CHAPTER IV

PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA

This chapter presents the analysis and interpretation of the data gathered based on the

research questions as stated in Chapter 1. Tabular forms were used to present the data analysis

and interpretation of the findings for clearer understanding.

Table 1 shows the Demographic profile summary of respondents, including age, gender,

location, and the level of familiarity of the respondents with digital-based mental health

interventions. The respondents consisted of mostly those aged between 15-24 years, at 76.67%;

this is a relatively young population that is likely to open up to using digital tools for mental

health support because they easily get familiar with technology (Graham et al., 2021). The

balance between both genders is approximately equal, with just a slight edge at 51.00% of

females representing the more general patterns of females being marginally more inclined to
engage with mental health services than men, particularly in digital forms (Rural Health

Information Hub, 2022).

To some extent, both rural and urban perspectives have been represented by the data;

however, research studies have shown that digital mental health attitudes can differ between the

two groups. It has been shown that urban respondents are likely to have accessibility to and

familiarity with digital sources of which they may be more readily able to make use. Key barriers

remain in rural areas; low access to the internet and high stigma levels around issues of mental

health. However, digital mental health interventions are seen to offer some useful means to

bridge gaps in access to care. In total, 74.00% of respondents reported some knowledge of digital

mental health tools, and even though it might represent a high level of awareness, this also

suggests an opportunity to engage targeted outreach in underserved areas.

Table 2 presents the Attitudes toward digital interventions for mental health Confidence

in effectiveness Anonymity benefits Skepticism Perception of technologization threats

Respondents Attitudes toward digital mental health tools- Generally positive attitudes are mainly

depicted by responses. Much agreement is seen in the highest rating for Confidence in

Effectiveness, where respondents maintain a positive belief in the effectiveness of digital

interventions. This is in line with research that reveals increasing trust in these tools, especially
because they can offer timely and readily accessible mental health support (Naslund et al., 2020).

Similarly, Anonymity Benefits scored positive opinion from the respondents with a mean value

of 3.55. These respondents appreciated benefits like online privacy as it will remove or reduce

stigma and enhance utilization, especially in rural settings where stigma still stands as one of the

biggest barriers to mental health services traditionally offered (Graham et al., 2021; NRHA,

2022).

However, there was Neutrality (mean = 3.24) regarding Skepticism and Perceived Risk,

as expressed by people's concern over the safety and reliability of the interventions, especially in

ensuring data privacy and security. These are not exclusive to the adoption of digital health,

where user concerns center on the possibility of data breaches and the general effectiveness of

virtual solutions (Torous & Vahia, 2020). Finally, Technologization Threat (mean = 3.53) seems

to be a fear of losing the component of human interaction/ connection in mental health care as

respondents feel that the part will get lost. This belief finds its relevance in literature where it is

argued that a balance between digital and traditional mental health support is important for

providing care with a human touch (Torous & Vahia, 2020).

 Table 3 presents the controlling for perceived usefulness, ease of use, social influence,

behavioral control, and intention to use, the rural and urban communities' beliefs toward digital

interventions for their mental health. Generally, there is evidence that shows respondents from

both rural and urban communities are inclined to harbor positive views toward issues regarding

the usefulness and ease of using the tools related to mental health but with a slight difference

inasmuch as the urban respondents rated these slightly higher.

Furthermore, in the context of Perceived Usefulness Beliefs, relative to the rural group,

the means of the urban group indicate that the digital interventions are useful. The result suggests

that the perceived utility of such tools is highly accepted regardless of location. This proves some

of the recent studies, which have come out stressing the importance of digital tools in improving

mental health outcomes, especially for populations that do not have access to regular in-person

care (Torous et al., 2020).

Third, in relation to Perceived Ease of Use, rural respondents scored slightly lower than

urban respondents-mean = 3.60 for rural versus mean = 3.74 for urban; however, both groups
agree that the tools are easy to use. This bears some of the challenges facing rural areas, such as

less-developed digital literacies or technological infrastructure, affecting ease of use (Graham et

al., 2021).

Concerning Social Influence/Subjective Norms, rural respondents agree that social norms

and outside influences do determine their decisions to use digital interventions. Mean = 3.53.

Similarly, the urban respondents agreed with a mean score of 3.50 about social norms and

outside influences determining their decisions to use digital interventions. Rural respondents are

a bit more likely to consider social pressure than the urban population. This is because social

stigma and actual norms could be stronger in the rural settings, which might influence the uptake

of these psychological interventions (NRHA, 2022).

