iOS vs Android App Development: Uncovering Key Differences

Most likely you have used these digital tools at least once – Google Docs, Dropbox, and Azure. They are based on the SaaS model. Apart from this widespread one, there are other variations of cloud application services, such as PaaS and IaaS. You will find out about their differences in this article, so keep on reading it. ‍

IaaS, PaaS, and SaaS: Pillars of Cloud Services at a Glance

The highlighted models – IaaS, PaaS, and SaaS – are aimed at delivering digital tools and services to end users through the cloud on the subscription basis.

According to each aforementioned cloud model, end users don't have to pay for these services and tools one time – instead, as they are owned and supported by a specific vendor, the users are provided with entry credentials as they pay for a subscription. Only a steady web connection is needed to start using such a cloud application. At the same time, entire maintenance efforts in terms of cloud services remain on the provider's side. Even more, users are allowed to optimize their own facilities by offloading apps. Thus, they get more space while specific info is stored remotely on a secured server. 

Let's take a deep look at each of these variations:

• IaaS – stands for Infrastructure as a Service and implies access to demand compute, storage, and networking resources, according to the pay-as-you-go pricing model. In this case, we speak about the IT infrastructure used to arrange the operation of diverse tools and regular processes in the remote, end-user’s office outside the vendor’s premises. 
• SaaS – means Software as a Service and supposes that the cloud-based software vendor deploys it on its computing premises, supports it, and provides users with access to it as a ready-made web service. 
• PaaS – stands for Platform as a Service and consists of providing end users with a ready-to-use cloud platform for developing, testing, and deploying their own applications, from simple cloud services to end-to-end industrial systems.

Let's check these cloud service models in more detail.

IaaS Is about Infrastructure

When the IaaS access option is requested, users get numerous facilities –  servers, storage capacities, as well as network options, among others, –  to leverage them as if those could be available physically within their own premises. Overall, the IaaS meaning lies in ensuring steady connection between the end users and IT facilities; the latter ones are located in remote spots.

SaaS Is about Services

This is the most sought-after offer that supposes using apps that are hosted remotely. Based on individual credentials, end users obtain access to such tools to cope with regular personal or business tasks. In return, they pay a predefined price for a timeframe of leveraging SaaS (usually, this is one year or one month). Thus, SaaS meaning is to guarantee straightforward access to specific software under remote and subscription terms.

PaaS Is about a Platform 

It is a remote, cloud-hosted, platform aiming to produce, leverage, and support the operation of diverse apps. The facility holder owns all types of assets that guarantee steady operation. This is an all-in-one option comprising apps, systems, storage facilities, frameworks, functions, safety arrangements and protocols, backup copies, etc. PaaS meaning lies in forming a remote space where users can create, test, and run applications with specific functionality. For an oblivious reason, the PaaS variation is far cheaper in contrast when a user ensures all similar arrangements independently.

Public vs Private Cloud

But what about public vs private cloud – which of these options does each of the above models provide? A private option is entirely controlled by a single service provider without sharing the facilities with others. A public counterpart is offered to an unlimited number of external subjects who only intend to utilize specific offers. Most of the cloud providers are categorized as ones belonging to the second type.

But are there any intermediary options? Yes, there are hybrid cloud solutions, too, that are created and maintained on the so-called “edge” locations, i.e., thanks to both private and public facilities. 

SaaS vs PaaS vs IaaS: Distinct Features to Know

Each approach from the SaaS vs PaaS vs IaaS trio is associated with distinct peculiarities. We will look at them from the user’s perspective:

Choosing the Right Model for Your Case

When the story comes to making a choice, there are numerous pitfalls to take into account:

Bottom Line 

Leveraging software as a service is an efficient approach. It frees the assets owned by an end user and reduces one's expenses drastically. The single point is to have a clear overview of the project for which you request these external services. Therefore, you have to make a perfect match by saving this info with the comparison of sought-after models. 

If you require further assistance in selecting personalized solutions, please do not hesitate to contact us. Our team possesses a vast portfolio that includes cases of bringing multiple IT solutions of different complexity into life. Just share with us your individual preferences and requirements, and get a custom solution in return.

In recent years, mental health has taken center stage globally. Currently, approximately 792M people globally have mental issues and lack access to traditional therapy due to financial constraints or societal stigma. The best way to solve the issue — is to go digital. That is where mental health app development comes into play. It cuts costs and makes mental health available to everybody around the globe. 

