INTRODUCTION:

One of the main reasons why aging is considered a critical political problem is the dramatic growth of the elderly population around the world^1-4. The United Nations report that in 2022, the number of people aged 65 and older reached 771 million, which is three times more than in 1980 (258 million)⁵.

By 2030, the elderly population is predicted to rise to 994 million people, and by 2050 – to 1.6 billion. Thus, by 2050, there will be almost twice as many people aged 65 and older as children under 12⁵. Regrettably, despite convincing data suggesting that seniors live longer, the quality of their lives during these later years is unclear^{1, 6}. Several studies on the older generation indicate an increased prevalence of chronic^1,7-9 and concomitant diseases^10-13. A progressive decline in the body’s adaptive capacity and changes in its reactivity create preconditions for the development of pathologies^1,14-17. The rate of morbidity in the elderly is 2-6 times higher than in the young^1,18. The primary challenges of drug therapy in the elderly are the need to prescribe more than one medication due to the presence of several diseases; the need for long-term use of medications due to the chronic course of many diseases; disruption of pharmacodynamics and pharmacokinetics of drugs against the background of age-related changes in organs and systems, as well as existing pathologies; compliance issues – insufficient or improper compliance with the prescribed drug therapy regimen^1,19-25. For these reasons, high-quality drug treatment for senior citizens is an acute task of medicine and pharmacy. A way to address this problem is the use of mobile applications^26-29. The use of mobile apps has increased significantly in recent years^30-34. According to an App Annie report, consumer spending on mobile apps in 2022 grew 19% over the previous year³⁵. Mobile healthcare apps (mHealth) offer older citizens reminders to take a specific medication at a certain time along with its dosage and to buy a new pack of medication, as well as information on administration. They can even monitor physiological parameters^36,37. Mobile applications of pharmacy chains, individual pharmacies, and aggregators to search for medications and their prices allow seniors to purchase and get deliveries of necessary medications with minimal time and resources²⁶. However, older adults' attitudes toward mobile apps for drug therapy are currently ambiguous and need to be scientifically investigated. This objective is especially relevant given emergencies like the COVID-19 pandemic^38-42.

The goal of the present study is to research the reasons hindering the adoption of mobile applications for drug treatment by senior citizens in Russia by determining their attitudes to applications in general and with a focus on differences between the attitudes of potential and actual consumers in particular.

METHODS:

A marketing descriptive study was conducted based on a survey that featured older users of mobile apps for medication therapy in Russia.

The objects of the study were three groups of mobile applications for drug treatment: healthcare applications (mHealth), applications of pharmacy chains and individual pharmacies, and drug search applications (aggregators of medications and their prices).

The subjects of the study (survey participants) were 816 elderly users of mobile applications for drug treatment from 37 constituent entities of the Russian Federation. The respondents were divided into two target segments. The first segment (S1) included 400 actual app users, and the second (S2) – 416 potential users. In marketing, an actual consumer is a person who currently uses the product or service, and a potential consumer is the one who currently shows interest in the product or service or may become interested in the future^43,44. Among potential consumers, 196 of our respondents (47.1%) wished to use mobile apps for drug therapy currently, and 220 respondents (52.9%) – in the future. The inclusion criteria for the study were: actual and potential consumers of mobile medication treatment apps over the age of 55 who had smartphones and were willing to participate in the survey. Participation in the study was anonymous and voluntary. The respondents were fully informed of the purpose, nature, and potential risks and benefits of the survey. The study was conducted in accordance with the Declaration of Helsinki and the International Code on Market and Social Research (ICC/ESOMAR)⁴⁵. Sampling was performed using a probabilistic (random) stratified method. The sample size of each target segment was determined by time and resource constraints.