As for Perceived Behavioral Control/Facilitating Conditions, the two groups gave the

necessary positive perceptions; in that, both believe facilitating conditions to the use of digital

tools are present in their behavior with a mean = 3.60 for the rural and a mean = 3.76 for the

urban group. In other words, they feel that all the facilitating conditions of using digital tools are

available to them except, perhaps better access to technology which may end up making the rural

group score lower as compared to the urban one (Naslund et al., 2020).

Lastly, Intention and Behavior Outcome shows very high intention to adapt digital

interventions, where the respondents from the rural region had scored 3.73 while that from the

urban region scored 3.91 that indicates both 'clearly intended to use the digital tools but the urban

group is slightly more committed to adopting these tools; this is due to probably having greater

connectivity with digital infrastructure coupled with higher levels of comfort with the use of the

technologies in urban settings (Torous & Vahia, 2020).

 Table 4.1 shows the significant differences by sex at birth in attitudes toward digital

mental health interventions: Test results A difference in Confidence in Effectiveness The bar

chart clearly shows that there is a significant difference between males (M = 3.82, SD = 0.69)

and females (M = 4.00, SD = 0.56), where p = 0.014 (p < 0.05). This goes on to prove that

women have a better perception concerning the efficiency of digital mental health tools than men

do. Other researchers have explored the distinctions between both genders concerning attitudes

towards mental health interventions whereby, in most cases, women tend to be more receptive

and trusting concerning conventional and digital mental health services (Vahia et al., 2020;

Naslund et al., 2020).

And then, no significant difference exists on the aspects of anonymity benefits among

males and females (p = 0.395), skepticism and risk perception (p = 0.885), and technologization

risk threat (p = 0.274). Both genders tended to agree on the anonymity benefits of digital

intervention in general, with higher means from the respondents who were males with 3.59,

whereas the mean for females is 3.52, and both genders show similar levels of skepticism and

perceived risks with male mean scores as 3.24 and female mean as 3.23. Views on the risk of
technologization were also alike (male mean = 3.49, female mean = 3.57). Findings resulted in

the fact that both gender equally operate at a level of awareness with the anonymity that can be

achieved through digital interventions as well as shared common concern over the dangers of

technology use in mental health care. In line with the literature that pointed out the establishment

of anonymity as critical towards the attenuation of stigma for both genders toward mental health-

related assistance, issues related to privacy and data security tend to affect all users with equal

weighting (Graham et al., 2021; Torous & Vahia, 2020; Torous et al., 2021).

All in all, the study shows some differences between males and females as to the

perceived effectiveness of digital interventions, but the attitudes of both males and females are

very similar in terms of other benefits of anonymity and perceived risks and technologization.

This is in agreement with recent studies, which suggest that when both males and females have

barriers associated with the acceptance of digital health tools, the factors may differ between

genders, such as effectiveness and trust that might affect females slightly more (Naslund et al.,

2020; Vahia et al., 2020).

 Table 4.2 shows the result of a comparison of attitudes towards digital mental health

interventions of 15- to 24-year-old persons and 25- to 35-year-old respondents. No attitudes

could be found to be significantly different for the four indicators: Confidence in Effectiveness,

Benefit from Anonymity, Skepticism and Perception of Risk, and Threat due to

Technologization with p-values > 0.05 for each indicator. For Confidence in Effectiveness, the

means of the young respondents were 3.94 and adults were 3.82, with a p-value of 0.204 so that

the tool can be believed to be relatively effective by both the young and adults to an equal

degree. Other than that, for the benefit of Anonymity, the mean scores for the young respondents

were 3.53, whereas as against it, the adults had a higher mean score at 3.61, however not

statistically significant (p = 0.509). Both the groups were in agreement with respect to anonymity

while using the digital intervention. This is a function of studies that reveal, among other

elements of privacy and anonymity, to be critical determinants for adopting digital health

solutions, especially concerning mental health issues (Torous & Vahia, 2020; Naslund et al.,

2020).
 For Perception Risk and Skepticism, the groups were almost identical in terms of the

level of skepticism; their means for the young were 3.24 and 3.23 for adults with a p-value of

0.957, not indicating that there is any statistical difference. The same case is applicable to the

Technologization Threat where, between the two, there was no statistical difference marked;

indicated by the p-value of 0.954 between young's 3.53 and adults 3.52. This thus points that

both the young and adult respondents share the same interest in issues pertaining to

technologization risks in mental health interventions. Overall, considering limited differences in

means, young and adult respondents' attitudes towards digital interventions on mental health

show a very high degree of similarity, since firstly, both are benefitting from the aspect of

anonymity, and second, view the tools as effective while sharing concerns on privacy and

technology-induced risk. These findings correlate with research on the general paradigm of

digital health interventions in the conclusion that different age groups share similar attitudes

regarding the possibility of digital tools for improving mental health care (Torous et al., 2021;

Vahia et al., 2020).