As to the market, in 2024 alone, the app market saw expansion to approximately $7.38B. In a decade, forecasts promise growth up to nearly 10% annually, scorching $17.52B. 

If you are ready to build a new solution — now is the perfect time to start. Below, we will explain how to develop a mental health app, share standout mental health app ideas, and highlight key factors to keep in mind.

Why mental health apps are in demand

Even though people have faced mental disorders throughout the entire history, only in recent years solving these problems become normal and generally accepted. And it won’t stop. Let’s numbers speak louder — according to 2019 alone, the global capitalization for the global antidepressant market was estimated at $11.67B. By 2027, the market promises to grow to a record $18.29B. 

Of course, depression is not the only issue. According to the World Health Organization (WHO), there is a growing tendency for PTSD, anxiety, and OCD (due to economic instability, military conflicts, pandemics, as well as personal problems). 

Additionally, the fast-paced world daily brings panic attacks, triggers, and burnout (prevalent among doctors, teachers, and IT workers). Youngsters are prone to issues, too; among the most “popular” — are low self-esteem and social isolation.

Financial constraints and a lack of free time put hefty pressure on those who need a traditional approach to addressing mental problems. Then, an in-person visit to a psychologist or psychiatrist becomes a real luxury. But what if there is a more efficient, accessible alternative? That’s where developing your mental health app comes in.

Business and monetization models of mental health applications

For mental health app development, the following monetization models have proven to be the most profitable:

• Fee for the services of real psychologists.
  According to this model, the application acts as a platform, connecting users with professional psychologists, coaches, or therapists (similar to a marketplace with reviews, ratings, cost of services, and other attributes). In this case, the application earns the commission from each transaction (usually 15-30%).
• Subscription-based model.
  This model has a fixed fee for regular access to content and/or services for a certain period (month, year, etc.). If your app has diverse content and functions, offer multiple pricing models. This lets users pick a plan that suits their needs best.
• Freemium.
  These models give free access to basic functionality, with particular features to be paid. Usually, there are personalized recommendations, access to exclusive courses, advanced progress analytics, etc.
• One-time purchase.
  This model involves a one-time purchase of the application, after which the user has access to all its functionality.
• In-app purchases.
  Here, the basic functionality is available for free, but additional materials or services are paid (personalized plans, unique selections of tracks for meditation, etc.).
• Ad-supported model.
  In this case, app is free but includes built-in advertising (banners, videos, native advertising, etc.). At the same time, to improve the user experience, you can offer an option to turn off ads for an extra fee.
• B2B model.
  This model translates into you selling licenses to companies with internal programs to support employee mental health.
• Selling merch.
  This model focused on branded wellness merchandise promotion via scented candles, self-improvement guides, and mindfulness notebooks.

Top mental health apps on the market

Now, let's explore the most popular mental health apps. Perhaps they'll give you extra inspiration for your mental health app development project.

Headspace

Endorsed by the editors of the New York Times and 2.8 million users globally, Headspace is a product of the mental health company of the same name. Its core functionality includes meditations dedicated to improving sleep quality, relaxation, and cultivating mindfulness. They also offer courses on meditation, managing borderline emotional states, and more. Moreover, the platform has scientifically proven results in stress reduction and a user-friendly interface.

‍

Calm

The Calm app is loved for high-quality content and a simple and intuitive interface. by 4.5 million (2023). And it is rightfully so. This app spins everything, from meditation sessions and effective breathing exercises to audio programs that are good for falling asleep faster. As for monetization, there is a free version with limited access.  Full access to functionals is only available with a paid subscription.

‍

BetterHelp

BetterHelp has over 2 million users and connects with licensed therapists via text, phone, and video. Patients must pay a fee to continue their subscription and can also volunteer to donate to others. This app goes far beyond mood issues. It covers complex disorders and symptoms, such as clinical depression and PTSD. 

Talkspace

Talkspace provides online therapy with licensed therapists through a tiered subscription model (with health insurance coverage). Moreover, this app is ideal for managing medication treatment and has many formats for direct communication with psychotherapists (including cases of emergencies).