The survey instrument, a structured questionnaire, consisted of three parts and contained 17 questions. The first part of the questionnaire focused on survey participants' general opinion about using mobile apps for medication therapy (five questions) and targeted primarily S1 segment consumers. The second part of the questionnaire included questions about factors influencing older adults' adoption of apps and about relevant personal motivational incentives and barriers (six questions). The third part of the questionnaire included questions concerning the respondents' characteristics (6 questions). A scale Likert was used in the answers to some questions of the questionnaire, and a free text field was used for a deeper insight into the respondents' opinions.

A preliminary pilot study was conducted to test the questionnaire on 15 users of mobile drug treatment apps in the 55-85 age range. The objective of this study was to determine the time required for the survey, the technical opportunities to administer the survey online, and the clarity and understandability of the survey questions.

The final version of the questionnaire was administered during the field phase of the study in April-August 2022 with an in-person oral survey (24.5%) and an online survey (75.5%). Respondents were recruited from medical and pharmaceutical organizations in Moscow and the Moscow region, on Vkontakte and Facebook, and in online forums for senior citizens and retirees, including Aktivnoedolgoletie ["Active Longevity"] and Moskovskoedolgoletie ["Moscow Longevity"]. All questionnaires were assigned codes for tracking, and the codes were stored securely.

Statistical data processing was performed with IBM SPSS Statistics 28.0.1 software. Respondent characteristics of the target segments studied were expressed either in absolute and relative values or in metric units such as median, lower (25%) and upper (75%) quartiles (IQR), or mean±standard deviation (SD). Cross tabulations, the Mann-Whitney test, and the Kruskal-Wallis test were used to assess differences between individual groups. The critical level of significance for statistical hypothesis testing in the study was taken to be 0.05.

RESULTS:

Characteristics of survey participants:

Among the 816 respondents, women predominated: in the target segment S1 they accounted for 81.5%, and in the segment S2 – for 79.6%. The mean age of survey participants in S1 was 66.7±5.1 years (median 67, IQR: 62-72) and in S2 – 67.2±5.8 years (median 67, IQR: 61-73). The predominant share of respondents had a higher professional education (specialist’s, master’s, or bachelor’s degree): 68.3% in S1 and 74.5% in S2. In terms of social status, a significant part of respondents was working pensioners (S1 – 37.5%, S2 – 34.1%). Specifically, most of the employed pensioners worked white-collar jobs (70-78%). Regarding average monthly income per family member, most survey participants were at the average level (S1 – 40.8%, S2 – 35.6%). Residents of Moscow and the Moscow region made up 34.8% of the sample. The share of respondents from central Russia was 22.4%, from Southern regions – 15.6%, from the Far North and Siberia – 16.9%, and from other regions of the country – 10.3%

Respondents in each target sample were assigned to age groups: 55 to 65 years (in S1 – n=194; in S2 – n=184), 65 to 75 years (in S1 – n=147; in S2 – n=165), and 75 years and older (in S1 – n=59; in S2 – n=67).

Factors affecting the adoption of mobile apps for drug treatment by seniors:

The survey provides evidence that older people do use or wish to use one or several mobile apps for drug therapy. In S1, mHealth apps are used by 87.3% of respondents, mobile apps of pharmacy chains and individual pharmacies – by 34.5%, and drug price and search applications (aggregators) – by 18.0%. Another 10.5% of survey participants report using other apps, including medication directories (8.5%). Regarding S2, most of the respondents in it show a willingness to use mHealth apps presently (90.8%) and 95.9% wish to do so in the future; apps of pharmacy chains and individual pharmacies are planned to be used currently or in the future by 71.4 and 85.0%, respectively; and drug search apps – by 69.4 and 76.4%, respectively.

When asked how often they used the indicated apps, seniors in S1 gave the following answers: several times a day – 74.5%, daily – 15.5%, several times a week – 5.5%, weekly – 3.0%, monthly – 1.5%.

We distinguish two groups of factors that affect the use of mobile applications by the elderly:

· factors that form older people's attitudes toward apps;

· factors that maintain older people's attitudes toward apps.