 Table 4.3 shows the results of Test of Significant Differences in Attitudes toward Digital

Mental Health Interventions, Rural and Urban Respondents Summarizes the outcome of the

analysis of four key indicators: Confidence in Effectiveness, Anonymity Benefits, Skepticism

and Perception Risk, and Technologization Threat. With Confidence in Effectiveness, the p-

value is at 0.339 such that there is no significant difference between respondents from rural areas

with a mean of 3.88 and SD of 0.66 against respondents from urban who posted a mean of 3.94

and SD of 0.61, which indicates there is no big difference generally between groups regarding

the effectiveness of digital mental health interventions. Similarly, studies emphasis that it is

observed generally that people from different geographical areas consider digital health tools to

be equally effective (Torous et al., 2021).

Results for Anonymity Benefits show that there is no significant difference between rural

(mean = 3.50, SD = 0.75) and urban (mean = 3.61, SD = 0.71) respondents who would value the

anonymity that digital interventions afford them, p-value of 0.180. This supports evidence which

places more emphasis on privacy as a key determinant of uptake of digital mental health services

(Sarkar et al., 2019; Hennemann et al., 2020). Skepticism and Perception Risk : For Skepticism

and Perception Risk, the p-value of 0.273 means that there is not much of a difference in

responses between rural respondents (mean = 3.29, SD = 0.72) and urban respondents (mean =

3.19, SD = 0.80), meaning that both have a pretty significant concern about data privacy as such

risks included in digital tools (Vahia et al., 2020; Hennemann et al., 2020). Lastly, to

Technologization Threat, the p-value of 0.184 actually repeats the fact that the rural (mean =

3.58, SD = 0.64) and the urban group (mean = 3.48, SD = 0.68) might not differ significantly,

meaning that both of the groups' sets of respondents voice their concerns over the threats that

over-reliance on technology would pose for mental health care in equal measure. These results
are in line with other studies that note the presence of widespread skepticism about the

technologization of health care within multiple populations (Graham et al., 2021).

Table 4.4 shows the results of comparison test results: Attitudes toward digital mental

health interventions Knowledgeful participants Not knowledgeable participants Important

differences Importance Confidence in Efficacy Anonymity Benefits Skeptical and Perception

Risk Technologization Threat.

Confidence in Efficacy Knowledgeful participants vs. Not knowledgeable participants

mean difference was statistically significant at p-value: .017, mean = 3.97, SD = 0.60; mean =

3.75, SD = 0.71. Those knowledgeable about the digital mental health interventions reported

higher agreement of their effectiveness. This fits with research indicating greater familiarity with

the digital technologies may be advantageous to user self-efficacy (Lattie et al., 2020; Naslund et

al., 2020). However, regarding the Anonymity Benefits, with a p-value of 0.276, the differences

between knowledgeable mean = 3.58, SD = 0.73 and nonknowledgeable mean = 3.47, SD = 0.72
are rather similar. Indeed both stated that anonymity is essential to encourage online participation

in mental health resources (Sarkar et al., 2019; Shaughnessy et al., 2021).

With a p-value of 0.957, and from the case of Skepticism and Perception Risk, we see

that there is no significant difference between the two groups because well-informed (mean =

3.24, SD = 0.79), as well as uninformed (mean = 3.24, SD = 0.68), respondents treated their

concerns over perceived risks. This conclusion, therefore, aligns with earlier studies that insist

that mistrust in the security and privacy of digital mental health interventions cuts across wide

spectrums irrespective of the level of knowledge (Graham et al., 2021; Torous & Vahia, 2020).

In the case of Technologization Threat, the p-value is at 0.315; this too indicates that there is no

statistical difference between the two groups in the context of anxiety concerning the effects of

enhanced technology reliance for psychological treatments. Such concerns related to the

technologization of healthcare have an array of reports across different populations (Graham et

al., 2021; Naslund et al., 2020).

 Table 5.1 presents the results of Test of the differences in the beliefs toward the digital

mental health intervention between the male and female respondents: The indicators studied

were Perceived Usefulness Beliefs, Perceived Ease of Use Beliefs, Social Influence/Subjective

Norms Beliefs, Perceived Behavioral Control/Facilitating Conditions Beliefs, Intention and the

Behavior Outcome.