‍

Moodfit

Founded in 2018, Moodfit has become the top mood assistant for more than a million people worldwide. It has personalization options, customized mood data analysis through visualization tools, and mood-improving recommendations. In addition, the app has cognitive-behavioral therapy exercises as a handy and entertaining way to deal with mental issues. 

‍

Woebot

Woebot is a free AI-driven bot founded by Dr. Alison in 2017.  It is based on text format and has cognitive behavioral therapy methods. Initially, this software was intended for youngsters in college and graduate school, but today, people of all ages use it.

Sanvello

Sanvello, created by Dale Beermann and Chris Goettel, provides evidence-based CBT techniques and tools to support mental well-being. Since 2015, the app has offered free features and premium content through subscription or insurance.

Key components of a mental health app

Let's determine what mental health app features should be included by default.

Registration/authentication/authorization system 

The main functionality of this system includes two types of registration: full-fledged, with the user’s email, and fast, through social networks (this is implemented through the OAuth 2.0 protocol, which is suitable for integration with Google, Apple, and Facebook). 

For better protection of user data, use two-factor authentication and store hashed passwords. This can be done, for example, using bcrypt. Additionally, allow password recovery via email or SMS and register log-in/logout events for a data security audit.

User profile

Include the functionality for adding, saving, and changing personal information (name, age, mental health goals), maintaining the user’s activity history (exercise completed, courses, sessions with psychologists, etc.), and privacy settings (public/anonymous profile). Typically, profile data is stored in a relational database (PostgreSQL/MySQL); it is also necessary to set a clear separation between public and private user data.

Home screen and navigation

The home screen should feature a clickable menu, allowing users to update content based on their settings. You can also add push notifications (for example, using Firebase Cloud Messaging). As for the menu, place meditations, psychological tests, stretching, and yoga exercises in text, video, and/or audio format. You can also include real-time communication with specialists via text, voice, and video chats.

Use cloud platforms such as AWS S3 to ensure scalable content storage. If your application is media-rich — add media streaming via HLS. 

Finally, localize content for users from different regions if you plan to maximize your target audience. 

In-app payment system

If you plan to monetize your app through subscription payments or in-app purchases, integrate App Store and Google Play to process payments via the In-App Purchase API. You can deploy the web version via Stripe. Once everything is ready, provide access control based on the paid features.

Analytics and recommendations

Place functionality for tracking user progress and boosting their motivation (e.g., mood changes) and recommendations based on analytics. The latter makes sense to implement using machine learning models (e.g., based on TensorFlow).

What to consider before creating a mental health app?

The basic functionality of a mental health app goes far beyond making it popular and profitable. Therefore, to maximize your chances of success, consider the following factors before creating a mental health app.

Competitive environment

Usually, it involves the user interface, content accessibility, and the quality of the exercises/recommendations. Notably, the Calm application (sleep stories) and BetterHelp (online chat with therapists) are prime examples of such. 

Analysis of bad ratings — matters too. In particular, users usually complain about the high subscription costs, lack of personalization, navigation problems, and negative experiences with customer support service. You can use it to make a competitive feature. 

Target audience

Your target audience — above all. This can be young people (18-35 years old) who need an effective solution for stress management and improving sleep quality. Or the elderly might be searching for a more convenient professional in-home/palliative care format. Finally, it could be corporate clients who want to implement programs for the mental support of their employees. 

Ultimately, user needs may vary. Based on the insights, determine the preferred content format (e.g., meditation, CBT, DBT, video sessions) and presentation style.

Regulatory requirements and user data privacy

The most common and comprehensive regulations are GDPR and HIPAA regulations, which govern the processing of personal data and medical information. To comply with them under the mental health app development process, you must implement data encryption (via SSL/TLS) and ensure transparent privacy policies.

Marketing strategy

To attract a broad user base, create a unique selling proposition. This can be achieved through AI diagnostics, integration with wearable devices via IoT, or simply offering a lower price than competitors. Next, point out the comprehensive marketing strategy. Select the right promotion channels: social media, partnerships with therapists, or advertising through user reviews. is essential for developing a comprehensive marketing strategy. Additionally, to retain users — regularly update content. 

Testing and feedback

It’s better to subject an app with a diverse target audience to beta testing. To do so, find the first users who could be your potential consumers, gather feedback, and optimize the app based on their input.