The formative factors are understood as those that define the choice of a mobile app and apply mostly to potential consumers. The maintaining factors are considered as those that determine further use of the app and mostly concern actual consumers.

Analysis of factors that form and maintain the attitudes of older people to mobile apps for drug treatment indicates minor differences between the opinions of respondents in S1 and S2 (Tables 1 and 3), which concurs with previous research^{36, 37} and literature^46-49. Notably, the present study includes additional factors that affect the adoption of mobile applications by seniors. Specifically, the new formative factor "Level of consistency of the application's core function set with the initial demands for medication therapy" is recognized by S1 and S2 survey participants as the most significant (R_i=14, W_i=0.133) (Table 1). The next in importance in S2 comes "Technical ease of use" (R_i=13, W_i=0.124), ranking 12 in S1 (W_i=0.114). After that in S2 follow the factors of "Availability with the necessary software" (R_i=12, W_i=0.114) and "Quality" (R_i=11, W_i=0.105), which in S1 rank 13 (W_i=0.124) and 10 (W_i=0.095), accordingly. The newly introduced factors of "Clear and understandable instructions for use" and "Opportunity to limit contact with other people" rank 5-9 and, therefore, can also be considered indicators of the special attitude of the elderly toward mobile apps for medication therapy at this time.

Table 1: Significance of the factors forming the attitudes toward mobile apps for drug treatment in the two target segments of older adults

Factor	Target segment
	S1			S2
	Rank (R_i)*¹	Rank price (С)*²	Rank weight (W_i)*³	Rank (R_i)	Rank price (С)	Rank weight (W_i)
Technical ease of use	12	0.0095	0.114	13	0.0095	0.124
Quality	10		0.095	11		0.105
Price	7		0.067	8		0.076
Availability with the necessary software	13		0.124	12		0.114
Safety	11		0.105	10		0.095
Visual design	4		0.038	4		0.038
Amount of mobile content	9		0.086	5		0.048
Developer	3		0.029	1		0.010
Clear and understandable instructions for use	8		0.076	9		0.086
Level of consistency of the application's core function set with the initial demands for medication therapy	14		0.133	14		0.133
Extent of regulation by professional agencies	1		0.010	2		0.019
Opportunity to communicate with the attending physician or a pharmacist	6		0.057	7		0.067
Opportunity to limit contact with other people	5		0.048	6		0.057
Multiple users (e.g., all family members) being able to obtain drug treatment	2		0.019	3		0.029
Note. ¹ Direct ranking method. ²С = 1/∑R_i. ³W_i= C • R_i.*

Table 2: Results of an overall evaluation of mobile apps for drug therapy by seniors in the two target segments based on the formative factors

Factor	Target segment
	S1			S2
	(A_i±a)*¹	P_i*²	P_n*³	A_i±a	P_i	P_n
Technical ease of use	4.33±0.05	0.49	4.3	4.18±0.07	0.52	4.1
Quality	4.62±0.03	0.44		4.60±0.04	0.48
Price	4.88±0.05	0.33		4.75±0.06	0.36
Availability with the necessary software	4.59±0.04	0.57		4.36±0.05	0.50
Safety	4.43±0.03	0.47		4.32±0.05	0.41
Visual design	4.45±0.06	0.17		4.28±0.07	0.16
Amount of mobile content	4.34±0.04	0.37		4.47±0.05	0.21
Developer	4.87±0.03	0.14		4.80±0.04	0.05
Clear and understandable instructions for use	3.31±0.05	0.25		2.84±0.06	0.24
Level of consistency of the application's core function set with the initial demands for medication therapy	4.18±0.04	0.56		3.85±0.05	0.51
Extent of regulation by professional agencies	3.79±0.03	0.04		3.87±0.05	0.07
Opportunity to communicate with the attending physician or a pharmacist	3.54±0.05	0.20		3.30±0.06	0.22
Opportunity to limit contact with other people	4.88±0.04	0.23		4.92±0.05	0.28
Opportunity for multiple users (e.g., all family members) to receive drug treatment	4.32±0.06	0.08		4.13±0.07	0.12

Note. *¹А_i+a – weighted average score, points (on a five-point scale).