For perceived usefulness beliefs, p-value = 0.302 indicates no significant difference

between males (mean = 3.73 SD = 0.62 and females mean = 3.80, SD = 0.65), indicating that

both perceive digital interventions similarly to be useful in life. Similarly, in the case of

Perceived Ease of Use Beliefs, there is no significant difference between males with a mean of

3.63, SD = 0.77 and females with a mean of 3.71, SD = 0.64 with the p-value being 0.329. In

parallel to previously executed studies, it was not feasible to find any gender-based difference for

the ease of using digital tools in terms of mental health (Lattie et al., 2020; Lin et al., 2022).

For Social Influence/Subjective Norms Beliefs p-value = 0.223 shows no significant

gender differences by comparing means with equal SDs = 0.62 for both. Men and women both

share the same beliefs on how much social influence is applied in enforcing electronic

interventions as suggested by previous studies where there is evidence that contribution of social

influence to attitude toward electronic health services manifests across the genders (Vasilenko et

al., 2021). Similarly, no significant difference can be seen for Perceived Behavioral

Control/Facilitating Conditions Beliefs, with a p-value of 0.541, indicating that both groups hold

similar views regarding the ability of accessing as well as using these interventions (Sarkar et al.,

2020).

Finally, for Intention and the Behavior Outcome, with a p-value of 0.545, this affirms the

no significant difference about the gender group between male subjects (mean = 3.85, SD =
0.82) and female ones (mean = 3.80, SD = 0.68). Both genders almost have the same intention to

make use of their digital mental health tools, and it does not indicate that differences in gender

may determine differences in shaping the intentions of its users to interact with these

interventions (Matusitz & McCormick, 2020).

Table 5.2 shows the result of significant differences testing between beliefs among

young-aged (15-24 years) and adult-aged respondents (25-35 years) toward digital mental health

interventions. The indicators considered in the model are Perceived Usefulness Beliefs,

Perceived Ease of Use Beliefs, Social Influence/Subjective Norms Beliefs, Perceived Behavioral

Control/Facilitating Conditions Beliefs, and Intention and the Behavior Outcome.

Perceived Usefulness beliefs have the p-value of 0.287 indicates that there is not a

significant difference for the group of young respondents and the adult respondent as they have

average ratings equal to 3.79, SD = 0.63 for the former and 3.69, SD = 0.67 for the latter. From

this result, we may infer that both share the same viewpoint in the perception that digital mental

health interventions are useful. Similarly, Perceived Ease of Use Beliefs has a p-value of 0.222,
indicating that there is no significant difference between the young (mean = 3.70, SD = 0.69) and

adult (mean = 3.58, SD = 0.75) groups, since the two groups perceive ease of use in a similar

manner, in that ease of use is most often well accepted among different age groups O'Neill et al.,

2021; Hill et al., 2022).

The indicator in the Social Influence/Subjective Norms Beliefs has a p-value of 0.678;

hence, there is no significant difference between the young and the adult group on what they

believe regarding the influence that social norms have on their behavior. This result is in line

with the literature in that, especially about the adoption of technology for health, social influence

does not differ much by age (Wang et al., 2020). For Perceived Behavioral Control/Facilitating

Conditions Beliefs, the p-value was 0.24. This means that there is no difference between the two

groups (young: mean = 3.71; SD = 0.59; adult: mean = 3.59; SD = 0.80), which suggests that

both of the age groups feel about equally capable of using digital mental health interventions.

Thirdly, Intention and Behaviour Outcome with p-value of 0.153 greater than the level of

significance at 0.05 and the younger people (mean = 3.86, SD = 0.71) and older people (mean =

3.70, SD = 0.89) and hence there was no significant difference. This implies that the intention to

use digital mental health interventions is not significantly influenced by age, consistent with the

other findings that intention to make technology use is high across most of the age groups

(Matusitz & McCormick, 2020).

 Table 5.3 shows the results of test of significant differences of beliefs toward the digital

mental health interventions between the respondents from rural and that from urban locations.

Measured indicators: Perceived Usefulness Beliefs, Perceived Ease of Use Beliefs, Social

Influence/Subjective Norms Beliefs, Perceived Behavioral Control/Facilitating Conditions

Beliefs, and Intention and the Behavior Outcome.

The Perceived Usefulness Beliefs indicator reveals no significant difference between

rural and urban respondents: mean = 3.77, SD = 0.68 for the former and mean = 3.76, SD = 0.59

for the latter; p = 0.892, which is above the threshold for significance. This result means that

both rural and urban respondents considered digital mental health interventions to be similarly

useful, in accordance with other studies indicating that geographic location has no impact in the

perceptions of utility about digital health technology (Chong et al., 2020; Papageorgiou et al.,

2021).