Financial costs and ROI

Finally, estimate the project budget. It should include development, marketing, updates, customer support, and infrastructure maintenance. Given the costs, you must also estimate how long it will take till your project is profitable. It might be useful for future investors.

What are the main phases of mental health app development?

Now that you have so many insights at hand, you can start the mental health app development process. Let's find out how this happens in practice.

Ideation 

First, define the problem. It is the mental health issues that trouble your audience and their goals. Obviously, your app should cover it. The solution might vary. It could reduce stress, help with sleep, or heal depression. Moreover, in the very first stage — conduct a competitive analysis. This will help identify niche leaders, find the target audience, and formulate a USP.

Planning 

At this stage of the mental health app development process, you will already have enough information to determine the main functionality of your teletherapy application. Select a technology stack (or at least decide whether it will be a native or cross-platform solution), and clarify the business model. Based on this, you can calculate an approximate project budget.

Design 

From now on, your mental health app developers can start creating prototypes and gradually turn them into a full-fledged design. Note that to develop mental health apps, you must use WCAG 2.0 guidelines, which ensure all users can access the app's functionality. Once the mental health app design is complete, test usability with real users to refine the navigation.

‍

Development 

The mental health app development process is divided into frontend and backend. The first includes the implementation of the user part of the software, and the second – everything that happens on the server side. As individual modules are ready, your mental health app developers will need to perform unit and integration testing to prevent difficult-to-fix bugs in the future.

Testing 

Once the entire codebase is ready, QA specialists and testers will create test cases to ensure each function works correctly and the app performs well under high user load. This testing also ensures that all user actions within the app are secure and protect their privacy.

Release

Now that testing is complete, and all detected bugs are fixed, you can publish the application in the App Store and/or Google Play (your development team will first need to check whether it meets all platform requirements). After publishing, you can launch an advertising campaign to attract the first users, as well as set up tracking tools like Google Analytics and Amplitude to analyze user behavior.

Post-release support

At this mental health app development stage, you must check your application's speed and stability regularly. You will also need to update/expand its functionality once in a while and optimize what already exists based on feedback from real users. An equally important point is ensuring compatibility with newer versions of iOS/Android.

Challenges in mental health app development

Various challenges can arise during the mental health app development process. Let’s analyze them:

• Compliance with regulations.
  Mental health apps often handle and maintain personal information, including medical data, which imposes obligations on you as a developer to implement GDPR, CCPA, or HIPAA compliance.
• Balance between personalization and privacy. 

While personalization — is a key feature of these apps, it sometimes conflicts with privacy requirements. To address this, implement advanced mechanisms for anonymizing user data, which will reduce the need to send sensitive information to the server.

• Evidence base.
  The content provided by your app must be scientifically sound and effective for users. To do this, you should either accompany all your treatment plans with individual recommendations from real therapists or initially use approaches with proven effectiveness.
• User retention.
  Many users abandon apps after a few days of use, so your app may need additional retention mechanics (such as gamification and adaptive push notifications) that won’t make users feel guilty or overwhelmed.
• Monetization efficiency.
  Most users search for free or cheap health-related apps. At this point, you need to figure out the balance between user accessibility and the financial sustainability of your software.

How much do developers charge to build a mental health application?

The budget for developing a mental health app development depends on its complexity. So, we can't give exact numbers without first discussing your idea with your development team. But the approximate price ranges from:

• $140K for a teletherapy app.  
• $70K for a simple mood-tracking app with self-monitoring features.

Back-end features, like a database and admin panel, are often overlooked in cost estimates. Developers typically include these in the overall pricing for mental health applications.

If you want to get an estimate of your project, please contact us. 

Mental health app design: Best practices

Now, let's analyze several mental health apps (some of which have already been presented to you above) whose design has pleasantly surprised us. Maybe they will help you think better through your mental health app development process. 

Headspace

This app is praised for its simple and minimalistic interface, with bright illustrations and smooth animations that literally "nudge" users to meditate with its help. It is also adapted for beginners and is generally perceived as intuitive. This approach to design minimizes anxiety in users and motivates them to meditate regularly.

Calm

The aesthetics of the Calm app lie primarily in the author's images of nature, a soft color scheme, and smooth animations. Together, they create an atmosphere of relaxation  - that’s what you need to reduce stress. The app also stands out from its competitors with its "sleep stories" that help people with high anxiety fall asleep faster. 