*²Р_i – parametric index; Р_i=А_i• W_i. *³ composite parametric index; Р_n=∑Р_i.

Table 3: Results of the analysis of factors that maintain older adults' attitudes toward mobile apps for drug therapy in the two target segments

Factor	Target segment
	S1						S2
	R_i	C	W_i	A_i±a	P_i	P_n	R_i
Effectiveness of using the app	12	0.0110	0.132	4.58±0.07	0.60	4.3	13
Application matching the description	10		0.110	4.64±0.05	0.51		11
Convenience of use	8		0.088	4.42±0.06	0.39		9
User interface design	6		0.066	4.37±0.04	0.29		8
Technical problems with the application	9		0.099	3.89±0.05	0.39		7
Errors in the application	7		0.077	4.73±0.06	0.36		6
Reliability of information	5		0.055	4.82±0.03	0.27		5
Simple and logical navigation	11		0.121	4.04±0.06	0.44		10
Development of the application's functional purpose system	13		0.143	3.95±0.07	0.57		12
Ability to enable additional functions	3		0.033	4.21±0.05	0.14		2
Font and picture size	4		0.044	3.87±0.04	0.17		4
Availability of loyalty programs, a bonus system	2		0.022	4.25±0.07	0.09		3
Presence of advertisements in the app	1		0.011	3.74±0.06	0.04		1

Responses to the question about whether the S1 target segment survey participants were satisfied with the use of mobile apps for medication therapy are as follows: fully satisfied or rather satisfied – 42.3%, difficult to answer – 30.2%, rather dissatisfied – 21.5%, fully dissatisfied – 6.0%. Respondents in the 55- to 65-year-old age group are more satisfied with the apps than respondents in the 65- to 75-year-old age group (р=0.045) and seniors aged 75 and older (р=0.024).

To the survey question "Do you intend to use mobile apps for drug treatment in the future?", the overwhelming majority of the respondents (70.5%) answered "definitely yes" and "likely yes", 22.3% – "difficult to answer", and 7.2% – "likely no". None of the participants chose the "definitely no" option for this question.

DISCUSSION:

The market for mobile apps for drug therapy is now rapidly developing in Russia. This market includes three main groups of apps: mHealth apps, apps of individual pharmacies and chains, and medication search apps or aggregators of drugs and their prices. Mobile applications of the first group have long been present in the Russian market. These apps are used to support seniors' compliance with medication treatment and clarify information on the use, indications, and contraindications of drugs and their dosage, as well as for reminders to purchase a new pack of medication. Although this group of applications is diverse and abundant, not all mHealth applications offer a full range of features for providing drug treatment. Mobile apps in the two other groups enable seniors to search, purchase, and get deliveries of the needed medication with minimal time and resources and provide detailed information on drugs and their prices. The market for these kinds of applications is still developing. This is explained by the issuance of permission for the retail sale of over-the-counter medications in Russia in 2020 and by the passage of the Prescription Drug Retail Experiment Act in 2022. There are some requirements for pharmacy organizations for the use of mobile apps for drug therapy, as well as restrictions on the sale of drugs through apps. In particular, pharmacy chains and individual pharmacies can provide medication online only if they have a license for pharmaceutical activities and a permit from the Federal Service for Supervision of Health Care.A mandatory condition for pharmacy organizations is the availability of equipped storage facilities for formed orders, a website on the Internet, an electronic payment system, and its own delivery service that ensures the necessary temperature conditions for the delivery of thermolabile drugs. Mobile apps cannot be used to sell prescription drugs (outside of the experiment), narcotic and psychotropic medications, and alcohol-containing medications with a volume fraction of ethyl alcohol over 25%. Regarding the possibility of using mobile applications for retail sales of prescription drugs as part of the experiment (in three regions of Russia), a list of such allowed medication has been developed, which excludes drugs containing narcotic and psychotropic substances and their precursors, drugs containing strong substances, radiopharmaceutical and immunobiological drugs, and alcohol-containing drugs with a volume fraction of ethyl alcohol over 25%, as well as drugs that must be stored at temperatures below 15^оС and drugs manufactured in pharmacies. The use of mobile applications for the provision of medication does not apply to prescription drugs dispensed free or at a discount to persons who are entitled to receive medication at the expense of budgetary funds. The target segments of mobile applications in the latter two groups are still relatively small and unstable and are mainly represented by middle-aged consumers. This can explain the average distribution of actual consumers of the S1 target segment in our study between the three groups of application in the proportion of 5:2:1. However, further development of the market for drug treatment apps assumes a major expansion of the limits of apps developed by individual pharmacies and chains and drug search aggregators. In this study, for example, the number of potential consumers of the target segment S2 in the different groups of mobile applications is in a ratio of about 1:1:1. This rise in the need for apps in the last two groups also owes to the consequences of the COVID-19 pandemic^50-54, as ratings on the factor "Opportunity to limit contact with other people" in S1 and S2 reach 4.88 and 4.92 points, respectively.