With Perceived Ease of Use Beliefs, p-value =0.092, which means there was no

significant difference among the rural and the urban respondents. At face value, it seems this
study is affiliated with literature stating that ease of use perceptions may be relatively consistent

between the urban and rural populations, although in ways unique to the rural individual,

challenges related to access arise (Rao et al., 2020).

Regarding Social Influence/Subjective Norms Beliefs, there is no significant difference

between the two groups (rural: mean = 3.53, SD = 0.64; urban: mean = 3.50, SD = 0.60) with a

p-value of 0.71. This result comes out with the inference that the social influences towards the

use of digital mental health interventions are viewed in an identical manner in both rural and

urban locations, though an inference which supports that proposition comes from the work of Xu

et al. (2021), who presented the theory that subjective norms may not be particularly strongly

affected by setting.

For Perceived Behavioral Control/Facilitating Conditions Beliefs, the p-value of 0.033 is

significant, suggesting that there would be a difference between the rural and the urban

respondents; mean = 3.60, SD = 0.63, for rural and mean = 3.76, SD = 0.65, for urban. It

indicates that perhaps the respondents of the urban areas may feel a little more capable or have

easy access to digital health technologies. There is research which says that there is an advantage

in infrastructure and resources for digital health interventions in urban areas as compared to rural

ones (Ding et al., 2019).

Lastly, Intention and the Behavior Outcome has a p-value of 0.039, which is statistically

significant because the mean intention and behavior among rural respondents is 3.73, SD = 0.75,

and among urban is 3.91, SD = 0.75, meaning the intention of the urban to use digital mental

health interventions is slightly higher. Other studies also indicate that urban populations would

be more exposed to and willing to use digital health technologies because of increased awareness

and the increased availability of services offered (Kang et al., 2021).

 Table 5.4 shows the results of Belief differences in views toward digital mental health

interventions existing between respondent groups who know or do not know the subject

Indications under investigation Perceived usefulness beliefs Perceived ease of use beliefs Social

influence/subjective norms beliefs Perceived behavioral control/facilitating conditions beliefs

Intention and the behaviour outcome.

There was no significant difference between the knowledge group, mean = 3.76, SD =

0.59 and the no-knowledge group, mean = 3.77, SD = 0.76, p-value = 0.934, which is above the

level of significance, meaning that the degree of knowledge about digital mental health

interventions does not interfere with the perceived useful level of interventions. As already seen

in the preceding studies discussing the perceived usefulness of digital tools, often not related to

individual knowledge about a person (Harrington et al., 2021; Asri et al., 2022);

For Perceived Ease of Use Beliefs the p-value is also at 0.194 and appears that no

difference exists between both groups (with knowledge: mean = 3.71, SD = 0.67; without

knowledge: mean = 3.58, SD = 0.79). This means knowledge among the users in place does not
have a bearing on perceptions about how easy or hard it is to use digital mental health tools.

More often, factors such as the design interface, or internet availability influence ease of use than

the user's knowledge, as could be seen in previous studies carried out by Günther et al., 2020).

Therefore, for Social Influence/Subjective Norms Beliefs, the p-value of 0.496 signifies

that there is no difference between the respondents who have knowledge and those who have no

knowledge because both of them are not having any significant difference among them with

mean values of 3.53, SD = 0.61 and mean = 3.47, SD = 0.64 respectively. Thus social influence

is a function of people's level of knowledge. For example, social factors like having peer support

can affect the implementation of technology, while knowledge levels rank as one of the lowest

reasons to initiate such a project (Garrido et al., 2020).

The Perceived Behavioral Control/Facilitating Conditions Beliefs scale is highly

significant with p-value 0.028. Those respondents who were cognizant reported having a higher

sense of control and self-efficacy compared with those not aware (mean = 3.73, SD = 0.63 and

mean = 3.54, SD = 0.66). The study results thus imply that education over digital health tools

enhances the perception of ability. These results are consistent with the Technology Acceptance

Model as they indicate that indeed a positive influence in one's sense of control over their

behavior is gained from knowledge (Venkatesh et al., 2021).

The last result for Intention and for the Behaviour Outcome was p-value = 0.315, which

did not reveal an important difference between groups. It was either with knowledge, mean =

3.85, SD = 0.72 or without knowledge, mean = 3.74, SD = 0.84. It suggests that awareness has

little impact on the intention to use the digital interventions in intervention and perhaps shows

that factors like motivation or barriers well beyond one's control-for instance, access to
technology-are far more important in determining intent than awareness of what needs to be

different in theory, according to some studies, as revealed by Fang et al., 2021.

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