Reflectly

Reflectly's unique design uses artificial intelligence to offer a personalized experience. A clear, user-friendly interface, dynamic prompts, and mood analytics complement this. Together, these features make the app an ideal choice for audiences of all ages.

Daylio

Daylio's intuitive interface is accompanied by simple icons for tracking the user’s mood and activity. Moreover, all these application elements are easy. Developers ensured that performing target actions doesn’t take too long. The application also has a built-in report generator with visualization elements so that users can monitor their progress.

Happify

The Happify app has a gamified interface. It simplifies and informalises the process of improving the psycho-emotional state. The gamification principles here are based on scientific methods to improve mood. So, it does not add to users' cognitive load.

Mental health app ideas to succeed in 2025

In this section, let’s look through the most viral mental health app development ideas so you can pinpoint your project to success:

• Integration of AI.
  AI assistants can help analyze moods and behavior patterns, give personalized recommendations on how to improve well-being, and remind them of any regular upcoming activities, like a daily mood rate system.
• Social interaction.
  This can be implemented via in-app groups of users with similar mental problems where they could share their healing experiences and receive mutual support.
• Integration with wearable devices.
  Through the IoT, you can analyze heart rate, assess stress levels, determine sleep quality, and create a common mental health map.
• AR and VR tools integration.
  It might be useful for relaxation (to enhance the immersion effect).
• "Instant help".
  Through the screen for quick access to ready-made materials and an online chat with a psychotherapist.
• Content specially adapted for children and adolescents.
  For example, these could be games for managing emotions or recommendations for teenagers on dealing with anxiety and stress;
• B2B solutions for companies.
  in particular, these could be psychotherapeutic assistance to prevent burnout.

Highlights of our experience in delivering healthcare solutions

Finally, we'd like to share our experience developing a mental health app. A client approached us to expand their services to the web, specifically to support small businesses recovering from the recession caused by the coronavirus pandemic. The objective was to create a platform to attract a target audience seeking health-related products and services.

For this project, we assembled a team of ten specialists. We chose Ionic and Vue.js for the frontend tech stack, with Laravel for the backend. The result was an online platform featuring a simplified login process, the ability to schedule and reschedule meetings between clients and trainers, an intuitive search for events and classes, role-based access, and an integrated payment system for online payments (covering group and individual courses, as well as event participation). We also implemented live session connections via Google Meet and Zoom. The solution was complemented by a clean, minimalist design with a calming color scheme, ensuring a pleasant and user-friendly experience.

If you want to learn more about this project, please follow this link.

Final thoughts

With this comprehensive guide, you can confidently start looking for specialists who would bring your idea to life. Don’t go any further, as you are already in the right place! Just fill out this form, and our mental health app development team will contact you as soon as possible!

Digitalization fosters the development of all sectors of the economy, making them simpler and more responsive to people's needs. If previously customers and services interacted mostly in person, spending a significant amount of time on each side, now it is possible to shorten the distance to effective solutions. AI developments make it possible to solve typical problems quickly and effectively. In fact, only complicated and non-standard issues are left for a support department.

Many users and business owners are still a bit skeptical about AI developments. In this overview, we will cover the widespread and effectual AI instruments that can strengthen engagement shortly, provided that they are arranged properly. Let's take a deeper look at how two of the most popular AI instruments function. In addition, we will also cover why the apps fit nearly any commercial enterprise. It is definitely now already – the future belongs to them as well.

What is a Chatbot?

This is a specialized software app designated with the purpose of ascertaining the intent of a person's message and picking the most relevant answer in return. Thanks to the conversational interface, chatbot analyzes any input provided by a visitor and highlights the core phrases that mark the user's intent. If you have doubts about whether this is possible to make accurately, there is a simple point here. Statistics and analytics help to shortlist the most common requests and elaborate on the responses to the point. This is the basic original approach. 

The further tech development enabled the creation of a separate AI enabled chatbot system. It is trained on extensive volumes of data and implements machine learning (ML). The latter allows these apps to “brainstorm” an extended range of non-scripted, organic replies to the requests that visitors input. This advancement is coherent with other hardware and apps that a company utilizes.

What Is Conversational AI?

A conversational AI is actually a comprehensive development that includes chatbots too. This means that it covers text and voice altogether. A conversational bot is frequently treated as an upgraded version of a classical textbot.