A predominant barrier to the adoption of mobile applications for the provision of medication therapy among seniors, as indicated by our respondents, is the need to purchase several apps (in S1, this point is voiced by 74.5% of respondents, and in S2 – by 81.7%). For this reason, the main vector in the development of opportunities for the provision of medication treatment via applications should be merging all three groups of apps into a single one, like a mobile pharmacy app (mPharm). One of the survey participants made such a suggestion: "To create an optimal mobile system for providing drug therapy to older people, including functions for searching for, ordering, purchasing, delivering, and administering medications". In this case, the most important word is "optimal". On the one hand, it has to do with a large set of functions for searching, ordering, buying, delivering, and administering medications. The use of drugs alone encompasses a considerable amount of information on the pharmacological effects, indications, contraindications, side effects and interactions, routes of administration, and dosages. In addition, if we consider the motivational incentives for using mHealth mobile apps that are presented in this paper, they include reminders to take medications at certain times, clarification of medication dosages, warnings about double dosing, and reminders to buy a new package of medication. Consequently, combining the functions of all three groups of mobile apps for medication therapy in a single app is challenging. On the other hand, older people have certain limitations in their ability to use applications. This is due to their physiological peculiarities, technical difficulties, and psychological barriers. We argue that to develop opportunities for the provision of drug treatment and to align the desire of seniors to use mobile applications for drug treatment with their capabilities, it is necessary to develop an optimal multifunctional version of a platform-type service specifically for older people. In this, it is also critical to eliminate the barriers that currently prevent the elderly from adopting mobile apps, which are described in this paper. Some of these are poor correspondence of the set of main app functions to the initial demand, a lack of clarity and logic in the app navigation, and small font and picture sizes.The next vector in the development of opportunities for the provision of drug treatment through mobile applications, as indicated by our survey participants, can be the optimization of senior citizens' interactions with their attending physician and pharmacist (rated by S1 respondents with 3.54 points, and by S2 respondents – with 3.30 points). So far, consultations with pharmacists are not fully developed in the applications of individual pharmacies and chains, although they present a significant motivational incentive for the adoption of apps by the elderly (in S1 – for 52.0% of respondents; in S2 – for 74.5%).

