to, you know, you get a lot of stuff and another thing coming up on the newsfeed.”
"Well, I’m not on Twitter so I had no desire to join the Twitter-verse. Not that I'm anti-Twitter I'm just like, just not really that into social media. And Facebook I felt at work that was tricky, like I try not to be on Facebook at work. So I really try to limit most of my internet time to work hours and then like if I check Facebook it's really brief, like did someone message me or whatever, so really I did depend on the emails that way.”
Engagement with intervention content was highest during the first week of the study and lower throughout the intervention period (Figure 3). On average, 30.1% of participants engaged with content within an email on a given week. Engagement was highest in week 1 (83.1% clicked through) and lowest in week 5 (6.8% clicked through). Data related to the number of emails received and opened were unavailable due to a technical issue with the analytics software. Number of pages per session (mean: 2.8, range 2.3 to 3.2), and time per session (mean: 4.6 min, range: 2.8 to 5.7) was consistent throughout the study period. When separated by topic (Figure 4), engagement with intervention content related to diet and physical activity was higher than engagement with topics related to alcohol intake or smoking.