In addition to ML, conversational AI has implemented natural language processing (NLP). It helps the tools to figure out the viewer's intent correctly and proceed with a deep interaction, respectively. The core advantage of integrating conversational AI is the possibility to emphasize and expand maximally the essence of the message conveyed. That is a point that classical chatbots fail to deliver under any terms. If a company devotes extra resources to enhancing its AI instruments, the latter operates maximally close to human behavior.

Overall, the classification of types of conversational AI fully illustrates the highlighted points:

• AI textbots – handle a textual conversation with the visitors;
• Voice assistants – more intelligent dialog that stands on a spoken language procession;
• Virtual assistants – all-inclusive support with resolving multiple assignments, with an emphasis on textual and voice inputs jointly.

Chatbots (CB) vs Conversational AI (CAI): Brief Comparison

While exploring the nature of the said technological upgrades, it is worth noting that there are far more differences between them that do not lie on the surface.

A classical chatbot and a conversational bot pursue the common aim of optimization and, therefore, guarantee a positive effect on dealing with the website viewers. However, an AI voice bot upgrades the overall communication with the visitors since it adds a voice in addition to the textual support. Therefore, the second one guarantees extra positive outcomes, unlike typical chatbot apps.

Why Choose Conversational AI Over Traditional Chatbots

On balance, a conversational AI-based bot obviously can guarantee extra positive outcomes compared to classical tools, including:

• Better engagement in the communication with the visitors – classical textbots will fail to show the answers outside the scope of the databases of replies; CAI will proceed and succeed with addressing all the inquiries; in other words – CB is rigid while CAI possesses more flexible algorithms.
• Contextual analysis – CB will fail to do this again limiting its effort to the intent only, CAI will cover both equally well. The latter tool delivers customized replies.
• Multitasking – typically, users input several issues to solve and want to know everything at once. Under such terms, CB will recognize one intent only, typically, the first one, but it fails to do so with the rest of the issues. On the other side, CAI will analyze and reply to all the intents that a user indicated in one's message, attributed to the essence of what has been communicated. 
• Scalability – CB is not integrated with the remainder of the tools that a company uses, therefore, they may operate a bit haphazardly. On the other side, CAI is more integrated into the entire IT architecture that a company has built. In addition, it is possible to assess CAI's performance results more precisely.

There is also one scalable and impressive outcome – it is estimated that chatbot conversation apps have facilitated getting the retail sector extra $12 billion in 2023.

Which Solution Suits Your Business Best

It is not likely possible to craft a one-fits-all conversational chatbot solution since, in this case, we survey a very flexible technology. Indeed, it can be modified, highlighting the goals and tastes that a business communicates. This tool can truly address effectively all the challenges that a service provider may face while interacting with its customers. 

Overall, there are several filters to apply when building an AI solution tailored to your actual needs:

• Commercial plans – typically, AI solutions are requested when it is necessary to (i) upgrade the current level of user happiness, or (ii) enter a new level of operation. AI developers address each case individually to make the tech solutions 100% workable as owners think this fits best. 
• Nature of dealings with the visitors and clients – pre-evaluation of the client database and preceding dealings are always made before integrating tech solutions. To this end, it is worth noting that for standard requests and straightforward dialogs with visitors, textbots may suffice. Variable and compound dialogs will demand conversational AI, of course. 
• Viewer's profile – a target audience should be assessed precisely in this course. Nuanced and contextual dialog is very important for better user satisfaction. 
• Budget – it is crucial to find a balance between the funds needed and the earnings AI tech solutions promise to bring.
• Measurable outputs – textbots are rough to measure the effect of their performance on a business. Conversational AI solutions succeed in turning the statistics into gains, which are scalable, of course.

Closing Line

Almost any instrument can be both helpful and irritating. The way the work is arranged always affects the AI's performance and results. If this is done well, AI chatbots and conversational AI can work wonders and make your visitors love you.

Merely brainstorm ideas; perhaps they may even inspire the next developments within the IT sector, ensuring the next upgrade of user engagement. We are ready to ease your life if you find that a bit complicated. Our vast expertise and impressive portfolio enable us to elaborate on and bring to life even the most extraordinary solutions that perfectly align with a business's nature and purpose. Contact us, and we will offer some truly fitting ideas for your business to help it grow further.