Another vector for general and personal adoption of mobile apps for medication therapy among seniors is to optimize training on the use of mobile apps (indicated by 32.3% of respondents in S1 and 64.4% in S2) and improve computer literacy (needed by 21.5% of respondents in S1 and 38.2% in S2). In Moscow, this can be done for the elderly, for example, under the programs Moskovskoedolgoletie ["Moscow Longevity"] and Serebrianyiuniversitet ["Silver University"], and in Russia overall – as part of the charity project SviazPokolenii ["Linking Generations"] and on the courses Moi smartfon ["My Smartphone"], Osnovyrabotynasmartfone ["Smartphone Basics"], and Navykirabotynaplansheteismartfone ["Skills for Working with a Tablet and Smartphone"]. Furthermore, an important aspect for quickly learning how to use a drug treatment app is clear and understandable user instructions (received 3.31 points in S1 and 2.84 points in S2). Creating compact, yet content-rich and easy-to-follow instructions, and properly integrating them with the mobile app interface will help older people save time on mastering the app and also increase their loyalty owing to professional technical support when using the app (the participants' rating for the "Technical problems in the application" factor in Segment S1 is 3.89).

CONCLUSION:

1. To develop opportunities to provide drug treatment to senior citizens using mobile applications and expand and improve the market for mobile apps, the study examines the limitations and opportunities of mobile apps in terms of providing pharmaceutical care in Russia and investigates the reasons that hinder the adoption of mobile apps in this functional group by older people. A survey of 816 elderly users of mobile apps is conducted. The study identifies and explores 14 formative factors and 13 factors maintaining respondents' attitudes toward medication therapy apps in general and with a focus on differences between actual and potential consumers in particular. The key personal motivational incentives (10 parameters) and barriers (10 parameters) to the adoption of drug treatment mobile applications by the elderly are determined and researched.

2. As a result of the evaluation and calculation of integral indicators for each formative and sustaining factor, the reasons that prevented the adoption of mobile applications by older people are identified. The main impediments to the adoption of mobile apps for medication therapy among the elderly areinsufficient correspondence of the set of primary app functions to the initial demand (in the S1 segment – A_i=4.18, P_i=0.56; in the S2 segment – A_i=3.85, P_i=0.51), lack of clarity and understandability in user instructions (in S1 – A_i=3.31, P_i=0.25; in S2 – A_i=2.84, P_i=0.24), the limited possibility of communication with the attending physician and pharmacist (in S1 – A_i=3.54, P_i=0.20; in S2 – A_i=3.30, P_i=0.22), technical problems in the operation of the app (in S1 – A_i=3.89, P_i=0.39), and small font and picture size (in S1 – A_i=3.87, P_i=0.17). The special attitudes of elderly people towards different groups of mobile applications, including mHealth apps, applications of pharmacy chains and individual pharmacies, and aggregators to search for drugs and their prices, are demonstrated.

3. The results of the analysis of personal motivational incentives and barriers among seniors to purchase and use mobile apps reveal personal reasons that hinder the adoption of apps. The key personal reasons constraining the purchase and use of mobile apps for medication therapy by older persons are the need to get multiple apps for drug treatment (in S1 – 74.5% of respondents; in S2 – 81.7%), difficulties in learning to use the app (in S1 – 32.3%; in S2 – 64.4%), deterioration of vision (in S1 – 57.8%; in S2 – 62.3%), impaired attention span (in S1 – 32.8%; in S2 – 36.1%), decline in mental activity (in S1 – 30.5%; in S2 – 35.8%), decline in working memory (in S1 – 28.5%; in S2 – 32.9%), and insufficient computer literacy (in S1 – 21.5%; in S2 – 38.2%). Attention is drawn to particularly pronounced personal motivational barriers in the older age groups of 65 to 75 years and 75 years and older.

The obtained results point to the main limitations and conditions for the implementation of mobile applications from the point of providing drug treatment in Russia. The findings reveal the opportunities to improve the provision of drug treatment to the elderly through mobile applications by setting limits on applications and possibly leveling out the reasons that prevent seniors from adopting mobile applications. The principal vectors for further practical improvement of mobile applications for drug treatment for the elderly are scientifically substantiated.

CONFLICT OF INTEREST:

The authors have no conflict of interest to declare.

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Received on 17.01.2023 Modified on 08.03.2023

Research J. Pharm. and Tech 2023; 16(10):4741-4750.

DOI: 10.52711/0974-360X.2023.00770